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Cramer H, Hughes J, Johnson R, Evans M, Deaton C, Timmis A, Hemingway H, Feder G, Featherstone K. 'Who does this patient belong to?' boundary work and the re/making of (NSTEMI) heart attack patients. SOCIOLOGY OF HEALTH & ILLNESS 2018; 40:1404-1429. [PMID: 29956339 PMCID: PMC6282527 DOI: 10.1111/1467-9566.12778] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
This ethnography within ten English and Welsh hospitals explores the significance of boundary work and the impacts of this work on the quality of care experienced by heart attack patients who have suspected non-ST segment elevation myocardial infarction (NSTEMI) /non-ST elevation acute coronary syndrome. Beginning with the initial identification and prioritisation of patients, boundary work informed negotiations over responsibility for patients, their transfer and admission to different wards, and their access to specific domains in order to receive diagnostic tests and treatment. In order to navigate boundaries successfully and for their clinical needs to be more easily recognised by staff, a patient needed to become a stable boundary object. Ongoing uncertainty in fixing their clinical classification, was a key reason why many NSTEMI patients faltered as boundary objects. Viewing NSTEMI patients as boundary objects helps to articulate the critical and ongoing process of classification and categorisation in the creation and maintenance of boundary objects. We show the essential, but hidden, role of boundary actors in making and re-making patients into boundary objects. Physical location was critical and the parallel processes of exclusion and restriction of boundary object status can lead to marginalisation of some patients and inequalities of care (A virtual abstract of this paper can be viewed at: https://www.youtube.com/channel/UC_979cmCmR9rLrKuD7z0ycA).
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Affiliation(s)
- Helen Cramer
- Centre for Academic Primary Care, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUK
| | - Jacki Hughes
- Centre for Trials ResearchCardiff UniversityCardiffUK
| | - Rachel Johnson
- Centre for Academic Primary Care, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUK
| | - Maggie Evans
- Centre for Academic Primary Care, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUK
| | - Christi Deaton
- Department of Public Health and Primary Care, School of Clinical MedicineUniversity of CambridgeCambridgeUK
| | - Adam Timmis
- Department of CardiologyBarts and The London NHS TrustLondonUK
| | - Harry Hemingway
- UCL PartnersFarr Institute of Health Informatics ResearchLondonUK
| | - Gene Feder
- Centre for Academic Primary Care, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUK
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Hemingway H, Feder GS, Fitzpatrick NK, Denaxas S, Shah AD, Timmis AD. Using nationwide ‘big data’ from linked electronic health records to help improve outcomes in cardiovascular diseases: 33 studies using methods from epidemiology, informatics, economics and social science in the ClinicAl disease research using LInked Bespoke studies and Electronic health Records (CALIBER) programme. PROGRAMME GRANTS FOR APPLIED RESEARCH 2017. [DOI: 10.3310/pgfar05040] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
BackgroundElectronic health records (EHRs), when linked across primary and secondary care and curated for research use, have the potential to improve our understanding of care quality and outcomes.ObjectiveTo evaluate new opportunities arising from linked EHRs for improving quality of care and outcomes for patients at risk of or with coronary disease across the patient journey.DesignEpidemiological cohort, health informatics, health economics and ethnographic approaches were used.Setting230 NHS hospitals and 226 general practices in England and Wales.ParticipantsUp to 2 million initially healthy adults, 100,000 people with stable coronary artery disease (SCAD) and up to 300,000 patients with acute coronary syndrome.Main outcome measuresQuality of care, fatal and non-fatal cardiovascular disease (CVD) events.Data platform and methodsWe created a novel research platform [ClinicAl disease research using LInked Bespoke studies and Electronic health Records (CALIBER)] based on linkage of four major sources of EHR data in primary care and national registries. We carried out 33 complementary studies within the CALIBER framework. We developed a web-based clinical decision support system (CDSS) in hospital chest pain clinics. We established a novel consented prognostic clinical cohort of SCAD patients.ResultsCALIBER was successfully established as a valid research platform based on linked EHR data in nearly 2 million adults with > 600 EHR phenotypes implemented on the web portal (seehttps://caliberresearch.org/portal). Despite national guidance, key opportunities for investigation and treatment were missed across the patient journey, resulting in a worse prognosis for patients in the UK compared with patients in health systems in other countries. Our novel, contemporary, high-resolution studies showed heterogeneous associations for CVD risk factors across CVDs. The CDSS did not alter the decision-making behaviour of clinicians in chest pain clinics. Prognostic models using real-world data validly discriminated risk of death and events, and were used in cost-effectiveness decision models.ConclusionsEmerging ‘big data’ opportunities arising from the linkage of records at different stages of a patient’s journey are vital to the generation of actionable insights into the diagnosis, risk stratification and cost-effective treatment of people at risk of, or with, CVD.Future workThe vast majority of NHS data remain inaccessible to research and this hampers efforts to improve efficiency and quality of care and to drive innovation. We propose three priority directions for further research. First, there is an urgent need to ‘unlock’ more detailed data within hospitals for the scale of the UK’s 65 million population. Second, there is a need for scaled approaches to using EHRs to design and carry out trials, and interpret the implementation of trial results. Third, large-scale, disease agnostic genetic and biological collections linked to such EHRs are required in order to deliver precision medicine and to innovate discovery.Study registrationCALIBER studies are registered as follows: study 2 – NCT01569139, study 4 – NCT02176174 and NCT01164371, study 5 – NCT01163513, studies 6 and 7 – NCT01804439, study 8 – NCT02285322, and studies 26–29 – NCT01162187. Optimising the Management of Angina is registered as Current Controlled Trials ISRCTN54381840.FundingThe National Institute for Health Research (NIHR) Programme Grants for Applied Research programme (RP-PG-0407-10314) (all 33 studies) and additional funding from the Wellcome Trust (study 1), Medical Research Council Partnership grant (study 3), Servier (study 16), NIHR Research Methods Fellowship funding (study 19) and NIHR Research for Patient Benefit (study 33).
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Affiliation(s)
- Harry Hemingway
- Institute of Health Informatics, University College London, London, UK
- Farr Institute of Health Informatics Research, University College London, London, UK
| | - Gene S Feder
- Centre for Academic Primary Care, School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Natalie K Fitzpatrick
- Institute of Health Informatics, University College London, London, UK
- Farr Institute of Health Informatics Research, University College London, London, UK
| | - Spiros Denaxas
- Institute of Health Informatics, University College London, London, UK
- Farr Institute of Health Informatics Research, University College London, London, UK
| | - Anoop D Shah
- Institute of Health Informatics, University College London, London, UK
- Farr Institute of Health Informatics Research, University College London, London, UK
| | - Adam D Timmis
- Farr Institute of Health Informatics Research, University College London, London, UK
- Barts Health NHS Trust, London, UK
- Farr Institute of Health Informatics Research, Queen Mary University of London, London, UK
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