Health status transitions in community-living elderly with complex care needs: a latent class approach

Electronic Health Literacy Among Baby Boomers: A Typology

BACKGROUND

Forecasts suggest that older adults will place unprecedented demands on future health care systems. Electronic health (eHealth) resources can potentially mitigate some pressures, but to be effective patients need to be able to use them. The negative relationship between eHealth literacy and age usually results in older adults classified as one homogenous mass, which misses the opportunity to tailor interventions.

OBJECTIVE

This research examines similarities and differences within the baby boom cohort among a sample that uses the internet for health information.

METHODS

We used an electronic survey with random samples of baby boomers (N = 996) from the United States, the United Kingdom, and New Zealand.

KEY RESULTS

Four distinct subgroups, or segments, emerged. While not different from a socioeconomic perspective, these four groups have very different levels of eHealth literacy and corresponding health behaviors. Therefore, we contribute a more complex picture than is usually presented in eHealth studies.

CONCLUSIONS

Resulting insights offer a useful starting point for providers wishing to better tailor health products, services, and communications to this large cohort of future older individuals. [HLRP: Health Literacy Research and Practice. 2024;8(1):e3-e11.].

Multidimensional health heterogeneity of Chinese older adults and its determinants

Background

Nowadays, the "Healthy China" and "Actively Addressing Population Aging" are two important national strategies in China. Promoting high-quality development of demand-driven older adults health services is an important way to achieve these strategies. From the perspective of active ageing, assessing the health status of older adults from multiple dimensions becomes crucial as it helps identify their specific health service needs, intervention measures, and health policies tailored to this population.

Methods

Data were derived from the China Health and Retirement Longitudinal Study (CHARLS) wave 4 (2018). A total of 4190 older adults (aged ≥60 years) were included as the analysis sample. Latent class analysis was performed to categorize older adults based on 6 health indicators, including Activities of Daily Living (ADLs), Instrumental Activities of Daily Living (IADLs), doctor diagnosed chronic diseases, depressive symptoms, cognitive function, and social participation. Multinomial logistic model was used to explore determinants associated with the various patterns of multidimensional health of older adults.

Results

The multidimensional health of older people was classified into three latent classes: Relatively Healthy (Class 1, n = 2806, 66.97%), Highly Depressed and Relatively Health Risk (Class 2, n = 1189, 28.38%), and Functional Impairment (Class 3, n = 195, 4.65%). Gender, age, education, marital status, number of children, alcohol consumption, physical activity, savings, residence, air quality satisfaction, and medical service satisfaction had significant effects on the attribution of all multidimensional health latent classes.

Conclusion

Heterogeneous and multidimensional health classes exist in China's older population, and these classes are influenced by a variety of factors and to varying degrees. Policymakers and healthcare providers can use these evidence to further address the diverse needs of older adults and improve older-care health services, ultimately achieving the goal of Active Ageing and Healthy China.

Transitions of Activities of Daily Living Status among Inpatients with Subacute Stroke: A Latent Class Approach

Objectives

This study investigated the transition patterns of activities of daily living (ADL) status based on the Functional Independence Measure (FIM) motor and cognitive items in patients who experienced subacute stroke.

Methods

In this single-site, retrospective investigation, 1592 FIM samples were collected during the hospitalization of 373 stroke patients who were admitted between April 2018 and March 2020. FIM item levels were transformed from seven to three (FIM1-2, Complete Dependence; FIM3-5, Modified Dependence; FIM6-7, Independence). FIM samples were classified by latent class modeling into six latent ADL states based on the independence levels of FIM motor and cognitive items. We created an ADL status transition diagram based on the FIM sample's probability of belonging to each status at different hospitalization timepoints.

Results

Transition diagrams for each ADL status at admission revealed distinct patterns. In two ADL statuses for which patients required full assistance in FIM motor items, the patients remained motor-dependent without achieving independence on discharge. In contrast, patients in transition from the other four ADL statuses largely achieved independence in motor items by the time of discharge. The time required to reach higher ADL status varied according to the initial ADL status at admission; the slowest improvement was observed in statuses initially classified as needing the most assistance, whereas many patients achieved transition within 3 months from admission.

Conclusions

Based on the characteristics of patient ADL status and timing of its changes, the classification of ADL status and visualization of ADL transition can contribute to improved treatment.

Three-year trajectories in functional limitations and cognitive decline among Dutch 75+ year olds, using nine-month intervals

Background

Using longitudinal panel data, we aimed to identify three-year trajectories in cognitive and physical functioning among Dutch older adults, and the characteristics associated with these trajectories.

Methods

We used Group-based Trajectory Modelling with mortality jointly estimated to identify trajectories, using a scale composed of 6 Activities of Daily Living (ADL) as a measure of physical functioning, and the short mini mental status examination (sMMSE) or the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) as a measure of cognitive functioning. Data came from 574 Dutch adults aged 75+, collected in five nine-month measurement waves (2015–2018) for the Longitudinal Aging Study Amsterdam.

