Project: Clinical Decision Support tools for asthma in Primary Care Research Fellow overview Project: Clinical Decision Support tools for asthma in Primary Care Based at: University of Edinburgh Email: holly.tibble@ed.ac.uk There is huge potential to make use of the wealth of data collected from routine asthma care to inform data-driven clinical support, to reduce the risk of asthma exacerbations resulting in the need for oral steroids, emergency care, hospital admissions and, in some cases, death. My first aim is to refine and validate my developing risk prediction model. However, it is crucial that qualitative research is conducted with key stakeholders to steer risk stratification research towards maximum value and impact. My second aim is to work with clinicians and patients to design a clinical decision support tool powered by this model, to guide primary care consultations and reduce the risk of serious outcomes. Image Holly Tibble, Centre Research Fellow About me Holly studied Mathematics with Operational Research and Statistics for her undergraduate degree in Cardiff University, Epidemiology for her MPhil at Cambridge University, and Medical Informatics for her PhD at Edinburgh University (2021). After completing her MPhil she spent two years at the Melbourne School for Population and Global Health, working in evaluating the impact of policy changes to mental health legislation, using electronic health records. After completing her PhD, she undertook a two-year post-doctoral fellowship in Edinburgh within the Data Analytics Research and Technology in Healthcare (DARTH) group, focusing on evaluating the real-world impact of interventions using electronic health records and other administrative health datasets, and predicting clinical outcomes in these datasets using machine learning. In 2023, she was awarded a prestigious Chancellor’s Fellowship from the University of Edinburgh: a five-year fellowship designed to help the most promising academics advance from the early stages of their career to more senior roles, and to empower their ground-breaking research. Publications Tibble H, Sheikh A, Tsanas A. (2022) Estimating Medication Adherence from Electronic Health Records Using Rolling Averages of Single Refill-based Estimates. 2022 IEEE International Engineering in Medicine and Biology Conference (EMBC) (In Press). Tibble H, Sheikh A, Tsanas A. (2021) Estimation of Asthma Severity from Electronic Prescription Records using British Thoracic Society and Scottish Intercollegiate Guidelines Network Treatment Steps. 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM): Fifth Edition of Workshop Processes and Algorithms for Healthcare and Life Quality Improvement (CBPBL). (In Press). Nwaru BI, Shah SA, Tibble H, Pillinger R, McLean S, Ryan D, Critchley H, Hawrylowicz CM, Simpson CR, Soyiri IN, Appiagyei F, Price D, Sheikh A. (2021) Hormone replacement therapy and risk of severe asthma exacerbation in peri-menopausal and post-menopausal women: 17-year national cohort study. Journal of Allergy and Clinical Immunology in Practice. (DOI: 10.1016/j.jaip.2021.02.052) Sheikh A, Anderson M, Albala S, Casadei B, Dean Franklin B, Richards M, Taylor D, Tibble H, Mossialios E. (2021) Health information technology and digital innovation for national learning health and care systems. Lancet Digital Health. (DOI: 10.1016/S0140-6736(21)00232-4) Nwaru BI, Tibble H, Shah SA, Pillinger R, McLean S, Ryan D, Critchley HOD, Price D, Hawrylowicz CM, Simpson CR, Soyiri IN, Appiagyei F, Sheikh A. (2021) Hormonal contraception and the risk of severe asthma exacerbation: 17-year population-based cohort study. Thorax. 76(2). p.109-115. DOI: 10.1136/thoraxjnl-2020-215540 Stage Baxter M, Tibble H, Bush A, Sheikh A, Schwarze J. (2021) Efficacy of mobile health interventions to improve nasal corticosteroid adherence in allergic rhinitis: a systematic review. Clinical and Translational Allergy. 11(9). e12075. Tibble H, Flook M, Sheikh A, Tsanas A, Horne R, Vrijens B, De Geest S, Stagg HR. (2020) Measuring and reporting treatment adherence: what can we learn by comparing two respiratory conditions? British Journal of Clinical Pharmacology. 87(3). p.825-836. Tibble H, Chan AHY, Mitchell EA, Horne E, Doudesis D, Horne R, Mizani MA, Sheikh A, Tsanas A. (2020) A Data-Driven Typology of Asthma Medication Adherence using Cluster Analysis. Scientific Reports. 10(1). 14999. DOI: 10.1038/s41598-020-72060-0 Tibble H, Lay-Flurrie J, Sheikh A, Horne R, Mizani MA, Tsanas A, The Salford Lung Study Team. (2020) Linkage of Primary Care Prescribing Records and Pharmacy Dispensing Records in the Salford Lung Study: Application in Asthma. BMC Medical Research Methodology. 20(1). 303. DOI: 10.1186/s12874-020-01184-8 Tibble H, Horne E, Horne R, Mizani AM, Simpson CR, Sheikh A, Tsanas A. (2019) Predicting asthma attacks in primary care: protocol for developing a machine learning-based prediction model. BMJ Open. 9(7), e028375. DOI: 10.1136/bmjopen-2018-028375 Holly's other publications can be found on her ORCID page Research Activity Oral Presentations Adult Asthma Attack Risk Prediction in Primary Care. AUKCAR ASM, 15th June 2022, Leeds UK. Estimating Use of Short-Term Asthma Reliever Inhalers from Electronic Prescription Records. BIOSTEC 2022, 9th February, 2022. Virtual. Estimation of Asthma Severity from Electronic Prescription Records using British Thoracic Society and Scottish Intercollegiate Guidelines Network Treatment Steps. IEEE BIBM, 9th December 2021, Virtual. Hormonal contraceptives and clinical outcomes of asthma in reproductive-age women: UK population-based cohort study. Asthma UK Centre for Applied Research ASM, 26th March 2020, Virtual Event. Linkage of Primary Care Prescribing Records and Pharmacy Dispensing Records in the Salford Lung Study: Application in Asthma. Administrative Data Research, 9th – 11th December 2019, Cardiff, UK. Heterogeneity in Asthma Medication Adherence Measurement. IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE), 28th – 30th October 2019, Athens, Greece. Poster presentations Estimating Medication Adherence from Electronic Health Records Using Rolling Averages of Single Refill-based Estimates. IEEE EMBC, 14th July 2022, Glasgow UK. Linkage of Primary Care Prescribing Records and Pharmacy Dispensing Records in the Salford Lung Study: Application in Asthma Adherence Research. International Society for Pharmacoepidemiology (ISPE) Mid-Year Meeting, 15th September 2020, Virtual Event. Measuring and Reporting Treatment Non-Adherence: What Can We Learn from the Cross-Comparison of Two Respiratory Conditions? Asthma UK Centre for Applied Research ASM, 26th March 2020, Virtual Event. Linkage of Primary Care Prescribing Records and Pharmacy Dispensing Records in the Salford Lung Study: Application in Asthma Adherence Research. Asthma UK Centre for Applied Research ASM, 26th March 2020, Virtual Event. A Data-Driven Typology of Asthma Medication Adherence Subgroups and their Associated Clinical Outcomes. Scottish Informatics and Computer Science Alliance (SICSA), 18th – 19th June 2019, Aberdeen, UK. Predicting asthma attacks in primary care: protocol for developing a machine learning-based prediction model. Asthma UK Centre for Applied Research ASM, 12th March 2019, London, UK. Follow Holly Holly's LinkedIn profile Holly's Twitter profile This article was published on 2024-09-24