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From the Health IT Leadership Summit

From the Health IT Leadership Summit

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    Mark Dente's Presentation Mark Dente's Presentation Presentation Transcript

    • The virtualization of the bricks and mortar of the Healthcare delivery setting: The impact and direction of Healthcare ITMark A Dente, mdCMIO 1/GE Healthcare IT e-Infrastructure for the Future of Diagnostics 4 November 2011
    • The virtualization of the bricks and mortar of theHealthcare delivery setting:• Digitation & Connectivity of Data: Accessing and integrating information from multiple sources• Advanced Data Processing & Information Fusion: Turning “Insight” into Action• THE FUTURE is sooner than you think: Empower every person to live an independent, confident, healthier life through connected technologies
    • Healthcare Challenges: Improve Outcomes &Avoid or Reduce Cost• Meaningful Use & Quality Metrics - Clinical Decision Support• New delivery Models like ACO’s - Patient and Population Health Mgmnt• Shift care to lower cost settings - Chronic Disease Mgmnt & Remote Monitoring• Early identification of at-risk individuals - Genomics Personalized therapy selection & Better therapy monitoring (Surveillance Monitoring) 3/ e-Infrastructure for the Future of Diagnostics 4 November 2011
    • The Clinical Knowledge-Processing Burden“Current medicalpractice reliesheavily on the Knowledge processing requirementunaided mind torecall a greatamount of detailedknowledge – aprocess which, to This gapthe detriment of all injures patientsstakeholders, hasrepeatedly been Knowledge processing capacityshown unreliable”Crane and RaymondThe Permanente JournalWinter 2003 Volume 7 No.1Kaiser Permanente Institute forHealth Policy Many years ago Today 4/ e-Infrastructure for the Future of Diagnostics 4 November 2011
    • ‘The complexity of modern medicine exceeds theinherent limitations of the unaided human mind.’David M. EddyMD, Ph.D. Patient 5/ e-Infrastructure for the Future of Diagnostics 4 November 2011
    • Meaningful use criteria reinforcing the need forthe Patient Centered Care Team Care • Exchange key clinical information electronically Document exchange of meds, problems, allergies, labs, etc. • Perform medication reconciliation for 80% of encounters Coordination • Provide summary care record for 80% of care transitions w/discharge summary Portals for provider access Document exchange of meds, Engage • Provide patients w/electronic copy of health information • Provide timely electronic access w/in 96 hours problems, allergies, labs, etc. w/discharge summary Patients • Provide clinical summaries for each office visit Portals for patient access Improve • Leverage clinical decision support & interaction checking • Send reminders to patients, outreach, reduce disparities Decision support based on HIE Alerting & secure messaging Quality • Report ambulatory measures to CMS or states Quality reporting • Protect electronic health information through technology Highest security standards Privacy • Review security risks and implement security updates Audit trail of all HIE accesses Document submission to state • Submit electronic data to immunization registries registries • Electronically submit reportable lab results Public Health • Provide syndromic surveillance data to public agencies Quality reporting 6/ e-Infrastructure for the Future of Diagnostics 4 November 2011
    • The virtualization of the bricks and mortar of theHealthcare delivery setting:• Digitation & Connectivity of Data: Accessing and integrating information from multiple sources
    • Data InteroperabilityWhy is it important?• Real-time access to relevant clinical intelligence across the community• Improve quality & coordination of care with. Government• Prepare organizations for advanced stages of Meaningful Use and an Accountable Care model.eHealth offers:• eHealth Info Exchange• eHealth Community Desk• Centricity Patient Online• eHealth Image Exchange 8/ e-Infrastructure for the Future of Diagnostics 4 November 2011
