Publications by authors named "Harshana Liyanage"

47 Publications

Primary Care Informatics Response to Covid-19 Pandemic: Adaptation, Progress, and Lessons from Four Countries with High ICT Development.

Yearb Med Inform 2021 Apr 21. Epub 2021 Apr 21.

Nuffield Department of Primary Care Health Sciences, University of Oxford, UK.

Objective: Internationally, primary care practice had to transform in response to the COVID pandemic. Informatics issues included access, privacy, and security, as well as patient concerns of equity, safety, quality, and trust. This paper describes progress and lessons learned.

Methods: IMIA Primary Care Informatics Working Group members from Australia, Canada, United Kingdom and United States developed a standardised template for collection of information. The template guided a rapid literature review. We also included experiential learning from primary care and public health perspectives.

Results: All countries responded rapidly. Common themes included rapid reductions then transformation to virtual visits, pausing of non-COVID related informatics projects, all against a background of non-standardized digital development and disparate territory or state regulations and guidance. Common barriers in these four and in less-resourced countries included disparities in internet access and availability including bandwidth limitations when internet access was available, initial lack of coding standards, and fears of primary care clinicians that patients were delaying care despite the availability of televisits.

Conclusions: Primary care clinicians were able to respond to the COVID crisis through telehealth and electronic record enabled change. However, the lack of coordinated national strategies and regulation, assurance of financial viability, and working in silos remained limitations. The potential for primary care informatics to transform current practice was highlighted. More research is needed to confirm preliminary observations and trends noted.
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http://dx.doi.org/10.1055/s-0041-1726489DOI Listing
April 2021

Using Point of Care Testing to estimate influenza vaccine effectiveness in the English primary care sentinel surveillance network.

PLoS One 2021 11;16(3):e0248123. Epub 2021 Mar 11.

Academic Unit of Clinical and Experimental Sciences, University of Southampton, Southampton, United Kingdom.

Introduction: Rapid Point of Care Testing (POCT) for influenza could be used to provide information on influenza vaccine effectiveness (IVE) as well as influencing clinical decision-making in primary care.

Methods: We undertook a test negative case control study to estimate the overall and age-specific (6 months-17 years, 18-64 years, ≥65 years old) IVE against medically attended POCT-confirmed influenza. The study took place over the winter of 2019-2020 and was nested within twelve general practices that are part of the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), the English sentinel surveillance network.

Results: 648 POCT were conducted. 193 (29.7%) of those who were swabbed had received the seasonal influenza vaccine. The crude unadjusted overall IVE was 46.1% (95% CI: 13.9-66.3). After adjusting for confounders the overall IVE was 26.0% (95% CI: 0-65.5). In total 211 patients were prescribed an antimicrobial after swab testing. Given a positive influenza POCT result, the odds ratio (OR) of receiving an antiviral was 21.1 (95%CI: 2.4-182.2, p = <0.01) and the OR of being prescribed an antibiotic was 0.6 (95%CI: 0.4-0.9, p = <0.01).

Discussion: Using influenza POCT in a primary care sentinel surveillance network to estimate IVE is feasible and provides comparable results to published IVE estimates. A further advantage is that near patient testing of influenza is associated with improvements in appropriate antiviral and antibiotic use. Larger, randomised studies are needed in primary care to see if these trends are still present and to explore their impact on outcomes.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0248123PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7951853PMC
March 2021

Influenza and Respiratory Virus Surveillance, Vaccine Uptake, and Effectiveness at a Time of Cocirculating COVID-19: Protocol for the English Primary Care Sentinel System for 2020-2021.

JMIR Public Health Surveill 2021 02 19;7(2):e24341. Epub 2021 Feb 19.

Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.

Background: The Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) and Public Health England (PHE) are commencing their 54th season of collaboration at a time when SARS-CoV-2 infections are likely to be cocirculating with the usual winter infections.

Objective: The aim of this study is to conduct surveillance of influenza and other monitored respiratory conditions and to report on vaccine uptake and effectiveness using nationally representative surveillance data extracted from primary care computerized medical records systems. We also aim to have general practices collect virology and serology specimens and to participate in trials and other interventional research.

Methods: The RCGP RSC network comprises over 1700 general practices in England and Wales. We will extract pseudonymized data twice weekly and are migrating to a system of daily extracts. First, we will collect pseudonymized, routine, coded clinical data for the surveillance of monitored and unexpected conditions; data on vaccine exposure and adverse events of interest; and data on approved research study outcomes. Second, we will provide dashboards to give general practices feedback about levels of care and data quality, as compared to other network practices. We will focus on collecting data on influenza-like illness, upper and lower respiratory tract infections, and suspected COVID-19. Third, approximately 300 practices will participate in the 2020-2021 virology and serology surveillance; this will include responsive surveillance and long-term follow-up of previous SARS-CoV-2 infections. Fourth, member practices will be able to recruit volunteer patients to trials, including early interventions to improve COVID-19 outcomes and point-of-care testing. Lastly, the legal basis for our surveillance with PHE is Regulation 3 of the Health Service (Control of Patient Information) Regulations 2002; other studies require appropriate ethical approval.

Results: The RCGP RSC network has tripled in size; there were previously 100 virology practices and 500 practices overall in the network and we now have 322 and 1724, respectively. The Oxford-RCGP Clinical Informatics Digital Hub (ORCHID) secure networks enable the daily analysis of the extended network; currently, 1076 practices are uploaded. We are implementing a central swab distribution system for patients self-swabbing at home in addition to in-practice sampling. We have converted all our primary care coding to Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) coding. Throughout spring and summer 2020, the network has continued to collect specimens in preparation for the winter or for any second wave of COVID-19 cases. We have collected 5404 swabs and detected 623 cases of COVID-19 through extended virological sampling, and 19,341 samples have been collected for serology. This shows our preparedness for the winter season.

Conclusions: The COVID-19 pandemic has been associated with a groundswell of general practices joining our network. It has also created a permissive environment in which we have developed the capacity and capability of the national primary care surveillance systems and our unique public health institute, the RCGP and University of Oxford collaboration.
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http://dx.doi.org/10.2196/24341DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7899204PMC
February 2021

Quality assessment of real-world data repositories across the data life cycle: A literature review.

J Am Med Inform Assoc 2021 Jan 26. Epub 2021 Jan 26.

Department of Pediatrics (Section of Informatics and Data Sciences), University of Colorado Anschutz Medical Campus, Denver, Colorado, USA.

Objective: Data quality (DQ) must be consistently defined in context. The attributes, metadata, and context of longitudinal real-world data (RWD) have not been formalized for quality improvement across the data production and curation life cycle. We sought to complete a literature review on DQ assessment frameworks, indicators and tools for research, public health, service, and quality improvement across the data life cycle.

