Opioid Use and Related Harms in NSW...2 NSW Health Opioid Use and Related Harms in NSW Executive summary The rate of opioid-related deaths increased between 2004 and 2015, and has

Opioid Use and Related Harms in NSWSurveillance Report to December 2019

ii NSW Health Opioid Use and Related Harms in NSW

NSW Ministry of Health 1 Reserve Road ST LEONARDS NSW 2065 Tel. (02) 9391 9000 Fax. (02) 9391 9101 TTY. (02) 9391 9900 www.health.nsw.gov.au

Produced by: NSW Ministry of Health

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© NSW Ministry of Health 2020

SHPN (CAOD) 200656 ISBN 978-1-76081-505-9

Further copies of this document can be downloaded from the NSW Health website www.health.nsw.gov.au

November 2020

NSW Health Opioid Use and Related Harms in NSW 1

Contents Executive summary .........................................................................................................................2

Opioid use in NSW.................................................................................................................................................2

Opioid-related harms in NSW ...........................................................................................................................3

1. Opioid use ................................................................................................................................... 41.1 Prescription opioids dispensed under the Pharmaceutical Benefits Scheme ........................4

1.2 Opioid use at the population level ......................................................................................................... 10

1.3 Opioid use in selected populations in NSW ...................................................................................... 14

1.4 Heroin purity .................................................................................................................................................. 15

2. Health harms from opioid use ............................................................................................... 172.1 Suspected opioid-related ambulance callouts ..................................................................................17

2.2 Opioid-related emergency department presentations ................................................................. 18

2.3 Opioid-related hospitalisations .............................................................................................................. 22

2.4 Treatment episodes for opioid use .......................................................................................................30

2.5 Opioid-related deaths ................................................................................................................................. 31

2.6 Opioid-related calls to drug information services .......................................................................... 35

3. Limitations of the data ........................................................................................................... 38Pharmaceutical Benefits Scheme (PBS) data .......................................................................................... 38

Survey data ............................................................................................................................................................ 38

Routinely collected data .................................................................................................................................. 39

Appendix A: Data sources and descriptions ..........................................................................40

Appendix B: Reference list ......................................................................................................... 42

Appendix C: Case selection for PBS and NSW Health data ..............................................43

2 NSW Health Opioid Use and Related Harms in NSW

Executive summaryThe rate of opioid-related deaths increased between 2004 and 2015, and has subsequently stabilised in the most recent data available. Rates of opioid-related hospitalisations and emergency department presentations have remained relatively stable between 2013-14 and 2018-19.

There was a small decline in the total opioids dispensed in NSW under the Pharmaceutical Benefits Scheme (PBS) between 2014 and 2018, as measured by oral morphine equivalent dose.

The highest rates of opioid-related harm were seen in: males, people aged 35-44 years, the most disadvantaged socioeconomic groups, and Aboriginal people. Harms seen in these groups were measured by emergency department presentations, hospitalisations, and deaths data.

The rescheduling of codeine to a prescription only medicine appears to have reduced both use and harms of codeine, as reflected in survey, emergency department, and call centre data.

Certain groups of people with high rates of use and harms may not be well reflected in overall statewide data. The limitations of the data sources used to inform this report are described further in the appendices.

This report focuses on data up until 31 December 2019. The major impacts that the COVID-19 pandemic has had on our society may have since influenced opioid-related use and harms in NSW.

Opioid use in NSW1. Between 2014 and 2018 there was a reduction in opioids dispensed in NSW from 967 to 831 oral

morphine equivalent doses (OME) per 1,000 population per day. Note that this analysis excludes opioids dispensed for opioid dependency.

2. There was a decrease in the amount of fentanyl dispensed in NSW between 2014 and 2018.

3. There was a notable increase in the amount of tapentadol dispensed in NSW between 2014 and 2018, since it was listed on the PBS in 2014.

4. Remote areas appeared to have higher rates of opioids dispensed under the PBS (as measured by oral morphine equivalent dose) than metropolitan areas.

5. In Australia, there was a reduction in the proportion of people who reported using ‘pain-killers/pain relievers and opioids’ between 2016 and 2019 from 3.6% to 2.7%.

6. The rescheduling of codeine in 2018 to a prescription only medicine appeared to influence several indicators. Most noticeably, codeine combination analgesic calls to the Poisons Information Centre from NSW callers dropped from 1,221 (2017) to 663 (2019).

7. Wastewater analyses indicated that rates of pharmaceutical opioid use (licit or illicit) were higher in regional NSW.

8. Among people who inject drugs, heroin remained the drug reported as most frequently injected between 2004 and 2019.

9. Overall, the median purity of seized heroin appeared to increase from 2013 to 2019. In 2019 the median purity of seized heroin was 76%. The increase may have been influenced by legislative changes in 2017, resulting in a greater proportion of heroin tested being of a larger quantity, which may have higher purity than smaller seizures of the drug.


Opioid-related harms in NSW1. Rates of opioid-related hospitalisations remained stable in NSW between 2013-14 and 2018-19.

The rate of opioid-related hospitalisations in NSW in 2018-19 was 169 per 100,000 population.

2. The highest rates of opioid-related hospitalisations were in: males, Aboriginal people, people aged 35-44 years, and people in the most disadvantaged socioeconomic group. Rates of opioid-related hospitalisations were six times higher for Aboriginal people than non-Aboriginal people in NSW in 2018-19.

3. Heroin-related presentations to emergency departments remained stable at a rate of 1 per 1,000 presentations between 2011-12 and 2018-19.

4. The highest rates of heroin-related emergency department presentations were in males and people aged 35-44 years.

5. Rates of heroin-related emergency department presentations were higher at metropolitan than regional hospitals, while rates of fentanyl-related emergency department presentations were higher at regional hospitals than metropolitan hospitals.

