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December 12, 2025BMC Health Services ResearchOpen Access

Multimorbidity measurement strategies for predicting hospital visits

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Why the study?

While multiple methods exist to measure multimorbidity from electronic health records, their relative performance for predicting hospital utilization remains unclear.

Does multimorbidity measurement using different phenotyping strategies and indices improve the prediction of hospital visits in adult patients?

Population

925,508 patients from a Portuguese hospital

Comparison

Three phenotyping strategies and five multimorbidity indices

Design

Retrospective cohort study

Follow-up

30-365 days

Authors

BNBernardo NevesSGSimão GonçalvesJCJorge Cerejo

Discussion

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Member takes

Overview

Multi-source phenotyping and multimorbidity indices consistently improve the prediction of hospital utilization beyond basic demographics and prior healthcare use.

Structured PICO

Does multimorbidity measurement using different phenotyping strategies and indices improve the prediction of hospital visits in adult patients?

P
Population
925,508 adult patients (aged 18 or older) with at least one visit to a Portuguese hospital (Hospital da Luz Lisboa) between 2007 and 2022, mean age 49.3, 61.4% female.
I
Intervention
Multimorbidity measurement using three phenotyping strategies (multi-source rule-based dictionary, CCSR mapping, drug-based mapping) and five indices (Charlson Comorbidity Index, Elixhauser, Multimorbidity Weighted Index, RxRisk, disease counts) combined with demographics and healthcare utilization features.
C
Comparator
Demographics only, or different combinations of phenotyping methods and comorbidity indices.
O
Outcome
Emergency department (ED) visits, hospital admissions, unplanned admissions, and readmissions over 30, 90, 180, and 365 days.

Multi-source phenotyping and multimorbidity indices consistently improve the prediction of hospital utilization beyond basic demographics and prior healthcare use.

Cite This Study

Neves et al. (2025) studied this question.

synapsesocial.com/papers/6a834fc39afa9c8d94b484a6https://doi.org/10.1186/s12913-025-13817-z
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Also Consider

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  1. 1Comparison of count-based multimorbidity measures in predicting emergency admission and functional decline in older community-dwelling adults: a prospective cohort study2016 · 49 citations
  2. 2Best Definitions of Multimorbidity to Identify Patients With High Health Care Resource Utilization2020 · 38 citations
  3. 3Multimorbidity network patterns improve the explanation of inpatient outcomes beyond conventional comorbidity assessment: a retrospective cohort study across 32 tertiary hospitals2026
  4. 4Measuring multimorbidity in hospitalised patients using linked hospital episode data: comparison of two measures2019 · 14 citations
  5. 5Prevention of Unplanned Hospital Admissions in Multimorbid Patients Using Computational Modeling: Observational Retrospective Cohort Study2023 · 21 citations