thesis health care utilization

• Open access
• Published: 07 November 2021

Factors influencing access and utilization of health services among older people during the COVID − 19 pandemic: a scoping review

• Peivand Bastani 1   na1 ,
• Mohammadtaghi Mohammadpour 2   na1 ,
• Mahnaz Samadbeik   ORCID: orcid.org/0000-0002-4756-2364 3 ,
• Misagh Bastani 4 ,
• Giampiero Rossi-Fedele 5 &
• Madhan Balasubramanian 6  

Archives of Public Health volume  79 , Article number:  190 ( 2021 ) Cite this article

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Access to healthcare and service utilization are both considered essential factors for improving the general health and wellbeing of older people, especially at the time of COVID-19 pandemic. The aim of the study is to explore factors affecting healthcare access and health service utilization for older people during the pandemic.

PubMed, Web of Science, Scopus and Embase were systematically searched for relevant articles. Access, utilization, health, elderly and COVID-19 were used as keywords in the search strategy. A total of 4308 articles were identified through the initial database search; 50 articles were included in the review as passing the eligibility criteria. The searches were conducted up to August 2021. Data extraction was performed, and evidence was descriptively illustrated. Thematic analysis was used to explore factors influencing the elderly’s access and utilization of healthcare services, using Max QDA 10 , a qualitative analysis software.

Among articles included in the review ( n  = 50), a majority of the studies were from the United States (36%), followed by India (8%). According to the main healthcare services, a large number of articles (18%) were related to mental health services, followed by digital health services (16%). Factors were identified at an individual, provider and systems level. Seven main themes emerged from the thematic analysis, as determinants of elderly’s access and utilization of healthcare services during COVID-19 pandemic. These included: access to non-COVID related services, access to COVID-related services, literacy and education, accommodation challenges, perceived attitudes of aging, and policies and structures, and social determinants.

Mental health and digital health services were identified as major issues influencing or contributing to or influencing older people’s health during the COVID-19 pandemic. We also argue on the importance of a rounded view, as attention to a range of factors is vital for policy decisions towards sustainable care and equitable interventions for improving the health of older people.

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Sustainable access and improved utilization to healthcare services are vital towards the physical, social, and mental health and of older people [ 1 ]. Several studies have identified that psychological, physical and economic barriers can influence health care access among the older population groups [ 2 ]. In pandemic scenarios, such as COVID-19, these barriers to access and utilization of services can appear prominent. Germain and Yong (2020) suggest that some barriers can appear amplified, contributing to further inequalities to access to health services during the COVID-19 pandemic. These barriers include differences in perception to medical issues among various ethnic groups, cultural issues, gender, information barriers, legal barriers and the stigma related to the disease [ 3 ].

In general, older people encounter more barriers to access and utilization, when compared with other groups due to a number of factors ranging from their physical conditions to disabilities and mental problems. Radwan et al. (2020) have mentioned five main challenges that older people experience during COVID-19 pandemic [ 4 ]. These include: violence, misinformation, nutritional challenges, problems related to wellbeing, and limitations to routine activities [ 4 ]. According to Neumann-Podczaska et al. (2020) a large number of symptoms may occur following the onset of COVID-19 in old people. These symptoms include failure and complications associated with respiratory, gastrointestinal, cardiovascular, and neurological systems [ 5 ]. All the aforementioned, can highly worsen the condition and make it more complicated for the older people.

To date, there is growing evidence on issues of access and utilization of health services for older people during the pandemic. Due to the growing importance of the social determinants influencing older people care and costs involved in the health system [ 6 ], understanding access and utilization to necessary services during the pandemic is vital. A better understanding of these impacts can be significant for the health policymakers and the health care providers for better planning and provision of inpatient services, Intensive Care Units (ICUs) and hospitalizations and outpatient and routine care services for older people. Therefore, the present study aims to explore the factors affecting the elderly’s access and utilization to health services during the pandemic through a comprehensive investigation of available literature mainly to support health planners, providers and policymakers.

Scoping review methods were adopted for this study. Broadly, scoping reviews attempt to initially assess the scope of those available evidence to determine the nature and conceptual boundaries of the topic [ 7 ]. According to Joanna Briggs Institute’s, scoping reviews bring potential in mapping the key concepts of the research along with also making the definitions and the concepts more explicit [ 8 ]. In this review, the approach proposed by Levac, Colquhoun and ‘O’Brien (2010) [ 9 ] was applied. This approach included six main steps for conducting the scoping reviews as follows:

Clarifying and linking the purpose and research question

This scoping review was designed to answer the question that "what are the main factors affecting the access and utilization of health services among the elderly population during COVID -19 pandemic?"

Balancing feasibility with breadth and comprehensiveness of the scoping process

The main keywords were agreed by the research team considering the research question. The main keywords include utilization, access, health, elderly and COVID-19. For achieving more sensitivity, the logical operators OR /AND were used to combine the related keywords. Four main databases of PubMed, Scopus, Web of Science, and Embase were searched systematically according to the search strategy (Table 1 ). The scoping review was conducted in February and March 2021. Data was searched and updated up to 08.14.2021.

Using an iterative team approach to selecting studies and extracting data

Following the systematic search, applying the aforementioned search strategy, a total of 4308 articles were retrieved from the four databases. After refining for duplicates, 722 cases were eliminated. Title/abstract screening led us to n  = 187 articles, which were included for full-text screening. Non-English articles, including conference proceedings and books were excluded. In general, a PCC (population, concept and context) was used as eligibility criteria along with the scoping review’s research question to screen the articles and include the most relevant ones. The present PCC was defined as follows: Population: elderly population, Context: access and utilization during COVID-19 pandemic and Concept: health service access and utilization. Articles that did not meet the PCC criteria and were not in line with the aims of the study were also excluded. According to this, the exclusion criteria was those articles with no full texts in English, articles with conference proceedings designs, books and book chapters and those articles which ‘weren’t coherent with the defined PCC. Endnote X7.1, by Thomson Reuters, was used as a reference manager software. The PRISMA flowchart that illustrates the aforementioned process is presented in Fig.  1 .

The PRISMA flowchart of the scoping review

Incorporating a numerical summary and qualitative thematic analysis

The data extraction form was designed in Microsoft Excel 2013 containing the first authors` name, the year and place of study, types of healthcare services, the study aim and design, as well as the main results of the included studies ( Table A-supplement ). Data extraction was completed by two of the authors (MM and MS), and at times of disagreement, the third research member (PB) made the final decision. and the descriptive results of this step is presented in Fig.  2 . A thematic analysis approach was applied for evidence synthesis.

Identifying the implications of the study findings for policy, practice or research

In order to conduct the thematic analysis, Thomas and Harden’s approach was used [ 10 ]. This approach helped us to achieve and explore the content as the main and sub-determinants of access and utilization of health services by the elderly population during COVID-19 pandemic. To this purpose, after familiarization with the extracted data via continuous and mutual reviewing of the content, the research team tried to seek meaningful units according to the research question and created and labelled the initial codes. The process of open coding was continued and through a final reviewing and refining initial codes via merging the similar codes and omitting the duplications, the final codes were explored and labelled. Then the emergent sub-themes and the main themes were categorized into final codes. More than the themes` labels, in this step, the definitions and descriptions of the themes were considered, and the main and the sub-themes were tabulated (Table  2 ). In order to conduct the data analysis, we utilized a Qualitative Software for Data Analysis (MAX QDA) version 10.

Adopting consultation as a required component of scoping study methodology

Finally, in the last step of the scoping review, a conceptual thematic map was proposed for better illustration of the concepts and better understanding of health care policymakers and decision makers. The research team based on the explored themes and the sub-themes designed the initial draft of the thematic map that was finalized and confirmed by a mini panel of experts in the area of elderly health and public health.

The frequency of the included articles according to the place of study

A total of 4308 articles were available after a preliminary search from the four databases; 187 articles were included for full text reading, and a total of n  = 50 articles were selected for this review after confirming eligibility. The majority of published literature came from the United States ( n  = 18; 36%), followed by India ( n  = 4; 8%). Figure  2 provides an illustration of the frequency of the included articles, based on the location the study was conducted (Fig. 2 ).

A large number of studies were cross-sectional, followed by commentaries and viewpoint articles. (Fig.  3 ).

The frequency of the included articles according to types of healthcare services

According to the main healthcare services, most of the articles (9 articles; 18%) were related to mental health services, followed by Telehealth and digital health services (Fig.  4 ).

The frequency of the included articles according to the study type

The thematic analysis led to seven main themes as follows: Social determinants, access to non-COVID related services, access to COVID-related services, literacy and education, accommodation challenges, perceived attitudes of aging, and policies and structures. These main themes are the sub themes of access and utilization of healthcare services among the elderly during COVID-19 pandemic is provided in Table 2 . Further description and definition of the main themes and sub-themes are below.

Access to COVID-related services

Synthesis of findings identified that the elderly population require specialized services due to a higher probability of morbidity among the population group. The subthemes accommodated three concepts: acute COVID-19 services, the need for supplementary oxygen and ICU services. According to the data from studies contributing to this theme, there is a higher occurrence of acute respiratory distress syndrome [ 12 ] and a high risk of presenting complications from COVID-19 [ 11 ] and the particular need for ICU service [ 54 ]. are among the main aspects. Also, contextual factors and underlying conditions of older people can determine the health needs and utilization of the health services during COVID-19 pandemic.

Access to non-COVID related services

Older people require access to non-COVID related services during the pandemic. Based on the studies' data, these services are presented as nine sub-themes of access to homecare, tele health services, routine/outpatient healthcare services, oral, mental and palliative services, medications, and chronic and other primary healthcare services.

Studies have identified a higher prevalence of known risk factors for suicide [ 30 , 33 ], increased risks of mental and physical health problems [ 32 ], susceptibility to the effects of stress and major depression [ 12 , 29 ], probability of mental disorders [ 12 ] as well as preexisting or experience of loneliness [ 19 , 30 , 33 , 35 ]. In addition, among the older people during the COVID-19 pandemic, the need to improving positive coping strategies [ 33 ] and more substantial psychosocial support [ 11 ] are considered as mental health strategies.

In regard to oral health services, Leon et al. [ 24 ] have noted inequities in oral health care and dental services during COVID-19 for older patients. Palliative care as critical services for the elderly – studies have raised interdisciplinary palliative care approaches [ 23 , 39 ], accompanied by the digital provision of such care [ 23 ].

A further sub-theme is access to routine healthcare services. During COVID-19 pandemic, the number of physician consultations seems to have decreased [ 21 ] and some concerns about the maintenance of routine care of the older patients have been raised [ 21 ]. Limited access to routine health care [ 10 ] and reduced accessibility of health care for older patients [ 24 , 30 , 35 ] has potentially contributed to an increase in the number of delayed or missed medical appointments [ 30 ] and medical comorbidities [ 30 , 35 ] among the elderly.

Studies also raised the importance of medication delivery services, particularly on the establishment of medication impress systems [ 20 ]. Access to home care services is among other sub-themes in this area. Shortage of physicians for home visits and the restricted facilities for laboratory tests [ 15 ] can potentially affect the access to medical home visits [ 14 ] among the old population during COVID-19 pandemic.

Tele health services have emerged as an important service during COVID-19. Studies have pointed to developing telehealth for old patients [ 11 , 29 , 33 , 35 , 39 ] while the others have mentioned new ways to use telehealth services similar to video visits [ 18 ], digital image prescriptions [ 20 ], E-Prescribing, online health services [ 22 ], tele palliative care [ 23 ] and teledentistry [ 24 ].

Literacy and education

Literacy and education of the older people also seemed to affect their access and utilization of the health services during the COVID-19 pandemic. Creating a continuous learning environment for older people and improving their digital literacy is vital. Implementing digital literacy programs in elderly populations [ 32 ] is emphasized in the included studies. At the same time, it shouldn't be forgotten that in such a population, there is always a potential for social and digital exclusion [ 22 ]. In other words, the use of virtual social media and other digital applications by old people can be accompanied by inconvenience, stress, incapability or not being user-friendy.

More than improving the level of education, health literacy and digital literacy, another considerable sub-theme is the existence and development of misinformation [ 11 , 19 ]. It should be noticed that false information can be disseminated very fast and with the higher speed and impact of accurate health information and education.

Perceived attitudes of aging

As the process of aging occurs, the physical, mental and even social capabilities of the people are restricted. In this regard, it is essential for an old person to accept the situation and have a positive attitude. During the pandemic, this condition is intensified because of the uncertainty about the future [ 29 ]. Such a condition causes the necessity of more compliance to recommendations [ 36 ] along with a comprehensive understanding of ageism [ 48 ]. Reframing the aging initiative is among other strategies and solutions that can help increase access to health services and cope with the new condition by an old person.

Accommodation challenges

Another theme explored in this study is the challenges related to the accommodation of the old populations. This accommodation can include various types of nursing homes [ 15 , 44 , 45 ] for old people. However, this kind of accommodation can barely affect and worsen the condition of morbidity of the diseases, particularly during the COVID-19 pandemic. The elderly's nutritional challenges [ 29 ] and the issues related to their caregivers and nurses are also among the other sub-themes mentioned in this area.