6. There was a steady increase in the rate of opioid-related deaths in NSW between 2004 (2.8 per 100,000 population) and 2015 (5.8 per 100,000 population), which then stabilised through to 2018 (5.4 per 100,000 population).

7. Among deaths in NSW where opioids were detected in toxicological analysis, morphine and drugs that can be metabolised into morphine (heroin and codeine) were the most common opioids detected between 2010 and 2019.

8. Among the deaths in NSW in 2019 where opioids were detected in toxicological analysis, over 60% also had a benzodiazepine detected.


1. Opioid use

1.1 Prescription opioids dispensed under the Pharmaceutical Benefits Scheme

Figure 1: Total age- and sex-adjusted oral morphine equivalent dose (OME) dispensed, NSW, 2014 to 2018

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Source: Pharmaceutical Benefits Scheme Notes: Oral Morphine Equivalent (OME) is based on the idea that different doses of different opioids may give a similar analgesic effect. Where the doses of two different opioids are considered to give a comparable analgesic effect, they are deemed to be equianalgesic doses. (NDARC, 2014). More information is provided in the methods section (Appendix C).

There was a reduction in total opioids dispensed in NSW under the Pharmaceutical Benefits Scheme (PBS) between 2014 and 2018 from 927.8 to 829.7 oral morphine equivalent doses (OME) per 1,000 population per day (Figure 1).

Figure 2: Proportion of oral morphine equivalent dose (OME) dispensed, by age group, NSW, 2014 to 2018

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< 15 15 − 24 25 − 34 35 − 44 45 − 54 55 − 64 65 − 74 75 − 84 85+ Age group (years)

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%)

Male Female



Those aged 55-64 years were dispensed the most opioids in NSW under the PBS between 2014 and 2018, as measured by oral morphine equivalent dose (OME), accounting for 22.6% of the total opioids dispensed in NSW as OME (Figure 2). For each age group over 65 years, females were dispensed a greater proportion of opioids than males, potentially reflecting the larger number of females than males in those age groups in the general population.

Figure 3: Pattern of opioid prescriptions dispensed to different age groups, by proportion of total for each opioid, NSW, 2014 to 2018

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Bupre− norphine

Codeine Fentanyl Hydro− morphone

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Figure 4: Pattern of opioid prescriptions dispensed to different age groups, by proportion of total for each age group, NSW, 2014 to 2018


Figure 5: Proportion of age- and sex- adjusted oral morphine equivalent dose (OME) dispensed, by drug, NSW, 2014 to 2018

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Bupre− norphine

Codeine Fentanyl Hydro− morphone

Methadone Morphine OxycodoneTapentadol Tramadol

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ME

(%

)

2014 2015 2016

2017 2018

Source: Pharmaceutical Benefits Scheme Notes: Oral Morphine Equivalent (OME) is based on the idea that different doses of different opioids may give a similar analgesic effect. Where the doses of two different opioids are considered to give a comparable analgesic effect, they are deemed to be equianalgesic doses (NDARC, 2014). More information is provided in the methods section (Appendix C).

When the potency of each type of opioid is taken into account, oxycodone represented the largest proportion of opioids dispensed in NSW, accounting for nearly 40% of OME doses throughout the period from 2014 to 2018 (Figure 5). Between 2014 and 2018, there was a noticeable decrease in fentanyl OME dispensing (from 15% in 2014 to 10% in 2018, of all OME); and an increase in tapentadol OME dispensing, newly listed on the PBS in 2014 (from 1% in 2014 to 12% in 2018, of all OME). The potency of fentanyl is highlighted given the relatively low number of prescriptions dispensed (see Figure 4) in comparison to the large proportion of OME dispensed represented by fentanyl in NSW.


Figure 6: Age- and sex-adjusted OME dispensing per 1,000 persons per day, by socioeconomic status*, NSW, 2014 to 2018

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* According to the Socio-Economic Indexes for Areas (SEIFA) developed by the Australian Bureau of Statistics.

Between 2014 and 2018, the two lowest socioeconomic groups showed higher OME dispensing per 1,000 people per day compared with the highest socioeconomic group, in NSW (Figure 6). Data suggest that there was a small decrease in OME dispensing per 1,000 persons per day within the two lowest socioeconomic groups between 2014 and 2018.

Figure 7: Age-adjusted OME dispensing per 1,000 persons per day, by remoteness, NSW, 2014 to 2018

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Major Cities Inner Regional Outer Regional Remote Very Remote

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Remote, outer regional and inner regional areas had the highest rates of OME dispensing per 1,000 persons per day over the period from 2014 to 2018 (Figure 7). Data for major cities, inner regional and outer regional areas appeared to show decreases in OME per 1,000 persons per day between 2015 and 2018, although remote and very remote areas have fluctuated during this same period.


Figure 8: Age-and sex- adjusted OME dispensing per 1,000 persons per day by Local Health District, NSW, 2014 to 2018

2014 2015 2016 2017 2018

Northern Sydney

Sydney

South Eastern Sydney

Western Sydney

South Western Sydney

Nepean Blue Mountains

Hunter New England

Northern NSW

Central Coast

Illawarra Shoalhaven

Southern NSW

Western NSW

Murrumbidgee

Mid North Coast

Far West

0 400 800 1200 1600 2000OME/1,000 persons/day


Over the period 2014 to 2018, most metropolitan Local Health Districts (LHDs) in NSW had lower rates of opioids dispensed compared with regional LHDs in terms of OME per 1,000 population per day (Figure 8). Many LHDs appeared to show decreases in OME dispensing under the PBS over this period.


