Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Medical Informatics: Improving Health Care Through Information

Medical Informatics: Improving Health Care Through Information Health care is an information-based science. Much of clinical practice involves gathering, synthesizing, and acting on information. Medical informatics is the field concerned with the management and use of information in health and biomedicine. This article focuses on the problems that motivate work in this field, the emerging solutions, and the barriers that remain. It also addresses the core themes that underlie all applications of medical informatics and unify the scientific approaches across the field. There is a growing concern that information is not being used as effectively as possible in health care. Recent reports from the Institute of Medicine have reviewed research findings related to information use and expressed concerns about medical errors and patient safety,1 the quality of medical records,2 and the protection of patient privacy and confidentiality.3 The latest Institute of Medicine report on this topic ties all these problems and potential solutions together in a vision for a health care system that is safe, patient-centered, and evidence-based.4 A variety of solutions is required to address the information-related problems in health care; many solutions involve the use of computers and computer-related technologies. The Field of Medical Informatics Medical informatics is a heterogeneous field, composed of individuals with diverse backgrounds and levels of training. Although virtually all health science universities have some entity with the word "informatics" in its title, there are fewer than 25 that carry out research in medical informatics and offer educational programs.5 At some institutions, medical informatics is viewed as a service (eg, helping clinicians implement informatics applications), but it is more appropriately considered a science that addresses how best to use information to improve health care. The government leader in funding research and education in medical informatics has been the National Library of Medicine (http://www.nlm.nih.gov). Some have argued that the adjective medical in front of informatics is inappropriate because it implies the work of physicians and not the remainder of health care and biomedical science. However, this name has achieved widespread usage. In the article by Kukafka et al,6 Shortliffe described medical informatics as the broad term representing the core theories, concepts, and techniques of information applications in health and biomedicine, with the other adjectives preceding the word informatics denoting the specific application area (Box). Core themes that emerge from informatics science (standards, terminology, usability, and demonstrated value) are relevant across all levels of medical informatics, not solely clinical informatics. Box. The 4 Levels of Medical Informatics and Their Respective Foci From the Cell to the Population* Bioinformatics—molecular and cellular processes, such as gene sequences and maps Imaging informatics—tissues and organs, such as radiology imaging systems Clinical informatics—clinicians and patients, including applications of nursing, dentistry, and other clinical specialties Public health informatics—populations, such as disease surveillance systems *Adapted from Kukafka et al.6 Applications of Clinical Informatics There is a variety of classification types for the different applications of clinical informatics; one approach is by the type of information used. There are essentially 2 types of information used in clinical informatics: patient-specific and knowledge-based. Patient-specific information is generated by and used in the care of patients in the clinical setting, whereas knowledge-based information comprises the scientific basis of health care. Electronic Medical Records The core application using patient-specific information is the electronic medical record (EMR). The paper-based medical record has its tradition and virtues; however, research has shown it can be illegible, incomplete, difficult to access in more than one place, and insecure from unauthorized uses and users.2 Although the EMR overcomes some of these problems, there are challenges to implementing the EMR at the levels of the individual and the organization. The main challenge to individual use of the EMR has been its integration into the busy clinical workflow. The few studies that have been performed show computerized physician order entry (CPOE) adds time for the clinician, although other time savings are usually gained elsewhere through error reduction or the automation brought about by other features of the EMR (eg, accessing test results).7-9 A related challenge is determination of the optimal computing device for the clinical setting. Handheld computers (also called personal digital assistants) are increasingly popular, as documented by their use by internal medicine10 and family practice physicians.11 While their portability is of great value, most usage has focused on entry and retrieval of simple data (eg, prescription writing and drug information) and it is unclear whether other usage (eg, image viewing and literature access) is amenable to these portable devices or whether larger devices might be required. At the organizational level, the key challenges have been