Policies and structures

More than the themes above that most of them have a direction toward the old patient or their required health services or conditions, the health policies and structures of the health systems can also be effective on the access to the services. Health policy priorities, the same as the development of the Age-Friendly University (AFU) Movement [ 48 ] and engaging in policy change through investments in social protection [ 43 ], are among what was mentioned in the included evidence. Another important sub-theme in this area is the existing policies and structure to preserve the continuity of critical health services during the COVID-19 pandemic. Multidisciplinary approaches [ 18 ] can be helpful in this regard. At the same time, the policymakers should be aware of the negative impacts of decreasing the demand and supply for non-COVID-19 healthcare services [ 47 ] that can directly threaten the continuity of the services for old people.

About the other sub-theme in this area, organizational communication, the included evidence have emphasized the need to create a link with local community-based organizations [ 18 ] and attention to the local government–based support programs for community-dwelling older adults [ 44 ]. And finally, the ethical dilemma in care for the elderly during hospitalization [ 49 ] is the last issue requiring consideration to improve the access of the old population to health services during COVID-19 pandemic.

Socio-cultural

Social, cultural, economic, and physical determinants can affect access and utilization of health services on a large scale. Demographic determinants, the same as gender [ 6 , 30 , 51 ] and the old person's marital status [ 6 ], can directly affect access to the required health services. Physical determinants like the old person's physical immobility [ 6 ], his/her perception of self-health [ 32 ] and the increased risks of mental and physical health problems [ 44 ] are among the most significant related items in the included evidence. Cultural determinants, the same as cultural, social and language factors [ 18 ] are also can be effective in the access and utilization of health services among the elderly.

Social determinants include a wide range of factors, according to the included evidence. For instance, 'place of residence [ 6 , 50 ], their social group [ 6 , 51 ] and group activities [ 34 ], limited social activities [ 11 ] and social networks [ 11 ] accompanied 'with living arrangements [ 6 ] and the inequalities related to rural/urban inhabitants [ 50 ] and being homebound [ 52 ] are among the essential social determinants in the present literature. Moreover, the extensive social networks that can be accessed by the elderly was among an essential item in this regard [ 53 ].

And finally, the economic determinants are the last sub-theme in this area. The included evidence have noticed the economic levels of the old population [ 6 , 50 ], their financial resources [ 50 ] and also financial concerns [ 29 ]. The elderly's economic dependence [ 6 , 50 ] can also be noticeable as an effective factor on the access and utilization of health services.

Finally, for a better illustration of the main themes and creating a map for policymakers and health managers, a thematic map of the scoping review is presented (Fig. 5 ).

A thematic map of the scoping review

According to Fig. 5 , the mutual relationship between the access of the elderly to COVID-19 related services and non COVID-19 related is centrally mentioned that can be affected by the personal determinants the same as the elderly’s accommodation challenges and their perceived attitude of aging. At the same time, the determinant of literacy and education can have the same role at this level. It should not be forgotten that micro determinants are not the only factors that can affect the elderly’s access and utilization to health services during the pandemic, but also macro determinants. Health policies and the system’s structure, along with complex demographic, physical, social, cultural and economic factors, can also play a dominant role in this regard.

Results of the present scoping review have shown that access to non-COVID related services, access to COVID-related services, literacy and education, accommodation challenges, perceived attitudes of aging, and policies and structures can influence the access and utilization of healthcare services among older people during the COVID-19 pandemic. According to the Build Back Fairer: The COVID-19 Marmot Review, the COVID-19 condition has intensified the inequalities in health among the whole community. According to the review, the risk of mortality rate because of the disease has increased due to socio-economic and ethnic inequality among the populations. For instance, a higher rate of death has been reported among the homeless population, those living in deprived areas or overcrowded shelters, those who work closely with others, those with poorer health conditions, and the elderly population [ 55 ].

As the elderly are considered as a vulnerable group due to their physical, mental and social conditions and their economic status, the results of the present study highlight the areas that need attention, particularly during the pandemic. According to the present results from the service provider perspective, two categories of COVID-related services and the non-COVID-related ones can be important during the pandemic. According to a cohort study in Portugal, the older patients have a twice larger need for admission in the ICUs than other age groups [ 56 ].

According to the present results, access to home care services, telehealth, oral and mental healthcare, palliative healthcare, medication and routine healthcare are among the significant factors in non COVID-related services for the elderly. In this regard, other evidence shows that the COVID-19 condition can change the health care systems by reducing the need for face to face visits and the limitations in appropriate palliative services for those who suffer from cancers and their medications [ 57 ]. At the same time, as Banerjee (2020) stated, the fear and uncertainty resulting from the pandemic can cause older people to suffer more senses of loss, anxiety, fear, loneliness, or sometimes, self-neglect and indifference [ 58 ]. This can clarify the need for particular attention to access mental health services during the pandemic, especially among the elderly.

Another important sub-theme, the access to telehealthcare along with digital literacy, is considerably emphasized in the present study. The pandemic condition requires alternative facilities aiming to replace traditional care with telehealth. These changes are obvious in the areas of consulting, oral health, palliative care and so on. Nonetheless, the use of telehealth services among the elderly can raise various concerns of their lack of digital literacy, increasing misinformation and lack of confidence or the ability to use the technology. In this regard, evidence shows that some older people’s demographic characteristics, together with visual and auditory abilities, and their physical and mental capabilities, can highly affect their tendency and ability to accept and use tele health care [ 59 ]. These items and their digital literacy and education level and the need for developing the applications and devices so that both the older people and their caregivers can benefit them are among the considerable recommendations in this area.

Apart from the aforementioned micro and personal factors, other present findings have emphasized the role of health policies and the system’s structure along with a complex of demographic, physical, social, cultural and economic factors. For example, Doetsch et al. (2017) have proposed that health policies such as health reforms, allocated health budgets and the degree of communication between different levels of the health sector have a positive association with equality in access to healthcare services among the elderly [ 60 ].

Saeed et al. (2016) have also confirmed that health status, income, education, health insurance, employment and residence status are among socio-economic factors that can affect the utilization of healthcare services by the elderly [ 61 ]. Furthermore, according to Qureshi (2002), demographic factors and social and economic determinants can affect the political directions and the provision of health services for the elderly and the number of allocated resources to the older population’s health needs [ 62 ]. Hamiduzzaman et al. (2017) have also noted that some factors like overall health status, healthcare needs, social and economic factors and cultural determinants can more affect the access to healthcare services by the elderly than existing healthcare centers and facilities [ 63 ].

Limitations

The inability to access the full-text document of all the abstracts potentially fulfilling the inclusion criteria should be considered as one of the limitations of the present study. Another limitation can be the potentially restricted number of original articles or reviews in this area due to the short time from the beginning of the pandemic.

Conclusions

Results of this study have shown that healthcare provider-level factors can affect the access to health care services for the elderly during the pandemic. These determinants include access to health services both related to the diagnosis and treatment of COVID-19 and the routine services non-related to COVID-19. Furthermore, some micro factors at the personal level can influence the elderly’ utilization of health services, such as accommodation challenges, the perceived attitude of aging and the level of literacy and education of the elderly. Also, the macro determinants, which are the health policies and the system’s structure and a complex of demographic, physical, social, cultural and economic factors, are considered important in this area. Considering all these factors together can shed light for policymakers to achieve a broader view of the issue and, as a result, aim to follow a new direction to seek better and more equitable interventions and decisions for the elderly’s access and utilization of healthcare services during the COVID − 19 pandemic.

Availability of data and materials

While identifying/confidential patient data should not be published within the manuscript, the datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Intensive Care Units

Qualitative Document Analysis

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Dr Peivand Bastani and Mr Mohammadtaghi Mohammadpour have equally participated as co-first authors.

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Health Human Resources Research Center, School of Management and Medical Information Sciences, Shiraz University of Medical Sciences, Shiraz, Iran

Peivand Bastani

Social Determinants of Health Research Center, Yasuj University of Medical Sciences, Yasuj, Iran

Mohammadtaghi Mohammadpour

Social Determinants of Health Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran

Mahnaz Samadbeik

Anesthesiologist, Shiraz University of Medical Sciences, Shiraz, Iran

Misagh Bastani

Adelaide Dental School, The University of Adelaide, Adelaide, SA, 5000, Australia

Giampiero Rossi-Fedele

Research Fellow and Lecturer, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia

Madhan Balasubramanian

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BP has designed the study, finalized the search strategy and implemented the thematic analysis, MM and MB have searched and screened the articles and extracted the initial codes for data charting. MS has supervised the whole review process, JRF has contributed in revising the finalizing data analysis and MB has technically edited and finalized the article. The authors read and approved the final manuscript.

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Table A-Supplement- The characteristics of the included studies.

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Bastani, P., Mohammadpour, M., Samadbeik, M. et al. Factors influencing access and utilization of health services among older people during the COVID − 19 pandemic: a scoping review. Arch Public Health 79 , 190 (2021). https://doi.org/10.1186/s13690-021-00719-9

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Home > College of Public Health > Health Services Research & Administration > Theses & Dissertations

Theses & Dissertations: Health Services Research, Administration, and Policy

Theses/dissertations from 2023 2023.

Factors Associated with the Difficulty of Computerized Tasks Among Office-Based Physicians in the United States , Khalid Alshehri

Reducing Oral Health Disparities: Effectiveness of Preventive Dental Care on Treatment Use, Expenditures and Determinants of Service Utilization , Rashmi Lamsal

'The Very Structure of Opportunities Has Collapsed': How Taxation Policies Enhance, Decay, and Otherwise Affect the Distribution of Health & Health Services in the United States , Valerie Pacino

An Exploration of Policies, Equity, and Emerging Threats to the Traffic Safety Environment in the U.S. , Sachi Verma

Theses/Dissertations from 2022 2022

The State of Oral Health in People with Disabilities and the Impact of Family-Centered Care on the Oral Health of Children with Special Health Care Needs , Bedant Chakraborty

Theses/Dissertations from 2021 2021

The Ecology of Mental Health and the Impact of Barriers on Mental Health Service Utilization , Alisha Aggarwal

Health Service Utilization and Expenditure in Cardio-Metabolic Conditions in the United States Adults , Kavita Mosalpuria

Impact of Prescription Drug Monitoring Program on Drug Misuse and Drug-related Fatal Vehicle Crashes , Moosa Tatar

Theses/Dissertations from 2020 2020

Essays on rehospitalization under the Hospital Readmission Reduction Program , Yangyuna Yang

Theses/Dissertations from 2019 2019

Impact of Healthcare Delivery and Policies on Children's Outcomes after the Affordable Care Act of 2010 , Shreya Roy

Examining the Effects of Approaches on Reducing Hospital Utilization: The Patient-Centered Medical Home, Continuity of Care, and the Inpatient Palliative Consultation at the End-of-Life , Xiaoting Sun

Theses/Dissertations from 2018 2018

Essays on the Patient-Centered Medical Home in the United States Military Health System , Glen N. Gilson

A Multi-Level Assessment of Healthcare Facilities Readiness, Willingness, and Ability to Adopt and Sustain Telehealth Services , Jamie Larson

Healthcare Utilization for Behavioral Health Disorders: Policy Implications on Nationwide Readmissions, and Outcomes in the States of Nebraska and New York , Rajvi J. Wani

Theses/Dissertations from 2017 2017

Structural violence and gender-based violence in the United States , Sarbinaz Z. Bekmuratova

Community Benefits Spending by Private Tax-Exempt Hospitals in the U.S. , Wael ElRayes

Patient-Centered Medical Home Adoption in School-Based Health Centers , Abbey Gregg

Meaningful Use of Electronic Health Records for Population Health Management in U.S. Acute Care Hospitals , Niodita Gupta

Hospital Based Emergency Department Visits With Dental Conditions: Outcomes and Policy Implications in the States of California, Nebraska and New York , Sankeerth Rampa

Theses/Dissertations from 2016 2016

Adoption of Medication Management Technologies by U.S. Acute Care Hospitals after the HITECH Act , Aastha Chandak

The Impact of Electronic Health Records on Healthcare Service Delivery, Patient Safety, and Quality , Kate Elizabeth Trout

Essays on Immigration-Related Disparities in Health Behavior and Health Care Utilization , Yang Wang

Theses/Dissertations from 2015 2015

The Impact of Gasoline Prices on Medical Care and Costs of Motor Vehicle Injuries , He Zhu

Theses/Dissertations from 2014 2014

Provision, cost, and quality of robot-assisted radical prostatectomies in the United States , Soumitra Sudip Bhuyan

Organizational factors associated with the implementation of evidence-based public health interventions in local health department settings , Janelle J. Jacobson

Hospital cost shifting in the United States , Tao Li

Patient-centered medical home readiness in the veterans health administration: an organizational perspective , Anh T. Nguyen

Organizational and environmental correlates of electronic health records implementation and performance in acute care hospitals in the United States , Diptee Ojha

Assessing geographic variation and migration behaviors of foreign-born medical graduates in the United States , Samuel Tawiah Yaw Opoku

Theses/Dissertations from 2013 2013

Organizational and environmental correlates of strategic behavior and financial performance in the US hospice industry , Bettye Appiah Apenteng

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Digital Commons @ USF > College of Public Health > Public Health Practice > Theses and Dissertations

Public Health Theses and Dissertations

Theses/dissertations from 2023 2023.

