The Following Are Barriers To Electronic Health Record Except

The main objective of this research is to identify, categorize, and analyze barriers perceived by physicians to the adoption of Electronic Medical Records (EMRs) in order to provide implementers with beneficial intervention options.

A systematic literature review, based on research papers from 1998 to 2009, concerning barriers to the acceptance of EMRs by physicians was conducted. Four databases, Science, EBSCO, PubMed and The Cochrane Library, were used in the literature search. Studies were included in the analysis if they reported on physicians' perceived barriers to implementing and using electronic medical records. Electronic medical records are defined as computerized medical information systems that collect, store and display patient information.

The study includes twenty-two articles that have considered barriers to EMR as perceived by physicians. Eight main categories of barriers, including a total of 31 sub-categories, were identified. These eight categories are: A) Financial, B) Technical, C) Time, D) Psychological, E) Social, F) Legal, G) Organizational, and H) Change Process. All these categories are interrelated with each other. In particular, Categories G (Organizational) and H (Change Process) seem to be mediating factors on other barriers. By adopting a change management perspective, we develop some barrier-related interventions that could overcome the identified barriers.

Comparison Of User Groups' Perspectives Of Barriers And Facilitators To Implementing Electronic Health Records: A Systematic Review

Despite the positive effects of EMR usage in medical practices, the adoption rate of such systems is still low and meets resistance from physicians. This systematic review reveals that physicians may face a range of barriers when they approach EMR implementation. We conclude that the process of EMR implementation should be treated as a change project, and led by implementers or change managers, in medical practices. The quality of change management plays an important role in the success of EMR implementation. The barriers and suggested interventions highlighted in this study are intended to act as a reference for implementers of Electronic Medical Records. A careful diagnosis of the specific situation is required before relevant interventions can be determined.

Electronic Medical Records (EMRs) are computerized medical information systems that collect, store and display patient information. They are a means to create legible and organized recordings and to access clinical information about individual patients. Further, EMRs are intended to replace existing (often paper based) medical records which are already familiar to practitioners [1]. Patient records have been stored in paper form for centuries and, over this period of time, they have consumed increasing space and notably delayed access to efficient medical care [2]. In contrast, EMRs store individual patient clinical information electronically and enable instant availability of this information to all providers in the healthcare chain and so should assist in providing coherent and consistent care.

Electronic Medical Records (EMRs) and Electronic Health Records (EHRs) are viewed as interchangeable synonyms in most health informatics. Other similar expressions exist albeit with a sometimes slightly restricted focus. While EMRs have a general focus on medical care, Electronic Patient Records (EPRs) and Computerized Patient Records (CPRs) contain clinical information about a patients from a particular hospital and Electronic Health Care Records (EHCRs) contain a patient's health information [3].

Ehr Implementation: Top Challenages And Barriers To Adoptation And Use

The perceived advantages of EMRs can be summarized as optimizing the documentation of patient encounters, improving communication of information to physicians, improving access to patient medical information, reduction of errors, optimizing billing and improving reimbursement for services, forming a data repository for research and quality improvement, and reduction of paper [4]. As EMRs are viewed as having a great potential for improving quality, continuity, safety and efficiency in healthcare, they are being implemented across the world.

Despite the high expectations and interest in EMRs worldwide, their overall adoption rate is relatively low and they face several problems [5]. For instance, they are seen as contrary to a physician's traditional working style, they require a greater capability in dealing with computers and installing a system absorbs considerable financial resources [6]. According to Meinert [7], the slow rate of adoption suggests that resistance among physicians must be strong because physicians are the main frontline user-group of EMRs. Whether or not they support and use EMRs will have a great influence on other user-groups in a medical practice, such as nurses and administrative staff. As a result, physicians have a great impact on the overall adoption level of EMRs.

