A21/B21: IHI 23rd Annual National Forum on Quality Improvement in Health Care Carolyn Sanders, RN, PhD, NEA-BC Vice President, Patient Services & Chief Nursing Officer Lorna Prutzman, RN, MSN Executive Director, Cardiac & Vascular Services These presenters have nothing to disclose. December 4-7, 2011 Objectives Use the principles of real-time capacity demand management Implement real-time demand capacity strategies in your facility Develop an appropriate real-time capacity demand management metric dashboard 1
The View from Where We Started UCH Overview Only academic medical center in the region 400+ beds 20,000 annual admissions and growing 700,000 outpatient encounters and growing 65,000 annual ED visits ADC of 9 inpatients Over 5,000 staff and faculty Magnet status for 9 years 2011 UHC Quality Award winner #1 hospital in Denver US News & World Report 2
Background Capacity issues began in 2001 It s an ED problem National crisis Previous failed attempts to improve No measurable outcomes Realized the need for scientific theory, leading to 3
Imperatives for Change July 2009: 15 inpatient nurse managers, house managers and case managers Led by CNO Mandated education relative to capacity management Immediate implementation Critical success factor = incentive Costly diversion (patient satisfaction/ community reputation) Purpose of Throughput To cycle patients through a hospital s fixed resources (beds, procedure rooms, imaging) more effectively and efficiently 4
Cost of Divert Urban teaching 95% CI: $1,186/hr revenue ($696 $1,598) Suburban teaching 95% CI: $5,840 revenue UCH goal 5 hours monthly: $5,930 YTD UCH lost $33,682/$8,420 In 2007 >$1.2M Source: Chanmugam, Kirsch, Mollin, Patel, Pham (2006). The Effects of Ambulance Diversion. Academic Emergency Medicine 13, 1220-1227. Every system is perfectly designed to produce the results it produces. 5
Structures for Change Leadership accountability identified Organization/Unit Daily 0800 bed-board meeting Weekly capacity management meeting Established buy-in across organization Monthly steering committee meeting Big picture big decisions Management Principles Predict capacity each day based upon reality Predict demand each day based upon reality AND historical data Match your service capacity to your patient demand New lens Daily predictions and plans Establish real-time dashboard Key operational cycle times Measure and monitor 6
The Science and Art of Operations Management and Variability Capacity FY10-FY12 Q1 (Discharges) Managers Month of FY10 Avg FY11 Avg Jul Aug Sep FY12 Q1 Avg Shiskowsky 6E 78% 63% 62% 71% 58% 64% Heilman 6W 67% 65% 57% 43% 68% 56% Limon 7E 64% 63% 86% 71% 74% 77% Limon 7W 65% 69% 67% 86% 63% 72% Hagman Rehab 8E 94% 86% 90% 100% 95% 95% McDevitt 8W 62% 59% 81% 67% 79% 76% Baker 9E GS 71% 68% 67% 48% 42% 52% Baker 9W - P 77% 73% 67% 86% 68% 74% Zwink 11EW 74% 73% 71% 67% 79% 72% Bonini 10E 59% 53% 52% 71% 47% 57% Bliton 12E -CTRC 66% 42% 52% 52% 37% 47% Hagman 12W 77% 72% 57% 76% 79% 71% Williams 5W - AIOB 51% 37% 38% 57% 42% 46% Overall Avg/Mo 64% 63% 65% 69% 64% 66% 7
Demand FY10-FY11 Q1 (Admits) Managers Month of FY10 Avg FY11 Avg Jul Aug Sep FY12 Q1 Avg Shiskowsky 6E 57% 32% 19% 10% 26% 18% Heilman 6W 69% 64% 76% 71% 53% 67% Limon 7E 68% 45% 38% 29% 26% 31% Limon 7W 47% 31% 14% 19% 16% 16% Hagman 8E Rehab 84% 64% 71% 90% 89% 84% McDevitt 8W 63% 61% 52% 43% 68% 55% Baker 9E-GS 64% 48% 33% 5% 21% 20% Baker 9W-P 72% 58% 67% 67% 74% 69% Zwink 11EW 63% 45% 52% 33% 58% 48% Bonini 10E 32% 30% 24% 19% 5% 16% Bliton 12 CTRC 86% 71% 71% 57% 74% 67% Hagman 12W 94% 61% 57% 62% 53% 57% Holden Burn 82% 83% 86% 90% 100% 