Health information technology
Health information technology (HIT) provides the umbrella framework to describe the comprehensive management of health information across computerized systems and its secure exchange between consumers, providers, government and quality entities, and insurers. Health information technology (HIT) is in general increasingly viewed as the most promising tool for improving the overall quality, safety and efficiency of the health delivery system (Chaudhry et al., 2006). Broad and consistent utilization of HIT will:
- Improve health care quality or effectiveness;
- Increase health care productivity or efficiency;
- Prevent medical errors and increase health care accuracy and procedural correctness;
- Reduce health care costs;
- Increase administrative efficiencies and healthcare work processes;
- Decrease paperwork and unproductive or idle work time;
- Extend real-time communications of health informatics among health care professionals; and
- Expand access to affordable care.
Interoperable HIT will improve individual patient care, but it will also bring many public health benefits including:
- Early detection of infectious disease outbreaks around the country;
- Improved tracking of chronic disease management; and
- Evaluation of health care based on value enabled by the collection of de-identified price and quality information that can be compared.
Concepts and Definitions 
Health information technology (HIT) is “the application of information processing involving both computer hardware and software that deals with the storage, retrieval, sharing, and use of health care information, data, and knowledge for communication and decision making” (Brailer, & Thompson, 2004). Technology is a broad concept that deals with a species' usage and knowledge of tools and crafts, and how it affects a species' ability to control and adapt to its environment. However, a strict definition is elusive; "technology" can refer to material objects of use to humanity, such as machines, hardware or utensils, but can also encompass broader themes, including systems, methods of organization, and techniques. For HIT, technology represents computers and communications attributes that can be networked to build systems for moving health information. Informatics is yet another integral aspect of HIT.
Informatics refers to the science of information, the practice of information processing, and the engineering of information systems. Informatics underlies the academic investigation and practitioner application of computing and communications technology to healthcare, health education, and biomedical research. Health informatics refers to the intersection of information science, computer science, and health care. Health informatics describes the use and sharing of information within the healthcare industry with contributions from computer science, mathematics, and psychology. It deals with the resources, devices, and methods required for optimizing the acquisition, storage, retrieval, and use of information in health and biomedicine. Health informatics tools include not only computers but also clinical guidelines, formal medical terminologies, and information and communication systems. Medical informatics, nursing informatics, public health informatics, and pharmacy informatics are subdisciplines that inform health informatics from different disciplinary perspectives. The processes and people of concern or study are the main variables.
Implementation of HIT 
The Institute of Medicine’s (2001) call for the use of electronic prescribing systems in all healthcare organizations by 2010 heightened the urgency to accelerate United States hospitals’ adoption of CPOE systems. In 2004, President Bush signed an Executive Order titled the President’s Health Information Technology Plan, which established a ten-year plan to develop and implement electronic medical record systems across the US to improve the efficiency and safety of care. According to a study by RAND Health, the US healthcare system could save more than $81 billion annually, reduce adverse healthcare events and improve the quality of care if it were to widely adopt health information technology.
The American Recovery and Reinvestment Act, signed into law in 2009 under the Obama Administration, has provided approximately $19 billion in incentives for hospitals to shift from paper to electronic medical records. The American Recovery and Reinvestment Act has set aside $2 billion which will go towards programs developed by the National Coordinator and Secretary to help healthcare providers implement HIT and provide technical assistance through various regional centers. The other $17 billion dollars in incentives comes from Medicare and Medicaid funding for those who adopt HIT before 2015. Healthcare providers who implement electronic records can receive up to $44,000 over four years in Medicare funding and $63,750 over six years in Medicaid funding. The sooner that healthcare providers adopt the system, the more funding they receive. Those who do not adopt electronic health record systems before 2015 do not receive any federal funding. 
While electronic health records have potentially many advantages in terms of providing efficient and safe care, recent reports have brought to light some challenges with implementing electronic health records. The most immediate barriers for widespread adoption of this technology have been the high initial cost of implementing the new technology and the time required for doctors to train and adapt to the new system. There have also been suspected cases of fraudulent billing, where hospitals inflate their billings to Medicare. Given that healthcare providers have not reached the deadline (2015) for adopting electronic health records, it is unclear what effects this policy will have long term. 
