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Incorporating the Present-on-Admission Indicator to Predict In-hospital Mortality Through Elixhauser Measures

A Medicare Data Analysis

Dados Bibliográficos

ID9103845
AutoresJianfang Liu (0000-0002-9235-3166, Columbia University School of Nursing, New York, NY, autor correspondente), Ani Bilazarian (0000-0002-7095-5369, McKinsey and Company Inc., New York, NY), Madeline M Pollifrone (0000-0001-8342-2003, Columbia University School of Nursing, New York, NY, autor correspondente), Sunmoo Yoon (0000-0001-9413-8980, Columbia University Irving Medical Center, New York, NY), Rachel Siegel (0009-0007-1839-0085, Columbia University School of Nursing, New York, NY, autor correspondente), Lusine Poghosyan (0000-0002-0529-8171, Stone Foundation and Elise D. Fish Professor of Nursing, Columbia University School of Nursing and Professor of Health Policy and Management, Mailman School of Public Health, Columbia University, Executive Director, Center for Healthcare Delivery Research and Innovations (HDRI), New York, NY)
Ano2025
Volume63
Fascículo12
Páginas929-935
Data de publicação2025-12-01
Peer ReviewedSim
Open AccessNão
TipoARTICLE
PeriódicoMedical Care (JOURNAL)
Identificadores do periódicoISSN: 0025-7079 • E-ISSN: 1537-1948
EditoraOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/mlr.0000000000002192
PMID40846637
OpenAlexW4413441217
IdiomaEN
Referências citadas16

BACKGROUND: In 2021, the Agency for Health Care Research and Quality (AHRQ) updated its guidelines for using the Present-on-Admission (POA) indicator in the Elixhauser comorbidity index. This update helps distinguish pre-existing comorbidities from complications that arise after hospital admission, improving the validity of hospital performance assessments and more accurately measuring patients' severity of illness upon admission. OBJECTIVE: To evaluate differences in comorbidity prevalence and the predictive performance of the Elixhauser Comorbidity Index for in-hospital mortality at admission under 3 comorbidity coding guidelines, including one that ignores the POA indicator. RESEARCH DESIGN: A retrospective analysis of inpatient administrative data on Medicare beneficiaries. SUBJECTS: The dataset included 1,810,106 adult Medicare inpatient admissions across 6 U.S. states between 2017 and 2019. METHODS: Elastic net models were applied to predict in-hospital mortality using 3 approaches to coding comorbidities: (1) No-POA (including all conditions as admission comorbidities), (2) Full-POA (including only POA conditions as comorbidities), and (3) the 2021 AHRQ Partial-POA (applying POA to a subset of conditions to code comorbidities). Results: C-statistics were 0.800 (0.797-0.804), 0.768 (0.763-0.771), and 0.786 (0.781-0.790) for No-POA, full-POA, and 2021 AHRQ partial-POA guidelines, respectively. CONCLUSION: Ignoring the POA inflated model performance by misclassifying complications as admission comorbidities. The 2021 Partial-POA guidelines achieved intermediate C-statistics while ensuring internal validity by accurately measuring illness severity at admission. This supports improved hospital evaluations, care quality, resource allocation, tailored intervention, and reimbursement. The elastic net model shows promise as a standard for predicting in-hospital mortality with the Elixhauser comorbidity measure

Statistics · Chronic Disease Management Strategies · Emergency Medicine · Mathematics · Medicine · Primary Care and Health Outcomes · Sepsis Diagnosis and Treatment

  • Regularization and Variable Selection Via the Elastic Net

    Open Access•Hui Zou, Trevor Hastie•Journal of the Royal Statistical…•2005

  • Cross-Validatory Choice and Assessment of Statistical Predictions

    Open Access•M Stone•Journal of the Royal Statistical…•1974

  • Coding Algorithms for Defining Comorbidities in ICD-9-CM and ICD-10 Administrative Data

    Hude Quan, Vijaya Sundararajan et al.•Medical Care•2005

  • Comorbidity Measures for Use with Administrative Data

    Anne Elixhauser, Claudia Steiner et al.•Medical Care•1998

  • Comparison of the Elixhauser and Charlson/Deyo Methods of Comorbidity Measurement in Administrative Data

    Danielle A Southern, Hude Quan et al.•Medical Care•2004

  • A Modification of the Elixhauser Comorbidity Measures Into a Point System for Hospital Death Using Administrative Data

    Carl van Walraven, Peter C Austin et al.•Medical Care•2009

  • A New Elixhauser-based Comorbidity Summary Measure to Predict In-Hospital Mortality

    Nicolas R Thompson, Youran Fan et al.•Medical Care•2015

Velocidade de citaçãohistorical
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