Modeling for the Care of Complex Patients

267 Pages·2017·4.97 MB·English

by  Nisha Nataraj

ABSTRACT
NATARAJ,NISHA.ModelingfortheCareofComplexPatients.(UnderthedirectionofJulieS.Ivy.)
In this research, we study the manifestation of complexity via comorbidity in two different
indexdiseases,diabetesandsepsis.Complexity,attributabletoanumberoffactors,makespatients
moredifficulttodiagnoseandtreat.Fromamodelingperspective,adequatelyrepresentingmore
thanonediseaseposesseveralchallenges,includingdetermininghowtoaccountforcomorbidity,
interactionsbetweenthediseases,aswellaslimitationsindatasources.Thegoalofthisresearch
istoimprovetheunderstandingofcomplexpatientsviacomorbidityintwoindexdiseasesfrom
asystemsperspectiveandproviderecommendationsforpersonalizedcareunderthreedifferent
settings.Usingregressionmodels,clusteringmethodsanddiscrete-eventsimulation,weexamine
thechallengeofmultimorbiditybystudying(i)theburdenofcomorbidityindiabetesandtherole
ofsexandraceinhospitaloutcomesusinganationalinpatientdataset,(ii)diseaseinteractionand
medicationregimensinacombinedsimulationmodelofdiabetesanditscomorbidityofbreast
cancerusingmultipledatasources,and(iii)theimplicationsofdifferentdefinitionsandguidelines
onthediagnosisandtreatmentofsepticpatientswithcomorbidityusingelectronichealthrecords.
Inthehospitalizedpopulation,weshowthatthecomorbiditiesofdiabetescanimpactinpatient
outcomesincludinglengthofstay,totalchargesanddischargedisposition.Althoughhospitalized
womenhavebetteroutcomesthanmen,theimpactofdiabetesisworseinwomen,particularlyof
minorityraces.Thecombinedsimulationmodelofdiabetesandbreastcancerallowsustofocuson
aspecificcomorbidityofdiabetes.Here,westudyoutcomesunderdifferentassumptionsabout
therelationshipbetweendiabetes,glycemic-controlmedicationandbreastcancerincidence.Our
simulationexperimentsrevealthatmetforminimprovescanceroutcomesaswellaslowersthe
riskofhypoglycemiainwomen.Further,weshowthattheriskforhypoglycemiaacrossallracesis
asignificantdriverindelayinginsulininitiation.Finally,inpatientswithsepsis,ourresultsshow
thatthetimetofirsttreatmentis,onaverage,higherinpatientswithcomorbidity,suggestingthat
sepsis progresses differently in individuals with a large number comorbidities. The model also
shows significant differences in definition-driven outcomes, particularly when compared with
administrative(ICD9)codesavailableinpatients’records.
Thisresearchprovidesmodelsfordecisionmakinginthecontextofcomorbidityinaddition
tothemanagementandanalysisofcomplex,longitudinaldata.Thefindingsfromthisresearch
underscoreconsistentlytheimportanceofraceandgenderwhencaringforpatientswithmulti-
morbidity.Despitethechallengesanddatalimitationsassociatedwithmodelingmultiplediseases,
ourresultshighlighttheneedtomovefromasingle-diseasetoamulti-diseasefocus.
©Copyright2017byNishaNataraj
AllRightsReserved
ModelingfortheCareofComplexPatients
by
NishaNataraj
AdissertationsubmittedtotheGraduateFacultyof
NorthCarolinaStateUniversity
inpartialfulfillmentofthe
requirementsfortheDegreeof
DoctorofPhilosophy
IndustrialEngineering
Raleigh,NorthCarolina
2017
APPROVEDBY:
MariaMayorga FayCobbPayton
JamesWilson JulieS.Ivy
ChairofAdvisoryCommittee
DEDICATION
Thisdissertationisdedicatedtomyparents,RevathiandNataraj,fortheirunconditionallove,
supportandfaithinme,andmygrandparents,forepitomizingthevalueofpatienceand
perseverance.
ii
BIOGRAPHY
Nisha Nataraj is a PhD candidate in the Edward P. Fitts Department of Industrial and Systems
Engineering.SheisfromBangalore,IndiawhereshereceivedherBachelor’sdegreein2010fromM.S.
