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Добірка наукової літератури з теми "Electronic health record systems"

Автор: Grafiati
Опубліковано: 10 січня 2023
Оновлено: 28 січня 2023

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Статті в журналах з теми "Electronic health record systems"

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Mehmood, Hamid, Muhammad Aslam, Sadia Aslam, Ammara Waqar, Athar Khan, Yasir Hassan, Faryal Murtaza Cheema, Hassan Mujtaba, and Noor-e. Maham. "ELECTRONIC HEALTH RECORD SYSTEMS;." Professional Medical Journal 24, no. 01 (January 18, 2017): 182–87. http://dx.doi.org/10.29309/tpmj/2017.24.01.401.

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Анотація:
Introduction: e-Health is a combination of medical informatics, public health,business and information technology. Health information technology has increased theproductivity by reengineering of health care but it requires new measurement tools to monitorthe impact of it .e-health is not only for the development of technologies but also it includesproper planning, thinking, broad thinking to improve healthcare services with the help ofinformation and communication technology. Objectives: 1) To assess the perceptions ofphysicians towards the use, effectiveness and efficiency of EHR 2) To identify the differencesbetween electronic and paper based records 3) To evaluate the usage of Electronic HealthRecords.4) To analyze satisfaction and challenges face by the physicians using EHR. ResearchDesign: This is an Exploratory and Descriptive Research. In this study hybrid research methodis used which includes qualitative and quantitative research methods. Sampling technique:For this study, a purposive sample of 43 physicians was selected. The sample size was 60but 17 responses were incomplete so they were excluded and the final sample size was 43.Data was collected from two different hospitals of Pakistan which include the physicians fromShaukat Khanum Memorial Cancer Hospital and Research Centre, and Indus Hospital. Of the43 participants, 51% were from Indus Hospital and 49% were from Shaukat Khanum MemorialCancer Hospital and Research Centre. Instrument: A structured questionnaire was used tocollect data and it was collected by email responses and direct interview. EHR Questionnaire:A questionnaire was used in the study. The EHR Questionnaire has comprised of 24 items. Thisquestionnaire was developed by Msukwa. B.K.Martin.1 Data Analysis: Data analysis was doneby Statistical Package for Social Sciences (SPSS) and Microsoft Excel. Procedure: The sampleconsisted of physicians from Shaukat Khanum Memorial Cancer Hospital and Research Centre,and Indus Hospital from Karachi. EHR is a new technology and hospitals are moving towardsit, some are under process and very few like the above mentioned hospitals are using it. Thequestionnaire was not complicated. It was a structured questionnaire with easy questions withmultiple options to fill in. Respondents were also acknowledged for their cooperation andparticipation in the study. Conclusion: EHR should be used effectively, proper training is neededto ensure that physicians are able to operate the system and can have maximum benefits fromthe technology by utilizing all its applications. The government should encourage adoption ofElectronic Health l Records in Pakistan by developing a public-private partnership. The studyfocused also on EHR effectiveness by checking the working of EHR its quick and satisfactoryresults its accuracy, adequacy, timeliness, user- friendliness, availability and reliability.
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Seymour, Tom, Dean Frantsvog, and Tod Graeber. "Electronic Health Records (EHR)." American Journal of Health Sciences (AJHS) 3, no. 3 (July 13, 2012): 201–10. http://dx.doi.org/10.19030/ajhs.v3i3.7139.

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Анотація:
Electronic Health Records are electronic versions of patients’ healthcare records. An electronic health record gathers, creates, and stores the health record electronically. The electronic health record has been slow to be adopted by healthcare providers. The federal government has recently passed legislation requiring the use of electronic records or face monetary penalties. The electronic health record will improve clinical documentation, quality, healthcare utilization tracking, billing and coding, and make health records portable. The core components of an electronic health record include administrative functions, computerized physician order entry, lab systems, radiology systems, pharmacy systems, and clinical documentation. HL7 is the standard communication protocol technology that an electronic health record utilizes. Implementation of software, hardware, and IT networks are important for a successful electronic health record project. The benefits of an electronic health record include a gain in healthcare efficiencies, large gains in quality and safety, and lower healthcare costs for consumers. Electronic health record challenges include costly software packages, system security, patient confidentiality, and unknown future government regulations. Future technologies for electronic health records include bar coding, radio-frequency identification, and speech recognition.
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Galli, Brian J. "Ethics of Electronic Health Record Systems." International Journal of Information Systems and Social Change 9, no. 3 (July 2018): 53–69. http://dx.doi.org/10.4018/ijissc.2018070104.

