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Improving Clinical Outcomes through Technology


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  • 1. Brought to you by Improving Clinical Outcomes Through Technology How Six Sigma and Business Intelligence Support CAMC Initiatives for Reducing Medication Reconciliation Failure Rates
  • 2. Thank You to Our Sponsor The outcomes achieved by the Siemens customers described herein were achieved in the customers’ unique setting. Since there is no “typical” hospital and many variables exist (e.g., hospital size, case mix, level of IT adoption), there can be no guarantee that others will achieve the same results.
  • 3. How to Participate • Submit your questions in the GoToWebinar presentation window. • This webinar will be recorded and available for download a few days after the webinar. The slides will also be available.
  • 4. About the Panel Karen Miller, RN, MSN, MBA; Lean Six Sigma Director; Master Black Belt; Charleston Area Medical Center Karen Miller has over 20 years’ experience in healthcare administration, program development and project management with proven expertise in the ability to create strong functional teams for the development and execution of quality and cost improvement projects. She supervises, manages, coordinates, and integrates quality initiatives and process improvement activities to facilitate achievement of organizational goals at Charleston Area Medical Center system using Lean Six Sigma tools, methodologies and philosophy. She reports to and works closely with the Chief Quality Executive and administrators to effectively initiate and manage change. Janet Hickman, R.T. (R),(N)(ARRT), NMTCB; Systems Analyst, Siemens Managed Services I’ve worked in the healthcare industry for over 38 years and am currently employed by Siemens Managed Services as a DSS System Analyst. I am based at Charleston Area Medical Center (CAMC) and act as the DSS team lead. Before working for Siemens, I was employed by CAMC as a Decision Support Consultant, Laboratory System Analyst, Nuclear Medicine Technologist, and Radiologic Technologist. Janet M. Kennedy, Moderator Janet M. Kennedy , CMD is the Director of Marketing and Digital Strategy for Health Vue, a big data analytics firm working in healthcare. Janet creates and presents webinar and in-person social media training for healthcare organizations through a partnership with EHR2.0. She is also the host of “Get Social Health” a podcast about social media for healthcare. Follow her @GetSocialHealth.
  • 5. At the conclusion of this presentation participants should be able to:  Describe the Define, Measure, Analyze, Improve, and Control (DMAIC) Six Sigma methodology and benefits  Describe the key role Healthcare Intelligence (HI) plays in the measure phase  Describe how information technology, Six Sigma, and clinical staff collaborate to develop clinical documentation, work lists, and education for process changes  Describe how to develop and use Crystal reports to monitor improvements and maintain projects in control Objectives 5
  • 6. Charleston Area Medical Center  Non-profit, 908-bed, 4-campus teaching hospital system and tertiary regional referral center  Servicing 557,328 mostly rural population  550,000+ outpatient visits  100,000+ ED visits  40,600+ Cancer Center Visits  38,000+ inpatient discharges  5,000+ employees  600+ physicians  500+ health professional students daily Memorial Hospital 6 General Hospital
  • 7. Charleston Area Medical Center  Primary Stroke Center of Excellence  Bariatric Surgery Center of Excellence  Heart & Vascular Center of Excellence  9,469 cardiac cath procedures  1,289 open heart bypass procedures  Level I Trauma Center  Only free standing Women & Children’s Hospital in state  Level III Neonatal Intensive Care Unit  3,000+ births Women & Children’s 7 Teays Valley
  • 8. Six Sigma Methodology DMAIC: To improve any existing product or process Define Measure Analyze Improve Control Who are the customers and what are their priorities? How is the process performing and how is it measured? What are the most important causes of the defects? How do we remove the causes of the defects? How can we maintain the improvements? 8
  • 9. Six Sigma Methodology DMADV : To redesign a bad process by improving the average and variation in the process Define Measure Analyze Design Verify Who are the customers and what are their priorities? How is the process performing and how is it measured? What are the most important causes of the defects? How do we design or redesign a process with minimal defects? How do we verify that the design meets the goal? 9
