Supporting Clinical Decision Making With Technology

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1 Supporting Clinical Decision Making With Technology A Complimentary Webinar From healthsystemcio.com Your Line Will Be Silent Until Our Event Begins Thank You!

2 Housekeeping Moderator Kate Gamble, Managing Editor, healthsystemcio.com Ask A Question We will be holding a Q&A session after the formal presentations. You may submit your questions at any time by clicking on the QA panel located in the lower right corner of your screen, type in your questions in the text field and hit send. Please keep the send to default as All Panelists. Download the Deck Go to: Shortened link below appears on most slides. View the Archive You will receive an when our archive recording is ready. Separate registration is required.

3 Agenda 45 Minutes 20 minutes: Luis Saldana, MD, CMIO, Texas Health Resources 25 minutes: Q&A w/luis Saldana, MD

4 Supporting Clinical Decision Making With Technology Luis Saldana, MD CMIO Texas Health Resources

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10 Growing Complexity of Clinical Care

11 Systems of Care and Technology

12 Drivers for improved outcomes Reimbursement Competition Value-based purchasing Accreditation Transparency Accountability Regulatory Meaningful Use Affordable Care Act The Key Ingredient is Measurement

13 What is Clinical Decision Support? Clinical decision support is a process for enhancing health-related decisions and actions with pertinent, organized clinical knowledge and patient information, to improve health and healthcare delivery. Source: Improving Outcomes with CDS: An Implementer s Guide, HIMSS 2012

14 CDS Can Be Strategic Tool for Achieving Desired Objectives Establish a Strong Foundation for Data and Clinical Decision Support Build a Shared Vision Within Your Organization Focus on Strategic Goals of Your Organization Build your Capabilities to leverage data and Clinical Decision Support Measurement as Key Success Factor Get some quick wins and Build on success Be visible within your Organization

15 Transforming Data to Value

16 Framework: 5 CDS Rights Right Information Evidence-based, actionable [what] Right Person Clinicians and patients [who] Right CDS Intervention Format Documentation tools, data display, answers, order sets, alerts [how] Right Channel EHR, smartphones, dashboard [where] Right Point in Workflow Key decision/action [when] Do CDS WITH your Users and not TO them

17 Sample CDS Architecture

18 Configuring Interventions

19 Workflow, workflow, workflow

20 Tools Alerts and Reminders Order Sets and Plans of Care Relevant Data Presentation Documentation Templates Clinical Decision Rules and Calculators Diagnostic support Predictive analytics Reference tools/info buttons Patient Registries

21 Value Realization Select Objectives That Align with Organizational Priorities Assess Baseline Performance and Measurement Methods and Goals Governance-Stakeholder Involvement and How are Decisions Made and Communicated (Culture) Capabilities of the HIT System and the Build/Implementation Team Impact of Interventions on Workflows

22 Start with the End in Mind What is the Business or Clinical Problem You are trying to address? Set Goals with Clear Metrics Up Front, Do Baseline Metrics Can Clinical Decision Support Impact or Add Value to the Decision Making? Do the Analysis- Analyze and Map Workflows, Look for Nodes for Interventions Design and Test the Interventions including workflow impact Measure, Evaluate and Iterate

23

24 Practical Implications of CDS CDS is significant component of Meaningful Use (MU) CDS and Quality Reporting also integral components of successful Accountable Care Organizations Population Health Management tools within EHR systems give providers the ability to access and track relevant patient data to manage and measure the quality of care delivered for a given population

25 Meaningful Use

26 The Transition Historically, Clinical Decision-making focused around a patient s diagnosis and the optimal course of therapy: has been driven by a combination of clinician observations and intuition gained through experience Moving toward process being driven more by patient specific data and less by clinician observations and intuition So will clinician observation and experience/instinct become obsolete?