1.2 Opioid use at the population level

Table 1: Self-reported recent use of painkillers/pain relievers and opioids for non-medical use among people aged 14 years or older, age-standardised proportion (%), by remoteness and socioeconomic status, Australia, 2016 and 2019

2016 2019 Change

TOTAL 3.6 2.7# Decrease

By area

Major cities 3.3 2.6# Decrease

Inner regional 3.6 2.5# Decrease

Outer regional 4.2 3.5

Remote / Very remote *6.6 *4.1

By socioeconomic status

1st (most disadvantaged) 4.8 3.0# Decrease

2nd 4 3.0# Decrease

3rd 3.6 2.8

4th 2.8 2.8

5th (least disadvantaged) 2.6 1.8# Decrease

Source: National Drug Strategy Household Survey 2019, Australian Institute of Health and Welfare Notes: Excludes over-the-counter medications such as paracetamol and aspirin.# Statistically significant decrease* Estimate has a relative standard error of 25% to 50% and should be used with caution.

In Australia, there was a reduction in the proportion of people using ‘pain-killers/pain relievers and opioids for non-medical use’ between 2016 and 2019 (Table 1). Driving this change was the proportion of people using codeine for non-medical purposes falling from 3.0% to 1.5% during the same period. This aligns with the rescheduling of codeine in 2018 making it a prescription only medication. Statistically significant decreases were seen across most strata by area and by socioeconomic status.


Figure 9: Estimated oxycodone consumption, in mass consumed per day (left axis) and doses per day (right axis) per 1,000 people, Australia, December 2019

Capital Regional All Site Average Capital Average Regional Average

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ated C

onsum

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oses/10

00

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imat

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ACT NTNSW QLD SA TAS VIC WA

Source: National Wastewater Drug Monitoring Program – 10th Report, June 2020, Australian Criminal Intelligence Commission Note: The number of collection days varied from 5 to 7. The x-axis shows the unique numbers which are allocated to each wastewater treatment plant (WWTP) to maintain confidentiality; names/locations of wastewater treatment plants are not disclosed publicly. The upper limit of each WWTP box represents the maximum day’s consumption over the collection period; the lower limit represents the minimum day’s consumption over the collection period, and the middle line represents the average (mean) over the collection period. Uncertainties in population estimates may be particularly evident in smaller regional communities or sites with short term population fluctuations. Further detail on the population estimates used is available in the National Wastewater Drug Monitoring Program report, from the Australian Criminal Intelligence Commission (ACIC, 2020).

According to wastewater analysis, oxycodone use in NSW in December 2019 was higher in regional areas than capital cities, which is consistent with national averages (Figure 9).


Figure 10: Estimated fentanyl consumption, in mass consumed per day (left axis) and doses per day (right axis) per 1,000 people, Australia, December 2019


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According to wastewater analysis, fentanyl use in NSW in December 2019 was similar to national averages for capital city sites, and above average for some NSW regional areas (Figure 10). One site in NSW showed particularly high detections of fentanyl; it is worth noting that high levels of other drugs such as methamphetamine were also detected at this site.


Figure 11: Estimated heroin consumption, in mass consumed per day (left axis) and doses per day (right axis) per 1,000 people, Australia, December 2019


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Wastewater analysis showed that heroin use in NSW in December 2019 was below national averages for the capital city site. Regional sites in NSW were either above or below the national regional average depending on the site (Figure 11).

At the national level, wastewater analyses showed that use of some pharmaceutical opioids (oxycodone and fentanyl) were higher in rural areas; whereas heroin use was higher on average in capital city sites (Figure 9-11).

As with most data sources, wastewater analysis should be viewed in the context of other information.


1.3 Opioid use in selected populations in NSWFigure 12: Self-report of drug reported as injected most often in the past month among people who inject drugs, NSW, 2003 to 2019

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%)

Heroin Methamphetamine

Source: Illicit Drug Reporting System NSW 2019, National Drug and Alcohol Research Centre

From 2003 to 2019 in NSW among people who inject drugs, heroin remained the drug reported as being injected most often in the past month (IDRS NSW, 2019), despite the increased use of methamphetamine as the drug injected most often in this group over this period (Figure 12).

Among people surveyed at Needle and Syringe Program services, the most frequently reported last drug injected in 2018 was methamphetamine (35%); heroin was the second most reported (30%) (ANSPS, 2014-18).

Figure 13: Self-reported recent use of opioids among persons entering NSW correctional centres, NSW, April 2017 to December 2019

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Apr−Jun 2017

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Oct−Dec 2019

Rep

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Heroin Pharmaceutical opioids (non−prescribed)

Source: Justice Health and Forensic Mental Health Network, NSW Health

Among people entering prison in NSW in 2019, around 9 per 100 entrants reported using heroin in the four weeks preceding incarceration; and 4 per 100 entrants reported recent use of non-prescribed pharmaceutical opioids (Figure 13). These rates appear to have remained relatively stable since 2017.


For a range of reasons, the clinical information provided by people on entry to or during custody may not always be accurate. For example, drug or alcohol use may be exaggerated, underestimated or denied.

1.4 Heroin purity

Figure 14: Median purity of heroin seized by NSW Police, by form, NSW, 2010 to 2019

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40

60

80

100

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Med

ian

Pur

ity

(%)

Compressed Powder All

Source: NSW Health Pathology Forensic & Analytical Science Service Notes: The shaded region represents the interquartile range (or middle 50% of values) and provides some indication of the variability in the estimated median purity of heroin across seizures. Changes to the Drug Misuse and Trafficking Regulation in 2017 for seized substances requiring testing may affect trend analyses.

Heroin seizures by NSW Police that were tested for purity showed an increase in the median purity across all forms from 26% in 2010 to 76% in 2019 (Figure 14).

