Transcript Automatic Surveillance and Pediatric Trigger Tools Thursday, June 19, 2008 12:00 – 1:00 p.m.

Automatic Surveillance
and Pediatric Trigger Tools
Thursday, June 19, 2008
12:00 – 1:00 p.m. EDT
© American Academy of Pediatrics 2008
Moderator:
Paul Sharek, MD, MPH, FAAP
Assistant Professor of Pediatrics, Stanford School of Medicine
Medical Director of Quality Management
Chief Clinical Patient Safety Officer
Lucile Packard Children’s Hospital
Palo Alto, California
DISCLOSURES
Financial Relationships
One individual involved in this webinar:
Melissa A. Singleton, M.Ed., Project Manager-Consultant
has disclosed a financial relationship with an entity producing,
marketing, re-selling, or distributing health care goods or
services consumed by, or used on, patients. Her husband is
employed by Walgreen Co. as a Workforce Administration
Manager (technology position) for the company’s call centers.
The AAP determined that this financial relationship does not
relate to the educational assignment.
None of the other involved individuals (Speakers, Moderators,
Project Advisory Committee members, or Staff) has disclosed a
relevant financial relationship.
Refer to full AAP Disclosure Policy & Grid available below
for download.
DISCLOSURES
Off-Label/Investigational Uses
None of the individuals (Speakers, Moderators, Project Advisory
Committee members, or Staff) has disclosed that they intend to
discuss or demonstrate pharmaceuticals and/or medical devices that
are not approved.
Refer to full AAP Disclosure Policy & Grid available below for
download.
This activity was funded through an
educational grant from the Physicians’
Foundation for Health Systems
Excellence.
Visit our website:
http://www.aap.org/saferhealthcare
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CME CREDIT
Live Webinar Only
The American Academy of Pediatrics (AAP) is accredited by the
Accreditation Council for Continuing Medical Education to
provide continuing medical education for physicians.
The AAP designates this educational activity for a maximum of 1.0
AMA PRA Category 1 Credit™. Physicians should only claim
credit commensurate with the extent of their participation in
the activity.
This activity is acceptable for up to 1.0 AAP credits. These credits
can be applied toward the AAP CME/CPD Award available to
Fellows and Candidate Members of the American Academy of
Pediatrics.
OTHER CREDIT
Live Webinar Only
This program is approved for 1.0 NAPNAP contact hours of which
0 contain pharmacology (Rx) content per the National
Association of Pediatric Nurse Practitioners Continuing
Education Guidelines.
The American Academy of Physician Assistants accepts AMA PRA
Category 1 Credit(s)TM from organizations accredited by the
ACCME.
Speaker:
Jeffrey M. Ferranti, MD, MS, FAAP
Associate Chief Information Officer
Duke University Health System
Durham, North Carolina
Speaker:
Anne Matlow, MD, FRCPC
Director, Infection Prevention and Control Programme
Medical Director, Patient Safety
The Hospital for Sick Children
Toronto, Ontario, Canada
LEARNING OBJECTIVES
Upon completion of the webinar, participants will be able to:
• List the various methodologies employed
to detect adverse events in health care.
• Describe the role of technology in the
detection and prevention of adverse
events.
• Discuss the epidemiology of adverse
events in the pediatric population.
Bridging the Gap
Understanding the role of Technology in
the Detection and Prevention Of Pediatric
Adverse Drug Events
Jeffrey M. Ferranti, MD, MS, FAAP
Associate CIO
Enterprise Analytics and Patient Safety
Duke University Health System
The Institute of Medicine Reports
• To Err is Human (2000)1
• Defines Scope of the Problem
• Defines Cost of the Problem
• Establishes National Focus on Safety
• Crossing the Quality Chasm (2001)2
• Strategies for Improving Care Delivery
• A Focus on Evidence Based Medicine
• A Focus on Information Technology
1. Institute of Medicine. To Err is Human. Washington, DC, National Academy Press, 2000.
2. Institute of Medicine. Crossing the Quality Chasm. Washington, DC, National Academy Press, 2001.
The Recent IOM Report
• Preventing Medication Errors (2006) 1
• Employ error detection methodologies in
“Health
allcare
care systems
settings should capture
information
onmedication
medication
and use
• Assess the
usesafety
process
this information
tomonitoring
improve the safety of
through active
1
their
care
delivery
systems.”
• Computerized detection of ADEs should
complement voluntary reporting
1. Institute of Medicine. Preventing Medication Errors: Quality Chasm Series. Washington, DC, National Academy Press, 2006.
Targeting Outcomes is Essential
Medication
Errors
ADEs
Endpoint of quality improvement should be the measurable reduction in
patient harm rather than medical errors per se
Bates DW, et al. Effect of Computerized Physician Order Entry and a Team Intervention on Prevention of Serious Medication Errors.
JAMA,1998. 280(15):1311-1316.
Error Monitoring at Duke
A Multi Faceted Approach
• The Qualitative Approach  Safety Reporting (SRS)
– Provides qualitative data that informs safety and quality initiatives
– Recent upgrade to SRS 2.0 which standardizes the reporting process
– Not a reliable metric.