    • Population Health Management & Community ofCare Network Hospital Community Health Center Group Care Granular Care / Case Network & Portal Information Managers Practices Communication Exchange Applications Surveillance eReferrals Services Population Mgmt / Information Analytics PATIENT Reconciliation Decision Support / Patient Image Event Alerts Exchange Care Registries Management (disease, vax) Medical Home Other HIE Family 9/ e-Infrastructure for the Future of Diagnostics 4 November 2011
    • eHealth Community DesktopA web-based clinical portal that enables collaborative careacross a community of clinicians without EMRs Widen community access with an easy, browser-based user interface Enable care teams, including case managers, to facilitate care coordination Bring various in-house applications together in one place Extend your HIE investment over time with add-on workflow and performance apps Increase HIE use with flexible screen layouts to match your look-and-feel 10 / e-Infrastructure for the Future of Diagnostics 4 November 2011
    • Patient Engagement – Centricity PT online Patient Online is a single channel of communications that extends the provider workflow to the patient’s home to reduce costs, increase quality, and increase access to care. Strengthens the HCO’s market/competitive position Improves efficiency of the patient management process Strengthens the patient- provider relationship Extends the HCO’s reach for proactive care management Enables HCO’s to meet all ARRA criteria for patient & family engagement 11 / e-Infrastructure for the Future of Diagnostics 4 November 2011
    • Community DesktopImage Exchange 12 / e-Infrastructure for the Future of Diagnostics 4 November 2011
    • The virtualization of the bricks and mortar of theHealthcare delivery setting:• Advanced Data Processing & Information Fusion: Turning “Insight” into Action
    • + + MayoKey Partners:Intermountain HealthcareMayo - RochesterHolistic approach 14 / e-Infrastructure for the Future of Diagnostics 4 November 2011
    • Holistic approach to DataKnowledge Workers Knowledge Repository Maps Models Codes Rules Constraints Queries Forms HL7 XDS ATNA Interface Manager PIX 1 Interface (e.g. Terminology Unified Data Applications PDQ HL7) to Model Translation, Repository of Assembled from Transforms Decision Models & User Generated CDA Support & Business Rules Terminology Based Data Alerts, Queries and Forms 2 3 4 5 Standard Models & Coded, Computable Configured by Shareable & 15 / Terminology Clinical Data Knowledge Workers e-Infrastructure for Assets of Diagnostics Reusable the Future 4 November 2011
    • Transforming data into insight: Advancedprocessing & Information fusionClinical Data Fusion: Qualibria Terminology Services The Terminology Foundation contains services and rich management tools for code mapping, browsing and querying: •Loadexternal code systems, including: SNOMED-CT, LOINC, ICD-9, ICD-10, CPT, RxNorm, HL7 Vocabularies, HCPCS, Genomics Ontologies, NCI Metathesaurus, Open Biomedical Ontologies, etc.Many entry forms forone concept• myocardial infarction• MI• S/P MI 1987• hx of heart attacks4500 Elemental termsavailable today 16 / e-Infrastructure for the Future of Diagnostics 4 November 2011
    • Value Created by Cardiology Program Defining the best practice clinical protocol • Impact of Discharge Med Program on Heart Failure Readmissions/Mortality • ACE inhibitor prescription at hospital discharge increased from 65% to 95% in 5 years • How did these Intermountain heart failure patients do? • One-year readmissions reduced from 46.5 % to 38.5% • 551 readmissions prevented per year • $2,480,000 saved based on avoided readmissions • One-year mortality rate reduced fromDr. Don Lappe 22.7% to 17.8%Chair, Cardiology • 331 lives saved per year • Quality is cheaper, safer, better all around ! 17 / e-Infrastructure for the Future of Diagnostics 4 November 2011
