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TMIT High Performer Webinar:
The OIG Report: How to Tell the Story
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© 2010 TMIT
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Welcome
Franck Guilloteau
Chief Technology Officer, HCC Corporation
Director, Texas Medical Institute of Technology (TMIT)
TMIT High Performer Webinar
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© 2010 TMIT
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Disclosure Statement
The following panelists certify:

that unless otherwise noted below, each presenter provided full disclosure information,
does not intend to discuss an unapproved/investigative use of a commercial
product/device, and has no significant financial relationship(s) to disclose. If
unapproved uses of products are discussed, presenters are expected to disclose this
to participants.
Franck Guilloteau: Director, TMIT; education grant (CareFusion) and co-production with Discovery
Channel
Ruth Ann Dorrill: Employed by Office of Inspector General
Amy Ashcraft: Employed by Office of Inspector General
Lee Adler: Employed by Florida Hospital
Stephen Knych: Employed by Florida Hospital
Christopher Landrigan: Employed by Harvard Medical School and Brigham and Women’s Hospital
Charles Denham: Chairman, TMIT; education grant (CareFusion) and co-production with Discovery
Channel
Steve Rel: Has no relevant financial interests in this presentation
© 2010 TMIT
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Roundtable Panelists
© 2010 TMIT
Franck Guilloteau
Ruth Ann Dorrill
Amy Ashcraft
Lee Adler
Stephen Knych
Chris Landrigan
Charles Denham
Steve Rel
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The Voice of the Patient and Family
Steve Rel
TMIT Patient Safety Advocate
Co-founder, Braxton Memorial Hockey Scholarship Fund
TMIT High Performer Webinar
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© 2010 TMIT
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Braxton Rel
© 2010 TMIT
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SafetyLeaders.org and
Safe Practice Overview
Franck Guilloteau
Chief Technology Officer, HCC Corporation
Director, Texas Medical Institute of Technology (TMIT)
TMIT High Performer Webinar
December 16, 2010
© 2010 TMIT
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TMIT Mission
Accelerate performance solutions that
save lives, save money, and build value
in the communities we serve and
ventures we undertake.
© 2010 TMIT
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Culture
2010 NQF Report
Consent & Disclosure
Consent and Disclosure
Workforce
Information Management and
Continuity of Care
Medication Management
Healthcare-Associated
Infections
Condition- &
Site-Specific Practices
© 2010 TMIT
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National Collaboratives Provide Performance Metrics:
Impact Calculators Provide
CFO Validated Performance Impact
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A Briefing on the OIG Report
Ruth Ann Dorrill, MPA
Team Leader
U.S. Department of Health and Human Services
Office of Inspector General
Amy Ashcraft, MPA
Team Leader
U.S. Department of Health and Human Services
Office of Inspector General
TMIT High Performer Webinar
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© 2010 TMIT
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Adverse Events in Hospitals:
Measurement and Results
OIG Report to Congress
Lee Adler, DO - Lead Physician Reviewer
Stephen Knych, MD - Physician Reviewer
Amy Ashcraft, MPA – OIGTeam Leader
Ruth Ann Dorrill, MPA – OIGTeam Leader
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Background
STUDY OBJECTIVES
PILOT STUDY
METHODS FOR NATIONAL INCIDENCE STUDY
Ruth Ann Dorrill, MPA – OIGTeam Leader
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Study Objectives
• Congressional Mandate
o Tax Relief and Health Care Act of 2006
o NQF Serious Reportable Events – “never events”
• OIG Objectives
o Capture national incidence of patient harm
o Assess preventability of adverse events
o Estimate costs to Medicare
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Two Event Rates – threshold of harm
• Adverse Event Rate: F - I
• Temporary Harm Event Rate: E only
Level E: Temporary harm requiring medical intervention
Level F: Prolonged hospital stay
Level G: Resulted in permanent harm
Level H: Required life-sustaining intervention
Level I: Contributed to patient death
NCC MERP Patient Harm Index
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Pilot Study – Methods
• Sample in Two Counties
o 24 hospitals
o 278 Medicare beneficiaries
o One-week time period in 2008
• Two-stage review
o Five screening methods to identify potential events
o
o
o
o
o
Hospital incident reports
AHRQ Patient Safety Indicators (PSIs)
Patient/family telephone interviews
