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Emma Parry's Outputs (4)

The accuracy of an electronic-Surprise-Question defining end-of-life cohorts in a whole adult population by algorithmic digital risk stratification: the Proactive Risk-Based and Data-Driven Assessment of Patients at the End of Life (PRADA). (2025)
Journal Article
Singh, B. M., Kumari-Dewat, N., Klaire, V., Lampitt, J., Palmer, A., Ryder, A., Ahmed, K., Sidhu, M., Jennens, H., Viswanath, A., & Parry, E. (2025). The accuracy of an electronic-Surprise-Question defining end-of-life cohorts in a whole adult population by algorithmic digital risk stratification: the Proactive Risk-Based and Data-Driven Assessment of Patients at the End of Life (PRADA). EBioMedicine, 115(May 2025), Article 105682. https://doi.org/10.1016/j.ebiom.2025.105682

Current methods for identifying end-of-life cannot be applied systematically to large populations. We have developed, tested, validated a mortality probability algorithm with that level of scalability. This was a prospective whole adult population co... Read More about The accuracy of an electronic-Surprise-Question defining end-of-life cohorts in a whole adult population by algorithmic digital risk stratification: the Proactive Risk-Based and Data-Driven Assessment of Patients at the End of Life (PRADA)..

Sequence Analysis to Phenotype Healthcare Patterns in Adults with Musculoskeletal Conditions Using Primary Care Electronic Health Records (2025)
Journal Article
Mathew, S., Peat, G., Parry, E., Wilkie, R., Jordan, K. P., Hill, J. C., & Yu, D. (in press). Sequence Analysis to Phenotype Healthcare Patterns in Adults with Musculoskeletal Conditions Using Primary Care Electronic Health Records. Arthritis Care & Research, 1-29. https://doi.org/10.1002/acr.25514

ObjectiveThe aim of this study was to apply sequence analysis (SA) to phenotype healthcare patterns of adult patients with musculoskeletal (MSK) conditions using primary care electronic health records and to investigate the association between these... Read More about Sequence Analysis to Phenotype Healthcare Patterns in Adults with Musculoskeletal Conditions Using Primary Care Electronic Health Records.

Developing an electronic Surprise Question to predict end-of-life prognosis in a prospective cohort study of acute hospital admissions (2025)
Journal Article
Singh, B., Kumari-Dewat, N., Ryder, A., Klaire, V., Jennens, H., Ahmed, K., Sidhu, M., Viswanath, A., & Parry, E. (2025). Developing an electronic Surprise Question to predict end-of-life prognosis in a prospective cohort study of acute hospital admissions. Clinical Medicine, Article 100292. https://doi.org/10.1016/j.clinme.2025.100292

Objective
Determining the accuracy of a method calculating the Gold Standards Framework Surprise Question (GSFSQ) equivalent end-of-life prognosis amongst hospital inpatients.
Design
A prospective cohort study with regression calculated 1-year mor... Read More about Developing an electronic Surprise Question to predict end-of-life prognosis in a prospective cohort study of acute hospital admissions.