Understanding the issues with the hospital antimicrobial consumtion data. Susan Hopkins (UK)

Understanding the issues with

Hospital antimicrobial

consumption data, UK-EN

Susan Hopkins Healthcare Epidemiologist, Public Health England Chair of the English Surveillance Programme on Antimicrobial Utilisation and Resistance Consultant in Infectious Diseases & Microbiology, Royal Free London

Public Health England & ESPAUR • English Surveillance Programme for Antimicrobial Utilisation and

Resistance (ESPAUR) was established by Public Health England (PHE) in

2013 in response to the strategy.

• Key aims:

• To develop surveillance systems to measure both antimicrobial utilisation and

resistance

• To measure the impact of antimicrobial utilisation on resistance and

patient/public safety

• To develop quality measures for optimal prescribing and markers for the

consequences of these quality measures within primary and secondary care

• To develop initiatives with key partners for both public and professional behaviour

change, including education, around antimicrobial prescribing and consumption.

2 ESPAUR - antibiotics in England

Antibiotic consumption, England 2010-2013

Total prescriptions 6%

GP 4.1%

Hospital inpatients 11.9%

Hospital outpatients stable

other community (e.g. dentists) 32%

Total antibiotic consumption by prescriber, England, 2010-2013 Total antibiotic consumption by AB group, England, 2010-2013

ESPAUR - antibiotics in England 3

GP consumption by ATs,

England, 2013

Hospital consumption, by ATs,

England, 2013

Total consumption, by ATs,

England, 2013

Significant regional variation General Practice

Durham, Darlington and Tees over 40% higher than London

26.5 compared to 18.9 DID

Hospital London twice Leicestershire and Lincolnshire

6.0 DID compared to 2.9 DID

Total Merseyside, highest (similar to Southern Europe) over 30% higher Thames Valley

30.4 DID compared to 22.8 DID

11/2/2015 ESPAUR - antibiotics in England 4

Antibacterial consumption, England


0.0

5.0

10.0

15.0

20.0

25.0

30.0

2010 2011 2012 2013

DD

D/1

00

0 in

ha

bit

an

ts/d

Year

General Practice Other (Dentist, HP10 etc) Hospital ambulatory Hospital inpatient

DDD in Hospitals

96% DDD from secondary or tertiary hospitals – large • Average admissions 98,760 per year (10,000-240,000)

• Mean day cases 40% (6-90%)

• 25% DDD parenteral

4% DDD from other hospitals • Average admissions 4,500 per year (7-27,000)

• Mean day cases 11% (0-99%)

• 10% DDD parenteral parenteral


Hospital type number admissions % total

admissions

Acute secondary/tertiary 159 14452279 95.5%

Community acute/chronic 129 295932 2.0%

Treatment centre – acute/private 169 380395 2.5%

Type of dispensed antibiotics

1. Bulk - ward or clinical area, A&E, day cases, satellite pharmacies, dialysis

• includes OPAT delivered to patient in an ambulatory setting including A&E,

dialysis, day treatment units etc

2. Individual patient

Inpatient (IP)

One-stop - to be used as inpatient or outpatient

Take away – at point of discharge to finish outside hospital; 2 weeks routine

Includes oral and parenteral (for OPAT, administered by community/ patient

Outpatient (OP) - usually from outpatient clinics, also community sites

Includes oral and parenteral (for OPAT, administered by community/ patient

Type of dispensing Inpatient Outpatient

Bulk X

Inpatient X

One-stop X

Outpatient X

Take away X

Quantities dispensed by method

Bulk IP One stop OP Take

away Total

Penicillins 9712 3950 2246 13128 10888 39924

Macrolides 1423 490 561 2879 705 6058

Quinolones 593 655 668 2144 1062 5122

Metronidazole 2011 611 198 793 1389 5002

Tetracyclines 150 213 728 1363 604 3059

Carbapenems 374 1015 7 188 32 1616

Cephalosporins 461 344 15 605 77 1502

Glycopeptides 500 486 143 144 121 1350

Aminoglycosides 130 225 37 19 411


Example of quantity dispensed for one month from a

teaching hospital, with an OPAT service

How does OPAT contribute?

Bulk IP One

Stop OP

Take

Away

Total

OPAT

% Total

Hospital

Carbapenems 22 7 188 32 249 15%

Cephalosporins 143 62 14 186 37 442 51%

Glycopeptides 1 144 93 245 20%

Aminoglycosides 37 19 56 14%


20% as day attendances (majority through A&E)

80% in the community:

60% community nurses 40% self-admin

Denominators?


y = 2.5497x + 4363.1 R² = 0.9194

-

100,000

200,000

300,000

400,000

500,000

600,000

700,000

800,000

- 50,000 100,000 150,000 200,000 250,000

pati

en

t-d

ays

admissions

Scatterplot of acute hospitals admissions and patient days, England, 2013/14

Numerator more clearly defined by admissions rather than

patient days, as ~ 1/3 of medications dispensed for

inpatients are used outside the hospital

Excellent correlation for patient-days and admissions

Scatterplot relationships for DDD/

various denominators


y = 19.232x + 91.684 R² = 0.1253

100

120

140

160

180

200

220

1.00 1.50 2.00 2.50 3.00 3.50

DD

D/1

000 i

nh

an

itan

ts/d

ay

DDD/100 bed-days

Relationship between DDD /1000 inhabitants/day and DDD/100/bed-days

across England Area Teams, 2013

y = 2.1628x + 1.7571 R² = 0.7148

100

150

200

250

300

350

400

450

500

100 120 140 160 180 200 220

DD

D/1

00 a

dm

issio

ns

DDD/100 bed-days

Relationship between DDD per 100/admissions and 100/bed-days across

England Area Teams, 2013

How to improve data?

E-prescribing Percentage

Trust has electronic-prescribing for inpatients 22.4

e-prescribing for >90% inpatients in:

Adult ICU 7.9

Paediatric/neonatal ICU 3.9

Neonatal/paediatrics 7.9

Adult medicine 15.8

Adult surgery 14.5

Geriatrics 15.8

All Areas 7.9

Other 5.3


Individual level dispensing….

When will that happen in England?

Final points

ENGLAND

1. Validation of hospital level compared to IMS Health datasets

2. Deepen understanding of hospital level data

3. Use admissions rather than bed-days or population as denomiantors

ECDC

1. Understand the differences in hospital prescribing across countries

2. Understand inpatient and outpatient differences

3. Clarify best denominators to use moving forward


Understanding the issues with the hospital antimicrobial consumtion data. Susan Hopkins (UK)

Health & Medicine

Transcript of Understanding the issues with the hospital antimicrobial consumtion data. Susan Hopkins (UK)