SOA at Intermountain Healthcare: New IDEAs and Progress Towards a New Platform SOA in Healthcare July 13, 2011 Stanley M. Huff, MD

Transcription

1 SOA at Intermountain Healthcare: New IDEAs and Progress Towards a New Platform SOA in Healthcare July 13, 2011 Stanley M. Huff, MD Huff # 1

2 Acknowledgements Tom Oniki Joey Coyle Craig Parker Yan Heras Cessily Johnson Roberto Rocha Lee Min Lau Alan James Many, many, others # 2

3 Intermountain Medical Center Women s and Newborn Main Tower Heart and Lung Hospital Cancer Center Outpatient Pavilion

4 Intermountain Healthcare 24 hospitals 2,488 inpatient beds 123,447 Acute admissions 98,674 Ambulatory surgeries 160,306 Homecare visits 502,327 Acute patient days 5,817,392 Outpatient visits 429,949 emergency room visits 38,103 inpatient surgeries

5 Homer Warner and HELP The first version of the HELP (Health Evaluation through Logical Processing) system was built in 1967 From its inception, the HELP system was built primarily to provide advanced decision support Dr. Homer Warner

6 Patient

7 Core Assumptions The complexity of modern medicine exceeds the inherent limitations of the unaided human mind. ~ David M. Eddy, MD, Ph.D.... man is not perfectible. There are limits to man s capabilities as an information processor that assure the occurrence of random errors in his activities. ~ Clement J. McDonald, MD

8 Clinical System Approach Intermountain can only provide the highest quality, lowest cost health care with the use of advanced clinical decision support systems integrated into frontline workflow

9 Adverse Drug Events Total # moderate + severe ADEs Rates today (2008-9) at about 230 per year Generates >$1 million per year in net cost reductions at LDS Hospital alone (3) Year

10 Neo-natal intensive care unit (NICU) admits by weeks gestation Deliveries w/o Complications, n = 8,001 18,988 33,185 19,601 4, Percent NICU admissions Weeks gestation 0

11 Elective inductions < 39 weeks % elective inductions < 39 weeks n = Jan 01 Mar May Jul Sep Nov Jan 02 Mar May Jul Jan 03 Mar May Jul Sep Nov Jan 04 Mar May Jul 0

12 Labor & delivery variable cost Average combined variable cost ($) Expected maternal and fetal combined variable cost Goal: hold increase to no more than 6.85% Actual combined variable cost Jan 2003 Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan 2004 Feb Mar Apr May

13 ARDS evidence in action Defining the best practice clinical protocol Physician compliance ARDS ventilator management: Survival 9.5% 44% ~$120,000 less cost per case!

14 Decision Support Modules Antibiotic Assistant Ventilator weaning ARDS protocols Nosocomial infection monitoring MRSA monitoring and control Prevention of Deep Venous Thrombosis Infectious disease reporting to public health Diabetic care Pre-op antibiotics ICU glucose protocols Ventilator disconnect Infusion pump errors Lab alerts Blood ordering Order sets Patient worksheets Post MI discharge meds

15 Infrastructure Vision Rapid application development environment Dynamic workflow configuration Standard data models and terminology Decision support authoring and execution Knowledge asset management Rules, alerts, protocols, reminders, reports End user preferences Common lists, Hot text Service Oriented Architecture/Enterprise Service Bus Huff # 15

16 Strategic Goals Minimum goal: Be able to share applications, reports, alerts, protocols, and decision support with ALL GE customers Maximum goal: Be able to share applications, reports, alerts, protocols, and decision support with anyone in the WORLD

17 Order Entry API (adapted from Harold Solbrig) Application VA Order Entry Update Medication Order Interface Service Data COS VA Order Services Update PharmacyOrder WHERE ordernumber = 4674 MUMPS Database

18 Order Entry API Different Client, Same Service (adapted from Harold Solbrig) Application Dept of Defense Update Medication Order Interface Service Data COS VA Order Services Update PharmacyOrder WHERE ordernumber = 4674 MUMPS Database

