Evidence map›Paper›PMID 24359533›Full record

ArticleHealth services research2014

The impact of electronic health records on workflow and financial measures in primary care practices.

Neil S Fleming, Edmund R Becker, Steven D Culler, Dunlei Cheng, Russell McCorkle, Briget da Graca, David J Ballard

Abstract read
In one paragraph

Article in Health services research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

29 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Article
  6. Article
  7. Article
  8. Article
  9. Physician Productivity and Supervision.The western journal of emergency medicine · 2023
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  12. Scribes, EHRs, and Workflow Efficiencies in Allergy Practices.Current allergy and asthma reports · 2020
    Review
  13. Article
  14. An Efficient Mobile-Healthcare Emergency Framework.Journal of medical systems · 2020
    Article
  15. Transformation of the Doctor-Patient Relationship: Big Data, Accountable Care, and Predictive Health Analytics.HEC forum : an interdisciplinary journal on hospitals' ethical and legal issues · 2019
    Article
  16. Prognostic models will be victims of their own success, unless….Journal of the American Medical Informatics Association : JAMIA · 2019
    Article
  17. Article
  18. A Time-Driven Activity-Based Costing Analysis of Emergency Department Scribes.Mayo Clinic proceedings. Innovations, quality & outcomes · 2019
    Article
  19. Using Smart City Technology to Make Healthcare Smarter.Proceedings of the IEEE. Institute of Electrical and Electronics Engineers · 2018
    Article
  20. Article
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

7 authors.

Neil S FlemingBaylor Health Care System, Dallas, TX.
Edmund R Becker
Steven D Culler
Dunlei Cheng
Russell McCorkle
Briget da Graca
David J Ballard

Funding

Impact of Health IT on Primary Care Work-flow and Financial MeasuresR03HS018220 · AHRQ · BAYLOR RESEARCH INSTITUTE · PI FLEMING, NEIL STEWART · 2009 to 2009
$100k
AHRQ HHS 1R-03 HS018220-01SAHRQ HHS R01 HS026232AHRQ HHS R03 HS018220ODCDC CDC HHS R01 CD000033
6 · The paper itself

Abstract

objectiveTo estimate a commercially available ambulatory electronic health record's (EHR's) impact on workflow and financial measures. DATA SOURCES/STUDY

settingAdministrative, payroll, and billing data were collected for 26 primary care practices in a fee-for-service network that rolled out an EHR on a staggered schedule from June 2006 through December 2008. STUDY

designAn interrupted time series design was used. Staffing, visit intensity, productivity, volume, practice expense, payments received, and net income data were collected monthly for 2004-2009. Changes were evaluated 1-6, 7-12, and >12 months postimplementation. DATA COLLECTION/EXTRACTION

methodsData were accessed through a SQLserver database, transformed into SAS®, and aggregated by practice. Practice-level data were divided by full-time physician equivalents for comparisons across practices by month. PRINCIPAL

findingsStaffing and practice expenses increased following EHR implementation (3 and 6 percent after 12 months). Productivity, volume, and net income decreased initially but recovered to/close to preimplementation levels after 12 months. Visit intensity did not change significantly, and a secular trend offset the decrease in payments received.

conclusionsExpenses increased and productivity decreased following EHR implementation, but not as much or as persistently as might be expected. Longer term effects still need to be examined.

Indexed as

Ambulatory CareEfficiency, OrganizationalElectronic Health RecordsFemaleHumansMaleMiddle AgedPractice Patterns, Physicians'Primary Health CareTexasTime FactorsWorkflowElectronic health recordsfinancial performanceworkflow

Identifiers

PMID24359533
PMCPMC3925410

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.