Information Technology Can Enhance Quality in Regional Health Delivery

N. Maglaveras; I. Chouvarda; V. Koutkias; S. Meletiadis; K. Haris; E. A. Balas

doi:10.1055/s-0038-1634368

Methods of Information in Medicine, Table of Contents

Methods Inf Med 2002; 41(05): 393-400
DOI: 10.1055/s-0038-1634368

Original Article

Schattauer GmbH

Information Technology Can Enhance Quality in Regional Health Delivery

Authors

N. Maglaveras

¹Aristotelian University, The Medical School, Lab of Medical Informatics Thessaloniki, Macedonia, Greece
I. Chouvarda

¹Aristotelian University, The Medical School, Lab of Medical Informatics Thessaloniki, Macedonia, Greece
V. Koutkias

¹Aristotelian University, The Medical School, Lab of Medical Informatics Thessaloniki, Macedonia, Greece
S. Meletiadis

¹Aristotelian University, The Medical School, Lab of Medical Informatics Thessaloniki, Macedonia, Greece
K. Haris

¹Aristotelian University, The Medical School, Lab of Medical Informatics Thessaloniki, Macedonia, Greece
E. A. Balas

²Center for Health Care Quality, University of Missouri, Columbia MO, USA

Abstract

Summary

Objectives: a) The use of information technology (IT) based solutions for quality health delivery in regional health information networks and the study of the enabling factors for their use in a regional health care network from key classes of users such as the medical personnel and the citizens. b) Identification of potential technologies for usage from all citizens and health providers in a regional environment, in all aspects of everyday life. c) Presentation of a generic user model for reference when developing and assessing IT based health delivery solutions.

Methods: After defining the major questions to be addressed, an overview of tele-health and tele-medicine technologies and solutions currently available shall be presented. Further, a generic user model applied to the use of IT based regional health delivery solutions both for the daily life and home care, and for research and clinical routine purposes are presented. Enabling technologies for integration of different IT modules, medical data processing and management procedures and the wireless application protocol (WAP) technology is discussed.

Results: Different levels of user applications are presented such as mobile telephony driven health information monitoring and systems integrating electronic health care records with multimedia medical information management and processing modules.

Conclusions: Although IT solutions are advanced and continue to evolve, still the user acceptance and user friendliness issues are unresolved. Mobile telecommunication solutions however may hold the key for wide scale implementation of IT solutions in regional health information networks and increased quality of health services.

Keywords

Information technology - telecare - medical information processing - computer patient record - regional health information network

Full Text

References

REFERENCES
1 Collen MF. Historical evolution of preventive medical informatics in the USA. Meth Inform Med 2000; 39 (Suppl. 03) 204-7.
2 Borowitz SM, Wyatt JC. The origin, content, and workload of E-mail consultations. JAMA 1998; 280: 1321-4.
3 Balas EA, Iakovidis I. Distance technologies for patient monitoring. BMJ 1999; 319 7220 1309.
4 Balas EA, Weingarten S, Garb CT. et al. Improving preventive care by prompting physicians. Arch Intern Med 2000; 160 (Suppl. 03) 301-8.
5 Altman DG, Goodman SN. Transfer of technology from statistical journals to the biomedical literature. Past trends and future predictions. JAMA 1994; 272 (Suppl. 02) 129-32.
6 Wilson Smith JS, Dahle KL, Ingersoll GL. Impact of home health care on health care costs and hospitalisation frequency in patients with heart failure. Am J Cardiol 1999; 83: 615-7.
7 Cordisco ME, Beniaminovitz A, Hammond K, Mancini D. Use of telemonitoring to decrease the rate of hospitalization in patients with severe congestive heart failure. Am J Cardiol 1999; 84: 860-2.
8 Horowitz JD. Home-based intervention: the next step in treatment of chronic heart failure?. Eur Heart J 2000; 21: 1807-9.
9 van Ginneken AM, Stam H, van Mulligen EM. et al. ORCA: The Versatile CPR. Methods Inf Med 1999; 38: 332-8.
10 Barnett GO. The application of computer-based medical-record systems in ambulatory practice. N Engl J Med 1984; 310: 1643-50.
11 Van der Lei J, Duisterhout JS, Westerhof HP. et al. The introduction of computer-based patient records in The Netherlands. Ann Intern Med 1993; 119: 1036-41.
12 de Groen PC, Barry JA, Schaller WJ. Applying World-Wide-Web technology to the study of patients with rare diseases. Ann Int Med 1998; 129: 107-13.
13 Maglaveras N, Koutkias V, Meletiadis S. et al. The role of wireless technology in home care delivery. Proc MEDINFO 2001, IOS Press; 2001: 835-9.
14 Flahaut A, Dias-Ferrao V, Chaberty P. et al. FluNet as a tool for global monitoring of Influenza on the Web. JAMA 1998; 280: 1330-2.
15 van Bemmel JH, van Ginneken AM. et al. Integration and Communication for the Continuity of Cardiac Care (I4C). J Electrocardiology 1998; 31 suppl 60-8.
16 Haris K, Efstratiadis S. Maglaveras, et al. Model-based Morphological Segmentation and Labeling of Coronary Angiograms. IEEE Trans on Medical Imaging 1999; 18 (Suppl. 10) 1003-15.
17 Eysenbach G, Diepgen TL. Patients looking for information on the INTERNET and seeking teleadvice. Arch Dermatol 1999; 135: 151-6.
18 Schiff GD, Rucker D. Computerized prescribing: Building the electronic infrastructure for better medication usage. JAMA 1998; 279: 1024-9.
19 Al-Ahmad W, Willems JL, Rubel P. ECG data interchange within the framework of the SCP-ECG and the OEDIPE projects. Computers in Cardiology. IEEE Comp Soc Press; 1994: 337-42.
20 Maglaveras N, Stamkopoulos T, Pappas C, Strintzis M. An adaptive back-propagation neural network for real-time ischemia episodes detection. Development and performance analysis using the European ST-T database. IEEE Trans Biomed Engng 1998; 45 (Suppl. 07) 405-13.
21 Maglaveras N, Stamkopoulos T, Diamantaras KI, Pappas C, Strintzis M. ECG pattern recognition and classification using non-linear transformations and neural networks: A review. International Journal of Medical Informatics 1998; 52: 191-208.
22 Haris K, Efstratiadis SN, Maglaveras N, Katsaggelos A. A hybrid image segmentation algorithm using watersheds and hierarchical region merging. IEEE Trans Image Proc 1998; 7 (Suppl. 12) 1684-99.
23 Haris K, Efstratiadis SN, Maglaveras N. et al. Coronary Artery Skeleton Detection Based on Topographic Features. Proc MIE97, IOS Press; 1997: 512-6.
24 Haris K, Efstratiadis SN, Maglaveras N. et al. Coronary Arterial Tree Extraction Based on Artery Tracking and Mathematical Morphology. Computers In Cardiology. IEEE Comp Soc Press; 1998: 769-72.
25 Dodge JT, Brown G, Bolson E, Dodge HT. Lumen Diameter of Normal Human Coronary Arteries: Influence of Age, Sex, Anatomic Variation, and Left Ventricular Hypertrophy or Dilation. Circulation 1992; 86 (Suppl. 01) 232-46.
26 Yates RD, Mandayam NB. Challenges in low-cost wireless data transmission. IEEE Signal Processing Magazine 2000; 17 (Suppl. 03) 93-102.