Pioneering Decision Services with Decision Modeling at Kaiser Permanente

Transcription

1 Pioneering Decision Services with Decision Modeling at Kaiser Permanente Building Business Capability BBC - Las Vegas 2016 David Herring - BPM & ODM Delivery Manager- Kaiser Permanente James Taylor CEO, Decision Management Solutions 1

2 Your Presenters James Taylor CEO, Decision Management Solutions I have spent the last 14 years focused on Business Rules, Analytics and Decision Management Published author, consultant, speaker David Herring Leads the Process Transformation and Decision Management Program at Kaiser Permanente Believes in developing innovative techniques that rapidly enhance healthcare applications without disrupting them Holds a Msc from Heriot- Watt University, Edinburgh in Digital Systems & AI 2

3 Agenda About Kaiser Permanente Decision Management Decision Model and Notation Decision Modeling in Context Decision Management at KP Methodology in Practice Iterative Business-Centric Development One Decision, Many Documents Avoiding Overfitting Summary and Conclusions Q&A 3

4 About Kaiser Permanente 4

5 Kaiser Permanente Integrated Northwest 10.6 million members 17,000+ physicians Northern California Colorado Mid-Atlantic 49,000+ nurses 192,000+ employees Southern Cal ifornia 8 States + District of Columbia Georgia 38 hospitals Hawaii 600+ medical offices $53 billion operating revenue Nation s largest not-for-profit health plan Scope includes ambulatory, inpatient, ACS, behavioral health, SNF, home health, hospice, pharmacy, imaging, laboratory, optical, dental, and insurance 5

6 Our Decision Management Journey SOA Infrastructure Enterprise Service Bus, Message Broker, WSRR, Web Services, APIs, ITCAM, DataPower, WAS Real Time In-Context Decision Management Operational Decision Automation, Tactical Decision Support, Rules using Location and Time Dimensions Predictive Analytics Predict Trends, Recognise Patterns, Manage Risk, Forecast Outcomes, Strategic Decisions Based on Evidence Business Process Management Task Orchestration, Message Notification, Document Generation, & WS integration Complex Event Processing Design and Develop a Robust Event-Centric Enterprise Capable of invoking Business Rules and integration with the IoT 6

7 Our Decision Management Journey 2 Billion messages per month 500 Enterprise Web Services Decision Management Performance Dashboards Analytics Tools Business Process Management Event Platform Landing Zone Other Data Sources Events SOA Messaging Bus Pharmacy Kp.org Mobile apps Membership Medical Devices Claims Other systems EPIC 7

8 Decision Management and Decision Modeling 8

9 A Decision Management Approach Relies On Decision #decisionmgt 2016 Decision Management Solutions 9

10 A Decision Model Shows Decision Requirements Decision Precise Decision Structure Knowledge #decisionmgt 2016 Decision Management Solutions 10

11 A Decision Model Puts Decisions In Context Process Motivation Organ izatio n Depar tment Team Role Depar tment Team Role Organization Loan Appliation 0.* -applicant -amount : Money -amountlimit : Money 1 -facilitytype : Enum -guarantor -id : String -repaymentby : Date -status : Enum 1.* 0. 1 Person -address : String -creditrtng : Enum -dateofbirth : Date -disqualified : Boolean -disqualificationreason : String -firstname : String -id : String -middleinitials : String -proofofidseenby : StaffId -surname : String -telephone : TelephoneNo Decision Pre-bureau risk category table UC Existing Customer Application Risk Score Pre-Bureau Risk Category 1 < 100 HIGH 2 [ [ MEDIUM 3 [ ] LOW 4 TRUE > 130 VERY LOW 5 < 80 DECLINE 6 [80..90] HIGH 7 [ ] MEDIUM 8 FALSE > 110 LOW 1 1 Financial Profile -annualincome : Money -employmentrecord : Enum -personaldebt : Integer * 0.* Employment AssetLiability -enddate : Date -realisationdate : Date -salary : Money -type : Enum -startdate : Date -value : Money -terminationreason : Enum -worktype : Enum #decisionmgt 2016 Decision Management Solutions 11

12 A Decision Model Includes Two Layers of Detail Decision Requirements Decision Logic Pre-bureau risk category table UC Existing Customer Application Risk Score Pre-Bureau Risk Category 1 < 100 HIGH 2 [ [ MEDIUM 3 [ ] LOW 4 TRUE > 130 VERY LOW 5 < 80 DECLINE 6 [80..90] HIGH 7 [ ] MEDIUM 8 FALSE > 110 LOW Or Business Rules In A #decisionmgt 2016 Decision Management Solutions 12