Needs Assessment for a Web-Based Support Resource for Patients with a Pathogenic Variant in LMNA , Dylan M. Allen

Evaluation of a Story-telling Approach to Educate Minority Populations About Inherited Cancer , Celestyn B. Angot

Using the Genetic Counseling Skills Checklist to Characterize Prenatal Genetic Counseling , David A. Cline

Reframing Resistance, Resilience, and Racial Equity in Maternal Health: A Mixed Methods Exploration of Paternal Involvement and the Racial Disparity in Severe Maternal Morbidity , Marshara G. Fross

Student Perceptions of the Nonmedical Use of Prescription Stimulants and Preferences for Health Education , Ana Gutierrez

Relationships between Leading and Trailing Indicators at Construction Sites in Yanbu Industrial City, Saudi Arabia , Anas H. Halloul

Variability of Air Sampling Results Using Air-O-Cell Cassettes , Christina M. Haworth

Use of Silica Dust and Lunar Simulants for Assessing Lunar Regolith Exposure , Layzamarie Irizarry-Colon

The Aging Workforce: How it Relates to Incident Rates within a Distribution Warehouse and a Chemical Manufacturing Building , Elisabeth V. Jones

Fuzzy KC Clustering Imputation for Missing Not At Random Data , Markku A. Malmi Jr.

Piloting a Spanish-language Web-based Tool for Hereditary Cancer Genetic Testing , Gretter Manso

Development of a ddPCR Multiplex to Measure the Immune Response to Borrelia burgdorferi. , Kailey Marie McCain

A Healthcare Claims Investigation of Parasomnia Epidemiology, Associations with Attention Deficit/Hyperactivity Disorder, and REM Sleep Behavior Disorder Correlates , Anh Thy Ha Nguyen

Diet and Salivary Microbiome on Cardiovascular Risk and Glycemic Control in Participants with and without Type 1 Diabetes: The CACTI Study , Tiantian Pang

Evaluation of Two Methods to Estimate Wet Bulb Globe Temperature from Heat Index , Stephi Pofanl

Intimate Conversations: A Mixed-Methods Study of African American Father-Adolescent Sexual Risk Communication , Shanda A. Vereen

Assessment of ISO Heart Rate Method to Estimate Metabolic Rate , Karl Williams

Theses/Dissertations from 2022 2022

Outcomes of a Periodic Exposure Assessment of Workers at a University Campus , Logan M. Armagast

Evaluating the Effect of Public Health Governance Structure and Public Opinion on COVID-19 Disease Control Interventions , Daniel Chacreton

Alpha Synuclein: A therapeutic target and biomarker for Parkinson’s Disease , Max Chase

A Study of Noise Exposures for Amusement Park Employees by Positions and Ride Categories , Danielle M. Dao

Bayesian Network-based Diagnostic Support Tool with Limited Point-of-Care Ultrasound for Work-related Elbow Injuries , Cristina Maria Franceschini Sánchez

Host-Pathogen Coevolution Between Tasmanian Devils (Sarcophilus harrisii) and Devil Facial Tumor Disease , Dylan Garret Gallinson

Measurements of Generalizability and Adjustment for Bias in Clinical Trials , Yuanyuan Lu

Examining the Relationship between Racial Respect among Black Early Childhood Professionals and their Perceptions of Black Children , Kayla Nembhard

Etiology of sterile intra-amniotic inflammation: An exploratory study , Zoe M. Taylor

Evaluating and Improving a Novel Toolkit for Implementation and Optimization of Lynch Syndrome Universal Tumor Screening , Tara M. Wolfinger

Theses/Dissertations from 2021 2021

Exploring Adult Attachment in Intimate Relationships among Women who Were Exposed to Intimate Partner Violence in Childhood: A Convergent Mixed Methods Approach , Ngozichukwuka C. Agu

Comparison of the Effectiveness of Disinfectant-Impregnated Wipes Versus Detergent Wipes for Surface Decontamination , Jacob Amadin

Limited Point of Care Ultrasound Clinical Decision Support Model for Work-related Injuries of the Shoulder Utilizing Bayesian Network , Gwen Marie Ayers

Synthesis of a Multimodal Ecological Model for Scalable, High-Resolution Arboviral Risk Prediction in Florida , Sean P. Beeman

Feasibility of a Virtual Group Nutrition Intervention for Adolescents with Autism Spectrum Disorder , Acadia W. Buro

Defining Codes Based on the Consolidated Framework for Implementation Research in the Context of the Implementing Universal Lynch Syndrome Screening , Jasmine A. Burton-Akright

Americans’ Familiarity, Interest, and Actions with Direct-to-Consumer Genetic Testing , Riley L. Carroll

Does Better A1C Control Worsen Osteoarthritis? An Electronic Health Record Cross-Sectional Study , Sarah C. Cattaneo

Analysis of Post-traumatic Stress Disorder Gene Expression Profiles in a Prospective, Community-based Cohort , Jan Dahrendorff

Differential Privacy for Regression Modeling in Health: An Evaluation of Algorithms , Joseph Ficek

Does Time-Weighted Averaging for WBGT and Metabolic Rate Work for Work-Recovery Cycles? , John W. Flach

Screening of Pregnant Women with Opioid Use Disorder: Identifying Factors Impacting Implementation of Screening Recommendations Using the Theoretical Domains Framework , Tara R. Foti

Epigenetic Potential in an Introduced Passerine , Haley E. Hanson

Face Mask Use to Protect Against COVID-19; Importance of Substrate, Fit, and User Tendencies , Evelyn Kassel

Novel Educational Material for Patients with a Variant of Uncertain Significance (VUS) in a Cancer Risk Gene , Meghan E. Kelley

Mechanisms and Mitigation: Effects of Light Pollution on West Nile Virus Dynamics , Meredith E. Kernbach

Seasonality in Competence to Transmit West Nile Virus for a Widespread Reservoir , Kyle L. Koller

Mealtimes in Early Childhood Education Centers During COVID-19: A Mixed-Methods Assessment of Responsibilities, Interactions, and Best Practices , Joanna Mackie

Development and Validation of an Isothermal Amplification Assay for Eastern Equine Encephalitis Virus , Mikayla D. Maddison

Evaluating the Development and Implementation of Campus-based Sexual and Interpersonal Violence Prevention Programming , Robyn Manning-Samuels

Bait-and-Kill: Targeting a Novel Heme Biochemical Pathway in Hundreds of Cancers , Christopher G. Marinescu

Acclimatization Protocols and Their Outcomes , Ayub M. Odera

Promoting HPV vaccination with vaccine-hesitant parents using social media: a formative research mixed-method study , Silvia Sommariva

Sleep Diagnoses and Low Back Pain in U.S. Military Veterans , Kenneth A. Taylor

Theses/Dissertations from 2020 2020

Journey Mapping the Minority Student’s Path Toward Genetic Counseling: A Holistic Picture , Tatiana E. Alvarado-Wing

Using Observations from the UAW-Ford Ergonomic Assessment Tool to Predict Distal Upper Extremity Musculoskeletal Disorders , Zachariah T. Brandes-Powell

Do Similar Exposure Groups (SEG) differ from Air Force base to Air Force base? A Combat Arms Training and Maintenance (CATM) noise exposure comparison of Moody AFB and MacDill AFB. , Miriam F. Escobar

Predictors of Premature Discontinuation from Behavioral Health Services: A Mixed Methods Study Guided by the Andersen & Newman Model of Health Care Utilization , Shawna M. Green

Non-invasive Sex Determination and Genotyping of Transgenic Brugia malayi Larvae , Santiago E. Hernandez Bojorge

Does Gestational Diabetes Mellitus Increases the Risk of Preeclampsia Among Primigravid Women? , Astha Kakkad

Evaluating Effects of Cancer Genetic Counseling on Several Brief Patient Impact Measures , Alyson Kneusel

Impact of Heat-Related Illness and Natural Environments on Behavioral Health Related Emergency and Hospital Utilization in Florida , Natasha Kurji

The Quantification of Heavy Metals in Infant Formulas Offered by the Florida WIC Program , Naya Martin

Differences in Knowledge Acquisition, Perceived Engagement and Self-Efficacy in Latino Promotores Delivering the Heart Disease Prevention Program Su Corazόn, Su Vida , Samuel Matos-Bastidas

Spatial and Temporal Determinants Associated with Eastern Equine Encephalitis Virus Activity in Florida , Kristi M. Miley

Using Observations from the UAW-Ford Ergonomic Assessment Tool to Predict Low Back Musculoskeletal Disorders , Colins Nwafor

On the Importance of Context: Examining the Applicability of Infertility Insurance Mandates in the United States Using a Mixed-Methods Study Design , Nathanael B. Stanley

Exploration of Factors Associated with Perceptions of Community Safety among Youth in Hillsborough County, Florida: A Convergent Parallel Mixed-Methods Approach , Yingwei Yang

Theses/Dissertations from 2019 2019

The Ability of the U.S. Military’s WBGT-based Flag System to Recommend Safe Heat Stress Exposures , David R. Almario

The Relationship between Continuous Glucose Monitor (CGM) Derived Metrics and Indices of Glycemic Control , Ryan Bailey

“Man plans but ultimately, God decides”: A Phenomenological Investigation of the Contextual Family Planning Beliefs of Recently Resettled Congolese Refugee Women in West Central Florida. , Linda Bomboka Wilson

‘If He Hits Me, Is That Love? I Don’t Think So’: An Ethnographic Investigation of the Multi-Level Influences Shaping Indigenous Women’s Decision-Making Around Intimate Partner Violence in the Rural Peruvian Andes , Isabella Li Chan

An Assessment of the Role of Florida Pharmacists in the Administration of Inactivated Influenza Vaccine to Pregnant Women , Oluyemisi O. Falope

Epidemiological Analysis of Malaria Decrease in El Salvador from 1955 until 2017 , Tatiana I. Gardellini Guevara

Self-Collected Sampling Methods for Chlamydia and Gonorrhea Screening Among College Women: Exploring Patient-Centered Intervention Characteristics , Stacey B. Griner

The Relationship Between Hand and Wrist Musculoskeletal Disorders and Hand Activity and Posture , Warren M. Henry

Speeding Diagnosis and Saving Money Using Point of Care Ultrasound Rather Than MRI for Work-related MSK Injuries , Jared A. Jeffries

Mitigating Barriers to Chronic Disease Risk Factor Prevention and Management in Disadvantaged Communities , Krys M. Johnson

Comparing Family Sharing Behaviors in BRCA Carriers with PALB2 Carriers , Joy E. Kechik

Investigating Air Pollution and Equity Impacts of a Proposed Transportation Improvement Program for Tampa , Talha Kemal Kocak

Exploring Young Women’s Choice to Initiate Use of Long-acting Reversible Contraception: A Mixed Methods Approach , Helen Mahony

Evaluation of Clinical Practices and Needs about Variants of Uncertain Significance Results in Inherited Cardiac Arrhythmia and Inherited Cardiomyopathy Genes , Reka D. Muller

Effects of Medications with Anticholinergic Properties and Opioids on Cognitive Function and Neural Volumetric Changes in Elderly Australians , Malinee Neelamegam

Sundaas Story: A Mixed-Methods Study of Household Sanitation Provisioning in Urban Informal Housing in India , Sarita Vijay Panchang

A Retrospective Study of the Opioid Epidemic and Fentanyl Related Overdose Fatality Cases in a Florida West Coast Medical Examiner District Population , Anne Terese Powell

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• Open access
• Published: 24 August 2023

Predictors of long-term care use - informal home care recipients versus private and public facilities residents in Poland

• Małgorzata Wrotek   ORCID: orcid.org/0000-0003-1450-3509 1 &
• Małgorzata Kalbarczyk   ORCID: orcid.org/0000-0002-9431-1947 1  

BMC Geriatrics volume  23 , Article number:  512 ( 2023 ) Cite this article

741 Accesses

Metrics details

The population aging, together with the shrinking caring potential of families, is a major challenge for social policy in the coming years. The aim of the study is to identify the factors that determine not only the use of long-term care (LTC) but also the selection of individual types of such care in Poland.

Using unique data collected from inpatient LTC facilities in Poland and the Survey on Health, Ageing and Retirement in Europe (SHARE) database, we estimate logistic regressions explaining the choice of LTC solution.

Our results suggest that social inequalities play a role in choosing the type of LTC. Better educated people choose private institutions, while people without support network use more often social residential homes. The impact of multimorbidity on choosing different types of inpatient facilities is limited, thus the number of ADL limitations remains a better indicator of long term care utilization.

Conclusions

The study confirms that social inequalities influence decisions about the choice of LTC. However, multi-morbidity is a predictor of using LTC to a limited extent. The differences in LTC selection determinants between women and men are noticeable.

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Introduction

In the last 20 years, the percentage of people aged 65 and over increased in the EU-27 by 5.4 pp. reaching 24.6% in 2021 Footnote 1 . In Poland, despite the fact that this indicator was lower than the average for the EU countries – 21.4%, it grew at an even greater rate of 6.5 pp [ 1 ]. The EUROPOP-19 Footnote 2 forecasts also show that in 2060 the increase in the percentage of people aged 65 + in Poland, as compared to 2021, will be more than twice as high as the average increase for the EU-27 (12.5 pp. vs. 5.7 pp.), and in 2070 Poland will see the highest growth of this indicator among all the EU countries [ 2 ]. In turn, the percentage of people aged 80 and over living in Poland in 2021 was 4.4% [ 1 ]. And although this value was lower than the EU-27 average (6%), Poland was among the 12 countries where the fastest growth of this indicator was noted over the last 20 years. By 2030, the increase in the percentage of people aged 80 and over for Poland will be higher than the average for the EU-27 countries. In 2070, the share of this age bracket in the total population will reach 15.6%, which means that Poland will experience the highest growth (11.2 pp.) in comparison with all EU countries [ 2 ].

