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.

Association of Social Support with Rehabilitation Outcome among Older Adults with Hip Fracture Surgery: A Prospective Cohort Study at Post-Acute Care Facility in Asia.

OBJECTIVES: There is growing interest in the role of social support during the recovery after hip fractures. The research to date has been mainly focused on structural support, with few studies concerned with functional support. This study examined the effects of both functional and structural aspects of social support on rehabilitation outcomes among older adults with hip fracture surgery. DESIGN: Prospective cohort study. SETTING AND PARTICIPANTS: Consecutive older adults (≥60 years) with hip fracture surgery who underwent inpatient rehabilitation in a post-acute care facility in Singapore between January 11, 2021, and October 30, 2021 (n = 112). METHODS: We administered the Medical Outcome Study-Social Support Survey (MOS-SSS) to assess perceived functional support of patients and used living arrangement as an indicator for structural support. Participants were followed up over the inpatient stay at the post-acute care facility until discharge; thereafter, rehabilitation efficiency (REy) and rehabilitation effectiveness (REs) were evaluated. Multiple linear regressions were performed to examine the associations of MOS-SSS score and living arrangement with REy and REs, respectively, adjusting for age, gender, ethnicity, comorbidity, body mass index, prefracture function, type of fracture, and length of stay. RESULTS: Perceived functional support had positive associations with rehabilitation outcomes. A 1-unit increase in MOS-SSS total score was associated with 0.15 units (95% CI 0.03-0.3, P = .029) greater gain in physical function after a typical 1-month stay, and 0.21 units (95% CI 0.01-0.41, P = .040) higher achievement in potential functional improvement upon discharge. In contrast, no association was observed between structural support and rehabilitation outcomes. CONCLUSIONS AND IMPLICATIONS: Perceived functional support may significantly impact the recovery of older adults with hip fracture during the inpatient rehabilitation process, independent of structural support. Our findings suggest the potential of incorporating interventions enhancing perceived functional support of patients into the post-acute care model for hip fracture.

Factors influencing medication adherence in multi-ethnic Asian patients with chronic diseases in Singapore: A qualitative study.

Background: Poor medication adherence can lead to adverse health outcomes and increased healthcare costs. Although reasons for medication adherence have been widely studied, less is explored about factors affecting medication adherence for patients in non-Western healthcare setting and from Asian cultures. This study aimed to explore cultural perspectives on factors influencing medication adherence among patients with chronic diseases in a multi-ethnic Asian healthcare setting. Methods: We conducted a qualitative study involving in-depth interviews with patients with chronic conditions purposively recruited from a community hospital in Singapore until data saturation was achieved. A total of 25 patients participated in this study. Interviews were transcribed and thematically analyzed. Themes were subsequently mapped into the World Health Organization (WHO) Framework of Medication Adherence. Results: Participants commonly perceived that sides effects (therapy-related dimension), poor understanding of medication (patient-related dimension), limited knowledge of condition (patient-related dimension), forgetfulness (patient-related dimension) and language issues within a multi-ethnic healthcare context (healthcare team and system-related dimension) as the main factors contributing to medication adherence. Importantly, medication adherence was influenced by cultural beliefs such as the notion of modern medicines as harms and fatalistic orientations towards escalation of doses and polypharmacy (patient-related dimension). Participants made various suggestions to foster adherence, including improved patient-physician communication, enhanced care coordination across providers, use of language familiar to patients, patient education and empowerment on the benefits of medication and medication adjustment. Conclusion: A wide range of factors influenced medication adherence, with therapy- and patient-related dimensions more pronounced compared to other dimensions. Findings demonstrated the importance of cultural beliefs that may influence medication adherence. Future efforts to improve medication adherence should consider a person-centered approach to foster more positive health expectations and self-efficacy on medication adherence, supplemented with routine reviews, development of pictograms and cultural competence training for healthcare professionals.

Implementing a community-based shared care breast cancer survivorship model in Singapore: a qualitative study among primary care practitioners.

