Health information technology

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Health information technology (HIT) is health technology, particularly information technology, applied to health and health care. It supports health information management across computerized systems and the secure exchange of health information between consumers, providers, payers, and quality monitors. [1] Based on a 2008 report on a small series of studies conducted at four sites that provide ambulatory care – three U.S. medical centers and one in the Netherlands, the use of electronic health records (EHRs) was viewed as the most promising tool for improving the overall quality, safety and efficiency of the health delivery system. [2]

Contents

Risk-based regulatory framework for health IT

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. [3] 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.

HIMSS Good Informatics Practices-GIP is aligned with FDA risk-based regulatory framework for health information technology. [4] GIP development began in 2004 developing risk-based IT technical guidance. [5] Today the GIP peer-review and published modules are widely used as a tool for educating Health IT professionals.

Interoperable HIT will improve individual patient care, but it will also bring many public health benefits including:

According to an article published in the International 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. 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. [6] Moreover, software's traceability features allow the hospitals to collect detailed information about the preparations dispensed, creating a database of every treatment that can be used for research purposes. [7]

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, health data, and knowledge for communication and decision making". [8] 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, pharmacy informatics, and translational bioinformatics are subdisciplines that inform health informatics from different disciplinary perspectives. [9] The processes and people of concern or study are the main variables.

Implementation

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. [10]

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. Meaningful Use, as a part of the 2009 Health Information Technology for Economic and Clinical Health Act (HITECH) was the incentive that included over $20 billion for the implementation of HIT alone, and provided further indication of the growing consensus regarding the potential salutary effect of HIT. 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 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. [11]

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. [12]

One approach to reducing the costs and promoting wider use is to develop open standards related to EHRs. In 2014 there was widespread interest in a new HL7 draft standard, Fast Healthcare Interoperability Resources (FHIR), which is designed to be open, extensible, and easier to implement, benefiting from modern web technologies. [13]

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). [14] They further defined applications for dispensing to include bar-coding at medication dispensing (BarD), robot for medication dispensing (ROBOT), and automated dispensing machines (ADM). They defined applications for administration to include electronic medication administration records (eMAR) and bar-coding at medication administration (BarA or BCMA). Other types include Health information exchange.

Electronic health record (EHR)

US medical groups' adoption of EHR (2005) EHRadoption.gif
US medical groups' adoption of EHR (2005)

Although the electronic health record (EHR), previously known as the electronic medical record (EMR), is frequently cited in the literature, there is no consensus about the definition. [15] 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. [16] 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. [17] 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). [18] 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". [19] However, recent surveys have shown physicians' deficiencies in understanding the patient safety features of the NPfIT-approved software. [20]

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. [21] The same finding was seen in an earlier article with the focus on CPOE and physician resistance to its use, Bhattacherjee et al. [22]

One opportunity for EHRs is to utilize natural language processing for searches. One systematic review of the literature found that searching and analyzing notes and text that would otherwise be inaccessible for review could be accessed through increasing collaboration between software developers and end-users of natural language processing tools within EHRs. [23]

Clinical point of care technology

Computerized provider (physician) order entry

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. [24] Computerized provider order entry (CPOE), also called computerized physician order entry, can reduce total medication error rates by 80%, and adverse (serious with harm to patient) errors by 55%. [25] A 2004 survey by found that 16% of US clinics, hospitals and medical practices are expected to be utilizing CPOE within 2 years. [26] In addition to electronic prescribing, a standardized bar code system for dispensing drugs could prevent a quarter of drug errors. [24] 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. [27] Such concerns are not inconsequential; standards for electronic prescribing for Medicare Part D conflict with regulations in many US states. [24] 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. [28]

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. [29] However, many system implementations have experienced costly failures. [30] Furthermore, there is evidence that CPOE may actually contribute to some types of adverse events and other medical errors. [31] For example, the period immediately following CPOE implementation resulted in significant increases in reported adverse drug events in at least one study, [32] and evidence of other errors have been reported. [25] [33] [34] 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. [35] [36] 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 [37] for the process and e-iatrogenic [38] for the individual error. The sources for these errors include:

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. [40] Numerous examples of bias introduced by artificial intelligence (AI) have been cited as the use of AI-assisted healthcare increases. See Algorithmic bias.

