Navigating a ship with a broken compass: evaluating standard algorithms to measure patient safety.

Objective: Agency for Healthcare Research and Quality (AHRQ) software applies standardized algorithms to hospital administrative data to identify patient safety indicators (PSIs). The objective of this study was to assess the validity of PSI flags and report reasons for invalid flagging.Material and...

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Publicado en:Journal of the American Medical Informatics Association Vol. 24; no. 2; pp. 310 - 316
Autores principales: Hefner, Jennifer L., Huerta, Timothy R., McAlearney, Ann Scheck, Barash, Barbara, Latimer, Tina, Moffatt-Bruce, Susan D.
Formato: research Journal Article
Publicado: Oxford University Press / USA Mar2017
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Mar2017
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      pub: Oxford University Press / USA
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        atl: Navigating a ship with a broken compass: evaluating standard algorithms to measure patient safety.
      aug:
        au:
          Hefner, Jennifer L.
          Huerta, Timothy R.
          McAlearney, Ann Scheck
          Barash, Barbara
          Latimer, Tina
          Moffatt-Bruce, Susan D.
        affil: Department of Family Medicine, College of Medicine, The Ohio State University, Columbus, Ohio, USA
      sug:
        subj:
          Algorithms
          Clinical Indicators
          Patient Safety
          Treatment Errors
          United States Agency for Healthcare Research and Quality
          Academic Medical Centers
          Retrospective Design
          Software
          Safety
          United States
          Human
          Validation Studies
          Comparative Studies
          Evaluation Research
          Multicenter Studies
      ab: Objective: Agency for Healthcare Research and Quality (AHRQ) software applies standardized algorithms to hospital administrative data to identify patient safety indicators (PSIs). The objective of this study was to assess the validity of PSI flags and report reasons for invalid flagging.Material and Methods: At a 6-hospital academic medical center, a retrospective analysis was conducted of all PSIs flagged in fiscal year 2014. A multidisciplinary PSI Quality Team reviewed each flagged PSI based on quarterly reports. The positive predictive value (PPV, the percent of clinically validated cases) was calculated for 12 PSI categories. The documentation for each reversed case was reviewed to determine the reasons for PSI reversal.Results: Of 657 PSI flags, 185 were reversed. Seven PSI categories had a PPV below 75%. Four broad categories of reasons for reversal were AHRQ algorithm limitations (38%), coding misinterpretations (45%), present upon admission (10%), and documentation insufficiency (7%). AHRQ algorithm limitations included 2 subcategories: an "incident" was inherent to the procedure, or highly likely (eg, vascular tumor bleed), or an "incident" was nonsignificant, easily controlled, and/or no intervention was needed.Discussion: These findings support previous research highlighting administrative data problems. Additionally, AHRQ algorithm limitations was an emergent category not considered in previous research. Herein we present potential solutions to address these issues.Conclusions: If, despite poor validity, US policy continues to rely on PSIs for incentive and penalty programs, improvements are needed in the quality of administrative data and the standardized PSI algorithms. These solutions require national motivation, research attention, and dissemination support.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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