BACKGROUND: The adaptability of existing recommendations on shared care implementation to Asian settings is unknown. This qualitative study aims to elicit public- and private-sectors primary care practitioners' (PCPs) perspectives on the sustainable implementation of a shared care model among breast cancer survivors in Singapore. METHODS: Purposive sampling was employed to engage 70 PCPs from SingHealth Polyclinics, National University Polyclinics, National Healthcare Group Polyclinics, and private practice. Eleven focus groups and six in-depth interviews were conducted between June to November 2018. All sessions were audio-recorded and transcribed verbatim. Guided by the RE-AIM framework, we performed deductive thematic analysis in QSR NVivo 12. RESULTS: PCPs identified low-risk breast cancer survivors who demonstrated clear acceptability of PCPs' involvement in follow-up as suitable candidates for shared care. Engagement with institution stakeholders as early adopters is crucial with adequate support through PCP training, return pathways to oncologists, and survivorship care plans as communication tools. Implementation considerations differed across practices. Selection of participating PCPs could consider seniority and interest for public and private practice, respectively. Proposed adoption incentives included increased renumeration for private PCPs and work recognition for public PCPs. Public PCPs further proposed integrating shared care elements to their existing family medicine clinics. CONCLUSIONS: PCPs perceived shared care favorably as it echoed principles of primary care to provide holistic and well-coordinated care. Contextual factors should be considered when adapting implementation recommendations to Asian settings like Singapore. With limited competitive pressure, the government is then pivotal in empowering primary care participation in survivorship shared care delivery.

Development and validation of an interpretable machine learning scoring tool for estimating time to emergency readmissions.

Background: Emergency readmission poses an additional burden on both patients and healthcare systems. Risk stratification is the first step of transitional care interventions targeted at reducing readmission. To accurately predict the short- and intermediate-term risks of readmission and provide information for further temporal risk stratification, we developed and validated an interpretable machine learning risk scoring system. Methods: In this retrospective study, all emergency admission episodes from January 1st 2009 to December 31st 2016 at a tertiary hospital in Singapore were assessed. The primary outcome was time to emergency readmission within 90 days post discharge. The Score for Emergency ReAdmission Prediction (SERAP) tool was derived via an interpretable machine learning-based system for time-to-event outcomes. SERAP is six-variable survival score, and takes the number of emergency admissions last year, age, history of malignancy, history of renal diseases, serum creatinine level, and serum albumin level during index admission into consideration. Findings: A total of 293,589 ED admission episodes were finally included in the whole cohort. Among them, 203,748 episodes were included in the training cohort, 50,937 episodes in the validation cohort, and 38,904 in the testing cohort. Readmission within 90 days was documented in 80,213 (27.3%) episodes, with a median time to emergency readmission of 22 days (Interquartile range: 8-47). For different time points, the readmission rates observed in the whole cohort were 6.7% at 7 days, 10.6% at 14 days, 13.6% at 21 days, 16.4% at 30 days, and 23.0% at 60 days. In the testing cohort, the SERAP achieved an integrated area under the curve of 0.737 (95% confidence interval: 0.730-0.743). For a specific 30-day readmission prediction, SERAP outperformed the LACE index (Length of stay, Acuity of admission, Charlson comorbidity index, and Emergency department visits in past six months) and the HOSPITAL score (Hemoglobin at discharge, discharge from an Oncology service, Sodium level at discharge, Procedure during the index admission, Index Type of admission, number of Admissions during the last 12 months, and Length of stay). Besides 30-day readmission, SERAP can predict readmission rates at any time point during the 90-day period. Interpretation: Better performance in risk prediction was achieved by the SERAP than other existing scores, and accurate information about time to emergency readmission was generated for further temporal risk stratification and clinical decision-making. In the future, external validation studies are needed to evaluate the SERAP at different settings and assess their real-world performance. Funding: This study was supported by the Singapore National Medical Research Council under the PULSES Center Grant, and Duke-NUS Medical School.

Risk of malignancies in patients with spondyloarthritis treated with biologics compared with those treated with non-biologics: a systematic review and meta-analysis.