Results

For physical functioning five trajectories were identified: ‘high’, ‘moderate’, ‘steeply declining’, ‘gradually declining’, and ‘continuously low’; and for cognitive functioning: ‘high’, ‘moderate’, ‘declining’, and ‘low’. Living in an institution, and being lower educated increased the probability of the two continuously low functioning trajectories, whereas old age and multimorbidity increased the probability of low physical functioning, but multimorbidity decreased the probability of low cognitive functioning. Associations for steeply declining physical functioning were absent. Being older and having multimorbidity increased the probability of gradually declining physical functioning and declining cognitive functioning. A higher prevalence of lung- and heart disease, cancer, and rheumatic disease was found in the gradually declining physical functioning group; and a higher prevalence of diabetes, cerebrovascular accidents, and cancer was found in the declining cognitive functioning group. High and moderate physical functioning and high cognitive functioning were characterized by being younger, community-dwelling, and higher educated. Having multimorbidity negatively predicted high and moderate physical functioning, but was not associated with high and moderate cognitive functioning.

Conclusions

This study identified trajectories comparable to studies that used longer time intervals, showing the consistent presence of heterogeneity in both physical and cognitive trajectories. Co-modelling mortality resulted in bigger group sizes for the more adverse trajectories. The favourable trajectories, containing most of the participants, were mostly characterized by absence of disease. The prevalence of chronic diseases differed between the declining trajectories, suggesting that certain diseases tend to induce cognitive decline rather than physical decline, and vice versa.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-021-02720-x.

Stratification in health and survival after age 100: evidence from Danish centenarians

BACKGROUND

The existence of a super-select group of centenarians that demonstrates increased survivorship has been hypothesized. However, it is unknown if this super-select group possesses similar characteristics apart from extreme longevity.

METHODS

In this study, we analyse high-quality health and survival data of Danish centenarians born in 1895, 1905 and 1910. We use Latent Class Analysis to identify unobserved health classes and to test whether these super-select lives share similar health characteristics.

RESULTS

We find that, even after age 100, a clear and distinct gradient in health exists and that this gradient is remarkably similar across different birth cohorts of centenarians. Based on the level of health, we identify three clusters of centenarians - robust, frail and intermediate - and show that these groups have different survival prospects. The most distinctive characteristic of the robust centenarians is the outperformance in different health dimensions (physical, functional and cognitive). Finally, we show that our health class categorizations are good predictors of the survival prospects of centenarians.

CONCLUSIONS

There is a clear stratification in health and functioning among those over 100 years of age and these differences are associated with survival beyond age 100.

A Latent Class Analysis of Health Lifestyles in Relation to Suicidality among Adolescents in Mauritius

Suicidality, which includes suicidal thoughts, planning, and suicide attempts, results mainly from a combination of psychological, sociological, and environmental factors. Despite a high prevalence of suicidality among adolescents in Africa, only a few studies have considered these factors simultaneously. The objective of the study was to identify the prevalence of suicidality, to draw up profiles of concomitant risks, and to examine the associations between these profiles and suicidality in Mauritius. This study used data from the 2017 Mauritian Global School-based Student Health Survey including 3012 adolescents with a mean age of 14.9 ± 1.4 years. Factors related to lifestyle such as consumptions of alcohol and tobacco, physical activity, violence, parental support, anxiety, and loneliness were considered. A latent class analysis was performed to identify the profiles. Finally, a modified Poisson regression analysis with generalized estimating equations, adjusted with sociodemographic characteristics, was used to assess the association between these profiles and suicidality. Overall, more than one in ten adolescents had at least one of the suicidality behaviors. Three profiles were identified: 1 = "low risk group" (63.9%); 2 = "problems with violence" (15.2%); 3 = "problems with violence, alcohol, tobacco and psychological distress" (20.9%). Profiles 2 and 3 were mainly made up of males. Adolescents under 15 represented the majority of individuals in profile 2. Finally, the risk of suicidality was higher in adolescents belonging to profiles 2 and 3 compared to profile 1 for the three suicidality behaviors (profile 3: Prevalence ratio (PR) for suicidal thoughts = 1.26, 95% CI = 1.19-1.34; PR for planning = 1.23, 95% CI = 1.17-1.30; PR for attempt = 1.23, 95% CI = 1.17-1.29). This study highlights the high prevalence of suicidality and a list of concomitant risks, emphasizing this suicidality in Mauritian adolescents. Therefore, these results recommend focusing preventive efforts toward a simultaneous consideration of these factors.

Profiles of Frailty among Older People Users of a Home-Based Primary Care Service in an Urban Area of Barcelona (Spain): An Observational Study and Cluster Analysis

Background: The multidimensional assessment of frailty allows stratifying it into degrees; however, there is still heterogeneity in the characteristics of people in each stratum. The aim of this study was to identify frailty profiles of older people users of a home-based primary care service. Methods: We carried out an observational study from January 2018 to January 2021. Participants were all people cared for a home-based primary care service. We performed a cluster analysis by applying a k-means clustering technique. Cluster labeling was determined with the 22 variables of the Frail-VIG index, age, and sex. We computed multiple indexes to assess the optimal number of clusters, and this was selected based on a clinical assessment of the best options. Results: Four hundred and twelve participants were clustered into six profiles. Three of these profiles corresponded to a moderate frailty degree, two to a severe frailty degree and one to a mild frailty degree. In addition, almost 75% of the participants were clustered into three profiles which corresponded to mild and moderate degree of frailty. Conclusions: Different profiles were found within the same degree of frailty. Knowledge of these profiles can be useful in developing strategies tailored to these differentiated care needs.

Portals to frailty? Data-driven analyses detect early frailty profiles

BACKGROUND

Frailty is an aging condition that reflects multisystem decline and an increased risk for adverse outcomes, including differential cognitive decline and impairment. Two prominent approaches for measuring frailty are the frailty phenotype and the frailty index. We explored a complementary data-driven approach for frailty assessment that could detect early frailty profiles (or subtypes) in relatively healthy older adults. Specifically, we tested whether (1) modalities of early frailty profiles could be empirically determined, (2) the extracted profiles were differentially related to longitudinal cognitive decline, and (3) the profile and prediction patterns were robust for males and females.

METHODS

Participants (n = 649; M age = 70.61, range 53-95) were community-dwelling older adults from the Victoria Longitudinal Study who contributed data for baseline multi-morbidity assessment and longitudinal cognitive trajectory analyses. An exploratory factor analysis on 50 multi-morbidity items produced 7 separable health domains. The proportion of deficits in each domain was calculated and used as continuous indicators in a data-driven latent profile analysis (LPA). We subsequently examined how frailty profiles related to the level and rate of change in a latent neurocognitive speed variable.

RESULTS

LPA results distinguished three profiles: not-clinically-frail (NCF; characterized by limited impairment across indicators; 84%), mobility-type frailty (MTF; characterized by impaired mobility function; 9%), and respiratory-type frailty (RTF; characterized by impaired respiratory function; 7%). These profiles showed differential neurocognitive slowing, such that MTF was associated with the steepest decline, followed by RTF, and then NCF. The baseline frailty index scores were the highest for MTF and RTF and increased over time. All observations were robust across sex.

CONCLUSIONS

A data-driven approach to early frailty assessment detected differentiable profiles that may be characterized as morbidity-intensive portals into broader and chronic frailty. Early inventions targeting mobility or respiratory deficits may have positive downstream effects on frailty progression and cognitive decline.

Health profiles and socioeconomic characteristics of nonagenarians residing in Mugello, a rural area in Tuscany (Italy)

Background

Health, as defined by the WHO, is a multidimensional concept that includes different aspects. Interest in the health conditions of the oldest-old has increased as a consequence of the phenomenon of population aging. This study investigates whether (1) it is possible to identify health profiles among the oldest-old, taking into account physical, emotional and psychological information about health, and (2) there are demographic and socioeconomic differences among the health profiles.

Methods

Latent Class Analysis with covariates was applied to the Mugello Study data to identify health profiles among the 504 nonagenarians residing in the Mugello district (Tuscany, Italy) and to evaluate the association between socioeconomic characteristics and the health profiles resulting from the analysis.

Results

This study highlights four groups labeled according to the posterior probability of determining a certain health characteristic: “healthy”, “physically healthy with cognitive impairment”, “unhealthy”, and “severely unhealthy”. Some demographic and socioeconomic characteristics were found to be associated with the final groups: older nonagenarians are more likely to be in worse health conditions; men are in general healthier than women; more educated individuals are less likely to be in extremely poor health conditions, while the lowest-educated are more likely to be cognitively impaired; and office or intellectual workers are less likely to be in poor health conditions than are farmers.

Conclusions

Considering multiple dimensions of health to determine health profiles among the oldest-old could help to better evaluate their care needs according to their health status.

Preferences heterogeneity of health care utilization of community residents in China: a stated preference discrete choice experiment

Background

To tackle the issue with the low usage of primary healthcare service in China, it is essential to align resource distribution with the preferences of the community residents. There are few academic researches for describing residents’ perceived characteristics of healthcare services in China. This study aims to investigate the preferences of healthcare services utilization in community residents and explore the heterogeneity. The findings will be useful for the policy makers to take targeted measures to tailor the provision of healthcare services.

Methods

The face-to-face interviews and surveys were conducted to elicit four key attributes (care provider; mode of services; cost; travel time) of the preference from community residents for healthcare utilization. A rational test was presented first to confirm the consistency, and then 16 pairs of choice tasks with 12 sociodemographic items were given to the respondents. Two hypothetical options for each set, without an opt-out option, were presented in each choice task. The latent class analysis (LCA) was used to analyse the data.

Results

Two thousand one hundred sixty respondents from 36 communities in 6 cities were recruited for our study. 2019 (93.47%) respondents completed valid discrete choice experiment (DCE) questionnaires. The LCA results suggested that four groups of similar preferences were identified. The first group (27.29%) labelled as “Comprehensive consideration” had an even preference of all four attributes. The second group (37.79%) labelled as “Price-driven” preferred low-price healthcare services. The third group labelled as “Near distance” showed a clear preference for seeking healthcare services nearby. The fourth group (34.18%) labelled as “Quality seeker” preferred the healthcare service provided by experts. Willingness to pay (WTP) results showed that people were willing to accept CNY202.12($29.37) for Traditional Chinese Medicine (TCM) services and willing to pay CNY604.31($87.81) for the service provided by experts.

