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Medication Error Detection and Risk Reduction Strategies

Ramona A. Davis, Pharm.D., CPPS System Director, Medication Safety Services Cleveland Clinic Department of Pharmacy

Objectives

• Discuss the prevalence of medication errors

• Review methods for the retrospective and prospective detection of medication errors

• Examine tools used in medication error analysis

• Identify risk reduction strategies for mitigation of medication errors

How problematic are medication errors?

´  To Err is Human: Building a Safer Health System (IOM)

´  November 1, 1999 ´  2% of hospital admissions

experienced a preventable adverse drug event (pADE)

´  Estimated $4,700/pADE ´  Estimated $2.8 million/

year spent on pADE for a 700 bed teaching hospital

´  Estimated $2 billion/year spent on pADE in United States

How problematic are medication errors?

´  Preventing Medication Errors: Quality Chasm Series (IOM)

´  July 20, 2006 ´  1.5 million pADEs/year in

United States ´ 380 – 450,000 inpatient ´ 800,000 long-term care ´ 530,000 outpatient

´  Does not include estimates of errors of omission – failure to prescribe in cases when a medication should be taken

Sebastian Ferrero

Josie King Betsy Lehman

Jasmine Gant

Emily Jerry

Chemo error kills patient Alberta health official apologizes to family of woman given overdose Powerful cancer drug administered over four hours instead of four days Sep. 1, 2006. 01:00 AM CANADIAN PRESS

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Medication Errors Percentage of Distribution

´ Systems Analysis of Adverse Drug Events (1995):

´ Physician ordering (39%) ´ Nurse administration (38%) ´ Transcription/verification (12%) ´ Pharmacy dispensing (11%)

Leape et al., 1995

48% were caught

2% were caught

33% were caught

34% were caught

Voluntary Event Reporting

´  Most systems rely on voluntary reporting of errors and near-miss events

´  While voluntary reporting may give insight into problematic issues or trends, it is by no means all-inclusive

´  Pros: confidential, unrestricted, timely, systems-oriented, can identify trends

´  Cons: lack of details, incomplete reporting, underreporting, reporting biases

Tip of the Iceberg

SERS (Safety Event Reporting System) IHI Global Trigger Tool Methodology • Trigger-based manual chart review

• Review team: minimum 3 reviewers; 2 reviewers (w/ clinical background), 1 physician

• Review process: 20 charts per month; 20 minutes/chart; 2 reviewers review chart independently and then meet to reach consensus; Physician- authenticates consensus decision

• Pros: measures harm over time, detects more events than voluntary reporting systems • Cons: cannot be used to determine preventability of errors, focus on errors of commission, manual process (time consuming)

Observation Based Medication Error Detection

´  Direct observation of medication administration during peak workload periods in selected nursing units

´  Observations are recorded and compared to the patients' charts to identify any

discrepancies between the observed administration and the physician's orders ´  Results are entered into a database and the observer meets with the observed nurse to

validate any discrepancies as errors and to solicit assistance in seeking “clues to cause” ´  Direct observation based research in 2002 showed that 605 out of 3216 doses

administered (19%) were given in error (nearly 1 of every 5 doses) ´  The rate of potentially harmful errors was 7%, or more than 40 per day in a 300-patient

facility Barker et al., 2002

´  Pros: not affected by lack of error awareness, lack of willingness to report errors or faulty memory

´  Cons: demands on observer, costly

Failure Mode & Effects Analysis (FMEA)

´  FMEA is a process used to identify risk within a process: “What could go wrong?”

´  Failures are prioritized according to how serious their consequences are, how frequently they occur and how easily they can be detected

´  Pros: proactive assessment tool (can be used for retrospective analysis) ´  Cons: bias in severity ratings, potential for “scope creep”, highly dependent

on team

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Failure Mode & Effects Analysis (FMEA)

Risk Priority Number (RPN) O = the rank of the occurrence of the failure mode S = the rank of the severity of the failure mode D = the rank of the likelihood the failure will be detected before reaching the patient All ranks are given on a scale from 1 to 10. The risk priority number (RPN) is defined as:

RPN = S × O × D

The larger the RPN, the greater the risk of failure in the process

Additional Detection Methods

´  Comparison of medications removed from ADC with prescriber orders

´  Clinical surveillance software (e.g. TheraDocTM , Sentri7®)

´  Monitoring of doses returned to the pharmacy

´  Comparison of MAR with prescriber orders

´  “We must accept human error as inevitable — and design around that fact.”

