title: Estimating the prevalence of medically unexplained symptoms from primary care records.
abstract: OBJECTIVE
  To develop models to estimate the likely prevalence of medically unexplained symptoms (MUS) and severe MUS in a primary care practice from existing patient electronic records collected in the previous 2 years for secondary prevention and commissioning of psychological treatment.
  
  
  METHODS
  Cross-sectional survey comparing general practitioners' (GPs) assessment of the presence or absence of MUS and severe MUS with clinical, demographic and service use variables associated with MUS or functional somatic syndromes from previous research in the patient's routine electronic record over the previous 2 years.
  
  
  METHODS
  Seventeen GPs from eight practices identified cases of MUS and severe MUS in 828 consecutive consulters in primary care. Models of variables associated with MUS and severe MUS were constructed using multivariate multilevel logistic regression. The predictive validity of the final models was tested, comparing predicted with observed data and expected prevalence rates from the literature.
  
  
  RESULTS
  Models to predict MUS and severe MUS had areas under the receiver operating characteristic curve of 0.70 [95% confidence interval (CI) 0.65-0.74] and 0.76 (95% CI 0.70-0.82), respectively. Both models showed adequate goodness of fit with observed data, and had good predictive validity compared with the expected prevalence of MUS, severe MUS, and anxiety or depression.
  
  
  CONCLUSIONS
  Models to predict the prevalence of MUS and severe MUS from routine practice records for commissioning purposes were successfully developed, but they require independent validation before general use. The sensitivity of these models was too low for use in clinical screening.
authors.affiliation: Department of Psychiatry, Institute of Mental Health, University of Nottingham, Innovation Park, Triumph Road, Nottingham NG7 2TU, UK. richard.morriss@nottingham.ac.uk
authors.forename: R
authors.initials: R
authors.lastname: Morriss
authors.forename: N
authors.initials: N
authors.lastname: Lindson
authors.forename: C
authors.initials: C
authors.lastname: Coupland
authors.forename: G
authors.initials: G
authors.lastname: Dex
authors.forename: A
authors.initials: A
authors.lastname: Avery
mesh_terms: D000328:Adult; D000368:Aged; D003430:Cross-Sectional Studies; D057286:Electronic Health Records; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D015995:Prevalence; D011320:Primary Health Care / Q000706:statistics & numerical data*; D015203:Reproducibility of Results; D012720:Severity of Illness Index; D013001:Somatoform Disorders / Q000453:epidemiology*