Types of technology 
In a recent study about the adoption of technology in the United States, Furukawa, and colleagues (2008) classified applications for prescribing to include electronic medical records (EMR), clinical decision support (CDS), and computerized physician order entry (CPOE). They further defined applications for dispensing to include bar-coding at medication dispensing (BarD), robot for medication dispensing (ROBOT), and automated dispensing machines (ADM). And, they defined applications for administration to include electronic medication administration records (EMAR) and bar-coding at medication administration (BarA).
Electronic Health Record (EHR) 
Although frequently cited in the literature the Electronic health record (EHR), previously known as the Electronic medical record (EMR), there is no consensus about the definition (Jha et al., 2008). However, there is consensus that EMRs can reduce several types of errors, including those related to prescription drugs, to preventive care, and to tests and procedures. Recurring alerts remind clinicians of intervals for preventive care and track referrals and test results. Clinical guidelines for disease management have a demonstrated benefit when accessible within the electronic record during the process of treating the patient. Advances in health informatics and widespread adoption of interoperable electronic health records promise access to a patient's records at any health care site. A 2005 report noted that medical practices in the United States are encountering barriers to adopting an EHR system, such as training, costs and complexity, but the adoption rate continues to rise (see chart to right). Since 2002, the National Health Service of the United Kingdom has placed emphasis on introducing computers into healthcare. As of 2005, one of the largest projects for a national EHR is by the National Health Service (NHS) in the United Kingdom. The goal of the NHS is to have 60,000,000 patients with a centralized electronic health record by 2010. The plan involves a gradual roll-out commencing May 2006, providing general practices in England access to the National Programme for IT (NPfIT), the NHS component of which is known as the "Connecting for Health Programme". However, recent surveys have shown physicians' deficiencies in understanding the patient safety features of the NPfIT-approved software.
Clinical point of care technology 
Computerized Provider (Physician) Order Entry (CPOE) 
Prescribing errors are the largest identified source of preventable errors in hospitals. A 2006 report by the Institute of Medicine estimated that a hospitalized patient is exposed to a medication error each day of his or her stay. Computerized provider order entry (CPOE), formerly called Computer physician order entry, can reduce total medication error rates by 80%, and adverse (serious with harm to patient) errors by 55%. A 2004 survey by Leapfrog found that 16% of US clinics, hospitals and medical practices are expected to be utilizing CPOE within 2 years. In addition to electronic prescribing, a standardized bar code system for dispensing drugs could prevent a quarter of drug errors. Consumer information about the risks of the drugs and improved drug packaging (clear labels, avoiding similar drug names and dosage reminders) are other error-proofing measures. Despite ample evidence of the potential to reduce medication errors, competing systems of barcoding and electronic prescribing have slowed adoption of this technology by doctors and hospitals in the United States, due to concern with interoperability and compliance with future national standards. Such concerns are not inconsequential; standards for electronic prescribing for Medicare Part D conflict with regulations in many US states. And, aside from regulatory concerns, for the small-practice physician, utilizing CPOE requires a major change in practice work flow and an additional investment of time. Many physicians are not full-time hospital staff; entering orders for their hospitalized patients means taking time away from scheduled patients.
Technological Innovations, Opportunities, and Challenges 
Handwritten reports or notes, manual order entry, non-standard abbreviations and poor legibility lead to substantial errors and injuries, according to the Institute of Medicine (2000) report. The follow-up IOM (2004) report, Crossing the quality chasm: A new health system for the 21st century, advised rapid adoption of electronic patient records, electronic medication ordering, with computer- and internet-based information systems to support clinical decisions. However, many system implementations have experienced costly failures (Ammenwerth et al., 2006). Furthermore, there is evidence that CPOE may actually contribute to some types of adverse events and other medical errors.(Campbell et al., 2007) For example, the period immediately following CPOE implementation resulted in significant increases in reported adverse drug events in at least one study (Bradley, Steltenkamp, & Hite, 2006) and evidence of other errors have been reported.(Bates, 2005a; Bates, Leape, Cullen, & Laird, 1998; Bates; 2005b) Collectively, these reported adverse events describe phenomena related to the disruption of the complex adaptive system resulting from poorly implemented or inadequately planned technological innovation.