    • Acute Care Program demonstrated Proof ofVentilator Weaning Protocol Effectiveness • Acute Respiratory Distress Dr. Alan Morris, LDS Hospital Syndrome (ARDS) survival rate used to be <10% • Intermountain physicians created a software based protocol to help patients wean from the ventilators faster • Patients weaned a full 24 hoursOutcome Physician Protocol earlier than before fromMedian Weaning Time 28 8(hrs) ventilatorTime on Ventilator (hrs) 118 94 • Acute Respiratory DistressBlood Gas Orders 93 45 Syndrome survival rateChest X-Ray Orders 12 3 increased from 10% to over 44% 18 / e-Infrastructure for the Future of Diagnostics 4 November 2011
    • Healthcare associated infections: Qualibria Annual U.S. cost of healthcare associated infections 1.7 million occurrences A 250-bed $35 billion hospital… 99,000 lives 473 occurrences $11 million 27 lives Annual Cost in Lives by Cause (US) 124,583 $9 $8 US 99,000 $635.0 Per capita HC exp. (000) $7 Japan 72,449 $6 Germany 56,326 $5 40,598 $4 UK 29,093 $3 Spain $2 $1 China Prostate Breast Influenza Diabetes Healthcare Chronic $- cancer cancer associated lower 0% 5% 10% 15% Brazil infections respiratory diseases Healthcare infection rate For GE internal use only. Not for external distribution 19 / e-Infrastructure for the Future of Diagnostics 4 November 2011
    • • Disseminate best practices• Increase adherence to protocols• Decrease time on ventilator• Improve medication utilization• Reduce length of stay• Decrease patient costsGE internal use only. Not for external distribution For 20 / e-Infrastructure for the Future of Diagnostics 4 November 2011
    • 21 /e-Infrastructure for the Future of Diagnostics 4 November 2011
    • 22 /e-Infrastructure for the Future of Diagnostics 4 November 2011
    • Real-time best practice dashboard 23 / e-Infrastructure for the Future of Diagnostics 4 November 2011
    • The virtualization of the bricks and mortar of theHealthcare delivery setting:• THE FUTURE is sooner than you think: Empower every person to live an independent, confident, healthier life through connected technologies
    • Achieving Patient & Population HealthManagement ProactiveInteroperability Collaboration Analytics Accountability Population Management Cost & One Patient, Communication Population Care Utilization One Record & Transparency Stratification Management Management Resource Health Workflow Care Predictive Management & Maintenance & Integration Transitions Modeling Productivity Wellness Guideline & Actionable & Patient Evolving Care Gaps in Care StandardsUsable Systems Activation Plan Driven Longitudinal 25 / e-Infrastructure for the Future of Diagnostics 4 November 2011
    • e Health - Beyond HIE Information Exchange Care Management targets the sickest-of-the-sick (5% of US pop = 49% of cost) Hospital Community HealthPopulation Health CenterManagement &Community of Care Care / Case Group GranularCare Network Practices Network & Communication Portal Information Exchange Managers Applications Surveillance eReferrals ServicesGeisinger Health Plan Geisinger’s Proven Population Mgmt / Information Reconciliation Health & ProvenCare Analytics• Preventative care bundle Patient Decision Support / Image 9.2 14.7% Event Alerts Exchange• Aligns incentives across Care Registries provider, patient and payer Management Medical (disease, vax)• 18 % admission, 36% Home Other HIE readmissions Family 26 / e-Infrastructure for the Future of Diagnostics 4 November 2011
    • The Medical Quality Improvement Consortium (MQIC)MQIC is a continuously updated database of 20 million unique, de-identifiedpatients – aimed at helping identify and inform industry best practices • Make data-driven decisions at the point of care • Enhance management of specific conditions and populations • Benchmark against similar practices for quality of care information • Participate more easily in PQRS, CMS eRx, and Bridges to Excellence Diabetes Recognition 27 / e-Infrastructure for the Future of Diagnostics 4 November 2011