The aging of the population increases the demand for LTC services. According OECD [ 3 ], LTC is defined as the services provided to persons dependent on activities of daily living (ADL) [ 4 ] and instrumental activities of daily living (IADL) [ 5 ] for an extended period of time and it may be provided in nursing homes, in assisted living facilities, in the community or at home [ 6 ]. As the number of older adults dramatically increases, it becomes a challenge for public policy in both the delivery of LTC services and expenditure on LTC. Thus, the progressive aging of the population makes us reflect on the factors leading to the choice of specific forms of LTC. In our study we use Andersen’s Behavioral Model of Health Services Use (1968) [ 7 ] to investigate how particular characteristics of the older adults correlate with using different forms of inpatient and informal care.

The aim of our study is to identify factors influencing the use of LTC and the selection of specific forms of residential care in relation to informal care in Poland. According to our knowledge, this is the first study of this type, presenting a quantitative approach based on data from Poland, as well as the first study involving three different types of inpatient LTC facilities, especially still poorly researched private inpatient sector.

In post-communist countries such as Poland, there is high supply of informal care and low supply of formal care [ 8 , 9 ]. The tendency to use residential care remains low [ 10 ] and the caring functions are mainly performed by the family [ 11 ], which suggests that cultural factors shape caring patterns. However, with declining caring potential of families, there is increasing pressure to develop formal forms of LTC. LTC in Poland includes cash and in-kind benefits and is provided by the health care, social assistance and private sectors. Two levels can be distinguished [ 12 , 13 ]: formal (institutional) care provided at home or in inpatient facilities and informal care (informal caregivers, most often family members). In terms of inpatient care in Poland, as of December 31, 2020, there were 30,638 people in long term care health sector facilities Footnote 3 [ 14 ], 18,176 people in officially registered private rest homes and 75,133 people in social residential homes [ 15 ]. At the same time, the total population of Poland was 38.1 million, of which 7.1 million were aged 65+ [ 16 ].

The criteria for admission to care facilities and the way in which they work are regulated by the relevant legal acts in Poland [ 17 , 18 ]. Both residential social homes and private rest homes are intended for persons who require 24/7 care due to age, illness or disability, who are unable to function independently in daily life and for whom the necessary care cannot be provided at home. Where these people also require enhanced medical care, they are referred to nursing homes. During admission to LTC facilities, documents are required to prove the health status and income situation of the potential resident/patient. In the case of residential social homes and private rest homes, a medical certificate of the health status of the person applying for admission is required, while in the case of nursing homes, Barthel scale scores and health insurance are additional criteria. The amount of fees varies regionally. In the case of private rest homes, the cost of the stay is paid in full by the residents (and/or their family). The stay in residential social homes and nursing homes is also chargeable, but the residents pay no more than 70% of their income. In the case of residential social homes, if the resident is not able to pay the fee himself, the spouse and children are obliged to do so, and if this is not enough, the municipality then contributes to the costs. In nursing homes, the fees paid by the patients (and/or their families if they have previously agreed to contribute to the costs) cover the costs of accommodation and meals, with the remaining amount being covered by the National Health Fund [ 17 , 18 ].

In Poland, LTC remains underfunded compared to the countries of Western and Northern Europe, as the expenditures on LTC (as % of GDP) remain relatively low. In the coming years, with the progressive aging of the population, the pressure on their growth is expected to increase. Additionally, solutions used in Poland, based on universal and wealth-related systems [ 19 ], mean that access to various forms of residential care is not equal and socio-economic factors seem to play an important role in both decisions related to the choice of LTC form, and in health inequalities.

In our study, the following research hypotheses will be verified:

Social inequalities play a role in long-term care decision-making.

Multi-morbidity (number of chronic diseases) is not a good predictor of LTC use.

There are different patterns of long-term care utilization between females and males.

Theoretical and empirical issues

Andersen’s Behavioral Model of Health Services Use, although originally used to predict the use of healthcare services, is now also used extensively in research focusing on actual LTC use. The original version of the model from 1968 focused on the family as the unit of analysis [ 7 ] and listed 3 groups of factors: predisposing, enabling and need as individual and contextual determinants of the use of healthcare services [ 20 ]. However, difficulties in developing measures at the family level led to the evolution of this model towards the patient as a sole decision-making entity [ 21 ]. In the following years, extensions were introduced to the original model, taking into account e.g. variability of individual factors over time, factors related to the health care system, measures of use of health services or consumer satisfaction as well as additional variables related to the external environment, making the model a useful tool for health policy or health reforms [ 21 ].

The explanation of the importance of the main factors (in relation to healthcare for which the original model was developed) was extensively described by Andersen and Davidson [ 22 ], where: (1) the term predisposing factors at the individual level refers to demographic characteristics of age and gender, social, i.e. education, profession, ethnicity or social relations, e.g. related to family status, mental factors, i.e. health values, attitudes towards health or knowledge related to health. In terms of the contextual dimension, predisposing factors are, inter alia , demographic and social composition of the population, cultural norms, organizational and collective values, political factors; (2) the term enabling factors refers to the group of factors enabling the use of services, i.e. financial factors (e.g. income, assets, price of healthcare services) and organizational factors (e.g. having a regular source of care and its nature, waiting time for care). From the contextual perspective, enabling factors of a financial nature will therefore refer to e.g. income per capita, the relative price of goods and services, expenditure on health care, and in terms of organization to e.g. the type, structure, location, number and distribution of health facilities and personnel, education and information programs, or health policies; (3) the term need factors refers to health status, functional status and disease symptoms at the individual level, and to environmental needs or population health indicators at the contextual level.

The determinants of LTC utilization based on the original version of the Andersen’s model or its extension was widely studied [ 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ]. These models were used in the context of utilization [ 31 , 33 , 36 ] or transition [ 27 , 34 ] and both in terms of actual data [ 24 , 33 ] or intended data [ 24 , 31 ]. Some of the studies focused on applying the model to informal care [ 27 ] or home and community LTC [ 25 , 26 , 27 , 29 , 31 , 32 ], while others focused also on institutional inpatient care [ 29 , 31 ]. Many of these studies built on the original division into predisposing, enabling and need factors. However, there are also numerous other studies focused on the determinants of LTC utilization, even though they were not formally based on the Andersen’s model. In many studies, the need factors were classified in the same way, but there were differences in the classification of the predisposing and enabling factors, as the caring potential of families (e.g. number of children or family contact frequency) was mentioned most often among enabling factors.

Predisposing factors

Many studies confirm the positive relationship between age and LTC demand [ 27 , 30 , 31 , 33 , 36 , 37 , 38 ]. However, the relationship between age and the demand for LTC is not obvious, as some studies showing a positive correlation between age and institutional LTC do not include variables relating to the level of dependency. In studies of the American population over 70 years of age, variable time to death (TTD) proves to be a significant factor in increasing the use of institutional LTC. However, the availability of informal caregivers, especially spouses, significantly reduces this effect [ 39 ]. Wren et al. [ 40 ] show that the convergence between female and male life expectancy, caused by faster male life extension, significantly contributes to falling demand for both health care and LTC.

Gender remains an important factor influencing the propensity for and use of LTC, but the results are inconsistent. Some findings show a higher probability of using LTC services among females than males [ 27 , 30 ], mostly explained by their longer average life expectancy compared to males [ 41 , 42 , 43 ], as well as chronic diseases (which cause a decline in functional abilities) occurring more severely in this group [ 44 ], or a higher probability of experiencing loneliness at the end of life [ 45 ]. However, in the literature opposite results can also be found, i.e. a greater risk of institutionalization of males than females, which is most often explained by the greater difficulties with daily chores among males [ 34 ].

The relationship between the level of education and morbidity [ 46 ] and mortality [ 47 , 48 , 49 ] has been addressed in numerous studies. Among better educated people, there is a higher probability of staying in good health [ 50 ] and less interest in inpatient LTC [ 37 ]. Although there is also evidence in support of an alternative concept [ 51 , 52 ]. Better education is associated with greater knowledge about the availability and possible types of formal care [ 51 ], which leads to increased use of formal home care and reduced informal care [ 52 ], or the choice of private care and reduced public care at the same time [ 53 ] by better educated people.

Enabling factors

Taking into account the structure of households, it is indicated that the risk of using formal LTC increases when living alone [ 54 , 55 ]. Living with a spouse or daughter reduces the demand for institutional LTC to a greater extent than living with other relatives [ 56 , 57 ]. However, when medical needs increase, the fact of having a spouse does not translate so clearly into a reduced need for inpatient care [ 58 ]. A Canadian study comparing the patient profile of LTC nursing homes with retirement homes shows that people with a spouse predominate in the first type of facilities, while single people in the second type [ 58 ]. Not only having children but also close relationships (frequency of visits etc.) with children play an important role in the LTC utilization patterns. According to some findings, when community care is compared with, respectively, home and institutional care, it turns out that older people who have a closer relationship with children are more likely to stay at home, and people who had less frequent of contacts are more likely to opt for institutional care [ 26 ].

Older people with higher incomes less frequently use institutional LTC [ 54 , 55 , 59 , 60 , 61 ] because they are able to pay more for additional home care [ 62 ]. Inpatient care remains a relatively inferior option when home care is affordable [ 62 , 63 , 64 , 65 ]. However, when comparing the informal to the formal, higher income increases the odds for utilization of formal LTC care [ 27 ], but also the first time LTC services utilization risk has been found to be lower among households with higher gross income [ 30 ]. There is also evidence of fairly limited impact of the income level on LTC utilization patterns [ 26 ]. Among the wealthy older adults, especially those with real estate, the lower risk of using institutional LTC may be explained by the increased efforts of relatives to inherit their property [ 66 ].

The place of residence is also relevant. People living in rural areas have a lower risk of being beneficiaries of institutional LTC than those living in urban areas [ 31 , 67 ]. It might be explained by different patterns of care between urban-rural areas, especially when seniors living in the village receive more help from family members than inhabitants of large cities [ 68 ].

Need factors

The morbidity and dependence that accompany the progressive aging processes are mentioned as the main determinants of the demand for formal LTC. The patterns of dependence and morbidity may, however, be different in particular countries, which is explained in the hypotheses existing in the literature: expansion of morbidity [ 69 , 70 , 71 ], compression of morbidity or disability [ 72 ], dynamic equilibrium, which combines the elements of both the expansion and compression hypotheses [ 73 ], or the concept of healthy aging [ 74 ]. Environmental changes and medical progress may make living with a disease less burdensome [ 75 , 76 , 77 ], while greater care for one’s own health may contribute to a decline in disability among the older adults [ 78 ].

The presence of an additional chronic disease increases the probability of utilizing any kind of LTC services [ 30 ] or institutional LTC [ 26 ] but there is also evidence of the insignificance of this variable for the risk of either home or institutional care [ 29 ]. The coexistence of several chronic diseases (multi-morbidity), especially dementia, Parkinson’s disease, urinary incontinence, and fractures as a result of falls, shows a positive correlation with ADL limitations and the demand for institutional LTC [ 38 , 45 , 59 , 79 , 80 , 81 , 82 , 83 ]. However, some studies [ 37 ] distinguish between dependency which is measured with ADL limitations (related to the demand for residential care) and IADL limitations (which determines the use of formal home care mainly), where the first indicator (named ADL limitations or disability or dependency levels) is recognized as one of the most important predictors of LTC use [ 31 ], especially nursing facilities [ 35 ].

Data and methods

In the presented study, we combined two databases: data from LTC facilities collected by us and available data from SHARE. We decided to combine the data from both databases in order to be able to differentiate the choice of specific forms of care: residential (formal) and informal. The SHARE data for Poland did not contain information on people using residential care, therefore, in order to achieve the purpose of the study, it was necessary to provide comparable information obtained directly from long-term care facilities. As no similar study was performed in Poland and there is no data available at the individual level on long-term care residents, we decided to collect unique data. At the stage of designing the research, we took care of the comparability of variables between the two databases. First, we used data collected by us in the years 2021–2022 on residents of inpatient LTC facilities (private rest homes, residential social homes and nursing homes). We sent out a questionnaire to the managers of institutions selected randomly from official registers kept by voivodeship offices and the Ministry of Health. Each type of facility is represented in all of the 16 voivodeships in Poland, and they vary in terms of the size of the place of their location. In the self-completion questionnaire, we asked for the data concerning selected socio-demographic information regarding health and independence, as well as family networks of all the residents. As a result, a unique database was created including 745 observations from the private rest homes, 2,258 observations from the residential social homes and 872 observations from the nursing homes. Another group of data was related to the people receiving informal care at home and those who do not receive any kind of care (no LTC). The data came from the SHARE, which is a biennial panel study conducted by using probability-based sampling on people aged 50 or older and their partners across European countries, including Poland [ 84 , 85 ]. The data contains socio-demographic information about respondents as well as information on physical and mental health and functional capacity and received informal care. The presented analysis used data from wave eight, which was conducted in 2019/2020 [ 86 , 87 ] and was limited to Poland (307 observations regarding informal care at home and 1,754 observations regarding no LTC). We used the information provided in the main questionnaire. As a result, the sample size of combined data from both databases was 5,936 observations in total.

Due to the necessity to make comparisons to SHARE, we decided to limit the sample to the age of 50+. From the SHARE database, regarding informal home care, we selected those who receive personal or domestic help (or both) at home, provided by members of the household or people outside the household. Regarding no LTC, we selected people who do not receive any kind of care Footnote 4 (informal or formal). In our cross-sectional analysis we based on Andersen’s Behavioral Model [ 7 ] which allow us distinguish three group of factors classified into predisposing, enabling, and need factors. Logistic regression and multinomial logistic regression was used as an appropriate statistical model for categorical dependent variables.

