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Getting to Zero and other Possible Dreams

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1 Getting to Zero and other Possible Dreams
Don Goldmann, M.D. Senior Vice President Institute for Healthcare Improvement Professor of Pediatrics Harvard Medical School No conflicts to declare

2 100,000 Lives Campaign Objectives (December 2004 – June 2006)
Avoid 100,000 unnecessary deaths in participating hospitals Enroll more than 2,000 facilities Raise the profile of the problem - and hospitals’ proactive response Build a reusable national infrastructure for change Some is not a number, soon is not a time - Berwick

3 100,000 Lives Campaign “Planks”
Rapid response teams Evidence-based care for acute myocardial infarction Prevention of adverse drug events (medication reconciliation) Prevention of central line infections (Central Line Bundle) Prevention of surgical site infections (correct perioperative antibiotics at the proper time and other elements of the Surgical Infection Bundle) Prevention of ventilator-associated pneumonia (Ventilator Bundle)

4 Campaign Field Operations
Introduction, expert support/science, ongoing orientation, learning network development, national environment for change IHI and Campaign Leadership Ongoing communication Local recruitment and support of a smaller network through communication/collaboratives NODES (> 55) *Each Node Chairs 1 Network Implementation (with roles for each stakeholder in hospital and use of existing spread strategies FACILITIES (3000-plus) *30 to 60 Facilities per Network

5 Measurement Strategy Change in aggregate hospital mortality, compared to 2004, in terms of “lives saved” Case mix adjustment from three sources, but not yet Hospital Standardized Mortality Ration (HSMR) Direct submission of monthly raw mortality data (deaths/discharges) to IHI Optional data at the intervention-level (e.g., ventilator pneumonia rates, process measures)

6 100,000 Lives Campaign Results
Estimated 120,000 lives saved by participating hospitals through overall improvement (IHI cannot attribute change in mortality to the Campaign per se – research studies pending) Over 3,100 Hospitals Enrolled Over 78% of all acute care beds Participation in Campaign Interventions Rapid Response Teams: 60% AMI Care Reliability: 77% Medication Reconciliation: 73% Surgical Site Infection Bundles: 72% Ventilator Bundles: 67% Central Venous Line Bundles: 65% All six: 42% Still lots of room for improvement in basic areas of harm reduction. Note Priority Partners/NQF priority.

7 100,000 Lives Campaign Results
Over 55 field offices (“nodes”) and over 130 mentor hospitals Strong national partner support (CDC, AHRQ, Joint Commission, ACC/AHA, etc.) Thousands on national calls Large increase in web activity and downloads of Campaign tool kits Great media coverage (Newsweek, US News and World Report, Wall Street Journal, NY Times) Related campaigns forming nationally and globally (Canada, Australia, Denmark, England) Changes in expectations for care (“getting to zero”) in some participating facilities (many reports of zero ventilator-associated pneumonia or catheter-related BSIs) Still anecdotal intervention-level data, which is limiting. Problem verifying validity of detection.

8 Success Factors Inspiring goal and clear deadline Easy sign-up
Minimal reporting requirements Straightforward interventions Optimism, personal motivation, volunteerism Practical direction for hospital leaders Demonstrated link between quality and cost Useful tools Vibrant, distributed national learning network Young, dedicated field team, logistics

9 5 Million Lives Campaign
A campaign against harm (injuries/adverse events) Harm is defined as levels e-i using NCC MERP* Index criteria Level e is temporary harm that required intervention Level i is death Harm is counted… Whether or not it is considered preventable Even if present on admission to the hospital if attributable to medical care * National Coordinating Council for Medication Error Reporting and Prevention

10 How did IHI Decide on 5 Million Harms?
37 million admissions to acute care US hospitals annually AHA National Hospital Survey, 2005 40-50 level e-i harms per 100 admissions Chart reviews in 3 hospitals using IHI Global Trigger Tool (GTT)* Therefore, about 15 million harms occur per year (37 million admissions X 40 harms per 100 admissions) If best known results can be replicated, might avoid 3.5 million harms per year = 7 million in 2 years 5 million seemed like a good stretch goal We know that even perfect compliance with all of the planks will not be enough to avoid 5 million harms Further validation of GTT psychometrics pending * IHIGlobalTriggerToolforMeasuringAEs.htm

11 5 Million Lives Campaign Planks
Reduce Surgical Complications – Adopt “SCIP” Prevent Harm from High Alert Medications Prevent MRSA Infections Reduce Readmissions in patients with Congestive Heart Failure Prevent Pressure Ulcers Get Boards on Board Won’t talk further about Boards, but arguably the best traction and most important.

