Post-surgery interventions for hip fracture: a systematic review of randomized controlled trials.

BACKGROUND: Interventions provided after hip fracture surgery have been shown to reduce mortality and improve functional outcomes. While some systematic studies have evaluated the efficacy of post-surgery interventions, there lacks a systematically rigorous examination of all the post-surgery interventions which allows healthcare providers to easily identify post-operative interventions most pertinent to patient's recovery. OBJECTIVES: We aim to provide an overview of the available evidence on post-surgery interventions provided in the acute, subacute and community settings to improve outcomes for patients with hip fractures. METHODS: We performed a systematic literature review guided by the Preferred Reporting Items for Systematic review and Meta-Analysis (PRISMA). We included articles that were (1) randomized controlled trials (RCTs), (2) involved post-surgery interventions that were conducted in the acute, subacute or community settings and (3) conducted among older patients above 65 years old with any type of non-pathological hip fracture that was surgically treated, and who were able to walk without assistance prior to the fracture. We excluded (1) non-English language articles, (2) abstract-only publications, (3) articles with only surgical interventions, (4) articles with interventions that commenced pre-surgery or immediately upon completion of surgery or blood transfusion, (5) animal studies. Due to the large number of RCTs identified, we only included "good quality" RCTs with Jadad score ≥ 3 for data extraction and synthesis. RESULTS: Our literature search has identified 109 good quality RCTs on post-surgery interventions for patients with fragility hip fractures. Among the 109 RCTs, 63% of the identified RCTs (n = 69) were related to rehabilitation or medication/nutrition supplementation, with the remaining RCTs focusing on osteoporosis management, optimization of clinical management, prevention of venous thromboembolism, fall prevention, multidisciplinary approaches, discharge support, management of post-operative anemia as well as group learning and motivational interviewing. For the interventions conducted in inpatient and outpatient settings investigating medication/nutrition supplementation, all reported improvement in outcomes (ranging from reduced postoperative complications, reduced length of hospital stay, improved functional recovery, reduced mortality rate, improved bone mineral density and reduced falls), except for a study investigating anabolic steroids. RCTs involving post-discharge osteoporosis care management generally reported improved osteoporosis management except for a RCT investigating multidisciplinary post-fracture clinic led by geriatrician with physiotherapist and occupational therapist. The trials investigating group learning and motivational interviewing also reported positive outcome respectively. The other interventions yielded mixed results. The interventions in this review had minor or no side effects reported. CONCLUSIONS: The identified RCTs regarding post-surgery interventions were heterogeneous in terms of type of interventions, settings and outcome measures. Combining interventions across inpatient and outpatient settings may be able to achieve better outcomes such as improved physical function recovery and improved nutritional status recovery. For example, nutritional supplementation could be made available for patients who have undergone hip fracture surgery in the inpatient settings, followed by post-discharge outpatient osteoporosis care management. The findings from this review can aid in clinical practice by allowing formulation of thematic program with combination of interventions as part of bundled care to improve outcome for patients who have undergone hip fracture surgery.

Role of Caregivers in Remote Management of Patients With Type 2 Diabetes Mellitus: Systematic Review of Literature.

BACKGROUND: With the growing use of remote monitoring technologies in the management of patients with type 2 diabetes mellitus (T2DM), caregivers are becoming important resources that can be tapped into to improve patient care. OBJECTIVE: This review aims to summarize the role of caregivers in the remote monitoring of patients with T2DM. METHODS: We performed a systematic review in MEDLINE, Embase, Scopus, PsycINFO, and Web of Science up to 2022. Studies that evaluated the role of caregivers in remote management of adult patients with T2DM were included. Outcomes such as diabetes control, adherence to medication, quality of life, frequency of home glucose monitoring, and health care use were evaluated. RESULTS: Of the 1198 identified citations, 11 articles were included. The majority of studies were conducted in North America (7/11, 64%) and South America (2/11, 18%). The main types of caregivers studied were family or friends (10/11, 91%), while the most common remote monitoring modalities evaluated were interactive voice response (5/11, 45%) and phone consultations (4/11, 36%). With regard to diabetes control, 3 of 6 studies showed improvement in diabetes-related laboratory parameters. A total of 2 studies showed improvements in patients' medication adherence rates and frequency of home glucose monitoring. Studies that evaluated patients' quality of life showed mixed evidence. In 1 study, increased hospitalization rates were noted in the intervention group. CONCLUSIONS: Caregivers may play a role in improving clinical outcomes among patients with T2DM under remote monitoring. Studies on mobile health technologies are lacking to understand their impact on Asian populations and long-term patient outcomes.