Present on Admission (POA) analysis
Nurse screening of medical records
o Onsite physician medical record review
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Pilot Study – Screening Cases
Hit Rate
Screening Method
Hospital Incident Reports
7%
AHRQ Patient Safety Indicators (PSI)
7%
Patient/FamilyTelephone Interviews
21%
Present on Admission (POA) Analysis
51%
Nurse Screening of Medical Record (GTT)
78%
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National Study – Methods
• Screening methods
o Nurse review of medical records
o Present on Admission (POA) analysis
o 30-day readmission
• Full physician review - 5 reviewers
o Dr. Lee Adler, Florida Hospital
o Dr. Jeanne Huddleston, Mayo Clinic
o Dr. Stephen Knych, Florida Hospital
o Dr. Gene Passamani, Suburban Hospital
o Dr. Lee Schwab, Holy Cross Hospital
• Consensus calls
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Sample for National Incidence Study
October 2008
999,645
• Sample month
• Medicare beneficiaries discharged
from acute care hospitals
780
• Sample Medicare beneficiaries
661
• Hospitals represented
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Sample Medicare Patient Statistics
59%
• Female
84%
• 65 years and older
5%
60%
• Stay lasting longer than 14 days
(ALOS = 5.2)
• Entered from Emergency Department
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Findings
INCIDENCE RATES
PREVENTABILITY RESULTS
COST of EVENTS TO MEDICARE
Amy Ashcraft, MPA – OIGTeam Leader
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Incidence Rates – of all beneficiaries
13.5%
• Adverse Events
(NQF, HAC, F– I Level)
0.6%
• NQF Serious Reportable Events
1.0%
• Medicare Hospital-Acquired Conditions
13.5%
• Temporary Harm Events (E Level)
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Percent of Adverse Events by Harm
LEVEL of HARM
% of EVENTS
F Level: Prolonged hospitalization
62%
G Level: Permanent harm
5%
H Level: Life-sustaining intervention
23%
I Level: Contributing to death
10%
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Percent of Adverse Events by Category
CLINICAL CATEGORY
% of EVENTS
Medication
31%
Patient Care
28%
Surgical/Procedural
26%
Infections
15%
Total
100%
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Preventability Results – all events
PREVENTABILITY
% of EVENTS
Preventable
44%
• Not preventable
51%
• Unable to determine
5%
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% Preventable by Clinical Category
CLINICAL CATEGORY
% of EVENTS
Infection
60%
Medication
50%
Patient care
51%
Surgery and other procedures
17%
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Cost of Events to Medicare
$324M
3.5%
• Cost to Medicare for sample month
• % of total Medicare inpatient expenditures
$4.4B
• Cost to Medicare extrapolation for full year
rds
2/3
• Result of additional hospital stays
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Medicare Inpatient Financial Impact
84%
$5,601
• Of events did not raise Medicare payment
• Average cost of event during initial hospital stay
$13,745
• Average cost of event-related additional stay
$0
• Cost reductions from Medicare HAC policy
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OIG Call to Action
OIG Recommendations
• Broaden the definition of adverse events
• Enhance efforts to identify events
• Provide incentives for hospitals to improve care
DHHS Agency Responses
• AHRQ acknowledged “alarming rate” of events and
promised enhanced research and collaboration
• CMS stated it would “aggressively pursue” broadening
the definition of events and further monitoring hospital
care
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The OIG Report: Perspective from the
Medical Reviewer
Lee M. Adler, DO
Vice President, Quality & Safety Innovation & Research
Florida Hospital
Stephen A. Knych, MD, MBA
Division Chief, Patient Safety and Quality Improvement
Florida Hospital, Celebration Health
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Harm Assessments
PATIENT HARM INDEX
PHYSICIAN PROTOCOL
CLINICAL CASE EXAMPLES
Stephen Knych, MD – Physician Reviewer
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Harm Assessments
Level E – temporary harm requiring intervention
delirium, allergic reaction, Stage I pressure ulcer
Level F – prolonged hospitalization
surgical-site infection, injury from patient fall
Level G – permanent harm
partial colon resection, permanent hemiparesis
Level H – life-sustaining intervention required
respiratory failure, hypoglycemic coma
Level I – contributing to death
bloodstream infection, excessive bleeding from blood-thinner
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Physician Protocol
S = Situation
ADVERSE EVENT REVIEW
Full description of event
TIME OF EVENT:______
I = Intervention
TYPE/SUBTYPE: ______
HARM LEVEL:
Intervention following event
______
B = Background
NQF EVENT?
