changes in healthcare tecnoligy policies regarding electronic healt records
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Changes in healthcare tecnoligy policies regarding electronic healt records

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Medical imaging had faced a similar challenge in the s: images captured using one make and model of equipment could not necessarily be analysed by another. The Fast Healthcare Interoperability Resources FHIR draft standard is trying to achieve the same thing for other forms of medical information, and it has now been accepted by most vendors of electronic health-record systems.

Regulations proposed by the US government health-insurance plan Medicare in February might soon make using FHIR in electronic health records a requirement. A big hope for electronic health records was that they would reduce mistakes and oversights. The notoriously illegible handwriting of many physicians has been blamed for countless errors.

Repeated photocopying or faxing can render even neatly printed documents unintelligible. And paper medical records can be mislaid, or might simply not be where they are needed. Yet digitalization has also introduced extra opportunities for error.

Wachter recalls the case of a year-old patient who, in , experienced a massive drug overdose at the UCSF Medical Center after a doctor entered the dosage in milligrams, as he would for an adult, without realizing that the computer expected the dosage to be given in milligrams per kilogram, as would be done for a child. The computer warned the dose was excessive, but the doctor had received so many false-positive warnings that he shrugged off the alert.

The pharmacist did the same. A robot then dutifully packaged the erroneously prescribed 38 and a half tablets. The nurse who administered the dose knew that it was a gross overdose, but the computer assured her that it had been signed off by both the doctor and the pharmacist, and she went ahead.

Tracking by the Pennsylvania Patient Safety Authority in Harrisburg found that from January to December , electronic health-record systems were responsible for problems during laboratory testing in the state 2 , with human—computer interactions responsible for Electronic health-record systems are designed to prevent errors by alerting clinicians to possible mistakes. But as the UCSF incident in shows, they are not foolproof.

A draft US government report issued in see go. After investigating the incident, Wachter says that UCSF identified some non-essential warnings in its electronic health-record system that staff members routinely ignored.

To reduce the risk of alert fatigue leading to similar mistakes in the future, it decided to switch off those most frequently ignored alerts. In , 11 chief executives of medical centres in the United States penned a joint open letter to their peers see go. Wachter blames this on user interfaces that look like they belong to the mids, with crucial clinical information sometimes requiring dozens of clicks to access.

Even with those clumsy interfaces, such systems enable doctors to retrieve information more efficiently than is possible with paper medical records. During the day, doctors at UCSF Medical Center spend much more time on their computers than they do with patients, he says, and they still need to spend a further two to three hours in the evening catching up on data entry.

To add insult to injury, they then often find that little of the laboriously entered information tells them something useful. A study of general practitioners in Wisconsin found that, on average, their working day lasted Of the time spent on the computer, Halamka stands by the recommendation as being reasonable, but says that when combined with other changes, including the enactment in of the US Affordable Care Act, extended patient privacy requirements and an updated version of the International Statistical Classification of Diseases and Related Health Problems, physicians have become overloaded.

Wachter notes, however, that some of the data elements were not intended to be used by doctors. Rather, their inclusion was requested by private health-care companies, which use them to reward hospitals that document good health practices in patients, such as stopping smoking.

But he also understands that it was an essential move to standardize data, to share them freely, and to get all physicians to work from the same type of medical record before implementing a further set of tools to improve performance. One way to free doctors from their keyboards might be to take advantage of improvements in the ability of machines to process the spoken word.

Some physicians already use speech-recognition systems to dictate letters, just as they used tape recorders and medical secretaries 30 years ago. Halamka imagines a system that could go beyond transcription to search for structured information in existing records.

For instance, if a person remembers having a vaccination for influenza, the system could search its files to identify the date it was administered, the supplier, the lot number and the expiration date. But questions remain, particularly with regard to patient privacy. Both Europe and the United States have strong medical-privacy rules that focus on the secure encryption of data, especially during its transmission between computers. Yet breaches of electronic health-record systems, particularly at health-insurance companies, have exposed the data of more than million people in the United States.

