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

Abstract

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.

Effect of Preoperative Geriatric Evaluation on Outcomes After Elective Surgery: A Population‐Based Study

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“…The primary outcome was 90‐day postoperative survival (from the RPDB—our reference standard for mortality). In‐hospital complications were identified using clusters of ICD‐10 type 2 diagnostic codes (captured from the DAD) . These codes demonstrated a positive likelihood ratio of 6.5 and a negative likelihood ratio of 0.39 when compared with complications prospectively captured through the National Surgical Quality Improvement Program .…”

Association between known or strongly suspected malignant hyperthermia susceptibility and postoperative outcomes: an observational population-based study

“…Major complications (secondary outcomes) were defined by CCI intervention codes, International Statistical Classification of Diseases-10 (ICD-10) diagnostic codes, 10 and/or Ontario Health Insurance Plan physician billings (eTable 2, available as ESM). Major complications were only included if they were diagnosed for the first time postoperatively.…”

Comparative assessment of two frailty instruments for risk-stratification in elderly surgical patients: study protocol for a prospective cohort study

“…Secondary outcomes will include complications (defined by Post-Operative Morbidity Survey [38] criteria, applied through a post-discharge chart review), patient safety events (defined by International Classification of Diseases Tenth Edition codes grouped by patient safety indicator clusters using Type 2 diagnoses [39]), hospital LOS, total health system costs (using standard person-level cost algorithms to identify costs of the index hospitalization, and total costs up to 30, 90 and 365 days after surgery [40]), discharge disposition (home vs. supported or institutional discharge). All secondary outcomes other than complications will be ascertained using validated methods through linkage to provincial health administrative data.…”