Conclusions

Our study qualitatively measures the distinct preferences for healthcare utilization in community residents in China. The results suggest that the care provider, mode of services, travel time and cost should be considered in priority setting decisions. The study, however, reveals substantial disagreement in opinion of TCM between different population subgroups.

Evaluation of bottom-up interventions targeting community-dwelling frail older people in Belgium: methodological challenges and lessons for future comparative effectiveness studies

Background

Optimizing the organization of care for community-dwelling frail older people is an important issue in many Western countries. In Belgium, a series of complex, innovative, bottom-up interventions was recently designed and implemented to help frail older people live at home longer. As the effectiveness of these interventions may vary between different population groups according to their long-term care needs, they must be evaluated by comparison with a control group that has similar needs.

Methods

The goal was to identify target groups for these interventions and to establish control groups with similar needs and to explore, per group, the extent to which the utilization of long-term care is matched to needs. We merged two databases: a clinical prospective database and the routine administrative database for healthcare reimbursements. Through Principal Component Analysis followed by Clustering, the intervention group was first stratified into disability profiles. Per profile, comparable control groups for clinical variables were established, based on propensity scores. Using chi-squared tests and logistic regression analysis, long-term care utilization at baseline was then compared per profile and group studied.

Results

Stratification highlighted five disability profiles: people with low-level limitations; people with limitations in instrumental activities of daily life and low-level of cognitive impairment; people with functional limitations; people with functional and cognitive impairments; and people with functional, cognitive, and behavioral problems. These profiles made it possible to identify long-term care needs. For instance, at baseline, those who needed more assistance with hygiene tasks also received more personal nursing care (P < 0.05). However, there were some important discrepancies between the need for long-term care and its utilization: while 21% of patients who were totally dependent for hygiene tasks received no personal nursing care, personal nursing care was received by 33% of patients who could perform hygiene tasks.

Conclusions

The disability profiles provide information on long-term care needs but not on the extent to which those needs are met. To assess the effectiveness of interventions, controls at baseline should have similar disability profiles and comparable long-term care utilization. To allow for large comparative effectiveness studies, these dimensions should ideally be available in routine databases.

Electronic supplementary material

The online version of this article (10.1186/s12913-019-4240-9) contains supplementary material, which is available to authorized users.

Predictive ability of an expert-defined population segmentation framework for healthcare utilization and mortality - a retrospective cohort study

Background

Population segmentation of patients into parsimonious and relatively homogenous subgroups or segments based on healthcare requirements can aid healthcare resource planning and the development of targeted intervention programs. In this study, we evaluated the predictive ability of a previously described expert-defined segmentation approach on 3-year hospital utilization and mortality.

Methods

We segmented all adult patients who had a healthcare encounter with Singapore Health Services (SingHealth) in 2012 using the SingHealth Electronic Health Records (SingHealth EHRs). Patients were divided into non-overlapping segments defined as Mostly Healthy, Stable Chronic, Serious Acute, Complex Chronic without Frequent Hospital Admissions, Complex Chronic with Frequent Hospital Admissions, and End of Life, using a previously described expert-defined segmentation approach. Hospital admissions, emergency department attendances (ED), specialist outpatient clinic attendances (SOC) and mortality in different patient subgroups were analyzed from 2013 to 2015.

Results

819,993 patients were included in this study. Patients in Complex Chronic with Frequent Hospital Admissions segment were most likely to have a hospital admission (IRR 22.7; p < 0.001) and ED visit (IRR 14.5; p < 0.001) in the follow-on 3 years compared to other segments. Patients in the End of Life and Complex Chronic with Frequent Hospital Admissions segments had the lowest three-year survival rates of 58.2 and 62.6% respectively whereas other segments had survival rates of above 90% after 3 years.

Conclusion

In this study, we demonstrated the predictive ability of an expert-driven segmentation framework on longitudinal healthcare utilization and mortality.

Electronic supplementary material

The online version of this article (10.1186/s12913-019-4251-6) contains supplementary material, which is available to authorized users.

Heterogeneous health profiles and healthcare utilization of the middle-aged and elderly with multiple health insurance schemes in China

OBJECTIVES

China is facing an escalating demand of healthcare services from the middle-aged and elderly. Compared with the traditional view of health on symptoms and diseases, this study aimed to assess the heterogeneous health profiles of middle-aged and elderly Chinese by a person-centered approach. Furthermore, this study examined the effects of health profiles and associated factors on healthcare utilization within the context of China's multiple health insurance schemes.

STUDY DESIGN

The study used the 2015 data of China Health and Retirement Longitudinal Study, a nationwide population-based sample of people aged 45 years and older.

METHODS

Latent class analysis (LCA) was adopted to identify the heterogeneous health profiles. Two-part models were adopted to assess the effects of associated factors on healthcare utilization.