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Анотація:
This article describes how healthcare and IT are combatting the ethical implications of electronic health records (EHRs) in order to make them adopted by over 90% of small practices. There is a lack of trust in EHRs and uneasiness about what they will accomplish. Furthermore, security concerns have become more prevalent as a result of increased hacker activity. The objective of this article is to analyze these ethical issues in an effort to eliminate them as a hinderance to EHR implementation. As of now, 98% of all hospitals use EHRs. Between 2009 and 2015, the government allocated money and resources for incentive programs to get EHRs into every healthcare providers' office. During this time period, over $800 million dollars facilitated EHR implementation. Using this as a tool EHRs negative perception can be revitalized and combated with the meaningful use program. This article will highlight the ethical implications of EHRs and suggest ways in which to avoid them to make EHRs available in every healthcare provider.
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Ohno-Machado, Lucila, Jihoon Kim, Rodney A. Gabriel, Grace M. Kuo, and Michael A. Hogarth. "Genomics and electronic health record systems." Human Molecular Genetics 27, R1 (April 18, 2018): R48—R55. http://dx.doi.org/10.1093/hmg/ddy104.

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Sanders, David S., Daniel J. Lattin, Sarah Read-Brown, Daniel C. Tu, David J. Wilson, Thomas S. Hwang, John C. Morrison, Thomas R. Yackel, and Michael F. Chiang. "Electronic Health Record Systems in Ophthalmology." Ophthalmology 120, no. 9 (September 2013): 1745–55. http://dx.doi.org/10.1016/j.ophtha.2013.02.017.

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Nøhr, C. "Evaluation of Electronic Health Record Systems." Yearbook of Medical Informatics 15, no. 01 (August 2006): 107–13. http://dx.doi.org/10.1055/s-0038-1638481.

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Анотація:
SummaryThe objective of this article is to present an overview of the various considerations to be made prior to evaluating electronic health record (EHR) systems.From the methodological literature, a number of themes for decisions are presented and related to the contemporary EHR situation. Special attention is paid to a number of important methodological themes.Definitive checklists for evaluation of EHR systems can not be recommended, but seven key steps are listed to guide the design of evaluation projects.It is concluded that the issues presented are not completely exhausted and the seven key steps might have to include iterative loops because of interdependencies between some of the steps.
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N., Gayathri. "A Model for Xml-based Electronic Health Record System." International Journal of Psychosocial Rehabilitation 24, no. 5 (April 20, 2020): 5785–807. http://dx.doi.org/10.37200/ijpr/v24i5/pr2020286.

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King, Jason, Ben Smith, and Laurie Williams. "Audit Mechanisms in Electronic Health Record Systems." International Journal of Computational Models and Algorithms in Medicine 3, no. 2 (April 2012): 23–42. http://dx.doi.org/10.4018/jcmam.2012040102.

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Анотація:
Inadequate audit mechanisms may result in undetected misuse of data in software-intensive systems. In the healthcare domain, electronic health record (EHR) systems should log the creating, reading, updating, or deleting of privacy-critical protected health information. The objective of this paper is to assess electronic health record audit mechanisms to determine the current degree of auditing for non-repudiation and to assess whether general audit guidelines adequately address non-repudiation. The authors analyzed the audit mechanisms of two open source EHR systems, OpenEMR and Tolven eCHR, and one proprietary EHR system. The authors base the qualitative assessment on a set of 16 general auditable events and 58 black-box test cases for specific auditable events. The authors find that OpenEMR satisfies 62.5% of the general criteria and passes 63.8% of the black-box test cases. Tolven eCHR and the proprietary EHR system each satisfy less than 19% of the general criteria and pass less than 11% of the black-box test cases.
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Winter, Alfred, Katsuhiko Takabayashi, Franziska Jahn, Eizen Kimura, Rolf Engelbrecht, Reinhold Haux, Masayuki Honda, et al. "Quality Requirements for Electronic Health Record Systems." Methods of Information in Medicine 56, S 01 (January 2017): e92-e104. http://dx.doi.org/10.3414/me17-05-0002.