Building Digital Literacy in Older Adults of Low Socioeconomic Status in Singapore (Project Wire Up): Nonrandomized Controlled Trial.

BACKGROUND: In a rapidly digitalizing world, the inability of older adults to leverage digital technology has been associated with weaker social connections and poorer health outcomes. Despite the widespread digital adoption in Singapore, older adults, especially those of lower socioeconomic status (SES), still face difficulties in adopting information and communications technology and are typically digitally excluded. OBJECTIVE: We aimed to examine the impact of the volunteer-led, one-on-one, and home-based digital literacy program on digital literacy and health-related outcomes such as self-reported loneliness, social connectedness, quality of life, and well-being for older adults of low SES. METHODS: A nonrandomized controlled study was carried out in Singapore between July 2020 and November 2021 involving 138 digitally excluded community-dwelling older adults aged ≥55 years and of lower SES. Older adults awaiting participation in the program served as controls. Older adults under the intervention were equipped with a smartphone and cellular data, underwent fortnightly to monthly digital literacy training with volunteers to learn digital skills, and digitally connected to their existing social networks. Primary outcome was the improvement in self-reported digital literacy. Secondary outcomes included improvements in University of California, Los Angeles 3-item loneliness scale, Lubben Social Network Scale-6, EQ-5D-3L and EQ visual analogue scale scores, and Personal Wellbeing Score. RESULTS: There were significant improvements in digital literacy scores in the intervention group as compared to controls (mean difference 2.28, 95% CI 1.37-3.20; P<.001). Through multiple linear regression analyses, this difference in digital literacy scores remained independently associated with group membership after adjusting for differences in baseline scores, age, gender, education, living arrangement, housing type, and baseline social connectivity and loneliness status. There was no statistically significant difference in University of California, Los Angeles 3-item loneliness scale, Lubben Social Network Scale-6, Personal Wellbeing Score, or EQ-5D Utility and visual analogue scale score. CONCLUSIONS: This study adds to the growing research on digital inclusion by showing that a volunteer-led, one-on-one, and home-based digital literacy program contributed to increase digital literacy in older adults of low SES. Future studies should look into developing more older adult-friendly digital spaces and technology design to encourage continued digital adoption in older adults and, eventually, impact health-related outcomes.

Ethics of participation and social inclusion of older persons in research: lessons learned from the COVID-19 pandemic in Singapore.

The COVID-19 pandemic brought about safe distancing measures that are unprecedented. This article details the impact of the pandemic across research studies involving older persons in Singapore, and assesses the different strategies used to adapt to their needs in the context of evolving public health measures. The pandemic exposed diverse experiences of vulnerability among older persons, pushing for critical reflections on ethics of participation and social inclusion as the new research normal. We emphasize the importance of practicing flexibility: consideration for differentiated approaches to recruitment and data collection that should be proactively embedded in research designs for older persons during the pandemic and beyond.

An Adaptable Framework for Factors Contributing to Medication Adherence: Results from a Systematic Review of 102 Conceptual Frameworks.

