2020-12-09

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Off-label drug use, medication errors

and adverse drug events - among

Swedish pediatric inpatients

Per Nydert

Handledare:

Professor Mikael NormanKarolinska InstitutetInstitutionen för klinisk vetenskap, intervention och teknik. Enheten för pediatrik

Bihandledare:

Docent Synnöve LindemalmKarolinska InstitutetInstitutionen för klinisk vetenskap, intervention och teknik. Enheten för pediatrik

Mentor:

Farm. Dr Peter PerssonCapio S:t Görans sjukhus, Stockholm

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Outline

Short background

Hypothesis and objectives

Papers

I. Kimland E, Nydert P, Odlind V, Böttiger Y, Lindemalm S. Paediatric drug use with focus on off-label prescriptions at Swedish hospitals – a nationwide study. Acta

Pæd 2012;101:772–8

II. Nydert P, Kumlien A, Norman M, Lindemalm S. Cross sectional study identifying high-alert substances in medication error reporting among Swedish pediatric inpatients Acta Pæd 2020 [Epub ahead of print]

III. Nydert P, Unbeck M, Pukk Härenstam K, Norman M, Lindemalm S. Drug Use and Type of Adverse Drug Events – Identified by a Trigger Tool in Different Units in a Swedish Pediatric Hospital. Drug, Healthcare and Patient Safety 2020;12:31-40

IV. Nydert P, Veg A, Bastholm-Rahmner P, Lindemalm S. Pediatricians' Understanding and Experiences of an Electronic Clinical-Decision-Support-System, Online J Public Health Inform 2017;9(3):e200

Per Nydert

Short background

Definitions:

Off-label use

Medication Errors (ME)

Adverse Drug Events (ADE)

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auth

ori

zed w

ays

of pre

scri

bin

g d

rugs

AvailabilityProduct

monographEvidence Example

registered

on-label

good penicillin V

poor cough syrup

off-label

goodmorphine to

newborn

economic issuerituximab to

adult with MS

poorfosaprepitant to

newborn

unlicensed

on-label good/poorchlortiazide to

child

off-label* good/poorchlortiazide to

newborn

extemporanous

large quantitiesphenobarbital

oral solution

small quantitiesspironolactone

oral solution

clinical trial aquiringclinical trial

substance

Off-label use

Per Nydert 5

*

*

Pictures from

life-time.setsunagujapan.comapl.seapoteket.se

Simplified distinction of off-label between the

regulation, the use of drugs and liability issues

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Type Regulation Usage Liability

System Pharmaceutical industry Health-care Insurance

Body Medical product agency National board of health and

welfare

Ministry of finance

Guiding regulation European/National National National

Process Drug distribution Drug handling Compensation

Simplified off-label

definition

Usage not stated in

product monograph.

Evidence- and experience-

based, intentional deviation

from product monograph

Organizational or

individual prescriber

decision

Mission Safe and single market

for medicinal products

Relation between

practitioner and patient.

Assures the responsibility

of the health-care regions

(LÖF) and the

pharmaceutical industry (LF)

Harm by intentional

use

Addressing filed report by

pharmacovigilance

File report of harm by drug

(adverse drug reaction)

Addressed by LF or LÖF

Harm by unintentional

use

* File report of harm by process

(medication error)*

Addressed by LÖF

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Definition of medication errors (ME)

and adverse drug events (ADE)

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risk

non-

preventable

harm = ADR

potential

harmerror = MEpreventable

harm = ADE

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Classification of ME and ADE

A

B

CDEF

G

H

IA

B-D

E-H

I

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System centered and

patient centered processes

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Process

Evaluation

System centered Patient centered

Outcome Root-cause analysis of ME/ADE Actual DRP by retrospective

medication review

Potential

outcome

Risk/Effect analysis (HFMEA) of

potential ME/ADE

Potential DRP by prospective

medication review

Type Latent Active

Terms used ME/ADE DRP

Documentation Incident reports Note in patient chart

Examples Potential ME/ADE: How can we

optimize the dosing schedule?

Prospective DRP: We need to

adjust the next dose.

ME/ADE: How can we avoid

reoccurrence?

Retrospective DRP: A too large

dose of morphine required

naloxone. Patient is stabilized and

adequately monitored.

Medication review with

potential DRP

Medicationreview with

actual DRP

Root-cause analysis of

ME/ADE

Risk/effect analysis of

potential ME/ADE

Examples of detection methods

*used in this thesis

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Method Mandated in Sweden Main

usage

Main type of failures Main finding

National ADR reports Yes Practice Latent ADR

*National severe reports (Lex Maria) Yes Practice Active/Latent ME/ADE

*Local incident reports Yes Practice Active/Latent ME/ADE

Administrative data No Practice Active/Latent ADE

*Clinical decision support systems System dependent Practice Active DRP/ME

*High-alert drugs No Practice Active ME

Drug chart review ≥75 years, ≥5 drugs Practice Active DRP/ME/ADE

*Triggers No Research Active ADE

Direct observation No Research Active/Latent ME

*Personnel and patient perspective No Research Active/Latent DRP/ME/ADE

Mixed-model No Research Active/Latent ME/ADE

Audit (clinical) No Audit Latent Risk

HFMEA No Audit Latent Risk

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Prevention of medication errors in pediatrics

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A Cochrane review studied 5 185 publications

7 were included with the goal of reducing ME or preventable ADE

Maaskant et al. Interventions for reducing medication errors in children in hospital.

Cochrane Database of Systematic Reviews 2015, Issue 3. Art.No.: CD006208

Hypothesis and objectives

We hypothesized that off-label use and ME is common in pediatrics and that health record data can help us to investigate the problem and understand the impact on patient safety.

Aims

I. Estimate the prevalence of drug use with focus on off-label

II. Investigate the characteristics of reported pediatric MEs and the prevalence of high-alert substances

III. Determine the incidence and type of ADE as identified by a pediatric trigger tool

IV. Explore pediatricians’ experiences of a clinical decision support

system (CDSS)

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Paper I Off-label drug use

I

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Objectives

Collect detailed information on prescribed drugs in the Swedish pediatric inpatient population.

Estimate the use of off-label (OL), unlicensed (UL) and extemporaneously prepared drugs (EPD)

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Methods

Descriptive cross sectional study, 2+2 days May and October 2008

Pediatric patients <18 years with drug treatment

41 hospitals

All orders checked for OL+UL+EPD

Off label

Age

Weight

Not recommended

Lack of pediatric data

Contraindication

Lack of indication

Route

I

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Orders

n = 11 294

Neonates

n = 1 875

69%

2.7(2.5-3)

Infants

n = 2 644

55%

2.1(1.9-2.3)

Children

n = 3 800

47%

1.7(1.6-1.8)

Adolescent

n = 2 975

34%

1.4(1.2-1.5)

Total orders

Result (I)

OL+UL+EPD %

(orders per pat)

2 947 patients

11 294 orders

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Results (II)

Some examples, % of all prescriptions OL+UL+EPD

ATC N: Paracetamol 2.8% (Off-label by age)

ATC B: Fluid therapy (Off-label by lack of pediatric data)

Carbohydrates 4.2%

TPN 2.7%

ATC A: Multivitamins 1.9% (Unlicensed)

ATC N: Caffeine citrate 0.8% (Extemporaneous)

I

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Conclusion Paper I

Pediatric OL+UL+EPD use is common at Swedish hospitals

OL+UL+EPD prescribing is most abundant in the neonatal population

The list of drugs have been sent to EMA Ongoing need for pediatric clinical trials

Ongoing need for compilation of existing clinical experience

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I

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Paper II Medication errors

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II

Objectives

Characterize national drug incident reports

Identify known high-alert substances from three different lists

Find the occurrence of high-alert substances in the incident reports from a local university hospital

Example of a short high-alert list (Colquhoun et al 2009)

Morphine

Fentanyl

Insulin

Potassium

Salbutamol

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II

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Methods

Analytical cross-sectional study

National reports:

Drug related national incident reports (Lex Maria) and complaints was retrieved from the Health and Social Care Inspectorate (IVO) 2011-2017

Investigating type of ME and harm by NCCMERP

Local reports:

Drug related local incident reports from Karolinska University Hospital 2011+2017.

Investigating substance involved and number of days a drug was administered (DDA).

In relation to high-alert substances in three lists

Long (12+21 ISMP), Medium (14+4 Maaskant), Short (5+0 Colquhoun)

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II

Two populations

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Inpatient with drug

Included

National - 7 years

1 164 LexM2 863 Complaints

150 (13%) LexM

54 (1.9%) Complaints

144 (12%) LexM

16 (0.6%) Complaints

Local - 2 years

4 295 reports

1 221 (28%) reports

885 (21%) reports

II

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Results (National data)

127 (79%) 0-6 years

108 (67%) Large university hospital region

105 (66%) Intravenous route

105 (66%) Potency errors

57 (36%) Prescribing with 34 (21%) wrong dose

45 (28%) Dispensing with 30 (19%) wrong concentration

58 (36%) Administration with 21 (13%) identity errors

32 (20%) No harm (A-D)

98 (61%) Temporary harm (E-F)

30 (19%) Long-term harm, major interventions or death (G-I) More common among children over 6 years RR=7 (2.2.-23)

Other type of modal events (omissions, technical errors) compared to dosing RR=9.2 (1.7-51)

Substances on all the high alert lists compared to non-alert substances RR=4.1 (1.5-11)

Per Nydert 23

II

Substance Total Prescribe Dispense Administrate

morphineSML 12 (7.5) 3 (5.3) 1 (2.2) 8 (14)

vancomycin 11 (6.9) 4 (7.0) 3 (6.7) 4 (6.9)

potassiumSML 7 (4.4) 2 (3.5) 3 (6.7) 2 (3.4)

midazolamL 5 (3.1) 2 (3.5) 2 (4.4) 1 (1.7)

heparinSL 5 (3.1) – 2 (4.4) 3 (5.2)

dalteparinL 5 (3.1) 1 (1.8) 4 (8.9) –

furosemide 4 (2.5) 2 (3.5) 1 (2.2) 1 (1.7)

clonidine 4 (2.5) 1 (1.8) 2 (4.4) 1 (1.7)

insulinSML 4 (2.5) – 2 (4.4) 2 (3.4)

fluid therapy 4 (2.5) – – 4 (6.9)

High‐‐‐‐alertS 27 (17) 6 (11) 7 (16) 14 (24)

High‐‐‐‐alertM 56 (35) 15 (26) 16 (36) 25 (43)

High‐‐‐‐alertL 76 (47) 23 (40) 29 (64) 24 (41)

All 160 (100) 57 (100) 45 (100) 58 (100)

Results (National high-alert substances)

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II

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Results (Local data)

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insulin

immunosuppresants

cytotoxics

anestetics

antibiotics blood substitutes and perfusions solutions

analgetics

drugs for acid related disorders

vitamins

Log (local incidences)

Log (local DDA)

Bubble size (national reports)

II

Results (Local high-alert substances)

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High-alert list Reports (%) DDA (%) Prevalence OR (CI 95%)

Short 88 (10) 33 420 (6.3) 0.26% 1.6 (1.3-2.0)

Medium 249 (28) 68 247 (13) 0.36% 2.7 (2.3-3.1)

Long 294 (33) 95 049 (18) 0.31% 2.3 (2.0-2.6)

All 885 (100) 530 184 (100) 0.17%

II

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Conclusion Paper II

17/35/47% of the national reports included high-alert substances from the short/medium/long list

Higher proportion of high alert-drugs among national reports with severe harm (NCC MERP G-I)

The prescribing, dispensing, administration have specific error types.

Local incident reports trends with volume of DDA

Prevalence of local reports is overall 0.17 reports/100 DDA but is 0.26/0.36/0.31 reports/100 DDA for the high-alert list substances.

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II

Paper III Adverse drug events

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III

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Objectives

To identify Adverse Drug Event (ADE) over time by a trigger-tool

The incidence rate of ADEs

Type of ADEs

e.g. naloxone as trigger

“if naloxone given – too much morphine might have been given”

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III

Methods

All inpatient admissions (>24 h) 2010

Cohort of 600 admissions stratified by unit of care 150 Neonatal

150 Surgery / Orthopedics

150 Medicine

150 Emergeny medicine

Registered nurses screened for 88 triggers (17 drug focused)

Pediatricians reviewed potential AE Causation

Prevention

Drug Association (ADE)

Severity (NCC MERP)

Clinical outcome (eg. Vascular harm, Pain, Hospital acquired infection)

III

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Causation

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Outcome

DrugIncident

High doseLiver failure

Misplaced deviceDiscomfort AE ADEADE

III

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Cohort

n = 600

Neonatology

LOS = 3 531

201 ADE

6 ADE≥F 4%

Surgery / Orthopedics

LOS = 812

44 ADE

4 ADE≥F 9.1%

Medicine

LOS = 1 065

47 ADE

7 ADE≥F 15%

Emergency

Medicine

LOS = 697

10 ADE

2 ADE≥F 20%

Trigger analysis

Results (I)

57 (49-65)

ADE/1000 d

54 (40-73)

ADE/1000 d

44 (33-59)

ADE/1000 d

14 (7.7-27)

ADE/1000 d

Number of ADE

NCCMERP ≥F

Rate of ADE

III

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Results (II) Admissions over time

with specified ADE by unit

III

Other studies / difficult to compare

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Year Author Patients T N

(harmed)

X

type

% ≥F X /1000

LOS

X/100 N N with X

/100 N

2002 Takata 12 Hospitals 15 960 (70) ADE 3.0% 15.7 11.1 7.3

2009 Kirkendall Academic center 53

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240 (62)

240 (-)

AE

ADE

24%

-

76.3

-

36.7

25

25.8

-

2010 Nydert All (weighted)

All drug-focused

88

17

600 (121)

600 (35)

ADE 8.0%

4.6%

47.4

7.0

41.7

7.2

20.2

5.8

Number of triggers / ADE or AE / Severity / Denominator

T - Trigger

III

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Conclusion Paper III

The incidence of ADE was high when including harm due to devices used for deliver drugs

Most harm was minor but NCCMERP ≥F occurred more than weekly in the study population.

Type of ADE varied with LOS and type of unit.

Comparing to other ADE-studies we have reported high numbers due to a broad inclusion criteria

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III

Paper IV Qualitative study on CDSS

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IV

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Objectives

Explore how pediatricians understand and experience a CDSS with a dose-range check and a weight-based dose calcualtion?

Per Nydert 37

IV

Methods

Qualitative study

Semi structured interviews, audio-recorded 25-40 min

17 pediatricians, Sampling by snowball stratergy 4,9% of all, 65% had a consultant role

Transcribed (NVivo8)

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IV

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Results

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17 pediatricians

Use

Clinical experience

Habits

Good not compulsory

Benefit

Prompts consideration

Help with calculations

Good in Emergency

care

Confidence

Still use manual check

Double checking

Disregards

When easy calculations

Special indications

Misgivings,

risks

Non diseasespecific

Unavoidable errors

Wrong weight

Development

Optional or compulsory

Signing for weight

IV

Conclusion Paper IV

Six categories and fourteen subcategories were identified that illustrated the post-development phase of a CDSS

The CDSS was appreciated with suggested improvments

The qualitative method did identify unfinished parts in the development of CDSS.

Per Nydert 40

IV

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Implications Paper I-IV

Paper I has helped to acknowledge the off-label situation in Sweden on a national and European level to achieve better medicines for children.

Paper II has suggested a high-alert list strategy based on process.

Paper III suggest that drug-therapy work should include a focus on preventing vascular harm, HAI and insufficiently treated pain. Knowing the time and unit scenario.

Paper IV can help in the implementation of new systems with dose-range check in Sweden as it is a recommendation to have in EMR by regulation HSLF-FS 2017:37.

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Thank you !

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Thank you !

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Drug and off-label use (I)

Off-label, Unlicensed, Extemporanous

Experimental

Consensus based

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Detection of pediatric ME and ADE

Incident reports

0.15 ME/100 admissions (Ross 2018)

0.56 ME/100 admissions (Manias 2018)

15 ME/100 admissions (Raju 1989)

Trigger tool

5 ADE /100 admissions (Maaskant 2015)

11 ADE /100 admissions (Takata 2008)

29 ADE/100 admissions (Burch 2011)

Personnel and patient perspective

Qualitative

Real time warnings

High-alert drugs

Dose-range check (CDSS)

Per Nydert 45

Use data carefully

1) Culture2) Method3) Denominator4) Causality

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