    • Chronic Disease ExampleAnomaly detection and guidelines decision support Personalized weight gain detection algorithms Moving Averages Example 230 70 220 60 210 50 weight 200 40 short-term ave long-term ave 190 30 difference 180 20 Search f or best l ong-t erm window and cut off 170 10 Alert limit 9 0.0% 160 0 8 0.0% Stable fit 7 0.0% 150 -10 6 0.0% sea rch 5 0.0% T ru e Base lne i Only 2 day s war ning Pro spects 140 -20 4 0.0% 3 0.0% on e v nt # 2 e New winner 8/11 9/30 11/19 1/8 2/27 4/18 2 0.0% 1 0.0% 0.0% 0 .0% 0 .5% 1.0% 1.5% 2.0% 2.5% 3.0% F alse Scale Precision Accuracy Compliance e Effe ct of Patient Complianc Effect of scale precision E ffect of Measurement Accuracy 70% 5% 70% 5% 80% 5% 60% 60% 70% 4% 4% 4% 50% 50% 60% Fal se Alert % Fal se alert % Fal se Alert % T rue alert % True alert % True al ert % 3% 3% 50% 3% 40% 40% TRUE TRUE TR UE 40% FALSE 30% 30% FA LSE 2% FALS E 2% 30% 2% 20% 20% 1% 20% 1% 1% 10% 10% 10% 0% 0% 0% 0% 0% 0% 0 1 2 3 0 1 2 3 50% 60% 70% 80% 90% 100% S ca le Preci si on Extra noi se in readi ngs (un it=1lb stdev) Comp li can ce: % days wei ght record ed Home Health Data Detection Algorithms Chronic Disease Monitoring Beta Blockers Application BB:br adycardia Taking bet a blocker? [21] no yes [38,53] input codes Br adycardia? 2 n d o 3 rd r BB:titrat ion (pulse < 60) de g e heart re block? (E KG) [82] [43] Pulse > 60? Br adycar dia? Pat i nt n ds e ee [43] (pulse < 50) imme di te a te ntio a t n. [43] Discont i u be ta ne blocke and othe r r Lower than Bradycar dia? dr u that may cause gs (pulse < 55) target dose? he tblock (di oxin, ar g and CCB, sotal l, o [21] upt it rat ing amiodarone ) BB:fatigue on BB? BB:HFsymptoms [21,43] Consi er cardiol gy d o r e fer ral (pac mak r ). e e Highe r dose alr e ady tr ie d? Possibl to e BB:he artblock Wit hin 2 w e eks S e ve re fat igue ? [21] de cre as ot h r e e aft er BB (act ivit y-r e late d Or de r E KG medst ha may t initiat ion / que stions) cause upt it rat ion? 4 we e ks si ce n for he ar t rhyt hm. bradycar di ?a [64] last tr y and OK Pe r for m (digoxi , CCB, n [21] t o re - ry (not t TS H/digoxin labs . sot al l, o pr e vi usly o amiod arone ) BB:l ungpatient de cre as d or e [25] discon inued t Fatigue for dyspne in a Dyspnea in l ng u lung patie )? nt laste d pat i n wi hi 2 e t t n F luid [21] daysafte r B B ret o n? enti for ove r 6 Consi er d S ymptoms of initiat ion? we e ks? br adycar di ? a [64] de cre asi g no n n- [21,66,84] 1-4 we e ks HFme dstha t (Dizzine ss? may cause Lighthead d- e passe d since bradycar di a ne ss? Fatigu ?) e last [60,62,64] incre ase ? Conside r discontinuing BB. [21] Conside r Conside r de cr easing incr easing be ta blocke r. Pulse < Conside r swit ching diure t ic(s). 45? t o cardiac-se lect ive Conside r ot he r Conside r [43] BB. Conside r sour ces of fat igue incr e asing be ta de cr e asing be ta (thyroid, de pre ssion, blocke r. Conside r de cre asing or discont inuing BB. Conside r blocke r s. wor se ning HF, sle e p Consi e small r dr e Pe rform TS H/ digoxin labs. spir ome tr y. apnea, ane mia) incre m ents ift his is Conside r car diology re fe rr al a re-try. (pace make r). GE Confi dential & Proprietary Electrolytes Medical Guidelines Medical Records Advanced Data: Activity 28 / e-Infrastructure for the Future of Diagnostics 4 November 2011
    • Physician to the Patient Chronic Dx ManagementApproach Tiny Sensors pick up activity data in the residence and Basic Package send to GE Server The Algorithm knows if the activity is “normal” – if not, Intelligent software: an alert is created Z-wave technology alerts, algorithms, etc. and sent to caregiver Benefits • Peace of Mind for Family • Customizable Alerts • Delay of Continued Care/Skilled Nursing • Extended Care The Well Check is Coverage without Made and the loop is additional staff Closed • Attraction/Retention of residents Patient Level Tools for the Care Team 29 / e-Infrastructure for the Future of Diagnostics 4 November 2011
