THE PREDICTION OF HEALTHCARE UTILIZATION BY FRAILTY AND DISABILITY AMONG DUTCH COMMUNITY-DWELLING PEOPLE AGED 75 YEARS OR OLDER

 

T. van der Ploeg¹, R.J.J. Gobbens^1,2,3,4

 

1. Faculty of Health, Sports and Social Work, Inholland University of Applied Sciences, Amsterdam, the Netherlands; 2. Zonnehuisgroep Amstelland, Amstelveen, the Netherlands;
3. Department Family Medicine and Population Health, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium; 4. Tranzo, Tilburg University, Tilburg, the Netherlands

Corresponding Author: Tjeerd van der Ploeg, PhD, Inholland University of Applied Sciences Faculty of Health, Sports and Social Work, De Boelelaan 1109, 1081 HV Amsterdam, The Netherlands, E-mail: tvdploeg@quicknet.nl, Phone: +31 6 53519264

J Frailty Aging 2024;in press
Published online February 6, 2024, http://dx.doi.org/10.14283/jfa.2024.14

 

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Abstract

BACKGROUND: Population aging is occurring worldwide. As a result, frailty and disability are in the full interest of practice, policy, and science. An increase in healthcare utilization is an adverse outcome of frailty and disability.
OBJECTIVE: The aim of the present study was the prediction of six indicators of healthcare utilization by frailty and disability measures. The six indicators of healthcare utilization of interest were: use of informal care, number of visits to a general practitioner, hospital admission, receiving nursing care, receiving personal care, and contacts with (health)care professionals.
METHODS: We used a sample of 484 people that was randomly drawn from the municipality of Roosendaal (the Netherlands), a municipality with 78,000 inhabitants. A subset of people who completed the Tilburg Frailty Indicator (TFI) at baseline and the Groningen Activity Restriction Scale (GARS) questionnaires was used with a nine-year followup. We used generalized estimation equations (GEE) to predict the six indicators with the frailty measures (physical, psychological, and social scores) and disability measures (ADL and IADL scores). We also performed GEE analyses adjusted for age, gender, and multimorbidity from part A of the TFI at baseline.
RESULTS: The significant predictors were different for each indicator. However, the physical frailty score, the ADL score, and the IADL score often emerged as significant predictors. These three variables predicted several indicators of healthcare utilization: use of informal care, number of visits to a general practitioner, hospital admission, receiving nursing care, receiving personal care, and contacts with (health)care professionals. The social score was found to be significant for the indicator use of disciplines.
CONCLUSIONS: In conclusion, our study showed that in particular physical frailty, and ADL and IADL disability predicted healthcare utilization in community-dwelling people aged 75 years or older. It is important that care and welfare professionals pay attention to physical frailty and both ADL and IADL disability aiming to diminish frailty and disability and preventing intensive healthcare utilization and related costs. Future research will have to focus on more representative Dutch municipalities in order to get a more reliable and accurate picture of the disciplines used by people with frailty and disability.

Key words: Healthcare utilization, disability, frailty, aging population, GEE analysis, Tilburg Frailty Indicator, Groningen Activity Restriction Scale.

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Introduction

Population aging is occurring worldwide (1). As a result, frailty and disability are in the full interest of practice, policy, and science. Indeed, their prevalence is related to increasing age (2–4). The focus on frailty and disability is high because both can lead to lower quality of life (5, 6), an increase in healthcare utilization and related increase in healthcare costs (7, 8), and mortality (9–12). Many definitions of both frailty and disability exist. With regard to frailty, two types of definitions can be roughly distinguished. Definitions that equate frailty with having physical limitations (physical frailty) and definitions that include not only physical limitations but also psychological and social limitations that older people may have (multidimensional frailty) (13). Disability can be considered as a possible adverse outcome of frailty (14). In studies that examined the relationship between the two concepts, disability is commonly defined as having limitations in performing activities of daily living (7, 15). The phenotype of frailty refers to defining frailty as having physical limitations. It contains five criteria to determine whether someone is frail: unintentional weight loss, weakness, exhaustion, slowness, and low physical activity (16). The Frailty Index and the Tilburg Frailty Indicator (TFI) (17) are examples of measures that include multiple domains of human functioning to determine whether an individual is frail (18).
As noted earlier, an increase in healthcare utilization is an adverse outcome of frailty and disability. There are several indicators of healthcare utilization such as hospitalization, institutionalization, using the emergency department, and contacts with healthcare professionals (e.g. physiotherapist, dietician, psychiatrist, and general practitioner). In particular, many studies have been conducted on the associations between frailty and hospitalization (11, 19, 20). A meta-analysis showed that people with frailty have a 1.2 to 1.8 fold risk for hospitalization (11). This finding was confirmed by a systematic review and meta-analysis, including 13 studies with an average follow-up of 3.1 years (20). To our knowledge, regarding the other indicators of healthcare utilization, only a systematic review and/or meta-analysis has been conducted on the association between frailty and institutionalization (21). This study reported pooled evidence that frailty is a significant factor for nursing home placement (21). In addition, no systematic reviews and meta-analyses were found focusing on the associations between disability and indicators of healthcare utilization. Other studies have been carried out. In Korea for example, people with disability had at least a twofold increase in the odds of using inpatient hospital services (22).
The present study is conducted in the Netherlands. As in many countries around the world, the number of older people in this country is increasing. It has been estimated that by 2050, 33.2% of the Dutch population will be 60 years or older (23). The Netherlands Institute for Social Research has forecasted that by 2030 the number of frail older people will increase to more than 1 million. In 2010, this number was 700.000 (24). This will increase pressure on the Dutch healthcare system. Therefore, the aim of the present study was to determine the prediction of six indicators of healthcare utilization by frailty and disability. The six indicators of healthcare utilization of interest were: use of informal care, number of visits to a general practitioner, hospital admission, receiving nursing care, receiving personal care, and contacts with (health)care professionals. Our study differs from previous studies in that we examined the associations between three domains of frailty (physical, psychological, social) and two types of disability, activities of daily living (ADL), and instrumental activities of daily living (IADL) using a sample of Dutch people aged 75 years or older and a follow-up period of nine years. Studying the effects of the three separate domains of frailty and the two types of disability on indicators of healthcare utilization provides more specific knowledge on which Dutch care and welfare professionals can focus their interventions.