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SummaryBackground: For more than 30 years, there has been close cooperation between Japanese and German scientists with regard to information systems in health care. Collaboration has been formalized by an agreement between the respective scientific associations. Following this agreement, two joint workshops took place to explore the similarities and differences of electronic health record systems (EHRS) against the background of the two national healthcare systems that share many commonalities.Objectives: To establish a framework and requirements for the quality of EHRS that may also serve as a basis for comparing different EHRS.Methods: Donabedian’s three dimensions of quality of medical care were adapted to the outcome, process, and structural quality of EHRS and their management. These quality dimensions were proposed before the first workshop of EHRS experts and enriched during the discussions.Results: The Quality Requirements Framework of EHRS (QRF-EHRS) was defined and complemented by requirements for high quality EHRS. The framework integrates three quality dimensions (outcome, process, and structural quality), three layers of information systems (processes and data, applications, and physical tools) and three dimensions of information management (strategic, tactical, and operational information management).Conclusions: Describing and comparing the quality of EHRS is in fact a multidimensional problem as given by the QRF-EHRS framework. This framework will be utilized to compare Japanese and German EHRS, notably those that were presented at the second workshop.
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McCormick, Danny, Stephanie Woolhandler, and David U. Himmelstein. "Electronic Health Record Systems: The Authors Reply." Health Affairs 31, no. 6 (June 2012): 1366. http://dx.doi.org/10.1377/hlthaff.2012.0475.

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Дисертації з теми "Electronic health record systems"

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Chang, Jaime. "Medication concepts, records, and lists in electronic medical record systems." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/35551.

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Анотація:
Thesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology, 2006.
Includes bibliographical references.
A well-designed implementation of medication concepts, records, and lists in an electronic medical record (EMR) system allows it to successfully perform many functions vital for the provision of quality health care. A controlled medication terminology provides the foundation for decision support services, such as duplication checking, allergy checking, and drug-drug interaction alerts. Clever modeling of medication records makes it easy to provide a history of any medication the patient is on and to generate the patient's medication list for any arbitrary point in time. Medication lists that distinguish between description and prescription and that are exportable in a standard format can play an essential role in medication reconciliation and contribute to the reduction of medication errors. At present, there is no general agreement on how to best implement medication concepts, records, and lists. The underlying implementation in an EMR often reflects the needs, culture, and history of both the developers and the local users. survey of a sample of medication terminologies (COSTAR Directory, the MDD, NDDF Plus, and RxNorm) and EMR implementations of medication records (OnCall, LMR, and the Benedum EMR) reveals the advantages and disadvantages of each. There is no medication system that would fit perfectly in every single context, but some features should strongly be considered in the development of any new system.
(cont.) A survey of a sample of medication terminologies (COSTAR Directory, the MDD, NDDF Plus, and RxNorm) and EMR implementations of medication records (OnCall, LMR, and the Benedum EMR) reveals the advantages and disadvantages of each. There is no medication system that would fit perfectly in every single context, but some features should strongly be considered in the development of any new system.
by Jaime Chang.
S.M.
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2

Sundvall, Erik. "Scalability and Semantic Sustainability in Electronic Health Record Systems." Doctoral thesis, Linköpings universitet, Medicinsk informatik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-87702.