12 Tough Questions IHI claims that organizations need to have leadership commitment, improvement expertise and capacity, and the ability to apply QI methods (rapid cycle PDSAs) – just for starters But contact with many participating hospitals suggests that such capability is not widespread So….are we Encouraging brute force (“hire-a-nurse”) projects to implement a few “planks?” Relying on charismatic champions? ….or…. Creating fertile soil for true institutional transformation? How good is the evidence? When is it good “good enough” to spread? MRSA and RRTs: more later

13 Prevent MRSA Infection

14 S. aureus bacteraemia: methicillin sensitivity (English NHS acute Trusts, voluntary surveillance ) Mandatory enhanced surveillance October 2005 Baseline year for targets 2003/04 Mandatory surveillance introduced April 2001 Provisional data

15 Temporal trends in MRSA bacteraemia rates, by region
Introduction of national target Estimated overall rate decrease 3% per quarter Homogeneous regional patterns Estimated overall rate increase % per quarter Heterogeneous regional patterns 0.5 Provisional data

16 MRSA in Europe

17 Is this remarkable variation due to:
Transmissibility and virulence of distinct genotypes? Size, design, or type of hospital? Case mix? Practice variation? Compliance with known, measurable evidence based practices? Less tangible features, such as culture and organization of an intensive care unit? Are nosocomial infections an “expected” consequences of caring for very sick, complex patients, or intolerable, potentially preventable adverse events Vermont Oxford NICQ visits to “best of breed” NICUs

18 A Modest Proposal… Improve reliability of basic infection control procedures Hand hygiene Isolation procedures Screening cultures

19 Reliability Science Health care is riddled with defects
40-50% compliance with hand hygiene!!?? What happens at Intel… What happens in Bowling Green… From the patient’s point of view, it’s “all or nothing” Reliability science offers robust approaches to reducing defects and harm in health care

20 Component vs. Composite Adherence Contact Precautions
COMPONENT: 80% hand hygiene, gloves on entering room COMPONENT: 78% gowns on entering room COMPONENT: 65% hand hygiene after removing gloves COMPOSITE: 50% get all three

21 Reliability is failure free operation over time from the viewpoint of the patient

22 Defects in outpatient asthma care
Defects in hospital care Acute asthma attack Admission through discharge Defects in outpatient care Years/Months Days Years/Months Defect free care overtime from the patient’s viewpoint

23 Levels of Reliability Chaotic process: Failure in greater than 20% of opportunities 10-1: 80 or 90 percent success: 1 or 2 failures out of 10 opportunities (no consistent articulated process) 10-2: 5 failures or fewer out of 100 opportunities (process is articulated by front line) 10-3: 5 failures or fewer out of 1000 opportunities 10-4: 5 failures or fewer out of 10,000 opportunities Blood banking and anesthesiology alone achieve the higher levels of reliability in medicine

24 Reliability in Healthcare
Remember, it’s “all or nothing” – not compliance with each individual component of “best practice” Most institutions do fairly well with individual components of evidence-based practice, but performance drops dramatically when the standard is “all or nothing” We are trying to decrease the “defect rate” and to achieve a reliability of performance to the 10-2 level (at least 95% compliance with the entire package of evidence-based practice) Howard Cohen

25 Guidelines v. Bundles (Intervention Packages)
Guidelines tend to be long, all-inclusive, and confusing Many potential interventions are supported by some evidence Guidelines are difficult to translate into action and often are ignored by clinicians What if just a few key, actionable interventions, supported by strong evidence, were culled from the guidelines?

26 What Is a Bundle? A grouping of best practices with respect to a disease process that individually improve care, but when applied together result in substantially greater improvement The science behind the bundle is so well established that it should be considered standard of care Bundle elements are dichotomous and compliance can be measured: yes/no answers Bundles eschew the piecemeal application of proven therapies in favor of an “all or none” approach

27 Central Venous Catheter Bundle
Hand hygiene before inserting a catheter or manipulating the system and catheter site Maximal barrier precautions for line insertion Hand hygiene Non-sterile cap and mask Sterile gown and gloves Large sterile drape Antiseptic prep used for catheter insertion as per hospital protocol 2% chlorhexidine supported by evidence (but FDA warning for neonates) Site selection Timely removal Daily assessment to determine if central venous catheter is still necessary; if not, removal within 8 hours