Such stolen medical data can be used to fraudulently invoice insurers for care that has never been provided, and on the dark net a network that hosts anonymous and often illegal online activity , the information sells for more than do credit-card data, says Erskine. More from Nature Outlooks. Speech-recognition systems process much voice data in the cloud, which could take those data out of the secure realm of the medical provider. However, to aid physicians with medical diagnoses, electronic health records could also draw on machine-learning techniques that were developed for recommending films or consumer products.

Wachter predicts systems that could search through large volumes of clinical records and insurance-reimbursement data to recommend the cheapest drug that would be effective for a patient.

This article is part of Nature Outlook: Digital health , an editorially independent supplement produced with the financial support of third parties. About this content. Dinov, I, D. PubMed Google Scholar. Liberatore, K. Patient Saf. Google Scholar.

Arndt, B. Article PubMed Google Scholar. Shanafelt, T. Mayo Clin. Download references. Digital assistants aid disease diagnosis. An AI boost for clinical trials. A fairer way forward for AI in health care. The emerging world of digital therapeutics. Your robot surgeon will see you now. An operating system for the biology lab.

News 22 NOV Science and the World Cup: how big data is transforming football. News Feature 15 NOV Hunting for the best bioscience software tool? Check this database. Technology Feature 12 JAN Should I join Mastodon? However, 4 4, 7, 10, and 20 did not provide specific information about it. No study indicated evidence of disadvantages in the quality of treatment from the use of an EMR.

Primary data studies and secondary data studies showed similar results. One of the striking studies, Zlabek et al [ 46 ] looked at the effects of an EMR system on selected measures of cost of care and patient safety.

In a national study about hospital computing and the costs and quality of care, Himmelstein et al [ 33 ] analyzed whether highly computerized hospitals had lower costs of care or administration, or better quality. They acquired the following outcomes in their work:.

In this regard, the authors found that EMRs do not reduce the rate of patient safety events. Thus, the authors concluded that EMRs contain costs by better coordinating care, a coordination that rescues patients from medical errors once they occur.

The study by Castellanos et al [ 26 ] analyzed cost and reimbursement data from a bed intensive care unit at a German university hospital in a retrospective analysis, 3 years before and 3 years after the implementation of a patient data management system PDMS. Costs and revenues increased continuously over the years. The profit of the investigated intensive care unit was fluctuating over the years and seemingly depending on other factors as well.

They found a small increase in profit in the year after the introduction of the PDMS, but not in the following years. Therefore, a clear evidence for cost savings after the introduction of PDMS was not seen. This review is an update of 2 previous analyses on the benefits and costs of EMRs, based on articles from to January [ 1 ] and to [ 2 ]. Using the same method, this review explored the progress in evidence from empirical studies.

Of the remaining 4 studies, 2 were conducted in Europe. Asia was represented by 1 Chinese and Japanese study each. South America, Africa, and Australia were not represented at all. Results of our reviews over the 3 periods showed a number of significant developments Table 6. For example, the total number of initial hits had almost doubled.

While the number of studies relevant to the evaluation remained more or less the same for the first and the current review, the second review produced almost one-third fewer studies. Remarkable in the current review was the predominant use of secondary data studies compared with primary data studies. In this context, highlighting the differences between primary and secondary studies should help to better assess the conclusions drawn from the results.

While the primary data studies collected new and yet unexplored data, the secondary data studies used statistical processing of already existing data. In general, secondary data studies do not reach the evidence level of meta-analyses comprising also already existing but initially primary data. The most important advantage of primary data studies is that data can be collected and statistically evaluated in a targeted and problem-oriented manner.

Their disadvantage is that specific surveys of patient data are often time-consuming and expensive compared with secondary data studies.

Furthermore, in case of complex interventions, as it is the case for EMRs, primary data studies are often not feasible [ 47 ]. The advantage of secondary data studies is that comparatively few resources are required to prepare them.