managing complex informatics applications and the computer networks upon which they run. Although individual computers are relatively inexpensive, maintaining large networks of them and training the myriad of health care workers who use them are not. Berg12 has noted that the interpersonal challenges to large organizations in implementing EMRs is much more daunting than managing the technology itself. Research has shown that involving users in the implementation process and providing features of benefit to them, such as time-saving measures like specialty-specific order sets, widespread implementation across the organization, and engaging the clinical leadership, are the most important keys to success.13 Organizational challenges are not limited to hospitals and other large institutions. A particular problem in the outpatient setting is that small practices usually lack the minimal technical capabilities and financial resources necessary to implement EMRs.14 A final challenge to all involved with the EMR is the protection of patient privacy and confidentiality, with the Health Insurance Portability and Accountability Act legislating their protection at substantial cost and effort.15 Information Retrieval The field concerned with the organization and retrieval of knowledge-based information (not limited to medicine) is called information retrieval.16 This area has seen tremendous growth due to the Internet and World Wide Web. More than 50% of the US population uses the Web regularly, and of those who do, more than 50% search for personal health information.17 Physicians have embraced the Web as well, with 90% using it on a regular basis.18 A large variety of online resources are now available to both patients and physicians. The oldest of these is MEDLINE, the bibliographic database of journal literature with more than 11 million references to approximately 4000 journals dating from 1966.19 Produced by the US National Library of Medicine, MEDLINE is freely available to the entire world via the PubMed system on the National Library of Medicine Web site (http://pubmed.gov). Bibliographic databases only contain titles and abstracts of articles; however, users increasingly want the full text of journals online. The technical challenge of producing such journals has been supplanted by the economic question of how to increase availability when electronic publication is cheaper (ie, less printing and mailing costs) but still has some cost (due to value added in editing and production).20 Another challenge is how to improve users' abilities to use such systems, as a systematic review has shown physicians do not always achieve optimal results with them.21 In addition to the journal literature, other knowledge-based information is available on the Web, including many of the traditional medical textbooks, clinical practice guidelines (National Guidelines Clearinghouse [http://guideline.gov]), and a growing number of Web sites aimed at patients and consumers, many of which can be found using the National Library of Medicine's MedlinePlus database (http://medlineplus.gov). One concern about Web sites is their quality, as peer-review mechanisms that normally control print literature are often not present, and sites purporting to provide balanced views may well be promoting a point of view or a product to sell.22 Concomitant with the growth of online information resources has been the emergence of tools to use them more effectively. Probably the most important of these is evidence-based medicine.23 The original focus of evidence-based medicine was to train clinicians to find and critically appraise individual studies. Few clinicians have ready access or the time required to search MEDLINE, read articles, and synthesize their findings in the busy clinical setting. As a result, the focus has changed toward approaches that provide highly concise information in the context of the specific patient and clinical problem.24 This has led to a change in the emphasis of evidence-based medicine toward the production of syntheses of clinical topics and concise synopses of their findings.25 Decision Support Systems One clinical informatics application, the decision support system, crosses the boundary of patient-specific and knowledge-based information. These applications, which apply knowledge to patient data, emerged from artificial intelligence and expert system research in the 1970s and 1980s that attempted to model the clinical diagnostician. However, the goal of building an electronic diagnostician never materialized and the resulting systems were too time-consuming for use in the clinical setting.26 These applications have reemerged in the form of decision support systems, which are embedded in the EMR and aim to detect critical situations and errors in care and then notify the clinician, provide appropriate information accordingly, or both.27 Several systematic reviews have documented the effectiveness of decision support applications within the EMR. A variety of approaches, including reminders that increase adherence with ordering preventive measures, hospital admission order sets and display of costs, and interventions to detect medication prescribing errors, has been found beneficial.28-30 Additional work has demonstrated the value of clinical practice guidelines to standardize care.31 One interesting finding of decision support systems applications