Personal profile
Overview
Shaolin is a Research Fellow in Health Economics at the Health Organisation, Policy and Economics (HOPE). She completed her PhD in Economics (2010) at the University of Dundee and has subsequently worked at Dundee as the Scottish Institute for Research in Economics (SIRE) Research Fellow in Health Economics on a number of research projects. In 2013 she joined the Imperial College London to conduct research within the economics, evaluation and policy research stream of the NIHR Imperial Patient Safety and Translational Research Centre. Shaolin took a three-year career break to care for her children and returned to academic life at the University of Manchester in 2018. She is an Honorary Research Fellow at Imperial College London.
Research interests
Shaolin is interested in the economic evaluations of health policy initiatives, and economic analyses of the behaviour and performance of organisations and individuals within the health care system. Her previous researches included investigating the practice style and retention of the migrant health professionals in NHS Scotland; evaluating the impact of the patient adherence on the cost-effectiveness of breast cancer endocrine therapy using linked data on community prescriptions, hospital admissions and cancer registry; estimating the socioeconomic costs of spousal bereavement in Scotland; and estimating the healthy life years lost due to hospital adverse patient safety events by developing economic methodologies of using English hospital data to control for patients’ life expectancy and quality of life weights. Shaolin is currently working on the MRC NIHR Methodology Research Programme to develop methodologies for identifying and measuring spillover effects in the evaluation of interventions to change health care delivery and organisation.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 3 Good Health and Well-being
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Clustering high-cost patients in England using machine learning: a population-based cohort study
Wang, S., Anselmi, L., Sutton, M., Kontopantelis, E., Beaney, T. & Anderson, M., 5 Jan 2026, (Submitted) medRxiv, 25 p.Research output: Preprint/Working paper › Preprint
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Workload and funding: nationwide cross-sectional study of general practices in England
Anselmi, L., Lau, Y.-S., Wang, S., Anderson, M., Kontopantelis, E. & Sutton, M., 30 Mar 2026, (E-pub ahead of print) In: British Journal of General Practice.Research output: Contribution to journal › Article › peer-review
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Accounting for morbidity in capitation payments: a person-based workload formula for primary medical care in England
Anselmi, L., Wang, S., Lau, Y.-S., Anderson, M., Kontopantelis, E. & Sutton, M., 18 Jul 2025, (E-pub ahead of print) In: Health Policy. 105406.Research output: Contribution to journal › Article › peer-review
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Predicting healthcare costs with diagnoses recorded in primary and secondary care: an analysis of linked records
Wang, S., Anselmi, L., Lau, Y.-S. & Sutton, M., 6 May 2025, (E-pub ahead of print) In: Social Science & Medicine. 118157.Research output: Contribution to journal › Article › peer-review
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Inequalities in the prevalence recording of 205 chronic conditions recorded in primary and secondary care for 12 million patients in the English National Health Service
Wang, S., Lau, Y.-S., Sutton, M., Anderson, M., Kypridemos, C., Head, A., Barr, B., Cookson, R., Bentley, C. & Anselmi, L., 2 Dec 2024, In: BMC Medicine. 22, 570.Research output: Contribution to journal › Article › peer-review
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