Technological Iatrogenesis 
Technology may introduce new sources of error Technologically induced errors are significant and increasingly more evident in care delivery systems. Terms to describe this new area of error production include the label technological iatrogenesis for the process and e-iatrogenic for the individual error. The sources for these errors include:
- Prescriber and staff inexperience may lead to a false sense of security; that when technology suggests a course of action, errors are avoided.
- Shortcut or default selections can override non-standard medication regimens for elderly or underweight patients, resulting in toxic doses.
- CPOE and automated drug dispensing was identified as a cause of error by 84% of over 500 health care facilities participating in a surveillance system by the United States Pharmacopoeia.
- Irrelevant or frequent warnings can interrupt work flow.
Healthcare information technology can also result in iatrogenesis if design and engineering are substandard, as illustrated in a 14-part detailed analysis done at the University of Sydney.
See also 
- Consumer health informatics
- Dental informatics
- Health informatics
- Imaging informatics
- Public health informatics
- Patient Safety
- RAND Healthcare: Health Information Technology: Can HIT Lower Costs and Improve Quality? Retrieved on July 8, 2006
- "Centers for Medicare and Medicaid Services".
- Freudenheim, Milt (10/8/2012). "The Ups and Downs of Electronic Medical Records". New York Times.
- American College of Physicians Observer: How EMR software can help prevent medical mistakes by Jerome H. Carter (September 2004)
- Kensaku Kawamoto, fellow1, Caitlin A Houlihan, E Andrew Balas, David F Lobach (2005). "Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success". British Medical Journal 330 (7494): 765–768. doi:10.1136/bmj.38398.500764.8F. PMC 555881. PMID 15767266. Retrieved 2006-06-29.
- Gans D, Kralewski J, Hammons T, Dowd B (2005). "Medical groups' adoption of electronic health records and information systems". Health affairs (Project Hope) 24 (5): 1323–1333. doi:10.1377/hlthaff.24.5.1323. PMID 16162580. Retrieved 2006-07-04.
- NHS Connecting for Health: Delivering the National Programme for IT Retrieved August 4, 2006
- C J Morris, B S P Savelyich, A J Avery, J A Cantrill and A Sheikh (2005). "Patient safety features of clinical computer systems: questionnaire survey of GP views". Quality and Safety in Health Care 14 (3): 164–168. doi:10.1136/qshc.2004.011866. PMC 1744017. PMID 15933310. Retrieved 2006-07-08.
- The Institute of Medicine (2006). "Preventing Medication Errors". The National Academies Press. Retrieved 2006-07-21.
- David W. Bates, MD et al. (1998). "Effect of Computerized Physician Order Entry and a Team Intervention on Prevention of Serious Medication Errors". JAMA 280 (15): 1311–1316. doi:10.1001/jama.280.15.1311. PMID 9794308. Retrieved 2006-06-20.
- "Hospital Quality & Safety Survey" (PDF). The Leapfrog Group. 2004. Retrieved 2006-07-08.
- Kaufman, Marc (2005-07-21). "Medication Errors Harming Millions, Report Says. Extensive National Study Finds Widespread, Costly Mistakes in Giving and Taking Medicine". The Washington Post. pp. A08. Retrieved 2006-07-21.
- "Computerized Physician Order Entry: Coming to a Hospital Near You" J. Scott Litton, Physicians Practice, March 2012.
- Institute of Medicine (2001). "Crossing the Quality Chasm: A New Health System for the 21st Century". The National Academies Press. Retrieved 2006-06-29.
- Ross Koppel, PhD et al. (2005). "Role of Computerized Physician Order Entry Systems in Facilitating Medication Errors". JAMA 293 (10): 1197–1203. doi:10.1001/jama.293.10.1197. PMID 15755942. Retrieved 2006-06-28.
- Lohr, Steve (2005-03-09). "Doctors' Journal Says Computing Is No Panacea". The New York Times. Retrieved 2006-07-15.
- Patrick Palmieri et al. (2007). "Technological iatrogenesis: New risks force heightened management awareness". Journal of Healthcare Risk Management 27 (4): 19–24. doi:10.1002/jhrm.5600270405. PMID 20200891. Retrieved 2008-07-02.
