Health information technology

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Health information technology (HIT) is the application of "hardware and software in an effort to manage and manipulate health data and information."[1] HIT acts as a framework for the comprehensive management of health information originating from consumers, providers, governments, and insurers in order to improve the overall state of health care. Among those improvements, the Congressional Budget Office (CBO) of the United States believes HIT can[2]:

  • reduce or eliminate errors from medical transcription.
  • reduce the number of diagnostic tests that get duplicated.
  • improve patient outcomes and service efficiency.
  • encourage rigorous scientific comparisons of treatment efficacy and cost to make treatment cheaper and more effective.
  • improve the portability of personal/protected health information (PHI).

The "technology" of "health information technology" represents computers, software, and communications infrastructure that can be networked to create systems for manipulating health information. As such, the science of informatics and its focus on information processing and systems engineering is also integral to the development, application, and evaluation of HIT. In particular the subdivision of health informatics, which focuses on the resources, devices, and methods required for optimizing the acquisition, storage, retrieval, and use of information in health and biomedicine, is most relevant. However, other subdivisions of informatics such as medical informatics, public health informatics, pharmacoinformatics, and translational research informatics are able to inform health informatics from different disciplinary perspectives.[3][4]

U.S. implementation of HIT

In a 2001 report titled Crossing the Quality Chasm: A New Health System for the 21st Century, the Institute of Medicine called for changes to the U.S. healthcare system, declaring a need for "an environment in which public policy and market forces are aligned and in which the change process is supported by an appropriate information technology infrastructure."[5] This report arguably set the tone for further pushes to develop health information technologies and support their adoption.

This eventually led to an announcement by President Bush in April 2004 that a new 10-year initiative was being developed to encourage greater electronic health record adoption, increase funding to health information technology initiatives, and create a new National Health Information Coordinator position. That initiative was furthered by two executive orders signed into law, requiring the Department of Health and Human Services (HHS) to take the lead in advancing the cause.[6][7] Shortly after, several studies from RAND Corporation and the Center for Information Technology Leadership optimistically stated the impact of widespread HIT adoption would potentially lead to nearly $80 billion U.S. annually in the health care sector. However, in 2008 the Congressional Budget Office (CBO) found limitations in those studies — which looked at potential impact rather than likely impact — and found the annual savings numbers to be significantly overstated.[2] The CBO elaborated:

Estimating the impact of some potential sources of savings, especially those arising from greater exchange of information among providers, insurers, and patients, is especially difficult because health IT networks are in an early stage of development. Furthermore, health care providers and hospitals that were early adopters of health IT may have been motivated by particular characteristics of their organizations or operations that made them more likely than nonadopters to achieve benefits from health IT—in which case the outcomes they have seen might not be generalizable. Evidence of savings in the health care sector as a whole from adopting health IT is also limited.[2]

Additional momentum towards furthering HIT implementation arrived in 2009 with the Obama Administration's passage of the American Recovery and Reinvestment Act and it's included Health Information Technology for Economic and Clinical Health Act (HITECH), which provided approximately $19 billion in incentives for the health care system to shift towards using health information technology. Approximately $2 billion was earmarked for 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 in incentives came from Medicare and Medicaid funding for those who adopt HIT before 2015. A year later Obama's Patient Protection and Affordable Care Act (PPACA) was enacted, among other things linking quality care with payment through mandated quality reporting.[7]

One approach to reducing the costs and promoting wider use is to develop open standards related to HIT. In July 2011, after being frustrated with unnecessarily complex and inflexible standards for information interchange standards related to HIT, the Fast Health Interoperable Resources (FHIR) project was started with the desire "to drive down the costs of exchanging data [and] to set the healthcare information free so that people can solve real world healthcare problems more easily and cheaply."[8] Supported by Health Level Seven, the FHIR standard gained further support in 2014[8]{ and promised to improve on existing standards by making FHIR fast and easy to implement, free to use, and based on modern web standards.[9]

Types of technology

In a 2008 study about the adoption of technology in the United States, Furukawa, and colleagues classified applications for prescribing to include electronic medical records (EMR), clinical decision support (CDS), and computerized physician order entry (CPOE).[10] 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)

US medical groups' adoption of EHR (2005)

