ArticleJournal of diabetes science and technology2015
Mixed Influence of Electronic Health Record Implementation on Diabetes Order Patterns for Michigan Medicaid Adults.
Article in Journal of diabetes science and technology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 2 citations in OpenAlex.
- [Electronic Medical Record for Prenatal Care of Diabetic Women].Revista brasileira de ginecologia e obstetricia : revista da Federacao Brasileira das Sociedades de Ginecologia e Obstetricia · 2016Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThese 2011-2013 analyses examined the authors' hypothesis that relative diabetes care order changes would be measured after electronic health record (EHR) implementation for 291 Medicaid adults who received all of their office-based care at one midwestern federally qualified health center (FQHC) over a 24-month period (n = 2727 encounters, 2489 claims).
methodBeneficiary sociodemographic, clinical, and claims data were validated with clinic EHR and state Medicaid claims linked to providers' national identifier numbers. Overall pre-post order rate comparisons, and a series of controlled within group binary logistic models were conducted under penalized maximum likelihood estimation terms.
resultsAfter EHR implementation, both the overall order rates and odds ratios of per beneficiary hemoglobin A1C (HbA1C) orders increased significantly (ie, from mean of 0.65 [SD = 1.19] annual tests to 0.96 tests [SD = 1.24] [P < .001]). Although the overall post-EHR order rates of dilated eye exams and microalbumin urine tests appeared fairly stable, the odds of eye exam orders being placed at the claims level decreased significantly (OR = 0.774, P = .0030).
conclusionsThese mixed results provide evidence of the varied diabetes care ordering patterns likely seen from increased office use of EHR technologies. The authors attempt to explain these post-EHR differences (or lack of) that generally resemble some of the authors' results from another funded project. Ideally, these findings provide Medicaid and health care officials with a more realistic indication of how EHRs may, or may not, influence diabetes care ordering patterns for vulnerable lower-income primary health care consumers.
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