is that their benefits do not appear to be educational (ie, they do not result in clinicians learning how to provide better care). This is illustrated by the fact that when decision support systems applications are removed, the adherence to specific recommendations returns to the presystem baseline.32 Decision support systems provide timely reminders for busy clinicians. Core Themes There are a number of core themes that underlie medical informatics, not limited to clinical informatics: standards, terminology, usability, and demonstrated value. As most applications in medical informatics interact with others in a federation of different systems, standards are essential to facilitate integration of data, especially across systems from different vendors.33 One area in which standards are particularly important is terminology.34 While most individuals know that an upper respiratory tract infection, a cold, and a viral syndrome are similar, computers do not inherently know this. If the benefits of data aggregation are to be achieved (eg, comparing patient outcomes and resource utilization across practices, institutions, and regions), then standard terminology is essential. Standardizing the structure of clinical documents will also make aggregation and movement of data across systems easier.35 Another core theme in medical informatics is usability. Systems must be integrated into the clinical workflow and demonstrate other benefits when they require more time or effort on the part of the user. One example of research focused on usability found that a CPOE system that allowed physicians to type in orders in free text and mapped them to known order sets was faster and more acceptable than a standard system based on a point-and-click interface.36 Related to usability is the need to demonstrate value. One study of CPOE demonstrated that use of guidelines and dose selection menus resulted in significantly increased adherence to prescribing regimens known to optimize patient safety and reduce cost.37 Future Directions Although considerable challenges remain, the impact of medical informatics will certainly grow. The imperatives of improving documentation, reducing error, and empowering patients will continue to motivate use of information technology in health care. There is plenty of evidence that clinical informatics applications can address these imperatives to enhance patient outcomes, reduce costs, and provide access to knowledge. Evidence alone will not be enough to ensure their widespread adoption. For example, one concern is that most of the studies documenting the effectiveness of decision support have been carried out in academic medical centers with institution-specific EMRs and may not be generalizable. Another concern is that while the correction of a small number of clinical anomalies (eg, improper drug doses) is feasible, the increase of this process might lead to cognitive overload of the clinician. It is also too early to know the true cost of widespread use of these applications.38 The optimal use of clinical informatics applications will require some reengineering of the health care system. It will be crucial for the medical informatics field to account for the needs and concerns of all parties who participate in the process: patients, clinicians, payers, and governments. Clinicians will have to accept some impact on their practices, particularly as the individual physician becomes more accountable to document increasingly expensive care and demonstrate avoidance of error. They will have to accept CPOE, because this is the only place to effectively apply decision support. Society as a whole will need to determine who will pay the costs of EMRs and CPOE, because even if they save money in the long term, the up-front investment will be substantial. The key challenge across all applications will be adherence to the basic goals of the science of medical informatics: developing systems that are easy to use and provide demonstrable benefit. References 1. Kohn LT, Corrigan JM, Donaldson MS. To Err Is Human: Building a Safer Health System. Washington, DC: National Academy Press; 2000. 2. Dick RS, Steen EB, Detmer DE. The Computer-Based Patient Record: An Essential Technology for Health Care, Revised Edition. Washington, DC: National Academy Press; 1997. 3. For the Record: Protecting Electronic Health Information. Washington, DC: National Academy Press; 1997. 4. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: National Academy Press; 2001. 5. American Medical Informatics Association. Resource Center: Academic & Training Programs. Available at: http://www.amia.org/resource/acad&training/f1.html. Accessed April 15, 2002. 6. Kukafka R, O'Carroll PW, Gerberding JL. et al. Issues and opportunities in public health informatics: a panel discussion. J Public Health Manag Pract.2001;7:31-42.Google Scholar 7. Bates DW, Boyle DL, Teich JM. Impact of Computerized Physician Order Entry on Physician Time: Proceedings of the 18th Annual Symposium on Computer Applications in Medical Care, 1994. Washington, DC: Heinley & Belfus; 1994:996. 