 

Methods

Study Population and Data Collection

In June 2008, a questionnaire including the Tilburg Frailty Indicator (TFI), the Groningen Activity Restriction Scale (GARS), and questions about socio-demographic characteristics was sent to a sample comprising 1,154 community-dwelling people aged 75 years or older. For the TFI, we refer to Appendix A and for the GARS, we refer to Appendix B. The sample was randomly drawn from the municipality of Roosendaal (the Netherlands), a municipality with 78,000 inhabitants. A total of 484 people completed the questionnaire, of which 479 were usable for analysis. Until June 2017, the people who belonged to the sample were invited annually to fill in the same questionnaire. We were therefore able to present the results of nine consecutive measurements. The sample was previously used for frailty studies, e.g. focusing on the psychometric properties of the TFI (17, 25), the relationship between frailty and quality of life in older people (26), and the use of Bayesian techniques in predicting frailty (27).

Frailty Measurements

Part A of the TFI includes ten determinants of frailty. In this study, we used the data from three determinants: age, gender, and multimorbidity. Part B of the TFI contains fifteen components of frailty (total frailty). Eight, four, and three of these components belong to physical, psychological, and social frailty, respectively. The components of physical frailty are physically unhealthy, unexplained weight loss, difficulty in walking, difficulty in maintaining balance, poor hearing, poor vision, lack of strength in the hands, and physical tiredness. Psychological frailty consists of problems with memory, feeling down, feeling nervous or anxious, and unable to cope with problems. Finally, social frailty includes living alone, lack of social relations (loneliness), and lack of social support. The scores range from 0 to 15, 0 to 8, 0 to 4, and 0 to 3 in total, and the physical, psychological, and social domains of frailty, respectively. Higher scores refer to a higher level of frailty.

Disability Measurements

The GARS is a self-reported questionnaire that contains two subscales. One subscale focuses on disability in activities of daily living (ADL) with eleven items. The other subscale measures instrumental activities of daily living (IADL) with seven items. Each of the eighteen items has four response categories: 1) able to perform the activity without any difficulty, 2) able to perform the activity with some difficulty, 3) able to perform the activity with great difficulty, and 4) unable to perform the activity independently. The score for total disability (ADL and IADL disability) ranges from 18 (no disability) to 72 (maximum disability). For the ADL and IADL subscales, the score ranges from 11 to 44 and from 7 to 28, respectively. The GARS has been validated in the Netherlands and demonstrated to have good psychometric properties to assess disability among older people (28, 29).

Outcomes

In this study, we considered the following six outcomes over nine time points (T1 to T9):
– Use of informal care (no, yes)
– Number of visits to general practitioner (4 or less, 5 or more)
– Hospital admission (no, yes)
– Professional help with nursing care (no, yes)
– Professional help with personal care (no, yes)
– Number of disciplines used (4 or less, 5 or more), see appendix C

Predictors

We considered the physical, psychological, and social frailty scores, and the ADL and IADL disability scores at baseline as predictors for the nine consecutive measurements of each outcome.

