Informatics in Primary Care (BCS, The Chartered Institute for IT)
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595 research outputs found
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Effectively reducing amylase testing using computer order entry in the emergency department: quality improvement without eliminating physician choice
Full text linkBackground Amylase and lipase, pancreatic biomarkers, are measured in acute pancreatitis diagnosis. Since amylase testing does not add diagnostic value, lipase testing alone is recommended. Despite new recommendations, many physicians and staff continue to test both amylase and lipase.Objective To reduce unnecessary diagnostic testing in acute pancreatitis.Methods The pre-checked amylase test within the Emergency Department’s Computerized Provider Order Entry (CPOE) abdominal pain order set was changed to an un-checked state, but kept as an option to order with a single click. Amylase testing, lipase testing and cost were measured for one year pre and post intervention.Results Simple de-selection intervention reduced redundant amylase testing from 71% to 9%, resulting in a percent of decrease of 87% and an annualized saving of approximately $719,000 in charges.Conclusion CPOE de-selection is an effective tool to reduce non-value added activity and reduce cost while maintaining quality patient care and physician choice
A survey exploring National Health Service ePrescribing Toolkit use and perceived usefulness amongst English hospitals
Full text linkBackground: There is currently limited guidance for hospitals to implement ePrescribing systems. We have developed an ePrescribing Toolkit designed to support ongoing implementation, adoption and optimisation of efforts.Aim: To investigate the perceived usefulness, reported use and areas for further development of the Toolkit by ePrescribing implementers in English hospitals.Methods: Questionnaire-based survey of hospitals that have or are interested in implementing ePrescribing systems.Results: We received responses from a total of 78 individuals representing 49 English NHS Trusts (out of 82 different Trusts who were emailed the survey, 60% response rate). The overwhelming majority of respondents (92%) were familiar with the ePrescribing Toolkit and 66% reported using it to guide their ongoing implementation efforts. The majority of ePrescribing Toolkit users (85%) viewed it as a helpful resource. Implementers particularly valued the case studies describing lessons learnt from hospitals that had already implemented ePrescribing systems. Suggestions for improvement included more information in relation to the progress of hospitals implementing systems, the names of key contacts in these sites, a list of available systems and the contact details of ePrescribing vendors. Respondents also highlighted the need for more information on optimisation and specialist prescribing.Conclusions: Interactive elements and learning lessons from early adopter sites that had accumulated experiences of implementing systems was viewed as the most helpful aspect of the ePrescribing Toolkit. The Toolkit now needs to be further developed to facilitate the continuing implementation/optimisation of ePrescribing and other health information technology across the NHS
Ethnicity Recording in Primary Care Computerised Medical Record Systems: An Ontological Approach
Full text linkBackground Ethnicity recording within primary care computerised medical record (CMR) systems is suboptimal, exacerbated by tangled taxonomies within current coding systems.Objective To develop a method for extending ethnicity identification using routinely collected data.Methods We used an ontological method to maximise the reliability and prevalence of ethnicity information in the Royal College of General Practitioner’s Research and Surveillance database. Clinical codes were either directly mapped to ethnicity group or utilised as proxy markers (such as language spoken) from which ethnicity could be inferred. We compared the performance of our method with the recording rates that would be identified by code lists utilised by the UK pay for the performance system, with the help of the Quality and Outcomes Framework (QOF).Results Data from 2,059,453 patients across 110 practices were included. The overall categorisable ethnicity using QOF codes was 36.26% (95% confidence interval (CI): 36.20%–36.33%). This rose to 48.57% (CI:48.50%–48.64%) using the described ethnicity mapping process. Mapping increased across all ethnic groups. The largest increase was seen in the white ethnicity category (30.61%; CI: 30.55%–30.67% to 40.24%; CI: 40.17%–40.30%). The highest relative increase was in the ethnic group categorised as the other (0.04%; CI: 0.03%–0.04% to 0.92%; CI: 0.91%–0.93%).Conclusions This mapping method substantially increases the prevalence of known ethnicity in CMR data and may aid future epidemiological research based on routine data
Health Information Exchange as a Complex and Adaptive Construct: Scoping Review