  • 10. Allocation of Six Sigma Resources  8 full time black belts  Online request for complex problem solving  Request must include scoped problem statement, aligned strategic goal, and estimated Return on Investment (ROI)  Online requests are presented by Vice Presidents at monthly executive meetings  Start dates are determined and assigned based on current workload and strategic priorities  Chief Information Officer frequent requestor of resources 10
  • 11. Define Phase  Identify key stakeholders  Executive sponsor, physician champion, and team members assigned  Concise problem statement and business case  Team defines and prioritizes possible causes of problem  Brainstorming and fishbone diagrams  Six Sigma assigned staff contacts Healthcare Intelligence for data D M A I C 11
  • 12. Define Example: Medication Reconciliation D M A I C Project Start Date: January 2011 Executive Sponsor: CQO Project Process Owner: CMO Physician Champions: Medicine, Hospitalist, and Information Services Clinical Directors Master Black Belt: Karen Miller Team Members: CPOE Design Team, Information Services, Transcription Services Project Description/Problem Statement: Discharge medication list defects account for 50% of the total Center for Medicare & Medicaid Services (CMS) discharge instructions defects. Project Scope: Discharge medication reconciliation CMS indicators: 1. Provider dictated discharge summary medications match discharge meds ordered 2. Med list given to patient match physician discharge meds ordered 3. Documentation med list given to patientAlignment: Strategic Vision Pillar: Best place to receive patient centered care Strategic Goal: Evidenced Based Care/ CMS Reliability TJC standards: CMS Congestive Heart Failure (CHF) discharge instruction indicator What is the project business case? Patient Safety: Incomplete discharge medication reconciliation contributes to readmissions, patient mortality and morbidity. Financial: Part of Meaningful Use criteria for potential $6 million. 12
  • 13. Define the Current Process D M A I C Physician uses Home & Current Medication Order form that prints from Soarian® to order meds Key Takeaway: Defining the current process identifies the data elements required for the measure phase and is the basis for discussion with Healthcare Intelligence resource staff Physician uses home med and clarification lists to order meds by circling continue or discontinue? Physician only uses physician blank order form and writes discharge meds? Physician uses Med Administration Check™ to identify inpatient meds? Nurse adds, deletes, and revises discharge med list based on discharge orders from multiple forms Physician dictates discharge summary up to 30 days past discharge Physician uses multiple forms to dictate medications in summary 13
  • 14. Measure Phase  Develop Excel document for data elements needed for the Analyze Phase  Meet with Healthcare Intelligence resource to explain the project business case and expected outcomes  Suggestions made for additional data elements  Many of the data elements can usually be supplied by Decision Support  Revise data collection plan and send to Healthcare Intelligence resource Key Takeaway: Often I don’t know all data elements needed or available until my project team member asks “would you want to know this”? D M A I C 14
  • 15. Healthcare Intelligence Resource  Compares data in Soarian® and Data Warehouse for availability of each data element  Helps team to import new Soarian data into warehouse if needed  Validates data by comparing warehouse data to Soarian  Sends draft data to Six Sigma  Six Sigma reviews data with team members and collaborates if revisions are needed  Approval received by Six Sigma to develop report  Final report formatted in Excel and sent to Six Sigma for statistical analysis D M A I C Key Takeaway: Frequent communication and collaboration required to meet customer needs 15
  • 16. Analyze Phase  Warehouse Excel data copied to statistical software for data analysis  Data elements supplied by warehouse allow for segmentation  Segments targeted in the improvement phase for cycles of change  Physician department, nurse department, time, admission source, documenter names, etc.  Example: 72% of defects were physician discharge summary dictation of med lists and 46% of those were Hospitalists D M A I C Key Takeaway: Healthcare Intelligence data helps identify root causes of defects 16