Table 2: Number of heroin samples seized by NSW Police, by form, NSW, 2010 to 2019

Form 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Compressed 33 94 124 82 70 57 87 97 61 30 69

Powder 45 79 90 70 48 67 82 79 54 26 47

Unspecified 20 29 29 36 12 21 33 27 16 9 38

Other 0 3 7 4 0 1 0 1 0 0 0

Total 98 205 250 192 130 146 202 204 131 65 154

Source: NSW Health Pathology Forensic & Analytical Science Service


Figure 15: Median heroin purity of each compressed heroin seizure tested, NSW, 2010 to 2019

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60

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100

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Med

ian

pur

ity

of

com

pre

ssed

her

oin

(%

)

Source: NSW Health Pathology Forensic & Analytical Science Service Note: The scatter plot shows the median purity of each sample that was tested. Vertical lines represent 1 January of each year.

Further analysis indicated that there are possibly two dominant circulating groups of heroin of different purity throughout this time period; one at approximately 20% and another at approximately 70% (Figure 15). From 2015 to 2019 the higher purity group dominated the heroin tested for purity. However, this may be an artefact due to changes in legislation, shifting focus to larger drug seizures, which may be more likely to have higher purities than smaller street-level seizures.


2. Health harms from opioid use

2.1 Suspected opioid-related ambulance callouts

Figure 16: Average naloxone administrations per day by NSW Ambulance, 2013 to 2019

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2013 2014 2015 201 62 017 2018 2019

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Source: NSW Ambulance Note: Cases included where naloxone administration (Pharmacology: ‘215’) was in either the electronic Medical Record (eMR) or Patient Health Care Record (PHCR)

The average number of ambulance callouts where naloxone was administered stayed relatively stable between 2013 and 2019 (6.13 to 7.12 administrations per day respectively) (Figure 16).


2.2 Opioid-related emergency department presentations

Figure 17: Heroin-related emergency department presentations per 1,000 presentations, NSW, 2011-12 to 2018-19

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2011−12 2012−13 2013−14 2014−15 2015−16 2016−17 2017−18 2018−19

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Source: NSW Public Health Rapid, Emergency, Disease and Syndromic Surveillance system (PHREDSS)

Heroin-related presentations to NSW emergency departments have remained stable between 2011-12 and 2018-19 (Figure 17).

Drug-related emergency department presentation data from the NSW Public Health Rapid, Emergency, Disease and Syndromic Surveillance system (PHREDSS) is likely to be an undercount. Therefore, the emergency department data presented in this report should be used to analyse trends over time or signals in the data, rather than as a measure of burden for drug-related harm.

Figure 18: Heroin-related emergency department presentations per 1,000 presentations, by age group, NSW, 2011-12 to 2018-19

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2011−12 2012−13 2013−14 2014−15 2015−16 2016−17 2017−18 2018−19

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16−24 years 25−34 years 35−44 years 45−54 years 55+ years


The highest rates of heroin-related emergency department presentations in NSW over the period 2012-13 to 2018-19 were in those aged 35-44 years (Figure 18). The decrease in the number of presentations in those aged 25-34 years over this period corresponds with an increase for those aged 35-44 years and 45-54 years, and likely demonstrates the same cohort aging and entering the older age groups.


Figure 19: Heroin-related emergency department presentations per 1,000 presentations, by sex, NSW, 2011-12 to 2018-19

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2011−12 2012−13 2013−14 2014−15 2015−16 2016−17 2017−18 2018−19

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Female Male


In NSW, males had more than double the rate of heroin-related emergency department presentations in 2018-19 compared with females (Figure 19). These rates have remained largely consistent over the period from 2011-12 to 2018-19.


Figure 20: Heroin-related emergency department presentations per 1,000 presentations, by triage category, NSW, 2011-12 to 2018-19

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2011−12 2012−13 2013−14 2014−15 2015−16 2016−17 2017−18 2018−19

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1 − Treat immediately 2 − Treat within 10mins

3 − Treat within 30mins 4 − Treat within 1hr

5 − Treat within 2hrs

Source: NSW Public Health Rapid, Emergency, Disease and Syndromic Surveillance system (PHREDSS)Notes: Triage category 1 - treatment immediately or within two minutes (immediately life-threatening condition) Triage category 2 - treatment within 10 minutes (imminently life-threatening condition) Triage category 3 - treatment within 30 minutes (potentially life-threatening condition) Triage category 4 - treatment within one hour (potentially serious condition) Triage category 5 - treatment within two hours (less urgent condition)

Between 2016-17 and 2018-19, there was a sharp increase in the rate of heroin-related emergency department presentations triaged into the most urgent group (treatment immediately or within two minutes) (Figure 20). Further analysis showed that this was driven by increases in urgent heroin-related emergency department presentations in Sydney metropolitan areas in particular.


Figure 21: Selected pharmaceutical opioid-related emergency department presentations per 1,000 presentations, NSW, 2011-12 to 2018-19

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Codeine Fentanyl Oxycodone


There was a small decrease in codeine-related emergency department presentations from 2016-17 to 2018-19 (Figure 21).

Of note, the selection criteria for pharmaceutical opioid-related emergency department presentations was different from heroin-related emergency department presentations. Therefore, it is difficult to make direct comparisons between heroin- and pharmaceutical opioid-related emergency department presentations. Furthermore, not all types of pharmaceutical opioids were readily identified in the emergency department data analysis.

Figure 22: Fentanyl-related emergency department presentations per 1,000 presentations, by remoteness of hospital, NSW, 2011-12 to 2018-19

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Metropolitan Sydney Rural and regional NSW


Over the period 2011-12 to 2018-19 in NSW, fentanyl-related emergency department presentations were higher in rural and regional areas compared with metropolitan Sydney (Figure 22).