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Анотація:
This work is a small contribution to the greater goal of making software systems used in healthcare more useful and sustainable. To come closer to that goal, health record data will need to be more computable and easier to exchange between systems. Interoperability refers to getting systems to work together and semantics concerns the study of meanings. If Semantic interoperability is achieved then information entered in one information system is usable in other systems and reusable for many purposes. Scalability refers to the extent to which a system can gracefully grow by adding more resources. Sustainability refers more to how to best use available limited resources. Both aspects are important. The main focus and aim of the thesis is to increase knowledge about how to support scalability and semantic sustainability. It reports explorations of how to apply aspects of the above to Electronic Health Record (EHR) systems, associated infrastructure, data structures, terminology systems, user interfaces and their mutual boundaries. Using terminology systems is one way to improve computability and comparability of data. Modern complex ontologies and terminology systems can contain hundreds of thousands of concepts that can have many kinds of relationships to multiple other concepts. This makes visualization challenging. Many visualization approaches designed to show the local neighbourhood of a single concept node do not scale well to larger sets of nodes. The interactive TermViz approach described in this thesis, is designed to aid users to navigate and comprehend the context of several nodes simultaneously. Two applications are presented where TermViz aids management of the boundary between EHR data structures and the terminology system SNOMED CT. The amount of available time from people skilled in health informatics is limited. Adequate methods and tools are required to develop, maintain and reuse health-IT solutions in a sustainable way. Multiple levels of modelling including a fixed reference model and another layer of flexible reusable ‘archetypes’ for domain specific data structures, is an approach with that aim used in openEHR and the ISO 13606 standard. This approach, including learning, implementing and managing it, is explored from different angles in this thesis. An architecture applying Representational State Transfer (REST) to archetype-based EHR systems, in order to address scalability, is presented. Combined with archetyping this architecture also aims at enabling a sustainable way of continuously evolving multi-vendor EHR solutions. An experimental open source implementation of it, aimed for learning and prototyping, is also presented. Manually changing database structures used for storage every time new versions of archetypes and associated data structures are needed is likely not a sustainable activity. Thus storage systems that can handle change with minimal manual interventions are desirable. Initial explorations of performance and scalability in such systems are also reported Graphical user interfaces focused on EHR navigation, time-perspectives and highlighting of EHR content are also presented – illustrating what can be done with computable health record data and the presented approaches. Desirable aspects of semantic sustainability have been discussed, including: sustainable use of limited resources (such as available time of skilled people), and reduction of unnecessary risks. A semantic sustainability perspective should be inspired and informed by research in complex systems theory, and should also include striving to be highly aware of when and where technical debt is being built up. Semantic sustainability is a shared responsibility. The combined results presented contribute to increasing knowledge about ways to support scalability and semantic sustainability in the context of electronic health record systems. Supporting tools, architectures and approaches are additional contributions.
Syftet med denna avhandling är ytterst att göra informationssystem som används i hälso- och sjukvård, särskilt patientjournaler, mer användbara och lättarbetade. Om systemen vore lättare att utveckla och underhålla skulle fler resurser kunna läggas på att tillföra nya och mer användarvänliga funktioner. Om journalsystem och datorprogram kan ”begripa” vad olika saker i journalen är och betyder så kan de vara till större hjälp, t.ex. genom att visa bättre patientöversikter och bidra med beslutsstöd. En del i att göra journalinnehållet begripligt och hanterbart för datorer är att använda sig av terminologisystem som t.ex. ICD-10 och SNOMED CT. En annan viktig del är datastrukturerna där man stoppar in text, mätvärden, koderna från terminologisystem etc. De flesta journalsystem har någon sorts mallar som datastrukturer. Projektet openEHR har tagit fram ett sätt att dela specifikationer av datastrukturer mellan olika journalsystem så att man lättare kan dela och återanvända dem och den journaldata som matats in i dem. Dessa specifikationer kallas ”arketyper” och arketyp-metoden beskrivs även i standarden ISO 13606. Om två olika journalsystem använder samma datastruktur, t.ex. med hjälp av samma arketyper, så kan de utväxla patientdata mellan varandra (de uppnår s.k. semantisk interoperabilitet). Begreppet ”Semantic sustainability” definieras i avhandlingen som ett förhållningssätt som är bredare än semantisk interoperabilitet. Det syftar till att möjliggöra långsiktigt hållbar utveckling av semantik (betydelse) i journalsystem och genom att hantera risker och resurser förståndigt. Förhållningssättet baserar sig på forskning och erfarenheter från systemutveckling och hantering av komplexa system och är avsett att stödja beslutsfattare, och de som utvecklar och underhåller journalsystem, relaterade system och strukturer. För att datorsystem ska kunna växa vid ökad användning ,utan att hamna i återvändsgränder avseende prestanda, så bör vissa designprinciper för skalbarhet följas. Avhandlingen presenterar en systemarkitektur baserad på sådana principer och på arketyp-metoden. Denna arkitektur gör det möjligt att bygga system med delsystem från flera olika leverantörer. Skalbarheten i några lagringslösningar redovisas också. Slutligen redovisas prototyper av gränssnitt för patientöversikter och journalläsning.
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Erdil, Nadiye Özlem. "Systems analysis of electronic health record adoption in the U.S. healthcare system." Diss., Online access via UMI:, 2009.

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Анотація:
Thesis (Ph. D.)--State University of New York at Binghamton, Thomas J. Watson School of Engineering and Applied Science, Department of Systems Science and Industrial Engineering, 2009.
Includes bibliographical references.
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4

Reid, Jr Marvin Leon. "Adoption of Electronic Health Record Systems Within Primary Care Practices." ScholarWorks, 2016. https://scholarworks.waldenu.edu/dissertations/2228.

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Анотація:
Primary care physicians (PCPPs) have been slow to implement electronic health records (EHRs), even though there is a U.S. federal requirement to implement EHRs. The purpose of this phenomenological study was to determine why PCPPs have been slow to adopt electronic health record (EHR) systems despite the potential to increase efficiency and quality of health care. The complex adaptive systems theory (CAS) served as the conceptual framework for this study. Twenty-six PCPPs were interviewed from primary care practices (PCPs) based in southwestern Ohio. The data were collected through a semistructured interview format and analyzed using a modified van Kaam method. Several themes emerged as barriers to EHR implementation, including staff training on the new EHR system, the decrease in productivity experienced by primary care practice (PCP) staff adapting to the new EHR system, and system usability and technical support after adoption. The findings may contribute to the body of knowledge regarding EHR system implementation and assist healthcare providers who are slow to adopt EHRs. Additionally, findings could contribute to social change by reducing healthcare costs, increasing patient access to care, and improving the efficacy of patient diagnosis and treatment.
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Borek, Jarrod. "Managerial Strategies for Maximizing Benefits From Electronic Health Record Systems." ScholarWorks, 2018. https://scholarworks.waldenu.edu/dissertations/4959.

