References
- Baker C. Population estimates & GP registers: why the difference? House of commons library; 2016. Available from: https://commonslibrary.parliament.uk/population-estimates-gp-registers-why-the-difference/. Accessed December 1, 2021.
- Foley T, Fairmichael F. The potential of learning healthcare systems. the learning healthcare project; 2015. Available from: https://learninghealthcareproject.org/wp-content/uploads/2015/11/LHS_Report_2015.pdf. Accessed December 1, 2021.
- Friedman CP, Wong AK, Blumenthal D. Achieving a nationwide learning health system. Sci Transl Med. 2010;2:57cm29. doi:10.1126/scitranslmed.3001456
- Bradley SH, Lawrence NR, Carder P. Using primary care data for health research in England - an overview. Future Healthc J. 2018;5:207–212. doi:10.7861/futurehosp.5-3-207
- Benson T. Why general practitioners use computers and hospital doctors do not--Part 1: incentives. BMJ. 2002;325:1086–1089. doi:10.1136/bmj.325.7372.1086
- NHS England. SNOMED CT; 2023. Available from: https://www.england.nhs.uk/digitaltechnology/digital-primary-care/snomed-ct/. Accessed April 11, 2023.
- World Health Organization. International classification of diseases (IDC-11); 2023. Available from: https://www.who.int/standards/classifications/classification-of-diseases. Accessed April 11, 2023.
- OPCRD research publications. Available from: https://opcrd.co.uk/publications/. Accessed November 12, 2020.
- Jones R, Davis A, Stanley B, et al. Risk predictors and symptom features of long COVID within a broad primary care patient population including both tested and untested patients. Pragmat Obs Res. 2021;12:93–104. doi:10.2147/POR.S316186
- Kostikas K, Rhee CK, Hurst JR, et al. Adequacy of therapy for people with both COPD and heart failure in the UK: historical cohort study. Pragmat Obs Res. 2020;11:55–66. doi:10.2147/POR.S250451
- Davey P, Kirby MG. Cardiovascular risk profiles of GnRH agonists and antagonists: real-world analysis from UK general practice. World J Urol. 2021;39:307–315. doi:10.1007/s00345-020-03433-3
- Colice G, Chisholm A, Dima AL, et al. Performance of database-derived severe exacerbations and asthma control measures in asthma: responsiveness and predictive utility in a UK primary care database with linked questionnaire data. Pragmat Obs Res. 2018;9:29–42. doi:10.2147/POR.S151615
- Nibber A, Chisholm A, Soler-Cataluña JJ, Alcazar B, Price D, Miravitlles M. Validating the concept of COPD control: a real-world cohort study from the United Kingdom. Copd. 2017;14:504–512. doi:10.1080/15412555.2017.1350154
- Thickett D, Voorham J, Ryan R, et al. Historical database cohort study addressing the clinical patterns prior to idiopathic pulmonary fibrosis (IPF) diagnosis in UK primary care. BMJ Open. 2020;10:e034428. doi:10.1136/bmjopen-2019-034428
- Price D, Jones R, Pfister P, et al. Maximizing adherence and gaining new information for your chronic obstructive pulmonary disease (MAGNIFY COPD): study protocol for the pragmatic, cluster randomized trial evaluating the impact of dual bronchodilator with add-on sensor and electronic monitoring on clinical outcomes. Pragmat Obs Res. 2021;12:25–35. doi:10.2147/POR.S302809
- Smith JR, Musgrave S, Payerne E, et al. At-risk registers integrated into primary care to stop asthma crises in the UK (ARRISA-UK): study protocol for a pragmatic, cluster randomised trial with nested health economic and process evaluations. Trials. 2018;19:466. doi:10.1186/s13063-018-2816-z
- Stanley B, Davis A, Jones R, et al. Characteristics of patients in platform C19, a COVID-19 research database combining primary care electronic health record and patient reported information. PLoS One. 2021;16:e0258689. doi:10.1371/journal.pone.0258689
- Alves L, Pullen R, Hurst JR, et al. CONQUEST: a quality improvement program for defining and optimizing standards of care for modifiable high-risk COPD patients. Patient Relat Outcome Meas. 2022;13:53–68. doi:10.2147/PROM.S296506