The Robert Wood Johnson Foundation's Aligning Forces for Quality provides tips on publicly reporting quality data in a report (pdf) titled "Can Publicly Reporting the Performance of Health Care Providers Spur Quality Improvement? Insights from Aligning Forces for Quality."
Publicly reporting quality data is one of the major aspects of AF4Q, a quality improvement program targeting 16 communities, as it motivates positive change.
In the report, AF4Q shares three tips for public reporting programs:
1. Consider what sources will be used to obtain quality performance information. AF4Q discusses four possible sources of quality data for healthcare organizations:
a. Clinical data: Information from electronic medical records, which can be supplemented by chart review or other manual processes.
b. Claims data: Data health plans collect.
c. Patient experience data: Responses from surveys of patients' experience.
d. Cost and efficiency data: Data from health plans, state hospital discharge data, state Medicaid programs, Medicare reports and state health information exchanges.
2. Consider what information can be realistically extracted from these data sources.
3. Consider which conditions or diseases are most critical to the community.
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Publicly reporting quality data is one of the major aspects of AF4Q, a quality improvement program targeting 16 communities, as it motivates positive change.
In the report, AF4Q shares three tips for public reporting programs:
1. Consider what sources will be used to obtain quality performance information. AF4Q discusses four possible sources of quality data for healthcare organizations:
a. Clinical data: Information from electronic medical records, which can be supplemented by chart review or other manual processes.
b. Claims data: Data health plans collect.
c. Patient experience data: Responses from surveys of patients' experience.
d. Cost and efficiency data: Data from health plans, state hospital discharge data, state Medicaid programs, Medicare reports and state health information exchanges.
2. Consider what information can be realistically extracted from these data sources.
3. Consider which conditions or diseases are most critical to the community.
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