OBJECTIVE: To summarize the available conceptual models for factors contributing to medication adherence based on the World Health Organization (WHO)'s five dimensions of medication adherence via a systematic review, identify the patient groups described in available conceptual models, and present an adaptable conceptual model that describes the factors contributing to medication adherence in the identified patient groups. METHODS: We searched PubMed®, Embase®, CINAHL®, and PsycINFO® for English language articles published from inception until 31 March 2020. Full-text original publications in English that presented theoretical or conceptual models for factors contributing to medication adherence were included. Studies that presented statistical models were excluded. Two authors independently extracted the data. RESULTS: We identified 102 conceptual models, and classified the factors contributing to medication adherence using the WHO's five dimensions of medication adherence, namely patient-related, medication-related, condition-related, healthcare system/healthcare provider-related, and socioeconomic factors. Eight patient groups were identified based on age and disease condition. The most universally addressed factors were patient-related factors. Medication-related, condition-related, healthcare system-related, and socioeconomic factors were represented to various extents depending on the patient group. By systematically examining how the WHO's five dimensions of medication adherence were applied differently across the eight different patient groups, we present a conceptual model that can be adapted to summarize the common factors contributing to medication adherence in different patient groups. CONCLUSION: Our conceptual models can be utilized as a guide for clinicians and researchers in identifying the facilitators and barriers to medication adherence and developing future interventions to improve medication adherence. PROTOCOL REGISTRATION: PROSPERO Identifier: CRD42020181316.

Population segmentation of type 2 diabetes mellitus patients and its clinical applications - a scoping review.

BACKGROUND: Population segmentation permits the division of a heterogeneous population into relatively homogenous subgroups. This scoping review aims to summarize the clinical applications of data driven and expert driven population segmentation among Type 2 diabetes mellitus (T2DM) patients. METHODS: The literature search was conducted in Medline®, Embase®, Scopus® and PsycInfo®. Articles which utilized expert-based or data-driven population segmentation methodologies for evaluation of outcomes among T2DM patients were included. Population segmentation variables were grouped into five domains (socio-demographic, diabetes related, non-diabetes medical related, psychiatric / psychological and health system related variables). A framework for PopulAtion Segmentation Study design for T2DM patients (PASS-T2DM) was proposed. RESULTS: Of 155,124 articles screened, 148 articles were included. Expert driven population segmentation approach was most commonly used, of which judgemental splitting was the main strategy employed (n = 111, 75.0%). Cluster based analyses (n = 37, 25.0%) was the main data driven population segmentation strategies utilized. Socio-demographic (n = 66, 44.6%), diabetes related (n = 54, 36.5%) and non-diabetes medical related (n = 18, 12.2%) were the most used domains. Specifically, patients' race, age, Hba1c related parameters and depression / anxiety related variables were most frequently used. Health grouping/profiling (n = 71, 48%), assessment of diabetes related complications (n = 57, 38.5%) and non-diabetes metabolic derangements (n = 42, 28.4%) were the most frequent population segmentation objectives of the studies. CONCLUSIONS: Population segmentation has a wide range of clinical applications for evaluating clinical outcomes among T2DM patients. More studies are required to identify the optimal set of population segmentation framework for T2DM patients.

Increasing the completion rate of the advance directives in primary care setting - a randomized controlled trial.

BACKGROUND: The completion rate of Advance Directives (ADs) has been low. This study aims to examine the effectiveness of two interventions 1) active counseling sessions coupled with passive patient education pamphlets, and 2) patient education pamphlets alone, compared with 3) control group (usual care), in increasing the completion rates of ADs in the primary care setting. METHODS: Multicenter randomised controlled trial in four public primary care clinics in Singapore under Singapore Health Services. Randomization was performed via block randomization with Sequential Numbered Opaque Sealed Envelopes. Participants were randomized into 1) active intervention group (both counseling by primary care physicians and patient education pamphlets) or 2) passive intervention group (only patient education pamphlets), and 3) control group (usual care) with follow-up at 6 weeks. The main outcome measure is the proportion of participants who completed / planned to complete) ADs six weeks post-intervention. RESULTS: Four hundred five participants were eligible to participate in the study. One hundred eighty-eight participants were recruited into the study (response rate = 46.4%), of which 158 completed the study. There was no significant difference between the control group, passive intervention group, and active intervention group, in terms of completion rates of ADs (29.4, 36.4, and 30.8% respectively). CONCLUSIONS: This randomized controlled trial did not support the use of patient education pamphlets with or without active counseling sessions in increasing the completion of ADs in a primary care setting in Singapore. The optimal intervention strategy depends on each health system's context and resources, taking into consideration patients' profiles, which deserves further studies. TRIAL REGISTRATION: Registered on April 17, 2018 clinicaltrials.gov ( NCT03499847 ).

