Change Management for Health IT: Preparing for your Next Challenge



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Change Management for Health IT: Preparing for your Next Challenge Krystyna Hommen BSc MBA President and CEO, Excelleris Technologies Laurie Poole BScN MHSA Vice President, Telemedicine Solutions, OTN Dr. Jeremy Theal MD FRCPC CMIO, North York General Hospital Moderator: Darren Larsen MD CCFP CMIO, OMA/OntarioMD

What is Change Management? a strategic and systematic approach that supports people and their organizations in the successful transition and adoption of electronic health solutions. The outcomes of effective change management include solution adoption by user and the realization of benefits. - Canada Health Infoway Pan-Canadian Change Management Network, 2011 Why is it needed? Resistance to change is not some inviolable law of nature; resistance to change occurs because individuals do not see the benefit of changing, or a high likelihood of being able to do so successfully. - Golden, B. Change: The Challenge of CPOE. Healthcare Quarterly v.10 2006

Community teaching hospital affiliated with the University of Toronto Catchment area: > 400,000 Three Sites: General, Branson, Seniors Health Beds: 418 acute care 192 long-term care Volume per year: 113,000 ED visits 29,500 inpatient cases 5,800 births

Change Management for CPOE 1. Organizational Goals, Vision, Commitment, Readiness 2. Select Leaders and Clinician Champions 3. Identify and Mitigate Barriers to Change 4. Communicate, Educate and Engage: Share the Vision, Goals and Plan Involve and Engage Clinicians Build Positive Anticipation pre- go live 5. Support Conversion: ensure CPOE is the new normal 6. Measure, Learn, Improve, Repeat

Challenges in Inpatient Care

What is ecare? Advanced Electronic Medical Record (EMR) + Multi-year hospital-wide clinical transformation project utilizing health information technology Standardization on Evidence-Based Care + Safe Prescribing and Medication Administration + Clinical Decision Support (Rules, Alerts) A new era in patient care using EMR technology

System Components Computerized Provider Order Entry (CPOE) Evidence-Based Order Sets & Clinical Workflows Closed-Loop Medication Administration emar, Medication Reconciliation, Depart Process Advanced Clinical Decision Support

Goals of the ecare Project Implement advanced electronic medical record technology to improve patient outcomes: Quality and safety of patient care Embrace culture of evidence-based care, best practices Make it easy to do the right thing Build evidence into clinical workflow SHARED VISION = by clinicians, for clinicians 100% clinician adoption Team-based interprofessional workflows

Clinician Champions Roles: Representation from each major scope of practice (MD, nursing, pharmacy, allied health) Responsibilities: Practice alongside peers and have their respect Create shared vision for project success Have paid, protected time for the project Have accountability to the success of the project Be local to each implementation site Work in partnership with clinicians, Clinical Informatics/IT, and Administration

Selecting Clinician Champions Effect of Peer Influence amongst clinicians: Clinicians (particularly MD s) value autonomy Changes perceived as imposed are not well adopted Changes suggested/demonstrated by peers more frequently adopted Essential to identify at every institution: Technophiles: innovators and early adopters Opinion leaders: with high peer influence Affinity to IT HIGH Affinity to IT LOW Peer Influence HIGH CLINICIAN CHAMPIONS STRONGEST RESISTORS Peer Influence LOW SuperUsers Intensify Training

Integrating Clinicians: Project Governance 3 main project foci: Medication Integration CPOE/Order Sets and Physicians Interprofessional Integration Each focus led by: Clinician Champion Executive Sponsor Foci integrated by: Steering Committee Core Committee

Clinician Adoption of IT: Supply/Demand Supply Development of innovations and technologies to enable efficiency and quality in healthcare Deployment of innovations depth (complexity) and breadth Demand Determining readiness of technology infrastructure and users Attracting users and fostering adoption of new technologies Traditional implementation approach focuses only on supply: Build it and they will come Up to 30% (of CPOE implementations) fail National Health Information Network Co-ordinator David Brailer, Washington Post, 2005 adoption is NOT guaranteed! For advanced systems must focus on demand: Technology readiness and adoption needs of diverse user groups

Understanding Your Users: Physicians Doctors are motivated by: Independence and autonomy (imposed change will fail) Efficiency (save time) Quality of patient care (often feel they give top quality already) Evidence need hard proof that change is warranted Peers based on respect, shared experience, training models Respect/Ego want respect of peers, don t want to lose face Competition show them they re falling behind the leaders of the pack, this will drive change faster Desire to lead, drive change Make them think it was their idea

Engaging Physicians Physician Input Iterative Design Buy-In: Led by Physician Champions (peer-based autonomy): Design of system components Review of order set evidence and content Order Sets are not Cookbook Medicine! Important message to address perceived autonomy MD makes decisions based on individual patient characteristics Order set simply provides evidence-based guardrails while improving efficiency, reducing callbacks, increasing safety

