The practice of manual information recording has been a norm for many healthcare facilities for years. However, with the increasing concerns about quality measurements, electronic health records (EHR) have started to become more popular as well (Clarke, 2013). In the presented scenario, a small practice has an EHR system, but all records are saved and input manually, thus making the computer system virtually useless in the setting. Therefore, the staff nurse has to take on the responsibility of collecting the necessary information by reviewing records. The initial step in this process would be to identify all patients with diabetes.
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It should be noted that, according to the Healthcare Effectiveness Data and Information Set (HEDIS), only patients with type 1 and 2 diabetes are counted (National Committee for Quality Assurance [NCQA], n.d.). Patients with official diagnoses of gestational or other forms of diabetes are not included in such measurements. Thus, as the staff nurse, I would need to find all patients with the official diagnosis of type 1 or type 2 diabetes. This information is located in patients’ records along with other attached charts such as the results of blood tests.
The following step would be to identify whether the selected patients meet all components of the HEDIS comprehensive care measures. The first of these is hemoglobin A1c (HbA1c) tests (NCQA, n.d.). In this case, one can collect data from glycosylated or glycated hemoglobin testing that was performed in the years the results are requested. This information should be written down in the charts or attached to the latest screenings and tests. Next, the results of the tests will be turned into HbA1c control measure, and patients will be further separated into a number of categories. Thus, patients with HbA1c poor control (with the outcome of >9.0%) will be separated.
Other groups will also include HbA1c control <7.0, HbA1c control <8.0, and, finally, HbA1c control <9.0 (NCQA, n.d.). The data of these control groups rely on the latest tests. If some patients do not have available recent results, they may fall into the category of poor control (Kutz et al., 2018). Another measurement-based indicator is BP (blood pressure) control. Here, all patients whose BP is lower than 140/90 mm Hg fit the outline of HEDIS comprehensive diabetes care.
The next measure is the result of the medical eye exam performed recently or in the year of data collection. Here, one can utilize the findings of two types: the first is the dilated eye or retinal exam that was performed by a specialist in the year of data gathering (NCQA, n.d.). The second option is the result of the same exam that was performed in the year prior; however, the outcomes of this testing should not indicate the presence of retinopathy.
Patients with retinopathy whose tests were not updated do not meet the criteria for HEDIS comprehensive care (NCQA, n.d.). Finally, the last measure that should be collected is linked to neuropathy. In this case, as a staff nurse, I can search for urine or microalbumin tests in patients’ records as well as nephropathy screening tests (NCQA, n.d.; Verma, Kumar, Sharma, Singh, & Singh, 2017). By collecting these data in manual records, I will be able to calculate the number of patients that have diabetes and meet the components of the latest HEDIS comprehensive diabetes care.
Clarke, B. (2013). The cost of manual charting. Point of Care, 12(2), 67-68.
Kutz, T. L., Roszhart, J. M., Hale, M., Dolan, V., Suchomski, G., & Jaeger, C. (2018). Improving comprehensive care for patients with diabetes. BMJ Open Quality, 7(e000101), 1-6.
National Committee for Quality Assurance. (n.d.). Comprehensive diabetes care (CDC). Web.
Verma, M. K., Kumar, P., Sharma, P., Singh, V. K., & Singh, S. P. (2017). Study of microalbuminuria as early risk marker of nephropathy in type 2 diabetic subjects. International Journal of Research in Medical Sciences, 5(7), 3161-3166.