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 of 2009 (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 procedures than codes available, and to document for procedures without an ICD-9 code, unspecified codes were utilized which did not fully capture the procedures or the work involved in turn affecting reimbursement. 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. [41]

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. [42]

See also

Related Research Articles

<span class="mw-page-title-main">Health informatics</span> Computational approaches to health care

Health informatics is the study and implementation of computer structures and algorithms to improve communication, understanding, and management of medical information. It can be viewed as a branch of engineering and applied science.

<span class="mw-page-title-main">Electronic health record</span> Digital collection of patient and population electronically stored health information

An electronic health record (EHR) is the systematized collection of patient and population electronically stored health information in a digital format. These records can be shared across different health care settings. Records are shared through network-connected, enterprise-wide information systems or other information networks and exchanges. EHRs may include a range of data, including demographics, medical history, medication and allergies, immunization status, laboratory test results, radiology images, vital signs, personal statistics like age and weight, and billing information.

Computerized physician order entry (CPOE), sometimes referred to as computerized provider order entry or computerized provider order management (CPOM), is a process of electronic entry of medical practitioner instructions for the treatment of patients under his or her care.

A clinical decision support system (CDSS) is a health information technology that provides clinicians, staff, patients, and other individuals with knowledge and person-specific information to help health and health care. CDSS encompasses a variety of tools to enhance decision-making in the clinical workflow. These tools include computerized alerts and reminders to care providers and patients, clinical guidelines, condition-specific order sets, focused patient data reports and summaries, documentation templates, diagnostic support, and contextually relevant reference information, among other tools. CDSSs constitute a major topic in artificial intelligence in medicine.

A personal health record (PHR) is a health record where health data and other information related to the care of a patient is maintained by the patient. This stands in contrast to the more widely used electronic medical record, which is operated by institutions and contains data entered by clinicians to support insurance claims. The intention of a PHR is to provide a complete and accurate summary of an individual's medical history which is accessible online. The health data on a PHR might include patient-reported outcome data, lab results, and data from devices such as wireless electronic weighing scales or from a smartphone.

Continuity of Care Record (CCR) is a health record standard specification developed jointly by ASTM International, the Massachusetts Medical Society (MMS), the Healthcare Information and Management Systems Society (HIMSS), the American Academy of Family Physicians (AAFP), the American Academy of Pediatrics (AAP), and other health informatics vendors.

Patient safety is a discipline that emphasizes safety in health care through the prevention, reduction, reporting and analysis of error and other types of unnecessary harm that often lead to adverse patient events. The magnitude of avoidable adverse events, often known as patient safety incidents, experienced by patients was not well known until the 1990s, when multiple countries reported significant numbers of patients harmed and killed by medical errors. Recognizing that healthcare errors impact 1 in every 10 patients around the world, the World Health Organization (WHO) calls patient safety an endemic concern. Indeed, patient safety has emerged as a distinct healthcare discipline supported by an immature yet developing scientific framework. There is a significant transdisciplinary body of theoretical and research literature that informs the science of patient safety with mobile health apps being a growing area of research.

Medcin, is a system of standardized medical terminology, a proprietary medical vocabulary and was developed by Medicomp Systems, Inc. MEDCIN is a point-of-care terminology, intended for use in Electronic Health Record (EHR) systems, and it includes over 280,000 clinical data elements encompassing symptoms, history, physical examination, tests, diagnoses and therapy. This clinical vocabulary contains over 38 years of research and development as well as the capability to cross map to leading codification systems such as SNOMED CT, CPT, ICD-9-CM/ICD-10-CM, DSM, LOINC, CDT, CVX, and the Clinical Care Classification (CCC) System for nursing and allied health.

