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Incorporating Present-on-Admission Indicators in Medicare Claims to Inform Hospital Quality Measure Risk Adjustment Models.
Triche, Elizabeth W; Xin, Xin; Stackland, Sydnie; Purvis, Danielle; Harris, Alexandra; Yu, Huihui; Grady, Jacqueline N; Li, Shu-Xia; Bernheim, Susannah M; Krumholz, Harlan M; Poyer, James; Dorsey, Karen.
Afiliación
  • Triche EW; Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, Connecticut.
  • Xin X; Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, Connecticut.
  • Stackland S; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.
  • Purvis D; Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, Connecticut.
  • Harris A; Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, Connecticut.
  • Yu H; Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, Connecticut.
  • Grady JN; Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, Connecticut.
  • Li SX; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.
  • Bernheim SM; Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, Connecticut.
  • Krumholz HM; Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, Connecticut.
  • Poyer J; Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, Connecticut.
  • Dorsey K; Section of General Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.
JAMA Netw Open ; 4(5): e218512, 2021 05 03.
Article en En | MEDLINE | ID: mdl-33978722
ABSTRACT
Importance Present-on-admission (POA) indicators in administrative claims data allow researchers to distinguish between preexisting conditions and those acquired during a hospital stay. The impact of adding POA information to claims-based measures of hospital quality has not yet been investigated to better understand patient underlying risk factors in the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision setting.

Objective:

To assess POA indicator use on Medicare claims and to assess the hospital- and patient-level outcomes associated with incorporating POA indicators in identifying risk factors for publicly reported outcome measures used by the Centers for Medicare & Medicaid Services (CMS). Design, Setting, and

Participants:

This comparative effectiveness study used national CMS claims data between July 1, 2015, and June 30, 2018. Six hospital quality measures assessing readmission and mortality outcomes were modified to include POA indicators in risk adjustment models. The models using POA were then compared with models using the existing complications-of-care algorithm to evaluate changes in risk model performance. Patient claims data were included for all Medicare fee-for-service and Veterans Administration beneficiaries aged 65 years or older with inpatient hospitalizations for acute myocardial infarction, heart failure, or pneumonia within the measurement period. Data were analyzed between September 2019 and March 2020. Main Outcomes and

Measures:

Changes in patient-level (C statistics) and hospital-level (quintile shifts in risk-standardized outcome rates) model performance after including POA indicators in risk adjustment.

Results:

Data from a total of 6 027 988 index admissions were included for analysis, ranging from 491 366 admissions (269 209 [54.8%] men; mean [SD] age, 78.2 [8.3] years) for the acute myocardial infarction mortality outcome measure to 1 395 870 admissions (677 158 [48.5%] men; mean [SD] age, 80.3 [8.7] years) for the pneumonia readmission measure. Use of POA indicators was associated with improvements in risk adjustment model performance, particularly for mortality measures (eg, the C statistic increased from 0.728 [95% CI, 0.726-0.730] to 0.774 [95% CI, 0.773-0.776] when incorporating POA indicators into the acute myocardial infarction mortality measure). Conclusions and Relevance The findings of this quality improvement study suggest that leveraging POA indicators in the risk adjustment methodology for hospital quality outcome measures may help to more fully capture patients' risk factors and improve overall model performance. Incorporating POA indicators does not require extra effort on the part of hospitals and would be easy to implement in publicly reported quality outcome measures.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Readmisión del Paciente / Medicare / Benchmarking / Indicadores de Calidad de la Atención de Salud / Hospitales Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Aged80 / Female / Humans / Male País/Región como asunto: America do norte Idioma: En Revista: JAMA Netw Open Año: 2021 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Readmisión del Paciente / Medicare / Benchmarking / Indicadores de Calidad de la Atención de Salud / Hospitales Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Aged80 / Female / Humans / Male País/Región como asunto: America do norte Idioma: En Revista: JAMA Netw Open Año: 2021 Tipo del documento: Article