Using Data for Quality Improvement Seton 1

Transcription

1 Using Data for Quality Improvement 2015 Seton 1

2 Presenter Disclosure Information Anne Robinson, MS, BSN, RN Seton Network Cardiovascular Analytic and Quality Manager FINANCIAL DISCLOSURE: None UNLABELED/UNAPPROVED USES DISCLOSURE: None 2015 Seton 2

3 Objectives Share how to use facility performance data to identify areas requiring process improvement and how to use the Plan-Do-Study-Act method to improve care Seton 3

4 Changing Healthcare In Today s Healthcare We Cannot Not be Accountable. No Outcomes; No Income 2015 Seton 4

5 Anchorman Logic She gets a special cologne... It's called Sex Panther by Odeon. It's illegal in nine countries... Yep, it's made with bits of real panther, so you know it's good. They ve done studies, you know Seton 5

6 It's a formidable scent... It stings the nostrils. In a good way. Brian, I'm gonna be honest with you, that smells like pure gasoline Seton 6

7 They've done studies, you know 60% of the time, it works every time Seton 7

8 So what do we do with all of this data? NCDR Action Registry NCDR Cath-PCI Mission Lifeline Reports Mission Lifeline System Reports Texas Health Care Information Collection HCAHPS 2015 Seton 8

9 Current Landscape Fee for Service Value Based Purchasing? Bundled Payments - CV Services next? CMS 30-Day Readmission Reduction Program - AMI Fee-for-Service Metrics Value-Based Care Metrics Door to Device times < 90 minutes Change in AMI D2D times compared to 90 minute benchmark Complication rates for PCI 30-day mortality for AMI, PCI Number of HAC/100 inpatient admissions Ratio of appropriate use criteria for PCI Hypertensive CAD pts with BP control Observation status use rates HCAHP Top Box Rate per Cardiac DRGs CAD pts on LDL lowering medications HF patient ED visit rate 2015 Seton 9

10 Financial Impact of Pay for Performance Hospital Adversely Impacted by P4P FY The Advisory Board Company advisory.com 2015 Seton 10

11 Data Presentation Scorecards/Dashboards Physician Buy-In; Preferably Physician Driven Combination of Quality and Utilization Value Based Metrics Benchmarked metrics Individual Performance Score Cards Analytic Department Not Needed 2015 Seton 11

12 Make a Compelling Case to Physicians National Trends Hospital Performance One-on-One, Face-to-Face Meetings Specialty Performance Individual Performance When physicians see their data (and charts), they want to solve problems 2015 The Advisory Board Company advisory.com 2015 Seton 12

13 Monthly STEMI Scorecard June 2015 STEMI Activations June YTD Total ED EMS InPt Other Total ED EMS InPt Other Total STEMI Activations CATRAC STEMI Criteria Met* (%) 60% 57% 67% % 67% 77% 75% -- True STEMI Rate 30% 29% 33% % 30% 46% 25% -- Walk-in Door to Device June Q th 90 th Volume Door to EKG min/% 7/100% 0/100% 7/80% 68% 86% EKG to 324-TIME Door to Device Time Door to Device < 90 min % 100% 100% 100% 97% 100% FMC to Device June Q Volume FMC to EKG Time EKG to 324-TIME EKG Transmission Rate (all activations) 100% 86% -- EKG to Hospital Arrival Hospital Arrival to Device Time FMC to Device Time FMC to Device < 90 min (%) 100% 100% 100% Other Metrics June Q th 90 th Cardiology Arrival Times 100% 100% 96% Mandatory 90% STEMI Line Process Variation 13% 12% Cardiac Rehabilitation (AMI) 100% 98% 86% 100% Risk Adjusted In-hospital Mortality % 7.3% 6.4% Volume Hosp 1 Transfer to Device Hosp 2 Door to EKG Time Hosp 1 Hosp 2 EKG Transmission Rate Hosp 1 (all activations) Hosp 2 EKG to 324-TIME Hosp 1 Hosp 2 Door-In to Door-Out Time Hosp 1 Hosp 2 June Q th 90 th % 50% - 100% 100% Arrival to Device Time State 28 Nation 27 1 st Door to Device Time st Door to Device < 120 min (%) 0% 100% 100% State 69% Inpatient EKG to Device Nation 67% June Q Volume EKG to STEMI line called EKG to Device Time EKG to Device < 90 min (%) % 100%