Figure 23: Heroin-related emergency department presentations per 1,000 presentations, by remoteness of hospital NSW 2011-12 to 2018-19

Metropolitan Sydney Rural and regional NSW

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2011−12 2012−13 2013−14 2014−15 2015−16 2016−17 2017−18 2018−19

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In contrast to fentanyl, heroin-related emergency department presentations were higher in metropolitan Sydney hospitals compared with rural and regional hospitals in NSW across the period from 2011-12 to 2018-19 (Figure 23).

2.3 Opioid-related hospitalisationsFigure 24: Rate of opioid-related hospitalisations per 100,000 population, by public and private hospitals, NSW, 2010-11 to 2018-19

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2010−11 2011−12 2012−13 2013−14 2014−15 2015−16 2016−17 2017−18 2018−19

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Private Public All

Source: NSW Combined Admitted Patient Epidemiology Data (CAPED), and Australian Bureau of Statistics (ABS) population estimates, Secure Analytics for Population Health Research and Intelligence (SAPHaRI); Centre for Epidemiology and Evidence, NSW Ministry of Health

The rate of opioid-related hospitalisations in NSW in 2018-19 was 169 per 100,000 population (Figure 24). Though there appeared to be a slight increase between 2010-11 and 2013-14, this rate remained stable over the period from 2013-14 to 2018-19.

In NSW across the period from 2010-11 to 2018-19, opioid-related hospitalisations were more frequently coded as ‘mental health and behavioural disorders’ than ‘injury, poisoning and certain other consequences of external causes’. These are the two main categories within the International Classification of Diseases to identify opioid-related presentations.


Figure 25: Rate of opioid-related hospitalisations per 100,000 population to all hospitals, by sex, NSW, 2010-11 to 2018-19

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2010−11 2011−12 2012−13 2013−14 2014−15 2015−16 2016−17 2017−18 2018−19

Rat

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Male Female

Source: NSW Combined Admitted Patient Epidemiology Data (CAPED), and Australian Bureau of Statistics (ABS) population estimates, Secure Analytics for Population Health Research and Intelligence (SAPHaRI); Centre for Epidemiology and Evidence, NSW Ministry of Health Notes: The shaded area represents the 95% confidence interval for each data point.

The rate of opioid-related hospitalisations in NSW was higher for males than females across the period from 2010-11 to 2018-19. In 2018-19, males had an opioid-related hospitalisation rate of 201 per 100,000 population compared with 138 per 100,000 population in females (Figure 25).

Figure 26: Rate of opioid-related hospitalisations per 100,000 population to all hospitals, by remoteness, NSW, 2010-11 to 2018-19

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2010−11 2011−12 2012−13 2013−14 2014−15 2015−16 2016−17 2017−18 2018−19

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ulat

ion

Major cities Inner regional Outer regional/remote

Source: NSW Combined Admitted Patient Epidemiology Data (CAPED), and Australian Bureau of Statistics (ABS) population estimates, Secure Analytics for Population Health Research and Intelligence (SAPHaRI); Centre for Epidemiology and Evidence, NSW Ministry of Health Notes: The shaded area represents the 95% confidence interval for each data point. Outer regional/remote refers to the ARIA designations of: ‘outer regional’, ‘remote’ and ‘very remote.’


In NSW in 2018-19, opioid-related hospitalisations were slightly lower in outer regional/remote areas (138 per 100,000 population) compared with major cities and inner regional areas (both with 168 opioid-related hospitalisations per 100,000 population) (Figure 26).

All areas have seen slight increases in opioid-related hospitalisations compared with estimates from 2010-11: major cities (134 per 100,000 population); inner regional (113 per 100,000 population); and outer regional/remote (103 per 100,000 population).

Figure 27: Rate of opioid-related hospitalisations per 100,000 population to all hospitals, by Aboriginality, NSW, 2010-11 to 2018-19

0

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2010−11 2011−12 2012−13 2013−14 2014−15 2015−16 2016−17 2017−18 2018−19

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Aboriginal Non−Aboriginal

Source: NSW Combined Admitted Patient Epidemiology Data (CAPED), and Australian Bureau of Statistics (ABS) population estimates, Secure Analytics for Population Health Research and Intelligence (SAPHaRI); Centre for Epidemiology and Evidence, NSW Ministry of Health Notes: The shaded area represents the 95% confidence interval for each data point. Based on data from the NSW Admitted Patient Data and Admitted Patient, Emergency Department Attendance and Deaths Register dataset (Centre for Epidemiology and Evidence, NSW Ministry of Health), from 2010-11 to 2018-19, the estimated percentage of NSW admitted patient records correctly reported for Aboriginal people rose from 72.5% to 84.5%. Similar improvements in reporting of Aboriginal people are expected for the hospitalisation data used for this report (NSW Combined Admitted Patient Epidemiology Data (CAPED), Centre for Epidemiology and Evidence, NSW Ministry of Health). Most incorrect reporting in the hospitalisations data is due to Aboriginal people incorrectly being reported as non-Aboriginal. There are also a relatively small percentage of records with missing information on Aboriginal status. For information on the method of calculating the level of reporting of Aboriginal people hospitalised, see http://www.healthstats.nsw.gov.au/Indicator/dqi_era_apd. Similar improvements in reporting of Aboriginal status over time have been reported at a national (census) level, see https://www.abs.gov.au/ausstats/[email protected]/Lookup/2077.0main+features52006-2011

In NSW, rates of opioid-related hospitalisations were far higher in Aboriginal people than non-Aboriginal people, and this disparity increased over the period from 2010-11 to 2018-19 (Figure 27). In 2018-19, the rate of opioid-related hospitalisations was 832 per 100,000 population among Aboriginal people compared with 149 per 100,000 population for non-Aboriginal people. The count of opioid-related hospitalisations for Aboriginal and non-Aboriginal people from 2010-11 to 2018-19 are shown in Table 3.


