Value Equation for Healthcare - PDF Free Download

Value Equation for Healthcare Value = (Outcomes + Patient Experience) x Appropriateness Cost + Hassle Factor

What Do Patients Hire Us to Provide What do they call Value Make the Right Diagnosis Deliver the Correct Therapy / Treatment Outcomes Prevent Complications or Errors in Care Deliver Safe Care regardless of the Inherent Risks Safety Get Me Home, Keep me at Home Respect my needs Give me my Money s Worth Patient / Family Experience Value This is all FLOW management it is essential for SAFETY, PATIENT / FAMILY EXPERIENCE and QUALITY DELIVERY

Health Care Delivery System Transformation Strategic Improvement Priorities and System Level Measures ACCESS, FLOW, PRODUCTIVITY PATIENT AND EMPLOYEE SAFETY CLINICAL EXCELLENCE, OUTCOMES TEAM WELLBEING PATIENT AND FAMILY EXPERIENCE 3 rd next available appointment % of patients delayed: ED, PICU, PACU Touch Time for care givers Adverse drug events Bloodstream infection rate Surgical site infection rate Infection rates: VAP Serious Safety Events OSHA recordable injury rate Codes outside the ICU rate/1,000 days MRT preventable codes outside the ICU Standardized PICU Mortality Ratio Expected/ Actual % use of Evidence-Based Care for eligible patients Staff Satisfaction Nursing turnover rate Overall Rating: Patient Satisfaction (best possible) Patient Satisfaction (0-6 ) Overall, Inpatient, Outpatient, ED, Urgent Cares, Ambulatory Surgery, Home Health 3

Hospital Flow - Challenge of Team E D E D Families Nursing O R Patients Medical Staff Housestaff OutPatients I C U InPatients Multiple Sites All Interactive / Interdependent 6

Flow is a Safety Initiative Prediction Framework for Safety Getting the Rights Right Right Diagnosis and Treatment Right Patient in Right Bed Location Right Nursing Staff and Staffing Expertise Disease Specific Expertise Equipment Expertise Best Care Model Requires ability to Predict future needs, and manage present capacity control variability Operations Management techniques to understand and manage variability are the key to success

Opt Surgery Saturday Surgery Hospital Wide Flow Smoothing OR Schedule Pediatric Adm Schedule More Cases Scheduled Smoothing OR Schedule (Elective Cases) Optimal Use of Inpatient Beds ICU Inflow Smoothing Elective Cases Smoothing Outpatient Admissions Demand : Capacity Matching ICU Outflow Prediction Model Heme Onc Discharge Predictions All Patients Optimal Use of ICU Beds

Block with Urgent Access Assured Predictive system Urgent Cases in Defined Rooms with Scheduled Teams Resources needed can be modeled Care based on Urgency / Medical Need

Key Drivers for Capacity Management IHI Drivers CCHMC Initiative Operations Possibilities Shape / Reduce Demand Predictable Care Delivery Management of Variability Best Practices, Analysis of ALOS and outliers, Standardize then Customize, Eliminate unnecessary care Identify Patient Streams Inpatient/Outpatient/OR Manage System Variation D/C Match Optimization of Flow Delivery Capacity Prediction Placement initiatives D:C Matching plans Discharge prediction and planning, Home Care, Parent Initiatives Integration of simulation modeling and planning Environmental Impact Reports for growth programs System Re-Design Capacity Management Flow:Safety Matching Simulation for design and patient placement Environments Impact Planning Flow Failure Analysis, GARDiANS

Organizing for Transformation Board Oversight Senior Leadership Focus System-Wide Goals CSI Goals Division/Microystem-Based Goals Individual Performance 11

Clinical Systems Improvement PATIENT/FAMILY Microsystems: Monitor & act on a dashboard of measures Inpatient Team Outpatient Team ED Team Peri-Op Team Home Care Team Mental Health Team Clinical & Non-Clinical Support Processes Develop, monitor & act on a dashboard of measures Comprised of Patient Services, Faculty, Administrative and Community Physician Leadership Develops, reviews & acts on System Level Measures Clinical System Improvement Integrating Team Board/ Leadership Team Provides strategic priority setting, resource allocation, organizational alignment Serves as champions/coaches to the Clinical Systems Improvement Teams and Sub-teams The Clinical System Improvement reports to the Patient Care Committee of the Board 12

Overview Operational & Experience Excellence: The CCHMC Way Objective: To achieve unprecedented performance in safety, flow, experience and outcomes across the inpatient system using high reliability concepts and key process reliability. Hypothesis: Strong integrated unit-based leadership teams, uniformly and reliably applying focused safety, leadership and staffing principles, coupled with key process reliability, advanced situation awareness and risk prediction tools, will dramatically improve patient care and safety while delivering better outcomes and patient experience. Objective: Determine key processes most critical to unit s work and sustain high reliability through leadership reinforcement, engagement & team member competency. Objective: Create a front-line driven system that comprehensively and efficiently presents information necessary for microsystem leadership to effectively manage their units. GARDIANS Daily Risk Management Reliably Execute Key Processes Build Engaged & Committed Teams Objective: Ensure clear understanding, competency and performance of predetermined fundamental behaviors for all team members on every inpatient unit. Patients & Families Objective Reliably implement situation awareness models and tools for successful implementation in both ICUs and non-icus. Reliably Implement Situation Awareness Maintain Resilient Staffing Develop Empowered & Accountable Microsystem Leadership Objective: Identify and develop leaders to achieve high reliability microsystem performance in a structure which is both empowering and accountable. Objective: Ensure staffing effectiveness by making realtime adjustments as needed Key Process Reliability Culture Risk Management & Prediction All areas 2