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Анотація:
In 2009, the U.S. government allocated $27 billion to health care agencies for electronic health records (EHRs) implementation. The increased use of EHR systems is expected to drive down health care costs and increase profits. To meet this anticipated return on investment (ROI), hospital managers need to be able to successfully design, deploy, and manage EHR systems. The purpose of this single case study was to explore organizational management strategies that hospital managers can use to ensure their investments in EHRs meet targeted ROIs and work efficiency goals. The conceptual framework for this study was based on the technology acceptance model. Primary data were collected from a criterion sample of 6 hospital managers with direct experience designing and implementing successful EHRs in a small hospital in the Northeastern United States. Secondary data were collected using public financial records available on the Internet. After cataloging and grouping the raw data, 4 emergent themes were identified: (a) training, (b) the role of organizational management strategies, (c) technological barriers, and (d) ongoing support and maintenance. Findings may contribute to social change through an increase in the quality of patient care and making health care records more accessible to doctors in isolated areas.
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Xin, Zhang. "Distributed Electronic Health Record System based on Middleware." Thesis, Mittuniversitetet, Institutionen för informationsteknologi och medier, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-18947.

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Анотація:
With the fast development of information technology, traditional healthcare is evolving to a more digital and electronic stage. Electronic HealthRecord (EHR) is residents’ basic information and health care relatedinformation conforming to standard. It can not only provide usefulinformation to medical workers, but also exchange resources with otherinformation systems. But with the growing complexity of electronichealth record data sources, it becomes a big challenge to set up a structurewhich allows different types of data sharing and exchanging inmulti-platform applications. It’s even more important to find out amethod to support great amount of users from different applicationplatform to sharing and exchanging data at the same time.In this paper, we proposed a distributed electronic health record systembased on middleware to address the problem. Both permanent and realtimedata should pass through the middleware provided by the system,and will be transformed into standard format for storage. Multi-threadand distributed server group design will let the system be more flexibleand scalable, and will be able to provide service to users concurrently.The system creates a standard data format for data transferring andstorage. All raw data collected from different kinds of sensor system willbe formatted with application programming interface (API) or softwaredevelopment kit (SDK) system provided before upload to the system.Encryption methods are also implemented to ensure data security andprivacy protection.
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Almutiry, Omar Saud. "Data quality assessment instrument for electronic health record systems in Saudi Arabia." Thesis, University of Southampton, 2017. https://eprints.soton.ac.uk/419029/.

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Анотація:
The provision of high quality data is of considerable importance to both business and government; poor data may lead to poor decisions, so quality plays a crucial role. With the proliferation of electronic data collection by businesses and governments, there has arisen a pressing need to assure this quality. This has been recognized by both the private and public sectors, and many initiatives such as the Data Quality Initiative Framework by the Welsh government, passed in 2004, and the Data Quality Act by the United States government, passed in 2002, have been launched to improve it in those countries. At the same time, healthcare is a domain in which the timely provision of accurate, current and complete patient data is one of the most important objectives. Instigation of a so-called Electronic Health Record (EHR), defined as a repository of patient data in digital form that is stored and exchanged securely and is accessible by different levels of authorized users, has been attracting the attention of both research and industry. EHRs allow information regarding a patient’s health to be distributed among heterogeneous information systems. This evolution has added a layer of complexity in data quality, making data quality assurance a challenging issue, as the key barriers to optimal use of EHR data are the increasing quantity of data and their poor quality. Many data quality frameworks have been developed to measure the quality of data in information systems. However, there is no consensus on a rigorously defined set of data quality dimensions. Existing dimensions are usually based on literature reviews, industrial experiences or intuitive understanding and do not take into consideration the nature of e-healthcare systems. Moreover, definitions of these dimensions vary from one data quality framework to another. The aim of this research is to develop a data quality framework consisting of health-relevant dimensions, and data quality measures that help health organisations to enhance the quality of their data. The study provides both subjective and objective measures for assessing the quality of data. An 11-dimensional data quality framework has been developed and confirmed by EHR stakeholders and a group of experts and data consumers. With each dimension, several associated measures have been developed to help an organisation to measure the quality of the data populating their EHR systems. Some issues linked with the measures associated with security-related dimensions have arisen during the confirmation stage. Therefore, these issues were further discussed and reviewed with security experts in order to revise the proposed framework and its measures. Subsequently, a case study was conducted in a large hospital to examine the practicality of the proposed instrument. The instrument was used to help hospitals to assess their data. After that, the usefulness and practicality of the instrument were examined through an evaluation questionnaire distributed to quality assessment team members. Follow-up interviews with senior managers were carried out to discuss the output of the assessment and its practicality. The contribution of this research is the development of a proper data quality framework for EHRs in the context of Saudi Arabia which resulted in 11 health-relevant data quality dimensions. An instrument was also introduced to represent all developed and confirmed measures that assess data population in EHRs.
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Tannan, Ritu. "Acceptance and Usage of Electronic Health Record Systems in Small Medical Practices." ScholarWorks, 2011. https://scholarworks.waldenu.edu/dissertations/1028.