Their disadvantage is that the data were not collected specifically to answer the research questions as part of a specifically designed study design. The annual number of studies on EMRs showed a continuous increase over our 3 review periods Table 6.

The same was true for the annual number of finally included studies. The methodological quality of the studies changed as well. The comparison of the 3 periods revealed a twofold shift.

On the other hand, the positive effects of EMRs on quality of care became apparent over time. In the first review, none of the 4 studies concerned with quality of care presented well-defined advantages. In this review, this was the case in 14 of 18 studies analyzing the effects of EMRs on quality of care. The reasons for this shift remain speculative. The focus of EMRs might have changed from an administrative one to a patient-oriented one.

Technological progress could have helped to achieve the clinical benefits that were an important motivator for the introduction of EMRs even in the early years [ 48 ]. In , it was reported that costs remained a significant barrier for EHRs [ 49 ]. Now, experiences concerning the introduction, implementation, and an accompanying change management might have better prepared hospitals for the harvesting of clinical benefits and simultaneously for the limiting of additional costs.

Both results were nearly equal compared with the 2 previous reviews, first phase 0. Unfortunately, measures of interrater reliability are usually not presented in systematic reviews.

We assume that our results are not inferior in comparison to comparable reviews. The agreement was high in excluding references that do not fulfill the inclusion criteria. Differences occur in the detection of appropriate studies. To avoid the exclusion of false negatives, contrary votes and unclear votes were dissolved in a consensus. Misunderstandings and errors in this process cannot be completely ruled out.

The results of univariate and multivariate analyses may not agree and positive effects in one medical condition could be absent in another condition. The authors kept the EMR as type of intervention for all 3 reviews and attached great importance to an unaltered approach.

This allowed the comparison of results over the whole series of reviews. The decision to maintain the focus on the EMR might be questioned because the literature addresses many different levels of IT used in hospitals. The results are therefore neither tailorable to more detailed types of IT providing only selective functionalities as CPOE nor generalizable to lifelong EPRs or to health information and communication technology overall.

Nevertheless, through the clear and persistent focus, the authors gained reliable and valid conclusions beyond transitory trends and fashions. Furthermore, the series maintained the same set of keywords. The authors could not rule out that newer functionalities of EMRs are not appropriately covered by this set.

However, even then, the striking results supporting an indisputable positive effect of EMRs would be an underestimation of the actual situation. It is unlikely that newer functionalities decline the effects of EMRs on quality of care.

The detected studies represent primarily the perspectives of the United States and developed countries. Developed countries have the economic power to implement EMRs and to realize respective evaluation studies.

This will not be the case for developing countries. However, the perspective for developing countries is similar. For example, Odekunle et al [ 50 ] reported for Sub-Saharan Africa the same vision as it was uncovered in our review.

EHRs will improve quality of care in Sub-Saharan Africa, but high costs of procurement and maintenance of the EHR system hindered their widespread adoption until now. In the then American President, John F. With the idea of a meaningful use, health care providers and hospitals should be rewarded for using an EHR under the Medicare and Medicaid schedule. The time gap between expectations and routine application makes it clear that the proposed advantages were neither easy to demonstrate nor easy to achieve [ 54 ].

Even a proposal in for a nationwide implementation of electronic records in the next decade failed [ 14 ]. Whether an evaluation of a technology in one country could be transferred to another one remains questionable, considering different health care systems and different strategies implemented with regard to the digitization of health care [ 55 ]. Our result of the positive impact of EMRs on the quality of care is supported by a systematic review by Campanella et al [ 56 ].

Their meta-analysis of 47 studies revealed a reduction of documentation time, a higher guideline adherence, and a lower number of medication errors and adverse drug events in the intervention group using an EHR.

However, no association with mortality was found. Different to our review, the authors included studies on CPOE and did not focus on a specific area. The effect on mortality might be too small to be statistically significant even in a meta-analysis.

Therefore, the inclusion of secondary data studies in our review series was reasonable. Thompson et al [ 57 ] also did not find a positive impact of EMRs on mortality. Besides, they did not find a positive impact on length of stay and costs. Moja et al [ 58 ] also did not find effects of CDSSs on mortality in their meta-analysis based on 16 randomized controlled trials [ 58 ].