8. Shu K, Boyle D, Spurr C. et al. Comparison of time spent writing orders on paper with computerized physician order entry. Medinfo.2001;10:1207-1211.Google Scholar 9. Overhage JM, Perkins S, Tierney WM, McDonald CJ. Controlled trial of direct physician order entry: effects on physicians' time utilization in ambulatory primary care internal medicine practices. J Am Med Inform Assoc.2001;8:361-371.Google Scholar 10. American College of Physicians, American Society of Internal Medicine. ACP-ASIM survey finds nearly half of US members use handheld computers. Available at: http://www.acponline.org/college/pressroom/handheld_survey.htm. Accessed April 15, 2002. 11. Criswell DF, Parchman ML. Handheld computer use in US Family Practice residency programs. J Am Med Inform Assoc.2002;9:80-86.Google Scholar 12. Berg M. Implementing information systems in health care organizations: myths and challenges. Int J Med Inf.2001;64:143-156.Google Scholar 13. Ahmad A, Teater P, Bentley TD. et al. Key attributes of a successful physician order entry system implementation in a multi-hospital environment. J Am Med Inform Assoc.2002;9:16-24.Google Scholar 14. Wager KA, Lee FW, White AW. et al. Impact of an electronic medical record system on community-based primary care practices. J Am Board Fam Pract.2000;13:338-348.Google Scholar 15. Gostin LO. National health information privacy: regulations under the Health Insurance Portability and Accountability Act. JAMA.2001;285:3015-3021.Google Scholar 16. Hersh WR. Information Retrieval: A Health Care Perspective. 2nd ed. New York, NY: Springer Verlag; 2002. 17. Fox S, Rainie L. The online health care revolution: how the Web helps Americans take better care of themselves. Available at: http://www.pewinternet.org/reports/pdfs/PIP_Health_Report.pdf. Accessed April 15, 2002. 18. Taylor H, Leitman R. The increasing impact of eHealth on physician behavior. Available at: http://www.harrisinteractive.com/news/newsletters/healthnews/HI_HealthCareNews2001Vol1_iss31.pdf. Accessed April 15, 2002. 19. Wood EH. MEDLINE: the options for health professionals. J Am Med Inform Assoc.1994;1:372-380.Google Scholar 20. Hersh WR, Rindfleisch TC. Electronic publishing of scholarly communication in the biomedical sciences. J Am Med Inform Assoc.2000;7:324-325.Google Scholar 21. Hersh WR, Hickam DH. How well do physicians use electronic information retrieval systems? JAMA.1998;280:1347-1352.Google Scholar 22. Silberg WM, Lundberg GD, Musacchio RA. Assessing, controlling, and assuring the quality of medical information on the Internet. JAMA.1997;277:1244-1245.Google Scholar 23. Sackett DL, Richardson WL, Rosenberg W, Haynes RB. Evidence-Based Medicine: How to Practice and Teach EBM. New York, NY: Churchill Livingstone; 2000. 24. Chueh H, Barnett GO. "Just-in-time" clinical information. Acad Med.1997;72:512-517.Google Scholar 25. Haynes RB. Of studies, syntheses, synopses, and systems: the "4S" evolution of services for finding current best evidence. ACP J Club.2001;134:A11-A13.Google Scholar 26. Miller RA. Medical diagnostic decision support systems—past, present, and future. J Am Med Inform Assoc.1994;1:8-27.Google Scholar 27. Bates DW, Cohen M, Leape LL. et al. Reducing the frequency of errors in medicine using information technology. J Am Med Inform Assoc.2001;8:299-308.Google Scholar 28. Hunt DL, Haynes RB, Hanna SE, Smith K. Effects of computer-based clinical decision support systems on physician performance and patient outcomes. JAMA.1998;280:1339-1346.Google Scholar 29. Gandhi TK, Bates DW. Computer adverse drug event (ADE) detection and alerts. In: Shojania K, Duncan B, McDonald K, Wachter R, eds. Making Health Care Safer: A Critical Analysis of Patient Safety Practices. Rockville, Md: Agency for Healthcare Research and Quality; 2001:79-85. AHRQ Publication No. 01-E058. 30. Kaushal R, Bates DW. Computerized physician order entry (CPOE) with clinical decision support systems (CDSSs). In: Shojania K, Duncan B, McDonald K, Wachter R, eds. Making Health Care Safer: A Critical Analysis of Patient Safety Practices. Rockville, Md: Agency for Healthcare Research and Quality; 2001:59-69. AHRQ Publication No. 01-E058. 31. Shiffman RN, Liaw Y, Brandt CA, Corb GJ. Computer-based guideline implementation systems. J Am Med Inform Assoc.1999;6:104-114.Google Scholar 32. McDonald CJ, Wilson GA, McCabe GP. Physician response to computer reminders. JAMA.1980;244:1579-1581.Google Scholar 33. McDonald CJ. The barriers to electronic medical record systems and how to overcome them. J Am Med Inform Assoc.1997;4:213-221.Google Scholar 34. Cimino JJ. Desiderata for controlled medical vocabularies in the twenty-first century. Methods Inf Med.1998;37:394-403.Google Scholar 35. Dolin RH, Alschuler L, Beebe C. et al. The HL7 clinical document architecture. J Am Med Inform Assoc.2001;8:552-569.Google Scholar 36. Lovis C, Chapko MK, Martin DP. et al. Evaluation of a command-line parser-based order entry pathway for the Department of Veterans Affairs electronic patient record. J Am Med Inform Assoc.2001;8:486-498.Google Scholar 37. Teich JM, Merchia PR, Schmiz JL. et al. Effects of computerized physician order entry on prescribing practices. Arch Intern Med.2000;160:2741-2747.Google Scholar 38. Overhage JM, Middleton B, Miller RA. et al. Does national regulatory mandate of provider order entry portend greater benefit than risk for health care delivery? J Am Med Inform Assoc.2002;9:199-208.Google Scholar http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png JAMA American Medical Association

Medical Informatics: Improving Health Care Through Information

Hersh, William R.
JAMA , Volume 288 (16) – Oct 23, 2002
Download PDF
4 pages

Loading next page...