RESULTS

Among 15,250 Chinese aged 45 years and older, six heterogeneous health profiles were identified and labeled as 'Quite Healthy', 'Relatively Healthy', 'Comprehensive Comorbidities', 'Functional Impairment', 'Severe Disability', and 'Relatively Frail'. The Relatively Frail profile was the heaviest healthcare user. The Severe Disability profile took the least use of outpatient services but had relatively high utilization of inpatient services and outpatient expenditure. The Comprehensive Comorbidities profile tended to have the smallest effect on the frequency of visits for both inpatient and outpatient services, but its effect on outpatient expenditure was high. After controlling for health profiles, the significant effects of different health insurance programs on healthcare utilization were discussed.

CONCLUSIONS

Introducing health profiles by the person-centered approach of LCA has provided a holistic understanding of complex healthcare demands for middle-aged and elderly Chinese. It is valuable for policy makers to improve healthcare resource allocation targeted for the middle-aged and elderly.

Health and Volunteering in Europe: A Longitudinal Study

This article examines the relationship between health and volunteering in advanced age in a cross-national comparison. We used longitudinal data from five waves of the Survey of Health, Ageing and Retirement in Europe covering 13 European countries from 2004 to 2015 and employed dynamic random-effects probit models to study the consequences of declining health on voluntary work. Our results confirm that worsening health conditions (i.e., mobility limitations and depression) reduce the likelihood of volunteering, whereas chronic diseases do not. Most interestingly, we found important differences across countries: Worsening health reduces voluntary work participation, especially in contexts characterized by high rates of volunteering. Our findings have implications for policy makers and voluntary organizations that aim to encourage participation: Individual characteristics and contextual aspects must be taken into account, and people with health problems might need specific support through policies, recruitment, and retention even in contexts of overall high levels of volunteering.

The (cost-)effectiveness of preventive, integrated care for community-dwelling frail older people: A systematic review

Integrated care is increasingly promoted as an effective and cost-effective way to organise care for community-dwelling frail older people with complex problems but the question remains whether high expectations are justified. Our study aims to systematically review the empirical evidence for the effectiveness and cost-effectiveness of preventive, integrated care for community-dwelling frail older people and close attention is paid to the elements and levels of integration of the interventions. We searched nine databases for eligible studies until May 2016 with a comparison group and reporting at least one outcome regarding effectiveness or cost-effectiveness. We identified 2,998 unique records and, after exclusions, selected 46 studies on 29 interventions. We assessed the quality of the included studies with the Effective Practice and Organization of Care risk-of-bias tool. The interventions were described following Rainbow Model of Integrated Care framework by Valentijn. Our systematic review reveals that the majority of the reported outcomes in the studies on preventive, integrated care show no effects. In terms of health outcomes, effectiveness is demonstrated most often for seldom-reported outcomes such as well-being. Outcomes regarding informal caregivers and professionals are rarely considered and negligible. Most promising are the care process outcomes that did improve for preventive, integrated care interventions as compared to usual care. Healthcare utilisation was the most reported outcome but we found mixed results. Evidence for cost-effectiveness is limited. High expectations should be tempered given this limited and fragmented evidence for the effectiveness and cost-effectiveness of preventive, integrated care for frail older people. Future research should focus on unravelling the heterogeneity of frailty and on exploring what outcomes among frail older people may realistically be expected.

Understanding complex care for older adults within Canadian home care: a systematic literature review

In the context of an aging population, both the need for home care services and its complexity of care have increased in many high-income countries. Yet, the definition of what constitutes complex care is largely elusive. This systematic review examined the conceptual definition of complex care within the home care environment using several social and health science databases for research published from 2000 to 2017. Of the 25 articles and reports identified, only 16 addressed complex care specifically and included older adults, aging, and/or home care. The results showed that complex care for older adults is primarily defined from a biomedical approach focusing on chronic disease and management and less commonly from the perspective of the social determinants of health. Future studies should consider the importance of the continuum of care needs from both the biomedical and the social determinants to adequately plan and provide care for older adults.

Assessing the validity of a data driven segmentation approach: A 4 year longitudinal study of healthcare utilization and mortality

BACKGROUND

Segmentation of heterogeneous patient populations into parsimonious and relatively homogenous groups with similar healthcare needs can facilitate healthcare resource planning and development of effective integrated healthcare interventions for each segment. We aimed to apply a data-driven, healthcare utilization-based clustering analysis to segment a regional health system patient population and validate its discriminative ability on 4-year longitudinal healthcare utilization and mortality data.

METHODS

We extracted data from the Singapore Health Services Electronic Health Intelligence System, an electronic medical record database that included healthcare utilization (inpatient admissions, specialist outpatient clinic visits, emergency department visits, and primary care clinic visits), mortality, diseases, and demographics for all adult Singapore residents who resided in and had a healthcare encounter with our regional health system in 2012. Hierarchical clustering analysis (Ward's linkage) and K-means cluster analysis using age and healthcare utilization data in 2012 were applied to segment the selected population. These segments were compared using their demographics (other than age) and morbidities in 2012, and longitudinal healthcare utilization and mortality from 2013-2016.

