Positive predictive value of diagnosis coding for hemolytic anemias in the Danish National Patient Register

Abstract

PURPOSE The nationwide public health registers in Denmark provide a unique opportunity for evaluation of disease-associated morbidity if the positive predictive values (PPVs) of the primary diagnosis are known. The aim of this study was to evaluate the predictive values of hemolytic anemias registered in the Danish National Patient Register. PATIENTS AND METHODS All patients with a first-ever diagnosis of hemolytic anemia from either specialist outpatient clinic contact or inpatient admission at Odense University Hospital from January 1994 through December 2011 were considered for inclusion. Patients with mechanical reason for hemolysis such as an artificial heart valve, and patients with vitamin-B12 or folic acid deficiency were excluded. RESULTS We identified 412 eligible patients: 249 with a congenital hemolytic anemia diagnosis and 163 with acquired hemolytic anemia diagnosis. In all, hemolysis was confirmed in 359 patients, yielding an overall PPV of 87.1% (95% confidence interval [CI]: 83.5%-90.2%). A diagnosis could be established in 392 patients of whom 355 patients had a hemolytic diagnosis. Diagnosis was confirmed in 197 of the 249 patients with congenital hemolytic anemia, yielding a PPV of 79.1% (95% CI: 73.5%-84.0%). Diagnosis of acquired hemolytic anemia could be confirmed in 136 of the 163 patients, resulting in a PPV of 83.4% (95% CI: 76.8%-88.8%). For hemoglobinopathy PPV was 84.1% (95% CI: 77.4%-89.4%), for hereditary spherocytosis PPV was 80.6% (95% CI: 69.5%-88.9%), and for autoimmune hemolytic anemia PPV was 78.4% (95% CI: 70.4%-85.0%). CONCLUSION The PPV of hemolytic anemias was moderately high. The PPVs were comparable in the three main categories of overall hemolysis, and congenital and acquired hemolytic anemia.

DOI: 10.2147/CLEP.S93643

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@inproceedings{Hansen2016PositivePV, title={Positive predictive value of diagnosis coding for hemolytic anemias in the Danish National Patient Register}, author={Dennis Lund Hansen and Ulrik Malthe Overgaard and Lars Pedersen and Henrik Frederiksen}, booktitle={Clinical epidemiology}, year={2016} }