The authors declare that they have no competing interests.
RPC conceptualized and designed the study, coordinated the fieldwork and wrote the article. SVD conducted the literature review, coordinated the development, definitions, and programming of the indicators, conducted the statistical analysis, and interpreted the data and contributed to drafting the article. MSO programmed the indicators and collaborated on the analysis; ML participated in assessing data quality and programming the indicators and reviewed critically the results and paper. AHP participated in the development of the study. JE and FEL participated in the design of the indicators and reviewed the paper for significant intellectual content. DR-D collaborated on conceptualizing and designing the study, participated in the development of the study and critically reviewed the paper. AKW collaborated on conceptualizing and designing the study, participated in the development of the study, reviewed the results and contributed to drafting the article. All authors approved the final manuscript.
The opinions expressed are those of the authors and do not necessarily represent the views of their institutions.
Several low and middle-income countries are implementing electronic health records (EHR). In the near future, EHRs could become an efficient tool to evaluate healthcare performance if appropriate indicators are developed. The aims of this study are: a) to develop quality of care indicators (QCIs) for type 2 diabetes (T2DM) in the Mexican Institute of Social Security (IMSS) health system; b) to determine the feasibility of constructing QCIs using the IMSS EHR data; and c) to evaluate the quality of care (QC) provided to IMSS patients with T2DM.
We used a three-stage mixed methods approach: a) development of QCIs following the RAND-UCLA method; b) EHR data extraction and construction of indicators; c) QC evaluation using EHR data from 25,130 T2DM patients who received care in 2009.
We developed 18 QCIs, of which 14 were possible to construct using available EHR data. QCIs comprised both process of care and health outcomes. Several flaws in the EHR design and quality of data were identified. The indicators of process and outcomes of care suggested areas for improvement. For example, only 13.0% of patients were referred to an ophthalmologist; 3.9% received nutritional counseling; 63.2% of overweight/obese patients were prescribed metformin, and only 23% had HbA1c <7% (or plasma glucose ≤130 mg/dl).
EHR data can be used to evaluate QC. The results identified both strengths and weaknesses in the electronic information system as well as in the process and outcomes of T2DM care at IMSS. This information can be used to guide targeted interventions to improve QC.