As it requires physicians to actively support and use EMRs to benefit from them, it is essential to understand the possible barriers to their implementation from the physicians' perspectives. Although there is already a body of literature on such barriers, there has been no systematic overview of these studies combined with an analysis of how to address these barriers. Therefore, the objective of this research is to identify, categorize, and analyze barriers perceived by physicians to the adoption of Electronic Medical Records (EMRs). Further, possible barrier-related interventions will be suggested to support implementers of EMRs in overcoming this reluctance.

An Overview Of Clinical Decision Support Systems: Benefits, Risks, And Strategies For Success

In the following sections, a systematic literature review will be carried out to identify all the barriers that result in physicians showing resistance towards EMRs. Following this, these barriers will be categorized in a taxonomy in order to gain a wider understanding of them. From an analysis of the taxonomy, the relationships among these barriers will be highlighted. Finally, possible barrier-related interventions will be suggested that could reduce resistance, and further research opportunities identified.

In order for this study to reflect recent events, be up-to-date and comprehensive, a systematic literature search of four relevant databases (Web of Science, EBSCO, PubMed and The Cochrane Library) was conducted for the period from January 1998 to May 2009. The search was performed using the key words: barrier, physician, doctor, |electronic medical record, electronic health record, adopt* and appropriate combinations thereof. Due to minor differences in search options, slightly different search strategies were used for each database. The reference lists of identified studies were scanned for further relevant articles.

For Search Strategy 3 and Search Strategy 4, the Subject Areas and Document Types fields were further refined in order to enhance the relevance of the results. The Subject Areas were limited to the sub-fields Health Care Sciences & Services, Medical Informatics, Medicine, General & Internal. Document Types were limited to Article and Proceeding Paper.

Three Common Barriers To Ehr Implementation And How To Avoid Them

Studies identified using the above strategies had to further meet the following selection criteria to be included in the literature review: 1) articles written in English, 2) article solely focused on EMR or EHR, not involving other electronic systems used in medical practices, 3) articles related to barriers linked to physicians (medical specialists, general practitioners), not to other medical staff, 4) based on empirical studies and published in scientific journals. As such, articles not specifically focusing on EMR/EHR (for example on IT systems or computerization) were excluded. Further, articles whose target groups were practices or clinicians were excluded because these articles not only covered physicians but also nurses, physician's assistants and other staff. The articles first identified in the reference lists of the papers found through the database searches were assessed using the same criteria.

For each of the studies that had survived this filtering, the research approach was first assessed. If it was a qualitative study, the number of cases and the methods used in data collection were identified. If it had used a quantitative approach, information concerning the sample size was sought. At the same time, the countries and the clinical areas of the included studies were recorded. Secondly, the empirical results of the studies related to expected or experienced barriers were summarized for further analysis. Further, the barrier focus of each study was deduced from the title or the abstract of the article.

By applying the different database search strategies, 1671 articles were identified (including several duplicates of articles appearing in more than one database), see Figure 1.

User Perspectives On Barriers And Facilitators To The Implementation Of Electronic Health Records In Behavioral Hospitals: Qualitative Study

After an initial screening carried out by two independent student researchers, 72 articles were duplicates. Of the remaining 1597 articles, 1533 were excluded because they did not meet, based on the content of their titles and abstracts, one of selection criteria 2), 3), and 4). Disagreements about exclusions between the two student researchers were resolved through discussions with one of the authors of this paper. Of the 64 articles remaining, 41 were commentaries or literature reviews, therefore lacking fresh empirical data and thus excluded. Of the 23 empirical studies left, one was presenting the same data with similar analyses and, as the relevance was minor, only one was retained. No additional relevant articles were found within the reference lists, as those meeting the selection criteria were already included. Thus, we ended up with 22 articles that met the inclusion criteria, and these were further analyzed by the two student researchers and both authors. Table 1 below lists the selected articles and the identified barriers.