RESULTS

Among 146,999 subjects, five distinct patient segments "Young, healthy"; "Middle age, healthy"; "Stable, chronic disease"; "Complicated chronic disease" and "Frequent admitters" were identified. Healthcare utilization patterns in 2012, morbidity patterns and demographics differed significantly across all segments. The "Frequent admitters" segment had the smallest number of patients (1.79% of the population) but consumed 69% of inpatient admissions, 77% of specialist outpatient visits, 54% of emergency department visits, and 23% of primary care clinic visits in 2012. 11.5% and 31.2% of this segment has end stage renal failure and malignancy respectively. The validity of cluster-analysis derived segments is supported by discriminative ability for longitudinal healthcare utilization and mortality from 2013-2016. Incident rate ratios for healthcare utilization and Cox hazards ratio for mortality increased as patient segments increased in complexity. Patients in the "Frequent admitters" segment accounted for a disproportionate healthcare utilization and 8.16 times higher mortality rate.

CONCLUSION

Our data-driven clustering analysis on a general patient population in Singapore identified five patient segments with distinct longitudinal healthcare utilization patterns and mortality risk to provide an evidence-based segmentation of a regional health system's healthcare needs.

The frail older person does not exist: development of frailty profiles with latent class analysis

Background

A fundamental issue in elderly care is targeting those older people at risk and in need of care interventions. Frailty is widely used to capture variations in health risks but there is no general consensus on the conceptualization of frailty. Indeed, there is considerable heterogeneity in the group of older people characterized as frail. This research identifies frailty profiles based on the physical, psychological, social and cognitive domains of functioning and the severity of the problems within these domains.

Methods

This research was a secondary data-analysis of older persons derived from The Older Person and Informal Caregiver Minimum Dataset. Selected respondents were 60 years and older (n = 43,704; 59.6% female). The following variables were included: self-reported health, cognitive functioning, social functioning, mental health, morbidity status, and functional limitations. Using latent class analysis, the population was divided in subpopulations that were subsequently discussed in a focus group with older people for further validation.

Results

We distinguished six frailty profiles: relatively healthy; mild physically frail; psychologically frail; severe physically frail; medically frail and multi-frail. The relatively healthy had limited problems across all domains. In three profiles older people mostly had singular problems in either the physical or psychological domain and the severity of the problems differed. Two remaining profiles were multidimensional with a combination of problems that extended to the social and cognitive domains.

Conclusions

Our research provides an empirical base for meaningful frailty profiles. The profiles showed specific patterns underlying the problems in different domains of functioning. The heterogeneous population of frail older people has differing needs and faces different health issues that should be considered to tailor care interventions. Evaluation research of these interventions should acknowledge the heterogeneity of frailty by profiling.

Electronic supplementary material

The online version of this article (10.1186/s12877-018-0776-5) contains supplementary material, which is available to authorized users.

Evaluation of a practical expert defined approach to patient population segmentation: a case study in Singapore

Background

Segmenting the population into groups that are relatively homogeneous in healthcare characteristics or needs is crucial to facilitate integrated care and resource planning. We aimed to evaluate the feasibility of segmenting the population into discrete, non-overlapping groups using a practical expert and literature driven approach. We hypothesized that this approach is feasible utilizing the electronic health record (EHR) in SingHealth.

Methods

In addition to well-defined segments of “Mostly healthy”, “Serious acute illness but curable” and “End of life” segments that are also present in the Ministry of Health Singapore framework, patients with chronic diseases were segmented into “Stable chronic disease”, “Complex chronic diseases without frequent hospital admissions”, and “Complex chronic diseases with frequent hospital admissions”. Using the electronic health record (EHR), we applied this framework to all adult patients who had a healthcare encounter in the Singapore Health Services Regional Health System in 2012. ICD-9, 10 and polyclinic codes were used to define chronic diseases with a comprehensive look-back period of 5 years. Outcomes (hospital admissions, emergency attendances, specialist outpatient clinic attendances and mortality) were analyzed for years 2012 to 2015.

Results

Eight hundred twenty five thousand eight hundred seventy four patients were included in this study with the majority being healthy without chronic diseases. The most common chronic disease was hypertension. Patients with “complex chronic disease” with frequent hospital admissions segment represented 0.6% of the eligible population, but accounted for the highest hospital admissions (4.33 ± 2.12 admissions; p < 0.001) and emergency attendances (ED) (3.21 ± 3.16 ED visits; p < 0.001) per patient, and a high mortality rate (16%). Patients with metastatic disease accounted for the highest specialist outpatient clinic attendances (27.48 ± 23.68 visits; p < 0.001) per patient despite their relatively shorter course of illness and high one-year mortality rate (33%).

Conclusion

This practical segmentation framework can potentially distinguish among groups of patients, and highlighted the high disease burden of patients with chronic diseases. Further research to validate this approach of population segmentation is needed.

Electronic supplementary material

The online version of this article (doi: 10.1186/s12913-017-2736-8) contains supplementary material, which is available to authorized users.