 
/lp/american-medical-association/medical-informatics-improving-health-care-through-information-qJekm0YcOs

References (57)

Publisher
American Medical Association
Copyright
Copyright © 2002 American Medical Association. All Rights Reserved.
ISSN
0098-7484
eISSN
1538-3598
DOI
10.1001/jama.288.16.1955
Publisher site
See Article on Publisher Site

Abstract

Health care is an information-based science. Much of clinical practice involves gathering, synthesizing, and acting on information. Medical informatics is the field concerned with the management and use of information in health and biomedicine. This article focuses on the problems that motivate work in this field, the emerging solutions, and the barriers that remain. It also addresses the core themes that underlie all applications of medical informatics and unify the scientific approaches across the field. There is a growing concern that information is not being used as effectively as possible in health care. Recent reports from the Institute of Medicine have reviewed research findings related to information use and expressed concerns about medical errors and patient safety,1 the quality of medical records,2 and the protection of patient privacy and confidentiality.3 The latest Institute of Medicine report on this topic ties all these problems and potential solutions together in a vision for a health care system that is safe, patient-centered, and evidence-based.4 A variety of solutions is required to address the information-related problems in health care; many solutions involve the use of computers and computer-related technologies. The Field of Medical Informatics Medical informatics is a heterogeneous field, composed of individuals with diverse backgrounds and levels of training. Although virtually all health science universities have some entity with the word "informatics" in its title, there are fewer than 25 that carry out research in medical informatics and offer educational programs.5 At some institutions, medical informatics is viewed as a service (eg, helping clinicians implement informatics applications), but it is more appropriately considered a science that addresses how best to use information to improve health care. The government leader in funding research and education in medical informatics has been the National Library of Medicine (http://www.nlm.nih.gov). Some have argued that the adjective medical in front of informatics is inappropriate because it implies the work of physicians and not the remainder of health care and biomedical science. However, this name has achieved widespread usage. In the article by Kukafka et al,6 Shortliffe described medical informatics as the broad term representing the core theories, concepts, and techniques of information applications in health and biomedicine, with the other adjectives preceding the word informatics denoting the specific application area (Box). Core themes that emerge from informatics science (standards, terminology, usability, and demonstrated value) are relevant across all levels of medical informatics, not solely clinical informatics. Box. The 4 Levels of Medical Informatics and Their Respective Foci From the Cell to the Population* Bioinformatics—molecular and cellular processes, such as gene sequences and maps Imaging informatics—tissues and organs, such as radiology imaging systems Clinical informatics—clinicians and patients, including applications of nursing, dentistry, and other clinical specialties Public health informatics—populations, such as disease surveillance systems *Adapted from Kukafka et al.6 Applications of Clinical Informatics There is a variety of classification types for the different applications of clinical informatics; one approach is by the type of information used. There are essentially 2 types of information used in clinical informatics: patient-specific and knowledge-based. Patient-specific information is generated by and used in the care of patients in the clinical setting, whereas knowledge-based information comprises the scientific basis of health care. Electronic Medical Records The core application using patient-specific information is the electronic medical record (EMR). The paper-based medical record has its tradition and virtues; however, research has shown it can be illegible, incomplete, difficult to access in more than one place, and insecure from unauthorized uses and users.2 Although the EMR overcomes some of these problems, there are challenges to implementing the EMR at the levels of the individual and the organization. The main challenge to individual use of the EMR has been its integration into the busy clinical workflow. The few studies that have been performed show computerized physician order entry (CPOE) adds time for the clinician, although other time savings are usually gained elsewhere through error reduction or the automation brought about by other features of the EMR (eg, accessing test results).7-9 A related challenge is determination of the optimal computing device for the clinical setting. Handheld computers (also called personal digital assistants) are increasingly popular, as documented by their use by internal medicine10 and family practice physicians.11 While their portability is of great value, most usage has focused on entry and retrieval of simple data (eg, prescription writing and drug information) and it is unclear whether other usage (eg, image viewing