Statistical Analysis

We used counts and percentages to describe the categorical variables. For the description of the continuous variables, we used mean, standard deviation, minimum value, and maximum value. For the multivariable analysis of the six measurements over time, we used generalized estimation equations (GEE) with correlation structure ‘exchangeable’ and family ‘binomial’ (30, 31). We used the predictors in 2.5 and we also performed GEE analyses with these predictors adjusted for the variables age, gender, and multimorbidity from part A of the TFI at baseline. We included these variables as covariates in the GEE analyses. A p-value <0.05 was considered significant (31). We used R version 3.4.4 (32) for all analyses.

 

Results

Table 1 shows the distribution of the six outcomes over the timepoints T1 to T9.

 

Table 2 shows the characteristics of the continuous predictor variables, and the adjustment variable ‘Age’ at baseline.

 

Table 3 shows the characteristics of the two categorial adjustment variables ‘Gender’ and ‘Multimorbidity’ at baseline.

 

The results of the GEE analyses (unadjusted and adjusted) with the use of ‘Informal care’ as the outcome are presented in Table 4. After adjustment for ‘Age’, ‘Gender’, and ‘Multimorbidity’, the ‘Physical frailty’ score and the ‘IADL score’ showed p-values <0.05 (0.001 and 0.032 respectively).

A=unadjusted; B=adjusted for gender, age, and multimorbidity

 

We dichotomized the number of general practitioner (GP) visits (4 or less vs 5 or more). This cut-off value was based on an article of Kringos et al., 2015 (33). The results of the GEE analyses (unadjusted and adjusted) with this outcome are presented in Table 5. After adjustment for ‘Age’, ‘Gender’, and ‘Multimorbidity’, the ‘Physical frailty score’ and the ‘IADL score’ showed p-values <0.05 (0.010 and 0.049 respectively).

A=unadjusted; B=adjusted for gender, age, and multimorbidity

 

The results of the GEE analyses for the outcome ‘Hospital admission’ are presented in Table 6. The only significant predictor variable after adjustment was the ‘Physical frailty score’ (p-value 0.001).

A=unadjusted; B=adjusted for gender, age, and multimorbidity

 

Table 7 shows that the variable ‘ADL score’ was the only significant predictor for ‘Professional help with nursing care’ after adjustment for ‘Age’, ‘Gender’, and ‘Multimorbidity’ (p-value <0.001).

A=unadjusted; B=adjusted for gender, age, and multimorbidity

 

For the outcome ‘Professional help with personal care’, the predictors ‘ADL score’ and ‘IADL score’ were significant after adjustment (p-values 0.010 and 0.008 respectively), see Table 8.

A=unadjusted; B=adjusted for gender, age, and multimorbidity

 

Participants were asked which disciplines they use. They could choose from eleven disciplines, see Appendix C. The outcome variable was the use of 4 or less vs 5 or more disciplines. This cut-off value was based on an article of Bijnsdorp et al, 2019 (34). Table 9 shows that the ‘Social frailty score’ was significant after adjustment (p-value 0.001).

A=unadjusted; B=adjusted for gender, age, and multimorbidity

 