Yes/No
MEDICARE EVENT?
Yes/No
CASCADE EVENT?
Yes/No
Reason for admission, circumstances leading
to event, pertinent co-morbidities, etc.
A = Assessment
Key clinical assessment leading to
identification of event
PREVENTABILITY RATING?_____
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Key Terms
• Commission vs. Omission
o Event resulting from medical intervention vs. events
resulting from lack of medical intervention
• Cascade Event
o A series of multiple, related adverse events counted
as a single harm
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Harm Assessment – questions
Q1: Did an event occur?
Q2: What was the level of harm?
Q3: Is this a case of omission or commission?
Q4: Is this a cascade event?
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Assessing Harm – case #1 scenario
• Day 1 – Total hip arthroplasty
• Day 4 – Discharged with post-op ileus
• Day 7 – ED visit – CT found no obstruction, but
enlarged cecum (9.5 cm) – Discharged from ED
with enemas for home use
• Day 9 – ED visit – Diagnosed with bowel
perforation and shock – Required urgent surgery
and near total colectomy
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Assessing Harm – case #1 answers
• Q1:
Yes, harm event
• Q2:
H harm, life-sustaining intervention
• Q3:
Omission of diagnosis,Toxic Megacolon
(Ogilvie’s Syndrome)
• Q4:
Cascade of events: post-op ileus 
toxic megacolon  bowel perforation 
shock  emergent surgery
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Assessing Harm – case #2 scenario
Day 1 – Admit with fatigue, malaise, and hypotension – History of COPD, CHF, CAD,
and current lung cancer
Day 4 –Vigorous treatment for dehydration with IV fluids – develops respiratory
insufficiency requiring intubation
Day 7 – Sputum grew Klebsiella – diagnosed withVAP
Day 14 – Given multiple doses of insulin (Blood glucose 230-297)
Day 15 – Found unresponsive in cardiac arrest at 5am – Blood glucose 38 –
CPR unsuccessful – Patient died in hospital
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Assessing Harm – case #2 answers
Q1: 3 Adverse Events
Q2: Volume overload (F harm – extending stay)
Q2: VAP (F harm – extending stay)
Q2: Hypoglycemic event (I harm – contributing to death)
Q3: All were events of commission
Q4: All independent events (not cascade)
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Preventability Assessments
PREVENTABILITY DECISION ALGORITHM
PREVENTABILITY RESULTS
CLINICAL CASE EXAMPLE
Lee Adler, DO – Lead Physician Reviewer
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Preventability Definitions
• Preventable – patient harm could have been avoided through
improved assessment or alternative actions
• Not preventable – patient harm could not have been avoided given
the complexity of the patient’s condition or the care required
• Unable to determine – physicians were unable to determine
preventability due to incomplete documentation or case
complexity
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Preventability Decision Algorithm – part 1
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Preventability Decision Algorithm – part 2
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Preventability Results
PREVENTABILITY ASSESSMENT
Preventable
% of EVENTS
44%
9%
35%
• Clearly preventable
• Likely preventable
Not preventable
51%
18%
33%
• Clearly not preventable
• Likely not preventable
Unable to determine
5%
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Rationales for Preventable Events
RATIONALE
% of EVENTS
Error related to judgment, skill, or patient management
58%
Appropriate treatment was provided in substandard way
46%
Patient’s progress was not adequately monitored
38%
Patient’s health status was not adequately assessed
23%
Necessary treatment was not provided
17%
Event rarely happens when proper procedures followed
14%
Communication between caregivers was poor
8%
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Rationales for Nonpreventable Events
RATIONALE
% of EVENTS
Event occurred despite proper procedures followed
62%
Patient was highly susceptible to event due to health status
50%
Care provider could not have anticipated event
35%
Patient’s diagnosis was unusual or complex
29%
Harm anticipated but risk acceptable given alternatives
14%
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Assessing Preventability – case #3 scenario
BACKGROUND: Admitted from ED for
gross hematuria from pulling out own Foley,
several medication allergies noted
8:00 AM – Cystoscopy
1:20 PM – Morphine administered
1:55 PM – Atrial fibrillation, Metoprolol admin.