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Анотація:
One of the objectives of the U.S. government has been the development of a nationwide health information infrastructure, including adoption and use of an electronic health records (EHR) system. However, a 2008 survey conducted by the National Center for Health Statistics indicated a 41.5% usage of the EHR system by physicians in office-based practices. The purpose of this study was to explore opinions and beliefs on the barriers to the diffusion of an ERH system using Q-methodology. Specifically, the research questions examined the subjectivity in the patterns of perspectives at the preadoption stage of the nonusers and at the postadoption stage of the users of an EHR system to facilitate effective diffusion. Data were collected by self-referred rank ordering of opinions on such barriers and facilitators. The results suggested that the postadoption barriers of time, change in work processes, and organizational factors were critical. Although the time barrier was common, barriers of organizational culture and change in work processes differed among typologies of perspectives at the postadoption stage. Preadoption barriers of finance, organizational culture, time, technology, and autonomy were critical. The typologies of perspectives diverged on critical barriers at the preadoptive stage. A customized solution of an in-house system and training is recommended for perspectives dealing with technical and organizational concerns and a web-based system for perspectives concerned with barriers of finance, technology, and organization. The social impact of tailoring solutions to personal viewpoints would result in the increased sharing of quality medical information for meaningful decision making.
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Chen, Rong. "Towards interoperable and knowledge-based electronic health records using archetype methodology /." Linköping : Department of Biomedical Engineering, Linköpings universitet, 2009. http://www.bibl.liu.se/liupubl/disp/disp2009/tek1280s.htm.

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San, Jose Rhoda Lynn Atienza. "Educating Nurses on Workflow Changes from Electronic Health Record Adoption." ScholarWorks, 2017. https://scholarworks.waldenu.edu/dissertations/3321.

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Workflow issues related to adoption of the electronic health record (EHR) has led to unsafe workarounds, decreased productivity, inefficient clinical documentation and slow rates of EHR adoption. The problem addressed in this quality improvement project was nurses' lack of knowledge about workflow changes due to EHR adoption. The purpose of this project was to identify changes in workflow and to develop an educational module to communicate the changes. This project was guided by both the ADDIE model (analysis, design, development, implementation, and evaluation) and the diffusion of innovations theory. Five stages were involved: process mapping, cognitive walkthrough, eLearning module development, pilot study, and evaluation. The process maps and cognitive walkthrough revealed significant workflow changes particularly in clinical practice guidelines, emergency department treatment plan, and the interdisciplinary care plan. The eLearning module was developed to describe workflow changes using gamification, scenario-based learning, and EHR simulation. The 14-item course evaluation included a 6-point Likert scale and closed- and open-ended questions. A purposive sample of nurses (N = 30) from the emergency department and inpatient care areas were invited to complete the eLearning module and course evaluation. Data were collected until saturation was achieved (n = 15). Descriptive statistics revealed the participants' positive learning experience. This quality improvement project is expected to contribute to positive social change by facilitating the effective use of the new EHR which can improve the quality of patient care, promote patient safety, reduce healthcare costs, and improve patient outcomes.
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Книги з теми "Electronic health record systems"

1

D, Gelzer Reed, and Bowers Donna, eds. How to evaluate electronic health record (EHR) systems. Chicago, Ill: American Health Information Management Association, 2008.

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Electronic health records for allied health careers. Boston: McGraw Hill, 2009.

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3

Walker, James M., Eric J. Bieber, and Frank Richards, eds. Implementing an Electronic Health Record System. London: Springer-Verlag, 2005. http://dx.doi.org/10.1007/b138849.

