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Background: Type II diabetes mellitus is a chronic medical condition affecting societies worldwide. The duration of hyperglycemia is a strong predictor of adverse outcomes and imposes immense clinical and public health concerns. The best way to prevent complications and reduce the economic burden is by capturing asymptomatic individuals early in the disease process.Local problem: Patients at a large urban academic medical center were not consistently identified as having a high risk of hyperglycemia. Methods:The project used a pretest-posttest design. Retrospective data on new-onset hyperglycemia incidence were compared for all individuals seeking primary care services 6 weeks before and after the intervention.Intervention: Patients without a known hyperglycemia history were provided the screening tool to determine risk status. Additional screening measures were implemented for patients identified as high risk on the initial screening.Results: A total of 52 (61.6%) of the 84 individuals who met inclusion criteria during the intervention period were diagnosed with new-onset chronic hyperglycemia. In contrast, 20 (22.5%) of the 89 individuals identified during the retrospective period resulted in a statistically significant difference (p < .001) in the frequency and accuracy of patients diagnosed with hyperglycemia between groups. Conclusion:A diabetes risk assessment tool is quick and reliable in capturing high-risk individuals who would benefit from additional screening measures.

BackgroundPhysical activity (PA) is a primary factor in reducing the risk of chronic diseases, yet only half of U.S. adults meet recommended levels.ObjectiveTo evaluate a PA self-monitoring pilot intervention using technology in obese adult primary care patients.MethodsThe project had a prospective, single group, pretest/posttest design using an accelerometer with a smartphone app. Obese adult primary care patients (N = 31) were followed over 6 months. Demographic (age, race, sex, marital status, educational level) and PA-relevant (PA, body mass index [BMI], self-efficacy for exercise [SEE]) data were collected at enrollment. PA and BMI were recorded monthly for 6 months. SEE was reassessed at 6 months.ResultsPA and BMI showed gradual improvement; however, changes in PA (p = .130), BMI (p = .326), and SEE (p = .877) at 6 months were not statistically significant. A strong, negative relationship was found between PA and BMI (r = −.727, p < .01). Anecdotal data indicated the smartphone app was acceptable to patients.ConclusionsData-supported clinician-initiated PA self-monitoring with a smartphone app was acceptable and showed favorable trends in improving PA and BMI in obese adult patients.Implications for NursingPrescribing PA self-monitoring using technology may be easily implemented.