Improving uptake of population health management through scalable analysis of linked electronic health data

Andras B. Varady; Richard M. Wood

doi:10.1177/14604582241259344

Improving uptake of population health management through scalable analysis of linked electronic health data

Andras B. Varady, Richard M. Wood

National Health Service Research

Research output: Contribution to journal › Article › peer-review

Abstract

Population Health Management – often abbreviated to PHM – is a relatively new approach for healthcare planning, requiring the application of analytical techniques to linked patient level data. Despite expectations for greater uptake of PHM, there is a deficit of available solutions to help health services embed it into routine use. This paper concerns the development, application and use of an interactive tool which can be linked to a healthcare system’s data warehouse and employed to readily perform key PHM tasks such as population segmentation, risk stratification, and deriving various performance metrics and descriptive summaries. Developed through open-source code in a large healthcare system in South West England, and used by others around the country, this paper demonstrates the importance of a scalable, purpose-built solution for improving the uptake of PHM in health services.

Original language	English
Journal	Health Informatics Journal
Volume	30
Issue number	3
DOIs	https://doi.org/10.1177/14604582241259344
Publication status	Published - 1 Jul 2024
Externally published	Yes

Data Availability Statement

The tool can be found at https://github.com/nhs-bnssg-analytics/ExploreR, which also includes further guidance and synthetic data that can be used with the tool

Funding

The authors are grateful to Anna Powell for contributions to the design principles and dissemination activities. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported The Health Foundation [Advancing Applied Analytics programme].

Funders	Funder number
Health Foundation

Keywords

electronic health data
population health management
population segmentation
risk stratification

ASJC Scopus subject areas

Health Informatics

Access to Document

10.1177/14604582241259344Licence: CC BY-NC

Cite this

@article{d6efdc1acbd24309b3b84e1b5b5448b1,

title = "Improving uptake of population health management through scalable analysis of linked electronic health data",

abstract = "Population Health Management – often abbreviated to PHM – is a relatively new approach for healthcare planning, requiring the application of analytical techniques to linked patient level data. Despite expectations for greater uptake of PHM, there is a deficit of available solutions to help health services embed it into routine use. This paper concerns the development, application and use of an interactive tool which can be linked to a healthcare system{\textquoteright}s data warehouse and employed to readily perform key PHM tasks such as population segmentation, risk stratification, and deriving various performance metrics and descriptive summaries. Developed through open-source code in a large healthcare system in South West England, and used by others around the country, this paper demonstrates the importance of a scalable, purpose-built solution for improving the uptake of PHM in health services.",

keywords = "electronic health data, population health management, population segmentation, risk stratification",

author = "Varady, {Andras B.} and Wood, {Richard M.}",

year = "2024",

month = jul,

day = "1",

doi = "10.1177/14604582241259344",

language = "English",

volume = "30",

journal = "Health Informatics Journal",

issn = "1460-4582",

publisher = "SAGE Publications Ltd",

number = "3",

}

TY - JOUR

T1 - Improving uptake of population health management through scalable analysis of linked electronic health data

AU - Varady, Andras B.

AU - Wood, Richard M.

PY - 2024/7/1

Y1 - 2024/7/1

N2 - Population Health Management – often abbreviated to PHM – is a relatively new approach for healthcare planning, requiring the application of analytical techniques to linked patient level data. Despite expectations for greater uptake of PHM, there is a deficit of available solutions to help health services embed it into routine use. This paper concerns the development, application and use of an interactive tool which can be linked to a healthcare system’s data warehouse and employed to readily perform key PHM tasks such as population segmentation, risk stratification, and deriving various performance metrics and descriptive summaries. Developed through open-source code in a large healthcare system in South West England, and used by others around the country, this paper demonstrates the importance of a scalable, purpose-built solution for improving the uptake of PHM in health services.

AB - Population Health Management – often abbreviated to PHM – is a relatively new approach for healthcare planning, requiring the application of analytical techniques to linked patient level data. Despite expectations for greater uptake of PHM, there is a deficit of available solutions to help health services embed it into routine use. This paper concerns the development, application and use of an interactive tool which can be linked to a healthcare system’s data warehouse and employed to readily perform key PHM tasks such as population segmentation, risk stratification, and deriving various performance metrics and descriptive summaries. Developed through open-source code in a large healthcare system in South West England, and used by others around the country, this paper demonstrates the importance of a scalable, purpose-built solution for improving the uptake of PHM in health services.

KW - electronic health data

KW - population health management

KW - population segmentation

KW - risk stratification

UR - http://www.scopus.com/inward/record.url?scp=85200207463&partnerID=8YFLogxK

U2 - 10.1177/14604582241259344

DO - 10.1177/14604582241259344

M3 - Article

C2 - 39095387

AN - SCOPUS:85200207463

SN - 1460-4582

VL - 30

JO - Health Informatics Journal

JF - Health Informatics Journal

IS - 3

ER -

Improving uptake of population health management through scalable analysis of linked electronic health data

Abstract

Data Availability Statement

Funding

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this