19 Order Entry API Different Server, Same Client (adapted from Harold Solbrig) Application Dept of Defense Update Medication Order Interface Service Data COS GE Services GE Repository Update PharmacyOrder WHERE ordernumber = 4674 Oracle Tables

20 Order Entry API (adapted from Harold Solbrig) Application... Interface COS Service Data

21 What Is Needed to Create a New Paradigm? Standard set of detailed clinical data models coupled with Standard coded terminology Standard API s (Application Programmer Interfaces) for healthcare related services Open sharing of models, coded terms, and API s

22 What are detailed clinical models? Why do we need them? # 22

23 A diagram of a simple clinical model Clinical Element Model for Systolic Blood Pressure SystolicBPObs SystolicBP data 138 mmhg quals BodyLocation BodyLocation data Right Arm PatientPosition PatientPosition data Sitting # 23

24 Need for a standard model A stack of coded items is ambiguous (SNOMED CT) Numbness of right arm and left leg Numbness ( ) Right ( ) Arm ( ) Left ( ) Leg ( ) Numbness of left arm and right leg Numbness ( ) Left ( ) Arm ( ) Right ( ) Leg ( ) # 24

25 What if there is no model? Site #1 Hct, manual: % Hct, auto : % Site #2 Hct : % Manual Auto Estimated # 25

26 HL7 V2.X Messages Site 1: OBX 1 CE ^Hct, manual 37 % OBX 1 CE ^Hct, auto 35 % Site 2: OBX 1 CE ^Hct 37 %. manual OBX 1 CE ^Hct 35 %. auto

27 Model fragment in XML Pre-coordinated representation <observation> <cd> Hct, manual (LOINC ) </cd> <value> 37 % </value> </observation> Post-coordinated (compositional) representation <observation> <cd> Hct (LOINC ) </cd> <qualifier> <cd> Method </cd> <value> Manual </value> <qualifier> <value> 37 % </value> </observation> # 27

28 Relational database implications Patient Identifier Date and Time Observation Type Observation Value Units /4/2005 Hct, manual 37 % /19/2005 Hct, auto 35 % Patient Identifier Date and Time Observation Type Weight type Observation Value Units /4/2005 Hct manual 37 % /19/2005 Hct auto 35 % If the patient s hematocrit is <= 35 then. # 28

29 Isosemantic Models Precoordinated Model HematocritManualModel HematocritManual (LOINC ) data 37 % Post coordinated Model (Storage Model) HematocritModel Hematocrit (LOINC ) data 37 % quals HematocritMethodModel Hematocrit Method data Manual # 29

30 More complicated items: Signs, symptoms Diagnoses Problem list Family History Use of negation No Family Hx of Cancer Description of a heart murmur Description of breath sounds Rales in right and left upper lobes Rales, rhonchi, and egophony in right lower lobe # 30

31 What do we model? All data in the patient s EMR, including: Allergies Problem lists Laboratory results Medication and diagnostic orders Medication administration Physical exam and clinical measurements Signs, symptoms, diagnoses Clinical documents Procedures Family history, medical history and review of symptoms

32 Model Subtypes Created Number of models created Laboratory models 2933 Evaluations 210 Measurements 353 Assertions 143 Procedures 87 Qualifiers, Modifiers, and Components Statuses 26 Date/times 27 Others 400+ # 32

33 How are the models used? Data entry screens, flow sheets, reports, ad hoc queries Basis for application access to clinical data Computer-to-Computer Interfaces Creation of maps from departmental/foreign system models to the standard database model Core data storage services Validation of data as it is stored in the database Decision logic Basis for referencing data in decision support logic Does NOT dictate physical storage strategy

