title: An algorithm to improve diagnostic accuracy in diabetes in computerised problem orientated medical records (POMR) compared with an established algorithm developed in episode orientated records (EOMR).
abstract: BACKGROUND
  An algorithm that detects errors in diagnosis, classification or coding of diabetes in primary care computerised medial record (CMR) systems is currently available. However, this was developed on CMR systems that are episode orientated medical records (EOMR); and do not force the user to always code a problem or link data to an existing one. More strictly problem orientated medical record (POMR) systems mandate recording a problem and linking consultation data to them.
  
  
  OBJECTIVE
  To compare the rates of detection of diagnostic accuracy using an algorithm developed in EOMR with a new POMR specific algorithm.
  
  
  METHODS
  We used data from The Health Improvement Network (THIN) database (N = 2,466,364) to identify a population of 100,513 (4.08%) patients considered likely to have diabetes. We recalibrated algorithms designed to classify cases of diabetes to take account of that POMR enforced coding consistency in the computerised medical record systems [In Practice Systems (InPS) Vision] that contribute data to THIN. We explored the different proportions of people classified as having type 1 diabetes mellitus (T1DM) or type 2 diabetes mellitus (T2DM) and with diabetes unclassifiable as either T1DM or T2DM. We compared proportions using chi-square tests and used Tukey's test to compare the characteristics of the people in each group.
  
  
  RESULTS
  The prevalence of T1DM using the original EOMR algorithm was 0.38% (9,264/2,466,364), and for T2DM 3.22% (79,417/2,466,364). The prevalence using the new POMR algorithm was 0.31% (7,750/2,466,364) T1DM and 3.65% (89,990/2,466,364) T2DM. The EOMR algorithms also left more people unclassified 11,439 (12%), as to their type of diabetes compared with 2,380 (2.4%), for the new algorithm. Those people who were only classified by the EOMR system differed in terms of older age, and apparently better glycaemic control, despite not being prescribed medication for their diabetes (p < 0.005).
  
  
  CONCLUSIONS
  Increasing the degree of problem orientation of the medical record system can improve the accuracy of recording of diagnoses and, therefore, the accuracy of using routinely collected data from CMRs to determine the prevalence of diabetes mellitus; data processing strategies should reflect the degree of problem orientation.
authors.affiliation: University of Surrey, Guildford, UK. s.lusignan@surrey.ac.uk.
authors.forename: Simon
authors.initials: S
authors.lastname: de Lusignan
authors.affiliation: University of New South Wales, Australia.
authors.forename: Siaw-Teng
authors.initials: ST
authors.lastname: Liaw
authors.affiliation: Clinical Practice Research Datalink, London, UK.
authors.forename: Daniel
authors.initials: D
authors.lastname: Dedman
authors.affiliation: University of Leicester, Leicester, UK.
authors.forename: Kamlesh
authors.initials: K
authors.lastname: Khunti
authors.affiliation: University of Surrey, Guildford, UK.
authors.forename: Khaled
authors.initials: K
authors.lastname: Sadek
authors.affiliation: University of Surrey, Guildford, UK.
authors.forename: Simon
authors.initials: S
authors.lastname: Jones
mesh_terms: D000465:Algorithms; D003937:Diagnosis, Differential; D057286:Electronic Health Records; D017050:Episode of Care; D006801:Humans; D008501:Medical Records, Problem-Oriented
keywords: computerized; diabetes mellitus; epidemiology; medical record systems; medical records; problem-oriented; records as topic