A predictive model to identify Parkinson disease from administrative claims data

Neurology

Volumn 89, Issue 14, 2017, Pages 1448-1456

  Nielsen, Susan Searles ^a   Warden, Mark N ^a   Camacho Soto, Alejandra ^a   Willis, Allison W ^b   Wright, Brenton A ^a   Racette, Brad A ^c  

^a WASHINGTON UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

^c UNIVERSITY OF THE WITWATERSRAND   (South Africa)

Author keywords

[No Author keywords available]

Indexed keywords

ADMINISTRATIVE CLAIMS (HEALTH CARE); AGED; ALGORITHM; ANOSMIA; ARTICLE; CASE CONTROL STUDY; CONFIDENCE INTERVAL; CONSTIPATION; CONTROLLED STUDY; DEMOGRAPHY; DIAGNOSTIC PROCEDURE; DIAGNOSTIC TEST ACCURACY STUDY; ETHNICITY; FEMALE; HEALTHCARE COMMON PROCEDURE CODING SYSTEM; HUMAN; HYPOSMIA; INCIDENCE; MAJOR CLINICAL STUDY; MALE; MEDICARE; PARASOMNIA; PARKINSON DISEASE; POPULATION BASED CASE CONTROL STUDY; PREDICTIVE VALUE; PREDICTOR VARIABLE; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; SMOKING; TASTE DISORDER; VERY ELDERLY; COMPLICATION; OLFACTION DISORDERS; RETROSPECTIVE STUDY; SLEEP WAKE DISORDERS; STATISTICS AND NUMERICAL DATA; UNITED STATES;

AGED; AGED, 80 AND OVER; CASE-CONTROL STUDIES; FEMALE; HUMANS; MALE; MEDICARE; OLFACTION DISORDERS; PARKINSON DISEASE; PREDICTIVE VALUE OF TESTS; RETROSPECTIVE STUDIES; ROC CURVE; SLEEP WAKE DISORDERS; UNITED STATES;

EID: 85030776257     PISSN: 00283878     EISSN: 1526632X     Source Type: Journal    
DOI: 10.1212/WNL.0000000000004536     Document Type: Article

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