2020
Exploring supervised machine learning approaches to predicting Veterans Health Administration chiropractic service utilization
Coleman BC, Fodeh S, Lisi AJ, Goulet JL, Corcoran KL, Bathulapalli H, Brandt CA. Exploring supervised machine learning approaches to predicting Veterans Health Administration chiropractic service utilization. Chiropractic & Manual Therapies 2020, 28: 47. PMID: 32680545, PMCID: PMC7368704, DOI: 10.1186/s12998-020-00335-4.Peer-Reviewed Original ResearchConceptsSpinal pain conditionsService utilizationPain conditionsChiropractic careConservative interventionsChiropractic servicesVA chiropractic servicesRetrospective cohort studyHealthcare service utilizationHealthcare cost burdenLimited clinical utilityLower healthcare costsCohort entryCohort studyDiagnosis cohortPain statusPrimary outcomeChiropractic visitsClinical featuresUS adultsClinical utilityHealthcare costsDifferent clinical populationsVisitsClinical populations
2011
Validity of diagnostic codes and liver‐related laboratory abnormalities to identify hepatic decompensation events in the Veterans Aging Cohort Study
Re V, Lim JK, Goetz MB, Tate J, Bathulapalli H, Klein MB, Rimland D, Rodriguez‐Barradas M, Butt AA, Gibert CL, Brown ST, Kidwai F, Brandt C, Dorey‐Stein Z, Reddy KR, Justice AC. Validity of diagnostic codes and liver‐related laboratory abnormalities to identify hepatic decompensation events in the Veterans Aging Cohort Study. Pharmacoepidemiology And Drug Safety 2011, 20: 689-699. PMID: 21626605, PMCID: PMC3131229, DOI: 10.1002/pds.2148.Peer-Reviewed Original ResearchConceptsVeterans Aging Cohort StudyHepatic decompensation eventsPositive predictive valueHigh positive predictive valueLaboratory abnormalitiesAging Cohort StudyDecompensation eventsDiagnostic codesCohort studyHepatic decompensationVariceal hemorrhageOutpatient diagnostic codesChronic liver diseaseSpontaneous bacterial peritonitisImpact of medicationLiver dysfunctionBacterial peritonitisLiver diseaseMedical recordsOutpatient codesPredictive valueNatural historyAbnormalitiesEpidemiologic researchPatients