Collecting and Interpreting Stewardship Data: Breakout Session

Transcription

1 Collecting and Interpreting Stewardship Data: Breakout Session Michael S. Calderwood, MD, MPH Regional Hospital Epidemiologist, Dartmouth-Hitchcock Medical Center March 20, 2019

2 None Disclosures

3 Outline Minutes: Examples of how to present stewardship data to senior leadership and frontline providers Minutes: Group discussion on what has and has not worked; opportunity share successes and challenges

4 Tracking and Reporting 1. Process Measures: A. Documentation of dose, duration, and indication B. Compliance with local disease treatment guidelines C. Obtaining cultures prior to treatment D. Modifying therapy appropriately based on microbiologic findings E. Acceptance rate for recommendations F. Number of dose and/or route optimizations 2. Outcome Measures: A. Total antibiotic expenditures B. Total days of therapy C. Mortality, Length of Stay, Readmission D. Rates of C. difficile E. Local antibiotic resistance rates

5 Quality Improvement Metrics for Evaluating Antimicrobial Stewardship Programs 10-member expert panel from US & Canada convened to develop standardized quality indicators to evaluate the impact of antimicrobial stewardship programs Infect Control Hosp Epidemiol 2012;33:500-6

6 Quality Improvement Metrics for Evaluating Antimicrobial Stewardship Programs 1. Days of therapy (DOT) per 1000 patient-days* 2. Number of patients with specific organisms that are drug resistant* 3. Mortality related to antimicrobial-resistant organisms 4. Conservable days of therapy among patients with community-acquired pneumonia (CAP), skin and soft-tissue infections (SSTI), or sepsis and bloodstream infections (BSI) 5. Unplanned hospital readmission within 30 days after discharge from the hospital in which the most responsible diagnosis was one of CAP, SSTI, sepsis or BSI * Recommended for public reporting Infect Control Hosp Epidemiol 2012;33:500-6

7 Quality Improvement Metrics for Evaluating Antimicrobial Stewardship Programs 1. Days of therapy (DOT) per 1000 patient-days* 2. Number of patients with specific organisms that are drug resistant* 3. Mortality related to antimicrobial-resistant organisms 4. Conservable days of therapy among patients with community-acquired pneumonia (CAP), skin and soft-tissue infections (SSTI), or sepsis and bloodstream infections (BSI) 5. Unplanned hospital readmission within 30 days after discharge from the hospital in which the most responsible diagnosis was one of CAP, SSTI, sepsis or BSI * Focus of CDC s Surveillance for Antibiotic Use and Antimicrobial Resistance

8 Quality Improvement Metrics for Evaluating Antimicrobial Stewardship Programs 19 member CDC-sponsored panel used a modified Delphi approach to select relevant metrics Clin Infect Dis 2017;64:377-83

9 Clin Infect Dis 2017;64:377-83

10 1. Use local data as an opportunity to gain support and to drive change 2. Track data over time and provide feedback on performance Clin Infect Dis 2017;64:377-83

11 What you don t see here is cost, although this has historically been the easiest data to pull and can be important when speaking with hospital leadership about ASP funding Clin Infect Dis 2017;64:377-83

12 Data on Cost #1: Percent Change in Antimicrobial Expenditures Compared with Prior Fiscal Year Percent Increase 25.0% 20.0% 15.0% 10.0% 5.0% 0.0% -5.0% -10.0% 16.0% 13.3% 19.5% 2.7% 9.4% Program Launch -2.1% -5.1% 0.8% -0.4% 8.3% 0.3% -3.6% 3.4% -4.4% 6.7% Non-DH Data

13 Data on Cost #2: Cost Avoidance Based on Growth of Antimicrobials Prior to Antimicrobial Stewardship Program $35.0 $30.0 ~Cost Avoidance Actual Expenditures Cost In Millions $ $25.0 $20.0 $15.0 $10.0 $5.0 $0.0 $3.2 $3.6 $4.2 $5.0 $0.7 $1.1 $2.3 $3.8 $5.1 Program Launch $5.6 $5.5 $5.2 $5.2 $5.3 $7.0 $5.2 $8.5 $10.7 $13.5 $5.6 $5.7 $5.5 $16.3 $20.1 FY00 FY01 FY02 FY03 FY04 FY05 FY06 FY07 FY08 FY09 FY10 FY11 FY12 FY13 FY14 FY15 $5.7 $5.4 $23.8 $5.8 Projected Growth ~ 16% annually (based on growth pattern prior to program launch) Estimated Cumulative Cost avoidance over 12 years ~ $113 million Non-DH Data

14 Data on Cost #3: Total Antimicrobial Expenditures vs. Total Drug Expenditures Cost in Millions $ $120.0 $110.0 $100.0 $90.0 $80.0 $70.0 $60.0 $50.0 $40.0 $30.0 $20.0 $10.0 $0.0 $15.9 All Other Drugs Antimicrobials $17.3 $23.2 $27.5 $29.7 Program Launch $32.7 $35.9 FY03 Abx ~ 15.4% of Rx Budget FY14 Abx ~ 4.8% of Rx Budget $40.4 $3.2 $3.6 $4.2 $5.0 $5.1 $5.6 $5.4 $5.2 $5.2 $5.2 $5.6 $5.7 $5.5 $5.7 $5.4 $5.8 FY00 FY01 FY02 FY03 FY04 FY05 FY06 FY07 FY08 FY09 FY10 FY11 FY12 FY13 FY14 FY15 $44.2 $45.6 $51.6 $56.0 $67.2 $82.1 $109.6 $114.2 Non-DH Data

