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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

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


Objectives

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


Methods

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.


Family medicine health information system

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


Data extraction

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


Extraction of routine ehr data to construct pre defined qci

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


Table 1 population and characteristics of the family medicine clinic

Table 1. Population and characteristics of the family medicine clinic


Type 2 diabetes patients general characteristics

Type 2 diabetes patients general characteristics


Medical history and use of healthcare services

Medical history and use of healthcare services


Table 4 quality of care indicators

Table 4. Quality of care indicators


Table 4 quality of care indicators1

Table 4. Quality of care indicators


Conclusions

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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