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Electronic health record: A systems analysis of the medications domain. Boca Raton: Taylor & Francis, 2012.

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Electronic health records. Boston: McGraw Hill Higher Education, 2009.

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6

Strategies for electronic document and health record management. Chicago, Illinois: AHIMA , American Health Information Management Association, 2014.

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7

Williams, Trenor. Electronic health records for dummies. Hoboken, N.J: Wiley, 2011.

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8

The electronic health record for the physician's office with Medtrak systems. St. Louis, Mo: Elsevier/ Saunders, 2012.

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9

Clinical problem lists in the electronic health record. Toronto: Apple Academic Press, 2015.

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10

Eichenwald, Shirley. Using the electronic health record in the health care provider practice. Clifton Park, NY: Thomson Delmar Learning, 2008.

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Частини книг з теми "Electronic health record systems"

1

Shabo, Amnon. "Electronic Health Record." In Encyclopedia of Database Systems, 1–6. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4899-7993-3_48-2.

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(Shvo), Amnon Shabo. "Electronic Health Record." In Encyclopedia of Database Systems, 1–6. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4899-7993-3_48-3.

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Shabo (Shvo), Amnon. "Electronic Health Record." In Encyclopedia of Database Systems, 968–72. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_48.

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Shabo (Shvo), Amnon. "Electronic Health Record." In Encyclopedia of Database Systems, 1273–79. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_48.

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Tang, Paul C., and Clement J. McDonald. "Electronic Health Record Systems." In Health Informatics, 447–75. New York, NY: Springer New York, 2006. http://dx.doi.org/10.1007/0-387-36278-9_12.

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McDonald, Clement J., Paul C. Tang, and George Hripcsak. "Electronic Health Record Systems." In Biomedical Informatics, 391–421. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4474-8_12.

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7

Bisbal, Jesus. "Electronic Health Record Systems." In Encyclopedia of Systems Biology, 649–50. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_630.

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Vimalachandran, Pasupathy, Hua Wang, and Yanchun Zhang. "Securing Electronic Medical Record and Electronic Health Record Systems Through an Improved Access Control." In Health Information Science, 17–30. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19156-0_3.

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Bisbal, Jesus. "Electronic Health Records." In Encyclopedia of Systems Biology, 650–52. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_222.

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Kök, Orhun Mustafa, Nuri Basoglu, and Tugrul U. Daim. "Adoption Factors of Electronic Health Record Systems." In Healthcare Technology Innovation Adoption, 189–249. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-17975-9_8.

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Тези доповідей конференцій з теми "Electronic health record systems"

1

AZHAGIRI, M., AMRITA R, R. APARNA, and JASHMITHA B. "Secured Electronic Health Record Management System." In 2018 3rd International Conference on Communication and Electronics Systems (ICCES). IEEE, 2018. http://dx.doi.org/10.1109/cesys.2018.8724010.

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Guang Dong and Weili Shi. "Community electronic health record system model." In 2011 International Conference on Computer Science and Service System (CSSS). IEEE, 2011. http://dx.doi.org/10.1109/csss.2011.5974778.

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Veinot, Tiffany C., Kai Zheng, Julie C. Lowery, Maria Souden, and Rosalind Keith. "Using electronic health record systems in diabetes care." In the ACM international conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1882992.1883026.

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4

Khan, Arshia, and John Grillo. "Quality of Care and Electronic Health Record Systems." In BCB'13: ACM-BCB2013. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2506583.2512371.

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Khan, Arshia, and John Grillo. "Role of Quality in Electronic Health Record Systems." In BCB'13: ACM-BCB2013. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2506583.2512379.

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Ved, Vishesh, Vivek Tyagi, Ankur Agarwal, and A. S. Pandya. "Personal Health Record System and Integration Techniques with Various Electronic Medical Record Systems." In 2011 IEEE 13th International Symposium on High-Assurance Systems Engineering (HASE). IEEE, 2011. http://dx.doi.org/10.1109/hase.2011.63.

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AlZghoul, Majd M., Majid A. Al-Taee, and Anas M. Al-Taee. "Towards nationwide electronic health record system in Jordan." In 2016 13th International Multi-Conference on Systems, Signals & Devices (SSD). IEEE, 2016. http://dx.doi.org/10.1109/ssd.2016.7473731.

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Popescu, Mihail, George Chronis, Rohan Ohol, Marjorie Skubic, and Marilyn Rantz. "An eldercare electronic health record system for predictive health assessment." In 2011 IEEE 13th International Conference on e-Health Networking, Applications and Services (Healthcom 2011). IEEE, 2011. http://dx.doi.org/10.1109/health.2011.6026742.

