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1 Epidemiology and Health Services Research Unit at Instituto Mexicano del Seguro Social;

Evaluating the quality of care for patients with type 2 diabetes using the electronic medical record information in Mexico. 1 Epidemiology and Health Services Research Unit at Instituto Mexicano del Seguro Social;

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1 Epidemiology and Health Services Research Unit at Instituto Mexicano del Seguro Social;

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  1. Evaluating the quality of care for patients with type 2 diabetes using the electronic medical record information in Mexico 1Epidemiology and Health Services Research Unit at Instituto Mexicano del Seguro Social; 2 Department of Population Medicine at Harvard Medical School and Harvard Pilgrim Health Care Institute; 3Centre for Health Services and Policy Research, The University of British Columbia, Canada. Ricardo Pérez-Cuevas1 Svetlana Doubova1 Michael Law3 Aakanksha Pande2Magdalena Suárez1 Dennis Ross-Degnan2 Anita Wagner2

  2. OBJECTIVES • To develop quality of care indicators (QCI) for type 2 diabetes in the Mexican Institute of Social Security (IMSS) • To assess the feasibility of extracting data from IMSS Electronic Health Record to construct the QCI; and • To evaluate the quality of care provided to patients with T2DM cared for at IMSS

  3. METHODS Design: The study used a mixed method approach consisting of : • Development of quality of care indicators for T2DM using the RAND-UCLA method; • Data extraction and construction of Indicators • Evaluation of quality of care for T2DM Setting: 4 clinics in Mexico City covering 520,000 people Study Population: Patients with T2DM who received care in 2009.

  4. Family medicine health information system Pharmacy Affiliates database e-prescription Transfer of data to other institutional systems- data warehouses Electronic health record Laboratory tests System for disability leaves Essential list of drugs

  5. Data extraction • Electronic health record • Clinical information, diagnosis, treatment, number of visits, laboratory tests ordered • Membership database • Members information: address, demographics, • Prescription • Drugs prescribed, amount and dosages • Laboratory • Laboratory results 2009

  6. Extraction of routine EHR data to construct pre-defined QCI Extract, standardize, and load high quality data Sources of data EHR Decision makers Clinicians Researchers Integrated data base Lab Difssemination of results Affiliation Validation Prescr. QCI analytical models Integration of data Analysis Generation of information Potential institutional benefits

  7. Table 1. Population and characteristics of the family medicine clinic

  8. Type 2 diabetes patients general characteristics

  9. Medical history and use of healthcare services

  10. Table 4. Quality of care indicators

  11. Table 4. Quality of care indicators

  12. CONCLUSIONS • It is feasible to evaluate QC using the IMSS EHR data. • It is necessary to improve both QC and quality of information in the EHR in IMSS. • Measuring QC in this way is efficient • It is possible to identify the performance of clinics or single providers and guide future interventions aimed at improving QC.

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