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.[11] 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.[12] 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.[13] 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).[14] 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".[15] However, recent surveys have shown physicians' deficiencies in understanding the patient safety features of the NPfIT-approved software.[16]

A main problem in HIT adoption is mainly seen by physicians, an important stakeholder to the process of EHR. The Thorn et al. article, elicited that emergency physicians noticed that health information exchange disrupted workflow and was less desirable to use, even though the main goal of EHR is improving coordination of care. The problem was seen that exchanges did not address the needs of end users, e.g. simplicity, user-friendly interface, and speed of systems.[17] The same finding was seen in an earlier article with the focus on CPOE and physician resistance to its use, Bhattacherjee et al.[18]

Sharing

According to the article published by the Internal Journal of Medical Informatics,Health information sharing between patients and providers helps to improve diagnosis, promotes self care, and patients also know more information about their health. Richard Kimball, Jr. of HEXL states that virtual health or telemedicine can offer patients immediate access to their doctors, which will in turn address early signs of diseases through preventive care. The use of electronic medical records (EMRs) is still scarce now but is increasing in Canada, American and British primary care. Healthcare information in EMRs are important sources for clinical, research, and policy questions. Health information privacy (HIP) and security has been a big concern for patients and providers. Studies in Europe evaluating electronic health information poses a threat to electronic medical records and exchange of personal information.[19]

Problems

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.[20]

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.[21] 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%.[22] A 2004 survey by found that 16% of US clinics, hospitals and medical practices are expected to be utilizing CPOE within 2 years.[23] In addition to electronic prescribing, a standardized bar code system for dispensing drugs could prevent a quarter of drug errors.[21] 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.[24] Such concerns are not inconsequential; standards for electronic prescribing for Medicare Part D conflict with regulations in many US states.[21] 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.[25]

Regulation and oversight

September 4, 2013 the Health IT Policy Committee (HITPC) accepted and approved recommendations from the Food and Drug Administration Safety and Innovation Act (FDASIA) working group for a risk-based regulatory framework for health information technology.[26] The Food and Drug Administration (FDA), the Office of the National Coordinator for Health IT (ONC), and Federal Communications Commission (FCC) kicked off the FDASIA workgroup of the HITPC to provide stakeholder input into a report on a risk-based regulatory framework that promotes safety and innovation and reduces regulatory duplication, consistent with section 618 of FDASIA. This provision permitted the Secretary of Health and Human Services (HHS) to form a workgroup in order to obtain broad stakeholder input from across the health care, IT, patients and innovation spectrum. The FDA, ONC, and FCC actively participated in these discussions with stakeholders from across the health care, IT, patients and innovation spectrum.

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.[27] However, many system implementations have experienced costly failures.[28] Furthermore, there is evidence that CPOE may actually contribute to some types of adverse events and other medical errors.[29] For example, the period immediately following CPOE implementation resulted in significant increases in reported adverse drug events in at least one study,[30] and evidence of other errors have been reported.[22][31][32] 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[33][34] 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[35] for the process and e-iatrogenic[36] 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.[37]
  • 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.[38]

Revenue Cycle HIT

The HIMSS Revenue Cycle Improvement Task Force was formed to prepare for the IT changes in the U.S. (e.g. the American Recovery and Reinvestment Act (HITECH), Affordable Care Act, 5010 (electronic exchanges), ICD-10). An important change to the revenue cycle is the international classification of diseases (ICD) codes from 9 to 10. ICD-9 codes are set up to use three to five alphanumeric codes that represent 4,000 different types of procedures, while ICD-10 uses three to seven alphanumeric codes increasing procedural codes to 70,000. ICD-9 was outdated because there were more codes than procedures available, and to document for procedures without an ICD-9 code, a paper-work process of modifiers and supplemental documentation was used. Hence, ICD-10 was introduced to simplify the procedures with unknown codes and unify the standards closer to world standards (ICD-11). One of the main parts of Revenue Cycle HIT is charge capture, it utilizes codes to capture costs for reimbursements from different payers, such as CMS.[39]

International Comparisons through HIT

International health system performance comparisons are important for understanding health system complexities and finding better opportunities, which can be done through health information technology. It gives policy makers the chance to compare and contrast the systems through established indicators from health information technology, as inaccurate comparisons can lead to adverse policies.[40]

