Using Precision Performance Measurement to Conduct Focused Quality Improvement

Quality measurement techniques have increased in sophistication during the past few decades and now allow for meaningful comparisons between health care facilities or health plans. However, as currently practiced, these methods cannot be used to raise health care quality to the highest possible level because measures that depend on data collected for administrative purposes inevitably have measurement inaccuracies at the individual patient level. Patients may incorrectly be considered eligible for a measure; appear to fail a quality measure they have met because data satisfying the measure was not captured; or have reasons the measure was not appropriate for them, such as exclusion criteria that the measurement system failed to detect.

The overall goal of this study was to determine whether a health information technology-enabled quality improvement strategy could improve performance on a set of 18 measures of quality of care for four chronic conditions and five preventive services. The specific aims were to:

• Create simple, standard ways for clinicians to document patient reasons or medical reasons for why quality measures are not met.
• Use the exception codes that clinicians enter (i.e., patient reasons and medical reasons for not providing a recommended therapy or preventive service) to target three strategies for quality improvement:
  • Peer review of all medical reasons for not adhering to guidelines followed by academic detailing if a clinician enters an unjustified reason for not following guidelines.
  • Counseling for all patients whose physician enters an exception code stating that the patient cannot afford a needed medication to determine ways of overcoming barriers.
  • Educational outreach to all patients who refuse recommended interventions, including mailing of plain-language health education materials or DVDs.
• Provide clinicians with highly accurate information on patients’ quality deficits immediately prior to each patient’s visit as part of routine work flow.

The study took place at the Northwestern Medical Faculty Foundation’s General Internal Medicine clinic. Exception codes for 18 national quality measures for four chronic conditions and five preventive services were introduced into the electronic health record. These measures had been developed by organizations such as the Physicians' Consortium for Performance Improvement at the American Medical Association or adapted from measures of the National Committee for Quality Assurance. Two measures were not implemented in the study due to technical limitations: blood pressure control in patients with and without diabetes. The statistical significance of changes was assessed with time-series analysis. In addition, physicians were repeatedly surveyed on their attitudes toward the interventions. Outcomes of the quality improvement activities were monitored as were the costs of the intervention.

During the first year of the intervention, performance improved significantly for 14 measures. For nine measures, the primary outcome improved more rapidly during the intervention year than during the prior year. The improvements in performance during the intervention phase were due to a combination of more patients satisfying the measures and physician documentation of exceptions. The project team found that the medical exceptions documented were almost always valid. For patients that refused recommended services, outreach, such as mailed educational materials and care manager calls to identify and resolve any barriers to obtaining the service, was not effective. For physicians whose overall performance lagged, the paper reminders provided to physicians to review prior to entering the examination room was also not effective.