92% Dzialo CICU 83% 80% 90% 95% 95% 93% Dzialo MICU 79% 80% 95% 86% 89% 90% Waite Neuro 74% 76% 86% 76% 68% 77% Paulson SICU 81% 74% 76% 67% 79% 74% Williams AIOB Birth 51% 21% 19% 33% 16% 23% Overall Avg/Mo 69% 57% 57% 53% 56% 55% Date: 3/4/2011 Unit System Plans Pred Pred D/Cs & Actual Adm/ Actual Trans D/Cs Acc'y Trans Trns Acc'y Pred Use Actual Use Open Out Out of In In of Status of D/C of D/C Success? Unit Beds <14:00 <14:00 Pred <14:00 <14:00 Pred at 14:00 Lounge Lounge Red Unit Plan: Y/N Result Reason 6E MDSS 0 4 4 y 5 1 n -1 3 623-1 (pft's earlier and dc) n cardiology team cxl'd the discharge, then wrote dc orders at 18:00 - ( of note, same scenario with pt in 635) 6W TXM 0 6 8 y 0 3 n 6 4 7E INMD 0 4 2 n 4 0 n 0 4 7W NUR 0 2 1 y 0 1 y 2 2 8E RHB 3 3 2 y 0 0 y 6 1 8W BON 0 4 6 n 1 1 y 3 0 9E GSRG 0 3 3 y 0 0 y 3 9W PLM 0 2 2 y 0 1 y 2 0 11 ONC/BMT 0 3 3 y 3 1 n 0 1 10 CARDS 0 3 3 y 5 0 n -2 12E CTRC 0 1 4 n 1 1 y 0 12W MED 1 4 2 n 2 1 y 3 1 BURN 0 0 0 n 0 0 y 0 1009 - lovenox set up for dc, 1018 - wean 02 (primary RN), y 1009 dc @ 12:10; 1018 dc @ 13:45. Nice! CICU 1 0 1 y 2 0 n -1 1006 orders to 7w + 1007 orders to SD n orders written on 1006, pt not moved (due to no bed availability on 7w), 1007 moved out to 12west around c.o.s. this a.m. to make room for cath lab pt. The pt was reportedly supposed to be SD status (orders written at 07:10) but in a floor bed. Later moved to 12e. MICU 0 0 0 y 1 0 y -1 213 (dc insulin gtt), 209 (floor orders for 7w), 202 to 629 to accom MET n 213 - no orders, 209 moved @ 18:40, 202 to go transfer to another facility (did not happen until 18:30) NEUS 0 0 1 y 1 0 y -1 send NEUS to sicu. n 1st case complicated, necessitated NEUS. NEUS able to get floor orders on two pts (1 before 14:00) to accommodate. SICU 0 2 1 y 2 2 y 0 dc, sd (cox to 6w, 220 to 6w) unanticipated code on 6tx needed sicu bed. AIOB 7 6 5 y 3 0 n 10 GI Lab 0 Access Ctr ED 18-18 6e x4, 7e x4, cards x4, 11, 12wx2 CVHD 2-2 12e, NEUS PACUIP 3 2-3 sicu x2, 8w x1 PACUOP 0 0 08:00-14:00 TOTALS 47 48 30 12 16 0 Prediction for Unit Successful Prediction: 0 to 5 + or - 1 6 to 10 + or - 2 11 to 15 + or - 3 16 to 20 + or - 4 8
Date: 3/15/2011 Unit System Plans Pred Pred D/Cs & Actual Adm/ Actual Trans D/Cs Acc'y Trans Trns Acc'y Open Out Out of In In of Status Pred Use of Actual Use of Success? Unit Beds <14:00 <14:00 Pred <14:00 <14:00 Pred at 14:00 D/C Lounge D/C Lounge Red Unit Plan: Y/N Result Reason 6E MDSS 1 2 3 y 7 3 n -4 635 - Amy will call to change diet to po, 623-1 (cr), 6w to assist. n 635 d/c'd by 1400, 623-1 cr level ok, but stayed b/c fluid pos. 6w did take ED pts 6W TXM 2 2 3 y 1 3 n 3 1 7E INMD 0 0 1 y 2 0 n -2 2 728 - switch to po meds, 726 - echo (David), 736 - transport to Durango (MT) n 728 did not dc by 2p- continues w/pain and on IV meds, 726- echo done/read early, not sure if going to dc, later dc'd on coumadin at 1745, 736- dc cx- no plan for home iv abx 7W NUR 0 1 2 y 3 0 n -2 0 hold NEUS x1, CN to get dc on mennigitis pt (706)., Suzie to send 713 to rehab. n 713 did dc by 2p, 706 did not DC- febrile overnight (mon noc), NEUS trsfr held 8E RHB 5 0 0 y 1 0 y 4 8W BON 1 2 0 n 3 1 n 0 2 9E GSRG 0 3 0 y 0 0 y 3 1 9W PLM 0 1 0 y 2 0 y -1 0 913 (home health MT) n 913 did not DC by 2p--increased to full liq diet, wanted to watch overnight to see CT output increased 11 ONC/BMT 2 1 2 y 1 1 y 2 1 10 CARDS 0 4 6 n 7 1 n -3 2 1035 (home o2 - RT), 1025 - hickman in IR, 1030 - MS to call MD. n 1025 and 1030 did dc by 2p, 1035 did not DC b/c rheumatology needed to see but was in clinic all day. Pt will still leave tonight (after 1800) 12E CTRC 3 0 1 y 3 1 n 0 12W MED 0 1 1 y 1 0 y 0 0 BURN 1 1 0 y 0 0 y 2 7e CICU 0 2 0 n 0 0 y 2 sd x2 MICU 0 2 0 n 1 0 y 1 6e, dc NEUS 1 3 2 y 0 0 y 4 2 dc, 7w SICU 1 2 0 n 0 1 y 3 sd x2 AIOB 2 5 2 n 2 0 n 5 GI Lab 0 Access Ctr ED 14-14 6e x5, 6w, 8w, 7w, 7e CVHD 4-4 6e, cards x3 PACUIP 4-4 8w x2, 9w x2 PACUOP 0 0 08:00-14:00 TOTALS 32 23 34 11 9 0 Prediction for Unit Successful Prediction: 0 to 5 + or - 1 6 to 10 + or - 2 11 to 15 + or - 3 16 to 20 + or - 4 The Science and Art of Operations Management and Variability 9