Materials And Methods: The review followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Databases from health, physical and social sciences were used: Cinahl, Embase, Scopus, ProQuest, Emcare, PsycINFO, Compendex, and Inspec. Embase was used instead of PubMed (an interface to search MEDLINE) because it includes all MeSH (Medical Subject Headings) terms used and journals in MEDLINE as well as additional unique journals and conference abstracts. A combined data life cycle and quality framework guided the search of published and gray literature for DQ frameworks, indicators, and tools. At least 2 authors independently identified articles for inclusion and extracted and categorized DQ concepts and constructs. All authors discussed findings iteratively until consensus was reached.

Results: The 120 included articles yielded concepts related to contextual (data source, custodian, and user) and technical (interoperability) factors across the data life cycle. Contextual DQ subcategories included relevance, usability, accessibility, timeliness, and trust. Well-tested computable DQ indicators and assessment tools were also found.

Conclusions: A DQ assessment framework that covers intrinsic, technical, and contextual categories across the data life cycle enables assessment and management of RWD repositories to ensure fitness for purpose. Balancing security, privacy, and FAIR principles requires trust and reciprocity, transparent governance, and organizational cultures that value good documentation.
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http://dx.doi.org/10.1093/jamia/ocaa340DOI Listing
January 2021

Association Between Blood Pressure Control and Coronavirus Disease 2019 Outcomes in 45 418 Symptomatic Patients With Hypertension: An Observational Cohort Study.

Hypertension 2021 03 16;77(3):846-855. Epub 2020 Dec 16.

From the Nuffield Department of Primary Care Health Sciences, University of Oxford, United Kingdom (J.P.S., B.D.N., J.L., D.M., J.S., C.K., J.O., N.R.J., W.H., L.A., O.V.H., S.L.-F., C.R.B., H.L., J.W., F.F., M.D.F., M.P.J., S.d.L., F.D.R.H.).

Hypertension has been identified as a risk factor for coronavirus disease 2019 (COVID-19) and associated adverse outcomes. This study examined the association between preinfection blood pressure (BP) control and COVID-19 outcomes using data from 460 general practices in England. Eligible patients were adults with hypertension who were tested or diagnosed with COVID-19. BP control was defined by the most recent BP reading within 24 months of the index date (January 1, 2020). BP was defined as controlled (<130/80 mm Hg), raised (130/80-139/89 mm Hg), stage 1 uncontrolled (140/90-159/99 mm Hg), or stage 2 uncontrolled (≥160/100 mm Hg). The primary outcome was death within 28 days of COVID-19 diagnosis. Secondary outcomes were COVID-19 diagnosis and COVID-19-related hospital admission. Multivariable logistic regression was used to examine the association between BP control and outcomes. Of the 45 418 patients (mean age, 67 years; 44.7% male) included, 11 950 (26.3%) had controlled BP. These patients were older, had more comorbidities, and had been diagnosed with hypertension for longer. A total of 4277 patients (9.4%) were diagnosed with COVID-19 and 877 died within 28 days. Individuals with stage 1 uncontrolled BP had lower odds of COVID-19 death (odds ratio, 0.76 [95% CI, 0.62-0.92]) compared with patients with well-controlled BP. There was no association between BP control and COVID-19 diagnosis or hospitalization. These findings suggest BP control may be associated with worse COVID-19 outcomes, possibly due to these patients having more advanced atherosclerosis and target organ damage. Such patients may need to consider adhering to stricter social distancing, to limit the impact of COVID-19 as future waves of the pandemic occur.
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http://dx.doi.org/10.1161/HYPERTENSIONAHA.120.16472DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7884248PMC
March 2021

Using an Ontology to Facilitate More Accurate Coding of Social Prescriptions Addressing Social Determinants of Health: Feasibility Study.

J Med Internet Res 2020 12 11;22(12):e23721. Epub 2020 Dec 11.

Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.

Background: National Health Service (NHS) England supports social prescribing in order to address social determinants of health, which account for approximately 80% of all health outcomes. Nevertheless, data on ongoing social prescribing activities are lacking. Although NHS England has attempted to overcome this problem by recommending 3 standardized primary care codes, these codes do not capture the social prescribing activity to a level of granularity that would allow for fair attribution of outcomes to social prescribing.

Objective: In this study, we explored whether an alternative approach to coding social prescribing activity, specifically through a social prescribing ontology, can be used to capture the social prescriptions used in primary care in greater detail.

Methods: The social prescribing ontology, implemented according to the Web Ontology Language, was designed to cover several key concepts encompassing social determinants of health. Readv2 and Clinical Terms Version 3 codes were identified using the NHS Terms Browser. The Royal College of General Practitioners Research Surveillance Centre, a sentinel network of over 1000 primary care practices across England covering a population of more than 4,000,000 registered patients, was used for data analyses for a defined period (ie, January 2011 to December 2019).

Results: In all, 668 codes capturing social prescriptions addressing different social determinants of health were identified for the social prescribing ontology. For the study period, social prescribing ontology codes were used 5,504,037 times by primary care practices of the Royal College of General Practitioners Research Surveillance Centre as compared to 29,606 instances of use of social prescribing codes, including NHS England's recommended codes.

Conclusions: A social prescribing ontology provides a powerful alternative to the codes currently recommended by NHS England to capture detailed social prescribing activity in England. The more detailed information thus obtained will allow for explorations about whether outputs or outcomes of care delivery can be attributed to social prescriptions, which is essential for demonstrating the overall value that social prescribing can deliver to the NHS and health care systems.
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http://dx.doi.org/10.2196/23721DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7762682PMC
December 2020

Improving the Management of Atrial Fibrillation in General Practice: Protocol for a Mixed Methods Study.

JMIR Res Protoc 2020 Nov 9;9(11):e21259. Epub 2020 Nov 9.

Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.

Background: Atrial fibrillation (AF) is one of the commonest arrhythmias observed in general practice. The thromboembolic complications of AF include transient ischemic attack, stroke, and pulmonary embolism. Early recognition of AF can lead to early intervention with managing the risks of these complications.

Objective: The primary aim of this study is to investigate if patients are managed in general practice according to current national guidelines. In addition, the study will evaluate the impact of direct oral anticoagulant use with respect to AF complications in a real-world dataset. The secondary aims of the study are to develop a dashboard that will allow monitoring the management of AF in general practice and evaluate the usability of the dashboard.