Table 3: Counts of opioid-related hospitalisations to all hospitals, by Aboriginality, NSW, 2010-11 to 2018-19

Year Aboriginal Non-Aboriginal

2010-11 729 6,467

2011-12 783 6,814

2012-13 900 7,494

2013-14 1,021 8,364

2014-15 1,069 8,881

2015-16 1,212 8,984

2016-17 1,347 9,311

2017-18 1,419 9,791

2018-19 1,427 9,275

TOTAL 9,907 75,381

Source: NSW Combined Admitted Patient Epidemiology Data (CAPED), and Australian Bureau of Statistics (ABS) population estimates, Secure Analytics for Population Health Research and Intelligence (SAPHaRI); Centre for Epidemiology and Evidence, NSW Ministry of Health Notes: Based on data from the NSW Admitted Patient Data and Admitted Patient, Emergency Department Attendance and Deaths Register dataset (Centre for Epidemiology and Evidence, NSW Ministry of Health), from 2010-11 to 2018-19, the estimated percentage of NSW admitted patient records correctly reported for Aboriginal people rose from 72.5% to 84.5%. Similar improvements in reporting of Aboriginal people are expected for the hospitalisation data used for this report (NSW Combined Admitted Patient Epidemiology Data (CAPED), Centre for Epidemiology and Evidence, NSW Ministry of Health). Most incorrect reporting in the hospitalisations data is due to Aboriginal people incorrectly being reported as non-Aboriginal. There are also a relatively small percentage of records with missing information on Aboriginal status. For information on the method of calculating the level of reporting of Aboriginal people hospitalised, see http://www.healthstats.nsw.gov.au/Indicator/dqi_era_apd. Similar improvements in reporting of Aboriginal status over time have been reported at a national (census) level, see https://www.abs.gov.au/ausstats/[email protected]/Lookup/2077.0main+features52006-2011


Figure 28: Number of opioid-related hospitalisations per 100,000 population to all hospitals, where people were reported as Aboriginal, NSW, 2010-11 to 2018-19

2010−11 2011−12 2012−13

2013−14 2014−15 2015−16

2016−17 2017−18 2018−19

0

200

400

600

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1000

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Num

ber

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ions

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re

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s A

bo

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inal

Source: NSW Combined Admitted Patient Epidemiology Data (CAPED), and Australian Bureau of Statistics (ABS) population estimates, Secure Analytics for Population Health Research and Intelligence (SAPHaRI); Centre for Epidemiology and Evidence, NSW Ministry of Health Notes: Based on data from the NSW Admitted Patient Data and Admitted Patient, Emergency Department Attendance and Deaths Register dataset (Centre for Epidemiology and Evidence, NSW Ministry of Health), from 2010-11 to 2018-19, the estimated percentage of NSW admitted patient records correctly reported for Aboriginal people rose from 72.5% to 84.5%. Similar improvements in reporting of Aboriginal people are expected for the hospitalisation data used for this report (NSW Combined Admitted Patient Epidemiology Data (CAPED), Centre for Epidemiology and Evidence, NSW Ministry of Health). Most incorrect reporting in the hospitalisations data is due to Aboriginal people incorrectly being reported as non-Aboriginal. There are also a relatively small percentage of records with missing information on Aboriginal status. For information on the method of calculating the level of reporting of Aboriginal people hospitalised, see http://www.healthstats.nsw.gov.au/Indicator/dqi_era_apd. Similar improvements in reporting of Aboriginal status over time have been reported at a national (census) level, see https://www.abs.gov.au/ausstats/[email protected]/Lookup/2077.0main+features52006-2011

The number of opioid-related hospitalisations where people were reported as Aboriginal was highest in major cities compared with inner regional, and outer regional and remote areas. In 2019 there were 825 opioid-related hospitalisations in major cities, 375 in inner regional areas, and 156 in outer regional and remote areas, where people were reported as Aboriginal (Figure 28).

In contrast, as a percentage of opioid-related hospitalisations where Aboriginality was reported, outer-regional and remote areas had the highest percentage of hospitalisations where people were reported as Aboriginal. In 2019, 10% of opioid-related hospitalisations in major cities, 20% in inner regional areas, and 32% in outer regional and remote areas were hospitalisations where people were reported as Aboriginal (Figure 29).


Figure 29: Percentage of opioid-related hospitalisations per 100,000 population to all hospitals, where people were reported as Aboriginal, NSW, 2010-11 to 2018-19

2010−11 2011−12 2012−13

2013−14 2014−15 2015−16

2016−17 2017−18 2018−19

0

10

20

30

40

50

60

Major Cities Inner Regional Outer Regional and Remote

Per

cent

age

of

hosp

ital

isat

ions

whe

re

peo

ple

iden

tife

d a

s A

bo

rig

inal

(%

)

