Disclosure Statement. Learning Objectives 4/11/2017. Practical Improvement Science in Medication Safety. Jason Timothy Wong, PharmD

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// Practical Improvement Science in Medication Safety Jason Timothy Wong, PharmD PGY Health-System Pharmacy Administration Resident Oregon Health and Science University OSHP Annual Seminar DATE: April, Disclosure Statement Jason Timothy Wong, PharmD Potential conflicts of interest: none Sponsorship: none Presentation is educational in nature and indicates agreement to abide by the non-commercialism guidelines provided Learning Objectives By the end of this presentation, you will be able to: Explain the role of improvement science in healthcare Apply improvement science methodology to ensure safe medication management Identify and create an improvement project

// Today s Agenda Review the dimensions of healthcare Discuss the model for improvement Learn to construct a run chart Apply the model for improvement Create a personal improvement project Safe Effective Timely Efficient Patient Centered Equitable Value Access Prevention

// What is improvement science? Improvement Change that produces visible, positive differences in results Science A system of acquiring knowledge attained through study or practice Scientific Knowledge Greater Improvement Profound Knowledge Model for Improvement What are we trying to accomplish? How will we know change is an improvement? What change will result in improvement?

// CE Question. What is the importance of running iterative PDSA cycles? A. Each PDSA cycle completed enhances knowledge of the system B. Quickly determine whether or not the intervention lead to improvement C. Completely change your project as needed to address your theory on improvement D. All of the above What are we trying to accomplish? AIM Statement Clear, concise, results oriented What by when statement Example: We will have a % reduction in hospital readmissions for patients with congestive heart failure by January, How will we know change is an improvement? Outcome measures Process measures Balancing measures

// What change will result in improvement? Making a fundamental change to the system First order change Second order change Every system is perfectly designed to achieve exactly the results it gets n Berwick, MD, MPP, FRCP Image from: www.beckershospitalreview.com What changes should be made next? Next cycle? Objectives Questions and predictions Who, what, when, where? for data collection Complete analysis Compare data to predictions Summarize what was learned Carry out plan cument problems Begin analysis of data Changes That Result In Improvement Hunches, Theories, Ideas Small Scale Tests Follow Up Tests Wide-Scale Tests Implementation Of Change

// CE Question. Which of the following is a reason to include a balancing measure in your improvement project? A. To ensure you are making progress toward your AIM statement B. To ensure the changes you have made to one area are not having a negative effect on another part of your system C. To ensure you are accurately measuring your outcome D. All of the above What is a run chart? Graphical display of data plotted over time Illustration of data to make performance visible Value TITLE Median Goal Time

// Constructing a run chart. Date/observation. Value/data. Median. Goal Date Value Median Goal Improving CrossFit Class Attendance Summer # of CrossFit Workouts Start of OHSU Residency Median Goal Week Run chart rule Shift or more consecutive data points above or below the median Measure Median Time

// Run chart rule Trend or more consecutive data points going up or going down Measure Median Time Run chart rule Too many/few runs Measure A run is a series of points in a row on one side of the median Median Data line crosses once Total: runs Time Run chart rule Astronomical data point Measure Median Time

// Week Date Number of Medication Errors // // // // // // // // // // // // Weeks Average:. Maximum: Minimum: INTERVENTION Weeks Average: Maximum: Minimum: Medication Errors Median Goal Months Medication Errors INTERVENTION (Week ) Week (Before Intervention) Week (After Intervention)

// Medication Errors Median Goal INTERVENTION (Week ) Months CE Question. Please select the following run chart graph that illustrates improvement over time resulting from your intervention: Hours Hours Hours A B C RUN CHART QUESTIONS? Image from: www.wallpapercave.com

// Case study Situation Patient admitted to trauma ward MD obtains medication list from daughter Phenobarbital mg QHS + Phenobarbital mg QAM MD starts phenobarbital Med rec completed by PharmD days after admit Phenobarbital.mg QD MD awaiting neuro/geriatric recs ( days) Patient combative towards staff Phenobarbital reduced to. mg QD PSI reported Model for Improvement What are we trying to accomplish? How will we know change is an improvement? What change will result in improvement?

// What are we trying to accomplish? AIM Statement There will be a % reduction in the number of medication reconciliation errors per patient measured each week on the trauma ward by January, How will we know change is an improvement? Outcome Measure Rate of medication reconciliation errors per patient Process Measure Number of medication reconciliation errors identified by pharmacist Balancing Measure Pharmacist clock out time What change will result in improvement? HYPOTHESIS If we implement a risk stratification tool, we will reduce the number of medication errors that will lead to a decrease in adverse medication related events

// What changes should be made next? Next cycle? Objectives Questions and predictions Who, what, when, where? for data collection Complete analysis Compare data to predictions Summarize what was learned Carry out plan cument problems Begin analysis of data OBJECTIVE To reduce the number of medication reconciliation errors on the trauma ward PREDICTION If we reduce the number of medication reconciliation errors, there will be a reduction in adverse drug events INTERVENTION: Risk stratify patients to alert pharmacist of prioritizing medication reconciliation

// Week Value Median Goal % Error Risk Stratification Intervention Goal Week PREDICTION If we reduce the number of medication reconciliation errors, there will be a reduction in adverse drug events % Error Risk Stratification Med Rec Intervention Median (before) Goal Median (after) Week

// Data from the run chart indicate a change after the intervention Where do we go from here? Changes That Result In Improvement Hunches, Theories, Ideas Small Scale Tests Follow Up Tests Wide-Scale Tests Implementation of Change Your turn!. What are you trying to accomplish? Issue, rationale, AIM statement. How will you know change is an improvement? Outcome, process, and balancing measures. What changes can you make to improve? Ideas of change, stakeholders, barriers

// Image from: www.hrpayrollsystems.net Thank You Jason Timothy Wong, PharmD wojas@ohsu.edu Acknowledgements: Jason Christensen, PharmD, MBA, MS Joe Fazio, Rph, MHA, MBI Seth Hartman, PharmD Jess Lassiter, PharmD, BCPS John Mackay, PharmD, BCPS AQ Cardiology Jake McFarland, PharmD, BCPS Renita Patel, PharmD, BCPS Colleen Shipman, PharmD, MPH, BCPS References. Berwick DM. Developing and testing changes in delivery of care. Ann Intern Med ;:.. Institute for Healthcare Improvement. (, February). Retrieved from http://www.ihi.org/resources/pages/howtoimprove/default.aspx. Institute of Medicine (U.S.). (). Crossing the quality chasm: A new health system for the st century. Washington, D.C: National Academy Press.. Langley G.J., Moen R.D., Nolan K.M., Nolan T.W., Norman C.L., & Provost L.P. (). The Improvement Guide, nd ed. San Francisco, CA: Jossey-Bass.. Øvretveit J. Understanding the conditions for improvement: research to discover which context influences affect improvement success. BMJ Qual Saf ;(Suppl ):i.. McGlynn, E.A., S.M. Asch, J. Adams, J. Keesey, J. Hicks, A. DeCristofaro, and E.A. Kerr.. "The quality of health care delivered to adults in the United States." New England Journal of Medicine():-.. Practical Improvement Science in Health Care: A Roadmap for Getting Results. Harvard edx, Feb., https://www.edx.org/course. Provost L.P., & Murray S.K. (). The Health Care Data Guide: Learning From Data For Improvement. San Francisco, CA: Jossey- Bass.. Taylor, M. J., McNicholas, C., Nicolay, C., Darzi, A., Bell, D., & Reed, J. E. (). Systematic review of the application of the plan-dostudy-act method to improve quality in healthcare. BMJ Qual Saf, (), -.