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
2018
Evaluation of Complementary and Integrative Health Approaches Among US Veterans with Musculoskeletal Pain Using Propensity Score Methods
Han L, Goulet JL, Skanderson M, Bathulapalli H, Luther SL, Kerns RD, Brandt CA. Evaluation of Complementary and Integrative Health Approaches Among US Veterans with Musculoskeletal Pain Using Propensity Score Methods. Pain Medicine 2018, 20: 90-102. PMID: 29584926, PMCID: PMC6329442, DOI: 10.1093/pm/pny027.Peer-Reviewed Original ResearchConceptsIntegrative health approachesPS matchingCIH exposureMusculoskeletal painPropensity score methodsSelf-rated pain intensityHealth approachHigher pain intensity ratingsPain intensity outcomesChronic musculoskeletal painPain intensity ratingsIPTW modelsRetrospective cohortPain intensityChronic painClinical visitsInitial diagnosisChiropractic careUS veteransBaseline differencesTreatment weightingExposure groupPainScore methodTreatment effectiveness
2016
Statistical Models for the Analysis of Zero-Inflated Pain Intensity Numeric Rating Scale Data
Goulet JL, Buta E, Bathulapalli H, Gueorguieva R, Brandt CA. Statistical Models for the Analysis of Zero-Inflated Pain Intensity Numeric Rating Scale Data. Journal Of Pain 2016, 18: 340-348. PMID: 27919777, DOI: 10.1016/j.jpain.2016.11.008.Peer-Reviewed Original ResearchConceptsStatistical modelStatistical methodsExcess of zerosAlternative statistical methodsFollowing statistical modelsNumeric rating scaleNRS scoresDiscrete valuesOrdinal dataLarge cohortLinear modelCumulative logit modelMusculoskeletal disordersRight-skewed distributionZerosObservational cross-sectional studyInterpretability of resultsMean NRS painPainful musculoskeletal disordersPredictor effectsVeterans Affairs (VA) carePain intensity dataCross-sectional studyNRS dataDiagnosis date