2:25 PM – Normal rhythm
3:20 PM – Pruritic rash, Diphenhydramine administered
3:30 PM – Lorazepam administered
4:10 PM – Patient fall (no injury)
5:25 PM – Stupor, shallow respiration
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Assessing Preventability – case #3 questions
Are these preventable events?
Q1: Medication-induced stupor (F harm)
Q2: Atrial fibrillation (E harm)
Q3: Allergic pruritic rash (E harm)
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Assessing Preventability – case #3 answers
Q1:
•
•
Q2:
•
•
Q3:
•
•
Medication-induced stupor
Clearly Preventable
Error of medical judgment, poor assessment
Atrial fibrillation
Likely Not Preventable
Could not have been anticipated
Allergic pruritic rash
Likely Not Preventable
Could not have been anticipated
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OIG Study Takeaways
Events are common
Patient harm as a result of medical care is common in
the Medicare population
Providers and payers must identify and measure
Systematic tracking and trending of adverse events is lacking
It is possible to assess preventability
Assessing preventability is important in driving patient safety policies,
helping to prioritize and focus resources
Reducing events is key to reducing costs
To reduce the national cost of medical care, providers and payers must
improve safety
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Developing a Method to Track
Regional and National Changes in
Rates of Harm Due to Medical Care
Christopher P. Landrigan, MD, MPH
Associate Professor of Medicine and Pediatrics, Harvard Medical School
Research Director, Inpatient Pediatrics Service,
Children’s Hospital Boston
Director, Sleep and Patient Safety Program,
Brigham and Women’s Hospital
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Methodology- AIMS
• Assess the feasibility to conduct a national harm study
using the GTT
• Determine the reliability of the GTT for estimating the
level of harm in a hospital and tracking over time
• Compare the rates of triggers, suspected harms, and
confirmed harms between
─ Hospital based (internal) reviewers vs.
─ 3rd party reviewers (external) vs.
─ Experienced reviewers
• Assess inter-rater reliability, intra-rater reliability,
sensitivity, specificity of GTT when used by both teams
• Determine if there was change in harm rates over time in
North Carolina (2002-2007)
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Sharek et al., HSR 2010
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Results
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Overall Rate of Harm
• Internal reviewers
‒ 25.1 harms / 100 admissions (588 harms /
2,341 record reviews)
423 unique admissions (18.1%)
‒ 56.4 harms per 1,000-patient days
• External reviewers
‒ 18.1 harms / 100 admissions (429 harms /
2,374 record reviews)
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Results - Completeness of Documentation
(10% random sample)
Quality of Documentation
• “No score” = 0: 87%
• “No score” = 1: 9.2%
• “No score” = 2: 3.4%
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Results - Within Team Comparisons
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Sharek
et al., HSR 2010
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Results
Comparisons to Experienced
Reviewers
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Results: Agreement of Internal/External with
Experienced Reviewers (Common charts reviewed)
Question: Was there at least 1 harm?