See also

References

  1. Ciampa, Mark; Revels, Mark (2013). Introduction to Healthcare Information Technology. Cengage Learning. pp. 320. ISBN 9781133787778. https://books.google.com/books?id=BdIZSlIXCcQC&printsec=frontcover. Retrieved 24 June 2015. 
  2. 2.0 2.1 2.2 Hagen, Stuart; Richmond, Peter; Mazade, Leah (ed.) (20 May 2008). "Evidence on the Costs and Benefits of Health Information Technology" (PDF). Congressional Budget Office. pp. 37. https://www.cbo.gov/sites/default/files/05-20-healthit.pdf. Retrieved 24 June 2015. 
  3. "When Healthcare and Computer Science Collide". University of Illinois at Chicago. http://healthinformatics.uic.edu/resources/infographics/when-healthcare-and-computer-science-collide/. Retrieved 25 June 2015. 
  4. Hersh, William (May 2009). "A stimulus to define informatics and health information technology". BMC Medical Informatics & Decision Making 9 (24). doi:10.1186/1472-6947-9-24. http://www.biomedcentral.com/1472-6947/9/24. Retrieved 24 June 2015. 
  5. Committee on Quality of Health Care in America (2001). Crossing the Quality Chasm: A New Health System for the 21st Century. National Academy Press. pp. 337. ISBN 0309072808. http://books.nap.edu/openbook.php?record_id=10027. Retrieved 24 June 2015. 
  6. "President Bush continues EHR push, sets national goals". Healthcare IT News. HIMSS Media. 26 April 2004. http://www.healthcareitnews.com/news/president-bush-continues-ehr-push-sets-national-goals. Retrieved 24 June 2015. 
  7. 7.0 7.1 "Health Information Technology". American College of Emergency Physicians. 2014. http://www.acep.org/Advocacy/Health-Information-Technology/. Retrieved 24 June 2015. 
  8. 8.0 8.1 Munro, Dan (30 March 2014). "Setting Healthcare Interop On Fire". Forbes. Forbes Media, LLC. http://www.forbes.com/sites/danmunro/2014/03/30/setting-healthcare-interop-on-fire/. Retrieved 24 June 2015. 
  9. "1.7 Introducing HL7 FHIR". Health Level Seven. 30 September 2014. http://www.hl7.org/fhir/DSTU1/summary.html. Retrieved 24 June 2015. 
  10. Furukawa, M. F., Raghu, T. S., Spaulding, T. J., & Vinze, A. (2008). Health Affairs, 27, (3), 865-875.
  11. 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.
  12. American College of Physicians Observer: How EMR software can help prevent medical mistakes by Jerome H. Carter (September 2004)
  13. Kawamoto, Kensaku; Houlihan, Caitlin A; Balas, E Andrew; Lobach, David F (2 April 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): 765–774. doi:10.1136/bmj.38398.500764.8F. PMC 555881. PMID 15767266. http://bmj.bmjjournals.com/cgi/content/full/330/7494/765. Retrieved 2006-06-29. 
  14. 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. http://content.healthaffairs.org/cgi/content/abstract/24/5/1323. Retrieved 2006-07-04. 
  15. NHS Connecting for Health: Delivering the National Programme for IT Retrieved August 4, 2006
  16. 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. http://qhc.bmjjournals.com/cgi/content/full/14/3/164. Retrieved 2006-07-08. 
  17. Thorn. S., Carter M., Bailey J. | http://www.annemergmed.com/article/S0196-0644(13)01449-2/abstract
  18. Bhattacherjee A., Hikmet N. | http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.101.9714&rep=rep1&type=pdf
  19. Perera, Gihan; Holbrook, Anne; Thabane,Lehana; Foster, Gary; Willison, Donald J. (February 2011). "Views on health information sharing and privacy from primary care practices using electronic medical records". Internal Journal of Medical Information 80 (2): 94–101. doi:10.1016/j.ijmedinf.2010.11.005. 
  20. Freudenheim, Milt (2012-10-08). "The Ups and Downs of Electronic Medical Records". New York Times. http://www.nytimes.com/2012/10/09/health/the-ups-and-downs-of-electronic-medical-records-the-digital-doctor.html?pagewanted=all&_r=0. 
  21. 21.0 21.1 21.2 The Institute of Medicine (2006). "Preventing Medication Errors". The National Academies Press. http://www.nap.edu/catalog/11623.html. Retrieved 2006-07-21. 
