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Matthew Sperrin

  • PhD
  • Senior Lecturer in Health Data Science
  • University of Manchester
  • 12h-indexImpact measure calculated using publication and citation counts. Updated daily.
  • 444CitationsNumber of citations received by Matthew's publications. Updated daily.

Research interests

EpidemiologyStatistics

About

Dr Sperrin researches new statistical methodology to make inference with observational health data, collaborating closely with clinicians, epidemiologists, health informaticians, software engineers and statisticians. His research can be categorised in three areas: 1. Understanding the observation process. When data are observational it is crucial to understand why data are present (and why not present). For example, a blood pressure measurement in a medical record implies both that the patient has made contact with a healthcare professional, and the professional has deemed it appropriate to measure blood pressure. In other words, the presence of the measurement (or the absence) can be just as important as the measurement itself. This is often ignored in statistical analysis, which can lead to biased results. 2. Inferring trends and patterns from data. This can range from simple applied questions (is X associated with Y?) through to advanced statistical techniques to uncover hidden structure in a population. For example, a disease such as asthma may actually consist of a number of subdiseases (endotypes) that may have different outcomes and require different treatment. 3. Making predictions and decisions. Given what we know about a patient now, what do we think will happen to them in the future, and (therefore) what should happen next? For example, this involves developing prediction models for disease incidence and mortality, and complex simulation models to understand how disease may progress under different scenarios, both at an individual and population level.

Co-authors (225)

  • Hannah Lennon
  • Iain Buchan
  • Evangelos Kontopantelis

Publications (5)

  • A review of statistical updating methods for clinical prediction models

    • Su T
    • Jaki T
    • Hickey G
    • et al.
    N/AReaders
    0Citations
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  • Features of asthma which provide meaningful insights for understanding the disease heterogeneity

    • Deliu M
    • Yavuz T
    • Sperrin M
    • et al.
    N/AReaders
    0Citations
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  • Do patients have worse outcomes in heart failure than in cancer? A primary care-based cohort study with 10-year follow-up in Scotland

    • Mamas M
    • Sperrin M
    • Watson M
    • et al.
    N/AReaders
    4Citations
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  • Increased Radial Access Is Not Associated with Worse Femoral Outcomes for Percutaneous Coronary Intervention in the United Kingdom

    • Hulme W
    • Sperrin M
    • Kontopantelis E
    • et al.
    N/AReaders
    7Citations
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  • Relative survival after transcatheter aortic valve implantation: How do patients undergoing transcatheter aortic valve implantation fare relative to the general population?

    • Martin G
    • Sperrin M
    • Hulme W
    • et al.
    N/AReaders
    0Citations
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Professional experience

Senior Lecturer in Health Data Science

University of Manchester

May 2013 - Present