Internal team agree with Experienced Reviewers = 81%
External team agree with Experienced Reviewers = 75%
Kappa: Internal team/ Experienced Reviewers = 0.49
Kappa: External team/ Experienced Reviewers = 0.32
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Internal team
agrees with
Experienced
Reviewers more
than does External
team
Agreement between External/Internal and
Experienced Reviewers
Sharek et al., HSR 2010
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Trends in Harm Over Time
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Trends in All Harms Over Time: Internal
Slope: 0.99 (95% CI 0.94, 1.04 p = 0.61)
Landrigan et al., N Engl J Med 2010;363:2124-34
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Trends in All Harms Over Time: External
Slope: 0.98 (95% CI 0.93, 1.04 p = 0.47)
Landrigan et al., N Engl J Med 2010;363:2124-34
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Trends in Preventable Harms Over Time: Internal
Slope: 1.00 (95% CI 0.94, 1.06 p = 0.92)
Landrigan et al., N Engl J Med 2010;363:2124-34
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Trends in Preventable Harms Over Time: External
Slope: 0.92 (95% CI 0.85, 1.00 p = 0.06)
Landrigan et al., N Engl J Med 2010;363:2124-34
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Trends in High Severity (F-I) Harms Over Time: Internal
Slope: 0.98 (95% CI 0.92, 1.04 p = 0.49)
Landrigan et al., N Engl J Med 2010;363:2124-34
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Trends in High Severity (F-I) Harms Over Time: External
Slope: 0.98 (95% CI 0.91, 1.04 p = 0.44)
Landrigan et al., N Engl J Med 2010;363:2124-34
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Summary: Highlights
1. Striking difference between harms
identified by internal vs. external teams
Internal = 537
External = 403
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Summary: Highlights
2. inTER and inTRA-rater reliability
consistently better for internal review team
─ No instances where external with higher agreement
(kappa) than internal
─ More consistent findings on re-review (i.e.,
inTRArater) for internal reviewers
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Summary: Highlights
3. Experienced Reviewers more likely to
identify harms than Internal or External
Reviewers; Internal more likely than
External to Agree with Experienced
‒ Harm rates (per 100 patients)
Gold standard = 36.6
Internal = 24.3
External = 15.8
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Summary: Highlights
4. No evidence of change in total harm rates over
time (2002-2007)
─ Base model: internal or external reviewers
─ Multivariate model: internal or external reviewers
─ Per admission or per 1,000-patient days
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Conclusions
• Rates of harm remained common 20022007 in NC, a state highly engaged in
efforts to reduce harm
• Proven interventions need to be better
disseminated, and efforts to coordinate
improvement efforts across centers are
needed
• A systematic monitoring system to reliably
track harm is urgently needed
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Using Story Power to Drive Action
Charles Denham, MD
Chairman, TMIT
Co-chairman, NQF Safe Practices Consensus Committee
Chairman, Leapfrog Safe Practices Program
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© 2010 TMIT
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Facts are re-told…
Stories are retained…
Quaid D, Thao J, Denham CR. Story power: The secret weapon. J Patient Saf 2010 Mar;6(1):5-14.
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Storytelling: Stephen Denning
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S.U.C.C.E.S.
Simple
Unexpected
Concrete
Credible
Emotional
Stories
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High Performance Care
Leadership
Practices
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© 2006 HCC, Inc. CD000000-0000XX
Technologies
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C-Suite Question
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© 2010 TMIT
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Laura Slayton, M.Ed.
TMIT Content Manager
Call to Action: Using
Social Media for
Improving Patient Safety
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Roundtable Q & A
© 2010 TMIT
Franck Guilloteau
Ruth Ann Dorrill
Amy Ashcraft
Lee Adler
Stephen Knych
Chris Landrigan
Charles Denham
Steve Rel
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The Voice of the Patient and Family
Steve Rel
TMIT Patient Safety Advocate
Co-founder, Braxton Memorial Hockey Scholarship Fund
TMIT High Performer Webinar
December 16, 2010
© 2010 TMIT
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