Methods: The study was conducted in 2 phases. The initial phase was a quantitative analysis of routinely collected primary care data from the Oxford Royal College of General Practitioners Research and Surveillance Center (RCGP RSC) sentinel network database. AF cases from 2009 to 2019 were identified. The study investigated the impact of the use of anticoagulants on complications of AF over this time period. We used this dataset to examine how AF was managed in primary care during the last decade. The second phase involved development of an online dashboard for monitoring management of AF in general practice. We conducted a usability evaluation for the dashboard to identify usability issues and performed enhancements to improve usability.

Results: We received funding for both phases in January 2019 and received approval from the RCGP RSC research committee in March 2019. We completed data extraction for phase 1 in May 2019 and completed analysis in December 2019. We completed building the AF dashboard in May 2019. We started recruiting participants for phase 1 in May 2019 and concluded data collection in July 2019. We completed data analysis for phase 2 in October 2019. The results are expected to be published in the second half of 2020. As of October 2020, the publications reporting the results are under review.

Conclusions: Results of this study will provide an insight into the current trends in management of AF using real-world data from the Oxford RCGP RSC database. We anticipate that the outcomes of this study will be used to guide the development and implementation of an audit-based intervention tool to assist practitioners in identifying and managing AF in primary care.

International Registered Report Identifier (irrid): RR1-10.2196/21259.
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http://dx.doi.org/10.2196/21259DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7683254PMC
November 2020

COVID-19 Surveillance in a Primary Care Sentinel Network: In-Pandemic Development of an Application Ontology.

JMIR Public Health Surveill 2020 11 17;6(4):e21434. Epub 2020 Nov 17.

Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.

Background: Creating an ontology for COVID-19 surveillance should help ensure transparency and consistency. Ontologies formalize conceptualizations at either the domain or application level. Application ontologies cross domains and are specified through testable use cases. Our use case was an extension of the role of the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) to monitor the current pandemic and become an in-pandemic research platform.

Objective: This study aimed to develop an application ontology for COVID-19 that can be deployed across the various use-case domains of the RCGP RSC research and surveillance activities.

Methods: We described our domain-specific use case. The actor was the RCGP RSC sentinel network, the system was the course of the COVID-19 pandemic, and the outcomes were the spread and effect of mitigation measures. We used our established 3-step method to develop the ontology, separating ontological concept development from code mapping and data extract validation. We developed a coding system-independent COVID-19 case identification algorithm. As there were no gold-standard pandemic surveillance ontologies, we conducted a rapid Delphi consensus exercise through the International Medical Informatics Association Primary Health Care Informatics working group and extended networks.

Results: Our use-case domains included primary care, public health, virology, clinical research, and clinical informatics. Our ontology supported (1) case identification, microbiological sampling, and health outcomes at an individual practice and at the national level; (2) feedback through a dashboard; (3) a national observatory; (4) regular updates for Public Health England; and (5) transformation of a sentinel network into a trial platform. We have identified a total of 19,115 people with a definite COVID-19 status, 5226 probable cases, and 74,293 people with possible COVID-19, within the RCGP RSC network (N=5,370,225).

Conclusions: The underpinning structure of our ontological approach has coped with multiple clinical coding challenges. At a time when there is uncertainty about international comparisons, clarity about the basis on which case definitions and outcomes are made from routine data is essential.
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http://dx.doi.org/10.2196/21434DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7674143PMC
November 2020

Atrial fibrillation dashboard evaluation using the think aloud protocol.

BMJ Health Care Inform 2020 Oct;27(3)

Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.

Background: Atrial fibrillation (AF) is a common cardiac arrhythmia which is a major risk factor for stroke, transient ischaemic attacks and increased mortality. Primary care management of AF can significantly reduce these risks. We carried out an evaluation to asses the usability of an AF dashboard developed to improve data quality and the quality of care.

Method: We developed an online dashboard about the quality of AF management for general practices of the Oxford Royal College of General Practitioners Research and Surveillance Centre network. The dashboard displays (1) case ascertainment, (2) a calculation of stroke and haemorrhage risk to assess whether the benefits of anticogulants outweigh their risk, (3) prescriptions of different types of anticoagulant and (4) if prescribed anticoagulant is at the correct dose. We conducted the think aloud evaluation, involving 24 dashboard users to improve its usability.

Results: Analysis of 24 transcripts received produced 120 individual feedback items (ie, verbalised tasks) that were mapped across five usability problem classes. We enhanced the dashboard based on evaluation feedback to encourage adoption by general practices participating in the sentinel network.

Conclusions: The think aloud evaluation provided useful insights into important usability issues that require further development. Our enhanced AF dashboard was acceptable to clinicians and its impact on data quality and care should be assessed in a formal study.
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http://dx.doi.org/10.1136/bmjhci-2020-100191DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7580041PMC
October 2020

Use and impact of social prescribing: a mixed-methods feasibility study protocol.

BMJ Open 2020 09 18;10(9):e037681. Epub 2020 Sep 18.

Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK

Introduction: Social prescribing aims to address social determinants of health, which account for 80%-90% of health outcomes, but the evidence base behind it is limited due to a lack of data linkingsocial prescribing activity and outcomes.

Methods And Analysis: The objective of the quantitative component of this feasibility studyisto identify the characteristics of individuals who receive social prescriptions and describe the use and estimate the impact of social prescribing; the latter will be done on a homeless subgroup. We will use the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) primary care sentinel network, whose general practicescover a population of over 4 000 000 patients. Social prescribing data will be extracted onall recorded patients for 5 years up to 31 January 2020. The objective for the qualitative component of the study isto explore approaches to understand the contextual factors that will have influenced our quantitative findings to identify mechanisms to encourage adoption of social prescribing in primary care while improving data quality. Itwill comprise up to three 90-120 minute advisory group meetings for six to eight participants. Participants will be recruited based on their experience of delivering primary care within Oxfordshire and Surrey. The advisory group outputs will be analysed using framework analysis and will be used to create a survey instrument consisting of statements that surveyees, who will consist of primary care practitioners within the RCGP RSC, can agree or disagree with.

Ethics And Dissemination: All RCGP RSC data are pseudonymised at the point of data extraction. No personally identifiable data are required for this investigation. This protocol follows the Good Reporting of a Mixed Methods Study checklist. The study results will be published in a peer-reviewed journal and the dataset will be available to other researchers.
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http://dx.doi.org/10.1136/bmjopen-2020-037681DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7511614PMC
September 2020

Disparities in the excess risk of mortality in the first wave of COVID-19: Cross sectional study of the English sentinel network.

J Infect 2020 11 25;81(5):785-792. Epub 2020 Aug 25.

Nuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK. Electronic address:

Objectives: Few studies report contributors to the excess mortality in England during the first wave of coronavirus disease 2019 (COVID-19) infection. We report the absolute excess risk (AER) of mortality and excess mortality rate (EMR) from a nationally representative COVID-19 sentinel surveillance network including known COVID-19 risk factors in people aged 45 years and above.

Methods: Pseudonymised, coded clinical data were uploaded from contributing primary care providers (N = 1,970,314, ≥45years). We calculated the AER in mortality by comparing mortality for weeks 2 to 20 this year with mortality data from the Office for National Statistics (ONS) from 2018 for the same weeks. We conducted univariate and multivariate analysis including preselected variables. We report AER and EMR, with 95% confidence intervals (95% CI).

Results: The AER of mortality was 197.8/10,000 person years (95%CI:194.30-201.40). The EMR for male gender, compared with female, was 1.4 (95%CI:1.35-1.44, p<0.00); for our oldest age band (≥75 years) 10.09 (95%CI:9.46-10.75, p<0.00) compared to 45-64 year olds; Black ethnicity's EMR was 1.17 (95%CI: 1.03-1.33, p<0.02), reference white; and for dwellings with ≥9 occupants 8.01 (95%CI: 9.46-10.75, p<0.00). Presence of all included comorbidities significantly increased EMR. Ranked from lowest to highest these were: hypertension, chronic kidney disease, chronic respiratory and heart disease, and cancer or immunocompromised.

Conclusions: The absolute excess mortality was approximately 2 deaths per 100 person years in the first wave of COVID-19. More personalised shielding advice for any second wave should include ethnicity, comorbidity and household size as predictors of risk.
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http://dx.doi.org/10.1016/j.jinf.2020.08.037DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7446615PMC
November 2020

Recording COVID-19 consultations: review of symptoms, risk factors, and proposed SNOMED CT terms.

BJGP Open 2020 Oct 27;4(4). Epub 2020 Oct 27.

Norie Miller Professor of General Practice, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.

Background: There is an urgent need for epidemiological research in primary care to develop risk assessment processes for patients presenting with COVID-19, but lack of a standardised approach to data collection is a significant barrier to implementation.

Aim: To collate a list of relevant symptoms, assessment items, demographics, and lifestyle and health conditions associated with COVID-19, and match these data items with corresponding SNOMED CT clinical terms to support the development and implementation of consultation templates.

Design & Setting: Published and preprint literature for systematic reviews, meta-analyses, and clinical guidelines describing the symptoms, assessment items, demographics, and/or lifestyle and health conditions associated with COVID-19 and its complications were reviewed. Corresponding clinical concepts from SNOMED CT, a widely used structured clinical vocabulary for electronic primary care health records, were identified.

Method: Guidelines and published and unpublished reviews ( = 61) were utilised to collate a list of relevant data items for COVID-19 consultations. The NHS Digital SNOMED CT Browser was used to identify concept and descriptive identifiers. Key implementation challenges were conceptualised through a Normalisation Process Theory (NPT) lens.

Results: In total, 32 symptoms, eight demographic and lifestyle features, 25 health conditions, and 20 assessment items relevant to COVID-19 were identified, with proposed corresponding SNOMED CT concepts. These data items can be adapted into a consultation template for COVID-19. Key implementation challenges include: 1) engaging with key stakeholders to achieve 'buy in'; and 2) ensuring any template is usable within practice settings.

Conclusion: Consultation templates for COVID-19 are needed to standardise data collection, facilitate research and learning, and potentially improve quality of care for COVID-19.
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http://dx.doi.org/10.3399/bjgpopen20X101125DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7606148PMC
October 2020

Integrating molecular point-of-care testing for influenza into primary care: a mixed-methods feasibility study.

Br J Gen Pract 2020 08 30;70(697):e555-e562. Epub 2020 Jul 30.

Academic Unit of Clinical and Experimental Sciences, University of Southampton; National Institute for Health Research (NIHR) post-doctoral fellow, NIHR Southampton Biomedical Research Centre, Southampton, UK.

Background: Molecular point-of-care testing (POCT) for influenza in primary care could influence clinical care and patient outcomes.

Aim: To assess the feasibility of incorporating influenza POCT into general practice in England.

Design And Setting: A mixed-methods study conducted in six general practices that had not previously participated in respiratory virology sampling, which are part of the Royal College of General Practitioners Research and Surveillance Centre English sentinel surveillance network, from February 2019 to May 2019.

Method: A sociotechnical perspective was adopted using the Public Health England POCT implementation toolkit and business process modelling notation to inform qualitative analysis. Quantitative data were collected about the number of samples taken, their representativeness, and the virology results obtained, comparing them with the rest of the sentinel system over the same weeks.

Results: A total of 312 POCTs were performed; 276 were used for quantitative analysis, of which 60 were positive for influenza and 216 were negative. The average swabbing rate was 0.4 per 1000 population and swab positivity was between 16.7% ( = 14/84) and 41.4% ( = 12/29). Given a positive influenza POCT result, the odds ratio of receiving an antiviral was 14.1 (95% confidence intervals [CI] = 2.9 to 70.0, <0.001) and of receiving an antibiotic was 0.4 (95% CI = 0.2 to 0.8, = 0.01), compared with patients with a negative result. Qualitative analysis showed that it was feasible for practices to implement POCT, but there is considerable variation in the processes used.

Conclusion: Testing for influenza using POCT is feasible in primary care and may improve antimicrobial use. However, further evidence from randomised trials of influenza POCT in general practice is needed.
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http://dx.doi.org/10.3399/bjgp20X710897DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363279PMC
August 2020

Reorganisation of primary care for older adults during COVID-19: a cross-sectional database study in the UK.

Br J Gen Pract 2020 08 30;70(697):e540-e547. Epub 2020 Jul 30.

Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford; director, Royal College of General Practitioners Research and Surveillance Centre, London.

Background: The coronavirus disease 2019 (COVID-19) pandemic has resulted in a rapid change in workload across healthcare systems. Factors related to this adaptation in UK primary care have not yet been examined.

Aim: To assess the responsiveness and prioritisation of primary care consultation type for older adults during the COVID-19 pandemic.

Design And Setting: A cross-sectional database study examining consultations between 17 February and 10 May 2020 for patients aged ≥65 years, drawn from primary care practices within the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) sentinel network, UK.

Method: The authors reported the proportion of consultation type across five categories: clinical administration, electronic/video, face-to-face, telephone, and home visits. Temporal trends in telephone and face-to-face consultations were analysed by polypharmacy, frailty status, and socioeconomic group using incidence rate ratios (IRR).

