Evidence map›Paper›PMID 11936958›Full record

ArticleBMC medical informatics and decision making2002

Selecting information technology for physicians' practices: a cross-sectional study.

Karen Beekman Eden

Abstract readComparative StudyValidation Study
In one paragraph

Article in BMC medical informatics and decision making, 2002. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

1 author.

Karen Beekman EdenDivision of Medical Informatics and Outcomes Research, Oregon Health Sciences University, BICC, 3181 S,W, Sam Jackson Park Road, Portland, OR 97201-3098, USA. edenk@ohsu.edu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany physicians are transitioning from paper to electronic formats for billing, scheduling, medical charts, communications, etc. The primary objective of this research was to identify the relationship (if any) between the software selection process and the office staff's perceptions of the software's impact on practice activities.

methodsA telephone survey was conducted with office representatives of 407 physician practices in Oregon who had purchased information technology. The respondents, usually office managers, answered scripted questions about their selection process and their perceptions of the software after implementation.

resultsMultiple logistic regression revealed that software type, selection steps, and certain factors influencing the purchase were related to whether the respondents felt the software improved the scheduling and financial analysis practice activities. Specifically, practices that selected electronic medical record or practice management software, that made software comparisons, or that considered prior user testimony as important were more likely to have perceived improvements in the scheduling process than were other practices. Practices that considered value important, that did not consider compatibility important, that selected managed care software, that spent less than 10,000 dollars, or that provided learning time (most dramatic increase in odds ratio, 8.2) during implementation were more likely to perceive that the software had improved the financial analysis process than were other practices.

conclusionPerhaps one of the most important predictors of improvement was providing learning time during implementation, particularly when the software involves several practice activities. Despite this importance, less than half of the practices reported performing this step.

Indexed as

Computer Communication NetworksCross-Sectional StudiesData CollectionDecision Support TechniquesGroup PracticeHumansLogistic ModelsOregonPersonnel Staffing and Scheduling Information SystemsPractice Patterns, Physicians'Predictive Value of TestsPrivate PracticeSoftware

Identifiers

PMID11936958
PMCPMC102764

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.