Incorporating Longitudinal Comorbidity and Acute Physiology Data in Template Matching for Assessing Hospital Quality

OBJECTIVE: We sought to build on the template-matching methodology by incorporating longitudinal comorbidities and acute physiology to audit hospital quality. STUDY SETTING: Patients admitted for sepsis and pneumonia, congestive heart failure, hip fracture, and cancer between January 2010 and November 2011 at 18 Kaiser Permanente Northern California hospitals. STUDY DESIGN: We generated a representative template of 250 patients in 4 diagnosis groups. We then matched between 1 and 5 patients at each hospital to this template using varying levels of patient information. DATA COLLECTION: Data were collected retrospectively from inpatient and outpatient electronic records. PRINCIPAL FINDINGS: Matching on both present-on-admission comorbidity history and physiological data significantly reduced the variation across hospitals in patient severity of illness levels compared with matching on administrative data only. After adjustment for longitudinal comorbidity and acute physiology, hospital rankings on 30-day mortality and estimates of length of stay were statistically different from rankings based on administrative data. CONCLUSIONS: Template matching-based approaches to hospital quality assessment can be enhanced using more granular electronic medical record data

Audit · Comorbidity · Intensive care medicine · Longitudinal study · Matching (statistics) · Medical record · MEDLINE · Pathology · Chronic Disease Management Strategies · Emergency Medicine · Internal Medicine · Medical Coding and Health Information · Medicine · Sepsis Diagnosis and Treatment

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  William Kruskal, William H Kruskal et al.•Journal of the American…•1952

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  Harvey Goldstein, David J Spiegelhalter•Journal of the Royal Statistical…•1996

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  ELIZABETH A MCGLYNN, Steven M Asch et al.•New England Journal of Medicine•2003

  Añadir item

• Constructing a Control Group Using Multivariate Matched Sampling Methods That Incorporate the Propensity Score

  Paul R Rosenbaum, Donald B Rubin•The American Statistician•1985

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• Judging hospitals by severity-adjusted mortality rates

  Lisa I Iezzoni, Arlene S Ash et al.•American Journal of Public Health•1996

  Añadir item

• Impact of Changing the Statistical Methodology on Hospital and Surgeon Ranking

  Laurent G Glance, Andrew W Dick et al.•Medical Care•2006

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• Risk-adjusting Hospital Mortality Using a Comprehensive Electronic Record in an Integrated Health Care Delivery System

  Gabriel J Escobar, Marla N Gardner et al.•Medical Care•2013

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• Length of Stay Predictions

  Vincent Liu, Patricia Kipnis et al.•Medical Care•2010

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• How Accurate are Hospital Discharge Data for Evaluating Effectiveness of Care

  Jesse Green, 寿一 木村 et al.•Medical Care•1993

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  Hude Quan, Gerry A Parsons et al.•Medical Care•2002

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