Operating Assumptions- Improvement Capability and capacity Building improvement capability at CCHMC goes beyond acquisition of knowledge and skills to action-oriented improvement that achieves critical results and accelerates transformation. As an Academic Medical Center, CCHMC s strategy for building improvement capability focuses on engaging and developing faculty as improvement leaders, educating trainees and advancing the scholarship of health care improvement through rigorous methods and quality improvement research. Different groups of people will have different levels of need for improvement knowledge and skill to achieve results, and each group should receive the training they need when they need it and in the appropriate amount. All members of the organization should incorporate improvement into their daily work and have the ability to advance their improvement knowledge and skills to achieve critical results, and function at any level of the CCHMC improvement ladder.

Critical Flow Failures 38 Months 39 Months 1 in 38 Months 39 Months

Delivering on Operations Reliably in a Mesosystem PeriOp Virtual Site Visit B\\Barbara Tofani, RN Frederick C. Ryckman, MD.

ICU Admission Model Elective Cases Short Stay Cases Access Cap # Cases on Schedule / Day Long Stay Cases Fixed # Beds

ICU Bed Availability ICU Scheduling Category Case Statistics by Category Total PICU Days Case Count ALOS Short 224.47 177 (61%) 1.27 (27%) Medium 304.74 82 (28%) 3.72 (37%) Long 302.56 31 (11%) 9.76 (36%) Grand Total 831.78 290 2.87

Spread Plan

Patients who Utilize an ICU bed because an Appropriate Floor Bed is Not Available

Strategies for Patient Placement Early Day Beds PICU, CICU Critical Units Later Day Beds All units Demand : Capacity Match Opportunistic with Forethought Specific Bed D:C Match Unit Bed Awareness

Critical Care Bed Predictions 2 Types of Demand SCHEDULED: Demand that we know about ahead of time because we have scheduled it (i.e. a planned admission or a planned elective surgical case) UNSCHEDULED: Demand that we don t know about ahead of time. This unscheduled demand is a random pattern that happens every day or year and may or may not be seasonal. ANALYTICS TO IMPROVE FLOW Determine method to control flow Can t control UNSCHEDULED but can understand it better Develop plan for SCHEDULED demand SIMULATION MODELS Determine beds needed for UNSCHEDULED Daily CAP for SCHEDULED procedures to utilize remaining capacity

Critical Care Bed Predictions

Predicting ICU Discharge

Respiratory Care Outside ICU Asthma: Continuous Albuterol On A6S x 5 years On LA-4 x 1 year Bronchiolitis: High Flow Nasal Cannula A6S and LA-4 initiated last respiratory season

Mar-13, n=471 Apr-13, n=582 May-13, n=599 Jun-13, n=571 Jul-13, n=610 Aug-13, n=579 Sep-13, 9/13: n=514 Non-verbal report spread complete Oct-13, n=523 Nov-13, n=492 Dec-13, n=533 Jan-14, n=495 Feb-14, n=463 Mar-14, n=490 Apr-14, n=599 May-14, n=578 Jun-14, n=620 Jul-14, n=624 Aug-14, n=559 Sep-14, n=496 Oct-14, n=564 Nov-14, n=461 Dec-14, n=514 Jan-15, n=477 Feb-15, n=382 2/4/15: Epic transport go live Mar-15, n=479 Apr-15, n=515 May-15, n=514 Jun-15, n=612 Jul-15, n=630 Aug-15, n=593 Sep-15, n=561 Oct-15, n=549 Nov-15, n=517 Dec-15, n=523 Jan-16, n=457 Feb-16, n=533 Mar-16, n=578 Apr-16, n=573 May-16, n=567 Jun-16, n=597 Jul-16, n=535 Aug-16, n=579 5/13: Pend transport within 5 minutes of criteria met 6/13: Standardized phone script 3/14: Eliminated inpatient RN call-back 100% Percent of patients for whom transport is requested by nurse within 5 minutes of meeting discharge criteria Population: Inpatient and short stay surgical patients with a PACU stay who are admitted Desired direction 95% 90% 85% 80% 75% 70% 65% 60% 55% 50% Last updated 9/6/16 by Mike Platt, James M. Anderson Center Month, patients Pct pended within 5 mins Center line = 72.9% (trial) Control limits Goal (66%)

Unit/Dept. Calls TT for a Transport Unit/ Dept.(limited) Request Transport via Order Entry (RDE) Transport Tracking Flow Process with TeleTracking System Pages Next Available Escort Closest to the Origin Zone Escort Receives Page and Calls System (2-9616) Call is Accepted and Goes into Dispatched Mode Escort Arrives at Unit/Dept. of Origin Proper Transport or Patient is Set Up and RN is Notified, Escort Call System to Go In-progress Pending Calls in System Transporter notifies system of any delays Idle till next Request Escort becomes Idle Patient Is Received by Receiving Unit/Dept. Escort calls System Call is then Completed