RamaiahInstituteofTechnologyinIndustrialEngineeringandManagement.Shethencompleted
herMaster’sinIndustrialandSystemsEngineeringin2012fromRochesterInstituteofTechnology,in
Rochester,NewYork.Herresearchinterestsincludetheanalyticalandpredictivemodelingofhealth
systemsresearchanddeliveryusingsimulation,andappliedstatisticalandstochasticmethods.She
isinterestedinthestudyofdiseaseprogression,managementandoutcomes,withaspecificinterest
inchronicdiseases,comorbidities,andhealthequity.SheisamemberoftheInstituteforIndustrial
and Systems Engineers (IISE) and the Institute for Operations Research and the Management
Sciences(INFORMS).
iii
ACKNOWLEDGEMENTS
Iamforeverindebtedtomyadvisor,Dr.JulieS.Ivy,forherinsight,patienceandunwaveringsupport
inthisendeavor.Iamprofoundlygratefulnotonlyforherguidanceinacademicmatters,butalso
forhercounselandunderstandinginotherrealmsaswell.
Iwouldliketoexpressmyenormousgratitudetothevaluablemembersofmycommitteeforall
theirtime,helpandvaluablefeedback.IamsincerelythankfultoDr.JimWilson,fortheinnumerable
hourspatientlyinvestedinhelpingmeanswerdifficultquestionsandhisdedicationtoperfection.
IowemanythankstoDr.MariaMayorgaforteachingmethevalueofperspectiveandclarityin
researchandtoDr.FayCobbPaytonforshowingmetheimportanceofthebigpicture.
AportionofthisworkwassupportedbyNationalScienceFoundationAward#1522107.Data
sourcesincludedtheNationalCancerInstitute-fundedBreastCancerSurveillanceConsortiumand
theHealthcareCostandUtilizationProject(HCUP)datapartners.Iwouldliketothankthemembers
oftheS.E.P.S.I.Sworkinggroupfortheircollaborativeefforts.Ialsothankthebreastcancer-diabetes
researchgroupfortheirinputandcontributions.SpecialthanksgotoDrs.JeanneHuddleston,Muge
Capan,RyanArnold,MinChiandJenniferMasonLobo,andtheS.E.P.S.I.Sstudentgroupfortheir
helpandinputs.
IowemuchtotheIndustrialandSystemsEngineeringdepartment,comprisingboththepeople
andresourcesrequiredtocompletethisresearch.IamespeciallythankfultoDr.AnitaVila-Parrish
forservingasmymentor,particularlyduringmyearlyyearsintheprogram.Thelastfewyearswere
madesignificantlyeasierbymyfellowgraduatestudentsandfriendsinDaniels375and373.Iam
particularlygratefultoRachelTownsley,KendallMcKenzie,KarenHicklinandShakibaEnayatifor
theirfriendshipandsupport.
Myundertakingwouldhavebeenimpossiblewithoutthesupportofmyfamily,fromeverycorner
oftheworld.Iamdeeplygratefultomysecondfamily,Suraj,SoudhaminiandGaurav,forbeinga
constantsourceofencouragementandcomfort.Myenormousgratitudeextendstomybrother,
Nakul,sister-in-law,Namitha,andmyaunt,Suma.Ihavereliedheavilyontheirsupport,loveand
iv
wordsofwisdom.Iwouldnothaveundertakenthisjourneyhaditnotbeenformygrandmother,
who has always been my inspiration. I am ever so grateful to my parents-in-law, Prapulla and
Ramaprasad,forlovingandtakingcareofmeastheirown.Icannoteverfullyexpresshowthankful
Iamtomyparentsforgivingmethecouragetocompletethisjourneydespitebeingthousandsof
milesaway,nurturingmyinterests,andmostimportantly,theirunconditionallove.
