The common data quality problems in healthcare performance measurement include the limitations of administrative data as most of it lacks the clinical details required to generate credible measures. Medical record data while being detailed about clinical issues often lacks standardization and may vary widely depending on settings. Survey data from patients is expensive to obtain and is unreliable due to site variation in response rates leading to biases.
The common challenges an administrator may face when attempting to measure a physician’s performance are the heterogeneity of scientific processes and the limitations of the measure sets that are in use currently. In particular, managers are concerned about the limited scope of the measures that are in use and the defects that are inherent to these measures. The invalid inferences resulting from these measures can compromise measurement efforts for physicians.
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Administrators should evaluate the sufficiency of the data quality by determining its reliability and credibility in relation to established quality and safety standards. For instance, process measures are preferred by administrators because they are standardized and have minimal need for risk-adjustment. Further, administrators should determine if data measure reflects professional standards of care. The consequences of using poor quality data are that an administrator may risk endorsing practices that are contrary to evidence-based care. Using poor quality data may also result in using data that does not capture the quality it was supposed to measure.
The relationship between continuous quality improvement and physician profiling is that administrators use physician profiles to measure how they are responding to quality improvement initiatives. The profiles indicate how different physicians respond to quality measures and helps administrators determine the best improvement approaches for different physicians.
