Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Deriving ICD-10 Codes for Patient Safety Indicators for Large-scale Surveillance Using Administrative Hospital Data

Bibliographic Data

ID9099775
AuthorsDanielle A Southern (0000-0002-0006-0033, University of Calgary, corresponding author), Bernard Burnand (0000-0002-5678-6044, University Hospital of Lausanne), Saskia E Droesler (Faculty of Health Care, Niederrhein University of Applied Sciences, Krefeld, Germany), Ward Flemons (University of Calgary), Alan J Forster (0000-0003-2942-2891, University of Ottawa), Yana Gurevich (Canadian Institute of Health Information, ON, Canada), James Harrison (0000-0001-9893-8491, Flinders University, Adelaide, SA, Australia), Hude Quan (0000-0002-7848-7256, University of Calgary, corresponding author), Harold Alan Pincus (RAND Corporation, corresponding author), Patrick S Romano (0000-0001-6749-3979, Division of General Medicine, University of California–Davis School of Medicine, Sacramento, CA), Vijaya Sundararajan (0000-0001-9387-1865, The University of Melbourne), Nenad Kostanjsek (World Health Organization, Classifications, Terminology and Standards, Geneva, Switzerland), William A Ghali (University of Calgary, corresponding author)
Year2017
Volume55
Issue3
Pages252-260
Publication date2017-03-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueMedical Care (JOURNAL)
Journal identifiersISSN: 0025-7079 • E-ISSN: 1537-1948
PublisherOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/mlr.0000000000000649
PMID27635599
OpenAlexW2520043947
LanguageEN
Citations received3
References cited21

BACKGROUND: Existing administrative data patient safety indicators (PSIs) have been limited by uncertainty around the timing of onset of included diagnoses. OBJECTIVE: We undertook de novo PSI development through a data-driven approach that drew upon "diagnosis timing" information available in some countries' administrative hospital data. RESEARCH DESIGN: Administrative database analysis and modified Delphi rating process. SUBJECTS: All hospitalized adults in Canada in 2009. MEASURES: We queried all hospitalizations for ICD-10-CA diagnosis codes arising during hospital stay. We then undertook a modified Delphi panel process to rate the extent to which each of the identified diagnoses has a potential link to suboptimal quality of care. We grouped the identified quality/safety-related diagnoses into relevant clinical categories. Lastly, we queried Alberta hospital discharge data to assess the frequency of the newly defined PSI events. RESULTS: Among 2,416,413 national hospitalizations, we found 2590 unique ICD-10-CA codes flagged as having arisen after admission. Seven panelists evaluated these in a 2-round review process, and identified a listing of 640 ICD-10-CA diagnosis codes judged to be linked to suboptimal quality of care and thus appropriate for inclusion in PSIs. These were then grouped by patient safety experts into 18 clinically relevant PSI categories. We then analyzed data on 2,381,652 Alberta hospital discharges from 2005 through 2012, and found that 134,299 (5.2%) hospitalizations had at least 1 PSI diagnosis. CONCLUSION: The resulting work creates a foundation for a new set of PSIs for routine large-scale surveillance of hospital and health system performance

Data quality · Delphi method · Diagnosis code · Environmental health · Health care · Medical diagnosis · Medical emergency · Metric (unit) · Operations management · Patient safety · Population · Quality (philosophy) · Scale (ratio) · Clinical Reasoning and Diagnostic Skills · Computer Science · Emergency Medicine · Medical Coding and Health Information · Medicine · Primary Care and Health Outcomes

  • Health Disparities of Healthcare Utilization and Opioid Use Disorders Among Chronic Pain Patients

    Open Access•Jeong-Hui Park, Tyler Prochnow et al.•International Journal of Mental…•2025

  • Validating ICD-10 Algorithms for Identifying Patient Safety Indicators Through 10,655 Charts Review

    Guosong Wu, Jie Pan et al.•Medical Care•2026

  • Adverse Events Among Hospitalized Critically Ill Patients

    Khara M Sauro, Andrea Soo et al.•Medical Care•2020

  • The Nature of Adverse Events in Hospitalized Patients

    LUCIAN L LEAPE, Troyen A Brennan et al.•New England Journal of Medicine•1991

  • Incidence of Adverse Events and Negligence in Hospitalized Patients

    Troyen A Brennan, LUCIAN L LEAPE et al.•New England Journal of Medicine•1991

  • Incidence and Types of Adverse Events and Negligent Care in Utah and Colorado

    Eric J Thomas, David M Studdert et al.•Medical Care•2000

  • Can Administrative Data Be Used to Compare Postoperative Complication Rates Across Hospitals

    Patrick S Romano, Benjamin K Chan et al.•Medical Care•2002

  • Identifying Complications of Care Using Administrative Data

    Lisa I Iezzoni, JENNIFER DALEY et al.•Medical Care•1994

  • Evaluating the Patient Safety Indicators

    Amy K Rosen, Peter Rivard et al.•Medical Care•2005

  • Racial, Ethnic, and Socioeconomic Disparities in Estimates of AHRQ Patient Safety Indicators

    Rosanna M Coffey, Roxanne M Andrews et al.•Medical Care•2005

  • Improved Coding of Postoperative Deep Vein Thrombosis and Pulmonary Embolism in Administrative Data (AHRQ Patient Safety Indicator 12) After Introduction of New ICD-9-CM Diagnosis Codes

    Banafsheh Sadeghi, Richard H White et al.•Medical Care•2015

Unique citing works3
Citations per year0,5
Citation span2020 - 2026 (7)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 3

Tools

Open DOISci-HubOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae