Improving Patient Safety Outcomes:Improving Patient Safety Outcomes:Impact of BarImpact of Bar--code Technologycode Technology

11

Mitchell Buckley, PharmD, BCPSMitchell Buckley, PharmD, BCPS

Clinical Pharmacy SpecialistClinical Pharmacy Specialist

Banner Good Samaritan Medical CenterBanner Good Samaritan Medical Center

Phoenix, AZPhoenix, AZ

January 11, 2010January 11, 2010

DisclosureDisclosure

•• No financial disclosuresNo financial disclosures

2

ObjectivesObjectives

•• Review medication error epidemiologyReview medication error epidemiology

•• Evaluate barEvaluate bar--code technology studies impacting dispensing and code technology studies impacting dispensing and administration errorsadministration errors

•• Discuss types and severity of errors affected by barDiscuss types and severity of errors affected by bar--codingcoding

3

Technology Prevention Strategies

Electronic Medication Electronic Medication Administration RecordAdministration Record

BarBar--coded Medication coded Medication AdministrationAdministration

Automated MedicationAutomated MedicationDispensing MachineDispensing Machine

44

PrescribingPrescribing TranscriptionTranscription DispensingDispensing AdministrationAdministration

Computerized Physician Computerized Physician Order EntryOrder Entry

IV Infusion IV Infusion Safety PumpsSafety Pumps

Oren E. Am J Health Syst Pharm 2003;60:1447Oren E. Am J Health Syst Pharm 2003;60:1447--14581458

Medication Error EpidemiologyMedication Error Epidemiology

55

BackgroundBackground

•• 1.5 million patients harmed by medications in U.S. annually1.5 million patients harmed by medications in U.S. annually

•• Hospitalized patients at risk for medication errorsHospitalized patients at risk for medication errors

•• 19% of all medical errors were medication19% of all medical errors were medication--relatedrelated

•• 400,000 preventable ADEs per year400,000 preventable ADEs per year

(~1 medication error / patient / year)(~1 medication error / patient / year)

6

(~1 medication error / patient / year)(~1 medication error / patient / year)

•• 78% of medical errors in ICU associated with medications78% of medical errors in ICU associated with medications

•• 28% of ADEs estimated to be preventable28% of ADEs estimated to be preventable

•• Increased hospital length of stay, cost and mortalityIncreased hospital length of stay, cost and mortality

Bates DW. Am J Health Syst Pharm 2007;64(Suppl 9):S3Bates DW. Am J Health Syst Pharm 2007;64(Suppl 9):S3--S9S9

Rothschild JM. Crit Care Med 2005;33:533Rothschild JM. Crit Care Med 2005;33:533--540540

Leape LL. N Engl J Med 1991;324:377Leape LL. N Engl J Med 1991;324:377--384384

Bates DW. JAMA 1995;274:29Bates DW. JAMA 1995;274:29--3434

Overall Medication Error Rate: Distribution in Medication Use Process

Administration

38%

Prescribing

39%

77

Transcription

12%Dispensing

11%

Leape LL. N Engl J Med 1991;324:377Leape LL. N Engl J Med 1991;324:377--384384

Incidence of ICU Medication Errors:Distribution in Medication Use Process

77

60

80

100

Pe

rce

nta

ge

(%

)P

erc

en

tag

e (

%)

Potential ADEs (n=110)Potential ADEs (n=110)

Actual Preventable ADEs (n=22)Actual Preventable ADEs (n=22)

88

Kopp BJ. Crit Care Med 2006;34:415Kopp BJ. Crit Care Med 2006;34:415--425425

28

5

34 34

0 0

23

0

20

40

60

Prescribing Transcription Dispensing Administration

Pe

rce

nta

ge

(%

)P

erc

en

tag

e (

%)

Stage of the Medication Use ProcessStage of the Medication Use Process

Severity of ICU Medication Errors:Distribution in Medication Use Process

80

100

SeriousSerious

SignificantSignificant

FatalFatal

LifeLife--ThreateningThreatening

Pe

rce

nta

ge

(%

)P

erc

en

tag

e (

%)

99

Kopp BJ. Crit Care Med 2006;34:415Kopp BJ. Crit Care Med 2006;34:415--425425

0

20

40

60

Prescribing Transcription Dispensing Administration

Pe

rce

nta

ge

(%

)P

erc

en

tag

e (

%)

(n=48)(n=48) (n=5)(n=5) (n=37)(n=37) (n=42)(n=42)

BCMA Technology Impact:Published Data

1010

Medication Errors & Potential ADEs:Before and After BCMA Implementation

• Objective

• Evaluate BCMAs impact of on dispensing errors

• Methods

• 735-bed tertiary care academic center

• Before and after observational study

1111

• Before and after observational study

• Data collected over 20 month period

PoonPoon EG. Ann Intern Med 2006;145:426EG. Ann Intern Med 2006;145:426--434434

Medication Errors & Potential ADEs:Before and After BCMA Implementation

60

80

100Annual Error Prevention ProjectionsAnnual Error Prevention Projections

•• >13,500 dispensing errors>13,500 dispensing errors

•• >6000 potential ADEs>6000 potential ADEs

p<0.0001p<0.0001

36%36%ReductionReduction

1.0

0.8

0.6

Pe

rce

nta

ge

(%

)P

erc

en

tag

e (

%)

1212

PoonPoon EG. Ann Intern Med 2006;145:426EG. Ann Intern Med 2006;145:426--434434

0

20

40

60

Dispensing Error Rate Potential ADE Rate

PrePre--Bar Code PeriodBar Code Period PostPost--Bar Code PeriodBar Code Period

p<0.0001p<0.0001

63%63%ReductionReduction

0.6

0.4

0.2

0

Pe

rce

nta

ge

(%

)P

erc

en

tag

e (

%)

Medication Errors in the ICU:Before and After BCMA Implementation

• Objective

• Measure the impact of BCMA on medication

administration error rates in MICU

• Methods

• 744-bed community, teaching hospital

1313

• 744-bed community, teaching hospital

• 38-bed MICU

• Direct observation technique

DeYoungDeYoung JL. Am J Health JL. Am J Health SystSyst PharmPharm 2009;66:11102009;66:1110--55

Incidence of Medication Errors:Impact of BCMA in the ICU

• Before BCMA

• n=47 patients

• 153 errors / 775 administrations

p<0.001

19.720

25

30

35

40

Inc

ide

nc

e (

%)

14

• 153 errors / 775 administrations

• After BCMA

• n=45 patients

• 60 errors / 690 administrations

DeYoungDeYoung JL. Am J Health JL. Am J Health SystSyst PharmPharm 2009;66:11102009;66:1110--55

Before After

19.7

8.7

0

5

10

15

20

Implementation Phase

Inc

ide

nc

e (

%)

Type of Error

p<0.001

Pe

rce

nta

ge

(%

)P

erc

en

tag

e (

%)

15

Wrong Time

DeYoungDeYoung JL. Am J Health JL. Am J Health SystSyst PharmPharm 2009;66:11102009;66:1110--55

Omission Wrong Drug Documentation

p=NS

p=NS

p=NS

Pe

rce

nta

ge

(%

)P

erc

en

tag

e (

%)

BCMA Impact on Medication Errors:ICU vs. General Ward

• Objective

• Measure the impact of BCMA on administration

error rates in multiple patient care areas

• Methods

• Prospective, observational study

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• Prospective, observational study

• 386-bed academic teaching hospital

• Multiple patient care areas

• 2 medical-surgical wards

• MICU

• SICU

Helmons PJ. Am J Health Syst Pharm 2009;66:12021210Helmons PJ. Am J Health Syst Pharm 2009;66:12021210

Overall and “Wrong-Time” Error Types:ICU vs. General Ward

p=NS

p=NSOverall• No difference in error rate (ICU or non-ICU)

General Ward• Increase in “wrong-time

errors” after BCMA• 58% decrease after BCMA

17

Helmons PJ. Am J Health Syst Pharm 2009;66:12021210Helmons PJ. Am J Health Syst Pharm 2009;66:12021210

(excluding “wrong-time”errors)

ICU• No differences

Types of Errors Excluding “Wrong-Time”:ICU vs. General Ward

General Ward• Decrease in “omission” errors

(p<0.0001)• Decrease in “drugs not available” errors

(p<0.05)

ICU

18

Helmons PJ. Am J Health Syst Pharm 2009;66:12021210Helmons PJ. Am J Health Syst Pharm 2009;66:12021210

• No differences

Severity of Drug Administration Errors

• Objective

• Evaluate the severity of potential medication errors

during administration phase intercepted by BCMA

• Methods

• 6 community hospitals

1919

• 6 community hospitals

• Same BCMA system

• Multidisciplinary reviewing panel (n=6)

• Medication Errors classified by severity

• Minimal

• Moderate

• Severe

SakowskiSakowski J. Am J HealthJ. Am J Health--SystSyst PharmPharm 2008;65:16612008;65:1661--16661666

Results

• Overall severity

• 945 total errors detected

• 9% (n=81) were “Moderate” or “Severe”

• “Moderate” or “Severe” errors by type

• 21% “no order”

2020

• 21% “no order”

• 9% “discontinued or expired order”

• 4% “dose early”

• 4% “wrong dose”

• Errors involving “high-alert” medications

• 20% = insulin, narcotics, potassium, sodium, anticoagulants

• Narcotics most common of “high-alert” drugs (74%)

SakowskiSakowski J. Am J HealthJ. Am J Health--SystSyst PharmPharm 2008;65:16612008;65:1661--16661666

Conclusion

• Types of errors impacted by BCMA varied between ICU and non-ICU patient care areas

• Although the clinical significance of “wrong-time” errors remains controversial, BCMA has the potential reduce other clinically important medication errors

• Medication errors still occur despite BCMA suggesting the

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• Medication errors still occur despite BCMA suggesting the necessity for continued process improvement and further system changes to compliment this technology

• Studies limited by low baseline prevalence of medication error

• Dispensing and administration errors were significantly decreased with BCMA technology

QuestionsQuestions

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Incidence of Medication Errors:Intensive Care Unit vs. General Ward

30

40

50

ICUICU General WardGeneral Ward

Pe

rce

nta

ge

(%

)P

erc

en

tag

e (

%)

p=NSp=NS

p=NSp=NS

2323

Cullen D. Cullen D. CritCrit Care Med 1997;1289Care Med 1997;1289--12971297

0

10

20

30

Prescribing Transcription Dispensing Administration

Stage of the Medication Use ProcessStage of the Medication Use Process

Pe

rce

nta

ge

(%

)P

erc

en

tag

e (

%)

p=NSp=NS p=NSp=NS

Bar-code Medication Administration Technology Prevalence

30

40

Perc

enta

ge (

%)

Perc

enta

ge (

%)

U.S. Hospitals with BCMAU.S. Hospitals with BCMA

30

40

Perc

enta

ge (

%)

Perc

enta

ge (

%)

BCMA Acquisition PlansBCMA Acquisition Plans

2424

Pedersen C. Am J Health Syst Pharm 2008;65:2244Pedersen C. Am J Health Syst Pharm 2008;65:2244--22642264

0

10

20

30

2002 2005 2007 2008

Perc

enta

ge (

%)

Perc

enta

ge (

%)

YearYear

0

10

20

<1 >3 No Plan

Perc

enta

ge (

%)

Perc

enta

ge (

%)

Implementation Timeframe (Years)Implementation Timeframe (Years)11-- 33