Prepared and highly committed despite the risk of COVID-19 infection: a cross-sectional survey of primary care physicians' concerns and coping strategies in Singapore.

BACKGROUND: Primary care physicians (PCPs) are first points-of-contact between suspected cases and the healthcare system in the current COVID-19 pandemic. This study examines PCPs' concerns, impact on personal lives and work, and level of pandemic preparedness in the context of COVID-19 in Singapore. We also examine factors and coping strategies that PCPs have used to manage stress during the outbreak. METHODS: Two hundred and sixteen PCPs actively practicing in either a public or private clinic were cluster sampled via email invitation from three primary care organizations in Singapore from 6th to 29th March 2020. Participants completed a cross-sectional online questionnaire consisting of items on work- and non-work-related concerns, impact on personal and work life, perceived pandemic preparedness, stress-reduction factors, and personal coping strategies related to COVID-19. RESULTS: A total of 158 questionnaires were usable for analyses. PCPs perceived themselves to be at high risk of COVID-19 infection (89.9%), and a source of risk (74.7%) and concern (71.5%) to loved ones. PCPs reported acceptance of these risks (91.1%) and the need to care for COVID-19 patients (85.4%). Overall perceived pandemic preparedness was extremely high (75.9 to 89.9%). PCPs prioritized availability of personal protective equipment, strict infection prevention guidelines, accessible information about COVID-19, and well-being of their colleagues and family as the most effective stress management factors. CONCLUSIONS: PCPs continue to serve willingly on the frontlines of this pandemic despite the high perception of risk to themselves and loved ones. Healthcare organizations should continue to support PCPs by managing both their psychosocial (e.g. stress management) and professional (e.g. pandemic preparedness) needs.

Measurement Properties of Patient-Reported Outcome Measures for Diabetes: Systematic Review.

BACKGROUND: The management of diabetes is complex. There is growing recognition of the use of patient-reported outcome measures (PROMs) as a standardized method of obtaining an outlook on patients' functional status and well-being. However, no systematic reviews have summarized the studies that investigate the measurement properties of diabetes PROMs. OBJECTIVE: Our aims were to conduct a systematic review of studies investigating the measurement properties of diabetes PROMs by evaluating the methodological quality and overall level of evidence of these PROMs and to categorize them based on the outcome measures assessed. METHODS: This study was guided by the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) guidelines. Relevant articles were retrieved from the Embase, PubMed, and PsychINFO databases. The PROMs were evaluated with the COSMIN (COnsensus-based Standards for the selection of health Measurement Instruments) guidelines. RESULTS: A total of 363 articles evaluating the measurement properties of PROMs for diabetes in the adult population were identified, of which 238 unique PROMs from 248 studies reported in 209 articles were validated in the type 2 diabetes population. PROMs with at least a moderate level of evidence for ≥5 of 9 measurement properties include the Chinese version of the Personal Diabetes Questionnaire (C-PDQ), Diabetes Self-Management Instrument Short Form (DSMI-20), and Insulin Treatment Appraisal Scale in Hong Kong primary care patients (C-ITAS-HK), of which the C-PDQ has a "sufficient (+)" rating for >4 measurement properties. A total of 43 PROMs meet the COSMIN guidelines for recommendation for use. CONCLUSIONS: This study identified and synthesized evidence for the measurement properties of 238 unique PROMs for patients with type 2 diabetes and categorized the PROMs according to their outcome measures. These findings may assist clinicians and researchers in selecting appropriate high-quality PROMs for clinical practice and research. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42020180978; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020180978.

Roles and recommendations from primary care physicians towards managing low-risk breast cancer survivors in a shared-care model with specialists in Singapore-a qualitative study.