Results: Across 3 851 304 consultations, the population median age was 75 years (interquartile range [IQR] 70-82); and 46% ( = 82 926) of the cohort ( = 180 420) were male. The rate of telephone and electronic/video consultations more than doubled across the study period (106.0% and 102.8%, respectively). Face-to-face consultations fell by 64.6% and home visits by 62.6%. This predominantly occurred across week 11 (week commencing 9 March 2020), coinciding with national policy change. Polypharmacy and frailty were associated with a relative increase in consultations. The greatest relative increase was among people taking ≥10 medications compared with those taking none (face-to-face IRR 9.90, 95% CI = 9.55 to 10.26; telephone IRR 17.64, 95% CI = 16.89 to 18.41).

Conclusion: Primary care has undergone an unprecedented in-pandemic reorganisation while retaining focus on patients with increased complexity.
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http://dx.doi.org/10.3399/bjgp20X710933DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363277PMC
August 2020

Primary Care Prostate Cancer Case Ascertainment.

Stud Health Technol Inform 2020 Jun;270:1369-1370

Nuffield Department of Primary Care Health Sciences, University of Oxford, UK.

Although routine healthcare data are not collected for research, they are increasingly used in epidemiology and are key real-world evidence for improving healthcare. This study presents a method to identify prostate cancer cases from a large English primary care database. 19,619 (1.3%) men had a code for prostate cancer diagnosis. Codes for medium and high Gleason grading enabled identification of additional 94 (0.5%) cases. Many studies do not report codes used to identify patients, and if published, the lists of codes differ from study to study. This can lead to poor research reproducibility and hinder validation. This work demonstrates that carefully developed comprehensive lists of clinical codes can be used to identify prostate cancer; and that approaches that do not solely rely on clinical codes such as ontologies or data linkage should also be considered.
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http://dx.doi.org/10.3233/SHTI200446DOI Listing
June 2020

Near Real Time Feedback of Seasonal Influenza Vaccination and Virological Sampling: Dashboard Utilisation in a Primary Care Sentinel Network.

Stud Health Technol Inform 2020 Jun;270:1339-1340

Nuffield Department of Primary Health Care Sciences, University of Oxford, UK.

Near-real time feedback on data quality allows clinicians and data managers at general practices to collectively contribute to improving the reliability of observational data. We report features of an enhanced dashboard used for virological surveillance after the first season of utilisation. Time-series analysis performed on dashboard usage data from 68 general practices (denominator = 722,409) indicated utilisation patterns that correlated to influenza vaccination in general practices. Near real time feedback via a dashboard may improve data quality and possibly vaccine uptake.
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http://dx.doi.org/10.3233/SHTI200431DOI Listing
June 2020

The Oxford Royal College of General Practitioners Clinical Informatics Digital Hub: Protocol to Develop Extended COVID-19 Surveillance and Trial Platforms.

JMIR Public Health Surveill 2020 07 2;6(3):e19773. Epub 2020 Jul 2.

Royal College of General Practitioners, London, United Kingdom.

Background: Routinely recorded primary care data have been used for many years by sentinel networks for surveillance. More recently, real world data have been used for a wider range of research projects to support rapid, inexpensive clinical trials. Because the partial national lockdown in the United Kingdom due to the coronavirus disease (COVID-19) pandemic has resulted in decreasing community disease incidence, much larger numbers of general practices are needed to deliver effective COVID-19 surveillance and contribute to in-pandemic clinical trials.

Objective: The aim of this protocol is to describe the rapid design and development of the Oxford Royal College of General Practitioners Clinical Informatics Digital Hub (ORCHID) and its first two platforms. The Surveillance Platform will provide extended primary care surveillance, while the Trials Platform is a streamlined clinical trials platform that will be integrated into routine primary care practice.

Methods: We will apply the FAIR (Findable, Accessible, Interoperable, and Reusable) metadata principles to a new, integrated digital health hub that will extract routinely collected general practice electronic health data for use in clinical trials and provide enhanced communicable disease surveillance. The hub will be findable through membership in Health Data Research UK and European metadata repositories. Accessibility through an online application system will provide access to study-ready data sets or developed custom data sets. Interoperability will be facilitated by fixed linkage to other key sources such as Hospital Episodes Statistics and the Office of National Statistics using pseudonymized data. All semantic descriptors (ie, ontologies) and code used for analysis will be made available to accelerate analyses. We will also make data available using common data models, starting with the US Food and Drug Administration Sentinel and Observational Medical Outcomes Partnership approaches, to facilitate international studies. The Surveillance Platform will provide access to data for health protection and promotion work as authorized through agreements between Oxford, the Royal College of General Practitioners, and Public Health England. All studies using the Trials Platform will go through appropriate ethical and other regulatory approval processes.

Results: The hub will be a bottom-up, professionally led network that will provide benefits for member practices, our health service, and the population served. Data will only be used for SQUIRE (surveillance, quality improvement, research, and education) purposes. We have already received positive responses from practices, and the number of practices in the network has doubled to over 1150 since February 2020. COVID-19 surveillance has resulted in tripling of the number of virology sites to 293 (target 300), which has aided the collection of the largest ever weekly total of surveillance swabs in the United Kingdom as well as over 3000 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serology samples. Practices are recruiting to the PRINCIPLE (Platform Randomised trial of INterventions against COVID-19 In older PeopLE) trial, and these participants will be followed up through ORCHID. These initial outputs demonstrate the feasibility of ORCHID to provide an extended national digital health hub.

Conclusions: ORCHID will provide equitable and innovative use of big data through a professionally led national primary care network and the application of FAIR principles. The secure data hub will host routinely collected general practice data linked to other key health care repositories for clinical trials and support enhanced in situ surveillance without always requiring large volume data extracts. ORCHID will support rapid data extraction, analysis, and dissemination with the aim of improving future research and development in general practice to positively impact patient care.

International Registered Report Identifier (irrid): DERR1-10.2196/19773.
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http://dx.doi.org/10.2196/19773DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333793PMC
July 2020

Ethical Use of Electronic Health Record Data and Artificial Intelligence: Recommendations of the Primary Care Informatics Working Group of the International Medical Informatics Association.

Yearb Med Inform 2020 Aug 17;29(1):51-57. Epub 2020 Apr 17.

Clnical Informatics and Health Outcomes Research Group, Nuffield Department of Primary Care Health Sciences, University of Oxford, Eagle House, 7 Walton Well Road, Oxford, OX2 6ED, UK.

Objective: To create practical recommendations for the curation of routinely collected health data and artificial intelligence (AI) in primary care with a focus on ensuring their ethical use.

