Evidence map›Paper›PMID 24171799›Full record

ArticleBMC medical informatics and decision making2013

Measuring the impact of a health information exchange intervention on provider-based notifiable disease reporting using mixed methods: a study protocol.

Brian E Dixon, Shaun J Grannis, Debra Revere

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

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

  1. Tailored interventions to address determinants of practice.The Cochrane database of systematic reviews · 2026
    Pooled it
  2. Tailored interventions to address determinants of practice.The Cochrane database of systematic reviews · 2015
    Pooled it
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Generalization of Machine Learning Approaches to Identify Notifiable Conditions from a Statewide Health Information Exchange.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2020
    Article
  8. Review
  9. Falling short: how state laws can address health information exchange barriers and enablers.Journal of the American Medical Informatics Association : JAMIA · 2018
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Strategies to Maximize Data Collection Response Rates in a Randomized Control Trial Focused on Children with Medical Complexity.Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2016
    Article
  17. Improving injury prevention through health information technology.American journal of preventive medicine · 2015
    Article
  18. Article
  19. 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

3 authors.

Brian E Dixon
Shaun J Grannis
Debra RevereUniversity of Washington, School of Public Health, Seattle, WA, USA. drevere@uw.edu.

Funding

Improving Population Health Through Enhanced Targeted Regional Decision SupportR01HS020909 · AHRQ · INDIANA UNIVERSITY INDIANAPOLIS · PI DIXON, BRIAN E. · 2011 to 2015
$2.0M
AHRQ HHS R01 HS020909AHRQ HHS R01HS020909
6 · The paper itself

Abstract

backgroundHealth information exchange (HIE) is the electronic sharing of data and information between clinical care and public health entities. Previous research has shown that using HIE to electronically report laboratory results to public health can improve surveillance practice, yet there has been little utilization of HIE for improving provider-based disease reporting. This article describes a study protocol that uses mixed methods to evaluate an intervention to electronically pre-populate provider-based notifiable disease case reporting forms with clinical, laboratory and patient data available through an operational HIE. The evaluation seeks to: (1) identify barriers and facilitators to implementation, adoption and utilization of the intervention; (2) measure impacts on workflow, provider awareness, and end-user satisfaction; and (3) describe the contextual factors that impact the effectiveness of the intervention within heterogeneous clinical settings and the HIE. METHODS/

designThe intervention will be implemented over a staggered schedule in one of the largest and oldest HIE infrastructures in the U.S., the Indiana Network for Patient Care. Evaluation will be conducted utilizing a concurrent design mixed methods framework in which qualitative methods are embedded within the quantitative methods. Quantitative data will include reporting rates, timeliness and burden and report completeness and accuracy, analyzed using interrupted time-series and other pre-post comparisons. Qualitative data regarding pre-post provider perceptions of report completeness, accuracy, and timeliness, reporting burden, data quality, benefits, utility, adoption, utilization and impact on reporting workflow will be collected using semi-structured interviews and open-ended survey items. Data will be triangulated to find convergence or agreement by cross-validating results to produce a contextualized portrayal of the facilitators and barriers to implementation and use of the intervention. DISCUSSION: By applying mixed research methods and measuring context, facilitators and barriers, and individual, organizational and data quality factors that may impact adoption and utilization of the intervention, we will document whether and how the intervention streamlines provider-based manual reporting workflows, lowers barriers to reporting, increases data completeness, improves reporting timeliness and captures a greater portion of communicable disease burden in the community.

Indexed as

Clinical Laboratory Information SystemsClinical Trials as TopicElectronic Health RecordsHealth Information SystemsHumansInformation DisseminationPopulation SurveillancePublic Health SurveillanceResearch Design

Identifiers

PMID24171799
PMCPMC3819468

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.