  22. 22.0 22.1 Bates, DW; Leape, LL; Cullen, DJ; Laird, N; Petersen, LA; Teich, JM; Burdick, E; Hickey, M et al. (21 October 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. http://jama.ama-assn.org/cgi/content/abstract/280/15/1311. Retrieved 2006-06-20. 
  23. "Hospital Quality & Safety Survey" (PDF). The Leapfrog Group. 2004. http://www.leapfroggroup.org/media/file/Leapfrog-Survey_Release-11-16-04.pdf. Retrieved 2006-07-08. 
  24. 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. http://www.washingtonpost.com/wp-dyn/content/article/2006/07/20/AR2006072000754.html. Retrieved 2006-07-21. 
  25. "Computerized Physician Order Entry: Coming to a Hospital Near You" J. Scott Litton, Physicians Practice, March 2012.
  26. Daniel; Patel, Bakul Patel; Quinn, Matthew (5 September 2013). "The path toward a risk-based regulatory framework for health IT". Health IT Buzz. Office of the National Coordinator for Health IT (US). http://www.healthit.gov/buzz-blog/hit-policy-committee/path-riskbased-regulatory-framework-health/. 
  27. Institute of Medicine (2001). Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: The National Academies Press. http://www.nap.edu/books/0309072808/html. Retrieved 2006-06-29. 
  28. 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.
  29. 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.
  30. 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.
  31. Bates, D. (2005). Computerized Physician Order entry and medication errors: finding a balance. Journal of Biomedical Informatics, 38(4): 250-261.
  32. Bates, D.W. (2005). Physicians and ambulatory electronic health records. Health Affairs, 24(5): 1180-1189.
  33. 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. http://jama.ama-assn.org/cgi/content/abstract/293/10/1197. Retrieved 2006-06-28. 
  34. Lohr, Steve (2005-03-09). "Doctors' Journal Says Computing Is No Panacea". The New York Times. http://www.nytimes.com/2005/03/09/technology/09compute.html?ei=5089&en=402b792e748d99a2&ex=1268110800&adxnnl=1&partner=rssyahoo&adxnnlx=1150474153-xVix1BcYkvTKJpuLyHStrQ. Retrieved 2006-07-15. 
  35. 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. http://www.hom.ba.ttu.edu/FordPub/Palmieri_JHCRM_2008_Technological%20iatrogenesis.pdf. Retrieved 2008-07-02. 
  36. 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. http://www.jamia.org/cgi/reprint/14/3/387.pdf. Retrieved 2008-08-24. 
  37. Santell, John P (2004). "Computer Related Errors: What Every Pharmacist Should Know" (PDF). United States Pharmacopia. http://www.usp.org/pdf/EN/patientSafety/slideShows2004-12-09.pdf. Retrieved 2006-06-20. 
  38. A Study of An Enterprise Health Information System
  39. "The Future of Revenue Cycle: Preparing for Near-Term Change". http://himss.files.cms-plus.com/HIMSSorg/content/files/FutureofRevenueCycleWhitePaper-EDITED5-24NV.pdf. Retrieved 18 May 2013. 
  40. World Health Organization/Europe regional office | http://www.euro.who.int/en/data-and-evidence/evidence-informed-policy-making/publications/2012/health-system-performance-comparison-an-agenda-for-policy,-information-and-research-2012

Further reading

  • 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.
  • 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.
  • Holden, Richard J., Brown, Roger L., Alper, Samuel J., Scanlon, Matthew C., Patel, Neal R., Karsh, Ben-Tzion (July 2011). That’s nice, but what does IT do? Evaluating the impact of bar coded medication administration by measuring changes in the process of care. International Journal of Industrial Ergonomics, 41(4), 370-379.
  • Moore, An’nita & Fisher, Kathleen (2012, March). Healthcare Information Technology and Medical-Surgical Nurse: The Emergence of a New Care Partnership. CIN: Computers, Informatics, Nursing, 30(3),157-163.
  • Milstein, Julia A. & Bates, David W. (2010, March–April). Paperless healthcare: Progress and challenges of an IT-enabled healthcare system. Business Horizons, 53(2), 119-130.
  • 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.

External links

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