Source: NSW Combined Admitted Patient Epidemiology Data (CAPED), and Australian Bureau of Statistics (ABS) population estimates, Secure Analytics for Population Health Research and Intelligence (SAPHaRI); Centre for Epidemiology and Evidence, NSW Ministry of Health Notes: Based on data from the NSW Admitted Patient Data and Admitted Patient, Emergency Department Attendance and Deaths Register dataset (Centre for Epidemiology and Evidence, NSW Ministry of Health), from 2010-11 to 2018-19, the estimated percentage of NSW admitted patient records correctly reported for Aboriginal people rose from 72.5% to 84.5%. Similar improvements in reporting of Aboriginal people are expected for the hospitalisation data used for this report (NSW Combined Admitted Patient Epidemiology Data (CAPED), Centre for Epidemiology and Evidence, NSW Ministry of Health). Most incorrect reporting in the hospitalisations data is due to Aboriginal people incorrectly being reported as non-Aboriginal. There are also a relatively small percentage of records with missing information on Aboriginal status. For information on the method of calculating the level of reporting of Aboriginal people hospitalised, see http://www.healthstats.nsw.gov.au/Indicator/dqi_era_apd. Similar improvements in reporting of Aboriginal status over time have been reported at a national (census) level, see https://www.abs.gov.au/ausstats/[email protected]/Lookup/2077.0main+features52006-2011. This analysis excludes records where Aboriginal status was missing or unstated.


Figure 30: Rate of opioid-related hospitalisations per 100,000 population to all hospitals, by socioeconomic status*, NSW, 2010-11 to 2018-19

0

50

100

150

200

250

2010−11 2011−12 2012−13 2013−14 2014−15 2015−16 2016−17 2017−18 2018−19

Rat

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,00

0 p

op

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ion

1 Least disadvantaged Quintile 2 Quintile 3

Quintile 4 5 Most disadvantaged

Source: NSW Combined Admitted Patient Epidemiology Data (CAPED), and Australian Bureau of Statistics (ABS) population estimates, Secure Analytics for Population Health Research and Intelligence (SAPHaRI); Centre for Epidemiology and Evidence, NSW Ministry of Health Notes: The shaded area represents the 95% confidence interval for each data point. The most recent population estimates by socioeconomic status available on SAPHaRI are for 2016. In this analysis, the 2016 population estimates by socioeconomic status have been carried forward to provide the denominators for rate calculations in 2017-18 and 2018-19. The effect is that rate estimates in this analysis for 2017-18 and 2018-19 may be slightly higher than expected given trends in population growth in NSW.

* According to the Socio-Economic Indexes for Areas (SEIFA) developed by the Australian Bureau of Statistics.

Over the period 2010-11 to 2018-19 in NSW, socioeconomic status was clearly reflected in the rate of opioid-related hospitalisations, with the most socioeconomically disadvantaged group having the highest rate of hospitalisations (225 per 100,000 population in 2018-19) compared with the least disadvantaged group (140 per 100,000 population in 2018-19) (Figure 30).


Figure 31: Rate of opioid-related hospitalisations per 100,000 population to all hospitals, by age group, NSW, 2010-11 to 2018-19

0

100

200

300

400

500

2010−11 2011−12 2012−13 2013−14 2014−15 2015−16 2016−17 2017−18 2018−19

Rat

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er 1

00

,00

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op

ulat

ion

16 − 24 25 − 34 35 − 44

45 − 54 55 − 64 65+

Source: NSW Combined Admitted Patient Epidemiology Data (CAPED), and Australian Bureau of Statistics (ABS) population estimates, Secure Analytics for Population Health Research and Intelligence (SAPHaRI); Centre for Epidemiology and Evidence, NSW Ministry of Health Notes: The shaded area represents the 95% confidence interval for each data point.

Similar to opioid-related ED presentations, those aged 35-44 years had the highest rate of opioid-related hospitalisations in 2018-19 at 290 per 100,000 population (Figure 31). Increases were seen across the period from 2010-11 to 2018-19 in all groups aged 35 years and older, with a decrease in those aged 25-34 years.


2.4 Treatment episodes for opioid use

Figure 32: Number of closed treatment episodes by NSW Health-funded drug and alcohol services for opioids as principal drug of concern, NSW, 2012-13 to 2018-19

0

1

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4

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6

2012−13 2013−14 2014−15 2015−16 2016−17 2017−18 2018−19

Num

ber

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lose

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rvic

e ep

isod

es (

’00

0)

Government non−OTP Government OTP Non−government services (non−OTP)

Source: NSW Alcohol and Other Drugs Treatment Service Minimum Data Set, Centre Alcohol and Other Drugs, NSW Ministry of Health Note: Administrative closed service episodes and Commonwealth funded agencies excluded. The OTP data included in this figure does not include data from Justice Health or private clinics.

Treatment services provided by NSW Health-funded drug and alcohol services include services from the NSW Opioid Treatment Program (OTP) as well as other service types (as listed in Table 4). In 2018-19, there were: 5,078 non-OTP treatment episodes provided by government services, 3,751 OTP treatment episodes provided by government services, and 1,147 non-OTP treatment episodes provided by non-government services (Figure 32).

Table 4: Number of closed non-OTP treatment episodes by NSW Health-funded drug and alcohol services for opioids as principal drug of concern, NSW, 2018-19

Main service provided Counts %

Consultation activities 1,716 28%

Counselling 1,243 20%

Assessment Only 1,123 18%

Withdrawal Management (detox) 846 14%

Support and case management only 792 13%

Rehabilitation activities 478 8%

Information and education only 16


2.5 Opioid-related deaths

Figure 33: Opioid deaths as underlying or associated cause of death, and as underlying cause of death only, by number of deaths and rate of deaths per 100,000 population, NSW, 1999 to 2018

Num

ber o

f deaths

199

9

200

0

200

1

200

2

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3

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2010

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Underlying and related cause

Underlying cause only

Rate per 10

0,00

0 population

Source: Mortality estimates for years up to 2005 are based on Australian Bureau of Statistics death registration data. Data from 2006 onwards were provided by the Australian Coordinating Registry, Cause of Death Unit Record File; the data for the two most recent years are preliminary (SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health)

Opioid-related deaths increased in NSW between 2004 and 2018. Using data for both underlying and associated causes of death the number of deaths increased from 187 (2004) to 421 (2018), and for underlying cause of death only (opioid-induced deaths), the increase was from 164 (2004) to 332 (2018) (Figure 33).

