Factors influencing the development of primary care data collection projects from electronic health records: a systematic review of the literature (original) (raw)
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Family Practice, 2005
de Lusignan S and van Weel C. The use of routinely collected computer data for research in primary care: opportunities and challenges. Family Practice 2006; 23: 253-263. Introduction. Routinely collected primary care data has underpinned research that has helped define primary care as a specialty. In the early years of the discipline, data were collected manually, but digital data collection now makes large volumes of data readily available. Primary care informatics is emerging as an academic discipline for the scientific study of how to harness these data. This paper reviews how data are stored in primary care computer systems; current use of large primary care research databases; and, the opportunities and challenges for using routinely collected primary care data in research.
BMC medical informatics and decision making, 2016
Electronic medical records (EMR) offer a major potential for secondary use of data for research which can improve the safety, quality and efficiency of healthcare. They also enable the measurement of disease burden at the population level. However, the extent to which this is feasible in different countries is not well known. This study aimed to: 1) assess information governance procedures for extracting data from EMR in 16 countries; and 2) explore the extent of EMR adoption and the quality and consistency of EMR data in 7 countries, using management of diabetes type 2 patients as an exemplar. We included 16 countries from Australia, Asia, the Middle East, and Europe to the Americas. We undertook a multi-method approach including both an online literature review and structured interviews with 59 stakeholders, including 25 physicians, 23 academics, 7 EMR providers, and 4 information commissioners. Data were analysed and synthesised thematically considering the most relevant issues. ...
einstein (São Paulo), 2019
Data collection for clinical research can be difficult, and electronic health record systems can facilitate this process. The aim of this study was to describe and evaluate the secondary use of electronic health records in data collection for an observational clinical study. We used Cerner Millennium®, an electronic health record software, following these steps: (1) data crossing between the study’s case report forms and the electronic health record; (2) development of a manual collection method for data not recorded in Cerner Millennium®; (3) development of a study interface for automatic data collection in the electronic health records; (4) employee training; (5) data quality assessment; and (6) filling out the electronic case report form at the end of the study. Three case report forms were consolidated into the electronic case report form at the end of the study. Researchers performed daily qualitative and quantitative analyses of the data. Data were collected from 94 patients. In the first case report form, 76.5% of variables were obtained electronically, in the second, 95.5%, and in the third, 100%. The daily quality assessment of the whole process showed complete and correct data, widespread employee compliance and minimal interference in their practice. The secondary use of electronic health records is safe and effective, reduces manual labor, and provides data reliability. Anesthetic care and data collection may be done by the same professional.
Electronic health records (EHRs) have emerged among health information technology as Bmeaningful use^ to improve the quality and efficiency of healthcare, and health disparities in population health. In other instances, they have also shown lack of interoperability, functionality and many medical errors. With proper implementation and training, are electronic health records a viable source in managing population health? The primary objective of this systematic review is to assess the relationship of electronic health records' use on population health through the identification and analysis of facilitators and barriers to its adoption for this purpose. Authors searched Cumulative Index of Nursing and Allied Health Literature (CINAHL) and MEDLINE (PubMed), 10/02/2012-10/02/2017, core clinical/academic journals, MEDLINE full text, English only, human species and evaluated the articles that were germane to our research objective. Each article was analyzed by multiple reviewers. Group members recognized common facilitators and barriers associated with EHRs effect on population health. A final list of articles was selected by the group after three consensus meetings (n = 55). Among a total of 26 factors identified, 63% (147/232) of those were facilitators and 37% (85/232) barriers. About 70% of the facilitators consisted of productivity/efficiency in EHRs occurring 33 times, increased quality and data management each occurring 19 times, surveillance occurring 17 times, and preventative care occurring 15 times. About 70% of the barriers consisted of missing data occurring 24 times, no standards (interoperability) occurring 13 times, productivity loss occurring 12 times, and technology too complex occurring 10 times. The analysis identified more facilitators than barriers to the use of the EHR to support public health. Wider adoption of the EHR and more comprehensive standards for interoperability will only enhance the ability for the EHR to support this important area of surveillance and disease prevention. This review identifies more facilitators than barriers to using the EHR to support public health, which implies a certain level of usability and acceptance to use the EHR in this manner. The public-health industry should combine their efforts with the interoperability projects to make the EHR both fully adopted and fully interoperable. This will greatly increase the availability, accuracy, and comprehensiveness of data across the country, which will enhance benchmarking and disease surveillance/prevention capabilities.
Data recording in primary care field studies: Patient records enhancement project
2011
This position paper describes the Human-Computer Interaction (HCI) field studies component of the multidisciplinary Patient Records Enhancement Project (PREP). PREP seeks to understand variability of data found in primary care electronic records, in particular the balance between coded data and doctor's 'free text' notes. HCI fieldwork will establish variables that affect recording practices. In field studies we observe and record data recording practices in general practice (GP) surgeries, interview staff, video consultations with real patients and video consultations with standardized patients (played by medical actors). By standardizing patients we can compare the impact of other variables: different doctors, in different surgeries, using different e-health systems. Our early findings suggest that variability is due to a complex web of reasons, driven by personal, contextual and organizational processes. Findings from thematic analysis will result in design implications for studies by epidemiologists and public health researchers, design of NHS training and work processes, and design of electronic health record interfaces.
Studies in Health Technology and Informatics, 2011
Objective: To define the key concepts which inform whether a system for collecting, aggregating and processing routine clinical data for research is fit for purpose. Methods: Literature review and shared experiential learning from research using routinely collected data. We excluded socio-cultural issues, and privacy and security issues as our focus was to explore linking clinical data. Results: Six key concepts describe data: (1) Data quality: the core Overarching concept-Are these data fit for purpose? (2) Data provenance: defined as how data came to be; incorporating the concepts of lineage and pedigree. Mapping this process requires metadata. New variables derived during data analysis have their own provenance. (3) Data extraction errors and (4) Data processing errors, which are the responsibility of the investigator extracting the data but need quantifying. (5) Traceability: the capability to identify the origins of any data cell within the final analysis table essential for good governance, and almost impossible without a formal system of metadata; and (6) Curation: storing data and look-up tables in a way that allows future researchers to carry out further research or review earlier findings. Conclusion: There are common distinct steps in processing data; the quality of any metadata may be predictive of the quality of the process. Outputs based on routine data should include a review of the process from data origin to curation and publish information about their data provenance and processing method.
Enabling research in general practice--increasing functionality of electronic medical records
Australian family physician, 2010
With an estimated 80% of Australians visiting a general practitioner at least once a year, the data generated by GPs is a rich source of the overall health profile of patients. However, this data is rarely used to report on health outcomes. This article reports on the use of remote access of electronic medical records (EMRs) for the purpose of collecting data during a collaborative research project involving the staff of three general practices and an external research team. Throughout the project numerous benefits to remotely accessing general practice EMRs were identified. However, there remain some difficulties which need to be addressed. An increased functionality of the software programs used in general practice is required, along with improvements in the utilisation of the software capabilities. Collaboration between clinicians, researchers and clinical software developers will be vital to advance this process.