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Using Data to Drive Health System Performance Commissioned from Ovations by the National

Using Data to Drive Health System Performance Commissioned from Ovations by the National Primary and Care Trust Development Programme. Purpose of the Course:. Demonstrate how to use data to drive PCT health system performance by translating: > Data to Information

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Using Data to Drive Health System Performance Commissioned from Ovations by the National

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  1. Using Data to Drive Health System Performance Commissioned from Ovations by the National Primary and Care Trust Development Programme

  2. Purpose of the Course: Demonstrate how to use data to drive PCT health system performance by translating: > Data to Information > Information to Knowledge > Knowledge to Strategy > Strategy to Implementation By using the Knowledge Management Cycle

  3. Course Objectives: By the end of the course, participants will: • Discuss how information and knowledge are used as necessary tools for driving health care strategy for PCTs • Explain how to create health care strategic plans for PCTs using the PRECEDE/ PROCEED Framework and the Strategy Change Cycle as suggested tools.

  4. Course Objectives (con’t): • Apply these tools to operationalise PCT health care strategies • Identify PCT data sources that can be used to answer key health care questions • Suggest metrics that would be appropriate means to measure and report PCT health care findings

  5. Make a Difference in Health Care Delivery Know Your Medical & Public Health Roots Broad Street Pump John Snow 1883

  6. Knowledge Management:Using Data to Drive Strategy Knowledge derives from information as information derives from data. Unlike data and information, knowledge contains judgment.

  7. Knowledge ManagementPlanning Cycle for Driving PCT Health Care System Performance Social/Health Indicators Evaluation Data & Analysis Implementation Useful Information Operations Planning Knowledge Management Strategy

  8. Data What are Data: > Sets of discrete, objective facts about events > Structured records of transactions > Essential raw material for the creation of information Data sets by themselves have little relevance or importance and no inherent meaning.

  9. Information • Information has meaning, relevance and purpose. • We transform data into information by adding value. Why was the data gathered? What units of analysis are used? How is the data analysed? How are errors removed? How is a summary createdbased on the data?

  10. Knowledge • Knowledge is neither data nor information though it is related to both • Data, information and knowledge are not interchangeable • Knowledge is a mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information. - Thomas H. Davenport, Laurence Prusak Working Knowledge: How Organizations Manage What they Know

  11. Knowledge • Knowledge has become a health care asset not only for the health provider, but for the patient as well. • Health care now, more than ever before, requires quality, value, service, innovation, efficiency and effectiveness.

  12. Knowledge If information is to become knowledge, then people must do the work to accomplish meaning. How does this compare to others? What are the implications for decisions? How does this relate to others? What do others think?

  13. What is Knowledge Management • The leveraging of collective wisdom to increase responsiveness and innovation. -The Delphi Group • KM is intended to allow organisations to protect and develop their knowledge resource. - The Applied Knowledge Resource Institute

  14. What is Knowledge Management • KM is a management discipline that focuses on enhancing knowledge production, integration and use in organisations. - Mark McElroy, Knowledge Management Consortium • A cycle of knowledge creation, integration and dissemination. - Gerhard Fisher, Jonathan Ostwald, Univ. of Colorado

  15. Knowledge Management (KM)Knowledge & the Business Process Environment Business Processes Reflect Mutually Held Knowledge in Practice Organisational Knowledge is Embodied in Agents & Artifacts Business Process Environment Business Process Behaviors of Interacting Agents - Knowledge Use Organisational Knowledge Containers - Artifacts & Codifications; Individuals & Teams Internal/external events Continuous exposure to events in the (Business) environment to which organisations react & adapt by drawing on their mutually held knowledge

  16. Knowledge ManagementNot How First-Generation KM has Seen It Business Process Environment Distributed Organisational Knowledge Business Process Behaviors of Interacting Agents - Knowledge Use Organisational Knowledge Containers - Artifacts & Codifications; Individuals & Teams Internal/external events Begins with the convenient assumption that valuable organisational knowledge simply exists All we need to do is capture, codify, and share it

  17. Knowledge Management10 Key Principles of Second Generation KM 1. Learning and innovation is a social process, not an administrative one - strong affinity with organisational learning theory 2. Organisational learning and innovation is triggered by the detection of problems 3. Valuable organisational knowledge does not simply exist - people create it

