| Title |
Critical factors influencing physicians’ intention to use computerized clinical practice guidelines: an integrative model of activity theory and the technology acceptance model
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, January 2016
|
| DOI | 10.1186/s12911-016-0241-3 |
| Pubmed ID | |
| Authors |
Ju-Ling Hsiao, Rai-Fu Chen |
| Abstract |
With the widespread use of information communication technologies, computerized clinical practice guidelines are developed and considered as effective decision supporting tools in assisting the processes of clinical activities. However, the development of computerized clinical practice guidelines in Taiwan is still at the early stage and acceptance level among major users (physicians) of computerized clinical practice guidelines is not satisfactory. This study aims to investigate critical factors influencing physicians' intention to computerized clinical practice guideline use through an integrative model of activity theory and the technology acceptance model. The survey methodology was employed to collect data from physicians of the investigated hospitals that have implemented computerized clinical practice guidelines. A total of 505 questionnaires were sent out, with 238 completed copies returned, indicating a valid response rate of 47.1 %. The collected data was then analyzed by structural equation modeling technique. The results showed that attitudes toward using computerized clinical practice guidelines (γ = 0.451, p < 0.001), organizational support (γ = 0.285, p < 0.001), perceived usefulness of computerized clinical practice guidelines (γ = 0.219, p < 0.05), and social influence (γ = 0.213, p < 0.05) were critical factors influencing physicians' intention to use computerized clinical practice guidelines, and these factors can explain 68.6 % of the variance in intention to use computerized clinical practice guidelines. This study confirmed that some subject (human) factors, environment (organization) factors, tool (technology) factors mentioned in the activity theory should be carefully considered when introducing computerized clinical practice guidelines. Managers should pay much attention on those identified factors and provide adequate resources and incentives to help the promotion and use of computerized clinical practice guidelines. Through the appropriate use of computerized clinical practice guidelines, the clinical benefits, particularly in improving quality of care and facilitating the clinical processes, will be realized. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 193 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Norway | 1 | <1% |
| Unknown | 192 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 34 | 18% |
| Student > Ph. D. Student | 27 | 14% |
| Researcher | 15 | 8% |
| Lecturer | 13 | 7% |
| Student > Doctoral Student | 13 | 7% |
| Other | 36 | 19% |
| Unknown | 55 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Business, Management and Accounting | 33 | 17% |
| Medicine and Dentistry | 32 | 17% |
| Computer Science | 17 | 9% |
| Nursing and Health Professions | 16 | 8% |
| Social Sciences | 9 | 5% |
| Other | 21 | 11% |
| Unknown | 65 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 January 2016.
All research outputs
#14,705,554
of 22,840,638 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,216
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Outputs of similar age
#215,594
of 392,526 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#24
of 35 outputs
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