Donabedian's Quality Framework
Avedis Donabedian's framework classifies healthcare quality measures into three categories: structure, process, and outcome. This framework is foundational to the Analytics domain and appears frequently on the RHIA exam in the context of quality measurement and performance improvement.
The Three Measure Types
- Structure measures: assess the setting and resources available for care, such as nurse-to-patient staffing ratios or availability of certified stroke center services
- Process measures: assess whether recommended clinical actions were performed, such as administering aspirin to a heart attack patient within a defined timeframe
- Outcome measures: assess the actual result of care, such as mortality rate, complication rate, or patient-reported functional status
Common Quality Indicator Sets
HIM professionals should be familiar with several nationally recognized quality indicator programs, including the Agency for Healthcare Research and Quality's Inpatient Quality Indicators and Patient Safety Indicators, the Centers for Medicare and Medicaid Services' Hospital-Acquired Condition and Hospital Readmissions Reduction Program measures, and The Joint Commission's core measure sets tied to accreditation requirements.
Risk Adjustment for Outcome Measures
Outcome measures generally require risk adjustment to fairly compare providers treating populations of differing acuity and complexity. Without adjustment, hospitals treating sicker patients may appear to have worse outcomes even when providing excellent care, so most publicly reported outcome measures incorporate a severity or comorbidity adjustment methodology.
The Role of Coded Data
Accurate ICD-10-CM and ICD-10-PCS coding directly affects quality indicator calculation, since many indicators, including patient safety indicators and hospital-acquired conditions, are derived from administrative claims data rather than chart abstraction. This makes coding accuracy and present-on-admission indicator assignment critically important to fair and accurate quality reporting, linking HIM coding practice directly to organizational quality performance.
Balancing Measures
Quality improvement initiatives should track balancing measures alongside primary outcome measures to ensure that improvement in one area does not create unintended harm elsewhere, such as monitoring readmission rates when an initiative focuses specifically on reducing length of stay.
Exam Tips
Expect questions asking you to classify a described measure as structure, process, or outcome. Also expect questions connecting coding accuracy, particularly present-on-admission indicators, to the integrity of publicly reported quality measures.
Key takeaway: Understanding the Donabedian framework and the coded-data foundation of many quality indicators is essential Analytics domain knowledge for the RHIA exam.