Build vs. Buy a Healthcare Enterprise Data Warehouse: Which is Best for You?

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Debating between building vs. buying your organization’s healthcare data warehouse? This presentation will explore the technical and organizational pros and cons of building vs. buying, as well as a third approach you may not have even considered.

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Build vs. Buy a Healthcare Enterprise Data Warehouse: Which is Best for You?

  1. 1. © 2013 Health Catalyst Prop©rie2t0a1ry3 aHnedalCthonCfaidtaelnytsiat l Proprwiewtawr.yheaanldthCcaotnafliydsetn.ctoiaml Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics Enterprise Data Warehousing in Healthcare Build vs Buy considerations www.healthcatalyst.com
  2. 2. Context for this topic Assess Design Implement Test Deploy “Do we have the tools to use data to transform care delivery and streamline operations?” “Assessment of our current state indicates we need a different future state. What should that look like?” “Key to our future state will be an Enterprise Data Warehouse (EDW) to integrate data from multiple sources and facilitate Triple Aim reporting. Make it so.” “We will test our EDW to ensure it is meeting our expectations.” “We will roll out our EDW and analytic applications to a broad group of users, including clinicians, leaders, and administrators.” Decision Should we build this EDW from scratch, or partner with a vendor to deliver this capability for the organization. Are those my only options? 1 © 2013 Health Catalyst Proprietary and Confidential www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 2
  3. 3. Agenda © 2013 Health Catalyst Proprietary and Confidential www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 3 ● Examine the options – Building an EDW – Buying an EDW – Hybrid solution ● Other Considerations ● About Health Catalyst ● Questions
  4. 4. Poll Question © 2013 Health Catalyst Prop©rie2t0a1ry3 aHnedalCthonCfaidtaelnytsiat l Proprwiewtawr.yheaanldthCcaotnafliydsetn.ctoiaml www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 4
  5. 5. Building an EDW © 2013 Health Catalyst Prop©rie2t0a1ry3 aHnedalCthonCfaidtaelnytsiat l Proprwiewtawr.yheaanldthCcaotnafliydsetn.ctoiaml www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 5
  6. 6. What is an EDW? Metadata, Security, and Auditing Common, Linkable Identifiers Financial SourceMarts Administrative SourceMarts Departmental SourceMarts Patient SourceMarts EMR SourceMarts HR SourceMart Hospital Operations Primary Care Asthma FINANCIALSOURCES (e.g. EPSi, Peoplesoft, Lawson) ADMINISTRATIVE SOURCES (e.g. API Time Tracking) EMR SOURCE (e.g. Epic, Cerner) DEPARTMENTAL SOURCES (e.g. Apollo) PATIENTSATISFACTION SOURCES (e.g. NRC Picker, Press Ganey) Human Resources (e.g. PeopleSoft) © 2013 Health Catalyst Proprietary and Confidential www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 6
  7. 7. Why choose to build an EDW? Benefits of a data warehouse: ● Performance ● Integration ● Ease of use Historically ● Dearth of proven solutions for healthcare ● Pioneers had to demonstrate value prior to funding © 2013 Health Catalyst Proprietary and Confidential www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 7
  8. 8. Considerations: building an EDW © 2013 Health Catalyst Proprietary and Confidential www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 8 Worst case scenario: project failure ● 50% of data warehouse projects fail Common among unsuccessful EDW builds: ● A solid business imperative is missing ● Executive sponsorship and engagement is missing ● Frontline users are not involved from start to finish Ongoing success is elusive ● Most healthcare IT groups not prepared to function like a software company ● Limited opportunities to learn lessons before funding is cut
  9. 9. Pros/Cons: Building an EDW © 2013 Health Catalyst Proprietary and Confidential www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 9 Pros ● Building it yourself means infinite customization ● Getting “something” built yourself may be “good enough” (for now) ● Pride of authorship Cons ● Staffing ● Shortage of qualified resources ● Re-learning lessons ● “Skunkworks” projects can be culturally divisive ● Project management challenges
  10. 10. © 2013 Health Catalyst Prop©rie2t0a1ry3 aHnedalCthonCfaidtaelnytsiat lFollow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics Buying an EDW Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics Proprwiewtawr.yheaanldthCcaotnafliydsetn.ctoiaml www.healthcatalyst.com 10
  11. 11. Why might someone buy an EDW? © 2013 Health Catalyst Proprietary and Confidential www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 11 Developing well-engineered, custom software may not be your core competency Market offerings for healthcare data warehousing solutions are better than 10 years ago Support and maintenance agreement help ensure long term success
  12. 12. Considerations: Buying an EDW © 2013 Health Catalyst Proprietary and Confidential www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 12 Many of the same risks with any vendor relationship Evaluating an analytics vendor ● Completeness of vision ● Culture and values ● Total cost ● Ability to execute – Where else have they had success? – Will their approach work for my organization? – Do they have expert resources? More information: ● How to evaluate a clinical analytics vendor
  13. 13. Pros/Cons: Buying an EDW © 2013 Health Catalyst Proprietary and Confidential www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 13 Pros ● Shortest time to value ● Real world experience: what works best in practice ● An infusion of help ● Lower total cost of ownership Cons ● Initial cost ● Knowledge transfer ● Tradeoff between “perfect” and “extremely good”
  14. 14. Poll Question © 2013 Health Catalyst Prop©rie2t0a1ry3 aHnedalCthonCfaidtaelnytsiat l Proprwiewtawr.yheaanldthCcaotnafliydsetn.ctoiaml www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 14
  15. 15. Hybrid Build and Buy © 2013 Health Catalyst Prop©rie2t0a1ry3 aHnedalCthonCfaidtaelnytsiat l Proprwiewtawr.yheaanldthCcaotnafliydsetn.ctoiaml www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 15