BACKGROUND: Breast cancer is prevalent and has high cure rates. The resultant increase in numbers of breast cancer survivors (BCS) may overwhelm the current oncology workforce in years to come. We postulate that primary care physicians (PCPs) could play an expanded role in comanaging survivors, provided they are given the appropriate tools and training to do so. OBJECTIVE: To explore the perspectives of PCPs towards managing BCS in a community-based shared-care programme with oncologists. METHODS: Eleven focus groups and six in-depth interviews were conducted with seventy PCPs recruited by purposive sampling. All sessions were audio-recorded, transcribed verbatim and coded by three independent investigators. Thematic data analysis was performed and the coding process facilitated by NVivo 12. RESULTS: Majority of PCPs reported currently limited roles in managing acute and non-cancer issues, optimizing comorbidities and preventive care. PCPs aspired to expand their role to include cancer surveillance, risk assessment and addressing unmet psychosocial needs. PCPs preferred to harmonize cancer survivorship management of their primary care patients who are also BCS, with defined role distinct from oncologists. Training to understand the care protocol, enhancement of communication skills, confidence and trust were deemed necessary. PCPs proposed selection criteria of BCS and adequacy of their medical information; increased consultation time; contact details and timely access to oncologists (if needed) in the shared-care programme. CONCLUSIONS: PCPs were willing to share the care of BCS with oncologists but recommended role definition, training, clinical protocol, resources and access to oncologist's consultation to optimize the programme implementation.

Do healthcare needs-based population segments predict outcomes among the elderly? Findings from a prospective cohort study in an urbanized low-income community.

BACKGROUND: A rapidly ageing population with increasing prevalence of chronic disease presents policymakers the urgent task of tailoring healthcare services to optimally meet changing needs. While healthcare needs-based segmentation is a promising approach to efficiently assessing and responding to healthcare needs at the population level, it is not clear how available schemes perform in the context of community-based surveys administered by non-medically trained personnel. The aim of this prospective cohort, community setting study is to evaluate 4 segmentation schemes in terms of practicality and predictive validity for future health outcomes and service utilization. METHODS: A cohort was identified from a cross-sectional health and social characteristics survey of Singapore public rental housing residents aged 60 years and above. Baseline survey data was used to assign individuals into segments as defined by 4 predefined population segmentation schemes developed in Singapore, Delaware, Lombardy and North-West London. From electronic data records, mortality, hospital admissions, emergency department visits, and specialist outpatient clinic visits were assessed for 180 days after baseline segment assignment and compared to segment membership for each segmentation scheme. RESULTS: Of 1324 residents contacted, 928 agreed to participate in the survey (70% response). All subjects could be assigned an exclusive segment for each segmentation scheme. Individuals in more severe segments tended to have lower quality of life as assessed by the EQ-5D Index for health utility. All population segmentation schemes were observed to exhibit an ability to differentiate different levels of mortality and healthcare utilization. CONCLUSIONS: It is practical to assign individuals to healthcare needs-based population segments through community surveys by non-medically trained personnel. The resulting segments for all 4 schemes evaluated in this way have an ability to predict health outcomes and utilization over the medium term (180 days), with significant overlap for some segments. Healthcare needs-based segmentation schemes which are designed to guide action hold particular promise for promoting efficient allocation of services to meet the needs of salient population groups. Further evaluation is needed to determine if these schemes also predict responsiveness to interventions to meet needs implied by segment membership.

Measurement Properties of Existing Patient-Reported Outcome Measures on Medication Adherence: Systematic Review.

BACKGROUND: Medication adherence is essential for improving the health outcomes of patients. Various patient-reported outcome measures (PROMs) have been developed to measure medication adherence in patients. However, no study has summarized the psychometric properties of these PROMs to guide selection for use in clinical practice or research. OBJECTIVE: This study aims to evaluate the quality of the PROMs used to measure medication adherence. METHODS: This study was guided by the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) guidelines. Relevant articles were retrieved from the EMBASE, PubMed, Cochrane Library, Web of Science, and CINAHL (Cumulative Index to Nursing and Allied Health Literature) databases. The PROMs were then evaluated based on the COnsensus-based Standards for the selection of health Measurement Instruments (COSMIN) guidelines. RESULTS: A total of 121 unique medication adherence PROMs from 214 studies were identified. Hypotheses testing for construct validity and internal consistency were the most frequently assessed measurement properties. PROMs with at least a moderate level of evidence for ≥5 measurement properties include the Adherence Starts with Knowledge 20, Compliance Questionnaire-Rheumatology, General Medication Adherence Scale, Hill-Bone Scale, Immunosuppressant Therapy Barrier Scale, Medication Adherence Reasons Scale (MAR-Scale) revised, 5-item Medication Adherence Rating Scale (MARS-5), 9-item MARS (MARS-9), 4-item Morisky Medication Adherence Scale (MMAS-4), 8-item MMAS (MMAS-8), Self-efficacy for Appropriate Medication Adherence Scale, Satisfaction with Iron Chelation Therapy, Test of Adherence to Inhalers, and questionnaire by Voils. The MAR-Scale revised, MMAS-4, and MMAS-8 have been administered electronically. CONCLUSIONS: This study identified 121 PROMs for medication adherence and provided synthesized evidence for the measurement properties of these PROMs. The findings from this study may assist clinicians and researchers in selecting suitable PROMs to assess medication adherence.

