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

Overview of attention for article published in BMC Health Services Research, November 2017
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Title
Evaluation of a practical expert defined approach to patient population segmentation: a case study in Singapore
Published in
BMC Health Services Research, November 2017
DOI 10.1186/s12913-017-2736-8
Pubmed ID
Authors

Lian Leng Low, Yu Heng Kwan, Nan Liu, Xuan Jing, Edwin Cheng Tee Low, Julian Thumboo

Abstract

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. 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. 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%). 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.

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Mendeley readers

The data shown below were compiled from readership statistics for 87 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 87 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 15%
Student > Bachelor 11 13%
Student > Ph. D. Student 10 11%
Student > Master 8 9%
Student > Doctoral Student 6 7%
Other 13 15%
Unknown 26 30%
Readers by discipline Count As %
Medicine and Dentistry 20 23%
Nursing and Health Professions 12 14%
Biochemistry, Genetics and Molecular Biology 4 5%
Social Sciences 4 5%
Business, Management and Accounting 3 3%
Other 14 16%
Unknown 30 34%