    • Technology EnablersHealthcare Desires Technology Enablers• Flexibility – systems for full acuity range; • Miniaturization equipment stays with patient (Nano, MEMS, EE, RF, CMUT)• Efficiency – productivity and improved • Sensors/Parameters quality/reduced errors (Fusion, Implants, New Types)• Home/Remote Monitoring – also disruptive • Wireless Technologies to Hospital Monitoring (Reliability, Capacity, Power)• Wearable – “Don’t know it’s there” • Expert Systems (Intelligence, Decisions, CAD)• Tracking – Patients, Parameters, Assets, Employees • Info/Data/Apps Architecture (Workflow, Integration, Apps)• Extremely Wireless – Zero Wires • Use/Human Factors• New Sensors /Parameters /Disease States (Goof Proof, Ease of Use) 30 / e-Infrastructure for the Future of Diagnostics 4 November 2011
    • Home Health ActivityHeart Failure • Actigraphy sensors • Correlated to HF status healthy • 60 person field trial • Columbia University Activity as a Vital SignFall Risk Assessment Sleep disorder • Research effort • “Automate” PT instruments • Daily assessments • University of Mo. – ColumbiaPrevent Falls Thru Identification Dementia the Future of Diagnostics/ 31 e-Infrastructure for 4 November 2011
    • GE HCIT: Chronic Dx, Social Networking & Consumerism Solving disparity of care challengesEnterprise Direct To ConsumerCorporate Stakeholders: Pharma, Employers Existing NBC health• EMR based intervention studies enables outcomes driven ecosystem brand/marketing strategies enables broad & localized Consumer reach Model is proven, enables our ability to extend SHARED to adjacent stakeholders INFRASTRUCTURE [CDS + Clinical HIE + Consumer Decision Support + Motivation] HEALTH-WEALTH IMPACTeHealth Health@HomePhysicians, Hospitals, IDNs, RHIOs• Leverages the richness of the physician to patient interaction; Connects HCIT within the home enables longitudinal approach to care to enable care and communicate w/ patient/family members Health information Disease management tools POL POL is an existing building block to access Centricity IB 32 / Physicians & patients e-Infrastructure for the Future of Diagnostics 4 November 2011
    • The Dundee Courier, 13th April, 2007 33 / e-Infrastructure for the Future of Diagnostics 4 November 2011
    • 34 /e-Infrastructure for the Future of Diagnostics 4 November 2011
    • 35 /e-Infrastructure for the Future of Diagnostics 4 November 2011
    • Many diseases have an underlying geneticconnection 36 / Detail of Gene - Disease Network e-Infrastructure for the Future of Diagnostics Goh et al. PNAS4 104 (2007) November 2011
    • Alzheimer’s Clinical Data AD BioSignaturePrognostic Modeling Rate of Cognitive Time To Survival/Progression Decline Progression/Death Probability • Early diagnosis • Personalized treatment • Therapy monitoring AD Prognostic Model ClinicalIn-vivo Imaging InformaticsPET, MRi, SPECT APOE4 (>0) Cognitive %Supra. CNS (+) Intracranial Genetics Clinical %Supra. CNS(-) %Ventricular (-) IVD, Genetics, circulating markers %Ventricular (-) %Subar. CSF Team of 10+ research scientists %TemporalCSF (-) %Subar. Lobe (+) committed in 2011 Algorithms, statistics, informatics %Total HSIA (-) %Temporal Lobe %Hippocampal(-) %Total HSIA (+) Adak, Illouz, Gorman, Tandon, Zimmerman, Guariglia, Moore, Kaye, “Predicting the rate of cognitive decline in %Hippocampal aging and early Alzheimer disease”, Neurology. 2004 Jul 37 / 13;63(1):108-14. e-Infrastructure for the Future of Diagnostics 4 November 2011
    • July 4th Boston: USS Constitution (Old Iron Sides) Thank you mark.dente@ge.com 38 / e-Infrastructure for the Future of Diagnostics 4 November 2011