  16. 16. Buying AND Building an EDW © 2013 Health Catalyst Proprietary and Confidential www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 16 In practice, more like “Buy and Extend” ● Leverage a vendor partner for some components ● Develop, using internal resources, others Examples: ● Select a vendor to: – Implement the data warehouse – Integrate several high priority data sources ● Leverage internal resources to: – Integrate additional data sources – Develop additional analytic applications – Integrate data from the warehouse into operational processes
  17. 17. Why choose to build AND buy? © 2013 Health Catalyst Proprietary and Confidential www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 17 Best of both worlds ● Rapid implementation ● As customizable as a purely “build” solution ● Higher potential for return on investment Mitigates risk ● Benefit from the lessons your vendor has learned ● Infusion of resources to help deploy and train
  18. 18. Other considerations © 2013 Health Catalyst Proprietary and Confidential www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 18 Potential pitfalls for any data warehouse project ● “Boil-the-ocean syndrome” ● Seeking governance “perfection” ● Rigid architecture Insights ● Original article ● Comparing data warehouse architectures for Healthcare Other Resources ● Healthcare Data WarehousingAssociation (HDWA) ● The Data Warehousing Institute (TDWI) ● Health Catalyst Knowledge Center
  19. 19. © 2013 Health Catalyst Prop©rie2t0a1ry3 aHnedalCthonCfaidtaelnytsiat lFollow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics About Health Catalyst Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics Proprwiewtawr.yheaanldthCcaotnafliydsetn.ctoiaml www.healthcatalyst.com 19
  20. 20. Health Catalyst Profile Integrated Delivery Systems Community Hospitals Academic Medical Centers Children’s Hospitals Patients Impacted © 2013 Health Catalyst Proprietary and Confidential www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 20 Hospitals & Clinics 25M 1400 Founded 2008 Employees 140 HQ Salt Lake City, UT
  21. 21. What does Health Catalyst offer? Late-Binding™ Data Warehouse Platform Data Warehouse, Architecture, Metadata Management, Security, and Auditing Analytic Applications Key Process Analysis, Dashboards, Advanced Analytics Services Installation Services, Clinical Improvement Services Integrates Disparate Data Apply Evidence and Standardize Change Process and Behavior © 2013 Health Catalyst Proprietary and Confidential www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 21
  22. 22. Application Families © 2013 Health Catalyst Proprietary and Confidential www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 22
  23. 23. Reduce Healthcare Labor Costs by using an EDW and Analytics “The work our organization is doing with the Health Catalyst team pushes the envelope of what it means to have near real-time data at our fingertips to make operational decisions. Their technology and processes put us on track to understand the potential upstream and downstream financial impact of even the smallest decision.” ~ Director Clinical Planning and Financial Management Objective • Manage labor costs by allocating resources appropriately to the demand for services • Eliminate the need to manually pull and consolidate reports on a monthly basis for a 3rd party point solution • Enable business and unit managers to better track and manage performance by providing more timely information Health Catalyst Solution • Late-Binding™ Data Warehouse • Labor Productivity AdvancedApplication Module • Installation Services • Improvement Services Results to date • Estimated 2% reduction in total salaries and benefits to date • 66% percent increase in the speed of data availability • Estimated NPV of $425K over a 4-year period from automated data integration • 500% increase in the number of managers using data to drive decisions © 2013 Health Catalyst Proprietary and Confidential www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 23
  24. 24. How to Reduce Heart Failure Readmissions • Late-BindingTM data warehouse that enables faster time-to-value • Integration of clinical, patient satisfaction and financial data to establish baseline, ongoing and balance measures • Discovery, Foundational andAdvanced HF applications including cohort finder, registry and evidence- based clinical content • Healthcare analytic visualization including gauges and trend lines for at-a-glance view • Seasonally adjusted rate reduction of 21% in 30- day and 14% in 90-day readmissions • 2X increase in the number of phone calls made to patients within 48 hours of discharge • Average of 63 % increase in physician medication reconciliation within 48 hours of discharge • Follow-up appointment intervention baseline and balance measures established “Our data is now accessible to stakeholders throughout the organization, including clinical teams who can use it to drive improvements in care processes, care quality and patient outcomes” ~ Director of Clinical & BusinessAnalytics Objective Health Catalyst Solution Results to date © 2013 Health Catalyst Proprietary and Confidential www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 24 • Define Heart Failure (HF) baseline measures for 30 and 90-day readmissions rates • Implement evidence- based practice interventions to drive HF readmission rate reductions • Establish balance metrics including ED visits, observation days and patient satisfaction • Develop sustaining processes for evaluating readmission rates to ensure continuous process improvement
  25. 25. Questions and Answers Additional Information • See us at HIMSS 2014 booth #6076 • Call 801.708.6800 to request a meeting • Listen to two clients speak: – “Improving Outcomes with an Innovative Approach to Population Health Analytics” » Stanford Hospital & Clinics » Yohan Vetteth, Pravene Nath, MD » Date/Time: Thursday, 2/27, 12 PM » Location: Room 304A, Session #229 – “Blending Clinical and Financial Data to Drive the Value Equation” » Texas Children’s Hospital » Charles Macias, MD » Date/Time: Wednesday, 2/26, 1 PM » Location: Room 304A, Session #191 • Follow us on Twitter – @healthcatalyst Explore our site: www.healthcatalyst.com © 2013 Health Catalyst Proprietary and Confidential www.healthcatalyst.com Follow the discussion on Twitter - #HCDatawarehouse, #TimeforAnalytics 25

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