Assessing future care preparation in late life: Two short measures

The purpose of this article is to introduce 2 short forms of the previously published measure of preparation for future care (PFC). Community-dwelling older adults ages 65-94 who had completed the 29-item Preparation for Future Care Needs scale were randomly divided into scale development (n = 697) and scale validation (n = 690) samples. Fifteen items were selected using exploratory and confirmatory factor analyses on the scale development and scale validation samples, respectively. Consistent with PFC theory, the 5 subscales of the original long-form measure (Awareness, Gathering Information, Decision Making, Concrete Planning, Avoidance of Care Planning) were maintained. A 5-item scale with acceptable score reliability and validity was also developed. Compared to the long form, these short forms are more easily incorporated into epidemiologic studies and can be used in medical, psychology, and social work practice to initiate discussions about long-term care planning. (PsycINFO Database Record

Health status profiles in community-dwelling elderly using self-reported health indicators: a latent class analysis

PURPOSE

Latent class analysis (LCA), a statistical method for identifying latent classes within a population using multiple indicators, has been used to study the heterogeneity of health among the elderly. We aim to identify health status profiles of older adults using LCA and examine the socio-demographic characteristics associated with each profile.

METHODS

A community health survey of residents ≥60 years was conducted in Marine Parade, Singapore. We performed LCA on seven health indicators (number of chronic conditions, activities of daily living (ADL) dependency, pain, depression, cognition, social isolation, and frequency of socialising) to identify distinct classes of health status profiles. Multivariable logistic regression was conducted to examine the socio-demographic characteristics associated with each profile.

RESULTS

Of the 2,444 elderly interviewed, we identified two health status profiles: "Health at risk" (n = 465, 19.0 %), and "Relatively healthy" (n = 1,979, 81.0 %). The "Health at risk" profile was characterised by high probabilities of 3+ chronic conditions (λ = 0.63), at least one basic/instrumental ADL dependency (λ = 0.56), moderate/extreme pain (λ = 0.55), cognitive impairment (λ = 0.29), depressive symptoms (λ = 0.29), social isolation (λ = 0.27), and infrequent socialisation (λ = 0.61). Individuals who were older (65-74, 75-84, and 85+ years), females, of non-Chinese ethnicity (Indian, Malay, and Others), had primary and lower education, and were unemployed/not employed were more likely to be "Health at risk".

CONCLUSION

Using LCA, we identified two distinct health status profiles which accounted for the heterogeneity of the elderly population. Selected socio-demographic characteristics were associated with different profiles and provide implications for the structuring of future public health interventions targeting the older population.

A person-centred segmentation study in elderly care: towards efficient demand-driven care

Providing patients with more person-centred care without increasing costs is a key challenge in healthcare. A relevant but often ignored hindrance to delivering person-centred care is that the current segmentation of the population and the associated organization of healthcare supply are based on diseases. A person-centred segmentation, i.e., based on persons' own experienced difficulties in fulfilling needs, is an elementary but often overlooked first step in developing efficient demand-driven care. This paper describes a person-centred segmentation study of elderly, a large and increasing target group confronted with heterogeneous and often interrelated difficulties in their functioning. In twenty-five diverse healthcare and welfare organizations as well as elderly associations in the Netherlands, data were collected on the difficulties in biopsychosocial functioning experienced by 2019 older adults. Data were collected between March 2010 and January 2011 and sampling took place based on their (temporarily) living conditions. Factor Mixture Model was conducted to categorize the respondents into segments with relatively similar experienced difficulties concerning their functioning. First, the analyses show that older adults can be empirically categorized into five meaningful segments: feeling vital; difficulties with psychosocial coping; physical and mobility complaints; difficulties experienced in multiple domains; and feeling extremely frail. The categorization seems robust as it was replicated in two population-based samples in the Netherlands. The segmentation's usefulness is discussed and illustrated through an evaluation of the alignment between a segment's unfulfilled biopsychosocial needs and current healthcare utilization. The set of person-centred segmentation variables provides healthcare providers the option to perform a more comprehensive first triage step than only a disease-based one. The outcomes of this first step could guide a focused and, therefore, more efficient second triage step. On a local or regional level, this person-centred segmentation provides input information to policymakers and care providers for the demand-driven allocation of resources.

Modeling the relationship between health and health care expenditures using a latent Markov model

We investigate the dynamic relationship between several dimensions of health and health care expenditures for older individuals. Health data from the Longitudinal Aging Survey Amsterdam is combined with data on hospital and long term care use. We estimate a latent variable based jointly on observed health indicators and expenditures. Annual transition probabilities between states of the latent variable are estimated using a Markov model. States associated with good current health and low annual health care expenditures are not associated with lower cumulative health care expenditures over remaining lifetime. We conclude that, although the direct health care cost saving effect is limited, the considerable gain in healthy lifeyears can make investing in the improvement of health of the older population worthwhile.

Effects of physical function trajectories on later long-term care utilization among the Taiwanese elderly

AIM

The aim of this study was to examine the effects of trajectories of physical function on later long-term care utilization based on longitudinal panel data of older adults.

METHODS

A representative longitudinal sample of older adults during the years 1993 to 2007 was used (n=1232). Trajectories of physical function from 1993 to 2007 were identified by group-based trajectory analysis, and then the relationships of the past trajectories with the use of nursing homes and care assistants, and the amount of utilization used in 2007 were examined.