Average Minutes ~ Request to Completed I2S2 Patient Escort Improvement Project 40 39 38 37 36 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 19 18 17 16 15 38 23.7 23.5 23.9 23.4 23 22.722.7 22.9 22.1 22.122.1 Baseline 38 Minutes with Manual Dispatch process Automated Dispatch Process 9/4/2006 9/18/2006 10/2/2006 Cancel after 15 minutes 10/16/2006 10/30/2006 23.6 23.6 23.8 23.1 11/13/2006 Updated February 4, 2008 Aditional Staff on Friday 11/27/2006 24.7 12/11/2006 23.9 23.4 Goal 20 Minutes 12/25/2006 PDSA Ramp Reschedule Pt Delays Peri-op PDSA Ramp 22.122.122.022.0 1/8/2007 Supervisor Team Lead Assess & Dispatch 1/22/2007 20.7 21.0 21.3 20.920.8 20.8 20.5 2/5/2007 2/19/2007 Weekend 3/4/2007 Weekend Alert/ Notification Staffing Adjustment 19.7 19.5 18.618.5 18.7 18.518.518.6 18.819.0 18.8 18.9 18.5 18.7 18.3 18.4 17.8 17.5 17.7 17.717.8 17.0 17.1 16.5 16.7 17.117.4 17.217.217.2 16.9 17.1 17.4 17.5 17.2 17.317.4 17.7 17.8 17.6 18 18.118 17.3 17.1 17.317.217.1 3/19/2007 Weekend Radiology Roundtrip's D/C'd 4/2/2007 4/16/2007 Alert/ Notificatio Key Staff, All Shifts 6 Months of Improvement 4/30/2007 5/14/2007 5/28/07 Week of Training for Alert/ Notificatio All Staff, All Shifts 6/11/07 Sustainability Measures Further Reinforced & Solidified 6/25/07 7/9/07 7/23/07 ER Data Feedback 8/6/07 8/20/07 ER Delay Data Collection 3-Sep 9/17/2007 A6S All D/C's PDSA Ramp Begins 9/23/2007 10/7/2007 MRI Rooms #'s Added 10/21/2007 11/3/2007 11/18/2007 D/C's Improvement Project Spread to A6N 12/2/2007 12/16/2007 D/C's Improvement Project Spread to A3N & A7 Almost 11 Months of Sustainability (n = 65,000 trips) 12/30/2007 Temp Handoff Process Audit 100% 1/13/2008 1/27/2008

FY17 Operations Management Scorecard OBJECTIVE: Optimize use of facilities and staff and improve patient flow to achieve 20% greater utilization of existing assets Site of Care Sub-Domain Measure FY15 FY16 FY17 Target July Aug Sept Q1 Q2 Q3 Q4 '16 TOT 2016 In-Patient Producti vity (Clinici Physician wrvu/clinical FTE: % Divisions above the 75th Percentile (Pediatrics) Physician wrvu/clinical FTE: % Divisions above the 55% 78% 65% 75% 55% 33% 65% 56% 65% 67% 62% 52% divisi on specif an) 75th Percentile (Surgical Services) ic Pt. Services = Hours per Patient Day 95-105% (Target) Space Utilization % Occupancy (All CCHMC w. sub-locations) 81% 77% 71% 68% 74% 71% tbd Critical Care - PICU 80% 78% 75% 65% 68% 69% Critical Care - CICU 75% 70% 75% 84% 87% 82% Critical Care - NICU 90% 89% 93% 82% 93% 92% Acute Care - Main Campus Peds 80% 75% 76% 70% 73% 73% Acute Care - Liberty Campus 50% 35% 30% 33% 34% 32% Acute Care - CBDI 85% 89% 71% 62% 67% 66% Specialty Care - TCC 91% 87% 73% 64% 86% 74% Specialty Care - Rehab 78% 77% 81% 73% 68% 74% Specialty Care - Psych (inpatient only) 83% 83% 61% 69% 86% 72% Flow Critical Flow Failures: Total 1585 8 19 112 139 Holds in the ED 82 9 0 0 0 0 PACU Overnight Holds 102 4 0 0 0 0 Patients in Other Overflow Units - 7 0 0 2 2 Patients Using ICU Bed 182 156 8 6 3 17 Psych Patients Not on Primary Unit 525 1220 0 12 106 118 HemOnc/BMT Patients Not on Primary Unit 109 188 0 1 1 2 System Transfer Delays: Percent of patients delayed 32% 27% 23% 24% 20% 22% 32% (20% ) % of Patients waiting > 2 hours to transfer from the ICU 62% 65% 58% 67% 65% 63% 60% to an inpatient unit % of ED Patients Waiting 1 hour or more for admission 23% 18% 11% 14% 12% 12% 32% Percent of PACU transfers to inpatient units at Base 34% 26% 22% 22% 16% 20% 33% >waiting 20 minutes or more Readmissions - 7 day all cause 4.6% 4.7% 4.6% 4.4% % of patients discharged within 2 hrs of being Medically Ready 82% 80% 86% 86% 85% 86% 80%

