An Audit of Cardiovascular Risk Management of A1c, Blood Pressure and Cholesterol (ABC) in a Diabetic Clinic: Identifying Gaps and Quality Improvement Implications
DOI:
https://doi.org/10.14738/bjhmr.115.17745Keywords:
Type 2 diabetes, CVD risk factors, Quality improvement (QI) initiatives, Clinical practice guidelines, Risk stratification, Low-and-middle income countries(LMICs)Abstract
Background: Type 2 diabetes increases cardiovascular disease (CVD) risk. Optimal management requires controlling blood sugar (A1c), blood pressure (BP), and LDL cholesterol (LDL-C). Quality improvement (QI) initiatives to track these factors are essential; however, resource limitations hinder optimal care in low- and middle-income countries (LMICs). Care audits aid in identifying gaps and guide QI initiatives. Methods: A retrospective cross-sectional audit (2019 data) of 362 type 2 diabetes patients’ files at Kenyatta National Hospital (Nairobi) was done using systematic random sampling. Data on demographics, diabetes duration, comorbidities, and CVD risk factors (A1c, BP, LDL-C) were extracted comparing them to Kenyan, European, and American Diabetes Association guidelines, to assess adherence and data use for decision-making. Results: Most participants (68%) were female, aged 50-59, with diabetes duration under 10 years. CVD risk stratification was not documented. We categorized patients into cardiovascular risk strata: very high (28.7%), high (57.7%), and moderate (13.5%). Only 50.6% had one risk factor controlled, and none had all three controlled, with 42.3% missing documentation for these factors. BP was the most frequently recorded parameter (99%). Clinic visit frequency was low, with 47.8% attending twice and 26.2% attending once in the year under consideration. Conclusion: We revealed deficiencies in documentation and suboptimal control of CVD risk factors. Absence of CVD risk stratification during care highlights the need for QI initiatives to improve documentation and translate guidelines into effective management practices. Addressing socioeconomic factors influencing follow-up visits and access to necessary tests is crucial for optimizing care in LMIC settings.
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