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Butt, Nida, and Juan Shan. "CyberCare: A Novel Electronic Health Record Management System." In 2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE). IEEE, 2016. http://dx.doi.org/10.1109/chase.2016.52.

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Caroprese, Luciano, Pierangelo Veltri, Eugenio Vocaturo, and Ester Zumpano. "Deep Learning Techniques for Electronic Health Record Analysis." In 2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA). IEEE, 2018. http://dx.doi.org/10.1109/iisa.2018.8633647.

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Звіти організацій з теми "Electronic health record systems"

1

Gillen, Emily, Olivia Berzin, Adam Vincent, and Doug Johnston. Certified Electronic Health Record Technology Under the Quality Payment Program. RTI Press, January 2018. http://dx.doi.org/10.3768/rtipress.2018.pb.0014.1801.

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The 2016 Quality Payment Program (QPP) is a Medicare reimbursement reform designed to incentivize value-based care over volume-based care. A core tenet of the QPP is integrated utilization of certified electronic health record technology (CEHRT). Adopting and implementing CEHRT is a resource-intensive process, requiring both financial capital and human capital (in the form of knowledge and time). Adoption can be especially challenging for small or rural practices that may not have access to such capital. In this issue brief, we discuss the role of CEHRT in the QPP and offer policy recommendations to help small and rural practices improve their health information technology (IT) capabilities with regards to participation in value-based care. The QPP requires practices to have health IT capabilities, both as a requirement for a complete performance score and to facilitate reporting. Practices that are unable to implement CEHRT will have difficulty complying with the new reimbursement system, and will likely incur financial losses. We recommend monetary support and staff training to small and rural practices for the adoption of CEHRT, and we recommend assistance to help practices comply with the requirements of the QPP and coordinate with other small and rural practices for reporting purposes.
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Barclay, Colleen, Meera Viswanathan, Shana Ratner, Julia Tompkins, and Daniel E. Jonas. Implementing Evidence-Based Screening and Counseling for Unhealthy Alcohol Use With Epic-Based Electronic Health Record Tools. A Guide for Clinics and Health Systems, Developed as Part of a Pilot Dissemination Project. Agency for Healthcare Research and Quality (AHRQ), September 2018. http://dx.doi.org/10.23970/ahrqepcmethengagealcoholguide.

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Schumacher, Robert M., and Svetlana Z. Lowry. Customizzed common industry format template for electronic health record usability testing. Gaithersburg, MD: National Institute of Standards and Technology, 2010. http://dx.doi.org/10.6028/nist.ir.7742.

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Hubbard, Rebecca A., Yong Chen, Jinbo Chen, Joanna Harton, Grace Choi, Arman Oganisian, Jing Huang, et al. Developing Statistical Methods for Estimating Phenotypes Using Electronic Health Record Data. Patient-Centered Outcomes Research Institute (PCORI), March 2021. http://dx.doi.org/10.25302/03.2021.me.151132666.

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Shepherd, Bryan_, and Pamela Shaw. New Methods to Improve Data Accuracy in Studies Using Electronic Health Record Data. Patient-Centered Outcomes Research Institute® (PCORI), August 2022. http://dx.doi.org/10.25302/08.2022.me.160936207.

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Dunn, Michael A., and Melissa Saul. Framework for Smart Electronic Health Record-Linked Predictive Models to Optimize Care for Complex Digestive Diseases. Fort Belvoir, VA: Defense Technical Information Center, July 2014. http://dx.doi.org/10.21236/ada608042.

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Veerappan, Ganesh. Framework for Smart Electronic Health Record - Linked Predictive Models to Optimize Care for Complex Digestive Diseases. Fort Belvoir, VA: Defense Technical Information Center, June 2012. http://dx.doi.org/10.21236/ada568058.

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Betteridge, John D. Framework for Smart Electronic Health Record- Linked Predictive Models to Optimize Care for Complex Digestive Diseases. Fort Belvoir, VA: Defense Technical Information Center, August 2013. http://dx.doi.org/10.21236/ada588419.

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Dunn, Michael A., and Melissa Saul. Framework for Smart Electronic Health Record-Linked Predictive Models to Optimize Care for Complex Digestive Diseases. Fort Belvoir, VA: Defense Technical Information Center, June 2013. http://dx.doi.org/10.21236/ada601336.

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Betteridge, John D. Framework for Smart Electronic Health Record- Linked Predictive Models to Optimize Care for Complex Digestive Diseases. Fort Belvoir, VA: Defense Technical Information Center, March 2015. http://dx.doi.org/10.21236/ada614941.

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