Healthcare Analytics: Introduction
Electronic Medical Records
Data processing techniques
Statistical concepts
Machine learning techniques
Case-studies
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Healthcare Analytics: IntroductionTrần Thế TruyềnCenter for Pattern Recognition and Data AnalyticsDeakin University, AustraliaEmail: truyen.tran@deakin.edu.auURL: truyen.vietlabs.comHUST, Dec 2013“It is a capital mistake to theorize before one has data.” - Sir Arthur Conan Doyle3mental healththe problemmental health problems increasinglaborious risk assessments.but all data is not easily accessibleCourse components11Major componentsElectronic Medical RecordsData processing techniquesStatistical conceptsMachine learning techniquesCase-studies12Optional componentsMedical text miningVisual analytics Research topics13What is healthcare analytics?Analytics is “data, statistical, and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions”. Davenport TH and Harris JG. 2007. Competing on Analytics. Boston: Harvard Business School Press.Healthcare analytics is “collection, statistical interpretation, qualitative analysis and predictive modelling of the vast amount of patient data to provide ready-made solutions and health plans to case-specific problems.” []Real-time: helps creating prescriptions of individual patientsBatch time: helps in managing the health of a broader population.1415 analytics examples16Suicide risk factors discoveryWhy healthcare analytics?Big data is there to explore and exploitImprove Decision Support SystemsReduce errorsSave moneyIncrease efficiencyMake better strategic decisionsGovernments want Return-Of-Investment (ROI)17when making choices in models of care through accurate risk predictionwhen treatments chosen for risky or rare cases – find me cases like this onewhen evaluating hospital quality and service efficiency next generation teaching – present thousands of cases to supplement number of cases seensolutions can inform1923.7%/yr Velocity VarietyAnalytics process21Source: sas.comHealthcare data types22Source: Sun & Reddy, Big Data Analytics for Healthcare, Tutorial at SDM’13risk prediction/stratification23readmissiondeathtoxicitystressquality-of-lifeprogression to advanced stageslength-of-stayside effectssuicide attempts24PRaDA Risk Stratification SystemWhere are we, in Vietnam?Digitalization of health recordsRural/remote areasEpidemiology25Project announcement26
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