We divided our econometric analysis into 3 stages. In the first stage we used logistic regression to compare the factors differentiating the people receiving some kind of LTC (informal care at home; or in private rest homes; or in social residential homes; or in nursing homes) from those who do not receive any kind of care. In the second stage, we used the multinomial logit to compare the recipients of informal care with those using in-patient care. This time, a dependent variable on four levels was used: inpatient care in private rest homes, social residential homes and in nursing homes. Informal care at home was used as the reference category for the comparison. In the third stage, the previously used multinomial logit was applied again, but this time separately among females and males.

Due to collinearity problem between the number of ADL limitations and particular ADL limitations, and also between the number of chronic diseases and particular chronic diseases, two versions of the model have been developed. In model 1, the number of ADL limitations and the number of chronic diseases were used, while in model 2 the type of ADL limitations and the type of chronic diseases were used.

In our models, we use the following three groups of factors considered at an individual level (see Table  1 ): predisposing factors (age, sex, education level), enabling factors (having a living partner, having living children, frequency of family’s members visits as a proxy for close relationships with family members or the involvement of family members in care, type of residence), need factors (functional health status – number of ADL limitations, type of ADL limitations, number of chronic diseases, type of diseases).

We are aware that among the variables it would be worth taking into account the income of the residents, or preferably the income of the family members (not only resident’s household) involved in the organization of care. As this data was not available for residents of long-term care facilities, the level of education in our study remains a proxy for the economic situation.

Differences between the two databases we used were noticeable in the case of 3 variables: frequency of visits by family members, ADL limitations, and chronic diseases. For the frequency of visits variable, we wanted to assess the degree of family involvement in care, so in the case of LTC facilities residents the proxy for this variable was the frequency of visits by family members, and in the case of informal care (SHARE database) the frequency of domestic and personal care received by family members.

In our questionnaire, we asked about the 6 ADLs using the Katz Index [ 4 ] (bathing, dressing, transferring, feeding, toileting, continence), while the SHARE questionnaire additionally listed getting into and out of bed but omitted continence. Hence, we decided to omit getting into and out of bed from the analysis and to combine toileting and continence, which took the value of 1 if any of these limitations occurred. The final number of ADL is therefore 5.

In addition, for chronic diseases, we did not use any available tool, which was dictated by the need to simplify our questionnaire as much as possible so that it could be easily completed by LTC staff. As a result of combining the databases, we did not use the original longer list of diseases, but only those that were the same or similar or that could be combined into specific, larger categories. As a result, we combined Alzheimer’s and dementia, as they occurred separately in our questionnaire and together in SHARE. In particular, it is worth mentioning how we combine the precise names of the diseases found in SHARE to the general categories we used in our questionnaire: lung disease such as chronic bronchitis or emphysema were categorized as respiratory system diseases; heart attack or myocardial infarction, coronary artery thrombosis or any other heart disease including congestive heart failure as heart diseases; other emotional disorders including fear, anxiety, nervous or psychiatric problems as other mental health problems; cataracts as vision impairment; having a hearing aid as hearing impairment. The cases of cancer might be underestimated regarding LTC facilities as we excluded hospice and palliative care facilities (in Poland hospice and palliative care is often reported separately from long-term care, however there are nursing homes dedicated to people suffering from cancer).

We did not follow any specific reporting tool as the questionnaire we designed had to be simplified as much as possible to encourage LTC staff to respond. However, regarding SHARE dataset, information about questionnaires, variable definitions and codes can be found in the SHARE Wave 8 methodology book [ 87 ]. All analyses were conducted using STATA 12.0.

Descriptive statistics

Regarding the predisposing factors, the statistics Footnote 5 of variables used in the explanatory analysis (see Table  2 ) show that females dominate in our sample for any type of LTC we studied, with the largest share of 74.42% observed in private rest homes, and the smallest in social residential homes – 54%). The informal care recipients are the youngest group of the older adults (mean of age is 74.65 years), while the oldest groups are observed in inpatient facilities (mean of age is respectively: 76.43 years in social residential homes, 79.92 years in nursing homes and 83.03 years in private rest homes). Among people staying in residential LTC facilities, those in private rest homes declare the highest level of education (53.33% – secondary education; 23% – tertiary education). In case of other types of care, the level of education is lower (the lowest number of people with secondary education is found in nursing homes – 34.32%, and with tertiary education in social residential homes – 5.12%). In terms of enabling factors, the highest proportion of people with a living partner (52.12%) and a child (92.25%) is observed among those who receive informal care at home, while for the residents of social residential homes these figures are the lowest (6.09% and 48.98% respectively). The residents of private rest homes and social residential homes are dominated by inhabitants of large cities (44.67% and 37.18% respectively), while people coming from rural areas prevail among the older adults in nursing homes and those who receive informal care (44.02% and 55.77% respectively). In terms of need factors, the highest level of dependency is observed among the residents of nursing homes (mean of number of ADL limitations is 3.66), while among informal care recipients it is at its lowest (mean of number of ADL limitations is 1.35). Regarding number of chronic diseases, the distribution is not obvious. Residents of social residential homes and informal care recipients suffer, on average, from 3.12 to 2.99 chronic diseases, while patients in nursing homes and private rest homes, respectively, from 2.28 to 1.71. Meanwhile, people who do not use any care have, on average, 1.72 chronic diseases (similar value as for private rest homes). This shows that the number of chronic diseases does not translate into the intensity of care, and that the type of disease is more important.

Given that, as mentioned earlier, the literature suggests that there is a close relationship between the level of education and health, and health inequalities caused by social factors are observed among older people in Poland [ 88 ], we decided to check our sample regarding the statistics of education level and place of living both for the presence of two or more chronic diseases (according to the full list) and limited to selected diseases Footnote 6 and the number of ADL limitations (Additional file 1 ).

The results of our analysis show that differences in the percentage of the older adults who suffer from chronic diseases between care recipients and no LTC group are smaller than in case of ADL limitations between the same two groups. The statistics presented in Additional file 1 confirm the existence of health inequalities related to social status among people using LTC, but only regarding the number of chronic diseases. Among the older adults with higher education levels, the percentage suffering from two or more chronic diseases (in both variants) is, on average, lower than among those with primary and secondary education. The number of chronic diseases decreases as the level of education increases, both among the recipients of any form of care and among the people who do not use any care. As far as the place of residence is concerned, in the group of care recipients with primary and secondary education, the percentage of the older adults who suffer from two or more chronic diseases increases along with the increase in the size of the city. On the other hand, among people with higher education, this tendency is not observed. Regarding ADL limitations, in our sample we do not observe any correlation between level of education (share of care recipients with primary education is smaller than of those with tertiary education – 65.8% vs. 66.3%) and the size of place of living.

Any kind of LTC vs. no LTC

Results of logistic regression regarding the first stage of our econometric analysis – the comparison between the older adults receiving any LTC with those who do not receive any kind of care – are presented in Table  3 .

In terms of the factors belonging to the predisposing group, we see that age is a factor that positively correlates with using any form of LTC (all age groups remain statistically significant, with the values ​​of the coefficients increasing as we move from younger to older age groups), which is consistent with other studies [ 27 , 30 , 31 ]. Being a woman negatively correlates with receiving LTC (which is surprising as LTC recipients are dominated by females due to their longer life on average). This result is in line with some studies [ 34 ], but opposite to other studies [ 27 , 30 ]. The level of education is insignificant, although it would be expected that people with higher education experience better health for longer [ 50 ] and therefore are less likely to receive LTC.

As for the enabling factors, both having a living partner and a child negatively correlates with receiving LTC and this result is in line with a previous study [ 56 , 57 ]. Most likely, this result can be explained by the fact that some people stay in LTC facilities due to loneliness [ 54 , 55 ]. Place of residence also turned out to be statistically significant, although the results remain somewhat non-obvious. Compared to rural inhabitants, the older adults living in small towns and large cities are both much more likely to use any form of LTC, while living in a medium-sized city is insignificant. These results can be explained by the uneven distribution of LTC facilities in Poland, as well as the diversity of care patterns, depending on the size of the place of living. Seniors living in villages receive more help from family members than inhabitants of large cities [ 68 ]. Perhaps, therefore, the residents of smaller locations can more often count on support from informal care, and residents of larger cities from inpatient care.

In terms of need factors, it is observed that both the increase in number of ADL limitations and the number of chronic diseases goes hand in hand with using any care, consistent with appropriately previous studies [ 30 , 31 ]. However, not all of the diseases we studied cause dependency. We can see that most of the chronic diseases remained insignificant (Parkinson’s disease, heart diseases, respiratory system diseases, vision impairment, hearing impairment), or even their impact was statistically significant but negative (hypertension, diabetes). On average, those who do not receive any care are more likely to suffer from hypertension and diabetes. The results show that diseases that make it impossible to function at home and are the main indication for care (apart from ADL limitations) are: chronic renal failure, Alzheimer or dementia diseases [ 31 , 35 ], mental health problems, cancer, group of other diseases including stroke.

Informal care vs. inpatient LTC

Table  4 presents the results of multinomial regression in case of informal care vs. inpatient LTC. In the group of predisposing factors, age turned out to be a strong predictor of using all three forms of inpatient care in relation to informal care. The influence remains statistically significant for the age group 70 + and grows for each subsequent age group. Thus, the results remained consistent with the previous research, where age was a strong predictor of institutionalization [ 30 , 31 ]. Although the inpatient LTC sector is dominated by female residents, in relation to informal care, being a female negatively correlates with using inpatient forms of care [consistent with 34; but opposite to 30], which might be explained by the fact that informal care is dominated by females even more than institutional care. Having secondary and higher education, as opposed to primary education, positively correlates with the probability of using private rest homes only. This means that people with a better social (and presumably economic) status, whenever they have a choice, prefer to use private care rather than public care [ 53 ], as expected within the first hypothesis. However, it is worth noting here that educated people have higher incomes and they usually don’t qualify to stay in public facilities. Of course, it should be taken into consideration that the preferences of older people are mainly focused on home care, although it was not possible to include formal (paid) home care in this study.

As for the enabling factors, support networks are a significant factor, which correlates negatively with using all three forms of inpatient care as compared to informal care. Having a living partner shows the strongest negative impact in the case of social residential homes, which suggests that people staying there most often experience loneliness comparing to the residents of other inpatient care. In the presented model, having children also negatively correlates with using residential care, but when it comes to choosing private nursing homes, this effect was the weakest or statistically insignificant. These results suggest that having more children correlates with using social residential homes and nursing homes, but does not affect the choice in the case of private institutions. The more frequent (at least once a week) are the visits by family members (more frequent help with personal and domestic activities at home), the lower is the choice of using inpatient care rather than informal care [ 26 ]. The involvement of family members in care is therefore one of the most important factors limiting the use of formal residential care. On the one hand, this result could suggest that people with better-developed support networks (caring patterns focused on family care) less often become residents of inpatient LTC. This effect could also be caused by a positive relationship between networks and health. It is again noted that loneliness is conductive to institutionalization [ 54 , 55 , 56 , 57 ] .

In the case of the size of the place of residence, the results are inconclusive. Inhabitants of small towns up to 20,000 people are more likely to benefit from all forms of inpatient care compared to rural residents using informal care. Most likely, this is due to the differences in the possibilities of providing care between urban and rural residents, and perhaps the greater availability of residential care facilities in larger centers. In the case of medium-sized cities between 20 and 100 thousand, positive and statistically significant influence is observed only in the social welfare sector. The fact of living in a big city with over 100,000 inhabitants compared to people living in rural areas and receiving informal care, positively correlates with using both private and social residential homes, while it is statistically insignificant for nursing homes. Perhaps these results indicate the uneven distribution of residential LTC facilities depending on the size of the city, i.e. not all have equal access to the full offer of institutional care. Nevertheless, rural residents are less likely to become residents of inpatient LTC and use informal care most often [ 31 , 67 , 68 ].

In the case of the group of factors classified as need factors, undoubtedly the level of dependence (measured by the number of ADL limitations) is the strongest positive predictor of using inpatient care (for all three types) as compared to informal care [ 31 , 35 ]. This means that people using informal care often remain more independent (and therefore do not require the involvement of informal caregivers so often). In model 2, where the impact of individual constraints was verified, the results also turn out to be inconclusive. Additional analyzes of placing particular ADL limitations individually in the model suggest that each limitation positively correlates with the use of inpatient care compared to informal care. However, when these variables are put together in the model, the correlation becomes negative in case of dressing and feeding, which may indicate that when the whole range of ADL limitations is considered, these specific activities do not require the use of inpatient care (informal caregivers are better at providing assistance in this type of activities and they are not an indication for placement in a inpatient facility). The positive impact of ADL-bathing or ADL-toileting or continence may be related to the fact that people staying in inpatient care facilities, regardless of the degree of independence in performing these activities, receive help on a routine basis.

Among the chronic diseases, only Alzheimer’s and dementia appear to positively correlate with using all three forms of inpatient care in a statistically significant way, as compared to informal care [ 35 ]. Other mental disorders positively correlate with going to social residential homes, while a chronic renal failure to nursing homes. The other diseases used in the study turned out to be either statistically insignificant or their influence on the use of inpatient LTC was negative. This means that mental disorders and diseases that seriously limit independent existence and have a direct impact on mental abilities, such as Alzheimer’s and dementia, are the most difficult types of diseases for informal caregivers (other diseases are not an indication for using institutional LTC).