Of these 22 studies, 13 were quantitative, 7 qualitative, 1 mixed qualitative-quantitative research, and 1 concept-mapping research. Only four of the studies were executed outside the USA, but many different clinical areas were included. As this breakdown indicates, the majority of the researchers had opted for quantitative research methods (questionnaires) to explore the barriers facing physicians in EMR adoption. This approach enables researchers to reach many physicians and cover a wide spectrum. This

In the following sections, a systematic literature review will be carried out to identify all the barriers that result in physicians showing resistance towards EMRs. Following this, these barriers will be categorized in a taxonomy in order to gain a wider understanding of them. From an analysis of the taxonomy, the relationships among these barriers will be highlighted. Finally, possible barrier-related interventions will be suggested that could reduce resistance, and further research opportunities identified.

In order for this study to reflect recent events, be up-to-date and comprehensive, a systematic literature search of four relevant databases (Web of Science, EBSCO, PubMed and The Cochrane Library) was conducted for the period from January 1998 to May 2009. The search was performed using the key words: barrier, physician, doctor, |electronic medical record, electronic health record, adopt* and appropriate combinations thereof. Due to minor differences in search options, slightly different search strategies were used for each database. The reference lists of identified studies were scanned for further relevant articles.

For Search Strategy 3 and Search Strategy 4, the Subject Areas and Document Types fields were further refined in order to enhance the relevance of the results. The Subject Areas were limited to the sub-fields Health Care Sciences & Services, Medical Informatics, Medicine, General & Internal. Document Types were limited to Article and Proceeding Paper.

Three Common Barriers To Ehr Implementation And How To Avoid Them

Studies identified using the above strategies had to further meet the following selection criteria to be included in the literature review: 1) articles written in English, 2) article solely focused on EMR or EHR, not involving other electronic systems used in medical practices, 3) articles related to barriers linked to physicians (medical specialists, general practitioners), not to other medical staff, 4) based on empirical studies and published in scientific journals. As such, articles not specifically focusing on EMR/EHR (for example on IT systems or computerization) were excluded. Further, articles whose target groups were practices or clinicians were excluded because these articles not only covered physicians but also nurses, physician's assistants and other staff. The articles first identified in the reference lists of the papers found through the database searches were assessed using the same criteria.

For each of the studies that had survived this filtering, the research approach was first assessed. If it was a qualitative study, the number of cases and the methods used in data collection were identified. If it had used a quantitative approach, information concerning the sample size was sought. At the same time, the countries and the clinical areas of the included studies were recorded. Secondly, the empirical results of the studies related to expected or experienced barriers were summarized for further analysis. Further, the barrier focus of each study was deduced from the title or the abstract of the article.

By applying the different database search strategies, 1671 articles were identified (including several duplicates of articles appearing in more than one database), see Figure 1.

User Perspectives On Barriers And Facilitators To The Implementation Of Electronic Health Records In Behavioral Hospitals: Qualitative Study

After an initial screening carried out by two independent student researchers, 72 articles were duplicates. Of the remaining 1597 articles, 1533 were excluded because they did not meet, based on the content of their titles and abstracts, one of selection criteria 2), 3), and 4). Disagreements about exclusions between the two student researchers were resolved through discussions with one of the authors of this paper. Of the 64 articles remaining, 41 were commentaries or literature reviews, therefore lacking fresh empirical data and thus excluded. Of the 23 empirical studies left, one was presenting the same data with similar analyses and, as the relevance was minor, only one was retained. No additional relevant articles were found within the reference lists, as those meeting the selection criteria were already included. Thus, we ended up with 22 articles that met the inclusion criteria, and these were further analyzed by the two student researchers and both authors. Table 1 below lists the selected articles and the identified barriers.

Of these 22 studies, 13 were quantitative, 7 qualitative, 1 mixed qualitative-quantitative research, and 1 concept-mapping research. Only four of the studies were executed outside the USA, but many different clinical areas were included. As this breakdown indicates, the majority of the researchers had opted for quantitative research methods (questionnaires) to explore the barriers facing physicians in EMR adoption. This approach enables researchers to reach many physicians and cover a wide spectrum. This