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PurposeTo evaluate the appropriateness of potential data sources for the population of performance indicators for primary care (PC) practices.MethodsThis project was a cross sectional study of 7 multidisciplinary primary care teams in Ontario, Canada. Practices were recruited and 5-7 physicians per practice agreed to participate in the study. Patients of participating physicians (20-30) were recruited sequentially as they presented to attend a visit. Data collection included patient, provider and practice surveys, chart abstraction and linkage to administrative data sets. Matched pairs analysis was used to examine the differences in the observed results for each indicator obtained using multiple data sources.ResultsSeven teams, 41 physicians, 94 associated staff and 998 patients were recruited. The survey response rate was 81% for patients, 93% for physicians and 83% for associated staff. Chart audits were successfully completed on all but 1 patient and linkage to administrative data was successful for all subjects. There were significant differences noted between the data collection methods for many measures. No single method of data collection was best for all outcomes. For most measures of technical quality of care chart audit was the most accurate method of data collection. Patient surveys were more accurate for immunizations, chronic disease advice/information dispensed, some general health promotion items and possibly for medication use. Administrative data appears useful for indicators including chronic disease diagnosis and osteoporosis/ breast screening.ConclusionsMultiple data collection methods are required for a comprehensive assessment of performance in primary care practices. The choice of which methods are best for any one particular study or quality improvement initiative requires careful consideration of the biases that each method might introduce into the results. In this study, both patients and providers were willing to participate in and consent to, the collection and linkage of information from multiple sources that would be required for such assessments.

BackgroundThis mixed methods study was designed to explore the acceptability and impact of feedback of team performance data to primary care interdisciplinary teams.MethodsSeven interdisciplinary teams were offered a one-hour, facilitated performance feedback session presenting data from a comprehensive, previously-conducted evaluation, selecting highlights such as performance on chronic disease management, access, patient satisfaction and team function.ResultsSeveral recurrent themes emerged from participants' surveys and two rounds of interviews within three months of the feedback session. Team performance measurement and feedback was welcomed across teams and disciplines. This feedback could build the team, the culture, and the capacity for quality improvement. However, existing performance indicators do not equally reflect the role of different disciplines within an interdisciplinary team. Finally, the effect of team performance feedback on intentions to improve performance was hindered by a poor understanding of how the team could use the data.ConclusionsThe findings further our understanding of how performance feedback may engage interdisciplinary team members in improving the quality of primary care and the unique challenges specific to these settings. There is a need to develop a shared sense of responsibility and agenda for quality improvement. Therefore, more efforts to develop flexible and interactive performance-reporting structures (that better reflect contributions from all team members) in which teams could specify the information and audience may assist in promoting quality improvement.

Background. Calculating disease prevalence requires both a numerator (number of persons with a disease) and a matching denominator (the 'population at risk' being studied). Determining primary care practice denominators is challenging.Objective. To develop and test a method to calculate primary care practice denominators. Methods.We compared a 'corrected yearly contact group', or practice population, with the number of patients enrolled with practices. The yearly contact group was the set of patients with a visit noted in the electronic medical records during the past year. The correction factor was the proportion of patients that reported contacting their physician in the past year. Eighty-one physicians from Toronto and Kingston, Ontario, provided data. The main outcome measure was the ratio of practice population to the number of enrolled patients. Other measures included the change in ratio over 2 years, differences between locations, and differences by provider, practice and patient characteristics. Results.The ratio of practice population to enrolled patients was 1.03 in 2010 (95% confidence interval 1.00 to 1.05) and 1.03 in 2011 (95% confidence interval 1.00 to 1.05). There was no change in the ratio over time. Ratios by location, provider or practice characteristics differed by less than 10%. There was a slight under-estimation of practice population for younger male patients and over-estimation for female patients.Conclusion. This method provided a denominator that was reasonably similar to the enrolled population and was stable over time and by location, provider and practice characteristics. In regions without patient enrollment, this may provide an estimate of practice denominators.