Types, Frequency and Consequences of Problems with the Availability or Quality of Health Information and Solutions Implemented in the Healthier Together Pilot Study
| HIE Data Quality Problem Type | Frequency of Data Quality Problem in HIE Records | Consequences of Data Quality Problem & ▸Mitigation Strategies |
|---|---|---|
| Patient is not attributed to a PCP (no PCP listed) | Decreased from 94% to 80% over the pilot | Services & quality metrics can't be linked to PCP ▸Additional patient matching using EHR data |
| Low actionable* data contribution from PCPs | Decreased from 89% to 66% over the pilot | Less information on PCP services ▸ Improving data interfaces & manual extractions from EHRs |
| Missing or wrong patient phone numbers | Decreased from 49% to 38% over the pilot | Patient reach barriers ▸ Better documentation & additional data extraction from billing records |
| Risk factor rate lower or higher than expected† | Smoker (5% vs. 16%‡) | Inaccurate care gap predictions ▸ Better chart documentation and calibrating data interfaces |
| Diabetic (21% vs. 10%‡) | ||
| Preventive service rates are lower than expected† | Mammography (5% vs. 11%‡; increased to 13% over time) | Inaccurate care gap predictions ▸ Better chart documentation and calibrating data interfaces |
| Race or ethnicity information not available | About 98% to 99% of records (remained unchanged) | Less tailored care recommendations ▸ Improve documentation of race in patient chart |
| Skewed data contribution among organizations | 30% of HIE records are over-concentrated in SE of county | Some organizations dominate as data source ▸ Oversample records in northern county region |
EHR, Electronic Health Record; HIE, Health Information Exchange (patient records aggregated regionally); PCP, primary care practice.
↵* Actionable data include health risk factors (e.g., smoking status), reports, and laboratory findings pertinent to prevention, and history of preventive services. Low-value data include administrative visit information and free text notes that often “bloat” interoperable records causing excessive transmission and processing times.
↵† Rate means the frequency of the occurrence of health risk factors or preventive services in HIE datasets relative to the known prevalence of these factors in the population.
↵‡ State of the State's Health Report 2014, Oklahoma State Department of Health.