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Objectives <p>Population segmentation provides a promising solution to address patients’ complex needs to provide “whole person” care. The primary objective of this study is to create an expert-based algorithm based on combinations of medical and social characteristics derived from the Simple Segmentation Tool (SST), that are indicative of high value health and health-related social service (HASS) needs for an elderly population. The secondary objective was to examine the association between failing to meet the HASS needs 3-months post hospital discharge suggested by the algorithm and adverse outcomes over the ensuing year.</p> Design &amp; setting <p>Based on a parsimonious set of 10 patient characteristics identified in the SST, a representative expert panel was engaged using the Modified Appropriateness Methodology (MAM). A prospective study was then performed on patients admitted to the Singapore General Hospital, using HASS needs identified at discharge and met needs at 3&#xa0;months post-discharge follow-up of services received, to assess whether unmet needs were associated with higher adverse outcomes in the year following discharge. The primary outcome of interest was time to all-cause mortality over 12-months post-discharge and was assessed with Cox regression analysis.</p> Results <p>The MAM exercise resulted in 12 normatively defined high value services, using a combination of patients’ medical and social characteristics based on the SST, as well as a list of means of providing those service needs. The all-cause mortality hazard ratio of having at least one unmet need versus having all needs met for individuals deemed to be chronically symptomatic at discharge was 1.949, (95% CI: 0.99 – 3.84, and <i>p</i> = 0.05), while for those who were either healthy or only had asymptomatic chronic conditions the all-cause mortality ratio of having at least one unmet need versus having all needs met was 0.28 (95% CI = 0.06–1.27 and <i>p</i>-value = 0.10). The hazard ratio for ED visits and hospital readmission were above one but did not reach level of 95% confidence level.</p> Conclusion <p>The SST methodology provides a practical way to assess HASS needs that are predictive of mortality when needs are not met. It could serve as a screening tool to identify individuals who are likely to benefit from detailed care planning and follow-up.</p>

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Development and validation of a brief assessment of normative health and health-related social needs using the Simple Segmentation Tool

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月11日

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  • David Matchar,
  • Rakhi Vashishtha,
  • Xu Jing,
  • Nirmali Sivapragasam,
  • Rita Sim,
  • Jia Loon Chong

摘要

Objectives

Population segmentation provides a promising solution to address patients’ complex needs to provide “whole person” care. The primary objective of this study is to create an expert-based algorithm based on combinations of medical and social characteristics derived from the Simple Segmentation Tool (SST), that are indicative of high value health and health-related social service (HASS) needs for an elderly population. The secondary objective was to examine the association between failing to meet the HASS needs 3-months post hospital discharge suggested by the algorithm and adverse outcomes over the ensuing year.

Design & setting

Based on a parsimonious set of 10 patient characteristics identified in the SST, a representative expert panel was engaged using the Modified Appropriateness Methodology (MAM). A prospective study was then performed on patients admitted to the Singapore General Hospital, using HASS needs identified at discharge and met needs at 3 months post-discharge follow-up of services received, to assess whether unmet needs were associated with higher adverse outcomes in the year following discharge. The primary outcome of interest was time to all-cause mortality over 12-months post-discharge and was assessed with Cox regression analysis.

Results

The MAM exercise resulted in 12 normatively defined high value services, using a combination of patients’ medical and social characteristics based on the SST, as well as a list of means of providing those service needs. The all-cause mortality hazard ratio of having at least one unmet need versus having all needs met for individuals deemed to be chronically symptomatic at discharge was 1.949, (95% CI: 0.99 – 3.84, and p = 0.05), while for those who were either healthy or only had asymptomatic chronic conditions the all-cause mortality ratio of having at least one unmet need versus having all needs met was 0.28 (95% CI = 0.06–1.27 and p-value = 0.10). The hazard ratio for ED visits and hospital readmission were above one but did not reach level of 95% confidence level.

Conclusion

The SST methodology provides a practical way to assess HASS needs that are predictive of mortality when needs are not met. It could serve as a screening tool to identify individuals who are likely to benefit from detailed care planning and follow-up.