OBJECTIVE
Given the slow adoption of medical informatics in Hong Kong and Asia, we sought to understand the contributory barriers and potential incentives associated with information technology implementation.
DESIGN AND MEASUREMENTS
A representative sample of 949 doctors (response rate = 77.0%) was asked through a postal survey to rank a list of nine barriers associated with clinical computerization according to self-perceived importance. They ranked seven incentives or catalysts that may influence computerization. We generated mean rank scores and used multidimensional preference analysis to explore key explanatory dimensions of these variables. A hierarchical cluster analysis was performed to identify homogenous subgroups of respondents. We further determined the relationships between the sets of barriers and incentives/catalysts collectively using canonical correlation.
RESULTS
Time costs, lack of technical support and large capital investments were the biggest barriers to computerization, whereas improved office efficiency and better-quality care were ranked highest as potential incentives to computerize. Cost vs. noncost, physician-related vs. patient-related, and monetary vs. nonmonetary factors were the key dimensions explaining the barrier variables. Similarly, within-practice vs external and "push" vs "pull" factors accounted for the incentive variables. Four clusters were identified for barriers and three for incentives/catalysts. Canonical correlation revealed that respondents who were concerned with the costs of computerization also perceived financial incentives and government regulation to be important incentives/catalysts toward computerization. Those who found the potential interference with communication important also believed that the promise of improved care from computerization to be a significant incentive.
CONCLUSION
This study provided evidence regarding common barriers associated with clinical computerization. Our findings also identified possible incentive strategies that may be employed to accelerate uptake of computer systems.
[1]
F. Sullivan,et al.
A descriptive feast but an evaluative famine: systematic review of published articles on primary care computing during 1980-97
,
2001,
BMJ : British Medical Journal.
[2]
K. Bowles.
The barriers and benefits of nursing information systems.
,
1997,
Computers in nursing.
[3]
B. Everitt,et al.
Cluster Analysis (2nd ed).
,
1982
.
[4]
Steve Dewar,et al.
The I in the new CHAI
,
2002,
BMJ : British Medical Journal.
[5]
K. B. Johnson.
Barriers that impede the adoption of pediatric information technology.
,
2001,
Archives of pediatrics & adolescent medicine.
[6]
P. Sopp.
Cluster analysis.
,
1996,
Veterinary immunology and immunopathology.
[7]
Joan S. Ash,et al.
Research Paper: Organizational Factors that Influence Information Technology Diffusion in Academic Health Sciences Centers
,
1997,
J. Am. Medical Informatics Assoc..
[8]
Richard A. Johnson,et al.
Applied Multivariate Statistical Analysis
,
1983
.
[9]
Lai Ming Ho,et al.
Physicians' attitudes towards the computerization of clinical practice in Hong Kong: a population study
,
2002,
Int. J. Medical Informatics.
[10]
Lai Ming Ho,et al.
Computerization of clinical practice in Hong Kong
,
2001,
Int. J. Medical Informatics.
[11]
Nancy M. Lorenzi,et al.
Barriers and Resistance to Informatics in Behavioral Health
,
2001,
MedInfo.