title: The accuracy of Scottish Morbidity Record (SMR1) data for identifying hospitalised stroke patients.
abstract: OBJECTIVE
  To assess the accuracy of the Scottish Morbidity Record (SMR1) data for stroke by comparing patients with a principal ICD-9 code of stroke on their SMR1 with those registered on our hospital-based stroke register (the Lothian Stroke Register [LSR]). We analysed why false positive and false negative SMR1 cases of stroke arose. We also compared two measures of outcome (death within 30 days, and proportion of patients discharged home within 56 days) in the group with verified stroke with those identified by SMR1 data.
  
  
  METHODS
  Retrospective, observational study.
  
  
  METHODS
  A university teaching hospital.
  
  
  METHODS
  (i) LSR group. We aimed to register all patients admitted to the medical directorate of our hospital with a stroke over a 36 month period. (ii) SMR1 group. All patients with a principal ICD-9 code of stroke on their SMR1 return for the same period.
  
  
  RESULTS
  566 strokes were registered on the LSR; 84 (15%) of these did not have a principal code of stroke on their SMR1. A further 75 patients not registered on the LSR, but who had a principal code of stroke on their SMR1, were identified; 39 of these had suffered a stroke, 28 had not, and no data were available for eight. Thus, including these missing eight as assumed strokes, the total number of verified strokes was 613; the sensitivity of the SMR1 data was 86%, the specificity 99.9%. Many of the SMR1 false positive and negative cases arose because of inaccurate or misleading diagnostic terms used by medical staff. There were no significant differences for the two outcome measures between the verified group and the SMR1 group.
  
  
  CONCLUSIONS
  Routinely collected SMR1 data for stroke in our hospital was reasonably accurate, but this result may not be widely generalisable as hospitals use different methods of coding. Inadequate data provided by clinicians was an important source of error, and should be correctable with better education. Despite the inaccuracies of the system, based on our results, the SMR1 data are probably a satisfactory way of identifying specific diagnostic groups for large scale audit.
authors.affiliation: University of Edinburgh, Department of Clinical Neurosciences, Western General Hospital.
authors.forename: R J
authors.initials: RJ
authors.lastname: Davenport
authors.forename: M S
authors.initials: MS
authors.lastname: Dennis
authors.forename: C P
authors.initials: CP
authors.lastname: Warlow
mesh_terms: D002561:Cerebrovascular Disorders / Q000175:diagnosis* / Q000453:epidemiology* / Q000401:mortality; D003951:Diagnostic Errors; D005189:False Positive Reactions; D006760:Hospitalization; D006801:Humans; D012042:Registries; D012189:Retrospective Studies; D012606:Scotland / Q000453:epidemiology; D012680:Sensitivity and Specificity