BACKGROUND: The aim of our study was to synthesize evidence on the occurrence of malignancy in spondyloarthritis (SpA), from randomized controlled trials (RCTs) comparing biologics with non-biologics and biologics to each other. METHODS: We systematically searched Medline, Cochrane Library, EMBASE, Scopus and ClinicalTrials.gov from inception until 31 October 2018. RCTs with ⩾24-week follow-up were included. We extracted data using standardized forms and assessed the risk of bias using the Cochrane Risk of Bias Tool. We performed pair-wise meta-analyses and network meta-analyses to compare the risk of malignancy for each biologics class and SpA type. We reported the Peto odds ratio (OR) of any malignancy along with 95% confidence intervals (95% CI). Bayesian posterior probabilities comparing risk of malignancy of each biologic class with non-biologics were computed as supplementary measures. RESULTS: Fifty-four trials were included; most (44/54) had follow-up <1 year. Among 14,245 patients, 63 developed a malignancy. While most Peto ORs were >1, they had wide 95% CI and p >0.05. The overall Peto OR comparing biologics with non-biologics was 1.42 (95% CI 0.80-2.53). Only interleukin-17 inhibitors in peripheral SpA had p <0.05 (Peto OR 2.77, 95% CI 1.07-7.13); the posterior probability that the risk was higher than non-biologics was 98%. Stratified analyses revealed no consistent trend by prior exposure to biologics, duration of follow-up, study quality, study-arm crossover, analytical approaches and type of malignancy. CONCLUSIONS: Our findings indicate no overall elevated risk of malignancy with biologics in SpA. As our meta-analyses are unable to conclude on the long-term risk, long-term pharmacovigilance of biologics in SpA may still be warranted.

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.

Characteristics and Health Care Utilization of Different Segments of a Multiethnic Asian Population in Singapore.

Importance: Descriptive population-level health data are critical components of the evidence base for population health policy. Human populations often display marked heterogeneity in their health status among subgroups of the population. The recent widespread adoption of electronic health records provides opportunities to use routine real-world health care data to examine population health. Objective: To report population sociodemographic characteristics, health conditions, health care utilization, and health care costs for different population segments of a multiethnic Asian population divided according to a modified British Columbia Population Segmentation Framework. Design, Setting, and Participants: This population-based cross-sectional study used 2016 data from the Singapore Eastern Regional Health System, the largest Regional Health System in Singapore. Data were obtained from deidentified national-level electronic health records at the Ministry of Health Singapore. Participants included all residents in the Singapore Eastern Regional Health System catchment area in 2016. The descriptive analysis was conducted in August 2018. Main Outcomes and Measures: Socioeconomic profiles, disease prevalence, health care utilization, and cost patterns of population segments. Results: The total size of the study population in 2016 was 1 181 024 residents (576 663 [48.83%] male; median [interquartile range] age, 40 [22-57] years). The population was divided into 8 segments: healthy with no outpatient utilization (493 483 residents), healthy with outpatient utilization (259 909 residents), healthy with inpatient admissions (49 588 residents), low complex (215 134 residents), medium complex (79 350 residents), high complex (44 445 residents), cancer (34 217 residents), and end of life (4898 residents). Overall, the 3 most prevalent conditions were chronic kidney disease (31.89%), hypertension (18.52%), and lipid disorders (18.33%). Distributions of chronic conditions differed across the segments. Different segments had varying health care utilization patterns: the high-complex segment had the highest number of primary care clinic visits (mean [SD], 4.25 [5.46] visits), the cancer segment had the highest number of specialist outpatient clinic visits (mean [SD], 5.55 [8.49] visits), and the end-of-life segment had the highest numbers of accident and emergency department visits (mean [SD], 1.80 [1.88] visits) and inpatient admissions (mean [SD], 1.99 [1.89] admissions) during 2016. For health care costs, specialist outpatient clinic and inpatient care together made up more than 85% of the total cost of nearly 2 billion Singapore dollars. The end-of-life segment contributed approximately 50% of the health care cost per capita of 60 000 Singapore dollars. Conclusions and Relevance: Different population segments displayed heterogeneity in sociodemographic characteristics, health conditions, health care utilization, and health care cost patterns. This critical health information can be used as baseline data to inform regional and national health priorities for health services research and policy.

A systematic review of the clinical application of data-driven population segmentation analysis.