The variable numbers of chronic diseases turn out to negatively correlate with the choice of each of the three analyzed types of inpatient care in relation to informal care. This means that Polish residents with a greater number of chronic diseases more often use care provided by family members or friends, as expected in the second hypothesis. In a way, this is a surprising result, as some literature [ 26 ] indicates a positive relationship between multimorbidity and the use of institutional LTC. But we can also find opposite results which show insignificance of multimorbidity on institutionalization [ 29 ]. The fact of a negative impact of multimorbidity on using inpatient care as compared to informal care may suggest the failure of the LTC system (for example problem with availability of inpatient LTC). On the other hand, as mentioned earlier, people with a lower socio-economic status (especially poorly educated) suffer from more number of chronic diseases and in a situation of limited access to public institutional care often opt for family care [ 52 ]. However, it is worth emphasizing that in our sample we have not found any relationship between the number of chronic diseases and the number of ADL limitations, which is consistent with another study [ 89 ] where showed that chronic diseases do not necessarily cause significant limitations in daily life.

Informal care vs. inpatient LTC – differences between males and females

As gender may be a factor not only differentiating patterns of care but also the occurrence of chronic diseases and ADL limitations, additional models were conducted separately for females (Table  5 ) and males (Table  6 ). The results show differences between males and females in all three factor groups: predisposing, enabling and need. This gives support to the third hypothesis.

In the group of models where informal care at home is the reference category, in terms of predisposing factors, the first significant difference between the sexes can be seen in terms of age – the threshold among females is 70 + as opposed to 90 + among males. When it comes to education, there are also differences observed. The fact of having secondary education significantly positively correlates with using private rest homes only among females. Males with the same level of education are more likely to stay in social residential homes. As for females, higher education positively correlates with using private care only. In the case of males, higher education increases using both private forms of care and nursing homes.

For the enabling factors, having a living partner negatively correlates with utilization of all three forms of inpatient care only among females, while it is insignificant in case of nursing homes among males. Significant differences are also observed with regard to having a living child. This variable negatively correlates with receiving any type of residential care among females, while among males it is significant only in the case of social residential homes. The frequency of visits/help remains a variable that negatively correlates with receiving any kind of care. Hence, having a family, matters only if the family members are in close contact with the person who needs care. Living children are more likely to provide informal care for mothers than for fathers but it might be explained by the fact that females (especially spouses) most often play the role of informal caregivers [ 90 , 91 ], hence males are more likely to receive informal care from their wives, but widowed females need to receive more support from their children. When it comes to the size of the place of residence, the greatest differences between the sexes occur in case of small towns, up to 20,000 inhabitants. Among females, living in small towns positively correlates with using inpatient care as compared to females in rural areas who are provided with informal care. Among males, this variable also positively correlates but only with private care and social residential homes and is insignificant for nursing homes. Inpatient care use patterns were similar for females and males living in large cities. This variable positively correlates with being residents of private rest homes and social residential homes but was insignificant for nursing homes.

In terms of the need factors, the direction of the impact of the variables, i.e.: number of ADL limitations (positive effect) and number of chronic diseases (negative effect) remains consistent among females and males. There are gender differences in the case of chronic diseases affecting the risk of using inpatient care compared to informal care. Heart diseases negatively correlate with using all three forms of inpatient care in the case of females compared to females receiving informal care (therefore, on average, females using informal care suffer from cardiovascular problems more often than females in inpatient care). When it comes to males, heart diseases negatively correlate with utilization of private rest homes and nursing homes. Among females, problems with the respiratory system also negatively correlates with using private care, while among males this variable remains insignificant. As for diabetes, on average, females receiving informal care at home suffer from this condition more often than females in all three types of inpatient care (the sign for this variable remains negative and statistically significant). Among males, this variable is insignificant. In the case of depression among females, this variable remains insignificant (depression is as common among females receiving informal care as among females in LTC facilities). Among males, depression negatively correlates with using inpatient care in all three analyzed types of inpatient care. This means that, on average, depression occurs more often among males staying at home than in LTC facilities (or this might be due to a different method of collecting data – data about no LTC and informal care groups came from direct interviews, and the data on residents were provided by the facilities’ staff). Alzheimer’s disease goes hand in hand with using residential care among both sexes, but the effect is statistically significant among females only for private care and social residential homes, and among males only for social residential homes and nursing homes. Regarding Alzheimer’s disease, there is therefore a gender differentiation according to the type of LTC facility. Other mental illnesses are statistically significant and positively correlate with using social residential homes only among males, while among females this variable is insignificant. There are also differences between males and females when it comes to hearing problems. Among males, it is a factor positively correlated with using private care, and among females, a factor that is insignificant or negatively correlated with using social residential homes. It therefore seems that informal care is more often provided to females despite of hearing problems, and in the case of males, hearing loss is a factor that increases the risk of institutionalization (still private rather than public).

In our study, based on the Andersen’s Behavioral Model of Health Services Use (1968) [ 7 ] we identified characteristics of people over the age of 50 that influence the probability of using different types of LTC in Poland compared to people who do not use any kind of LTC. We point out the factors that differentiate the choice between inpatient facilities as compared to informal care, and show the differences between sexes. All three hypotheses were confirmed.

We are aware that the level of income of all family members involved in providing care correlates with the choice of the form of care, however due to unavailability of this variable, we used an education level as a proxy for economic situation of older adults. The study confirms the first hypothesis that social inequalities influence decisions about the choice of LTC. Better educated people more often choose private care than people with a lower social status. Among the latter, the phenomenon of multi-morbidity (more than two chronic diseases) is more common, so social inequalities translate into inequalities in health. Therefore, it is important to both invest in education and develop the healthcare sector earlier in life. Such actions on the part of the government should mitigate the existing inequalities in health among the older adults.

However multi-morbidity is a predictor of using LTC to a limited extent. The influence of the number of chronic diseases depends on the variable used for comparisons. When we consider informal care vs. inpatient care the sign for multi-morbidity is negative, but when no LTC is used for the comparison with any kind of LTC, the sign is positive. This means that informal care beneficiaries suffer from more chronic diseases that residents of LTC facilities and no multi-morbidity itself, but particular diseases (especially Alzheimer’s, dementia and other mental diseases) should be taken into account when considering institutionalization, which confirms the second hypothesis. The number of ADL limitations is a much more relevant indicator, as it positively correlates with using LTC in each of the analyzed models.

We confirm existence of different patterns of LTC utilization between females and males with respect to all three groups of factors. Differences are observed regarding correlation between having a living partner and a child and institutionalization. Also we confirm the third hypothesis that there are differences between females and males in diseases that predisposed them to use LTC. Thus gender differences should be taken into account when planning future LTC arrangements.

Our results show that loneliness itself might be a strong predictor of social residential homes utilization. This observation is supported by two other results. Firstly, multi-morbidity is a factor with limited impact on shaping the demand for inpatient LTC. Secondly, for the older adults in social residential homes is noticed that number of ADL limitations is lower than for residents of other type of inpatient facilities. Thus, in the context of the public debate about the deinstitutionalization of the social LTC sector, our results suggest that in case of the older adults who stay in social residential homes because of their loneliness but without health reasons, there is a space to offer other type of LTC arrangements for example: housing estates for seniors. On the other hand, we also identified that Alzheimer’s disease, dementia or other mental health problems remain strong predictors of using social residential homes. For this group of the older adults it may be difficult or impossible to offer another form of care outside of institutional care. Therefore, it seems that the development of long-term psychiatric care and the promotion of behaviors that may delay the occurrence of Alzheimer’s and dementia from an early age are also the right direction to follow.

Our study has some limitations. Combining databases from two sources was a challenge for several reasons. The period of data collection, which coincided with the Covid-19 pandemic and the restrictions, may have influenced the underestimation of the ‘frequency of visits’ variable, even though in our survey we asked LTC staff to specify the visit frequency ‘usually’. In addition, the statistics presented should not be generalized to the whole population due to the impossibility of weighting the data dictated by different target populations and different way of drawing of the samples. The importance of ensuring maximum possible comparability regarding diseases and ADLs, meant that we were forced to drop some diseases or aggregate them into more general categories. Thus, the list of chronic diseases used in our analysis does not exhaust all possible types of diseases that the older adults suffer from. Therefore, there is a risk that we were not able to identify diseases other than those described, which would significantly increase the probability of institutionalization.

Also, it was not possible to include formal (paid) home care in this study, due to the lack of relevant data. Including this kind of care would allow us to extend the analysis, especially in the context of differences in care preferences depending on social status, as dependent people more often prefer to stay at their homes.

We are aware that, apart from demand factors, the decision-making selection should also take the supply factors (e.g. availability of facilities, price of stay, number of places, etc.) into account, but due to the comparability with SHARE data and objective difficulties in estimating the costs of informal care –at this stage we decided not to include the supply factors in the analysis. Probably the biggest deficit of the presented analysis is the lack of information on the economic situation of households of LTC residents, which was not available.

In addition, further analyzes should also use data from the households of dependent people, especially information on people directly involved in care (informal caregivers), as the decision-making processes related to the choice of the form of care are often collective decisions of households. The data collection methodology forced a specific selection of variables used in the model, hence the use of other methods of data collection – interviews with residents (often difficult due to the availability of people staying in inpatient facilities and / or poor health and difficulties in establishing contact) or asking questions about a hypothetical situation (the preferred form of care, if required) would certainly offer a broader perspective on the factors determining the selection of specific forms of care.

In this study, based on the Andersen’s Behavioral Model of Health Services Use, we examined the relationship between predisposing, enabling and need factors on the use of long-term care in Poland. Combining data from SHARE Wave 8 and data collected in the 2021/2022 LTC resident database, we made a comparison between older adults (aged 50+) receiving any LTC with those who do not use any kind of care. We also made a comparison between users of informal care and users of three different types (nursing homes, social residential homes and private rest homes) of inpatient LTC. The results of our study indicated that social inequalities influence LTC choice decisions. However, multimorbidity is a predictor of LTC use to a limited extent. There are also differences among men and women correlating with the use of specific forms of LTC, indicating gender-dictated variation in patterns of care. Limitations of ADLs, Alzheimer’s disease, dementia and other mental illnesses as factors that increase the risk of institutionalization in particular should be considered in projections of future LTC sector development as well as providing implications for health policy.

Availability of data and materials

The data under analysis has been obtained from the publicly available database SHARE: Survey of Health, Ageing and Retirement in Europe, http://www.share-project.org/data-access/user-registration.html . This paper uses data from SHARE Waves 8. The SHARE data collection has been funded by the European Commission, DG RTD through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812), FP7 (SHARE-PREP: GA N°211,909, SHARE-LEAP: GA N°227,822, SHARE M4: GA N°261,982, DASISH: GA N°283,646) and Horizon 2020 (SHARE-DEV3: GA N°676,536, SHARE-COHESION: GA N°870,628, SERISS: GA N°654,221, SSHOC: GA N°823,782, SHARE-COVID19: GA N°101,015,924) and by DG Employment, Social Affairs & Inclusion through VS 2015/0195, VS 2016/0135, VS 2018/0285, VS 2019/0332, and VS 2020/0313. Additional funding from the German Ministry of Education and Research, the Max Planck Society for the Advancement of Science, the U.S. National Institute on Aging (U01_AG09740-13S2, P01_AG005842, P01_AG08291, P30_AG12815, R21_AG025169, Y1-AG-4553-01, IAG_BSR06-11, OGHA_04–064, HHSN271201300071C, RAG052527A) and from various national funding sources is gratefully acknowledged (see www.share-project.org ). The datasets generated and analysed during the current study are not publicly available because there is no permission to share data from in-patient LTC facilities but data are available from the corresponding author on reasonable request with permission of in-patient LTC facilities. Statistical model syntax is available from one of the authors, Małgorzata Wrotek ([email protected]) on reasonable request.

Authors’ calculations based on data from Eurostat - Population on 1 January by age group and sex [demo_pjangroup] access: July 30, 2022.

Authors’ calculations based on data from Eurostat – EUROPOP-19 - Demographic balances and indicators by type of projection [proj_19ndbi]; Baseline projections; access: July 30, 2022.

Including nursing homes, psychiatric nursing homes and psychiatric chronic medical care homes, hospices as well as palliative care wards.

This group included the people who received help with paper work (but did not receive any personal or domestic help), as we decided that it is not a good predictor of being independent and it concerned only 25 observations (1,4% of no LTC group).

Data was unweighted due to the combination of two databases, so statistics are specified for our sample and should not to be generalized onto whole population of LTC recipients.

Group of selected diseases includes: Parkinson disease, heart diseases (inc. myocardial infarction), respiratory system diseases, chronic renal failure, Alzheimer or dementia diseases, mental health problems – other, other diseases (incl. stroke, somatic problems).

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Acknowledgements

This research was conducted as a part of research grant funded by University of Warsaw, grant number 01/IDUB/2019/94. We would like to thank Grzegorz Kula and Paweł Kaczmarczyk for their comments. We are also grateful for the insightful comments obtained from the anonymous Reviewers. Special acknowledgments to managers and other staff of LTC facilities for their involvement in the preparation and sharing of the data.

This work was supported by University of Warsaw, grant number 01/IDUB/2019/94. The founding source has no involvement in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.