Development of an Item Bank to Measure Medication Adherence: Systematic Review.

BACKGROUND: Medication adherence is important in managing the progression of chronic diseases. A promising approach to reduce cognitive burden when measuring medication adherence lies in the use of computer-adaptive tests (CATs) or in the development of shorter patient-reported outcome measures (PROMs). However, the lack of an item bank currently hampers this progress. OBJECTIVE: We aim to develop an item bank to measure general medication adherence. METHODS: Using the preferred reporting items for systematic review and meta-analysis (PRISMA), articles published before October 2019 were retrieved from PubMed, Embase, CINAHL, the Cochrane Library, and Web of Science. Items from existing PROMs were classified and selected ("binned" and "winnowed") according to standards published by the Patient-Reported Outcomes Measurement Information System (PROMIS) Cooperative Group. RESULTS: A total of 126 unique PROMs were identified from 213 studies in 48 countries. Items from the literature review (47 PROMs with 579 items for which permission has been obtained) underwent binning and winnowing. This resulted in 421 candidate items (77 extent of adherence and 344 reasons for adherence). CONCLUSIONS: We developed an item bank for measuring general medication adherence using items from validated PROMs. This will allow researchers to create new PROMs from selected items and provide the foundation to develop CATs.

Identifying optimal indicators and purposes of population segmentation through engagement of key stakeholders: a qualitative study.

BACKGROUND: Various population segmentation tools have been developed to inform the design of interventions that improve population health. However, there has been little consensus on the core indicators and purposes of population segmentation. The existing frameworks were further limited by their applicability in different practice settings involving stakeholders at all levels. The aim of this study was to generate a comprehensive set of indicators and purposes of population segmentation based on the experience and perspectives of key stakeholders involved in population health. METHODS: We conducted in-depth semi-structured interviews using purposive sampling with key stakeholders (e.g. government officials, healthcare professionals, social service providers, researchers) involved in population health at three distinct levels (micro, meso, macro) in Singapore. The interviews were audio-recorded and transcribed verbatim. Thematic content analysis was undertaken using NVivo 12. RESULTS: A total of 25 interviews were conducted. Eight core indicators (demographic characteristics, economic characteristics, behavioural characteristics, disease state, functional status, organisation of care, psychosocial factors and service needs of patients) and 21 sub-indicators were identified. Age and financial status were commonly stated as important indicators that could potentially be used for population segmentation across three levels of participants. Six intended purposes for population segmentation included improving health outcomes, planning for resource allocation, optimising healthcare utilisation, enhancing psychosocial and behavioural outcomes, strengthening preventive efforts and driving policy changes. There was consensus that planning for resource allocation and improving health outcomes were considered two of the most important purposes for population segmentation. CONCLUSIONS: Our findings shed light on the need for a more person-centric population segmentation framework that incorporates upstream and holistic indicators to be able to measure population health outcomes and to plan for appropriate resource allocation. Core elements of the framework may apply to other healthcare settings and systems responsible for improving population health. TRIAL REGISTRATION: The study was approved by the SingHealth Institutional Review Board (CIRB Reference number: 2017/2597).

Estimating Information Seeking-Behaviour of Public in Malaysia During COVID-19 by Using Google Trends.

