Duke-NUS Corporate PPT - What is Health Services and Systems ...

Bridging stakeholders & analystsin service to positive changeDavid Matchar, MDProfessor and Director, Duke-NUS HealthServices and Systems Research Program

Population aging in SingaporeProjected % increase inpopulation ≥65 years, 2000-2030Japan 54UK 55Germany 63United States 102Australia 108China 170Malaysia 277SINGAPORE 372What are our goals?A population that ages well;achieving this in a way that ispractical, acceptable, sustainable2

Decisions• What to change?– Long term social care– Medical care, especially forchronic conditions• What to change to?– Expanding existing careservices– Developing new models ofcare• How to change?– Coordinated action3

“Health policy decision makers have to make difficultchoices in a rapidly changing and highly complexenvironment, which often includes vast quantities ofcontradictory information. This task involvesbridging two distinct cultures—that of the analystand that of the policy maker. This bridgingdemands a strategy as well as a significantinvestment of time and a commitment. Modernhealth policy development requires more thantechnical excellence. It requires excellentrelationships between the analysis and policymakingcommunities.”Sarria-Santamera A, Matchar DB, Westermann-Clark E, Patwardhan MB. (2006). Evidencebasedpractice center network and health technology assessment in the United States:Bridging the cultural gap. International Journal of Technology Assessment in Health Care.5

CMS-sponsored technology assessment• Assess the benefits of FDG-PET scanning inpatients with dementia, with mild cognitiveimpairment (MCI) and in asymptomatic patientswith a family history of AD, subsequent to thestandard evaluation as described in theAmerican Academy of Neurology (AAN)guidelines7

Steps• Framing the problem• Examining the evidence• Synthesizing the evidence modeling• Communicating the results• Iterating…• Decision making• Action8

Examining the evidence: PET andAD diagnosis in MCIMany fewer false positivesa few more false negativesTrue +False +False –True –CorrectClinicaldiagnosis(%) (%) (%) (%) (%)56 44 0 0 56PET 49 6 7 38 8711

Modeling to “fill the cheese”EpidemiologyStudiesOptionsAdministrativeDataOutcomesRandomizedTrialsBridgingModelPatientPreferenceDataExpertOpinion14

Illustrative patient historyYear1Asy MCI MiD MoD SeD D2Asy MCI MiD MoD SeD D3Asy MCI MiD MoD SeD D4Asy MCI MiD MoD SeD D17

ResultsNo PET/Treat allPET/Treat PositivesSurvival7.89 7.88Severe DisabilityfreeSurvival4.02 4.0018

Primary conclusion• PET could improve the overall accuracycompared to clinical exam• However, treatment based on an examleads to better health outcomes thantreatment based on PET results19

Communicating the results:How could this be?• Recall: net accuracy with PET is better (many fewerfalse positives and a few more false negatives)• But, false positives ≠ false negatives– Incorrectly treating (false positive) is not as bad asincorrectly not treating (false negative)– Incorrectly treating:• Rx is relatively benign, may be beneficial even if patient does nothave AD– Incorrectly not treating:• Patient loses benefit of Rx20

Communicating the results:What do we need to know?• What is the loss from a false negative?– Does this predict response to therapy?• What is the value of a true positive?– Do patients and families benefit from this information?– Does earlier diagnosis by PET lead to more efficientevaluation?True -Value ofknowingTest True +TreatDelayedprogressionFalse -False +AdverseEventDecreasedmortality21

Thank Youdavid.matchar@duke-nus.edu.sgwww.duke-nus.edu.sg