15 Data on Cost #4: Antimicrobial Costs Per Case-Mix Adjusted Discharge (CMAD) $55.00 Program Launch Abx Cost / CMAD 140,000 Antimicrobial Cost / CMAD $50.00 $45.00 $40.00 $35.00 $30.00 CMAD 2013 vs CMAD: 21.5% Abx Cost/CMAD: 5% 130, , , ,000 90,000 80,000 CMAD $ ,000 $ ,000 Non-DH Data

16 Moving Beyond Cost: Tracking Trends in Days of Therapy 15% decline in overall antimicrobial days of therapy in past 2 years Targeted Extended-Spectrum Antibiotics: 18% decline in ceftazidime/cefepime/piperacillin-tazobactam use 14% decline in carbapenem use 20% decline in vancomycin/linezolid/daptomycin/ceftaroline Non-DH Data

17 Moving Beyond Cost: Tracking Trends in Days of Therapy Ceftriaxone Ceftazidime Cefepime 23% decline in cefepime use over 2 years 46% decline in ceftazidime use over 2 years Non-DH Data

18 Moving Beyond Cost: Performance Against Benchmark FY16-17 Data

19 Moving Beyond Cost: Performance Against Benchmark FY16-17 Data

20 Moving Beyond Cost: Where We Need to be Heading NQF-endorsed clinical quality measure The SAAR can be calculated for different patient care locations and antibiotics to provide a measure of the reported-to-predicted number of antimicrobialdays, where the predicted number is estimated using predictive models that take into account differences in patient care location and hospital characteristics Hospital bedsize, hospital number of ICU beds, medical school affiliation, location bedsize, and location type (ICU/ward, medical/medical surgical/surgical, adult/pediatric Currently no patient-level factors Clin Infect Dis 2018;67:179-85

21 Moving Beyond Cost: Where We Need to be Heading Median SAAR (with interdecile range) 2014 Data from: - 77 hospitals adult units - 33 pediatric units Clin Infect Dis 2018;67:179-85

22 How Do We Get There: Prior Authorization 7/2014-6/2015 Review: 859 calls for a restricted antimicrobial (average of 17 per week) Full ID consultation recommended in 20% of calls 67% of calls for empiric therapy Documented review for de-escalation in 56% of cases, with successful de-escalation in 16% of reviewed cases Non-DH Data

23 How Do We Get There: Prospective Audit and Daily Feedback 7/2014-6/2015 Review: 1,700 IV to PO conversions 776 interventions to optimize therapy based on drug susceptibilities 652 reviews of potential opportunities for stopping vancomycin 431 interventions to address redundant therapy (Staph, beta-lactam, anti-fungal, anaerobic) 205 interventions to tailor poly-antibacterial therapy Non-DH Data

24 But What Providers Need to See is the Impact on Patients Trend in hospitalonset C. difficile

25 But What Providers Need to See is the Impact on Patients Trend in hospitalonset C. difficile Good to mirror with antibiotic use data 9.8% reduction in FQs, 3 rd generation cephalosporins, and carbapenems from FY2017 to FY2018

26 Preserving the Armamentarium Educational tool to drive best practice. Links guideline-driven antibiotic selection with local resistance data.

27 Antimicrobial Resistance Methicillin-resistant Staphylococcus aureus 32%/36% of NH non-urine/urine S. aureus isolates; 45% of isolates nationally Vancomycin-resistant Enterococcus species 9%/6% of NH non-urine/urine Enterococcus isolates; 21% of isolates nationally 3 rd generation cephalosporin-resistant E. coli 5%/4% of NH non-urine/urine E. coli isolates; 15% of isolates nationally 3 rd generation cephalosporin-resistant Klebsiella pneumoniae 3%/3% of NH non-urine/urine K. pneumoniae isolates; 12% of isolates nationally Ceftazidime-resistant Pseudomonas aeruginosa 6%/6% of NH non-urine/urine P. aeruginosa isolates; 19% of isolates nationally Carbapenem-resistant Acinetobacter species 4%/4% of NH non-urine/urine Acinetobacter isolates; 30% of isolates nationally The Center for Disease Dynamics, Economics & Policy (

28 Outpatient Prescribing in NH, th best state in the U.S. 2 nd best state in New England

29 Outpatient Prescribing in NH, 2015 Dropped to 13 th best state in the U.S. Increase from 701 to 728 prescriptions per 1,000 in the population

30 The New Frontier of Stewardship: Outpatient Prescribing Need to collect and show providers data on peer-topeer comparisons Accountable justification Suggested alternatives Practice standardization

31 GROUP DISCUSSION I am ready for the challenge!