Finally,tomyhusbandandbestfriend,Tejas,Iowetheworld.Hispatience,love,andspirithave
beenthefoundationsofmystrength.Icouldnothavebeenblessedwithamoresupportivepartner,
andforthatIameternallygrateful.
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TABLEOFCONTENTS
LISTOFTABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii
LISTOFFIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv
Chapter1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 ComorbidityinComplexPatients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 IndexDiseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2.1 Diabetes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2.2 Sepsis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.3 ResearchObjectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Chapter2 QUANTIFYINGCOMORBIDITY. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.1 MeasuringComorbidity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.2 ResearchObjectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.3 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.3.1 RegressionAnalyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.3.2 PrincipalComponentandVariableClusterAnalyses. . . . . . . . . . . . . . . . . . . 20
2.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.4.1 Characterization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.4.2 RegressionAnalyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
2.4.3 DimensionReduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
2.4.4 SimplifiedCharlsonWIC. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
2.4.5 RegressionAnalysesRevisited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
2.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
Chapter3 MODELINGMULTIPLEDISEASES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
3.2 BreastCancerRisk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
3.2.1 ImpactofDiabetesonBreastCancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
3.2.2 ImpactofGlycemicControlMedicationonBreast-CancerRisk . . . . . . . . . . . 56
3.3 ExistingModels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
3.3.1 SimulationinHealthcare. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
3.3.2 DiabetesModels. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
3.3.3 BreastCancerModels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
3.4 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
3.5 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
3.5.1 DataSourcesandInitialization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
3.5.2 BreastCancerModel. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
3.5.3 DiabetesModel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
3.5.4 DeathSubmodel. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
3.6 Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
3.6.1 ExperimentalDesign . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
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3.6.2 ComparisonofScenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
3.7 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
3.7.1 BreastCancerPrevalence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
3.7.2 DiabetesComplications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
3.7.3 HypoglycemicEvents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
3.7.4 Death. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .108
3.7.5 ModelValidation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .109
3.8 Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .110
Chapter4 ModelingComplexConditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .115
4.1 ComplexityinSepsis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .116
4.2 ChallengeofDefiningSepsis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .118
4.2.1 CMSdefinition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .119
4.2.2 ThirdInternationalConsensusdefinition. . . . . . . . . . . . . . . . . . . . . . . . . . .119
4.2.3 S.E.P.S.I.SCollaborativedefinition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .121
4.2.4 IllustrativePatientTrajectory. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .124
4.3 ResearchObjectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .124
4.4 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .130
4.5 SimulationFramework. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .134
4.5.1 CohortDefinition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .135
4.5.2 VariableClusterAnalysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .137
4.5.3 SimulatingtheImpactofInterventions . . . . . . . . . . . . . . . . . . . . . . . . . . . .139
4.5.4 PatientSampling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .144
4.5.5 SimulationModel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .148
4.6 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .153
4.6.1 GeneralResults:MostImportantComorbidities . . . . . . . . . . . . . . . . . . . . . .154
4.6.2 GeneralResults:TimetoFirstIdentification. . . . . . . . . . . . . . . . . . . . . . . . .155
4.6.3 SimulationResults:ImpactofSimulatedInterventions. . . . . . . . . . . . . . . . .167
4.7 Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .173
Chapter5 ConclusionsandRecommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .176
5.1 MainFindingsoftheResearch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .176
5.2 RecommendationsforFutureWork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .179
BIBLIOGRAPHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .180
APPENDICES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .203
AppendixA Chapter2Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .204
A.1 ResultsfromPCAandClustering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .204
AppendixB Chapter3Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .208
B.1 NHANESEmpiricaldistributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .208
AppendixC Chapter4Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .218
C.1 ProbabilityofICD9SepsisDiagnosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .218
C.2 DistributionFitting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .219
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