The public was reported to be anxious and concerned during the pandemic. It is unknown whether these reactions had a relationship with the statistics of coronavirus disease 2019 (COVID-19) in Malaysia. We used Google Trends (GT) to understand whether the publics' inquisitiveness towards COVID-19 and its recommended precautionary measures had increased during the initial duration of the pandemic in Malaysia.

Factors associated with emergency room visits and hospitalisation amongst low-income public rental flat dwellers in Singapore.

BACKGROUND: In Singapore, a densely urbanised Asian society, more than 80% of the population stays in public housing estates and the majority (90%) own their own homes. For the needy who cannot afford home ownership, public rental flats are available. Staying in a public rental flat is associated with higher hospital readmission rates and poorer access to health services. We sought to examine sociodemographic factors associated with hospital admissions and emergency room visits amongst public rental flat residents. METHODS: We surveyed all residents aged ≥60 years in a public rental housing precinct in central Singapore in 2016. Residents self-reported their number of emergency room visits, as well as hospitalisations, in the past 6 months. We obtained information on residents' sociodemographic characteristics, medical, functional and social status via standardised questionnaires. We used chi-square to identify associations between emergency room visits/hospitalisations and sociodemographic characteristics, on univariate analysis; and logistic regression for multivariate analysis. RESULTS: Of 1324 contactable residents, 928 participated in the survey, with a response rate of 70.1%. A total of 928 residents participated in our study, of which 59.5% were male (553/928) and 51.2% (476/928) were ≥ 70 years old. Around 9% (83/928) of residents had visited the emergency room in the last 6 months; while 10.5% (100/928) had been admitted to hospital in the past 6 months. On multivariable analysis, being religious (aOR = 0.43, 95%CI = 0.24-0.76) and having seen a primary care practitioner in the last 6 months (aOR = 0.46, 95%CI = 0.27-0.80) were independently associated with lower odds of emergency room visits, whereas loneliness (aOR = 1.96, 95%CI = 1.13-3.43), poorer coping (aOR = 1.72, 95%CI = 1.01-3.03) and better adherence (aOR = 2.23, 95%CI = 1.29-3.83) were independently associated with higher odds of emergency room visits. For hospitalisations, similarly poorer coping (aOR = 1.85, 95%CI = 1.12-3.07), better adherence (aOR = 1.69, 95%CI = 1.04-2.75) and poorer functional status (aOR = 1.85, 95%CI = 1.15-2.98) were all independently associated with higher odds of hospitalisations, whereas those who were religious (aOR = 0.62, 95%CI = 0.37-0.99) and those who were currently employed (aOR = 0.46, 95%CI = 0.37-0.99) had lower odds of being hospitalised. CONCLUSION: In this public rental flat population, functional status, coping and adherence, and having a religion were independently associated with emergency room visits and hospitalisation. Residents who had seen a primary care practitioner in the last 6 months had lower odds of visiting the emergency room.

The heterogeneous health state profiles of high-risk healthcare utilizers and their longitudinal hospital readmission and mortality patterns.

BACKGROUND: High-risk patients are most vulnerable during transitions of care. Due to the high burden of resource allocation for such patients, we propose that segmentation of this heterogeneous population into distinct subgroups will enable improved healthcare resource planning. In this study, we segmented a high-risk population with the aim to identify and characterize a patient subgroup with the highest 30-day and 90-day hospital readmission and mortality. METHODS: We extracted data from our transitional care program (TCP), a Hospital-to-Home program launched by the Singapore Ministry of Health, from June to November 2018. Latent class analysis (LCA) was used to determine the optimal number and characteristics of latent subgroups, assessed based on model fit and clinical interpretability. Regression analysis was performed to assess the association of class membership on 30- and 90-day all-cause readmission and mortality. RESULTS: Among 752 patients, a 3-class best fit model was selected: Class 1 "Frail, cognitively impaired and physically dependent", Class 2 "Pre-frail, but largely physically independent" and Class 3 "Physically independent". The 3 classes have distinct demographics, medical and socioeconomic characteristics (p <  0.05), 30- and 90-day readmission (p <  0.05) and mortality (p <  0.01). Class 1 patients have the highest age-adjusted 90-day readmission (OR = 2.04, 95%CI: 1.21-3.46, p = 0.008), 30- (OR = 6.92, 95%CI: 1.76-27.21, p = 0.006) and 90-day mortality (OR = 11.51, 95%CI: 4.57-29.02, p <  0.001). CONCLUSIONS: We identified a subgroup with the highest readmission and mortality risk amongst high-risk patients. We also found a lack of interventions in our TCP that specifically addresses increased frailty and poor cognition, which are prominent features in this subgroup. These findings will help to inform future program modifications and strengthen existing transitional healthcare structures currently utilized in this patient cohort.

