| Literature DB >> 23216866 |
Murali Sambasivan1, Pouyan Esmaeilzadeh, Naresh Kumar, Hossein Nezakati.
Abstract
BACKGROUND: Computer-based clinical decision support systems (CDSS) are regarded as a key element to enhance decision-making in a healthcare environment to improve the quality of medical care delivery. The concern of having new CDSS unused is still one of the biggest issues in developing countries for the developers and implementers of clinical IT systems. The main objectives of this study are to determine whether (1) the physician's perceived professional autonomy, (2) involvement in the decision to implement CDSS and (3) the belief that CDSS will improve job performance increase the intention to adopt CDSS. Four hypotheses were formulated and tested.Entities:
Mesh:
Year: 2012 PMID: 23216866 PMCID: PMC3519751 DOI: 10.1186/1472-6947-12-142
Source DB: PubMed Journal: BMC Med Inform Decis Mak ISSN: 1472-6947 Impact factor: 2.796
Figure 1Theoretical Framework.
Cronbach’s Alpha (CR) and Composite reliability (COMP) of constructs (diagonal of the matrix contains the Average Variance Extracted (AVE) and off-diagonal elements are the squared correlations between constructs)
| INTENTION | 0.850 | 0.830 | 0.630 | | | | |
| INVOLVEMENT | 0.913 | 0.870 | 0.162 | 0.640 | | | |
| PERCEIVED THREAT | 0.890 | 0.890 | 0.223 | 0.016 | 0.670 | | |
| EFFORT EXPECTANCY | 0.900 | 0.930 | 0.274 | 0.108 | 0.038 | 0.700 | |
| PERFORMANCE EXPECTANCY | 0.920 | 0.930 | 0.209 | 0.108 | 0.019 | 0.489 | 0.700 |
Figure 2Structural model results.
Demographic Characteristics of Respondents
| Gender | Male | 144 | 46.6 |
| Female | 156 | 53.4 | |
| Age | 20-29 | 36 | 11.7 |
| 30-39 | 161 | 52.1 | |
| 40-49 | 75 | 24.3 | |
| 50-59 | 26 | 8.4 | |
| 60-69 | 10 | 3.2 | |
| Over 70 | 1 | 0.3 | |
| Working Experience | 1-5 | 74 | 23.0 |
| 6-10 | 95 | 30.0 | |
| 11-20 | 102 | 33.0 | |
| 21-30 | 25 | 9.0 | |
| Over 30 | 13 | 5.0 | |
| Specialty Areas | Anesthesiologist | 27 | 8.7 |
| Geriatric | 21 | 6.8 | |
| Gen Prac | 45 | 14.6 | |
| Gynecologist | 34 | 11.0 | |
| Internist | 33 | 10.7 | |
| Pathologist | 24 | 7.8 | |
| Pediatric | 39 | 12.6 | |
| Psychiatrist | 19 | 6.1 | |
| Radiologist | 22 | 7.1 | |
| Surgeon | 45 | 14.6 | |
| Level of familiarity with Clinical IT | Very low | 16 | 5.2 |
| Low | 70 | 22.7 | |
| Moderate | 173 | 56.0 | |
| High | 46 | 14.8 | |
| Very High | 4 | 1.3 | |
| Past experience in using CDSS | High | 32 | 10.4 |
| Little/No | 277 | 89.6 | |
| Type of Hospital | Public | 204 | 66.0 |
| Private | 105 | 34.0 |
Descriptive statistics of constructs
| INT | 3.5129 | 0.82439 | 1.00 | .403* | -.472* | .523* | .457* |
| INV | 2.8786 | 0.99728 | | 1.00 | -.125 | .328* | .328* |
| THREAT | 3.1489 | 0.91062 | | | 1.00 | -.139 | -.196 |
| EE | 3.1126 | 0.79968 | | | | 1.00 | .699* |
| PE | 3.7238 | 0.66066 | 1.00 | ||||
*significant at 0.01 significance level.
Legend: EE – Effort Expectancy, PE – Performance Expectancy.