Table 3.
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%#) Diabetic (21% vs. 10%#) |
Inaccurate care gap predictions ▶ Better chart documentation and calibrating data interfaces |
| Preventive service rates are lower than expected † | Mammography (5% vs. 11%#; increased to13% over time) | Inaccurate care gap predictions ▶ Better chart documentation and calibrating data interfaces |
| Race or ethnicity information not available | About 98–99% 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 |
HIE: Health Information Exchange (patient records aggregated regionally)
PCP: Primary Care Practice
EHR: Electronic Health Record
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