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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 pra...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5701430/ https://www.ncbi.nlm.nih.gov/pubmed/29169359 http://dx.doi.org/10.1186/s12913-017-2736-8 |
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author | Low, Lian Leng Kwan, Yu Heng Liu, Nan Jing, Xuan Low, Edwin Cheng Tee Thumboo, Julian |
author_facet | Low, Lian Leng Kwan, Yu Heng Liu, Nan Jing, Xuan Low, Edwin Cheng Tee Thumboo, Julian |
author_sort | Low, Lian Leng |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5701430 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-57014302017-12-04 Evaluation of a practical expert defined approach to patient population segmentation: a case study in Singapore Low, Lian Leng Kwan, Yu Heng Liu, Nan Jing, Xuan Low, Edwin Cheng Tee Thumboo, Julian BMC Health Serv Res Research Article 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. BioMed Central 2017-11-23 /pmc/articles/PMC5701430/ /pubmed/29169359 http://dx.doi.org/10.1186/s12913-017-2736-8 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Low, Lian Leng Kwan, Yu Heng Liu, Nan Jing, Xuan Low, Edwin Cheng Tee Thumboo, Julian Evaluation of a practical expert defined approach to patient population segmentation: a case study in Singapore |
title | Evaluation of a practical expert defined approach to patient population segmentation: a case study in Singapore |
title_full | Evaluation of a practical expert defined approach to patient population segmentation: a case study in Singapore |
title_fullStr | Evaluation of a practical expert defined approach to patient population segmentation: a case study in Singapore |
title_full_unstemmed | Evaluation of a practical expert defined approach to patient population segmentation: a case study in Singapore |
title_short | Evaluation of a practical expert defined approach to patient population segmentation: a case study in Singapore |
title_sort | evaluation of a practical expert defined approach to patient population segmentation: a case study in singapore |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5701430/ https://www.ncbi.nlm.nih.gov/pubmed/29169359 http://dx.doi.org/10.1186/s12913-017-2736-8 |
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