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91������ does not support NQF measure #1932: Diabetes Screening for People with Schizophrenia or Bipolar Disorder who are Using Antipsychotic Medications (SSD).” This measure represents an important clinical concept and clinicians should screen for diabetes in patients who are diagnosed with schizophrenia or bipolar disorder AND obesity and who are also prescribed antipsychotic medication therapy. However, developers do not cite a performance gap, the specifications are significantly flawed, and developers cite evidence on patients who are overweight to form the basis of the measure while this measure applies to all patients. Furthermore, the numerator should specify an evidence-based time-interval. In patients with normal results, the American Diabetes Association (ADA) recommends a minimum of 3-year intervals, with consideration of more frequent testing depending on initial results and risk status. While implementation poses low provider-burden, usability is low without evidence for when next to screen. Also, the numerator and denominator should specify an evidence-based age range and the age cut-off seems arbitrary. The ADA recommends testing begin at age 45 years in patients who are not overweight and who do not have any risk factors for developing diabetes. Testing for prediabetes should only be considered in adolescents who are overweight. Additionally, the specifications should include exclusion criteria for patients with limited life expectancy and increased fragility. Moreover, not all antipsychotic medications are likely to cause adverse metabolic effects. Developers should consider revising the specifications to exclude medications that do not increase the risk for diabetes in patients with serious mental illness. Furthermore, the measure has not been rigorously tested. Of note, while this measure is appropriately specified to assess performance at the health plan-/integrated delivery-level analysis, developers do not cite any data to support analysis at the individual clinician-level and therefore, measure feasibility is unknown. While health-plan data may include a sufficient denominator population to generate reliable results, the denominator population may be too low in some individual/group practices to produce a stable performance estimate. Furthermore, while health plans can easily obtain detailed clinical management data form various information systems (e.g., claims, EHRs, pharmacy), clinicians are not privy to the same information.