Full text linkObjectiveTo understand how the concept of Health Information Exchange (HIE) has evolved over time.Methods Supplementary analysis of data from a systematic scoping review of definitions of HIE from 1900 to 2014, involving temporal analysis of underpinning themes.ResultsThe search identified 268 unique definitions of HIE dating from 1957 onwards; 103 in scientific databases and 165 in Google. These contained consistent themes, representing the core concept of exchanging health information electronically, as well as fluid themes, reflecting the evolving policy, business, organisational and technological context of HIE (including the emergence of HIE as an organisational ‘entity’). These are summarised graphically to show how the concept has evolved around the world with the passage of time. The term HIE emerged in 1957 with the establishment of Occupational HIE, evolving through the 1990s with concepts such as electronic data interchange and mobile computing technology; then from 2006-10 largely aligning with the US Government’s health information technology strategy and the creation of HIEs as organisational entities, alongside the broader interoperability imperative, and continuing to evolve today as part of a broader international agenda for sustainable, information-driven health systems.ConclusionsThe concept of HIE is an evolving and adaptive one, reflecting the ongoing quest for integrated and interoperable information to improve the efficiency and effectiveness of health systems, in a changing technological and policy environment
Probabilistic linkage to enhance deterministic algorithms and reduce data linkage errors in hospital administrative data
No full textBackground: The pseudonymisation algorithm used to link together episodes of care belonging to the same patient in England [Hospital Episode Statistics ID (HESID)] has never undergone any formal evaluation to determine the extent of data linkage error.Objective: To quantify improvements in linkage accuracy from adding probabilistic linkage to existing deterministic HESID algorithms.Methods: Inpatient admissions to National Health Service (NHS) hospitals in England (HES) over 17 years (1998 to 2015) for a sample of patients (born 13th or 28th of months in 1992/1998/2005/2012). We compared the existing deterministic algorithm with one that included an additional probabilistic step, in relation to a reference standard created using enhanced probabilistic matching with additional clinical and demographic information. Missed and false matches were quantified and the impact on estimates of hospital readmission within one year was determined.Results: HESID produced a high missed match rate, improving over time (8.6% in 1998 to 0.4% in 2015). Missed matches were more common for ethnic minorities, those living in areas of high socio-economic deprivation, foreign patients and those with ‘no fixed abode’. Estimates of the readmission rate were biased for several patient groups owing to missed matches, which were reduced for nearly all groups.Conclusion: Probabilistic linkage of HES reduced missed matches and bias in estimated readmission rates, with clear implications for commissioning, service evaluation and performance monitoring of hospitals. The existing algorithm should be modified to address data linkage error, and a retrospective update of the existing data would address existing linkage errors and their implications
The Multimorbidity Cluster Analysis Tool: Identifying Combinations and Permutations of Multiple Chronic Diseases Using a Record-Level Computational Analysis
Full text linkIntroduction: Multimorbidity, or the co-occurrence of multiple chronic health conditions within an individual, is an increasingly dominant presence and burden in modern health care systems. To fully capture its complexity, further research is needed to uncover the patterns and consequences of these co-occurring health states. As such, the Multimorbidity Cluster Analysis Tool and the accompanying Multimorbidity Cluster Analysis Toolkit have been created to allow researchers to identify distinct clusters that exist within a sample of participants or patients living with multimorbidity. Development: The Tool and Toolkit were developed at Western University in London, Ontario, Canada. This open-access computational program (JAVA code and executable file) was developed and tested to support an analysis of thousands of individual records and up to 100 disease diagnoses or categories. Application: The computational program can be adapted to the methodological elements of a research project, including type of data, type of chronic disease reporting, measurement of multimorbidity, sample size and research setting. The computational program will identify all existing, and mutually exclusive, combinations and permutations within the dataset. An application of this computational program is provided as an example, in which more than 75,000 individual records and 20 chronic disease categories resulted in the detection of 10,411 unique combinations and 24,647 unique permutations among female and male patients. Discussion: The Tool and Toolkit are now available for use by researchers interested in exploring the complexities of multimorbidity. Its careful use, and the comparison between results, will be valuable additions to the nuanced understanding of multimorbidity.