  18. Knowledge Management10 Key Principles of Second Generation KM 4. The social pattern of organisational learning and innovation is largely self-organising and has regularity to it. 5. KM is a management discipline that focuses on enhancing knowledge production and integration in organisations 6. KM is not an application of IT - rather, KM sometimes uses IT to help it have impact on the social dynamics of knowledge processing

  19. Knowledge Management10 Key Principles of Second Generation KM 7. KM interventions can only have direct impact on knowledge processing outcomes, not business outcomes - impact on business outcomes is indirect 8. KM’s value proposition? KM enhances an organisations capacity to adapt by improving its ability to learn, innovate, and to detect and solve problems

  20. Knowledge Management10 Key Principles of Second Generation KM 9. If it doesn’t address value, veracity, or context, it’s not knowledge management 10. Business strategy is subordinate to KM strategy, not the reverse, because business strategy is itself a product of knowledge processing - KM is not an implementation toll for strategy; strategy follows from KP and is, therefore, downstream from KM.

  21. Knowledge Management versus Knowledge Processing Knowledge Management: is a management discipline that focuses on enhancing knowledge processing Knowledge Processing: is what organisations do to produce and integrate their knowledge

  22. What Investments in KM Cannot Do KM cannot make decisions on behalf of people operating on the front lines. KM has direct impact on Knowledge Processing outcomes, but only indirect impact on business outcomes.

  23. But Most KM Strategies Are Only Supply-Side in Scope Supply-Side KM Strategies Are All About Knowledge Capture, Sharing and Codification • Knowledge Integration • (Diffusion) • Sharing • Broadcasting • Searching • Teaching Organisational Knowledge Business Process Environment Business Process Behaviors of Interacting Agents (Knowledge Use) • Organisational Knowledge • Containers • Artifacts & Codifications • Individuals & Teams Distributed Organisational Knowledge

  24. Also IT- Centric and Transaction Oriented • Knowledge Integration • (Diffusion) • Sharing • Broadcasting • Searching • Teaching Tend to be Technology-Centric and Focus on Getting “The Right Info to the Right People at the Right Time” Organisational Knowledge Business Process Environment Business Process Behaviors of Interacting Agents (Knowledge Use) • Organisational Knowledge • Containers • Artifacts & Codifications • Individuals & Teams Distributed Organisational Knowledge

  25. Critical Differences Between Information Management and KM KM concerns itself with the value, veracity, or context of beliefs or claims. It also considers the production of related claims (knowledge claims) and ways they are integrated into an organisation.

  26. Critical Differences Between Information Management and KM Information Management tends to be aimed at managing work products and their content and/or attributes, but not beliefs or claims about their value, veracity, or context. In addition, it does not consider business processes and supporting systems that accompany the production and integration of related knowledge. IM can support KM strategies - but not the same as KM.

  27. Four Areas of Focus for KM Knowledge Production Knowledge Integration Social Dimension (people and Processes) Demand - Side Social KM Supply - Side Social KM Technology Dimension (IT) Demand - Side Technology KM Supply - Side Technology KM

  28. Demand-Side KM • Focus is on satisfying organisational demand for the production of new knowledge • Emphasises knowledge creation from a bottom-up perspective • Usually people and process-centric in its orientation (collaboration, organisational learning and innovation)

  29. Supply-Side KM • Focus is on”supplying” the right information to the rightpeople at the right time • Emphasises knowledge sharing from a top-down perpective • Usually technology-centric in its orientation(capture, codify and share knowledge)

  30. Approach Demand - Side KM Supply - Side KM Social Dimension (people and Processes) • Individual Learning • Group Learning • Think Tanks • M’gmt Planning • Innovation • Training Programs • Operations M’gmt • Knowledge Capture • Storytelling • KM Initiatives Technology Dimension (IT) • Knowledge Portals • Innovation M’gmt • tools • Groupware • Discussion groups • InformationPortals • Intranets • Information M’gmt • Content M’gmt • Imaging

  31. Recognisable Trends • The advent of 2nd-generation thinking seems to be taking hold: > More strategies taking an innovation view > R&D community embraces KM > Innovation as a core business strategy • View businesses as adaptive systems that rely on learning is increasing

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