Engaging Physicians: Evidence for Quality/Safety Inpatient management of diabetes and hyperglycemia: CPOE order sets for diabetes care 25% LOS reduction for diabetic inpatients, with improved glucose control Single hospital study, Schnipper, JL. J Hosp Med 2009; 4(1): 16-27 Sepsis CPOE order set: Length of stay reduced by 6.3 days (p=0.02) 15.5% absolute mortality reduction (p<0.01) Single hospital study, Thiel SW et al. Crit Care Med 2009 37(3):819-24 41-hospital study in Texas CPOE and CDS: 21% reduction in death from pneumonia, $538 saved/patient Amarasingham R et al. Arch Intern Med 2009 169(2):108-14

Evidence-Based Care: The Gaps 1) Belief Gap: I know everything already 2) Capacity Gap: 200 MB capacity GAP 6,000 articles/day 300,000 RCT s Finish medical school and residency knowing everything Read and retain 2 articles every single night At the end of 1 year: 1,225 years behind 3) Temporal Gap: Average of 17 years for evidence to reach the bedside

Insert ecare picture here

Training and Support Training: Multiple modalities for different practitioners/learning styles Computer-based training, classroom-style, simulation lab Carrots for physicians: CME, scheduling flexibility Audit, reinforce and repeat (drop-in, roamers, tips, portal) Support: Peer-to-peer where possible (clinician SuperUsers) Dedicated 24x7 support command center, for 4 weeks Centralized feedback system Change/improvement request triage with prompt response 18

\ Metro Edition Thursday Dec 13, 2012 In-Hospital Death Rates Down Across Greater Toronto Area Annual CIHI Report demonstrated that preventable in-hospital deaths were reduced NYGH top performer in Greater Toronto and second best in all of Canada CEO Tim Rutledge: health information technology has hard-wired quality and safety into the hospital

Study: CPOE and Evidence-Based Order Sets Retrospective chart review: All patients discharged with a main diagnosis of Pneumonia or COPD Population #1: Pre-CPOE (Jan-Sep 2010) n = 520 Population #2: Post-CPOE (Jan-Sep 2011) n = 511 Groups similar in age, gender distribution Corrections: Probability of Death, critical care admission Primary Hypothesis: Use of CPOE is associated with reduction in adjusted mortality, 30-day readmission, length of stay vs traditional paper processes Secondary Hypothesis: Use of CPOE with a matching evidence-based admission order set is associated with reduction in adjusted mortality, 30-day readmission, length of stay vs use of any order set

. 0.55 Vision Champions Barriers Engage Support Measure Study Results Primary Hypothesis (CPOE vs Paper) Outcome Odds Ratio Confidence Interval p-value Death adj for Probability of Death and CrCU Admission 0.55 0.36 0.83 0.005 Secondary Hypothesis (evidence-based OS selection) Order Set Outcome Odds Ratio Confidence Interval p-value Diagnosisappropriate Close to diagnosis Any order set Death adj for Probability of Death and CrCU Admission Death adj for Probability of Death and CrCU Admission Death 0.44 0.21 0.90 0.024 1.82 0.78 4.23 0.16 0.12 2.54 0.44

. Vision Champions Barriers Engage Support Measure Study Results: Subgroup Analysis Order Set Use Paper Orders CPOE (ecare) Percentage of patients for whom a diagnosisappropriate order set was used Percentage of patients for whom any admission order set was used Pneumonia 26.05% Pneumonia 60.43% COPD 0.0% COPD 45.1% Pneumonia 37.90% Pneumonia 97.54% COPD 35.11% COPD 97.35%

Leverages the non-competitive structure of Canadian healthcare to create a no-cost sharing platform for Canadian CPOE development resources Saves significant implementation time and cost CPOE Implementation guide (>500 pages) Searchable library of evidence-based order sets Medicine, Surgery, Critical Care, Paediatrics, Maternal-Newborn Coming soon: Long Term Care, Mental Health Multi-publisher sharing model Each contributing organization shares content at no cost, retains full ownership of all contributions

Table of Contents CPOE Project Governance Change Management and Physician Adoption Project Planning and Project Management Order Catalogue Creation Electronic Order Set Development Electronic Medication Management Clinical Decision Support Integrating Workflow Technical Implementation Training Go Live Maintenance Downtime Metrics and Quality Improvement

CPOE TOOLKIT: BY THE NUMBERS member organizations 42 4 contributing organizations 5 Canadian provinces 353 active users 652+600 evidence-based order sets

THANK YOU! Join today at: http://www.cpoe-toolkit.ca For more information, please contact: Jeremy Theal MD FRCPC Chief Medical Information Officer Email: Jeremy.Theal@nygh.on.ca Twitter: @drjeremytheal