• The Quantitative Approach  ADE-S
– Computerized detection of ADEs; Excellent Metric
– Based on the gold standard of manual chart review
– Standardized scoring system, published inter-rater reliability
• The Global Approach  IHI Trigger Tool
– New Initiative to review 20 charts per month
Synergistic Safety Event
Detection Methodologies
DUH
February
2008
ADE-Surveillance
CS>=5, SI>=3
Voluntary
Reporting
SI>=3
189
64
3
The DUHS Voluntary Safety
Reporting System (SRS)
The Qualitative Approach
Voluntary Safety Reporting System (SRS)
The DUHS Automated Adverse
Drug Event Surveillance System
The Quantitative Approach
Computerized ADE Surveillance
ADE
Database
ADT
Pharmacist Review
Lab
Pharmacy
Orders
Event Report Generator
CDR
Daily
Reports
Possible ADEs to Pharmacist for Review
Naranjo
SI
“It is much more important to know what
sort of a patient has a disease than what
sort of disease a patient has” 1
1. William Osler. Aequanimitas: With Other Addresses to Medical Students, Nurses and
Practitioners of Medicine. New York: McGraw Hill. 1932.
Background
• Although much has been published on ADE detection in
adult populations, less is known about Pediatric ADEs
• A recent study demonstrated an 11.1% ADE rate in Children
• The potential for adverse drug events in children is
estimated to be three times higher than adult patients
• Children are not little adults. Tools must be tailored to
meet their unique needs.
- Takata, GS, et al: Development, Testing, and Findings of a Pediatric-Focused Trigger Tool to Identify Medication-Related Harm in US Children’s Hospitals. Pediatrics, 2008, 121:e927-3935.
- Goldmann D, Kaushal R. Time to tackle the tough issues in patient safety. Pediatrics. 2002;110(4):823–826
- Kaushal R, Bates DW, Landrigan C, et al. Medication errors and adverse drug events in pediatric inpatients. JAMA. 2001; 285(16):2114–2120
Why are Children at High Risk
• Children have fragile physiologies which put them at
high risk for harm when medication errors occur
• Most medications used in children are packaged for
adults
• Many pediatric doses are hand calculated
• Many children are cared for in mixed adult and
pediatric environments
- Committee on the Future of Emergency Healthcare in the United States; the Institute of Medicine; Emergency Care for Children: Growing Pains.
- Koren G. 10-fold errors in administration of drug dosing: a neglected iatrogenic disease in pediatrics. Pediatrics ; 1986: 848-849.
- Vincer MJ. Drug Errors and incidents in a neonatal intensive care unit: A quality assurance activity. Am J Dis Child. 1989; 143: 737-740.
- Cowley E, Williams R, Cousins D. Medication Errors in Children: A Descriptive Summary of Medication Error Reports Submitted to the US Pharmacopeia. Curr. Therapeutic Research. 2001; 62 (9)
Goals
– Compare and contrast voluntary ADE reporting and
automated ADE surveillance in a pediatric population
– Determine ADE rates as determined by each detection
methodology
– Identify the primary drug classes involved in pediatric
events
– Outline areas where one detection methodology is
superior to the other
– Suggest areas for improvement
Methods
• Cohort
– All patients receiving service on 7 inpatient pediatric units (3
ICUs, 2 general care, 2 transitional care) from December 2004
– Jan 2006.
• Voluntary Safety Reporting System (SRS)
– Reported events scored for severity by medication safety
pharmacists and categorized by drug and event details
• Automated ADE Surveillance (ADE-S)
– Manual chart review of all computerized triggers, which are
scored for severity and causality by clinical pharmacists
(kappa >0.88) and grouped into drug category
• Data analysis
– Descriptive statistics of ADE rates (events/1000 patient days)
– Categorical data analysis to compare rates among groups
Results
• Voluntary reporting: 93 ADEs from 849 reports
• 1.8 events/1000 patient days
• Surveillance: 78 ADEs from 1537 reports
• 1.6 events/1000 patient days
• Overlap: Only 4 ADEs shared between the two
methods
• Event location: Most ADEs occur in critical care
units
Results
Conclusions
• Quantitative approach for known high risk
drugs = ADE surveillance
• Qualitative approach to define the types of
ADEs = Voluntary reporting
Surveillance rules designed for adults (7.5/1000
patient days) perform poorly in pediatrics
(1.6/1000 patient days), meaning pediatricspecific rule sets may be required
Bridging the Gap
Empowering Caregivers with Direct Access to Safety Data
Tabular Trending Report
Aggregate Trending Report
Detailed Event Descriptions
Severity Index 4:
DrugDrug
Category
Significant adverse patient effects occurred which required an intervention
such as a code, intubation, transfer to a higher level of care, interventional
drug therapy or increased length of stay > 2 days
Morphine
Anticoagulants
Benzodiazepines
Oxycodone
Fentanyl
Antineoplastic
Agents
Opiate
Agonists
Hydromorphone
Anticoagulants
Morphine
Hypotensive Agents
Misc.Methadone
Antibiotics
Hydantoins
Insulins
OxycodoneMisc Anti-Infectives
Acetaminophen
Quinilones
HydrocodoneReplacement Preparations
Acetaminophen
Roentgenography
Remifentanil
Sympathomimetics
Antineoplastics
Fentanyl
Opiate
Agonists
Benzodiazepines
Hydromorphone
Oxycodone
Healthcare IT at Duke
Past, Present, and Future
“Error Detection in
All Care Settings”
OR View
2000
E-Rx
2007