14 Dr. Odeon Interventional Cardiology Scorecard Q Scores National Benchmarks Metric Q Q Previous R4Q 50 th 90 th 1. Inappropriate indication for elective PCI 2.0% 13.4% 8.70% 13.2% 0.005% 2. Proportion of elective PCI procedures not classifiable for AUC reporting 1.3% 1.41% 1.6% 3.8% 0.31% 3. Direct cost per case 7.8K 9.1K 8.4K 9.14K 6.62K 4. Stent volume per admission Case time (mean) patient in to patient out stick to break scrub 93 min 57 min 6. Turnaround time (mean) min min min 7. LOS - Post-procedure LOS (in days) for PCI patients without CABG or major surgery (median) PCI case volume % Femoral access rate % Radial access rate % 28.7% % 26.73% % 25.26% 76.54% 23.17% 75.59% 24.08% 9. Bleeding rate (risk adjusted) Observed bleeding events Expected bleeding events 3.83% % % % 1.74% 10. Vascular access site injury requiring treatment or major bleeding Femoral access rate Radial access rate Proportion of PCI procedures with transfusion 3% 4.2% 0.0% 0.0% 2% 2.7% 0.0% 1.04% 3.6% 4.1% 2.0% 1.07% 1.5%* 1.8%* 0.5%* 1.8%* 11. Mortality rate (risk adjusted) 5.07% 0% 1.85% Observed mortality Expected mortality % 3.44% 12. Fluoro time (median) 11 min 10 min min 7 min 13. Return to lab within 24 hours rate 88 min 51 min 93 min 56 min 14. Readmission to any Seton facility within 30 days 5.00% 7.00% 6.00% 16% 0% 15. STEMI reperfusion times (median) Door to device First medical contact to device Transfer door to device 42 mins 88 mins 90 mins 48 mins 82 mins 96 mins 55 mins 88 mins 93 mins 59 mins 47 mins 88 mins 83 mins 105 mins 81 mins 2015 Seton 14

15 Dashboards 2015 Seton 15

16 Dashboards 2015 Seton 16

17 STEMI Dashboard 2015 Seton 17

18 STEMI Dashboard 2015 Seton 18

19 We have our data Now what? Streamline Accurate Data Abstraction Facilitate Problem Recognition Build High-Performance Infrastructure Promote Accountability 2015 Seton 19

20 Barriers to Data Collection, Data Quality and High Performance Data Collection Accurate Data Problem Recognition Process Improvement Reliance on manual data abstraction Incomplete medical records Inability to identify relevant data in medical record Inconsistent definitions across registries Incorrect interpretation of definitions by staff Poor Documentation Inability to integrate data from disparate reports Struggle to set realistic goals Unsure when to implement process improvement initiatives Lack of access to timely data Limited resources, staff availability to implement PI initiatives Poor physician/staff buy-in Moving best practices to the bedside quickly 2015 Seton 20

21 1.) Data Collection Navion Healthcare Solutions - Abstraction Services Remote abstraction services Decrease expensive manual data collection Improve data collection quality and reliability Reallocate resources from 100% data abstraction to PI processes, data analysis and education to affect meaningful change Customization of outcome reports Quick data turn-around-times 2015 Seton 21

22 2.) Accurate Data Manage Imprecise Documentation for Cath-PCI Standardize Common Documentation Terms. Interventionalist Documents: Consensus Definition: Subtotal occlusion 99% Less than 10% stenosis 5% Normal or Patent 0% Minimal or minor stenosis 10% Free of obstructive disease 10% Mild disease 20% Luminal irregularities 10% Severe disease 70% Culprit lesion First one stented in multiple blockages Slight /Borderline ST elevation Yes <0.1mV Unstable Angina Class Seton 22

23 3.) Problem Recognition Recognition Prioritize Metrics Differentiate between Score Cards and Dashboards 1. Score Cards: Physician driven Metrics essential to monitor to understand sub-service line performance but may not be hospital wide priority 2. Dashboards: Hospital driven Metrics critical to entire service line enterprise. Whole team commits to improving these metrics 2015 Seton 23

24 4.) Process Improvement Process Improvement Models Plan Do Check Adjust/Focus Plan-Do-Study- Act RAPID Model Diffusion Lean Six Sigma 2015 Seton 24

25 Inpatient Code STEMI using Mayo Clinic Model of Diffusion Mayo Clinic Model of Diffusion Checklist Ensures defined requirements, readiness, and enterprise acceptance are in place prior to launching QI efforts: Change management ensures that individuals are aware of, and accept/buy-in to the change, and have the ability to make and sustain the change in their daily work. Mayo Clinic uses change management model as follows: Awareness of need for change Desire to participate and support the change Knowledge how to change Ability to implement required skills and behaviors Reinforcement to sustain the change 2015 Seton 25

26 2015 Seton 26

27 Inpatient Code STEMI using Mayo Clinic Model of Diffusion Mayo Clinic Model Of Diffusion Checklist Verify Best Practice successful in at least one other clinic Confirm best practice vetted in the appropriate sites that will implement the change Ensure metrics are attainable in a sustainable manner Define key principles for the project-what aspect stay the same and where can there be variation Allocate budget as needed Define and complete infrastructure elements IT changes, order sets, communication Identify key messages and messengers elevator speech Test infrastructure changes to verify proper functioning Assign Champion, Administrator and Physician Leader(s) 2015 Seton 27

28 Inpatient Code STEMI 2015 Seton 28

29 Using Data for Quality Improvement Questions? 2015 Seton 29