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Can process mining automatically describe care pathways of patients with long-term conditions in UK primary care? A study protocol
  1. Ian Litchfield1,
  2. Ciaron Hoye2,
  3. David Shukla1,
  4. Ruth Backman1,
  5. Alice Turner3,
  6. Mark Lee4,
  7. Phil Weber5
  1. 1 Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
  2. 2 Digital Transformation, Birmingham Solihull Clinical Commissioning Group, Birmingham, UK
  3. 3 University Hospitals Birmingham NHS Foundation Trust and Institute of Applied Health Research, University of Birmingham, Birmingham, UK
  4. 4 School of Computer Science, College of Engineering and Physical Sciences, University of Birmingham, Birmingham, UK
  5. 5 School of Engineering and Applied Science, System Analytics for Innovation, Aston University, Birmingham, UK
  1. Correspondence to Dr Ian Litchfield; i.litchfield{at}


Introduction In the UK, primary care is seen as the optimal context for delivering care to an ageing population with a growing number of long-term conditions. However, if it is to meet these demands effectively and efficiently, a more precise understanding of existing care processes is required to ensure their configuration is based on robust evidence. This need to understand and optimise organisational performance is not unique to healthcare, and in industries such as telecommunications or finance, a methodology known as ‘process mining’ has become an established and successful method to identify how an organisation can best deploy resources to meet the needs of its clients and customers. Here and for the first time in the UK, we will apply it to primary care settings to gain a greater understanding of how patients with two of the most common chronic conditions are managed.

Methods and analysis The study will be conducted in three phases; first, we will apply process mining algorithms to the data held on the clinical management system of four practices of varying characteristics in the West Midlands to determine how each interacts with patients with hypertension or type 2 diabetes. Second, we will use traditional process mapping exercises at each practice to manually produce maps of care processes for the selected condition. Third, with the aid of staff and patients at each practice, we will compare and contrast the process models produced by process mining with the process maps produced via manual techniques, review differences and similarities between them and the relative importance of each. The first pilot study will be on hypertension and the second for patients diagnosed with type 2 diabetes.

Ethics and dissemination Ethical approval has been provided by East Midlands–Leicester South Regional Ethics Committee (REC reference 18/EM/0284). Having refined the automated production of maps of care processes, we can explore pinch points and bottlenecks, process variants and unexpected behaviour, and make informed recommendations to improve the quality and efficiency of care. The results of this study will be submitted for publication in peer-reviewed journals.

  • health informatics
  • organisation of health services
  • primary Care

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  • Contributors lL, PW and CH were responsible for the conception of the work and the design of the study. IL led the drafting of the article with input from PW, CH and DS. ML, AT, CH, DS and RB all provided critical revisions. The final version was drafted by lL and PW and approved by AT, RB, ML, CH and DS.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Patient consent Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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