title: Modelling Conditions and Health Care Processes in Electronic Health Records: An Application to Severe Mental Illness with the Clinical Practice Research Datalink.
abstract: BACKGROUND
  The use of Electronic Health Records databases for medical research has become mainstream. In the UK, increasing use of Primary Care Databases is largely driven by almost complete computerisation and uniform standards within the National Health Service. Electronic Health Records research often begins with the development of a list of clinical codes with which to identify cases with a specific condition. We present a methodology and accompanying Stata and R commands (pcdsearch/Rpcdsearch) to help researchers in this task. We present severe mental illness as an example.
  
  
  METHODS
  We used the Clinical Practice Research Datalink, a UK Primary Care Database in which clinical information is largely organised using Read codes, a hierarchical clinical coding system. Pcdsearch is used to identify potentially relevant clinical codes and/or product codes from word-stubs and code-stubs suggested by clinicians. The returned code-lists are reviewed and codes relevant to the condition of interest are selected. The final code-list is then used to identify patients.
  
  
  RESULTS
  We identified 270 Read codes linked to SMI and used them to identify cases in the database. We observed that our approach identified cases that would have been missed with a simpler approach using SMI registers defined within the UK Quality and Outcomes Framework.
  
  
  CONCLUSIONS
  We described a framework for researchers of Electronic Health Records databases, for identifying patients with a particular condition or matching certain clinical criteria. The method is invariant to coding system or database and can be used with SNOMED CT, ICD or other medical classification code-lists.
authors.affiliation: Institute of Biotechnology, University of Manchester, Manchester, United Kingdom.|Centre for Primary Care, NIHR School of Primary Care Research, Institute of Population Health, University of Manchester, Manchester, United Kingdom.
authors.forename: Ivan
authors.initials: I
authors.lastname: Olier
authors.affiliation: Centre for Primary Care, NIHR School of Primary Care Research, Institute of Population Health, University of Manchester, Manchester, United Kingdom.|Centre for Biostatistics, NIHR School of Primary Care Research, Institute of Population Health, University of Manchester, Manchester, United Kingdom.
authors.forename: David A
authors.initials: DA
authors.lastname: Springate
authors.affiliation: Centre for Pharmacoepidemiology and Drug Safety, Manchester Pharmacy School, University of Manchester, Manchester, United Kingdom.
authors.forename: Darren M
authors.initials: DM
authors.lastname: Ashcroft
authors.affiliation: Department of Health Sciences, University of York, York, United Kingdom.
authors.forename: Tim
authors.initials: T
authors.lastname: Doran
authors.affiliation: Centre for Primary Care, NIHR School of Primary Care Research, Institute of Population Health, University of Manchester, Manchester, United Kingdom.|Centre for Biostatistics, NIHR School of Primary Care Research, Institute of Population Health, University of Manchester, Manchester, United Kingdom.
authors.forename: David
authors.initials: D
authors.lastname: Reeves
authors.affiliation: Centre for Primary Care, NIHR School of Primary Care Research, Institute of Population Health, University of Manchester, Manchester, United Kingdom.
authors.forename: Claire
authors.initials: C
authors.lastname: Planner
authors.affiliation: Division of Health Research, University of Lancaster, Lancaster, United Kingdom.
authors.forename: Siobhan
authors.initials: S
authors.lastname: Reilly
authors.affiliation: Centre for Primary Care, NIHR School of Primary Care Research, Institute of Population Health, University of Manchester, Manchester, United Kingdom.|Centre for Health Informatics, Institute of Population Health, University of Manchester, Manchester, United Kingdom.
authors.forename: Evangelos
authors.initials: E
authors.lastname: Kontopantelis
mesh_terms: D000465:Algorithms; D059019:Clinical Coding; D016208:Databases, Factual; D057286:Electronic Health Records; D006801:Humans; D001523:Mental Disorders; D015233:Models, Statistical; D011320:Primary Health Care; D006113:United Kingdom