<span class="mw-page-title-main">First Databank</span>

First Databank (FDB) is a major provider of drug and medical device databases that help inform healthcare professionals to make decisions. FDB partners with information system developers to deliver useful medication- and medical device-related information to clinicians, business associates, and patients. FDB is part of Hearst and the Hearst Health network.

Patient portals are healthcare-related online applications that allow patients to interact and communicate with their healthcare providers, such as physicians and hospitals. Typically, portal services are available on the Internet at all hours of the day and night. Some patient portal applications exist as stand-alone web sites and sell their services to healthcare providers. Other portal applications are integrated into the existing website of a healthcare provider. Still others are modules added onto an existing electronic medical record (EMR) system. What all of these services share is the ability of patients to interact with their medical information via the Internet. Currently, the lines between an EMR, a personal health record, and a patient portal are blurring. For example, Intuit Health and Microsoft HealthVault describe themselves as personal health records (PHRs), but they can interface with EMRs and communicate through the Continuity of Care Record standard, displaying patient data on the Internet so it can be viewed through a patient portal.

<span class="mw-page-title-main">VistA</span> Health information system

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The Clinical Care Classification (CCC) System is a standardized, coded nursing terminology that identifies the discrete elements of nursing practice. The CCC provides a unique framework and coding structure. Used for documenting the plan of care; following the nursing process in all health care settings.

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<span class="mw-page-title-main">Adoption of electronic medical records in U.S. hospitals</span>

The adoption of electronic medical records refers to the recent shift from paper-based medical records to electronic health records (EHRs) in hospitals. The move to electronic medical records is becoming increasingly prevalent in health care delivery systems in the United States, with more than 80% of hospitals adopting some form of EHR system by November 2017.

Health data is any data "related to health conditions, reproductive outcomes, causes of death, and quality of life" for an individual or population. Health data includes clinical metrics along with environmental, socioeconomic, and behavioral information pertinent to health and wellness. A plurality of health data are collected and used when individuals interact with health care systems. This data, collected by health care providers, typically includes a record of services received, conditions of those services, and clinical outcomes or information concerning those services. Historically, most health data has been sourced from this framework. The advent of eHealth and advances in health information technology, however, have expanded the collection and use of health data—but have also engendered new security, privacy, and ethical concerns. The increasing collection and use of health data by patients is a major component of digital health.

Federal and state governments, insurance companies and other large medical institutions are heavily promoting the adoption of electronic health records. The US Congress included a formula of both incentives and penalties for EMR/EHR adoption versus continued use of paper records as part of the Health Information Technology for Economic and Clinical Health (HITECH) Act, enacted as part of the, American Recovery and Reinvestment Act of 2009.

<span class="mw-page-title-main">Dean F. Sittig</span> US Professor in Biomedical Informatics and Bioengineering

Dean Forrest Sittig is an American biomedical informatician specializing in clinical informatics. He is a professor in Biomedical Informatics at the University of Texas Health Science Center at Houston and Executive Director of the Clinical Informatics Research Collaborative (CIRCLE). Sittig was elected as a fellow of the American College of Medical Informatics in 1992, the Healthcare Information and Management Systems Society in 2011, and was a founding member of the International Academy of Health Sciences Informatics in 2017. Since 2004, he has worked with Joan S. Ash, a professor at Oregon Health & Science University to interview several Pioneers in Medical Informatics, including G. Octo Barnett, MD, Morris F. Collen, MD, Donald E. Detmer, MD, Donald A. B. Lindberg, MD, Nina W. Matheson, ML, DSc, Clement J. McDonald, MD, and Homer R. Warner, MD, PhD.