Don Berwick MD, MPP,FRCP (former Administrator, Centers for Medicare & Medicaid Services,

former President IHI)

Two kinds of error – Active and Latent

´  Active ´  Occur at the point of contact

between a human and some aspect of a larger system (e.g., a human-machine interface)

´  Generally readily apparent (e.g., pushing a wrong button, ignoring a warning light)

´  “Sharp end” - Almost always involves someone at the frontline

– MD who operates on wrong leg or RN who programs pump incorrectly

´  Latent ´  Less apparent failures of design or

systems that contributed to the error ´  “Blunt end” – Referring to the many

layers of the health care system that affect the person providing direct patient care ´ Use of multiple types of infusion

pumps at an institution making programming errors more likely

James Reason’s Swiss Cheese Model

Reason et al., 2001

Root Cause Analysis (RCA)

´  A process to identify the basic and causal factors that underlie variations in performance.

´  Focuses primarily on the systems and processes, not individual performance.

´  Identifies potential improvements in processes that would tend to decrease the likelihood of an event in the future or that no such improvement opportunity exists.

´  An action plan is the result of the RCA.

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RCA Tools: Cause & Effect Diagram (Fishbone or Ishikawa Diagram)

´  Graphical illustration of RCA ´  Identify the

problem/issue ´  Brainstorm ´  Draw fishbone

diagram ´  Align outputs

with cause categories

´  Allocate causes ´  Analyze for root

causes ´  Test for reality

RCA Tools: 5 Whys

´  Simple way to conduct analysis ´  Can be used to determine the relationship between different root

causes of a problem Example: The Washington Monument was disintegrating Why? Use of harsh chemicals Why? To clean pigeon poop Why so many pigeons? They eat spiders and there are a lot of spiders at the monument Why so many spiders? They eat gnats and there are lots of gnats at the monument Why so many gnats? They are attracted to the light at dusk. Solution: Turn on the lights at a later time.

Error Reduction Overview: Hierarchy of Controls

Error Reduction Strategies

´  Use visual controls ´  Avoid reliance on memory ´  Simplify and Standardize ´  Use constraints/forcing functions ´  Use protocols and checklists ´  Improve access to information ´  Reduce handoffs ´  Decrease look-alike / sound-alikes ´  Automate carefully ´  Reduce interruptions and distractions ´  Take advantage of habits and patterns ´  Promote effective team functioning ´  Specific

References ´  AHRQ (Agency for Healthcare Research and Quality) <http://www.ahrq.gov/>.

´  AU MEDS <http://www.medaccuracy.com/>.

´  Barker, K., E. Flynn, G. Pepper, D. Bates, and R. Mikeal. "Medication Errors Observed in 36 Health Care Facilities." Archives of Internal Medicine 162.16 (2002): 1897-903.

´  Bates, D., D. Cullen, N. Laird, L. Petersen, S. Small, D. Servi, G. Laffel, B. Sweitzer, B. Shea, R. Hallisey, M. Vander Vliet, R. Nemeskal, and L. Leape. "Incidence of Adverse Drug Events and Potential Adverse Drug Events." Journal of the American Medical Association 274.1 (1995a): 29-34.

´  Bates, D., D. Boyle, M. Vander Vliet, J. Schneider, and L. Leape. "Relationship between Medication Errors and Adverse Drug Events." Journal of General Internal Medicine 10.4 (1995b): 199-205.

´  IHI (Institute for Healthcare Improvement) <http://www.ihi.org/>.

´  ISMP (Institute for Safe Medication Practices) <http://www.ismp.org/>.

´  IOM (Institute of Medicine). To Err Is Human: Building a Safer Health System. Washington, D.C.: National Academy, 2000.

´  IOM. Preventing Medication Errors. Washington, DC: National Academies, 2007.

´  Kaushal, R., D. Bates, and C. Landrigan. "Medication Errors and Adverse Drug Events in Pediatric Inpatients." Journal of the American Medical Association 285.16 (2001): 2114-120.

´  Leape, L., D. Bates, D. Cullen, J. Cooper, H. Demonaco, T. Gallivan, R. Hallisey, J. Ives, N. Laird, G. Laffel, R. Nemeskal, L. Petersen, K. Porter, D. Servi, B. Shea, S. Small, B. Sweitzer, T. Thompson, and M. Vander Vliet. “Systems Analysis of Adverse Drug Events.” Journal of the American Medical Association 274.1 (1995): 35-43.

´  Medmarx/Quantros <http://www.medmarx.com/>

´  Reason, J., J. Carthey, and M. De Leval. "Diagnosing "Vulnerable System Syndrome": An Essential Prerequisite to Effective Risk Management." Quality in Health Care 10.Suppl II (2001): ii21-ii25.

´  Human Factors. Bonacum, Doug IHI Patient Safety Executive Development Program

´  TJC (The Joint Commission) <http://www.jointcommission.org/>.

´  USP (The United States Pharmacopeia) <http://www.usp.org/>.

´  WHO (World Health Organization) <http://www.who.org/>.