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.

Outpatient primary and tertiary healthcare utilisation among public rental housing residents in Singapore.

BACKGROUND: Globally, public housing is utilized to provide affordable housing for low-income households. Studies have shown an association between public housing and negative health outcomes. There is paucity of data pertaining to outpatient primary and tertiary healthcare resources utilization among public rental housing residents in Singapore. METHODS: A retrospective cohort study was performed, involving patients under the care of SingHealth Regional Health System (SHRS) in Year 2012. Healthcare utilization outcomes evaluated included number of outpatient primary and specialist care clinic visits, emergency department visits and hospitalization in Year 2011. Multivariate logistical analyses were used to examine the association between public rental housing and healthcare utilization. RESULTS: Of 147,105 patients, 10,400 (7.1%) patients stayed in public rental housing. There were more elderly (54.8 ± 18.0 vs 49.8 ± 17.1, p < 0.001) and male patients [5279 (50.8%) vs 56,892 (41.6%), p < 0.001] residing in public rental housing. Co-morbidities such as hypertension and hyperlipidemia were more prevalent among public rental housing patients. (p < 0.05). After adjustment for covariates, public rental housing was not associated with frequent outpatient primary care clinic or specialist outpatient clinic attendances (p > 0.05). However, it was associated with increased number of emergency department visits (OR: 2.41, 95% CI: 2.12-2.74) and frequent hospitalization (OR: 1.56, 95% CI: 1.33-1.83). CONCLUSION: Residing in public rental housing was not associated with increased utilization of outpatient healthcare resources despite patients' higher disease burden and frequency of emergency department visits and hospitalizations. Further research is required to elucidate their health seeking behaviours.

Identifying heterogeneous health profiles of primary care utilizers and their differential healthcare utilization and mortality - a retrospective cohort study.

BACKGROUND: Heterogeneity of population health needs and the resultant difficulty in health care resources planning are challenges faced by primary care systems globally. To address this challenge in population health management, it is critical to have a better understanding of primary care utilizers' heterogeneous health profiles. We aimed to segment a population of primary care utilizers into classes with unique disease patterns, and to report the 1 year follow up healthcare utilizations and all-cause mortality across the classes. METHODS: Using de-identified administrative data, we included all adult Singapore citizens or permanent residents who utilized Singapore Health Services (SingHealth) primary care services in 2012. Latent class analysis was used to identify patient subgroups having unique disease patterns in the population. The models were assessed by Bayesian Information Criterion and clinical interpretability. We compared healthcare utilizations in 2013 and one-year all-cause mortality across classes and performed regression analysis to assess predictive ability of class membership on healthcare utilizations and mortality. RESULTS: We included 100,747 patients in total. The best model (k = 6) revealed the following classes of patients: Class 1 "Relatively healthy" (n = 58,213), Class 2 "Stable metabolic disease" (n = 26,309), Class 3 "Metabolic disease with vascular complications" (n = 2964), Class 4 "High respiratory disease burden" (n = 1104), Class 5 "High metabolic disease without complication" (n = 11,122), and Class 6 "Metabolic disease with multi-organ complication" (n = 1035). The six derived classes had different disease patterns in 2012 and 1 year follow up healthcare utilizations and mortality in 2013. "Metabolic disease with multiple organ complications" class had the highest healthcare utilization (e.g. incidence rate ratio = 19.68 for hospital admissions) and highest one-year all-cause mortality (hazard ratio = 27.97). CONCLUSIONS: Primary care utilizers are heterogeneous and can be segmented by latent class analysis into classes with unique disease patterns, healthcare utilizations and all-cause mortality. This information is critical to population level health resource planning and population health policy formulation.