27 The New Clinician The future is clinical decision making by clinicians skilled in the effective use of patient and population specific data, clinical observation and intuition honed by experience

28 Putting the Patient in The Center Establish collaborative care plans to enable patient selfmanagement and track progress to goals Enable electronic communication between care team and patient Provide patients with online access to their personal health record Incorporate patient-reported and generated data Deliver educational resources to help patients prepare for visits or improve compliance Send patient alerts to improve preventive care, identify gaps in care, or detect changes in health Offer online health risk assessments and tools to help guide behaviors to enhance health

29 Patient Centered Care

30 Patient Facing CDS

31 Surveillance Systems

32 Moving In and Out Support Population Health decision making balanced with Personalized Health decision making

33 Will Need to Move Beyond Current EHRs Current EHRs support billable events, not coordination of care Can actually complicate information management and flows-data overload Can leverage internal tools for some patient specific interventions if all of information inside the EHR-often non specific and lacking context Need external tools to process the EHR data along with other data sources and generate an output to the EHR or other tools All of the patient specific data needs to follow the patient through their interactions with the system which needs to become continuous

34 Effective Care Coordination Measuring Quality and Efficiency Support for safe Transitions of Care and portability of critical patient data Personal Health Records Patient Generated Data and patient Reported Outcomes Chronic Disease and Wellness Registries Support for Team Based Care Clinical Decision Support-for Clinicians and Patients Build the Model Around the Patient ENGAGE THE PATIENT!

35 Moving from Volume to Value We are only scratching the surface of defining data sets that matter Still need to improve user interfaces and workflow integration, especially in tools to support clinical decision making (say no to alert fatigue) Improving data accuracy will lead to real-time analytics Real time analytics will lead to shorter analysis timeframes Shorter analysis timeframes will lead to efficiencies in the productivity of decision making Will create data algorithms that will more efficiently serve the move from volume to value

36 Key CDS Decisions What Data to Use-Quality, Availability What Type of CDS Tools to Use What Algorithms should be used How to Present Knowledge in the system How to Measure and Maintain the Interventions and the Knowledge base in the System The Lifecycle of A CDS Intervention and CDS Governance What vehicles or Platforms will we use to deliver CDS to the end user-build or Buy How will we maintain system performance, effectiveness and integration

37 Go From Slow to Fast

38 Why Optimize CDS? 1. Improved clinical outcomes 2. Improved performance on quality measures 3. Improved financial performance a) Value based purchasing b) Meaningful use c) Organizational Efficiency 4. Improved clinician satisfaction a) Reduced alert fatigue b) Streamlined and efficient CDS tools c) Data driven change management

39 KM life cycle Sources: Literature, guidelines, updates from vendors Content Selection: Review for applicability, evidence of positive impact Acquisition Retire Obsolete CDS elements Retirement Regular review by content owners for currency Monitor adherence, overrides Update, fine-tune CDS Review & Update Incorporation Adapt for local environment Identify best CDS mechanisms Incorporation into workflow Managing the Clinical knowledge Life Cycle, The Advisory Board

40 The Future of CDS (1 of 2) Leveraging Big Data and Unstructured Data Tools to manipulate data sets to manage health of Populations Delivering Predictive Analytics at Point of Care Point of Care on demand Queries Artificial Intelligence The future is already here it's just not evenly distributed. William Gibson

41 The Future of CDS (2 of 2) Personalized Healthcare through Genomics Patient Facing CDS Leveraging Patient Generated data Mobile and Novel Platforms to Deliver CDS

42 Thank

43 Q&A Click on the Q&A panel located in the lower right corner of your screen, type in your questions in the text field and hit send. Please keep the send to default as All Panelists.

44 Thank You! You will receive an when our archive recording is ready. (Separate registration is required) Don t Forget To Claim Your CHIME CHCIO Credits Attending healthsystemcio.com Webinars = 1 CEU Questions/Comments Kate Gamble Go to to view our upcoming schedule and see the last 12 months of archived events.

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