- Weiner et al. (2007). "e-Iatrogenesis: The most critical unintended consequence of CPOE and other HIT". Journal of the American Medical Informatics Association 14 (3): 387–388. doi:10.1197/jamia.M2338. PMC 2244888. PMID 17329719. Retrieved 2008-08-24.
- Santell, John P (2004). "Computer Related Errors: What Every Pharmacist Should Know" (PDF). United States Pharmacopia. Retrieved 2006-06-20.
- A Study of An Enterprise Health Information System 
Further reading 
- Ammenwerth, E., Talmon, J., Ash, J. S., Bates, D. W., Beuscart-Zephir, M. C., Duhamel, A., Elkin, P. L., Gardner, R. M., & Geissbuhler, A. (2006). Impact of CPOE on mortality rates – contradictory findings, important messages.” Methods Inf Med, 45(6): 586-593.
- Ash, J. S., Sittig, D. F., Poon, E. G., Guappone, K., Campbell, E., & Dykstra, R. H. (2007). The extent and importance of unintended consequences related to computerized provider order entry.” Journal of the American Medical Informatics Association, 14(4): 415-423.
- Bates, D. (2005a). Computerized Physician Order entry and medication errors: finding a balance. Journal of Biomedical Informatics, 38(4): 250-261.
- Bates, D.W. (2005b). Physicians and ambulatory electronic health records. Health Affairs, 24(5): 1180-1189.
- Bates, D. W., Leape, L. L., Cullen, D. J., & Laird, N. (1998). Effect of computerized physician order entry and a team intervention on prevention of serious medical errors. Journal of the American Medical Association, 280: 1311-1316.
- Bradley, V. M., Steltenkamp, C. L., & Hite, K. B. (2006). Evaluation of reported medication errors before and after implementation of computerized practitioner order entry. Journal Healthc Inf Manag, 20(4): 46-53.
- Brailer, D., & Thompson, T. (2004). Health IT strategic framework. Washington, DC: Department of Health and Human Services.
- Chaudhry, B. Wang, J., & Wu, S. et al., (2006). Systematic review: Impact of health information technology on quality, efficiency, and costs of medical care, Annals of Internal Medicine, 144(10), 742–752.
- Campbell, E. M., Sittig, D. F., Ash, J. S., Guappone, K. P., & Dykstra, R. H. (2007). In reply to: “e-Iatrogenesis: The most critical consequence of CPOE and other HIT. Journal of the American Medical Informatics Association.
- Edmunds M, Peddicord D, Detmer DE, Shortliffe E. Health IT Policy and Politics: A Primer on Moving Policy Into Action. Featured Session, American Medical Informatics Association Annual Symposium (2009). Available as a webinar at https://www.amia.org/amia-policy-101.
- Furukawa, M. F., Raghu, T. S., Spaulding, T. J., & Vinze, A. (2008). Health Affairs, 27, (3), 865-875.
- Institute of Medicine (2001). Crossing the quality chasm: A new health system for the 21st century. Washington, D.C: National Academies Press.
- Jha, A. K., Doolan, D., Grandt, D., Scott, T. & Bates, D. W. (2008). The use of health information technology in seven nations. International Journal of Medical Informatics, corrected proof in-press.
- Kawamoto, K. H., Caitlin, A., Balas, E. A., & Lobach, D. F. (2005). “Improving clinical practice using clinical decision support systems: A systematic review of trials to identify features critical to success.” British Journal of Medicine, 330(7494): 765-774.
- Sidrov, J. (2006). It ain’t necessarily so: The electronic health record and the unlikely prospect of reducing healthcare costs. Health Affairs, 25(4): 1079-1085.
- Health Resources and Services Administration (HRSA)
- Health Information Technology at US Department of Health & Human Services
- Healthcare Information Technology from American National Standards Institute (ANSI)
- Certification Commission for Healthcare Information Technology (CCHIT)
- Health Information Technology Videos
- Health IT Discussion Forum
- Hospital Management Information System from Center for Development of Advanced Computing (C-DAC)
- American Society of Health Informatics Managers
- Patient Safety Initiatives in India Using Health IT
- Health Information Technology Certification Programs
- Health Information Technology Careers