Evidence map›Paper›PMID 41994708›Full record

ArticleCureus2026

Impact of Dedicated Nurse Time on Electronic Health Record (EHR)-Based Diabetes Quality Measures: A Pre-Post Observational Study.

Bryan A Farford, Jacqueline K Hurd, Jeffery L Crick, Manisha Salinas, Christine Q Nguyen, Raphael A O Bertasi, Dani G Zapp, Tyler M Janitz, George G A Pujalte

Abstract read
In one paragraph

Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Bryan A FarfordFamily Medicine, Mayo Clinic, Jacksonville, USA.
Jacqueline K HurdNursing, Mayo Clinic, Jacksonville, USA.
Jeffery L CrickFamily Medicine, Mayo Clinic, Jacksonville, USA.
Manisha SalinasEpidemiology and Public Health, Center for Health Equity and Community Engagement Research, Mayo Clinic, Jacksonville, USA.
Christine Q NguyenFamily Medicine, Mayo Clinic, Jacksonville, USA.
Raphael A O BertasiInternal Medicine, Advent Health, Orlando, USA.
Dani G ZappFamily Medicine, Mayo Clinic, Jacksonville, USA.
Tyler M JanitzFamily Medicine, Mayo Clinic, Jacksonville, USA.
George G A PujalteFamily Medicine, Mayo Clinic, Jacksonville, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveDespite major advances in diabetes therapies, only about 60% of U.S. patients achieve recommended glycemic targets in primary care. Inconsistent electronic health records (EHR) complicate diabetes care delivery and highlight the need for strategies that support accurate documentation and patient engagement. The objective of this project is to have 50% of patients with diabetes meet six quality measures: hemoglobin A1c, blood pressure, statin use, aspirin use, tobacco status, and urine microalbumin.  Methods: In April 2019, a registered nurse (RN) was tasked with overseeing these six diabetes quality measures among 477 patients with diabetes. Using electronic health record (EHR) reports, the RN identified patients not meeting measures and implemented interventions, including patient outreach, laboratory coordination, medication reconciliation, and documentation updates. The primary outcome was the proportion of patients meeting all six measures ("all-or-none compliance"). The clinic transitioned its electronic health record (EHR) from Cerner to Epic in October 2018, which affected quality reporting during the study period.

resultsAll-or-none compliance was 40.0% during the pre-EHR transition phase, declined to 24.6% after EHR implementation (pre-RN phase), and increased to 40.6% during the RN intervention phase. At the start of the RN intervention, mean compliance was 35% and improved by an average of 45.7 patients (1.2%) per month through December 2019. RN review identified multiple deficiencies related to EHR documentation, including unreconciled medications, outdated tobacco status, missing external laboratory results, and patients no longer affiliated with the practice. Addressing these issues improved the accuracy of quality reporting and completion of required measures.

conclusionDiabetes often carries a complex care plan, initiated and managed in most primary care settings. It requires a multidisciplinary approach with EHR facilitating quality measurement. Dedicating an RN to oversee the quality of measures of patients with diabetes may improve the accuracy and completeness of EHRs.

Indexed as

data collectiondiabeteselectronic health recordquality improvementregistered nurse

Identifiers

PMID41994708
PMCPMC13082888

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.