Abstract
BACKGROUND: Implementation rates of interventions known to be beneficial for people with diabetes mellitus are often suboptimal. Computer-aided decision support systems (CDSSs) can improve these rates. The complexity of establishing a fully integrated electronic medical record that provides decision support, however, often prevents their use. OBJECTIVE: To develop a CDSS for diabetes care that can be easily introduced into primary care settings and diabetes clinics. THE SYSTEM: The CDSS uses fax-machine-based optical character recognition software for acquiring patient information. Simple, 1-page paper forms, completed by patients or health practitioners, are faxed to a central location. The information is interpreted and recorded in a database. This initiates a routine that matches the information against a knowledge base so that patient-specific recommendations can be generated. These are formatted and faxed back within 4-5 minutes. IMPLEMENTATION: The system is being introduced into 2 diabetes clinics. We are collecting information on frequency of use of the system, as well as satisfaction with the information provided. CONCLUSION: Computer-aided decision support can be provided in any setting with a fax machine, without the need for integrated electronic medical records or computerized data-collection devices.
Full text
PDF




Selected References
These references are in PubMed. This may not be the complete list of references from this article.
- Davis D. A., Thomson M. A., Oxman A. D., Haynes R. B. Changing physician performance. A systematic review of the effect of continuing medical education strategies. JAMA. 1995 Sep 6;274(9):700–705. doi: 10.1001/jama.274.9.700. [DOI] [PubMed] [Google Scholar]
- Haynes R. B. Loose connections between peer-reviewed clinical journals and clinical practice. Ann Intern Med. 1990 Nov 1;113(9):724–728. doi: 10.7326/0003-4819-113-9-724. [DOI] [PubMed] [Google Scholar]
- Hunt D. L., Haynes R. B., Hanna S. E., Smith K. Effects of computer-based clinical decision support systems on physician performance and patient outcomes: a systematic review. JAMA. 1998 Oct 21;280(15):1339–1346. doi: 10.1001/jama.280.15.1339. [DOI] [PubMed] [Google Scholar]
- Johnson S. B. Methodological issues in diabetes research. Measuring adherence. Diabetes Care. 1992 Nov;15(11):1658–1667. doi: 10.2337/diacare.15.11.1658. [DOI] [PubMed] [Google Scholar]
- Jørgensen C. K., Karlsmose B. Validation of automated forms processing. A comparison of Teleform with manual data entry. Comput Biol Med. 1998 Nov;28(6):659–667. doi: 10.1016/s0010-4825(98)00038-9. [DOI] [PubMed] [Google Scholar]
- Kravitz R. L., Hays R. D., Sherbourne C. D., DiMatteo M. R., Rogers W. H., Ordway L., Greenfield S. Recall of recommendations and adherence to advice among patients with chronic medical conditions. Arch Intern Med. 1993 Aug 23;153(16):1869–1878. [PubMed] [Google Scholar]
- McDonald C. J. The barriers to electronic medical record systems and how to overcome them. J Am Med Inform Assoc. 1997 May-Jun;4(3):213–221. doi: 10.1136/jamia.1997.0040213. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Orme C. M., Binik Y. M. Consistency of adherence across regimen demands. Health Psychol. 1989;8(1):27–43. doi: 10.1037//0278-6133.8.1.27. [DOI] [PubMed] [Google Scholar]
- Weiner J. P., Parente S. T., Garnick D. W., Fowles J., Lawthers A. G., Palmer R. H. Variation in office-based quality. A claims-based profile of care provided to Medicare patients with diabetes. JAMA. 1995 May 17;273(19):1503–1508. doi: 10.1001/jama.273.19.1503. [DOI] [PubMed] [Google Scholar]
