Literature DB >> 28500199

Data quality in electronic medical records in Manitoba: Do problem lists reflect chronic disease as defined by prescriptions?

Alexander Singer1, Andrea L Kroeker2, Sari Yakubovich3, Roberto Duarte4, Brenden Dufault5, Alan Katz6.   

Abstract

OBJECTIVE: To determine if the problem list (health conditions) in primary care electronic medical records (EMRs) accurately reflects the conditions for which chronic medications are prescribed in the EMR.
DESIGN: A retrospective analysis of EMR data.
SETTING: Eighteen primary care clinics across rural and urban Manitoba using the Accuro EMR. PARTICIPANTS: Data from the EMRs of active patients seen in an 18-month period (December 18, 2011, to June 18, 2013, or December 3, 2012, to June 3, 2014) were used. MAIN OUTCOME MEASURES: The likelihood of documentation in the EMR problem list of those specific chronic diseases for which drug prescriptions were documented in the EMR. Regression modeling was performed to determine the effect of clinic patient load and remuneration type on the completeness of EMR problem lists.
RESULTS: Overall problem-list completeness was low but was highest for diabetes and lowest for insomnia. Fee-for-service clinics generally had lower problem-list completeness than salaried clinics did for all prescription medications examined. Panel size did not affect problem-list completeness rates.
CONCLUSION: The low EMR problem-list completeness suggests that this field is not reliable for use in quality improvement initiatives or research until higher reliability has been demonstrated. Further research is recommended to explore the reasons for the poor quality and to support improvement efforts. Copyright© the College of Family Physicians of Canada.

Entities:  

Mesh:

Year:  2017        PMID: 28500199      PMCID: PMC5429058     

Source DB:  PubMed          Journal:  Can Fam Physician        ISSN: 0008-350X            Impact factor:   3.275


  22 in total

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Authors:  Noah Ivers; Jan Barnsley; Ross Upshur; Karen Tu; Baiju Shah; Jeremy Grimshaw; Merrick Zwarenstein
Journal:  Can Fam Physician       Date:  2014-03       Impact factor: 3.275

9.  Evaluation of Electronic Medical Record Administrative data Linked Database (EMRALD).

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