Intro to Medical Informatics Medical Informatics • Intersection of medicine and computing • Plus theory and experience specific to this combination • =Medical Computing, ~Health Informatics • Science • Applied science • Engineering 3 Outline • icare • l • 4 MI def ned by goals and methods of health Medical data: essentiaExpertise (methods) – Procedural – Inferential – Causal – Probabilistic The Medical Cycle observe plan decide patient data information diagnosis therapy initial presentation Care Processes Meta-level processes • Acquisition and application of knowledge • Data: instrumentation, monitoring, telemetry • Education • Information: interpretation, filtering, sampling, • Quality control and process improvement smoothing, clustering • Cost containment • Diagnosis: inference, model-based reasoning, classification • Reference (library) • Prognosis: prediction, natural course, experience • Therapy: planning, predicting effects, anticipating 5 6 Harvard-MIT Division of Health Sciences and Technology�� HST.950J: Medical Computing�� 2 Peter Szolovits, PhD9Intro to Medical Informatics Time scale in medicine • Cure—usually acute illness • Manage—long-term, chronic illness • Prevent • Predict (especially based on genetics) 7 WHO Constitution defines “health” “a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity” • Physical • Mental • Social —very hard to measure Distribution of Ages • Li(10 fe table deaths by year Japan, 1989) Life table death rates by age Life table cohort survival Measures of Health • Longevity at birth (CIA World Fact Book, 2001) US SSA 1997 11 12 8Intro to Medical Informatics Quality of life • Value of a total life depends on –Length (assume now is N) –Quality (q) over time –Discounts (� g) for future or past (depends very much on what the value is to be used for) VN=Integral[t=0,T] q(t) g(t-N) dt 13 14 Top 10 Chronic Conditions Persons aged � 65 15 16U.S. Nat’l Ctr Health Stat, Vital and Health Statistics, 1985 (1982 data) Causes of death (industrialized countries, 1989) Circulatory 48% system Malignant 19% neoplasms Accidents 7% Others 26% Modeling life quality Societal quality of life • Aggregation of individual qualities + Equity (distributions) • Is more better? (Population control.) • Is less better? • How much to spend? 17Intro to Medical Informatics Aggregation • Trend: social aggregation leads to decisions at a larger scale – Multi-specialty providers – Government guarantees and mandates – Risk sharing – Oregon-wide spending “optimization”; – British NHS 19 Changing Context of Health Care • Fee-for-service • HCFA (Health Care Financing Agency) pays for Medicare • Capitation – HMO’s (Health Maintenance Organizations) take overall responsibility to care for patient for fixed fee – Pushing risk down to the physician or group Determining Factors: $£€¥R 21 Exponentially growing expense of health care • More healthcare than steel in GM cars • Increased demand – Much more possible – Better tests, therapies – High human motivation • No pushback • Waste – Unnecessary procedures • ½ of health expenses in last year of life – Marginally useful procedures • Defensive medicine – Bad Medicine Managed Care Controlling Costs and Changing Patient Care IOM, 1989 23 20