Besides secondary data analyses, ecological analysis might be worthwhile, even though the risk of an ecological fallacy exists [ 59 ]. Defining a period overlapping with our study, , they included 23 studies with a control group.

About half of the studies reported beneficial effects. However, the authors did not clearly distinguish between the effects of medication prescribing alerts as intervention and CPOE systems as infrastructure. In summary, the impact of EMR subfunctionalities remains unclear in the literature. Having EMRs as the condition, the exchange of data via HIE might bring the breakthrough in terms of quality of care and cost reduction.

In their recent review, Sadoughi et al [ 62 ] considered 32 studies published between and that analyzed the financial or clinical impact of HIE. In that review, studies on EMRs were explicitly excluded.

Furthermore, 19 studies were labeled as cohort studies, supporting our observation of a rather small number of controlled trials. Contrary to a review including studies between and [ 63 ], Sadoughi et al [ 62 ] revealed a considerable progress in the use of HIE.

However, the advantages of EMRs have to be balanced with risks that are linked to IT not necessarily considered in evaluation studies.

The relationship between the level of digitization and effects on quality and costs of care must not be linear. Higher levels of digitization might be correlated with higher risks that could lead to a reversion of the effect, as indicated by a study about the HITECH Act [ 64 ]. Therefore, it might be worthwhile to focus on the appropriate level of health IT instead of looking for global effects. Furthermore, the type of technology might not make the difference but rather the usability of the technology.

For example, Roman et al [ 65 ] analyzed navigation-related issues in the field of EHRs. A lack in usability could induce risks for health care that lower the provided level of care. Finally, one should not forget that software, hardware, or electrical power supply can fail or can be a target for criminal attacks [ 66 ].

An overall perspective on the value of EMRs must therefore include a broader definition of assets and drawbacks. Our literature review revealed a clear evidence about the value of EMRs. Only some primary data studies failed to demonstrate a reduction of costs after the implementation of an EMR. Quality of care improved in all respective studies.

In comparison with our first review covering the period between and , the picture changed completely. At that point, only 4 of 20 studies published benefits for the quality of care and 19 reported a reduction of costs. In parallel with the appearance of the first secondary data studies, the proportions turned around in the second review from to Interestingly, the positive effects on costs could not be completely confirmed by primary data studies now. To promote an extended use of EMRs, there must be a financial refund of additional costs, given the current scientific evidence.

The switch from interventional studies to observational studies using publicly available data might have induced a bias in confirming everyday perceptions about electronic records in health care. Broader and better designed studies are needed to establish better scientific evidence regarding benefits of EMRs in hospital care.

Nevertheless, further studies could focus on specific aspects of electronic records to guide their implementation and operation. Edited by R Kukafka; submitted Skip to Main Content Skip to Footer. Article Authors Cited by Tweetations 10 Metrics. Introduction This review is an update of 2 previous literature analyses on the benefits and costs of electronic medical records EMRs , based on articles from to January [ 1 ] and from to [ 2 ].

Ten years later, the WHO put this straight by stating several advantages of electronic health records EHRs in the report of the third global survey on eHealth, which was produced by the Global Observatory for eHealth [ 4 ]: EHRs improve the quality, accuracy, and timeliness of patient information at the point of care. EHRs provide insights into health care costs, utilization, and outcomes.

EHRs promote quality of care, reduce costs, support patient mobility, increase reliability of information, and provide access to patient information to multiple health care providers.

Analyses from EHR data can highlight areas of concern and health services delivery. Methods Terminology of Electronic Records in Health Care Concepts and terms denoting electronic records in health care are still not unambiguously defined [ 17 ]. Study Selection Using titles and abstracts, both authors independently reviewed the literature references regarding the existence of an EMR, the application of an EMR in inpatient care, and an empirical analysis of benefits or costs.