28 Central line-associated bloodstream infection rate in 66 ICUs,
Central line-associated bloodstream infection rate in 66 ICUs, Southwestern Pennsylvania, April 2001-March 2005 CDC Pronovost et al.,N Engl J Med; 2006;355:2725 Decrease from 7.7 to 1.4 per 1000 catheter days in 103 ICUs

29

30 Imagine what would happen to the MRSA infection rate in there were nearly zero central venous catheter infections…

31 A Hand Hygiene “Bundle”
Staff knowledge Staff competency Alcohol and gloves available at the point of care Operational, full dispensers providing correct volume of rub At least 2 sizes of gloves Correct performance of hand hygiene + gloves worn for standard precautions Concurrent monitoring and feedback Focus on leaving the bedside Staff accountability

32 Prevent MRSA Infection and Colonization
Colonized patients comprise the reservoir for transmission (“colonization pressure”) High rates of MRSA colonization complicate empiric antibiotic therapy (e.g., vancomycin) Colonized patients have a high rate of MRSA infection Nearly 1/3 develop infection, often after discharge Colonization is long-lasting, and patients can transmit MRSA to patients in other health care settings (e.g., nursing homes), as well as to family members Mention C. diff as effect of antibiotics

33 Five Key Interventions
Compliance with Central Venous Catheter and Ventilator Bundles Hand hygiene* Active surveillance cultures (ASCs) Decontamination of the environment and equipment Contact precautions for infected and colonized patients Already mentioned CVC and hand hygiene bundles * Especially before contact with the patient and after contact with the patient and environment

34 What Changes Can We Make? Understanding the System
Color code the drivers, make Aim box large – transfer to HAI diagram- move ‘drives’ to avoid getting lost – make the whole thing bigger, or must move down Cause Effect Drives

35 What Changes Can We Make? Understanding the System for Weight Loss
“Every system is perfectly designed to achieve the results that it gets” Repeat the ‘every system is designed’ box here. Consider donabedian slide: outcome = structure (physiology, genes, also stuff in my fridge, exercise equipment. etc. Some can change, some are fixed) + process (how we do things, methods, habits) Outcome = Structure + Process -Donabedian

36 How Will We Know We Are Improving
How Will We Know We Are Improving? Understanding the System for Weight Loss with Measures Emphasize importance of secondary drivers, sequence. Measures let us • Monitor progress in improving the system • Identify effective changes

37 What Changes Can We Make
What Changes Can We Make? Understanding the System for Reducing Hospital Acquired Infections See the ‘Change Package’ Use colors in previous diagram

38 How Will We Know We Are Improving
How Will We Know We Are Improving? Understanding the System for Reducing Hospital Acquired Infections with Measures Use colors in previous diagram

39 Active Surveillance Perform active surveillance cultures (ASCs) to detect colonized patients on admission Necessity of ASCs per se in controlling MRSA is controversial – why are we recommending it? “Knowledge is power” – clinical cultures miss many colonized patients and vastly underestimate the magnitude of the problem Added value varies by institution (Huang SS: JID 2007;195:330-8) ASCs on admission, followed by testing weekly and/or at discharge, is necessary to document the extent of transmission and the success of control measures Nose +/- perineum/axilla +/- rectum and skin lesions/broken skin Successful programs combine ASCs with reliable implementation of other interventions Controversy regarding ASCs for high-risk areas (ICUs) vs. entire hospital So what is the evidence?

40 Evidence for ASCs European experience
Control of nosocomial MRSA outbreaks Mathematical models Observational studies from individual hospitals Interrupted time series study Cluster randomized trial

41 Antimicrobial Resistance in Staphylococcus aureus Blood Isolates, Denmark 1960-1995
100% 90% 80% 70% 60% 50% Methicillin resistance 40% 30% 20% 10% 0% DANMAP Report, 1997. Rosdahl VT et al. Infect Control Hosp Epidemiol 1991;12:83-88.

42 Impact of Active Surveillance in ICUs
Huang SS et al., Clin Infect Dis 2006;43:971-8

43 Active Surveillance Perform active surveillance cultures (ASCs) to detect colonized patients on admission Necessity of ASCs per se in controlling MRSA is controversial – why are we recommending it? “Knowledge is power” – clinical cultures miss many colonized patients and vastly underestimate the magnitude of the problem Added value varies by institution (Huang SS: JID 2007;195:330-8) ASCs on admission, followed by testing weekly and/or at discharge, is necessary to document the extent of transmission and the success of control measures Nose +/- perineum/axilla +/- rectum and skin lesions/broken skin Successful programs combine ASCs with reliable implementation of other interventions Controversy regarding ASCs for high-risk areas (ICUs) vs. entire hospital So what is the evidence?