References

  1. ↑ Fadahunsi, Kayode Philip; Akinlua, James Tosin; O’Connor, Siobhan; Wark, Petra A; Gallagher, Joseph; Carroll, Christopher; Majeed, Azeem; O’Donoghue, John (March 2019). "Protocol for a systematic review and qualitative synthesis of information quality frameworks in eHealth". BMJ Open. 9 (3): e024722. doi:10.1136/bmjopen-2018-024722. ISSN   2044-6055. PMC   6429947 . PMID   30842114.
  2. ↑ Chaudhry B, Wang J, Wu S, et al. (16 May 2006). "Systematic review: Impact of health information technology on quality, efficiency, and costs of medical care". Annals of Internal Medicine. 144 (10): 742–52. doi: 10.7326/0003-4819-144-10-200605160-00125 . PMID   16702590.
  3. ↑ Daniel, Jodi G; 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).
  4. ↑ Winslow, Ford; Asher, Anette; Fouskarinis, Steven; Fulop, Gabor; Gomez, Damian; Ghopeh, Oscar; Jacobson, Andrew; Kim, John; Speake, Linda; Vilicich, Mark; Asher, Howard (February 2011), "Chapter 1 - Executive Summary: A framework for trusted information systems" (PDF), Good Informatics Practice (GIP), Healthcare Information and Management Systems Society (HIMSS)
  5. ↑ Asher, Howard; Bourne, Phil (19 August 2009), LSIT Global Institute public debut, SciVee
  6. ↑ 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". International Journal of Medical Informatics. 80 (2): 94–101. doi:10.1016/j.ijmedinf.2010.11.005. PMID   21167771.
  7. ↑ "La dosis adecuada". Cluster Salud, La Industria de la vida (in European Spanish). 23 February 2017. Retrieved 2017-03-02.
  8. ↑ Brailer, D. (2004). The decade of health information technology. HHS Report, July, 21.
  9. ↑ "When Healthcare and Computer Science Collide". University of Illinois at Chicago. 9 September 2014. Retrieved 18 September 2014.
  10. ↑ RAND Healthcare: Health Information Technology: Can HIT Lower Costs and Improve Quality? Retrieved on July 8, 2006
  11. ↑ "Centers for Medicare and Medicaid Services".
  12. ↑ Freudenheim, Milt (2012-10-08). "The Ups and Downs of Electronic Medical Records". New York Times.
  13. ↑ Dan Munro (2014-03-30). "Setting Healthcare Interop On Fire". Forbes . Retrieved 2014-11-22.
  14. ↑ Furukawa M. F., Raghu T. S., Spaulding T. J., Vinze A. (2008). "Adoption Of Health Information Technology For Medication Safety In U.S. Hospitals, 2006". Health Affairs. 27 (3): 865–875. doi:10.1377/hlthaff.27.3.865. PMID   18474981.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  15. ↑ 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.
  16. ↑ American College of Physicians Observer: How EMR software can help prevent medical mistakes Archived 2008-08-30 at the Wayback Machine by Jerome H. Carter (September 2004)
  17. ↑ Kawamoto, Kensaku; Houlihan, Caitlin A; Balas, E Andrew; Lobach, David F (2 Apr 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 . Retrieved 2006-06-29.
  18. ↑ Gans D, Kralewski J, Hammons T, Dowd B (2005). "Medical groups' adoption of electronic health records and information systems". Health Affairs. 24 (5): 1323–1333. doi:10.1377/hlthaff.24.5.1323. PMID   16162580 . Retrieved 2006-07-04.
  19. ↑ NHS Connecting for Health: Delivering the National Programme for IT Archived 2006-08-10 at the Wayback Machine Retrieved August 4, 2006
  20. ↑ C J Morris; B S P Savelyich; A J Avery; J A Cantrill; 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.
  21. ↑ Thorn, S.; Carter, M.; Bailey, J. (2014). "Emergency Physicians' Perspectives on Their Use of Health Information Exchange". Annals of Emergency Medicine. 63 (3): 329–337. doi:10.1016/j.annemergmed.2013.09.024. PMID   24161840.