Discussion

Due to population ageing the prevalence of the number of people with frailty and disability is increasing. Both concepts can lead to adverse outcomes in older people including a lower quality of life (5, 6) and mortality (9, 10). The aim of this study was to determine the prediction of healthcare utilization by frailty and disability in a sample of Dutch community-dwelling older people aged 75 years or older using a follow-up of nine years. We used six indicators of healthcare utilization: the use of informal care, the number of visits to a general practitioner, hospital admission, receiving nursing care, receiving personal care, and contacts with (health)care professionals. Unlike many previous studies, we focused on the prediction of healthcare utilization using three frailty domains (physical, psychological, social), and two types of disability (ADL, IADL). The frailty and disability variables were assessed by the TFI (17) and GARS (28, 29), respectively.
The results of our GEE analyses are presented in Table 4 to Table 9. We discuss the significant predictors for the six outcomes after adjustment for the variables age, gender, and comorbidity from part A of the TFI at baseline. The variables ‘Physical frailty score’ and ‘IADL score’ were significant predictors for the outcomes ‘Informal care’ and ‘Number of visits GP (4 or less vs 5 or more)’ (Table 4 and Table 5). The variable ‘Physical frailty score’ was the only significant predictor for the outcome ‘Hospital admission’ (Table 6). The outcome ‘Professional help with nursing care’ had the variable ‘ADL score’ as significant predictor (Table 7). The outcome ‘Professional help with personal care’ had three significant predictors: ‘Psychological score’, ‘ADL score’, and ‘IADL score (Table 8). The variable ‘Use of disciplines (4 or less vs 5 or more)’ was significantly predicted by the variable ‘Social score’ (Table 9).
Our findings showed that physical frailty predicted the use of informal care, the number of visits to a general practitioner, and hospital admission. As mentioned in the introduction, many studies provided evidence for the prediction of hospital admission by frailty (11, 19, 20). It should be noted here that in the reviews and meta-analyses different frailty instruments were used such physical frailty scales as the phenotype of frailty by Fried et al. (16), and the Study of Osteoporotic Fractures (SOF) Frailty Index (35), and multidimensional frailty scales as the Sherbrooke Postal Questionnaire (SPQ) (36), and the TFI (17). In our study psychological and social frailty assessed with the TFI did not predict hospital admission, both unadjusted and adjusted for gender, age and multimorbidity. This finding is confirmed in a Brazilian study among 963 people aged 60 years or older using primary healthcare services with a follow-up period of one year (37). It was remarkable that contact with (health)care professionals was only predicted by social frailty. Components of social frailty are living alone, lack of social relations and lack of social support. Our finding indicates that people with social frailty contact healthcare and welfare professionals possible with the aim of reducing their social frailty. For example, a number of professionals in the list are not medically oriented (e.g. psychologist, social worker).
The finding that individuals with social frailty use many different disciplines implies that there should be good cooperation between disciplines so that the care and services provided by involved health and welfare professionals are well aligned. Policies should create opportunities for professionals from the care and welfare domains to get to know each other better and align their interventions to properly meet the wants and needs of people with social frailty. We recommend in particular a further study of the association between social frailty and the number of contacts with (health)care professionals. Moreover, we also recommend more studies focusing on the association between social frailty and the other indicators of healthcare utilization.
With regard to the two types of disability, IADL disability and ADL disability, predicted three and two indicators of healthcare utilization, respectively. Both predicted personal care. IADL disability also predicted informal care and the number of visits to a general practitioner, and ADL disability predicted nursing care. IADL disability usually precedes ADL disability. ADL disability represents a more severe and later form of disability (38, 39). This is supported by a Dutch study in a sample of 377 people aged 75 years or older that found that 67.4% and 54.6% of the participants had at least one IADL and ADL disability, respectively (6). This explains that people with IADL disability seek support from informal care and consult their general practitioner. People with ADL disability are more limited in performing activities of daily living and need support from a nurse who can help them with activities as wash and dry the whole body and dressing and undressing.
Some limitations of the present study should be mentioned. First, frailty and disability were assessed by the TFI and the GARS, respectively. Both are self-report scales, that do not include performance based measures. It is possible that a combination of self-report and performance based measures provides a more complete pictures of the concepts. However, among people aged 80 years or older it was observed that self-report of IADL and ADL disability reliably reflected assessment in performance (40). In another study substitution of performance-based criteria of the phenotype of frailty with self-report questions is suggested based on the large agreement between the two measures (41). Secondly, at baseline the sample consisted of 479 older people. As these were people aged 75 or older (mean age 80.3 years with sd 3.8), we lost a lot of people during the follow-up period of nine years. This effects the generalizability of the findings to the broader Dutch population and the external validity. A previous study showed that 162 of these people died in the years 2008 to 2015. Both frailty and disability, assessed with the TFI and GARS, respectively, predicted mortality (9, 42). The loss in follow-up also occurred in our previous longitudinal studies on disability and frailty (43–46). Finally, with regard to the multivariable analysis we only adjusted for age, gender and multimorbidity. Including other variables (e.g. education, income, ethnicity) in these analysis might have led to different results.
In conclusion, our study showed that in particular physical frailty, and ADL and IADL disability predicted healthcare utilization in community-dwelling people aged 75 years or older. These three variables predicted several indicators of healthcare utilization: use of informal care, number of visits to a general practitioner, hospital admission, receiving nursing care, receiving personal care, and contacts with (health)care professionals. It is important that care and welfare professionals pay attention to physical frailty and both ADL and IADL disability aiming to diminish frailty and disability and preventing intensive healthcare utilization and related costs. However, our study also demonstrated that psychological and social frailty are also important to take into account. Future research will have to focus on more representative Dutch municipalities in order to get a more reliable and accurate picture of the disciplines used by people with frailty and disability.

 

Acknowledgements: We would like to thank the municipality of Roosendaal for making their data available.

ORCID of the authors: Tjeerd van der Ploeg:0000-0003-0429-6753; Robbert J. J. Gobbens: 0000-0001-6225-5189.

Conflicts of interest: The authors stated that there were no conflicts of interest.

Ethical standards: All procedures performed in studies involving human participants followed the ethical standards of the institute or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. For the present study, medical ethics approval was not necessary because treatments or interventions were not offered or withheld from respondents. Moreover, the integrity of respondents was not encroached upon because of participating in this study, which is the main criterion in medical-ethical procedures in the Netherlands. Informed consent related to detailing the study and maintaining confidentiality was observed.

 

SUPPLEMENTARY MATERIAL

 

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