Our Dashboard: Where We Started Fiscal Year-End Goal LWBS 5.0% Divert (hrs) 5.0/wk ED Door to Floor (Med Hr) 5.0 Hr Clean to Occupy 44.0% LOS PACU (Avg Min) 124 D/C Time (Med) 1300-1400 FYE FY09 5.30% 21.0 7.0 22.0% 146 1501 The Science and Art of Operations Management and Variability 10
Strategies for Success Establish common, inpatient capacity agenda shared by clinical and operational leadership Establish process to review and refine: Access Capacity Bed-management processes Policies Accountability Align personnel roles to facilitate demand/capacity management structure for change 11
UCH Role Changes Hospital Manager Then: Continuous firefighting with patient placement issues Now: Responsible for system-level plans, coordinates changes to plans throughout the day, conducts bed meeting and provides metrics UCH Role Changes Unit Directors/Managers Then: Responded to crises identified by charge RN Now: Responsible for projecting capacity/demand formulating plan Facilitates structure and process to support successful capacity/demand management culture change 12
UCH Role Changes Charge Nurses Then: Responded to requests and demands for patient placement Now: Monitors patient care, quality, safety and supports staff Assists in identifying bottlenecks and opportunities for improvement Assists with capacity/demand projections UCH Role Changes Physicians Then: Thought to be prime link to solving flow issues Now: Engaged in short- and long-term strategies to achieve successful plans 13
Outcome Improvements Staff and patient satisfaction Quality and safety performance Service performance Financial performance Efficient use of capital Create a blueprint for certainty Teach the Next Generation Monthly capacity management class Includes everyone: Pharmacy EVS Transport Laboratory Over 600 staff trained CEUs offered Respiratory/PT Dietary Clinics 14
Results To Date LWBS Divert (hrs/wk) ED Door to Floor (med Hr) Clean to Occupy LOS PACU (Avg Min) D/C Time (Med) FY09 Baseline 5.3% 21.00 7.0 22.0% 146 1501 FY10 Goal 5.0% 1.25 5.0 44.0% 137 1441 FY10 Actual 4.6% 1.70 6.2 37.9% 140 1437 % Change from Baseline 13.2% 91.3% 11.8% 72.1% 4.2% 24 LWBS Divert (hrs/wk) ED Door to Floor <6 hrs Clean to Occupy % of PACU patients who are placed in inpatient bed within 60 minutes of ready to move timer started D/C Time (Med) FY10 Baseline 4.6% 1.70 49% 44.0% 50.0% 1437 FY11 Goal 4.0% 1.50 65% 50.0% 36.0% 1430 FY11 (6/30/11) Actual 4.5% 6.69 46% 46.0% 31.0% 1433 % Change from Baseline 2.2% 3.9% 7.1% 4.5 38.0% 4 Median Discharge Time 15
Median Discharge Times Fiscal Year Volume % Change Year-Over- Year Median Discharge Time 2009 13,939 1501 % Change Year-Over-Year 2010 15,142 9% 1437 1.6% 2011 15,540 3% 1433 0.3% 2012 YTD 5,230 1447-1.0% Impact of improved median discharge time: FY10 = 252 additional patient days FY11 = 43 additional patient days FY12 YTD = 51 lost patient days Implications for Practice Improved patient flow Leadership a key participant Right patient right bed first time Efficient resource management Interprofessional process Certainty for patients and staff 16
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