13 A Standard For Decision Models: Decision Model and Notation (DMN) Open Industry Standard Broad Vendor Support Decision Management Solutions, FICO, IBM, Oracle, TIBCO and others Object Management Group BPMN, UML and many other established standards provide a common notation that is readily understandable by all business users... DMN creates a standardized bridge for the gap between the business decision design and decision #decisionmgt 2016 Decision Management Solutions 13

14 Many Use Cases Human Decision-making Documenting human decision-making Improving human decision-making with analytics Training human decision-makers Requirements for automated Decision-making Business rules discovery and analysis Framing predictive analytics Dashboard design Implementing automated Decision-making Completely specifying business rules Acting as a BRMS front-end Orchestrating complex decisioning #decisionmgt 2016 Decision Management Solutions 14

15 Decision Modeling Lifecycle Decision Requirements Automation Boundary Traceability Orchestration Technology Selection Business Rules Predictive Analytics Implementation Decision Modeling Drives requirements and automation Supports business rules and analytic implementations Delivers traceability Allows for ongoing #decisionmgt 2016 Decision Management Solutions 15

16 Applying The Approach At Kaiser Permanente The Heart Failure Project 16

17 Heart Failure Project Determine Survival Rate Kaiser cardiologists have a need for a system to evaluate patients, using a simple set of conditions, to determine if patient needs to be referred to a heart failure specialist. 17

18 Methodology in Practice Model & Identify Suitable Decision for ODM Discovery Workshop Determine Survival Rate Transform Decision Models into Decision Tables Deploy Decision Tables to Operational Decision Manager ODM 18

19 Methodology in Practice - Discovery Discovery Workshop Discover & Identify Decisions: Brainstorming, Business Processes, KPI, Business Events, Legacy Systems Map Decisions to KPI and Business Objectives Understand Role of Decision in business processes and in responding to business events 19

20 Methodology in Practice - Modeling Identify and Model Suitable Decision Model the decision & requirements using DecisionsFirst Modeler Refine a decision through decomposition into more granular, reusable decisions 20

21 Methodology in Practice - Design Determine Survival Rate Decision Table Design Use Modeling Principles to Normalize Rules Represent business rules with structured format Easy to Read & Interpret Simple to Manage Determine Risk Score 21

22 Methodology in Practice - Deployment ODM Decision Deployment Decision Tables implemented as Business Rules in IBM Operational Decision Manager ODM Decision Service Decision Logic 22

23 Iterative Business-Centric Development 23

24 An Initial High Level Model 24

25 A Detailed Clinical Model 25

26 Model and Deploy Iteratively Build high level models Model a decision in detail Document decision logic #decisionmgt 2016 Decision Management Solutions 26

27 One Decision Many Documents 27

28 Problems With Clinical Guidelines Clinical Document Guidelines Information Overload Author not a practicing specialist Specificity Varies Implementation Varies Regional Variation Rarely Change Not Connected to SMEs Difficult to Maintain 28

29 National Guideline Clinical Guide 29

30 National Guideline Summary 30

31 Heart Failure Toolkit 31

32 A New Approach Studies & Research Studies & Research Evidence Based Guidelines Additional Toolkits Decision Model National Library National Library Decision Services Technical Designs Regional Implementations Technical Designs Regional Implementations Shared #decisionmgt 2016 Decision Management Solutions 32

33 Advantages Of New Approach Clinical Decision Services Extendable Shared Services Clinical Support Applications Modular Decision Logic Avoids the need to eyeball complex docs in real time 33

34 Avoiding Overfitting 34

35 Avoiding Noise and Overfitting Patient Hemodynamic Status Not all decision outcomes need to be granular Real Time Decisions requiring expert judgment fit into this category Patient Hemodynamic Status is a Sub-Decision in Vasodilator Decision Model Requires a physician to physically examine a patient Outcomes break into 2 categories: (Wet or Dry), (Warm or Cold) Temptation to add additional categorization (like a 1-12 scale) Example of Overfitting, counter-productive and creates noise 35

36 Manage Automation Boundaries Develop a decision model Identify scope of automation Feeder decisions Automated Overridable #decisionmgt 2016 Decision Management Solutions 36

37 Summary Conclusions and Recommendations Decision Modeling Workshops Engage Business Owners Reveal Automation Boundaries Integrate Multiple Perspectives and Documents Decision Modeling Supports Iterative Development Focuses BRMS Development Avoids Overfitting Decision Services Improve Processes Supports SOA Best Practices 37

38 Questions? 38

39 Contact Us David Herring James Taylor decisionmanagementsolutions.com Come by the bookstore! 39