FY17 Operations Management Scorecard OBJECTIVE: Optimize use of facilities and staff and improve patient flow to achieve 20% greater utilization of existing assets Site of Care Sub-Domain Measure FY15 FY16 FY17 Target July Aug Sept Q1 Q2 Q3 Q4 '16 TOT 2016 Outpatient Space Utilization % Space Utilized (Tot mins of room usage / avail room mins) 67% 71% 72% 68% 70% 70% 70% 70-85% Flow Percent of clinics that start on time (across all locations) 62% 63% 65% 64% 62% 64% 64% 95% Access: Wait for 3rd next available appointment for new visits - % Divisions <=10 days (under development) 66% 61% tbd Productivity Pt. Services = OR Worked Hours to OR Case Hours***'**** 6.16 5.83 6.8 (20% ) Space Utilization OR Utilization Rate - Base 74% 75% 76% 76% 74% 75% 75% 75% OR Utilization Rate - Liberty 60% 64% 67% 62% 64% 64% 64% 65% Block Time Utilization - Base 72% 75% 72% 75% Block Time Utilization - Liberty 66% 72% 74% 75% Flow Percent of first cases that start on time 65% 76% 75% 77% 77% 76% 70% OR Flow Failures: Total # of delayed or canceled surgery due to bed capacity failures 131 17 3 0 1 4 0 Flow Median Length of Stay (Hours): Base - Admits 4.62 4.61 4.22 4.40 4.20 Median Length of Stay (Hours): Base - Discharges 2.90 3.04 2.78 2.93 2.40 Median Length of Stay (Hours): Liberty - Admits 4.20 4.42 3.63 4.08 3.83 Median Length of Stay (Hours): Liberty - Discharges 2.08 2.27 1.90 2.08 1.80 % of Patients Left Without Being Seen: Base 3.01% 3.60% 0.71% 1.80% 2.26% 1.63% 2% % of Patients Left Without Being Seen: Liberty 1.15% 2.23% 0.39% 1.25% 1.85% 1.24% 2% Time to First MD (Minutes): Base 53 53 30 40 50 Time to First MD (Minutes): Liberty 43 40 24 33 50 Flow Flow Flow Failures: % of ED patients waiting 60 minutes or more for admission to College Hill Flow Failures: % of ED Patients Waiting 60 Minutes or More for Admission to A4C2 - Adolescent Psych Psych Flow Failures: Total # of Psychiatry Patients Placed Outside of Their Primary Unit Flow Failure: # of Patients N-TUC (Not Taken Under Care) Due to Inability to Staff (SUSTAIN) 58% 45% 24% 39% 38% 34% 42% 18% 7% 0% 13% 0% 4% 32% 525 1,220 0 12 106 118-1 3 0 1 0 1 0

Flow as a Safety Initiative Prediction Framework for Safety Getting the Rights Right Right Diagnosis and Treatment Right Patient in Right Bed Location Right Nursing Staff and Staffing Expertise Disease Specific Expertise Equipment Expertise Best Care Model Requires ability to Predict future needs, and manage present capacity - control variability Operations Management techniques to understand and manage variability are the key to success

Anticipated Recovery Clinical status Admission Assessment Systematic identification & Mitigation Early Warning Score Medical Emergency Team Effort needed to return to recovery CPR Brady Hospital Pediatrics 2014 Time

System that improved situation awareness and reduced untreated clinical deterioration would reliably: Proactively identify patients at risk Through PEWS, gut feeling ( watchers ), high-risk therapies, etc. Mitigate risk on the unit through primary team With specific, time-bound plans and predictions Escalate risk that is not fully addressed Through rapid response teams and scheduled huddles Brady Pediatrics 2013

Situation Awareness 1. Gather Information Perception What? 2. Recognize & Understand Comprehension So What? 3. Anticipate Projection What Now? Decide Act Brady Hospital Pediatrics 2014

Situation Awareness Model Family concerns Bedside Team Microsystem Team Organization Team High risk therapies Intern Watchstander Senior Resident MRT PEWS>5 Watcher Bedside nurse Watchstander PCF/Manager Safety Team (MPS and SOD) at 800, 1600 & 100 Communication concern Attending Reliable escalation of risk Rapid assessment and communication with primary team

Patient List Screen

Huddles Short, structured briefings designed to: look back on recent events look forward to upcoming events/emerging threats We integrate 3 tiers of huddles: Microsystem (e.g. general pediatric unit) Mesosystem (e.g. inpatient system) Macrosystem (organizational) Goldenhar BMJ Quality and Safety 2013

3 Level High Reliability Huddle System MICRO LEVEL (Unit Huddle) Look back: individual providers report on unexpected events, medical response team calls Look forward: individual providers report on individual patients at risk for safety events Integration: charge nurse considers overall unit status, planned discharges, staffing needs MESO LEVEL (Inpatient Huddle) Look back: charge nurses from each microsystem report on unexpected events, transfers to higher levels of care Look forward: individual microsystems report on higher risk patients in mesosystem, overall unit status Integration Manager of Patient Services (MPS) works with charge nurses to develop plans and predictions for highest risk patients, develop capacity plan through system, predict and mitigate experience failures MACRO LEVEL (Daily Operations Brief) Look back: mesosystem leaders report on unexpected outcomes over last 24 hours, resolution of concerns raised at previous brief Look forward: mesosystem leaders predict and plan for big issues of day with focus on problems at intersections of mesosystems Integration: administrator of the day identifies responsible party(ies) for each concerns and sets clear follow-up