and literature access) is amenable to these portable devices or whether larger devices might be required. At the organizational level, the key challenges have been managing complex informatics applications and the computer networks upon which they run. Although individual computers are relatively inexpensive, maintaining large networks of them and training the myriad of health care workers who use them are not. Berg12 has noted that the interpersonal challenges to large organizations in implementing EMRs is much more daunting than managing the technology itself. Research has shown that involving users in the implementation process and providing features of benefit to them, such as time-saving measures like specialty-specific order sets, widespread implementation across the organization, and engaging the clinical leadership, are the most important keys to success.13 Organizational challenges are not limited to hospitals and other large institutions. A particular problem in the outpatient setting is that small practices usually lack the minimal technical capabilities and financial resources necessary to implement EMRs.14 A final challenge to all involved with the EMR is the protection of patient privacy and confidentiality, with the Health Insurance Portability and Accountability Act legislating their protection at substantial cost and effort.15 Information Retrieval The field concerned with the organization and retrieval of knowledge-based information (not limited to medicine) is called information retrieval.16 This area has seen tremendous growth due to the Internet and World Wide Web. More than 50% of the US population uses the Web regularly, and of those who do, more than 50% search for personal health information.17 Physicians have embraced the Web as well, with 90% using it on a regular basis.18 A large variety of online resources are now available to both patients and physicians. The oldest of these is MEDLINE, the bibliographic database of journal literature with more than 11 million references to approximately 4000 journals dating from 1966.19 Produced by the US National Library of Medicine, MEDLINE is freely available to the entire world via the PubMed system on the National Library of Medicine Web site (http://pubmed.gov). Bibliographic databases only contain titles and abstracts of articles; however, users increasingly want the full text of journals online. The technical challenge of producing such journals has been supplanted by the economic question of how to increase availability when electronic publication is cheaper (ie, less printing and mailing costs) but still has some cost (due to value added in editing and production).20 Another challenge is how to improve users' abilities to use such systems, as a systematic review has shown physicians do not always achieve optimal results with them.21 In addition to the journal literature, other knowledge-based information is available on the Web, including many of the traditional medical textbooks, clinical practice guidelines (National Guidelines Clearinghouse [http://guideline.gov]), and a growing number of Web sites aimed at patients and consumers, many of which can be found using the National Library of Medicine's MedlinePlus database (http://medlineplus.gov). One concern about Web sites is their quality, as peer-review mechanisms that normally control print literature are often not present, and sites purporting to provide balanced views may well be promoting a point of view or a product to sell.22 Concomitant with the growth of online information resources has been the emergence of tools to use them more effectively. Probably the most important of these is evidence-based medicine.23 The original focus of evidence-based medicine was to train clinicians to find and critically appraise individual studies. Few clinicians have ready access or the time required to search MEDLINE, read articles, and synthesize their findings in the busy clinical setting. As a result, the focus has changed toward approaches that provide highly concise information in the context of the specific patient and clinical problem.24 This has led to a change in the emphasis of evidence-based medicine toward the production of syntheses of clinical topics and concise synopses of their findings.25 Decision Support Systems One clinical informatics application, the decision support system, crosses the boundary of patient-specific and knowledge-based information. These applications, which apply knowledge to patient data, emerged from artificial intelligence and expert system research in the 1970s and 1980s that attempted to model the clinical diagnostician. However, the goal of building an electronic diagnostician never materialized and the resulting systems were too time-consuming for use in the clinical setting.26 These applications have reemerged in the form of decision support systems, which are embedded in the EMR and aim to detect critical situations and errors in care and then notify the clinician, provide appropriate information accordingly, or both.27 Several systematic reviews have documented the effectiveness of decision support applications within the EMR. A variety of approaches, including reminders that increase adherence with ordering preventive measures, hospital admission order sets and display of costs, and interventions to detect medication prescribing errors, has been found beneficial.28-30 