44 Beware…. Pseudomonas Acinetobacter Stenotrophomonas Burkholderia
ESBL and carbapenemase-producing Gram-negative bacilli And many others….

45 Weighing the Evidence How much evidence is required before deciding to spread change? What kind of evidence is appropriate? Randomized controlled trials Cluster randomized trials Quasi-experimental studies Statistical process control Time-series analysis Qualitative studies Behavioral science, Sociology, Anthropology Mixed methods

46 Transition from Descriptive Theory to Normative Theory – ⇧Degree of Belief
Carlile and Christensen Practice and Malpractice In Management Research p.6

47 Pawson and Tilley: Realistic Evaluation
47

48 Pawson and Tilley The Classic Experimental Design: “OXO” Pre-Test
Treatment Post-Test Experimental Group O1 X O2 Control Group 48 Pawson R, Tilley N. Realistic Evaluation. London: Sage Publications, Ltd.; 1997.

49 Context + New Mechanism = Outcome
Pawson and Tilley Context + New Mechanism = Outcome C + M = O 49 Pawson R, Tilley N. Realistic Evaluation. London: Sage Publications, Ltd.; 1997.

50 Pawson and Tilley “Programs work (have successful ‘outcomes’) only in so far as they introduce the appropriate ideas and opportunities (‘mechanisms’) to groups in the appropriate social and cultural conditions (‘contexts’).” 50 Pawson R, Tilley N. Realistic Evaluation. London: Sage Publications, Ltd.; 1997.

51 (If only it was this simple!)
Is life this simple? X Y (If only it was this simple!)

52 Independent Variables
No, it looks more like this… In this model there are numerous direct effects between the independent and variables (the Xs) and the dependent variable (Y). X1 X4 Dependent or outcome variable Independent Variables X2 Y X5 Time 3 X3 Time 2 Time 1

53 Or, probably more like this… Key Reference on Causal Modeling
In this case, there are numerous direct and indirect effects between the independent variables and the dependent variable. For example, X1 and X4 both have direct effects on Y plus there is an indirect effect due to the interaction of X1 and X4 conjointly on Y. R1 Key Reference on Causal Modeling Blalock HM, ed. Causal Models in the Social Sciences. Chicago: Aldine; 1999. X1 R4 X4 RY X2 Y R2 X5 Time 3 X3 Time 2 R = residuals or error terms representing the effects of variables omitted in the model. R5 Time 1 R3

54 Rigorous Learning in Complex Systems
“Dynamic” Cluster RCTs Statistical Process Control Time Series Methods Mixed Methods Anthropology Ethnography Journalism “Rigorous” Learning Traditional RCTs Simple Linear Cause-and -Effect Complex Non-Linear Chaotic Case Series “Anecdotes” Static RCTs Poor Learning

55 Weighing the Evidence How much evidence is required before deciding to spread change? What kind of evidence is appropriate? Randomized controlled trials Cluster randomized trials Quasi-experimental studies Statistical process control Time-series analysis Qualitative studies Behavioral science, Sociology, Anthropology Mixed methods

56 The Case of Rapid Response Teams
“Early trials of medical emergency teams suggested a large potential benefit – to the point that some observers regarded further study as unethical. However, a large, randomized trial subsequently showed that medical emergency teams had no effect on patient outcomes.” Auerbach, et al., NEJM 2007:357:

57 The MERIT Cluster Randomized Trial
23 Australian hospitals randomized 2-month baseline, 4-month preparation period, 6-month intervention Superb statistical analytic plan More inter- and intra-hospital variance than expected, much lower event rate than expected Increased call rate in intervention hospitals, but no effect on outcomes Reduction in mortality in both arms of study Sub-optimal team activation in patients with call criteria MERIT Study Investigators, Lancet 2005;365:

58 What If…. Baseline period was used to adjust power
Study would have been “futile” Performance data were fed back in real time QI was encouraged to improve performance Mixed methods were used to understand context and outcomes in individual sites

59 Lessons Every QI “experiment” should use the most appropriate evaluation method for the question and context The broadest possible palette of methods should be utilized No opportunity to learn should be wasted


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