Proactive escalation through mesosystem huddle Three times daily discussion of any concerns not fully addressed and any predicted MRTs Includes: Charge nurse from each unit Nurse manager Senior attending Safety Officer Nurse manager and safety officer coach charge nurses

Safety officer of the day (SOD) Attending-level physician with: gray hair Clinical expertise Organizational expertise Gravitas Skilled communicator and teacher OR maybe? More junior physician with clear access to and authority given from senior leader (e.g., Chief of Staff, CMO)

Robust Planning Tool Identifying the problem or concern Making responsible parties aware Forming a plan Predicting an expected outcome Setting a deadline Deciding on an escalation plan if outcome is not met

Brady Pediatrics 2013 Defined as any patient that is transferred from unit to ICU and within 1 hour is: Intubated Placed on inotropes OR Given 3 or more fluid boluses

3/1/2010: Inpatient Situation Awareness 9/1/2010: Surgery Situation Awareness Last 8-10 Years Rate has Decreased 80%

Staff were busy and saw Joshua in brief snaps shots of time. The one constant throughout these critical hours was my wife and I. Our observations of Joshua were made with a full understanding of the history and context of his birth and on a continuous basis. As well as knowing their child better than anyone else, parents of children in hospital will always have this continuity and context on their side. BMJ Qual Saf. 2015 Mar;24(3):182-3. doi: 10.1136/bmjqs-2015-003951. Epub 2015 Jan 29

Journals from families

Conceptual Model: How families identify and communicate about child s evolving illness in hospital Familyfacing factors Evolution of expertise: -Experience with child and child s illnesses -Gateway skills: learned strategies for navigating and communicating -Advocacy skills and confidence Roadblocks and challenges to applying expertise: -Complex system barriers (long processes, large teams) -Medical cultural barriers -Emotional barriers (stress, fear, exhaustion) Communication strategies and skills: -Face-to-face communication -Facilitating a shared understanding with clear and explicit plan of care There s Parent not really anything else for me, except to watch expertise him. You feel like Hospital that s all you do is focus on him and you are frightened system of because We need a plan. And I kind care it s just of joke that, OK, if Partnership the two of you. you don t have the plan, I need a plan to make with clinicians a plan. Shared understanding of child and family status and needs Factors at intersection between families and clinicians Elements of a successful partnership: -Checking assumptions from textbook -Listening and collaboration skills -Respect and empathy Tension with expertise and role: -Unclear role for families that provide care at home -Occasionally competing expertise -Many new faces of clinicians Clinician/system facilitators of improved navigation: -More direct access to the right doctor -Tools/technology to record and share plan -Better continuity of care team and problem list

Interventions checklist Item Definition Example Briefing The charge nurse describes situation fully and allows for feedback Charge Nurse: Our watcher is a little 22-month-old. He s a short gut. He just came down from PICU two days ago. He was there for over a week - line infection. They just stopped antibiotics last night and he has spiked again. Verbalize expected time frame Escalation plan is predicted A clear and specific time frame is stated and agreed to during huddle A clear escalation plan (most commonly calling MRT) is stated and the need for it is explicitly predicted Charge Nurse: We are going to re-evaluate at 5. Charge Nurse: If he bradys or is difficult to arouse again, we will call an MRT and get him to the PICU.

CBDI: Quantitative Measures Identify Volume

July_11 (n=1247) Aug_11 (n=1094) Sept_11 (n=1122) Oct_11 (n=1238) Nov_11 (n=1295) Dec_11 (n=1380) Jan_12 (n=1526) Feb_12 (n=1362) Mar_12 (n=1434) Apr_12 (n=1550) May_12 (n=1352) Jun_12 (n=1410) Jul_12 (n=1501) Aug_12 (n=1415) Sep_12 (n=1240) Oct_12 (n=1280) Nov_12 (n=1058) Dec_12 (n=1136) Jan_13 (n=1228) Feb_13 (n=1081) Mar_13 (n=1234) Apr_13 (n=1314) May_13 (n=1368) June_13 (n=1246) Jul_13 (n=1695) Aug_13 (n=1652) Sep_13 (n=1456) Oct_13 (n=1606) Nov_13 (n=1473) Dec_13 (n=1414) Jan_14 (n=1553) Feb_14 (n=1426) Mar_14 (n=1774) Apr_14 (n=2157) May_14 (n=2222) Primary BSI Rate per 1000 line days CBDI: Quantitative Measures Identify Acuity 4.0 Primary BSI Rate in CCHMC CBDI (July 2011-May 2014) 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 Month Monthly Primary BSI Rate Median BSI rate Control Limits