Additional work has demonstrated the value of clinical practice guidelines to standardize care.31 One interesting finding of decision support systems applications is that their benefits do not appear to be educational (ie, they do not result in clinicians learning how to provide better care). This is illustrated by the fact that when decision support systems applications are removed, the adherence to specific recommendations returns to the presystem baseline.32 Decision support systems provide timely reminders for busy clinicians. Core Themes There are a number of core themes that underlie medical informatics, not limited to clinical informatics: standards, terminology, usability, and demonstrated value. As most applications in medical informatics interact with others in a federation of different systems, standards are essential to facilitate integration of data, especially across systems from different vendors.33 One area in which standards are particularly important is terminology.34 While most individuals know that an upper respiratory tract infection, a cold, and a viral syndrome are similar, computers do not inherently know this. If the benefits of data aggregation are to be achieved (eg, comparing patient outcomes and resource utilization across practices, institutions, and regions), then standard terminology is essential. Standardizing the structure of clinical documents will also make aggregation and movement of data across systems easier.35 Another core theme in medical informatics is usability. Systems must be integrated into the clinical workflow and demonstrate other benefits when they require more time or effort on the part of the user. One example of research focused on usability found that a CPOE system that allowed physicians to type in orders in free text and mapped them to known order sets was faster and more acceptable than a standard system based on a point-and-click interface.36 Related to usability is the need to demonstrate value. One study of CPOE demonstrated that use of guidelines and dose selection menus resulted in significantly increased adherence to prescribing regimens known to optimize patient safety and reduce cost.37 Future Directions Although considerable challenges remain, the impact of medical informatics will certainly grow. The imperatives of improving documentation, reducing error, and empowering patients will continue to motivate use of information technology in health care. There is plenty of evidence that clinical informatics applications can address these imperatives to enhance patient outcomes, reduce costs, and provide access to knowledge. Evidence alone will not be enough to ensure their widespread adoption. For example, one concern is that most of the studies documenting the effectiveness of decision support have been carried out in academic medical centers with institution-specific EMRs and may not be generalizable. Another concern is that while the correction of a small number of clinical anomalies (eg, improper drug doses) is feasible, the increase of this process might lead to cognitive overload of the clinician. It is also too early to know the true cost of widespread use of these applications.38 The optimal use of clinical informatics applications will require some reengineering of the health care system. It will be crucial for the medical informatics field to account for the needs and concerns of all parties who participate in the process: patients, clinicians, payers, and governments. Clinicians will have to accept some impact on their practices, particularly as the individual physician becomes more accountable to document increasingly expensive care and demonstrate avoidance of error. They will have to accept CPOE, because this is the only place to effectively apply decision support. Society as a whole will need to determine who will pay the costs of EMRs and CPOE, because even if they save money in the long term, the up-front investment will be substantial. The key challenge across all applications will be adherence to the basic goals of the science of medical informatics: developing systems that are easy to use and provide demonstrable benefit. References 1. Kohn LT, Corrigan JM, Donaldson MS. To Err Is Human: Building a Safer Health System. Washington, DC: National Academy Press; 2000. 2. Dick RS, Steen EB, Detmer DE. The Computer-Based Patient Record: An Essential Technology for Health Care, Revised Edition. Washington, DC: National Academy Press; 1997. 3. For the Record: Protecting Electronic Health Information. Washington, DC: National Academy Press; 1997. 4. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: National Academy Press; 2001. 5. American Medical Informatics Association. Resource Center: Academic & Training Programs. Available at: http://www.amia.org/resource/acad&training/f1.html. Accessed April 15, 2002. 6. Kukafka R, O'Carroll PW, Gerberding JL. et al. Issues and opportunities in public health informatics: a panel discussion. J Public Health Manag Pract.2001;7:31-42.Google Scholar 7. Bates DW, Boyle DL, Teich JM. Impact of Computerized Physician Order Entry on Physician Time: Proceedings of the 18th Annual Symposium on Computer Applications in Medical Care, 1994. Washington, DC: Heinley & Belfus; 1994:996. 