Unlocking Real-World Insights: The US Wound Registry’s Guide to Bias-Free Data in Wound Care
Summary: This white paper from the US Wound Registry (USWR), a non-profit patient registry since 2005 and CMS-recognized Qualified Clinical Data Registry since 2014, introduces the ABCs (Analysis of Bias Criteria) Checklist for minimizing bias in wound care registries and EHRs. It addresses the challenges of chronic wounds affecting 8.2 million Medicare patients at a cost of up to $96.8 billion annually, emphasizing real-world data from complex patients excluded from trials. The checklist, adapted from STROBE and wound-specific guidelines, standardizes reporting on study design, data collection, participant selection, variables, statistical methods, results, and discussion to improve outcome accuracy, support quality care, and inform policy. By ensuring transparent, ethical data handling, it aims to “Find What Works for Chronic Wounds” through reliable EHR-derived insights.
Key Highlights:
- Prevalence and Costs: Chronic wounds impact 15% of Medicare patients (8.2 million), costing $96.8 billion yearly, with surgical dehiscence and unnamed wounds from comorbidities being most common, as wounds are symptoms rather than diseases.
- Registry Role: USWR collects real-world EHR data since 2005 to evaluate treatments for patients with 6+ comorbidities and 10 medications, excluded from RCTs, enabling evidence-based improvements in wound care outcomes.
- Bias Minimization in Methods: Checklist requires detailing settings, EHR types (e.g., certification levels), participant inclusion (e.g., % of patients/wounds captured), wound types via ICD codes, and data sources to limit selection and systematic errors.
- Variables and Outcomes: Defines outcomes like healing rates (e.g., 1-year timeframe), confounders (e.g., ischemia, amputations), and standard-of-care factors (e.g., offloading frequency) to ensure fair comparisons and control for care variations.
- Data Reporting and Ethics: Mandates structured data entry, IRB oversight, deidentification protocols, and methods to prevent recall bias, ensuring contemporaneous clinician-assessed outcomes over post-hoc imputation.
- Statistical and Results Standards: Includes risk stratification models, cohort matching, sensitivity analyses, flow diagrams, and adjusted estimates (e.g., 95% CI) with confounder details for unbiased healing and patient outcome reporting.
- Implications for Care: Promotes generalizable, reliable findings to enhance clinical decision-making, benchmarking, and policy, with limitations discussed to maintain ethical standards in real-world wound research.
Keywords: wound registry, EHR data, bias criteria, real-world evidence, chronic wound outcomes