title: Inpatient electronic prescribing data can be used to identify 'lost' discharge codes for diabetes.
abstract: OBJECTIVE
  Accurate assessment of missed discharge codes for diabetes is critical for effective planning of hospital diabetes services. We wished to estimate the frequency of missed discharge diagnostic codes for diabetes and the impact missed codes would have on diabetes-related payments to the hospital.
  
  
  METHODS
  We linked Patient Administration System data to the Prescribing Information and Communication System. We defined diabetes as those having a discharge code for diabetes in the Patient Administration System and those on anti-diabetic medication in the Prescribing Information and Communication System. Based on the two sources, we calculated the estimated missed discharge codes for diabetes using the capture-recapture technique. We generated the Healthcare Resource Group for a given admission before and after correction for the missed code to estimate the impact that correction would make on payments to the hospital.
  
  
  RESULTS
  Among the 171 067 admissions linked, 22 412 (13.1%) had a code for diabetes at discharge. An additional 2706 admissions were classified as having diabetes based on prescription data. The capture-recapture technique estimated there were 4588 (2.7% of all admissions) admissions with diabetes missed by current coding, of which 2706 (60%) would be obtained from prescription data. After adding a diabetes diagnostic code, 12.8% of the missed admissions with diabetes resulted in a change to the Healthcare Resource Group tariff code and payment.
  
  
  CONCLUSIONS
  The use of electronic prescription data is a simple solution to correct for missed discharge diagnostic codes.
authors.affiliation: University of Birmingham, Birmingham, UK. k.nirantharan@bham.ac.uk
authors.forename: K
authors.initials: K
authors.lastname: Nirantharakumar
authors.forename: T
authors.initials: T
authors.lastname: Marshall
authors.forename: K
authors.initials: K
authors.lastname: Hemming
authors.forename: P
authors.initials: P
authors.lastname: Narendran
authors.forename: J J
authors.initials: JJ
authors.lastname: Coleman
mesh_terms: D000368:Aged; D059019:Clinical Coding / Q000458:organization & administration*; D003920:Diabetes Mellitus / Q000453:epidemiology*; D055695:Electronic Prescribing; D005260:Female; D006801:Humans; D007297:Inpatients / Q000706:statistics & numerical data*; D038801:International Classification of Diseases; D008297:Male; D016347:Medical Records Systems, Computerized / Q000458:organization & administration*; D008875:Middle Aged; D010351:Patient Discharge / Q000706:statistics & numerical data*; D006113:United Kingdom / Q000453:epidemiology