Evidence map›Paper›PMID 23612390›Full record

ArticleInteractive journal of medical research2013

Understanding electronic medical record adoption in the United States: communication and sociocultural perspectives.

Priya Nambisan, Gary L Kreps, Stan Polit

Abstract read
In one paragraph

Article in Interactive journal of medical research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. 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.

Priya NambisanGeorge Mason University, Department of Health Administration & Policy, Fairfax, VA, United States. pnambisa@gmu.edu.
Gary L Kreps
Stan Polit

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis paper adopts a communication and sociocultural perspective to analyze the factors behind the lag in electronic medical record (EMR) adoption in the United States. Much of the extant research on this topic has emphasized economic factors, particularly, lack of economic incentives, as the primary cause of the delay in EMR adoption. This prompted the Health Information Technology on Economic and Clinical Health Act that allow financial incentives through the Centers of Medicare and Medicaid Services for many health care organizations planning to adopt EMR. However, financial incentives alone have not solved the problem; many new innovations do not diffuse even when offered for free. Thus, this paper underlines the need to consider communication and sociocultural factors to develop a better understanding of the impediments of EMR adoption.

objectiveThe objective of this paper was to develop a holistic understanding of EMR adoption by identifying and analyzing the impact of communication and sociocultural factors that operate at 3 levels: macro (environmental), meso (organizational), and micro (individual).

methodsWe use the systems approach to focus on the 3 levels (macro, meso, and micro) and developed propositions at each level drawing on the communication and sociocultural perspectives.

resultsOur analysis resulted in 10 propositions that connect communication and sociocultural aspects with EMR adoption.

conclusionsThis paper brings perspectives from the social sciences that have largely been missing in the extant literature of health information technology (HIT) adoption. In doing so, it implies how communication and sociocultural factors may complement (and in some instances, reinforce) the impact of economic factors on HIT adoption.

Indexed as

communicationelectronic health records adoptionsystems approach

Identifiers

PMID23612390
PMCPMC3628120

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.