8. Shu K, Boyle D, Spurr C. et al. Comparison of time spent writing orders on paper with computerized physician order entry. Medinfo.2001;10:1207-1211.Google Scholar 9. Overhage JM, Perkins S, Tierney WM, McDonald CJ. Controlled trial of direct physician order entry: effects on physicians' time utilization in ambulatory primary care internal medicine practices. J Am Med Inform Assoc.2001;8:361-371.Google Scholar 10. American College of Physicians, American Society of Internal Medicine. ACP-ASIM survey finds nearly half of US members use handheld computers. Available at: http://www.acponline.org/college/pressroom/handheld_survey.htm. Accessed April 15, 2002. 11. Criswell DF, Parchman ML. Handheld computer use in US Family Practice residency programs. J Am Med Inform Assoc.2002;9:80-86.Google Scholar 12. Berg M. Implementing information systems in health care organizations: myths and challenges. Int J Med Inf.2001;64:143-156.Google Scholar 13. Ahmad A, Teater P, Bentley TD. et al. Key attributes of a successful physician order entry system implementation in a multi-hospital environment. J Am Med Inform Assoc.2002;9:16-24.Google Scholar 14. Wager KA, Lee FW, White AW. et al. Impact of an electronic medical record system on community-based primary care practices. J Am Board Fam Pract.2000;13:338-348.Google Scholar 15. Gostin LO. National health information privacy: regulations under the Health Insurance Portability and Accountability Act. JAMA.2001;285:3015-3021.Google Scholar 16. Hersh WR. Information Retrieval: A Health Care Perspective. 2nd ed. New York, NY: Springer Verlag; 2002. 17. Fox S, Rainie L. The online health care revolution: how the Web helps Americans take better care of themselves. Available at: http://www.pewinternet.org/reports/pdfs/PIP_Health_Report.pdf. Accessed April 15, 2002. 18. Taylor H, Leitman R. The increasing impact of eHealth on physician behavior. Available at: http://www.harrisinteractive.com/news/newsletters/healthnews/HI_HealthCareNews2001Vol1_iss31.pdf. Accessed April 15, 2002. 19. Wood EH. MEDLINE: the options for health professionals. J Am Med Inform Assoc.1994;1:372-380.Google Scholar 20. Hersh WR, Rindfleisch TC. Electronic publishing of scholarly communication in the biomedical sciences. J Am Med Inform Assoc.2000;7:324-325.Google Scholar 21. Hersh WR, Hickam DH. How well do physicians use electronic information retrieval systems? JAMA.1998;280:1347-1352.Google Scholar 22. Silberg WM, Lundberg GD, Musacchio RA. Assessing, controlling, and assuring the quality of medical information on the Internet. JAMA.1997;277:1244-1245.Google Scholar 23. Sackett DL, Richardson WL, Rosenberg W, Haynes RB. Evidence-Based Medicine: How to Practice and Teach EBM. New York, NY: Churchill Livingstone; 2000. 24. Chueh H, Barnett GO. "Just-in-time" clinical information. Acad Med.1997;72:512-517.Google Scholar 25. Haynes RB. Of studies, syntheses, synopses, and systems: the "4S" evolution of services for finding current best evidence. ACP J Club.2001;134:A11-A13.Google Scholar 26. Miller RA. Medical diagnostic decision support systems—past, present, and future. J Am Med Inform Assoc.1994;1:8-27.Google Scholar 27. Bates DW, Cohen M, Leape LL. et al. Reducing the frequency of errors in medicine using information technology. J Am Med Inform Assoc.2001;8:299-308.Google Scholar 28. Hunt DL, Haynes RB, Hanna SE, Smith K. Effects of computer-based clinical decision support systems on physician performance and patient outcomes. JAMA.1998;280:1339-1346.Google Scholar 29. Gandhi TK, Bates DW. Computer adverse drug event (ADE) detection and alerts. In: Shojania K, Duncan B, McDonald K, Wachter R, eds. Making Health Care Safer: A Critical Analysis of Patient Safety Practices. Rockville, Md: Agency for Healthcare Research and Quality; 2001:79-85. AHRQ Publication No. 01-E058. 30. Kaushal R, Bates DW. Computerized physician order entry (CPOE) with clinical decision support systems (CDSSs). In: Shojania K, Duncan B, McDonald K, Wachter R, eds. Making Health Care Safer: A Critical Analysis of Patient Safety Practices. Rockville, Md: Agency for Healthcare Research and Quality; 2001:59-69. AHRQ Publication No. 01-E058. 31. Shiffman RN, Liaw Y, Brandt CA, Corb GJ. Computer-based guideline implementation systems. J Am Med Inform Assoc.1999;6:104-114.Google Scholar 32. McDonald CJ, Wilson GA, McCabe GP. Physician response to computer reminders. JAMA.1980;244:1579-1581.Google Scholar 33. McDonald CJ. The barriers to electronic medical record systems and how to overcome them. J Am Med Inform Assoc.1997;4:213-221.Google Scholar 34. Cimino JJ. Desiderata for controlled medical vocabularies in the twenty-first century. Methods Inf Med.1998;37:394-403.Google Scholar 35. Dolin RH, Alschuler L, Beebe C. et al. The HL7 clinical document architecture. J Am Med Inform Assoc.2001;8:552-569.Google Scholar 36. Lovis C, Chapko MK, Martin DP. et al. Evaluation of a command-line parser-based order entry pathway for the Department of Veterans Affairs electronic patient record. J Am Med Inform Assoc.2001;8:486-498.Google Scholar 37. Teich JM, Merchia PR, Schmiz JL. et al. Effects of computerized physician order entry on prescribing practices. Arch Intern Med.2000;160:2741-2747.Google Scholar 38. Overhage JM, Middleton B, Miller RA. et al. Does national regulatory mandate of provider order entry portend greater benefit than risk for health care delivery? J Am Med Inform Assoc.2002;9:199-208.Google Scholar

Journal

JAMA – American Medical Association

Published: Oct 23, 2002

There are no references for this article.