title: Impact of systematic implementation of a clinical case finding strategy on diagnosis and therapy of postmenopausal osteoporosis.
abstract: BACKGROUND
  Case finding for osteoporosis in postmenopausal women is advocated in guidelines of osteoporosis, but implementation is unsatisfactory. We studied, in daily practice, the impact of systematic implementation of a previously validated clinical decision rule and fracture history on referral for bone densitometry (DXA) and drug prescription for osteoporosis.
  
  
  METHODS
  Before-after impact analysis in 41,478 consecutive consulting postmenopausal women, included by 1080 general practitioners (GPs) during 2 mo, using the osteoporosis self-assessment (OST) index (based on age and weight, indicating women at low [LR], moderate [MR], and high risk [HR] for having osteoporosis [T-score < -2.5 in spine and/or hip]) and fracture history. Relative risks (RRs) and 95% CIs were calculated between referrals before (n = 6580) and after intervention (n = 10,379) and between risk subgroups.
  
  
  RESULTS
  Post-intervention RR for referral for DXA was 1.9 (95% CI, 1.8-2.0). Compared with LR women with prior DXA, the RR was 6.3 (95% CI, 6.0-6.6) in MR and 10.7 (95% CI, 10.0-11.4) in HR women without fracture, but similar in MR and HR women with fracture (11.4 and 11.6, respectively). New cases of osteoporosis were diagnosed in 3811 women, 96% of whom were prescribed drug treatment. Of HR women, 79% were referred for DXA. The sensitivity of a low OST index to predict osteoporosis was 92% and specificity was 16%.
  
  
  CONCLUSIONS
  The impact of temporary systematic implementation of this case finding strategy on GP practice was high: it nearly tripled referrals for DXA, and 96% of patients found to have osteoporosis had treatment. The impact depended on OST index and fracture history. Only 79% of HR women were referred for DXA. Specificity of a low OST index to predict osteoporosis was low. This indicates the need in the GP population for case finding strategies with fewer barriers for referral for DXA and with higher accuracy for predicting osteoporosis.
authors.affiliation: Biomedical Research Institute, University Hasselt, Hasselt, Belgium. piet.geusens@scarlet.be
authors.forename: Piet
authors.initials: P
authors.lastname: Geusens
authors.forename: Bianca
authors.initials: B
authors.lastname: Dumitrescu
authors.forename: Tineke
authors.initials: T
authors.lastname: van Geel
authors.forename: Sven
authors.initials: S
authors.lastname: van Helden
authors.forename: Johan
authors.initials: J
authors.lastname: Vanhoof
authors.forename: Geert Jan
authors.initials: GJ
authors.lastname: Dinant
mesh_terms: D003720:Densitometry; D005260:Female; D006801:Humans; D008875:Middle Aged; D015663:Osteoporosis, Postmenopausal / Q000175:diagnosis* / Q000453:epidemiology / Q000628:therapy*