  22. ↑ Hikmet, N. "Physicians' Resistance toward Healthcare Information Technologies: A Dual-Factor Model". CiteSeerX   10.1.1.101.9714 .
  23. ↑ Turchin, Alexander; Florez Builes, Luisa F. (2021). "Using Natural Language Processing to Measure and Improve Quality of Diabetes Care: A Systematic Review". Journal of Diabetes Science and Technology. 15 (3): 553–560. doi:10.1177/19322968211000831. ISSN   1932-2968. PMC   8120048 . PMID   33736486.
  24. 1 2 3 The Institute of Medicine (2006). "Preventing Medication Errors". The National Academies Press. doi:10.17226/11623. ISBN   978-0-309-10147-9 . Retrieved 2006-07-21.
  25. 1 2 Bates, DW; Leape, LL; Cullen, DJ; Laird, N; Petersen, LA; Teich, JM; Burdick, E; Hickey, M; Kleefield, S; Shea, B; Vander Vliet, M; Seger, DL (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.
  26. ↑ "Hospital Quality & Safety Survey" (PDF). The Leapfrog Group. 2004. Archived from the original (PDF) on 2006-09-03. Retrieved 2006-07-08.
  27. ↑ 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.
  28. ↑ "Computerized Physician Order Entry: Coming to a Hospital Near You" Archived 2012-07-05 at the Wayback Machine J. Scott Litton, Physicians Practice, March 2012.
  29. ↑ Institute of Medicine (2001). Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: The National Academies Press. Archived from the original on 2007-06-26. Retrieved 2006-06-29.
  30. ↑ 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.
  31. ↑ 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.
  32. ↑ 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.
  33. ↑ Bates D (2005). "Computerized Physician Order entry and medication errors: finding a balance". Journal of Biomedical Informatics. 38 (4): 250–261. doi: 10.1016/j.jbi.2005.05.003 . PMID   15964247.
  34. ↑ Bates D.W. (2005). "Physicians and ambulatory electronic health records". Health Affairs. 24 (5): 1180–1189. doi:10.1377/hlthaff.24.5.1180. PMID   16162561. S2CID   26709237.
  35. ↑ Ross Koppel; Cohen, A; 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.
  36. ↑ Lohr, Steve (2005-03-09). "Doctors' Journal Says Computing Is No Panacea". The New York Times. Retrieved 2006-07-15.
  37. ↑ Patrick Palmieri; et al. (2007). "Technological iatrogenesis: New risks force heightened management awareness" (PDF). Journal of Healthcare Risk Management. 27 (4): 19–24. doi:10.1002/jhrm.5600270405. PMID   20200891. Archived from the original (PDF) on 2008-12-17. Retrieved 2008-07-02.
  38. ↑ Weiner; et al. (2007). "e-Iatrogenesis: The most critical unintended consequence of CPOE and other HIT" (PDF). Journal of the American Medical Informatics Association. 14 (3): 387–388. doi:10.1197/jamia.M2338. PMC   2244888 . PMID   17329719 . Retrieved 2008-08-24.
  39. ↑ Santell, John P (2004). "Computer Related Errors: What Every Pharmacist Should Know" (PDF). United States Pharmacopia. Archived from the original (PDF) on 2008-11-20. Retrieved 2006-06-20.
  40. ↑ "A Study of An Enterprise Health Information System". Archived from the original on 2016-04-17. Retrieved 2013-04-05.
  41. ↑ "The Future of Revenue Cycle: Preparing for Near-Term Change" (PDF). HIMSS Revenue Cycle Improvement Task Force. Archived from the original (PDF) on 14 December 2013. Retrieved 18 May 2013.
  42. ↑ "Health system performance comparison: an agenda for policy, information and research (2012)". World Health Organization | Europe. Archived from the original on 2020-07-15. Retrieved 2013-11-17.

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