34 Model Source Expression (CDL) model BloodPressurePanel is panel { key code(bloodpressurepanel_key_ecid); statement SystolicBloodPressureMeas systolicbloodpressuremeas optional systolicbloodpressuremeas.methoddevice.conduct(methoddevice) systolicbloodpressuremeas.bodylocationprecoord.conduct(bodylocationprecoord) systolicbloodpressuremeas.bodyposition.conduct(bodyposition) systolicbloodpressuremeas.relativetemporalcontext.conduct(relativetemporalcontext) systolicbloodpressuremeas.subject.conduct(subject) systolicbloodpressuremeas.observed.conduct(observed) systolicbloodpressuremeas.reportedreceived.conduct(reportedreceived) systolicbloodpressuremeas.verified.conduct(verified); statement DiastolicBloodPressureMeas diastolicbloodpressuremeas optional. statement MeanArterialPressureMeas meanarterialpressuremeas optional. qualifier MethodDevice methoddevice optional; md.code.domain(bloodpressuremeasurementdevice_domain_ecid); qualifier BodyLocationPrecoord bodylocationprecoord optional; blp.code.domain(bloodpressurebodylocationprecoord_domain_ecid); modifier Subject subject optional; } attribution Observed observed optional; attribution ReportedReceived reportedreceived optional; attribution Verified verified optional; # 34

35 So that is the vision of the future, what is happening right now? Huff # 35

36 Misys Lab GE/AGFA Radiology Tamtron Anatomic Pathology McKesson Pharmacy ARUP Blood Bank Blood Gas Machines Dictaphone Varis Oncology MRS Mammography GE/Logicare ER Computrition Dietary HELP Database ADT, Orders, Results, Billing HELP (Inpatient HIS) 3M ADT, Orders, Results, Billing egate Interface Engine Sun Registration, Scheduling ADT, Results, Orders Registration, Scheduling Care Flow (Outpatient) GEHC ADT, Billing ADT, Billing, Case Mix HDM & Medrec 3M Health Data Dictionary 3M Billing & Financial IHC Clinical Workstation 3M HELP 2 CD IHC Tuxedo CDR Database (HEMS) 3M DataStage Data Warehouse IHC

37 Application Explosion applications in the organization Applications being purchased or built include approximately 80% redundancy of functionality Data Explosion All new applications require duplication of data One example of data duplication 49 copies of patient registration data 294 million patient records online 288 million or 97% are duplicate copies 125,000 registration updates/day or 6.1 million total data updates daily

38 Information Delivery Enterprise Architecture

39 IDEA Governance Structure RESPONSIBILITES Provides strategic oversight and guidance for IDEA Empowers IDEA subcommittee to specifying standards, practices, guidelines and tools Approval of IDEA subcommittee proposals Monitors and is accountable for adherence to approved standards, practices, guidelines and tools EARB Chair: Chief Technology Officer IDEA GOVERNANCE IDEA Subcommittee Chair: Enterprise Software Architect MEMBERS PMO, HELP1, HELP2, Migration, Financial, Tactical, ebusiness, Clinical Operations, Interfaces, EDW, ECIS, Informatics, Security, Select Health, Operations, RIM, KTMI, HWCIR Fostering Excellence Workgroup Exception Handling Workgroup Auditing Workgroup Security Architecture Subcommittee Desktop Subcommittee RESPONSIBILITES Database Architecture Subcommittee Establish the Information Delivery Enterprise Architecture by specifying standards, practices, and guidelines and tools Build consensus and document software standards, processes, tools, and infrastructure to be approved by IDEA Governance Provides stewardship for respective teams Brings forth gaps, issues and solutions for IDEA

40 A Picture

41 Something More Concise Intermountain Application New 3 rd Party Application IDEA Enterprise Service Bus Intermountain Central Data Rep New 3 rd Party Data Repository

42 Nursing Medication Charting workflow

43 Physician Note Writing workflow

44 Clinician Data Review workflow

45 Potential Benefits Low risk Incremental changes - no big bang changes Gradual implementation of ESB Transition based on particular modules Results review, text documents, allergies, documentation, order entry Slowly increasing use of the new database Opportunity to tune performance Huff # 45

46 Questions? Huff # 46