Blood Stream Infections per 1000 Line Days Jul-11 (n=1247) Aug-11 (n=1094) Sep-11 (n=1122) Oct-11 (n=1238) Nov-11 (n=1295) Dec-11 (n=1380) Jan-12 (n=1526) Feb-12 (n=1362) Mar-12 (n=1434) Apr-12 (n=1550) May-12 (n=1352) Jun-12 (n=1410) Jul-12 (n=1501) Aug-12 (n=1415) Sep-12 (n=1240) Oct-12 (n=1280) Nov-12 (n=1058) Dec-12 (n=1136) Jan-13 (n=1228) Feb-13 (n=1081) Mar-13 (n=1234) Apr-13 (n=1314) May-13 (n=1368) Jun-13 (n=1246) Jul-13 (n=1695) Aug-13 (n=1652) Sep-13 (n=1456) Oct-13 (n=1606) Nov-13 (n=1473) Dec-13 (n=1414) Jan-14 (n=1553) Feb-14 (n=1426) Mar-14 (n=1774) Apr-14 (n=2157) May-14 (n=2222) Jun-14 (n=2143) Jul-14 (n=1437) Aug-14 (n=1680) Sep-14 (n=1560) Oct-14 (n=1678) Nov-14 (n=0800) Stressed Microsystem: CBDI Outcome 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 Primary Blood Stream Infection Rate in the Cancer and Blood Disease Institute (Infections / 1000 line days) Acute increase in census, phase 1 patients, relapsed refractory patients, national and Increased percentage of floating and inexperienced nursing Implementation of: Identification of high risk patients Improved daily CHG bathing/oral care compliance Increased awareness of high BSI-risk patients Assistance for nurses performing high BSIrisk procedures System to improve allocation of resources 0.0 Month (number of line days) Monthly Blood Stream Infection Rate Average Rate of Blood Stream Infections Control Limits

Stressed Microsystem: CBDI Mitigate Interventions Unit Inpatient System Serious Harm: BSI Stabilization of current processes 2 person dressing changes Daily prevention standard rounding with real time feedback Increased education to float staff and review of CVC care by all staff Physician engagement in BSI prevention work Pre assignment of float staff Organization Implementation of a system to improve allocation of resources and support to deescalate system stress Implementation of a experienced based knowledge bonus

Stressed Microsystem: CBDI Key Findings Decrease in primary BSI rate from 1.8 primary BSIs per 1000 line days to 0.21 BSIs per 1000 line days. Prolonged stress in complex systems with high-risk patients can contribute to increased BSI rates. Identifying key processes and executing mitigation strategies at the unit, microsystem and organizational levels can stabilize outcomes when under stress. Building on continued learnings from CBDI helped to identify the next stressed microsystem: NICU.

Stressed Microsystem: NICU Mitigate Interventions Unit PICC Team Targeted rounding Prediction (Watchers) Multi disciplinary Huddles 4 times per day Inpatient System Leadership Prevention Standard Rounds: all patients on all units. Weekly report out on all serious harm in leadership meeting. Pre-assignment of float staff. Organization Implementation of a system to improve allocation of resources Organizational support to deescalate system stress Implementation of a experienced based knowledge bonus Added FTE s

System Level Key Diagram Team Name: Stressed Microsystems Team Date: September 14, 2015 Revision: 11 Primary Key Drivers Global Aim Develop a system to identify, mitigate and predict microsystem stress in order to prevent serious harm (and other undesirable outcomes). Right factors (quantitative* and qualitative) are identified, validated, then utilized Timely access to the right data representing right factors Effective data analysis, review and data driven decisions Roles and processes for management and decisionmaking are clear Sub-Projects Identification and validation of quantitative factors Volume Staffing Patient Acuity Identification and validation of quantitative factors Duration Stressed System Identification and validation of qualitative factors Assessment of stress level by nursing Appropriate oversight and support by leadership Mitigation and Prediction Strategies KEY Gray box = completed intervention Green box = what we re working on right now White box = future work

Quantitative Factors: Staffing Predict Pick correct shift Add requests for needed staff

Quantitative Factors: Staffing Predict NHPPD

NICU: Qualitative Pilot Identify Family Stress

Qualitative Scoring Predict IS YOUR UNIT..... GREEN: Routine risk/stress level within normal variability met by daily operations YELLOW: Minimal risk/stress level with some variability met by minor operational adjustments ORANGE: Moderate risk/stress level with high level of variability, predicted or unanticipated that require considerable number of interventions and support RED: High risk/stress level with a high amount of variability predicted or unanticipated, that require a large amount of intervention and support but very challenging to meet.

Microsystem Stress: Qualitative Predict Capturing Impact of Stress on Staff Current Process Charge nurses determine overall color rating each shift with input from staff and key roles on their unit Rating is entered into automated system every 4 hours and comment entered if rated orange or red Comments provide information for resource allocation Comments also give insight into why the unit feels stressed Shift and aggregate data is utilized for real-time decisions and weekly trending