BACKGROUND: Data-driven population segmentation analysis utilizes data analytics to divide a heterogeneous population into parsimonious and relatively homogenous groups with similar healthcare characteristics. It is a promising patient-centric analysis that enables effective integrated healthcare interventions specific for each segment. Although widely applied, there is no systematic review on the clinical application of data-driven population segmentation analysis. METHODS: We carried out a systematic literature search using PubMed, Embase and Web of Science following PRISMA criteria. We included English peer-reviewed articles that applied data-driven population segmentation analysis on empirical health data. We summarized the clinical settings in which segmentation analysis was applied, compared and contrasted strengths, limitations, and practical considerations of different segmentation methods, and assessed the segmentation outcome of all included studies. The studies were assessed by two independent reviewers. RESULTS: We retrieved 14,514 articles and included 216 articles. Data-driven population segmentation analysis was widely used in different clinical contexts. 163 studies examined the general population while 53 focused on specific population with certain diseases or conditions, including psychological, oncological, respiratory, cardiovascular, and gastrointestinal conditions. Variables used for segmentation in the studies are heterogeneous. Most studies (n = 170) utilized secondary data in community settings (n = 185). The most common segmentation method was latent class/profile/transition/growth analysis (n = 96) followed by K-means cluster analysis (n = 60) and hierarchical analysis (n = 50), each having its advantages, disadvantages, and practical considerations. We also identified key criteria to evaluate a segmentation framework: internal validity, external validity, identifiability/interpretability, substantiality, stability, actionability/accessibility, and parsimony. CONCLUSIONS: Data-driven population segmentation has been widely applied and holds great potential in managing population health. The evaluations of segmentation outcome require the interplay of data analytics and subject matter expertise. The optimal framework for segmentation requires further research.

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.

Measurement properties of patient reported outcome measures for spondyloarthritis: A systematic review.

OBJECTIVES: This systematic review aimed to identify studies investigating measurement properties of patient reported outcome measures (PROMs) for spondyloarthritis (SpA), and to evaluate their methodological quality and level of evidence relating to the measurement properties of PROMs. METHODS: This systematic review was guided by the preferred reporting items for systematic review and meta-analysis (PRISMA). Articles published before 30 June 2017 were retrieved from PubMed®, Embase®, and PsychINFO® (Ovid). Methodological quality and level of evidence were evaluated according to recommendations from the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN). RESULTS: We identified 60 unique PROMs from 125 studies in 39 countries. Twenty-one PROMs were validated for two or more SpA subtypes. The literature examined hypothesis testing (82.4%) most frequently followed by reliability (60.0%). A percentage of 77.7% and 42.7% of studies that assessed PROMs for hypothesis testing and reliability, respectively had "fair" or better methodological quality. Among the PROMs identified, 41.7% were studied in ankylosing spondylitis (AS) only and 23.3% were studied in psoriatic arthritis (PsA) only. The more extensively assessed PROMs included the ankylosing spondylitis quality of life (ASQoL) and bath ankylosing spondylitis functional index (BASFI) for ankylosing spondylitis, and the psoriatic arthritis quality of life questionnaire (VITACORA-19) for psoriatic arthritis. CONCLUSION: This study identified 60 unique PROMs through a systematic review and synthesized evidence of the measurement properties of the PROMs. There is a lack of validation of PROMs for use across SpA subtypes. Future studies may consider validating PROMs for use across different SpA subtypes.

Frequent hospital admissions in Singapore: clinical risk factors and impact of socioeconomic status.

INTRODUCTION: Frequent admitters to hospitals are high-cost patients who strain finite healthcare resources. However, the exact risk factors for frequent admissions, which can be used to guide risk stratification and design effective interventions locally, remain unknown. Our study aimed to identify the clinical and sociodemographic risk factors associated with frequent hospital admissions in Singapore. METHODS: An observational study was conducted using retrospective 2014 data from the administrative database at Singapore General Hospital, Singapore. Variables were identified a priori and included patient demographics, comorbidities, prior healthcare utilisation, and clinical and laboratory variables during the index admission. Multivariate logistic regression analysis was used to identify independent risk factors for frequent admissions. RESULTS: A total of 16,306 unique patients were analysed and 1,640 (10.1%) patients were classified as frequent admitters. On multivariate logistic regression, 16 variables were independently associated with frequent hospital admissions, including age, cerebrovascular disease, history of malignancy, haemoglobin, serum creatinine, serum albumin, and number of specialist outpatient clinic visits, emergency department visits, admissions preceding index admission and medications dispensed at discharge. Patients staying in public rental housing had a 30% higher risk of being a frequent admitter after adjusting for demographics and clinical conditions. CONCLUSION: Our study, the first in our knowledge to examine the clinical risk factors for frequent admissions in Singapore, validated the use of public rental housing as a sensitive indicator of area-level socioeconomic status in Singapore. These risk factors can be used to identify high-risk patients in the hospital so that they can receive interventions that reduce readmission risk.

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.