  • 17. Improve/Design Phase  Process mapping of future state and potential failure identification  Identify pros/cons for different options  Potential failure mitigation strategies using electronic documentation and workflows  Identify education needs for process changes  Implement pilots for tests of change  Meet with BI people to develop data for analysis of pilots  Spread of successful improvements/design D M A D V D M A I C 17
  • 18. Improve/Design Outcomes  Dictated provider discharge summary medication lists matching the discharge orders is now at 2.68% defects compared to 34.21% with baseline data, which represents a 92% decrease in defects.  Initially targeted Hospitalists and spread success D M A D V D M A I C 18 10-13 07-13 04-13 01-13 10-12 07-12 04-12 01-12 10-11 07-11 11-10 0.6 0.5 0.4 0.3 0.2 0.1 0.0 Audit Date Proportion _ P=0.0268 UCL=0.0893 LCL=0 Baseline Hospitalists All Physicians Automation Tests performed with unequal sample sizes Provider Discharge Med Reconciliation Defects by Stage Electronic DC Instructions
  • 19. Improve/Design Outcomes  Decrease in provider dictated discharge summary med defects resulted in improvement of discharge med reconciliation CMS compliance D M A D V D M A I C 19
  • 20. Control/Verify Phase  Development of monitoring reports to obtain outcome data  Example: Physician CHF discharge summary Web Publishing report  Discharge department, status, account number, patient name, admission and discharge date/time, discharge med list date/time, person completing med list, discharge summary date/time, physician completing, attending physician at discharge  Development of control plan  Handoff to operations D M A I C D M A D V 20
  • 21. Implementation of Electronic Medication Collection, Admission & Discharge Reconciliation  Address physician concerns about home medication collection  Address defects from nursing transcription of discharge med orders to the patient discharge med list  Executives chartered team consisting of physicians, nurses, pharmacists, IS, and Six Sigma  Defined the problem  Measured the current process for med collection and admission reconciliation by completing process mapping  Analyzed risks D M A D V D M A I C 21
  • 22. Improve/Design Phase: Electronic Medication Reconciliation Implementation  Multidisciplinary team collaboration  Future state process mapping  Risk identification and mitigation strategy  28 process issues identified for mitigation  21 of the 28 were new process issues for mitigation  Pilot on large medicine nursing department  Feedback and redesign of process  Education prioritization based on risks D M A D V D M A I C 22
  • 23. Future State Process Risks: Electronic Discharge Med Reconciliation Risk: Med reconciliation not completed. Solution: Alert when discharge order placed. Risk: Duplicate inpatient and home med ordered. Solution: Default by drug sort. Risk: Chooses inpatient home med instead of “house icon” med – prints on med list to stop home med and then start same med. Solution: Default by drug sort “house "first. Risk: Provider adds new med under Soarian orders instead of Discharge Med Reconciliation Solution: Education, monitoring, & feedback. Risk: Meds added in “complete” status – how will nurse know when to print? Solution: Nurse alert if DMR changed after placed in a “complete” status. D M A D V D M A I C 23
  • 24. Risk Mitigation Implementation Strategies  Training for nurses, physicians, pharmacists  Mandatory computer based training  Whole house adoption on a single day  Pre loading inpatients home med list on the morning of the conversion  Two weeks of live support including Six Sigma staff  Job Instructional Training (JIT) competency validation within one month of go-live  Development of 13 Single Point Lessons (SPL) placed at work stations for visual aids D M A D V D M A I C 25
  • 25. DMR Single Point Lesson D M A D V D M A I C 26
  • 26. Control/Verify Example  Developed home med collection entry tips for high frequency problems associated with expansive Soarian drop down menus (51% OTC meds)  Web Publishing reports for daily and weekly nurse and individual provider defect monitoring for performance management  Cycles of analysis and improvements implemented from home med list collection report  50% of patients admitted through EDs  58% of ED home med lists had missing required med components  Implemented LPN home med collection in EDs resulting in 3-5% missing required med components, representing a 131% improvement  Weekly data patient file for CHF chart audits and monthly control charts for CMS medication compliance sent to administration D M A I C D M A D V 27