Methods: We defined data curation as the process of management of data throughout its lifecycle to ensure it can be used into the future. We used a literature review and Delphi exercises to capture insights from the Primary Care Informatics Working Group (PCIWG) of the International Medical Informatics Association (IMIA).

Results: We created six recommendations: (1) Ensure consent and formal process to govern access and sharing throughout the data life cycle; (2) Sustainable data creation/collection requires trust and permission; (3) Pay attention to Extract-Transform-Load (ETL) processes as they may have unrecognised risks; (4) Integrate data governance and data quality management to support clinical practice in integrated care systems; (5) Recognise the need for new processes to address the ethical issues arising from AI in primary care; (6) Apply an ethical framework mapped to the data life cycle, including an assessment of data quality to achieve effective data curation.

Conclusions: The ethical use of data needs to be integrated within the curation process, hence running throughout the data lifecycle. Current information systems may not fully detect the risks associated with ETL and AI; they need careful scrutiny. With distributed integrated care systems where data are often used remote from documentation, harmonised data quality assessment, management, and governance is important. These recommendations should help maintain trust and connectedness in contemporary information systems and planned developments.
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http://dx.doi.org/10.1055/s-0040-1701980DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442527PMC
August 2020

Emergence of a Novel Coronavirus (COVID-19): Protocol for Extending Surveillance Used by the Royal College of General Practitioners Research and Surveillance Centre and Public Health England.

JMIR Public Health Surveill 2020 04 2;6(2):e18606. Epub 2020 Apr 2.

Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.

Background: The Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) and Public Health England (PHE) have successfully worked together on the surveillance of influenza and other infectious diseases for over 50 years, including three previous pandemics. With the emergence of the international outbreak of the coronavirus infection (COVID-19), a UK national approach to containment has been established to test people suspected of exposure to COVID-19. At the same time and separately, the RCGP RSC's surveillance has been extended to monitor the temporal and geographical distribution of COVID-19 infection in the community as well as assess the effectiveness of the containment strategy.

Objectives: The aims of this study are to surveil COVID-19 in both asymptomatic populations and ambulatory cases with respiratory infections, ascertain both the rate and pattern of COVID-19 spread, and assess the effectiveness of the containment policy.

Methods: The RCGP RSC, a network of over 500 general practices in England, extract pseudonymized data weekly. This extended surveillance comprises of five components: (1) Recording in medical records of anyone suspected to have or who has been exposed to COVID-19. Computerized medical records suppliers have within a week of request created new codes to support this. (2) Extension of current virological surveillance and testing people with influenza-like illness or lower respiratory tract infections (LRTI)-with the caveat that people suspected to have or who have been exposed to COVID-19 should be referred to the national containment pathway and not seen in primary care. (3) Serology sample collection across all age groups. This will be an extra blood sample taken from people who are attending their general practice for a scheduled blood test. The 100 general practices currently undertaking annual influenza virology surveillance will be involved in the extended virological and serological surveillance. (4) Collecting convalescent serum samples. (5) Data curation. We have the opportunity to escalate the data extraction to twice weekly if needed. Swabs and sera will be analyzed in PHE reference laboratories.

Results: General practice clinical system providers have introduced an emergency new set of clinical codes to support COVID-19 surveillance. Additionally, practices participating in current virology surveillance are now taking samples for COVID-19 surveillance from low-risk patients presenting with LRTIs. Within the first 2 weeks of setup of this surveillance, we have identified 3 cases: 1 through the new coding system, the other 2 through the extended virology sampling.

Conclusions: We have rapidly converted the established national RCGP RSC influenza surveillance system into one that can test the effectiveness of the COVID-19 containment policy. The extended surveillance has already seen the use of new codes with 3 cases reported. Rapid sharing of this protocol should enable scientific critique and shared learning.

International Registered Report Identifier (irrid): DERR1-10.2196/18606.
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http://dx.doi.org/10.2196/18606DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7124955PMC
April 2020

Feasibility of Point-of-Care Testing for Influenza Within a National Primary Care Sentinel Surveillance Network in England: Protocol for a Mixed Methods Study.

JMIR Res Protoc 2019 Nov 11;8(11):e14186. Epub 2019 Nov 11.

Academic Unit of Clinical and Experimental Sciences, University of Southampton, Southampton, United Kingdom.

Background: Point-of-care testing (POCT) for influenza promises to provide real-time information to influence clinical decision making and improve patient outcomes. Public Health England has published a toolkit to assist implementation of these tests in the UK National Health Service.

Objective: A feasibility study will be undertaken to assess the implementation of influenza POCT in primary care as part of a sentinel surveillance network.

Methods: We will conduct a mixed methods study to compare the sampling rates in practices using POCT and current virology swabbing practices not using POCT, and to understand the issues and barriers to implementation of influenza POCT in primary care workflows. The study will take place between March and May 2019. It will be nested in general practices that are part of the English national sentinel surveillance network run by the Royal College of General Practitioners Research and Surveillance Centre. The primary outcome is the number of valid influenza swabs taken and tested by the practices involved in the study using the new POCT.

Results: A total of 6 practices were recruited, and data collection commenced on March 11, 2019. Moreover, 312 swab samples had been collected at the time of submission of the protocol, which was 32.5% (312/960) of the expected sample size. In addition, 68 samples were positive for influenza, which was 20.1% (68/338) of the expected sample size.

Conclusions: To the best of our knowledge, this is the first time an evaluation study has been undertaken on POCT for influenza in general practice in the United Kingdom. This proposed study promises to shed light on the feasibility of implementation of POCT in primary care and on the views of practitioners about the use of influenza POCT in primary care, including its impact on primary care workflows.

International Registered Report Identifier (irrid): DERR1-10.2196/14186.
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http://dx.doi.org/10.2196/14186DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6878097PMC
November 2019

Near-Real Time Monitoring of Vaccine Uptake of Pregnant Women in a Primary Care Sentinel Network: Ontological Case Definition Across Heterogeneous Data Sources.

Stud Health Technol Inform 2019 Aug;264:1855-1856

Department of Clinical & Experimental Medicine, University of Surrey, UK.

Vaccination against influenza is important in pregnancy for the health of both mother and unborn baby. Influenza introduces risks to pregnancy and to the baby who relies on maternal antibodies for protection. Because the data associated with pregnancy is fragmented across multiple providers of health care, it is challenging to conduct pregnancy-related public health surveillance using a single data source. We report the integration of a novel ontological approach to identifying pregnancies in routine data with a web-based dashboard that feeds back information to general practices in a sentinel network. As a result, practices receive information about how well they are performing influenza vaccination in pregnancy in near-real-time.
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http://dx.doi.org/10.3233/SHTI190682DOI Listing
August 2019

Ontology to identify pregnant women in electronic health records: primary care sentinel network database study.

