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. From Wikipedia, the free encyclopedia.
See also: Health informatics. Main article: Electronic health record. Main article: Computerized physician order entry. Medicine portal. BMJ Open. Annals of Internal Medicine. April Health IT Buzz.
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Many of the changes occurring within medicine are being catalyzed by the proliferation of professional and social activity with the internet and mobile technology. Understanding how healthcare is being transformed by IT is key to the improvement of medical standards and reduction of cost. The synergy between computer.
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Decision aids Doctor—patient relationship E-patient Health 2. Health information on Wikipedia Online patient education PubMed. Open-source healthcare software Patient opinion leader Research participant Virtual patient. Student nurse Clinical nurse leader Licensed practical nurse Registered nurse Graduate nurse. Clinical nurse specialist Nurse anesthetist Nurse midwife Nurse practitioner.
Nursing assessment Nursing diagnosis Nursing care plan Nursing theory. Category Commons WikiProject. Internal medicine. Obstetrics and gynaecology.
Gynaecology Gynecologic oncology Maternal—fetal medicine Obstetrics Reproductive endocrinology and infertility Urogynecology. Radiology Interventional radiology Nuclear medicine Pathology Anatomical Clinical pathology Clinical chemistry Clinical immunology Cytopathology Medical microbiology Transfusion medicine. A healthcare-focused librarian, under the direction of all authors, conducted the literature search. The articles for final selection were discussed and decided upon among the authors. The structured approach was guided by the model illustrated in Figure 3.
The process to article inclusion involved three passes to collect publications related to health IT in quality and patient safety for peer-reviewed studies published between , inclusive. From the articles gathered, additional keywords were added to the search. Each article was further analyzed to identify the degree to which the article discussed health IT in healthcare quality and patient safety.
To be considered for inclusion, the study needed to report on the actual use of health IT in healthcare quality and patient safety. Forty-one studies met these criteria. Those studies with their contributions to the results are shown in the results section of this paper. Qualitative data analysis software Atlas. All 41 documents were uploaded into the document manager in Atlas.
During this process, the article title was used as the PD name. Inductive thematic analysis with open coding was used under the three pre-set categories of prevention, identification, and action [ 22 ]. This allowed for capturing descriptions of how health IT was used in each circumstance. For example, prevention included descriptions of any use of health IT to prevent quality issues or potential safety events, identification included any descriptions of the use of health IT to identify quality issues or safety events, and action included any descriptions of the use of health IT to act on quality issues or safety events that have occurred.
When content was noted that did not fit into the three pre-set categories, an additional category was created. Additional categories were created to capture challenges relative to the use of health IT in quality and patient safety. Since some papers discussed how the use of health IT impacted health outcomes, an additional category was created for outcomes.
Lastly, an additional category was created to capture the study settings or location. The coding structure was agreed upon by all authors, and one author conducted the coding. After all of the studies were coded, two additional passes were made through the data. The first pass was to ensure that all information from the studies that should be coded was actually coded and coded to the correct code ie, was a passage that described prevention actually coded to prevention? The second pass was to consider sub-categories for consolidation.
Six sub-categories were consolidated. The purpose of examining co-occurrences is to understand what, if any, relation exists between concepts [ 22 , 23 ]. Within Atlas. This table was then exported to Microsoft Excel for further analysis. Network maps are a means by which analysis can be visualized in relationships to provide a different perspective on the codes, categories, etc. Those presented in the results do not differ from the final coding structure, but instead are used to provide a visual representation.
Literature reviews can be conducted using a qualitative approach [ 24 , 25 ] with the results displayed in a variety of ways to support models and show connections [ 22 ]. Table 1 provides a listing of the articles and their contribution in this results section to support the model Figure 2 , network maps Figure 4 through Figure 7 , and co-occurrences Table 2.
Article contribution to results in alphabetical order.
From the 41 studies that fit the inclusion criteria, any element in which the authors discussed the use of health IT for healthcare quality and patient safety was identified, even if it did not fit into the three previously determined categories. Across all of the articles, there were 63 and 92 descriptions of the use of health IT for identification and prevention of healthcare quality and patient safety issues, respectively. Health IT for action and the challenges associated with health IT for healthcare quality and patient safety was described 41 and 43 times, respectively.
The findings from the literature review are presented by the categories outlined in the previously introduced model for improving the reliability of healthcare quality and patient safety. The first exploration was across the literature that discussed health IT for prevention of quality and patient safety issues to see exactly how organizations were reporting health IT use to prevent a quality and safety event from even happening.
The greatest areas of use were around alerts [ 30 , 31 , 44 , 56 , 58 ], clinical decision support [ 39 , 44 , 47 , 56 ], implementation [ 10 , 32 , 37 , 38 , 56 ], interface design [ 26 , 34 , 42 , 45 , 56 , 59 ], and customized health IT solutions [ 29 , 30 , 32 , 34 , 46 - 50 , 56 , 58 , 59 ]. Customized health IT solutions were anything that described the use of health IT but lacked any specificity beyond that described in this section. For example, this could be something as simple as checklists or as complex as algorithmic diagnostic trees.
To clarify, alerts are a subset of clinical decision support. Since so many of the occurrences specified alerts and clinical decision support separately, these were coded separately. Implementation and interface design were each described in terms of having been poorly implemented or poorly designed and having implications on utility in healthcare quality and safety.
The next exploration was across the literature that discussed health IT for identification of quality and patient safety issues; in other words, how health IT was used to identify a quality and safety event when it is about to occur. In this regard, similar to prevention but described differently in the included studies , alerts [ 26 , 30 , 31 , 44 , 56 , 58 ], clinical decision support [ 30 , 31 , 39 , 44 , 56 , 58 ], implementation [ 10 , 32 , 38 , 56 ], and customized health IT solutions [ 10 , 30 , 31 , 34 , 46 - 49 , 52 , 56 , 58 ] were most prominent.
British Medical Journal. Healthcare Professional Engagement Self-learning and eDetailing mechanisms with a repository of interactive scientific medical data about drugs, procedures, diseases. Quality and Safety in Health Care. Hence, ICD was introduced to simplify the procedures with unknown codes and unify the standards closer to world standards ICD IT outsourcing, help desk, integration, analytics, performance monitoring, content management. Health Telematics Networks.
For example, alerts, clinical decision support, and customized health IT solutions were all described in the literature as having been implemented to identify a potential quality or patient safety issue, yet the literature also described how the implementation of these could have been better in terms of providing more training to those on the receiving end of the alerts, clinical decision support, or other customized health IT solutions.
The third exploration was across the literature that discussed health IT for action on a quality and safety event once it has already occurred. In regards to action, the major areas were documentation [ 10 , 32 , 37 , 41 , 46 , 56 , 58 ], implementation [ 10 , 32 , 37 , 58 ], and culture [ 10 , 29 , 41 , 53 , 58 ] relative to the use of health IT.
The findings from the review of the literature show that implementation appeared in prevention, identification, and action.
Implementation in general has been demonstrated in the literature as a challenge, and that was revealed in this literature review also. Culture was most often referred to as needing to create a culture of quality and patient safety in order for health IT to be embraced.
Organizations that started working on culture change before implementation of health IT solutions suggested that health IT for acting on quality and patient safety events was more favorable. Therefore, the analysis was run with challenges which suggests the major areas are: culture, implementation, and interface design.