Abstract
Background: It is important to assess how well patients respond to their medical treatments by observing the results that appear during the clinical treatments. As such, the clinical treatments and results must obtain information on how effective recommended treatments were for patients with diabetes.
Objective: This study examines how patients with diabetes mellitus responded towards their clinical treatments, where the probability distribution of patients and the types of treatment received were derived from the Rasch probabilistic model.
Methods: This is a retrospective study wherein data were collected from patients’ medical records at a local public hospital in Selangor, Malaysia. Clinical and demographic information such as fasting blood glucose, hemoglobin A1c (HbA1c), family history, type of diabetes (type 1 or type 2), types of medication (oral or insulin), compliance with treatments, gender, race and age were chosen as the agents of measurement.
Results: The use of Rasch analysis in the present study helped to compare the patients’ responses towards the DM treatments and identify the types of treatment they received. Results from the Wright map show that a majority of the diabetes mellitus patients who were diagnosed with type 2 diabetes have no controlled readings of HbA1c during their first and second visits to the medical center. However, patients with a family history of diabetes mellitus who took oral medication have controlled readings of fasting blood glucose based on the probabilistic outcomes of the treatment received by the patients.
Conclusion: Controlled readings were found only in the readings of fasting blood glucose during the first and second visits, followed by family history, types of medication received, and compliance with the treatment. This study has recommended that type 2 patients with diabetes without a family history of diabetes mellitus need to exercise more control over the readings of HbA1c.
Keywords: Diabetes mellitus, clinical treatments, outcomes, rasch measurement model, fasting blood glucose, HbA1c.
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