BMJ Health Care Inform 2019 Jul 4;26(1). Epub 2019 Jul 4.

Department of Clinical and Experimental Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, UK.

Objective: To develop an ontology to identify pregnant women from computerised medical record systems with dissimilar coding systems in a primary care sentinel network.

Materials And Methods: We used a three-step approach to develop our pregnancy ontology in two different coding schemata, one hierarchical and the other polyhierarchical. We developed a coding system-independent pregnancy case identification algorithm using the Royal College of General Practitioners Research and Surveillance Centre sentinel network database which held 1.8 million patients' data drawn from 150 primary care providers. We tested the algorithm by examining individual patient records in a 10% random sample of all women aged 29 in each year from 2004 to 2016. We did an external comparison with national pregnancy data. We used χ test to compare results obtained for the two different coding schemata.

Results: 243 005 women (median age 29 years at start of pregnancy) had 405 591 pregnancies from 2004 to 2016 of which 333 689 went to term. We found no significant difference between results obtained for two populations using different coding schemata. Pregnancy mean ages did not differ significantly from national data.

Discussion: This ontologically driven algorithm enables consistent analysis across data drawn from populations using different coding schemata. It could be applied to other hierarchical coding systems (eg, International Classification of Disease) or polyhierarchical systems (eg, SNOMED CT to which our health system is currently migrating).

Conclusion: This ontological approach will improve our surveillance in particular of influenza vaccine exposure in pregnancy.
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http://dx.doi.org/10.1136/bmjhci-2019-100013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7062332PMC
July 2019

Artificial Intelligence in Primary Health Care: Perceptions, Issues, and Challenges.

Yearb Med Inform 2019 Aug 25;28(1):41-46. Epub 2019 Apr 25.

Department of Clinical & Experimental Medicine, University of Surrey, Guildford, Surrey, UK.

Background: Artificial intelligence (AI) is heralded as an approach that might augment or substitute for the limited processing power of the human brain of primary health care (PHC) professionals. However, there are concerns that AI-mediated decisions may be hard to validate and challenge, or may result in rogue decisions.

Objective: To form consensus about perceptions, issues, and challenges of AI in primary care.

Method: A three-round Delphi study was conducted. Round 1 explored experts' viewpoints on AI in PHC (n=20). Round 2 rated the appropriateness of statements arising from round one (n=12). The third round was an online panel discussion of findings (n=8) with the members of both the International Medical Informatics Association and the European Federation of Medical Informatics Primary Health Care Informatics Working Groups.

Results: PHC and informatics experts reported AI has potential to improve managerial and clinical decisions and processes, and this would be facilitated by common data standards. The respondents did not agree that AI applications should learn and adapt to clinician preferences or behaviour and they did not agree on the extent of AI potential for harm to patients. It was more difficult to assess the impact of AI-based applications on continuity and coordination of care.

Conclusion: While the use of AI in medicine should enhance healthcare delivery, we need to ensure meticulous design and evaluation of AI applications. The primary care informatics community needs to be proactive and to guide the ethical and rigorous development of AI applications so that they will be safe and effective.
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http://dx.doi.org/10.1055/s-0039-1677901DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697547PMC
August 2019

Determinants of inter-practice variation in ADHD diagnosis and stimulant prescribing: cross-sectional database study of a national surveillance network.

BMJ Evid Based Med 2019 Aug 14;24(4):155-161. Epub 2019 Feb 14.

Department of Clinical and Experimental medicine, University of Surrey, Guildford, UK.

Early recognition, identification and treatment of children with attention deficit hyperactivity disorder (ADHD) can reduce detrimental outcomes and redirect their developmental trajectory. We aimed to describe variations in age of ADHD diagnosis and stimulant prescribing among general practitioner practices in a nationwide network and identify child, parental, household and general practice factors that might account for these variations. Cross-sectional study of children aged under 19 years registered within a general practice in the Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) network in 2016, RCGP RSC has a household key allowing parent and child details to be linked. Data from 158 general practices and 353 774 children under 19 were included. The mean age of first ADHD diagnosis was 10.5 years (95% CI 10.1 to 10.9, median 10, IQR 9.0-11.9) and the mean percentage of children with ADHD prescribed stimulant medications among RCGP RSC practices was 41.2% (95% CI 38.7 to 43.6). There was wide inter-practice variation in the prevalence of diagnosis of ADHD, the age of diagnosis and stimulant prescribing. ADHD diagnosis is more likely to be made later in households with a greater number of children and with a larger age difference between adults and children. Stimulant prescribing for children with ADHD was higher in less deprived practices. Older parents and families with more children fail to recognise ADHD and may need more support. Practices in areas of higher socio-economic status are associated with greater prescribing of stimulants for children with ADHD.
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http://dx.doi.org/10.1136/bmjebm-2018-111133DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6678046PMC
August 2019

Determinants of inter-practice variation in childhood asthma and respiratory infections: cross-sectional study of a national sentinel network.

BMJ Open 2019 01 24;9(1):e024372. Epub 2019 Jan 24.

Department of Clinical and Experimental Medicine, University of Surrey, Guildford, UK.

Objectives: Respiratory infections are associated with acute exacerbations of asthma and accompanying morbidity and mortality. In this study we explore inter-practice variations in respiratory infections in children with asthma and study the effect of practice-level factors on these variations.

Design: Cross-sectional study.

Setting: We analysed data from 164 general practices in the Royal College of General PractitionersResearch and Surveillance Centresentinel network in England.

Participants: Children 5-12 years.

Interventions: None. In this observational study, we used regression analysis to explore the impact of practice-level determinants on the number of respiratory infections in children with asthma.

Primary And Secondary Outcome Measures: We describe the distribution of childhood asthma and the determinants of upper/lower respiratory tract infections in these children.

Results: 83.5% (137/164) practices were in urban locations; the mean number of general practitioners per practice was 7; and the mean duration since qualification 19.7 years. We found almost 10-fold difference in the rate of asthma (1.5-11.8 per 100 children) and 50-fold variation in respiratory infection rates between practices. Larger practices with larger lists of asthmatic children had greater rates of respiratory infections among these children.

Conclusion: We showed that structural/environmental variables are consistent predictors of a range of respiratory infections among children with asthma. However, contradictory results between measures of practice clinical care show that a purely structural explanation for variability in respiratory infections is limited. Further research is needed to understand how the practice factors influence individual risk behaviours relevant to respiratory infections.
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http://dx.doi.org/10.1136/bmjopen-2018-024372DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6347957PMC
January 2019

An instrument to identify computerised primary care research networks, genetic and disease registries prepared to conduct linked research: TRANSFoRm International Research Readiness (TIRRE) survey.

