Peter Williams

Peter Williams is a Statistics Consultant affiliated with the School of Mathematics and Physics at the University of Surrey. He is actively engaged in health services research, contributing to numerous national and multi-institutional studies, particularly in primary care, palliative care, and public health.

• PhD in Statistics or related field (inferred from research level)
• Extensive collaboration with health researchers across the UK
• Longstanding involvement in NIHR-funded projects

His research interests center on medical statistics, statistical computing, epidemiology, and modelling. He applies advanced statistical methods to evaluate healthcare interventions, service delivery models, and patient outcomes. His work spans diverse areas including general practice, cancer survivorship, dementia care, and end-of-life services.

The recent publications reflect a strong trend in health services research and clinical epidemiology, with a focus on patient-reported outcomes, cost-effectiveness, and evaluation of complex interventions. Many studies employ mixed-methods, realist evaluation, and large-scale survey designs, indicating expertise in both quantitative and qualitative data analysis.

Peter Williams has collaborated on research evaluating:

• Team climate in general practices
• Hospice-at-home services
• First Contact Physiotherapy models
• Patient-initiated follow-up in cancer care
• Diagnostic pathways for autism
• Supportive care needs in cancer survivors

His work is consistently published in high-impact journals such as BMC Primary Care, Palliative Medicine, British Journal of General Practice, and Alimentary Pharmacology & Therapeutics. While no formal advising role is listed, his frequent co-authorship on student-involved projects suggests mentorship and collaborative supervision. Funded by major bodies like the NIHR, his research contributes significantly to evidence-based health policy and service improvement.

He is involved with several research collaborations, including EARNEST, and contributes to studies requiring robust statistical design and analysis. His work supports the development of clinical guidelines and service models across the NHS.