  • 27. Web Publishing Reports Daily report for home med list completion and completion within 4 hours of admission percentages Daily report for home meds missing required components that need corrections before discharge reconciliation Weekly report for identification of nurses using free text and entry of home meds with missing components for follow up Weekly report for physician completion rates for discharge medication reconciliation between 8:00 a.m. – 5:00 p.m. D M A I C D M A D V 28
  • 28. D M A I C D M A D V Patient Home Med List Key Takeaway: Executive patient data view for medications entered on the home medication list % patients with completed status Home Med List (HML) % patients with free text meds on HML % patients with a required med component missing on HML (excludes free text) % meds with required med component missing on HML 29
  • 29. Patient Home Med List Key Takeaway: Drill down to department level data to identify patients currently in the department that need home med list corrections D M A I C D M A D V 30
  • 30. Patient Home Med List Key Takeaway: Drill down to patient to identify home med lists that need correction for hospitalization continuity of care and prep for discharge reconciliation D M A I C D M A D V 31
  • 31. Patient Home Med List Patient location nurse dept and location HML collected Missing required components on HML Key Takeaway: Drill down to patient med components that need corrected D M A I C D M A D V 32
  • 32. Home Med Collection Key Takeaway: Executive view for home med list collection performance management D M A I C D M A D V 33
  • 33. Home Med Collection Key Takeaway: Drill down to department then to nurse/provider data for performance management D M A I C D M A D V 34
  • 34. % patients with HML not completed Key Takeaway: Drill down to department then to nurse data for timeliness performance management Home List Completion % patients with HML not completed within four hours of admission D M A I C D M A D V 35
  • 35. Provider Discharge Reconciliation Key Takeaway: Executive view of provider completion rates % with Discharge Med Reconciliation (DMR) in complete status and any status % initial DMR entry by physician or midlevel % last DMR entry by physician or midlevel % initial DMR entry by Privately Employed RN (PERN) % final DMR entry by Privately Employed RN (PERN) % initial DMR entry by staff RN% final DMR entry by staff RN% final DMR entry by staff RN 5:00 p.m. – 8:00 a.m. D M A I C D M A D V 36
  • 36. Provider Discharge Reconciliation Key Takeaway: Medical Affairs and medical staff leadership view for provider completion rates D M A I C D M A D V 37
  • 37. Provider Discharge Reconciliation Key Takeaway: Drill down to physician for identification of top performers, performance management and credentialing D M A I C D M A D V 38
  • 38. Six Sigma and Healthcare Intelligence Projects  Nursing admission assessment  Skin assessment/actions  Fall assessment/actions  Severe sepsis  Telemetry classifications  ED wait times and boarder hours  Patient discharge call backs  Glucose value < 60  Consult orders  Mortality  Complications and comorbidities  Readmissions  DRG physician detail  Case mix index  ALOS by nursing department Key Takeaway: 71 current Web Publishing reports being used for Six Sigma projects 39
  • 39. Healthcare Intelligence Resources Benefits  Access to100% of patient population  Eliminate manual data abstraction for key elements  Decrease measure phase time  Improve analysis for critical variables  Sustain gains after improvements Key Takeaway: Collaborating with BI team member improves efficiency & effectiveness in all project phases I ask the impossible and Healthcare Intelligence delivers! I simply couldn’t do my job without them! 40
  • 40. Six Sigma Benefits $- $20,000,000 $40,000,000 $60,000,000 $80,000,000 $100,000,000 $120,000,000 $140,000,000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Financial Impact 2001 - 2012 Cumulative Total Annual Improvements Key Takeaway: $132,603,856 over 11 year period with $13 million in expenses. Net ROI of $119,603,856. 41
  • 41. Questions ? 42