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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Małgorzata Wrotek and Małgorzata Kalbarczyk. The first draft of the manuscript was written by Małgorzata Wrotek and Małgorzata Kalbarczyk commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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The study uses data from publicly available SHARE survey database and unique data collected from in-patient LTC facilities in Poland. The SHARE study is subject to continuous ethics review. During Waves 1 to 4, SHARE was reviewed and approved by the Ethics Committee of the University of Mannheim. Wave 4 and the continuation of the project were reviewed and approved by the Ethics Council of the Max Planck Society. In addition, the country implementations of SHARE were reviewed and approved by the respective ethics committees or institutional review boards whenever this was required. The numerous reviews covered all aspects of the SHARE study, including sub-projects and confirmed the project to be compliant with the relevant legal norms and that the project and its procedures agree with international ethical standards. Opinion of the Ethics Council of the Max Planck Society on the “SHARE” Project: http://www.share-project.org/fileadmin/pdf.documentation/SHARE_ethics_approvals.pdf

Data collection from in-patient LTC facilities in Poland was reviewed and approved by the Ethics Committee of University of Warsaw Faculty of Economic Sciences (reference no. 4/2021). The need for Informed consent was waived by the Ethics Committee of University of Warsaw. All methods were carried out in accordance with the relevant guidelines and regulations.

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Additional file 1: table a1..

Statistics for education level and place of living vs. chronic diseases and ADL limitations

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Wrotek, M., Kalbarczyk, M. Predictors of long-term care use - informal home care recipients versus private and public facilities residents in Poland. BMC Geriatr 23 , 512 (2023). https://doi.org/10.1186/s12877-023-04216-2

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Impact of Community Health Workers on Use of Healthcare Services in the United States: A Systematic Review

Helen e. jack.

1 Center for Primary Care, Harvard Medical School, Boston, MA USA

2 Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, UK

Sophia D. Arabadjis

3 Harvard T.H. Chan School of Public Health, Boston, MA USA

Erin E. Sullivan

Russell s. phillips, associated data.

As the US transitions to value-based healthcare, physicians and payers are incentivized to change healthcare delivery to improve quality of care while controlling costs. By assisting with the management of common chronic conditions, community health workers (CHWs) may improve healthcare quality, but physicians and payers who are making choices about care delivery also need to understand their effects on healthcare spending.

We searched PubMed, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, PsycINFO, Embase, and Web of Science from the inception of each database to 22 June 2015. We included US-based studies that evaluated a CHW intervention for patients with at least one chronic health condition and reported cost or healthcare utilization outcomes. We evaluated studies using tools specific to study design.

Our search yielded 2,941 studies after removing duplicates. Thirty-four met inclusion and methodological criteria. Sixteen studies (47%) were randomized controlled trials (RCTs). RCTs typically had less positive outcomes than other study designs. Of the 16 RCTs, 12 reported utilization outcomes, of which 5 showed a significant reduction in one or more of ED visits, hospitalizations and/or urgent care visits. Significant reductions reported in ED visits ranged from 23%–51% and in hospitalizations ranged from 21%–50%, and the one significant reduction in urgent care visits was recorded at 60% (p < 0.05 for all).

Our results suggest that CHW interventions have variable effects, but some may reduce costs and preventable utilization. These findings suggest that it is possible to achieve reductions in care utilization and cost savings by integrating CHWs into chronic care management. However, variations in cost and utilization outcomes suggest that CHWs alone do not make an intervention successful. The paucity of rigorous studies and heterogeneity of study designs limited conclusions about factors associated with reduced utilization.

Electronic supplementary material

The online version of this article (doi:10.1007/s11606-016-3922-9) contains supplementary material, which is available to authorized users.

INTRODUCTION

Global and capitated payment models are changing healthcare delivery. These payment models set up incentives for practices to reduce use of costly services, while maintaining or improving health outcomes. Relative to a fee-for-service model, global payments give hospitals and primary care practices more flexibility to fund new ways of delivering care. Consequently, physicians and practice managers need to understand the evidence base on the value of care models.

Community health workers (CHWs), who have minimal formal training in healthcare and are hired primarily for their connection to a community, 1 have long been employed by primary care practices. Typically grant funded and not reimbursed through fee for service, they focus on health education, prevention, or chronic disease management for vulnerable and minority populations. 1 – 3 As value-based payment models expand, providers will have more flexibility to fund CHWs with global budgets, or payers may elect to reimburse for CHW services. 4 – 6

The emerging evidence base on CHW programs 7 for the prevention and management of chronic diseases includes systematic reviews concluding that CHW interventions can improve overall health outcomes 8 and outcomes for patients with heart disease, stroke, 9 type II diabetes, 10 – 12 HIV, 13 and asthma 2 , 14 and for vulnerable patients with or at risk for a variety of chronic diseases or cancer. 15 Other systematic reviews have also documented the costs and cost-effectiveness of CHW programs, 15 but none, outside of low and middle-income countries, 16 have examined the impact of CHWs on the utilization of health services by patients with chronic conditions. Because of their focus on prevention and disease management, CHWs have the potential to reduce use of certain preventable, costly healthcare services, such as emergency department (ED) or urgent care visits. In deciding whether to incorporate CHWs into a primary care practice, physicians and payers would benefit from an understanding of how CHWs impact spending and the populations in which CHWs may bring about the greatest savings.

In this context, we conducted a systematic review of studies that have a cost or healthcare utilization outcome, evaluate CHW interventions for chronic disease management, and are relevant to primary care. We can understand the effects of CHWs either directly, by measuring costs, or indirectly, by measuring how CHWs change potentially preventable utilization, an outcome that affects payers and practices using global or bundled payment models, but also affects healthcare efficiency and quality. Ours is the first systematic review to focus solely on the financial impacts of CHWs for chronic care management in the US. We limited our search to chronic care management because it is an area in which CHWs have potential to reduce spending, as patients with chronic conditions are among the most expensive and have the most preventable healthcare use. 17 , 18 These findings may inform physicians and payers and will help prioritize gaps for future research to address.

This systematic review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. 19 Protocol information can be accessed on the PROSPERO International register of systematic reviews online.

Search Strategy

We searched PubMed (1809–22 June 2015), Cochrane Database of Systematic Reviews (2000–22 June 2015), Cochrane Central Register of Controlled Trials (1992–22 June 2015), PsycINFO (1872–22 June 2015), Embase (1947–22 June 2015), and Web of Science (1900–22 June 2015). Our search strategy identified articles containing one or more terms related to the following three ideas: (1) CHWs, (2) cost or healthcare utilization related to chronic care management, and (3) a United States setting (see Appendix  1 , available online, for complete search strategy). We searched both free text and controlled vocabulary words and translated search terms into syntax appropriate for each database.

In order to capture the breadth of CHW job titles, we drew search terms from: (1) previous systematic reviews on CHWs, 8 , 20 – 22 (2) specific job titles used for CHWs in Massachusetts, based on a survey of CHW programs conducted by the Massachusetts Department of Public Health, 23 , 24 and (3) additional terms on health coaching and doulas, some of which were added after consulting with staff at the Massachusetts Department of Public Health’s Office of CHWs. Massachusetts is one of two states 25 with an office of CHWs and has a range of CHW programs, making the list of job titles broad.

Eligibility Criteria

We included peer-reviewed, primary research studies published in English that met the PICOS criteria displayed in Table  1 .

*We included adherence to medication as an outcome because medications contribute to healthcare costs, both in the short term (potential increase) and long term (potential decrease). For example, asthma, a condition that CHWs commonly treat, have medications that are used only or more often if the disease is poorly controlled (rescue inhalers), making medication a form of preventable utilization

Study Selection

Two researchers (SA, HJ) independently screened the titles, abstracts, and full texts of all studies, reconciling any differences through discussion and excluding studies that did not meet eligibility criteria. A third reviewer (ES) acted as a tiebreaker for any inclusion/exclusion disagreements. Following the full text screen, we screened the bibliographies of the included studies and articles that cited the studies. Any relevant titles were screened by abstract then by full text, as in the original screening process. Selected studies were incorporated into the final list of included studies. A primary care provider (RP) reviewed the list of included studies and excluded any studies not relevant to a primary care setting.

Studies were also assessed for methodological rigor. A team of two researchers (SA, LS) reviewed and evaluated studies by design type using the following scales: Jadad Scale for RCTs, 26 Quality Assessment Tool for Quantitative Studies for pre-post (single arm) studies, 27 Newcastle-Ottawa Scale for non-randomized matched cohort design, 28 and Consensus on Health Economic Criteria for the cost-effectiveness studies. 29 (Details on study exclusion at this step are presented in Appendix  2 , available online.) Studies were not compared across scales, as there was no way to standardize ratings. Instead, we provide each study’s design (Table  2 ), outcomes (Table  3 ), and risk of bias (Appendix  2 ) to facilitate interpretation of results.

Description of Included Studies

*We reported funding sources as one or more of seven types: private foundation, insurance provider, state or federal, healthcare provider, academic institution, local government, or other non-profit organization

†Intensity: number of visits, average length of visits (min), intervention length months, all group visits = 3, mixed group/one on one = 2, only one on one = 1, NS = Not stated

‡To describe the CHW role, we categorized CHW roles into eight groups: connecting patients with social service, care coordination, connecting patients to health services, health coaching, home visiting, environmental modification, advocacy, and health education. We assigned one or more of these labels to each study to capture all of the activities that the CHWs performed

§Community health workers were explicitly reported as bilingual

Cost and Utilization Outcomes

*Indicates significance between groups (control-intervention)

†Indicates significance within groups (pre-post single sample)

‡This cost-effectiveness study also included some outcome results reported relative to a randomized control and is considered an RCT in discussions of those outcomes

Data Collection and Synthesis

We extracted data based on a codebook developed by members of the research team (SA, HJ). The codebook included definitions for each indicator and sample extractions. Indicators selected are displayed in the top row of Tables  2 and ​ and3 3 and adhered to the PICOS criteria: patient (participant characteristics), intervention, comparison (study design and comparison group if present), outcome, and setting. Two researchers (HJ, SA) piloted the codebook on a small sample of studies and compared data extracted for consistency. The codebook was revised based on inconsistencies. Based on preliminary analysis of the data, we classified CHW activities into eight categories (Table  2 ) and described each intervention using one or more activity labels. As we extracted cost or outcome data, we maintained the units and format of data as the initial study presented it. We considered a p-value of less than 0.05 statistically significant. Because of variation in intervention and outcome reporting, we were not able to conduct a meta-analysis of study findings and thus had no specific summary measures. We compared the characteristics (displayed in Table  3 ) of RCTs with significant or non-significant results for the most costly utilization indicators (hospitalizations, urgent care visits, and ED visits) to look for trends and develop hypotheses about which features contribute to positive outcomes. We focused on RCTs in these comparisons because of their increased methodological rigor and decreased susceptibility to publication bias. 31 , 32 To examine trends in CHW intervention efficacy by population, we examined outcomes of studies addressing certain key conditions (asthma, diabetes) and targeting low-income populations.

To facilitate comparison between studies, we grouped the studies by outcome for our analysis and compared studies only within each outcome. We indicate only the direction of change and its statistical significance (significant, not significant, not calculated). Studies were considered statistically significant if they had p < 0.05. Detailed information about the outcomes of each study is displayed in Table  3 .

In this review, we aim to test the hypotheses that:

• CHWs reduce healthcare costs and utilization.
• Interventions that have CHWs integrated into the care team will have more positive results than those that do not integrate CHWs.

Our search yielded 2,941 results after duplicates were removed, 43 of which satisfied inclusion criteria (Fig.  1 ). We excluded nine studies based on the methodological review, leaving 34 studies in the final review (Appendix  2 , available online). Reviewers were consistent in 91% of inclusion/exclusion decisions in both abstract and full text screens.

Flowchart of inclusion and exclusion of studies

Sixteen studies (47%) were randomized control trials (RCTs), eight were pre-post studies (24%), six were cohort studies (18%), and four were cost-effectiveness analyses (12%). Interventions generally targeted either children (n = 13; 38%) or adults (n = 18; 53%), with only three (9%) including both. Most studies included only patients with a specific chronic condition, including asthma (n = 14; 41%), diabetes (n = 6; 18%), hypertension (n = 1; 3%), stroke (n = 1; 3%), or HIV (n = 1; 3%). Some studies had prior preventable healthcare use, such as recent ED visits for asthma, as an inclusion criteria (n = 14; 41%) or included only low-income, Medicaid, or uninsured patients or recruited patients from low-income areas (n = 14; 41%).

Interventions varied in intensity, lasting from two weeks to two years, and consisted of individual visits (n = 28; 82%), group visits (n = 3; 9%), or a combination of the two (n = 1; 3%) (two studies did not specify visit type.) Seven studies (21%) described specific ways in which CHWs were integrated into the care team. Information about the study setting, intervention, and patient population are shown in Table  2 .