Inclusion and exclusion criteria. Inclusion criteria Acute care hospital Inpatient care Electronic medical record Empirical result Statement about costs Statement about benefits Exclusion criteria Physician office Ambulatory care Picture archiving and communication system System for computerized physician order entry Textbox 1. Table 1. Table 2. Classification of study designs [ 22 ]. Evidence stage Study design 1 Meta-analyses of randomized controlled trials 2 Large-sample randomized controlled trials 3 Small-sample randomized controlled trials 4 Nonrandomized controlled prospective studies 5 Nonrandomized controlled retrospective trials 6 Cohort studies 7 Case—control studies 8 Noncontrolled clinical series, descriptive studies, consensus methods 9 Anecdotes or case reports.

Table 3. Characteristics of the included studies. Study number Reference Country Sample size Period Main outcomes 1 Adler-Milstein et al [ 24 ] United States hospitals 2 years EHR a adoption is associated with better performance in terms of payment and length of stay in well-run institutions.

EHR adoption may be associated with worse performance in poorly run institutions. No relationship between EHR level and overall risk-adjusted length of stay, risk-adjusted day readmission rates, and risk-adjusted inpatient costs. In case of patient safety events, EMRs reduce deaths, readmissions, and spending.

Mean time to disposition for admitted patients remained stable. EMR implementation may be associated with reduced demand for nurses.

More computerized hospitals might have a slight quality advantage for some conditions. Patients are slightly less likely to have a hospital stay longer than 4 days at hospitals with EHRs. An EMR has no positive effect on patient costs. Table 4. Sources used by the secondary data studies. Table 5. Final score and conclusions of the included studies. Table 6. Number of studies considered for the reviews.

Review Years, n Hits without duplicates, n Hits per year, mean First selection, n Finally included studies, n Finally included studies per year, mean First 38 Multimedia Appendix 1 Included studies with scoring results. Value of the electronic patient record: an analysis of the literature.

Value of the electronic medical record for hospital care: a review of the literature. Journal of Healthcare Engineering Sep;2 3 Resolutions and Decisions. Global Observatory for eHealth. Global diffusion of eHealth: Making universal health coverage achievable. Geneva, Switzerland: World Health Organization; European C. A European strategy for data. Brussels, The electronic health record: a comparison of some European countries. In: Ricciardi F, Harfouche A, editors. Information and communication technologies in organizations and society.

Past, present and future issues. Cham: Springer; Health IT and patient safety: building safer systems for better care. Washington D. C: National Academy of Sciences; Blumenthal D, Tavenner M.

The "meaningful use" regulation for electronic health records. N Engl J Med Aug 05; 6 Same goals, yet different outcomes: analysing the current state of ehealth adoption and policies in Austria, Germany, and Switzerland using a mixed methods approach.

Stud Health Technol Inform Aug 21; Could 9: connecting clinicians for better health care. Dick R, Steen E, editors. The computer-based patient record. An essential technology for health care. How well is the electronic health record supporting the clinical tasks of hospital physicians? A survey of physicians at three Norwegian hospitals. Berlin, Germany: Beuth; Definition, structure, content, use and impacts of electronic health records: a review of the research literature.

Int J Med Inform May;77 5 The five levels of electronic health records. MD Comput ;13 3 The measurement of observer agreement for categorical data. Biometrics Mar;33 1 Effects of computer-based clinical decision support systems on clinician performance and patient outcome.

A critical appraisal of research. Ann Intern Med Jan 15; 2 Assessing telemedicine: a systematic review of the literature.

Leveraging EHRs to improve hospital performance: the role of management. EHR adoption and hospital performance: time-related effects. Health Affairs Apr;29 4 Electronic health record functions differ between best and worst hospitals.

Health information technology and its effects on hospital costs, outcomes, and patient safety. A custom-developed emergency department provider electronic documentation system reduces operational efficiency. Ann Emerg Med Nov;70 5 Electronic medical records, nurse staffing, and nurse-sensitive patient outcomes: evidence from California hospitals,

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