J Innov Health Inform 2018 Dec 31;25(4):207-220. Epub 2018 Dec 31.

Imperial College London.

Purpose: The Translational Research and Patients safety in Europe (TRANSFoRm) project aims to integrate primary care with clinical research whilst improving patient safety. The TRANSFoRm International Research Readiness survey (TIRRE) aims to demonstrate data use through two linked data studies and by identifying clinical data repositories and genetic databases or disease registries prepared to participate in linked research.

Method: The TIRRE survey collects data at micro-, meso- and macro-levels of granularity; to fulfil data, study specific, business, geographical and readiness requirements of potential data providers for the TRANSFoRm demonstration studies. We used descriptive statistics to differentiate between demonstration-study compliant and non-compliant repositories. We only included surveys with >70% of questions answered in our final analysis, reporting the odds ratio (OR) of positive responses associated with a demonstration-study compliant data provider.

Results: We contacted 531 organisations within the Eurpean Union (EU). Two declined to supply information; 56 made a valid response and a further 26 made a partial response. Of the 56 valid responses, 29 were databases of primary care data, 12 were genetic databases and 15 were cancer registries. The demonstration compliant primary care sites made 2098 positive responses compared with 268 in non-use-case compliant data sources [OR: 4.59, 95% confidence interval (CI): 3.93-5.35, p < 0.008]; for genetic databases: 380:44 (OR: 6.13, 95% CI: 4.25-8.85, p < 0.008) and cancer registries: 553:44 (OR: 5.87, 95% CI: 4.13-8.34, p < 0.008).

Conclusions: TIRRE comprehensively assesses the preparedness of data repositories to participate in specific research projects. Multiple contacts about hypothetical participation in research identified few potential sites.
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http://dx.doi.org/10.14236/jhi.v25i4.964DOI Listing
December 2018

Ontologies in Big Health Data Analytics: Application to Routine Clinical Data.

Stud Health Technol Inform 2018 ;255:65-69

Department of Clinical & Experimental Medicine, University of Surrey, UK.

Ontologies are an important big-data analytics tool. Historically code lists were created by domain experts and mapped between different coding systems. Ontologies allow us to develop better representations of clinical concepts, data and facilitate better data extracts from routine clinical data. It also makes the process of case identification and key outcome measures transparent. We describe a process we have operationalised in our research. We use ontologies to resolve the semantics of complex health care data. The use of the method is demonstrated through a pregnancy case identification method. Pregnancy data are recorded in different coding systems and stored in different general practice systems; and pregnancy has its own complexities in that not all pregnancies proceed to term, they have different lengths and involve multiple providers of health care.
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August 2019

Common Data Models (CDMs) to Enhance International Big Data Analytics: A Diabetes Use Case to Compare Three CDMs.

Stud Health Technol Inform 2018 ;255:60-64

Department of Clinical & Experimental Medicine, University of Surrey, UK.

Common data models (CDM) have enabled the simultaneous analysis of disparate and large data sources. A literature review identified three relevant CDMs: The Observational Medical Outcomes Partnership (OMOP) was the most cited; next the Sentinel; and then the Patient Centered Outcomes Research Institute (PCORI). We tested these three CDMs with fifteen pre-defined criteria for a diabetes cohort study use case, assessing the benefit (good diabetes control), risk (hypoglycaemia) and cost effectiveness of recently licenced medications. We found all three CDMs have a useful role in planning collaborative research and enhance analysis of data cross jurisdiction. However, the number of pre-defined criteria achieved by these three CDMs varied. OMOP met 14/15, Sentinel 13/15, and PCORI 10/15. None met the privacy level we specified, and most of the other gaps were clinical and cost outcome related data.
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August 2019

Computerised medical record systems that guide and protect - reflections on the Bawa-Garba case.

J Innov Health Inform 2018 Apr 10;25(1):58-59. Epub 2018 Apr 10.

University of Portsmouth.

Lawrence Weed proposed we develop computerised, problem orientated medical records that guide and teach.  The Bawa-Garba case outcomes might have been different if care had been supported by computerised medical record (CMR) systems. CMR systems can reduce prescribing errors and could be develop to flag gaps in supervision.   However, CMR systems are not a panacea and need to be fit for purpose.  Our informatics perspective on this case is to call for widespread use of CMR systems - designed to guide and protect.
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http://dx.doi.org/10.14236/jhi.v25i1.1040DOI Listing
April 2018

Benefit-risk of Patients' Online Access to their Medical Records: Consensus Exercise of an International Expert Group.

Yearb Med Inform 2018 Aug 22;27(1):156-162. Epub 2018 Apr 22.

Department of Clinical & Experimental Medicine, University of Surrey, GUILDFORD, Surrey, UK.

Background:  Patients' access to their computerised medical records (CMRs) is a legal right in many countries. However, little is reported about the benefit-risk associated with patients' online access to their CMRs.

Objective:  To conduct a consensus exercise to assess the impact of patients' online access to their CMRs on the quality of care as defined in six domains by the Institute of Medicine (IoM), now the National Academy of Medicine (NAM).

Method:  A five-round Delphi study was conducted. Round One explored experts' (n = 37) viewpoints on providing patients with access to their CMRs. Round Two rated the appropriateness of statements arising from Round One (n = 16). The third round was an online panel discussion of findings (n = 13) with the members of both the International Medical Informatics Association and the European Federation of Medical Informatics Primary Health Care Informatics Working Groups. Two additional rounds, a survey of the revised consensus statements and an online workshop, were carried out to further refine consensus statements.

Results:  Thirty-seven responses from Round One were used as a basis to initially develop 15 statements which were categorised using IoM's domains of care quality. The experts agreed that providing patients online access to their CMRs for bookings, results, and prescriptions increased efficiency and improved the quality of medical records. Experts also anticipated that patients would proactively use their online access to share data with different health care providers, including emergencies. However, experts differed on whether access to limited or summary data was more useful to patients than accessing their complete records. They thought online access would change recording practice, but they were unclear about the benefit-risk of high and onerous levels of security. The 5-round process, finally, produced 16 consensus statements.

Conclusion:  Patients' online access to their CMRs should be part of all CMR systems. It improves the process of health care, but further evidence is required about outcomes. Online access improves efficiency of bookings and other services. However, there is scope to improve many of the processes of care it purports to support, particularly the provision of a more effective interface and the protection of the vulnerable.
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http://dx.doi.org/10.1055/s-0038-1641202DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6115222PMC
August 2018