Emergency Department Visits

Nineteen studies (56%) measured change in ED visits during or after the CHW intervention. Of those, eight were RCTs, and three showed a significant decrease in ED visits during or after the intervention, relative to a randomized control. 33 – 35 Five showed no significant difference in ED visits. 36 – 40

Of the eight pre-post studies, five showed a significant decrease in ED visits relative to a baseline measurement, 41 – 45 and one had no significant decrease. 46 Two pre-post studies did not indicate statistical significance; of these, one intervention resulted in a decrease in ED visits 47 and one in an increase in ED visits. 48 There were three cohort studies that examined ED use, two of which showed significant decreases in ED use in the intervention group. 49 , 50

Hospitalizations

Seventeen studies (50%) assessed the effect of the CHW intervention on hospitalizations, primarily during the CHW intervention. Of the seven RCTs, six showed no significant decrease in hospitalizations relative to a control or a randomized observation group. 34 , 35 , 37 , 39 , 40 , 51 One showed a significant decrease relative to the control. 36 Of the seven pre-post studies that assessed hospitalization, all showed a decrease in hospitalizations, 41 , 43 – 48 but only five indicated statistical significance. 41 , 43 – 46 Three cohort studies assessed the effect of the intervention on hospitalizations. One showed a decrease in costs without significance given 52 ; two indicated a significant decrease relative to an observation cohort. 5 , 49

Urgent Care Visits

Seven studies (21%) measured the effect of the CHW intervention on use of urgent care or other unscheduled outpatient medical services. Two of four RCTs demonstrated a significant decrease relative to control, 40 , 53 and two showed no significant decrease relative to control. 54 , 55 Of the four pre-post studies measuring this outcome, three demonstrated a statistically significant decrease, 41 , 44 , 45 and one showed a non-significant increase. 46

Medication Use

Fifteen studies (47%) measured medication use, assessing adherence (six studies), preventable use (six studies), or both (three studies). Of those assessing adherence, three RCTs found no significant change relative to a control. 33 , 56 , 57 Of four pre-post studies, three found an increase relative to baseline, 43 , 44 , 47 and one cohort study noted increased adherence relative to an observation cohort. 58 Of the four RCTs measuring preventable use, three found a statistically significant decrease relative to a control. 40 , 54 , 59 Three pre-post studies found a decrease in preventable use relative to baseline. 43 , 45 , 46 One cohort study found no change in emergency medication use, 49 while another (the only study that measured medication costs) noted a significant decrease in non-narcotic prescription costs for the control cohort relative to the CHW group. 5

Scheduled Outpatient Visits

Eight studies (24%) assessed aspects of healthcare utilization other than ED visits, hospitalizations, urgent care, or medication use. Of those, all measured scheduled outpatient visits, such as scheduled primary care provider appointments or maintenance appointments for a chronic condition. Three of six RCTs showed a significant increase in visits relative to a control, 39 , 51 , 60 while three had no significant change. 38 , 40 , 61 One pre-post study found no significant change in clinic visits, 41 and a single cohort study saw a significant increase in ambulatory care. 62

Cost reporting

The 17 studies (50%) that reported either program costs, overall costs (including savings from changes in utilization), or both are summarized in Table  4 . In the 14 studies that reported on program costs, the cost per patient or family per year ranged from $200 to $1472, but studies were not consistent in which operational costs they included in these totals, which does not enable direct comparison.

Studies that Examined Change in Overall Cost

*Indicates that some program costs, such as salary or benefits, were taken into account in cost reporting

†Indicates that study did not assess significance of reported cost-savings

‡Indicates significance at P  < 0.05 level

Eleven studies tracked changes in overall costs, including both the intervention costs and savings from reduced utilization. Seven studies included both the cost of the intervention and overall healthcare cost-related outcomes, and four studies reported cost-related outcomes without directly reporting operational costs. Eight studies found the CHW interventions decreased costs, while three suggested that the CHW interventions yielded no savings. 5 , 40 , 58

Two studies, both of which focused on care for adults with type II diabetes in Texas, assessed the cost-effectiveness of a CHW intervention. One found that each additional quality-adjusted life year (QALY) gained as a result of the CHW intervention cost $10,995 to $33,319. 63 The other found that each additional QALY cost $13,810. 64 The typical benchmark for the cost-effectiveness of an intervention is $50,000 or less per QALY. 65

Features of Interventions with Positive Utilization Outcomes

Fourteen studies (41%) demonstrated a statistically significant decrease in ED visits, hospitalizations, or urgent care visits among patients who received a CHW intervention, relative to a randomized control, baseline measure, or observational cohort. An additional three studies reported positive results for these outcome measures, but did not calculate statistical significance. To assess whether interventions with reductions in ED utilization, hospitalizations, and/or urgent care were associated with distinct patient traits, we examined these outcomes across common populations. Of 13 studies focused on pediatric asthma populations, significant reductions were achieved in hospitalization, ED visits, or urgent care visits in 9 of the 10 studies that reported these outcomes. Six studies focused on diabetic populations, where two of three studies achieved key outcome reductions. Fourteen studies focused on low socioeconomic status or public insurance populations, and significant reductions across key outcomes were reported in seven of nine studies. A more detailed examination of utilization indicators by these populations is presented in Appendix  3 , available online.

There was a trend for non-randomized studies to have more positive outcomes than RCTs. For both ED visits and hospitalizations, the frequency of positive RCTs was much less than in pre-post studies (ED visits: 3/8 RCTs positive, 5/8 pre-post positive; hospitalizations: 1/6 RCTs positive, 7/7 pre-post positive; urgent care visits: 2/4 RCTs positive, 4/4 pre-post positive). In light of this skew and the increased rigor of RCTs, we examined RCTs to compare the features of interventions that demonstrated a statistically significant decrease in healthcare utilization with those that did not. Of the 17 RCTs, 5 (29%) had statistically significant positive results in at least one of these areas. Seven (41%) showed no significant change in these outcomes. The other RCTs (five studies; 29%) did not measure ED visits, hospitalizations, or urgent care visits. Features and results of positive and negative RCTs are presented in Table  5 .

Characteristics and Results of Interventions Evaluated with an RCT

*Significant difference in ED visits, urgent care visits, or hospitalizations

†Based on insurance status, income status, or residence in low-income area

‡The Jadad Scale provides a quality rating out of 5 for RCTs; a score of 5 indicates greatest rigor

Our results provide evidence that CHW-based interventions have the potential to reduce costs and preventable healthcare utilization. We have shown that many, but not all, CHW interventions reduce healthcare utilization (Hypothesis One) and that interventions with CHWs integrated into the care team trend toward better outcomes (Hypothesis Two). Because of the variability in interventions, outcomes, and study quality, our findings do not allow us to draw firm conclusions about the effects of CHW interventions on costs or healthcare utilization.

Of the studies that reported overall costs, the majority found that the CHW interventions were cost saving, and all studies that measured the per-patient annual cost indicated that interventions are low cost, less than $1500 per patient per year. Additionally, while RCTs showed variation in intervention effects, 42% of the RCTs that measured ED visits, hospitalizations, or urgent care visits found that the CHW intervention resulted in a statistically significant decrease in the use of at least one of those services relative to a control. Further, our results suggest that CHWs may be better suited to address the needs of patients who are at high risk of preventable health emergencies, rather than those with more advanced disease, who may require intensive inpatient care: only one RCT found that the CHW-based intervention reduced hospitalizations (1/7), while a much greater fraction of RCTs found that CHW-based interventions could reduce ED or urgent care visits (3/8 and 2/4, respectively).

Prior reviews, many of which concentrate on CHW-based interventions for a specific population, found that some, but not all, CHW-based interventions are cost saving or reduce preventable utilization, 2 , 8 , 12 , 15 , 21 findings that correspond with our results. Our review builds on prior reviews that have examined the effects of CHW programs across diagnoses by showing that CHWs can reduce potentially preventable healthcare use for patients with chronic conditions, while prior studies have shown that they can increase appropriate healthcare use (routine or screening visits) for patients who do not yet have a severe, chronic disease. 8 , 15 Together, these findings can help payers choose which types of CHW interventions to fund.

Our review shows that costs or utilization was assessed in CHW-based interventions used to meet the needs of patients with five different chronic diseases or a combination of chronic conditions. There was, however, a focus on interventions for patients with asthma. While asthma accounts for a relatively larger number of preventable ED and hospital visits than many chronic conditions, 18 , 66 there is a need to explore the role that CHWs can play in improving outcomes and reducing costs for other conditions. For example, none of the studies in this review focused on behavioral health, although CHWs have been involved in mental health and substance use disorder care, 67 and behavioral health is often high cost for payers and hospitals. 68

The variation in the cost and utilization outcomes suggests that CHWs alone do not make an intervention successful. Like other healthcare workers, CHWs can be deployed in different ways. By examining characteristics of the positive and negative RCTs, we can develop hypotheses about what intervention characteristics may contribute to positive outcomes. Our findings allow us to hypothesize that setting (outside a hospital), integration (CHWs within a care team), and duration (1 year or more) may contribute to successful CHW interventions. These hypotheses warrant further study, as they are based on a small number of heterogeneous studies and observed trends, rather than statistical analysis. Overall, however, there were few apparent differences between the interventions that produced positive results and those that did not. The lack of clear differentiating factors may be, in part, due to the paucity of research on effects of CHW-based interventions in the US, constraining the sample size of this systematic review. There is also variable standardization and detail in descriptions of CHW-based interventions, limiting our ability to identify differentiating factors. To improve published descriptions of future interventions, we propose characteristics that should be reported for all CHW programs in Table  6 .

Reporting Domains for CHW Interventions

Our review has a number of limitations. First, there is great heterogeneity in study design, population, reporting of intervention characteristics, and outcomes measured, making it difficult to compare studies or determine which intervention characteristics are associated with positive outcomes. Second, the methodological rigor of the included studies is variable. Many were not RCTs, and some did not include calculations of statistical significance. However, we conducted a detailed methodological review, which improved the quality of evidence included and facilitated interpretation of evidence in light of methodological rigor. Third, the findings of this review are likely affected by publication bias, as studies with negative results are less likely to be published (in particular, non-RCT designs). By using the complete list of CHW job titles collected by the Massachusetts Department of Public Health, however, we were able to identify relevant published studies that may not have been captured in the narrower search strategies used in previous reviews on CHWs. Fourth, CHWs have many positive effects on health, including improving health outcomes and experience of care, that are not captured in the financial impacts that were the focus of this study. These health effects may, in the long-term, reduce costs, but the savings may not be realized within study evaluation periods. Fifth, we excluded interventions in which CHWs were unpaid or received only a stipend, which left out some studies that were part of prior systematic reviews.

The review highlights many opportunities for research. Future studies should test the hypotheses generated in our analysis of effective CHW interventions (setting, duration, and care teams); examine characteristics that have received little attention in the current literature, including supervision structures, smartphone-based strategies combined with CHW care, and alternate settings for chronic condition management; and identify which segments of the population would be most appropriate for CHW interventions, examining diagnosis, disease severity, minority status (racial, ethnic, linguistic), and comorbidities. We should also explore how to scale-up and sustainably fund evidence-based CHW interventions, as few interventions have been scaled at a population level, and there will be greater incentive to develop and test interventions if long-term funding is available.

Below is the link to the electronic supplementary material.

(DOCX 29 kb)

Acknowledgements

Contributors.

We would like to thank Jessica Alpert, Clemens Hong, David Osterbur, Judith Palfrey, and the staff of the Office of Community Health Workers at the Massachusetts Department of Public Health for their assistance with this review.

This study received support from the Harvard Medical School Center for Primary Care and the Massachusetts Department of Public Health (grant no. 225307).

Compliance with Ethical Standards

Conflict of interest.

During the majority of the time that this study was being conducted, Dr. Russell Phillips was an advisor to Rise Labs, a start-up that provides web-based nutrition coaching to individuals. He no longer serves in this role. All other authors declare no conflicts of interest.

Protocol registration number: CRD42016035728

Victor Mukhin

• Scientific Program

Title : Active carbons as nanoporous materials for solving of environmental problems

However, up to now, the main carriers of catalytic additives have been mineral sorbents: silica gels, alumogels. This is obviously due to the fact that they consist of pure homogeneous components SiO2 and Al2O3, respectively. It is generally known that impurities, especially the ash elements, are catalytic poisons that reduce the effectiveness of the catalyst. Therefore, carbon sorbents with 5-15% by weight of ash elements in their composition are not used in the above mentioned technologies. However, in such an important field as a gas-mask technique, carbon sorbents (active carbons) are carriers of catalytic additives, providing effective protection of a person against any types of potent poisonous substances (PPS). In ESPE “JSC "Neorganika" there has been developed the technology of unique ashless spherical carbon carrier-catalysts by the method of liquid forming of furfural copolymers with subsequent gas-vapor activation, brand PAC. Active carbons PAC have 100% qualitative characteristics of the three main properties of carbon sorbents: strength - 100%, the proportion of sorbing pores in the pore space – 100%, purity - 100% (ash content is close to zero). A particularly outstanding feature of active PAC carbons is their uniquely high mechanical compressive strength of 740 ± 40 MPa, which is 3-7 times larger than that of  such materials as granite, quartzite, electric coal, and is comparable to the value for cast iron - 400-1000 MPa. This allows the PAC to operate under severe conditions in moving and fluidized beds.  Obviously, it is time to actively develop catalysts based on PAC sorbents for oil refining, petrochemicals, gas processing and various technologies of organic synthesis.

Victor M. Mukhin was born in 1946 in the town of Orsk, Russia. In 1970 he graduated the Technological Institute in Leningrad. Victor M. Mukhin was directed to work to the scientific-industrial organization "Neorganika" (Elektrostal, Moscow region) where he is working during 47 years, at present as the head of the laboratory of carbon sorbents.     Victor M. Mukhin defended a Ph. D. thesis and a doctoral thesis at the Mendeleev University of Chemical Technology of Russia (in 1979 and 1997 accordingly). Professor of Mendeleev University of Chemical Technology of Russia. Scientific interests: production, investigation and application of active carbons, technological and ecological carbon-adsorptive processes, environmental protection, production of ecologically clean food.   

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