RESULTS

Four groups of physical function difficulties trajectories were identified: none (38.8%), little (34.1%), late increasing (16.1%) and early increasing (11.0%). The early- and late-increasing difficulty groups were more likely to use and used more nursing homes and care assistants. In particular, a long-term disability is closely related to a larger probability of using nursing homes than using care assistants at home. The utilization of care assistants seems a priority choice at the early-increasing stage of disability. When the disability worsens and lasts a long time, a nursing home is then the next choice.

CONCLUSION

Past physical function trajectories relate to later long-term care utilization.

The relationship of preparation for future care to depression and anxiety in older primary care patients at 2-year follow-up

BACKGROUND

: Preparation for future care needs has been hypothesized to help older adults adjust to inevitable life and health transitions and thereby decrease the likelihood of developing depression or anxiety.

METHODS

: A total of 190 primary care patients aged 65 years or more completed semistructured research interviews and mail-back surveys at study intake and 2 years later. Interviews included the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, the Hamilton Depression Rating Scale, Clinical Anxiety Scale and a measure of preparation for future care. Multiple regression analyses were used to determine the independent association of preparation for future care at intake with depression and anxiety severity at 2-year follow-up.

RESULTS

: Patients who had made more concrete plans at intake were less likely to meet criteria for depression diagnosis at follow-up. They also had lower anxiety severity scores. Patients who had avoided thinking about future care needs had greater depression symptom severity at follow-up. Findings were independent of potential confounds, including illness burden.

CONCLUSIONS

: Failure to prepare for future care is a novel putative risk marker for depression and anxiety in older adulthood. Clinicians should be aware that the lack of care planning and frank avoidance may pose a risk for depression and anxiety older their patients. Future research should explore the mechanisms of care planning's effects on subsequent mood.

Multidimensional health-transition patterns among a middle-aged and older population

AIM

Previous studies on health transition have focused on single-dimension outcomes and minimally evaluated heterogeneity. This study aimed to explore heterogeneous and multidimensional health-transition patterns on comorbidity, frailty and disability while examining the factors predicting different patterns of health transition.

METHODS

This study drew on data from a nationwide and longitudinally-followed sample of 5131 Taiwanese aged 50 years and older who were interviewed in 1996, 1999, 2003 and 2007. Latent class analysis (LCA) and multinomial logistic regression were applied to identify health-transition patterns and their predictors.

RESULTS

We identified six health-transition classes by applying LCA, including "persistently healthy", "well-managed comorbidity", "originally comorbid and gradually deteriorating to disability", "deteriorating gradually and died in late stage of the follow-up period", "deteriorating and died in middle stage of the follow-up period", and "originally comorbid and died in early stage of the follow-up period". Using the "well-managed comorbidity" class as the reference group, men had higher probabilities of being in the categories of dying in the follow-up period, but a lower risk of deteriorating to disability. Younger baseline age, higher education, having social engagement and non-smoking were predictors of "persistently healthy" and were associated with a lower risk of deteriorating to disability and death. Having a spouse and health examinations were associated with a lower risk of death, and also a lower probability of "persistently healthy".

CONCLUSIONS

Heterogeneous and multidimensional health-transition patterns exist in middle-aged and older populations. Several factors might have an effect on health-transition patterns.

Yearly transitions of disability profiles in older people living at home

PURPOSE

Planning home services for older people requires extensive knowledge about the progression of disabilities. Disability-based case-mix classifications identify meaningful groups of older people; yet transitions between profiles are mostly unknown.

METHODS

Disability was assessed annually over four years with the Functional Autonomy Measurement System (SMAF) in 1410 older people at risk of functional decline aged 75 and over and living at home. The SMAF generates a case-mix classification of 14 Iso-SMAF profiles with progressive mean disability levels. Transitions made by older people were analyzed using a continuous-time, multi-state Markov model to estimate the probabilities of annual transitions into and out of each profile as well as the mean sojourn time in each profile.

RESULTS

The probability of staying in a profile tended to decrease as profile severity increased. For profiles 5 and above, recovery to mild profiles 1, 2 and 3 was low, while annual probabilities of death and institutionalization were high (>0.10). The lower disability profiles (1 and 2) evidenced a mean profile sojourn time of over two years, contrary to sojourn times of 18 months or less with the other profiles.

CONCLUSIONS

The probabilities are identifiable, indicating that a disability-based classification can characterize progression in older people. Since the required resources and costs are known for each profile, these probabilities are very helpful in planning home services for elderly populations.

Planning and Decision Making for Care Transitions

The need to plan for future health care and residential adjustments increases with age, growing frailty, and restrictions in coverage of long-term care and will continue to grow with population aging. Older adults' lack of financial preparation for health care costs, insufficient knowledge about available options, and inadequate communication about care-related values has become an increasing public health challenge. This chapter describes a model of Preparation for Future Care (PFC), which encompasses different levels and domains of planning. Research about the extent to which planning is helpful in navigating care transitions is reviewed, and barriers and facilitators of planning including individual, familial, cultural, and national long-term care policy factors are discussed. Planning in the context of dementia and practical approaches that can be taken to enhance PFC is addressed, as well as recommendations for future research in the area of planning and decision making in the context of care transitions.