System Level Qualitative Data Predict Can see the entire day in 4 hour blocks

Inpatient Unit Level I Interventions Green Yellow Orange Red Attend bed huddle and Safety meeting. Match clinical resources to patient acuity and care needs. Offer any additional staff to the house. Continue with standard unit practices. Predict & plan for admissions, discharges, and other flow factors today & looking forward. Smooth resources & post shifts not at core and also ask clinical staff and standby to pick up extra shifts based on volume. D/C patients that meet criteria in a timely manner. Predict operational vacancy and staffing impact short term and long term. Strategize for increased RN hiring and orientation for large numbers of open positions. Utilize creative methodologies that expand beyond the unit. Assess available clinical resources and ability to care for patients based on acuity and care needs. Ask available current staff to work additional 4 hours Ask staff to work extra for defined shift with resource need. Ask available current staff to work an additional 4 hours. Request appropriate SRU/float staff for support such as RN, PCA, HUC, and Sitter. Evaluate the need to move support roles into charge or the direct care role. Unit level clinical and medical operational leaders to work on screening admissions and patient placement in collaboration with flow coordinators/mps lead. Make AVP aware of staffing and unit operations. Increase leadership rounding. Evaluate need to move manager into charge or direct care roll Evaluate the need to cancel OPT/Education if resource needs are not satisfactorily met. Evaluate the need to move a manager into charge or direct care role. Evaluate the ability to adjust Assignment with Preceptor/Orientee for Phase IV orientees close to completing orientation. Temporarily increase staff FTE as open positions filled Evaluate the need to cancel unit meetings or cancel staff attendance to department and division meetings. Evaluate the need for additional support from Pastoral services or other resources Consider purchasing food for staff. Evaluate the need for Organizational Support if Ongoing Orange. Unit level clinical and medical operational leaders discuss/determine need to reschedule pre-admissions and/or defer pts. Unit level clinical and medical operational leaders discuss ability to stop admissions and/or transferring patients to another facility. Evaluate the need for the Director to take charge/support role or continue with unit leadership activities to address unit operations. All hands on deck and attending meetings and other activities based on patient care needs and safety being met. All meetings and other non clinical activities cancelled and resources reassigned

Inpatient Unit Level II Interventions Green Yellow Orange Red Maintain current processes with distribution of SRU/Float Resources. Consider microsystems that have been stressed for over a week in distribution of resources. Include AVP/VP in discussion around support for unit microsystem. Implement all applicable interventions denoted at Orange level. Evaluate the ability to partner with another unit with similar competency and has a lower volume or more positive operational vacancy. Evaluate the need to pre-assign some SRU resources to promote consistency in support and decrease the staffing Evaluate the need for a special pay program based on prediction of gap. Increase Month s Team support. Evaluate the need for a special pay program based on prediction of operational vacancy and longer term staffing gaps. operational vacancy and longer term staffing gaps. Support manager and educators working extra clinical shifts. Evaluate the need to increase RN and Allied Health resources permanently related to new trends in ADC. Implement if appropriate. Evaluate the ability to cancel or hold off on accepting Destination and Tertiary Patients depending on clinical need, impact on program, etc. Evaluate the need for the use of Supplemental staff. Post positions if needed. Provide support to providers to assist with rounding and other clinical work.

From Disparate Data HIGH RELIABILITY DATA STRATEGY To Actionable Intelligence Data reported via multiple mechanisms due to sources and systems Data is reported as a single point in time Data is retrospective with little ability to identify opportunities to act Frequency of data review is reviewed monthly or quarterly Budgeted AWC AWC % Occupancy To Budgeted ADC % Occupancy to Capacity 52.8 50.9 96.4% 86.2% Performance report cards sent several weeks following monthly/quarterly close Data exists in one place, or automatically linked Data is trended over time with centerlines Data are routinely being used to predict performance and drive real-time decisions Frequency of data review is weekly or daily Performance report sent ahead or accessed real-time during huddles and other planning meetings

Unit level harm and stress Time Period of Stress Data Special Cause Last Updated 3/9/2015 by A. Anneken, James M. Anderson Center for Health Systems Excellence

Microsystem Dashboard CONCEPT Microsystem Outcomes Composite Measure Microsystem Key Processes (Nursing) Capacity Demand DRAFT Some measures are not completely operationalized. Measures are owned by various groups.

Microsystem Stress Report Predict B4 NICU 59 89.5% 52.8 52.2 98.9% 88.5% 18.2 17.0-1.2-6.6% 9.0% 685.1 12.8% 740 13.8% 7 1.4% 4.8% 0.0% 4.8%