Research Outputs of England’s Hospital Episode Statistics (HES) Database: Bibliometric Analysis
Full text linkBackground: Hospital administrative data, such as those provided by the Hospital Episode Statistics (HES) database in England, are increasingly being used for research and quality improvement. To date, no study has tried to quantify and examine trends in the use of HES for research purposes.Objective: To examine trends in the use of HES data for research.Methods: Publications generated from the use of HES data were extracted from PubMed and analysed. Publications from 1996 to 2014 were then examined further in the Science Citation Index (SCI) of the Thompson Scientific Institute for Science Information (Web of Science) for details of research specialty area.Results: 520 studies, categorised into 44 specialty areas, were extracted from PubMed. The review showed an increase in publications over the 18-year period with an average of 27 publications per year, however with the majority of output observed in the latter part of the study period. The highest number of publications was in the Health Statistics specialty area.Conclusion: The use of HES data for research is becoming more common. Increase in publications over time shows that researchers are beginning to take advantage of the potential of HES data. Although HES is a valuable database, concerns exist over the accuracy and completeness of the data entered. Clinicians need to be more engaged with HES for the full potential of this database to be harnessed.
Connecting Medical Records: An Evaluation of Benefits and Challenges for Primary Care Practices
Full text linkBackground: Implementation of systems to support health information sharing has lagged other areas of healthcare IT, yet offers a strong possibility for benefit. Clinical acceptance is a key limiting factor in health IT adoption.Objectives: To assess the benefits and challenges experienced by clinicians using a custom-developed health information exchange system, and to show how perceptions of benefits and challenges influence perceptions of productivity and care-related outcomes.Methods: We used a mixed methods design with two phases. First, we conducted interviews with stakeholders who were familiar with the health information exchange system to inform the development of a measure of benefits and challenges of the use of this system. Second, using this measure we conducted a survey of current and former users of the health information exchange system using a modified Dillman method.Results: 105 current and former users completed the survey. The results showed information quality, ease of completing tasks and clinical process improvement as key benefits that reduced workload and improved patient care. Challenges related to system reliability, quality of reports and service quality increased workload and decreased impact on care, though the effect of the challenges was smaller than that of the benefits.Conclusions: Even very limited health information exchange capabilities can improve outcomes for primary care users. Improving perceptions of benefits may be even more important the removing challenges to use, though it is likely that a threshold of quality must be achieved for this to be true
Design and implementation of an affordable, public sector electronic medical record in rural Nepal
Full text linkIntroductionGlobally, electronic medical records are central to the infrastructure of modern healthcare systems. Yet the vast majority of electronic medical records have been designed for resource-rich environments and are not feasible in settings of poverty. Here we describe the design and implementation of an electronic medical record at a public sector district hospital in rural Nepal, and its subsequent expansion to an additional public sector facility.DevelopmentThe electronic medical record was designed to solve for the following elements of public sector healthcare delivery: 1) integration of the systems across inpatient, surgical, outpatient, emergency, laboratory, radiology, and pharmacy sites of care; 2) effective data extraction for impact evaluation and government regulation; 3) optimization for longitudinal care provision and patient tracking; and 4) effectiveness for quality improvement initiatives.ApplicationFor these purposes, we adapted Bahmni, a product built with open-source components for patient tracking, clinical protocols, pharmacy, laboratory, imaging, financial management, and supply logistics. In close partnership with government officials, we deployed the system in February of 2015, added on additional functionality, and iteratively improved the system over the following year. This experience enabled us then to deploy the system at an additional district-level hospital in a different part of the country in under four weeks. We discuss the implementation challenges and the strategies we pursued to build an electronic medical record for the public sector in rural Nepal.DiscussionOver the course of 18 months, we were able to develop, deploy and iterate upon the electronic medical record, and then deploy the refined product at an additional facility within only four weeks. Our experience suggests the feasibility of an integrated electronic medical record for public sector care delivery even in settings of rural poverty