Week of: 9/11/2016 to 9/17/2016 Microsystem Stress Report Location Unit Population Capacity % Budgeted Occupancy Budgeted ADC Demand - Occupancy ADC % Occupancy To Budgeted ADC % Occupancy to Capacity Budgeted Bedside Care NHPPD Actual Average Direct Care NHPPD Variance to Direct Care NHPPD % Variance of Direct Care NHPPD Capacity - Staffing % Operational Vacancy Hours of Float Staff % Float Staff Hours Orientation % Orientatin Hours # of >13 hour Shift % 13 hour Shifts CN Assessment % Orange Shifts % Red Shifts % Orange and Red Shifts A3N Surgery 20 82.5% 16.5 14.3 86.7% 71.5% 11.6 13.0 1.3 11.6% 10.69% 97.4 11.4% 112 13.1% 2 2.2% 0.0% 0.0% 0.0% A3S TCC 24 91.7% 22.0 19.0 86.1% 79.0% 16.0 17.0 1.0 6.4% 19.43% 140.4 8.9% 260 16.5% 4 2.4% 7.1% 0.0% 7.1% A4C1 Rehab 12 69.2% 8.3 6.6 80.0% 55.4% 13.7 18.5 4.8 35.4% -7.50% 19.6 5.8% 0 0.0% 0 0.0% 0.0% 0.0% 0.0% A4N Transplant/Surgery 24 85.4% 20.5 15.0 73.3% 62.6% 13.1 14.9 1.8 13.9% 7.54% 0.9 0.1% 96 9.2% 1 0.9% 0.0% 0.0% 0.0% A4S GI/Colorectal 24 81.7% 19.6 15.5 79.0% 64.5% 11.6 12.9 1.4 11.7% 5.68% 28.6 2.7% 44 4.2% 1 0.8% 0.0% 0.0% 0.0% A5C Hem/Onc 32 90.4% 28.9 27.2 94.1% 85.1% 16.0 14.7-1.3-8.0% 2.67% 375.5 19.6% 384 20.0% 2 1.0% 0.0% 0.0% 0.0% A5S BMT 36 85.7% 30.9 19.0 61.4% 52.6% 17.5 18.4 0.9 5.4% 22.32% 0.2 0.0% 437 26.7% 1 0.5% 0.0% 0.0% 0.0% A6C Cardiology 17 88.2% 15.0 13.1 87.5% 77.2% 16.0 16.9 0.9 5.7% 23.08% 134.7 12.1% 216 19.4% 4 3.5% 2.4% 0.0% 2.4% A6N Adol. Medicine 24 72.9% 17.5 18.5 105.7% 77.1% 13.2 19.5 6.4 48.6% 2.67% 93.1 9.7% 64 6.7% 3 2.7% 0.0% 0.0% 0.0% A6S Child Medicine 24 72.9% 17.5 18.0 102.9% 75.0% 12.6 11.1-1.6-12.4% 9.42% 90.7 8.5% 0 0.0% 2 1.6% 4.8% 0.0% 4.8% A7C1 Complex Pulmonary 11 76.4% 8.4 8.2 97.8% 74.7% 12.9 13.0 0.1 0.8% 13.81% 53.1 13.6% 72 18.4% 1 1.8% 0.0% 2.4% 2.4% A7C2 CRC/Diabetes 11 81.8% 9.0 5.0 55.0% 45.0% 12.7 16.6 4.0 31.2% 40.18% 0.0 0.0% 0 0.0% 0 0.0% 0.0% 0.0% 0.0% A7NS Neurosciences 41 70.0% 28.7 27.3 95.2% 66.7% 15.1 17.2 2.1 14.0% 9.86% 334.5 18.2% 208 11.3% 5 2.5% 0.0% 7.1% 7.1% B4 NICU 59 87.8% 51.8 55.0 106.3% 93.3% 18.4 18.0-0.3-1.9% 9.75% 1087.5 18.7% 456 7.8% 18 3.1% 9.5% 0.0% 9.5% B5CA Complex Airway 11 66.4% 7.3 6.2 84.5% 56.1% 15.8 18.2 2.5 15.6% 1.54% 0.0 0.0% 0 0.0% 0 0.0% 0.0% 0.0% 0.0% B5CC PICU 35 85.0% 29.8 25.8 86.8% 73.7% 26.1 25.9-0.2-0.7% 18.37% 244.6 6.5% 400 10.7% 6 1.7% 0.0% 0.0% 0.0% B6HI CICU 25 80.8% 20.2 22.1 109.3% 88.3% 25.8 24.6-1.2-4.6% -12.73% 579.5 18.7% 496 16.0% 9 3.0% 16.7% 21.4% 38.1% LA4-1 Lib CBDI 10 49.6% 5.0 1.4 28.3% 14.0% 16.2 37.0 20.8 128.6% 0.00% 0.0 0.0% 0 0.0% 0 0.0% 0.0% 0.0% 0.0% LA4-2 Lib Hosp Med 32 45.0% 14.4 10.5 72.6% 32.7% 14.1 17.4 3.3 23.5% 0.00% 0.0 0.0% 0 0.0% 0 0.0% 0.0% 0.0% 0.0% Total 472 78.6% 371.2 327.7 88.3% 69.4% 3280.3 12.1% 3245 11.4% 59 2.0% 2.1% 1.6% 3.8% Status Criteria Red Yellow Green < 90%; > 105% 90% - 95%; 100% - 105% 95% - 100% < -5% > 12% > 15% > 10 % Microsystem Stress Report

How Are We Using This Information? Identify Mitigate Predict Guides drill-downs into the data, why are the number high or low and do we have opportunity? Initiative around sitter use Supports responding to trended data: Increase and/or reissuing RN FTEs Increase SRU RNs preassigned to an area Implement additional staffing interventions Utilize in decision making around distribution of resources from SRU Helps to predict intervention needs and explain current state Trended data helps to show duration

Impact of Growth on Critical Care Bed Needs PICU Growth Bone Marrow Transplant Neurosurgery ENT/ Airway Oncology Organ Transplants How many Critical Care Beds do we need to support growth and effectively utilize our facilities? What will happen if areas exceed their targets? When will we begin to run out of critical care beds? CICU Growth Heart Transplant Cardiomyopathy Adult Cardiothoracic Surgery Non-Surgical

Short Term Bed Prediction The ability to predict inpatient bed demand aids in determining appropriate clinical staffing and planning for overflow needs The scope of this project is to predict census, admissions, and discharges on seventeen inpatient units providing 10 day view of bed demand We have flow failures each week. Could we have predicted these failures and intervened? Can we insure that we have adequate staffing and resources available for our future demand? 83

Critical Care Bed Growth Analysis

Make it Personal Don t let the Data Drown out the Dream Stories not Statistics Names and Faces Accountability is Personal Group Responsibility & Collective Mission/Vision Cincinnati Children s Hospital Medical Center 2013