Correspondingly, the population rate of opioid-related deaths in NSW for underlying and associated cause of death increased between 2004 and 2018 from 2.8 per 100,000 population (2004) to 5.4 per 100,000 population (2018). For underlying cause of death only (opioid-induced deaths), the rate increased from 2.5 per 100,000 population (2004) to 4.3 per 100,000 population (2018) (Figure 33).


Figure 34: Opioid deaths as underlying or associated cause of death per 100,000 population, by remoteness NSW, 2001 to 2018

Rat

e o

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s p

er

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op

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Major cities Rural and remote

0

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Source: Mortality estimates for years up to 2005 are based on Australian Bureau of Statistics death registration data. Data from 2006 onwards were provided by the Australian Coordinating Registry, Cause of Death Unit Record File; the data for the two most recent years are preliminary (SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health) Notes: The shaded area represents the 95% confidence interval for each data point. ‘Rural and remote’ refers to the ARIA designations of: ‘inner regional’, ‘outer regional’, ‘remote’ and ‘very remote.’ This analysis includes opioid-related deaths identified in both underlying and associated cause of death.

There was an increase in opioid-related deaths in both metropolitan and rural areas in NSW between 2001 and 2018 (Figure 34). In 2018, rates were slightly higher in rural and remote areas (6.4 per 100,000 population) compared with major cities (5.0 per 100,000 population).

Figure 35: Opioid deaths as underlying cause only, by type of underlying cause of death per 100,000 population NSW, 2007 to 2018

0

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2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Rat

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Accidental poisoning Intentional self−poisoning Undetermined intent

Source: Mortality estimates for years up to 2005 are based on Australian Bureau of Statistics death registration data. Data from 2006 onwards were provided by the Australian Coordinating Registry, Cause of Death Unit Record File; the data for the two most recent years are preliminary (SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health) Note: The shaded area represents the 95% confidence interval for each data point. This analysis includes opioid-related deaths identified in both underlying and associated cause of death.

In NSW, between 2007 and 2018 the majority of opioid-induced deaths were coded as an ‘accidental poisoning’ (Figure 35). In 2018, the highest rate of opioid-related deaths was for those coded as accidental


poisoning (3.6 per 100,000 population), compared with intentional self-poisoning (0.6 per 100,000 population), and undetermined intent (0.1 per 100,000 population).

Figure 36: Deaths where opioids were detected in forensic toxicology, by drug type, NSW, 2010 to 2019

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2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Num

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Dea

ths

Any opioid Buprenorphine Codeine

Fentanyl Heroin (6−MAM) Methadone

Morphine (chemical only) Morphine/heroin/codeine Oxycodone

Source: NSW Health Pathology Forensic & Analytical Science Service Notes: At the forensic toxicology laboratory within FASS, prior to 2012, the levels of detection for morphine and codeine were 0.02mg/L. The previous method did not include 6-monoacetylmorphine (6-MAM, a heroin specific metabolite). In September 2014, FASS also implemented the screening method in urine for 6-MAM and 6-acetylcodeine with LOD for both 0.002mg/L.

Among deaths in NSW where opioids were detected in toxicological analysis over the period from 2010 to 2019, morphine and drugs that can be metabolised into morphine (coded as morphine/heroin/codeine) were the most commonly detected group (Figure 36). In 2019, there were 829 deaths in total where an opioid was detected in forensic toxicology in NSW.

Note: Detection of a substance means that the substance was present at the time of death. It does not confirm that the substance detected was the underlying or associated cause of death. In many cases, a number of substances were detected at the time of death.

Determination of the cause of death in cases where forensic toxicology tests were performed is a matter for the coroner. Cause of death information is presented separately above (see Figure 33).


Figure 37: Deaths where opioids were detected in forensic toxicology, by drug combination, NSW, 2010 to 2019

Num

ber

of

Dea

ths

Any opioid Opioid + (buprenorphine or methadone)

Opioid + (paracetamol or NSAID) Opioid + amphetamineOpioid + antidepressant Opioid + benzodiazepine

0

200

400

600

800

1000

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Source: NSW Health Pathology Forensic & Analytical Science Service

Among deaths in NSW where opioids were detected in toxicological analysis from 2010 to 2019, many cases had detections of other drugs (Figure 37). For instance, among the 829 deaths where an opioid was detected in 2019, 497 (60%) also had a benzodiazepine detected; and 300 (36%) had an antidepressant detected.

Note that the above groupings are not mutually exclusive, and toxicological analysis for some cases may have identified three or more classes of drugs.

Figure 38: Deaths where opioids were detected in forensic toxicology, by remoteness, NSW, 2010 to 2019

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2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

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Major cities Rural and remote

Source: NSW Health Pathology Forensic & Analytical Science Service Notes: The shaded area represents the 95% confidence interval for each data point. Rural and remote’ refers to the ARIA designations of: ‘inner regional’, ‘outer regional’, ‘remote’ and ‘very remote.’

Among deaths in NSW where opioids were detected in toxicological analysis, the rate of deaths for major cities was similar to that in rural and remote areas in 2018 and 2019 (Figure 38). However, the data suggest that rural and remote areas had a slightly higher rate than major cities between 2013 and 2017.


2.6 Opioid-related calls to drug information services

Figure 39: Opioid-related phone calls to NSW Alcohol and Drug Information Service (ADIS) NSW, 2012 to 2019

0

100

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2012 2013 2014 2015 2016 2017 2018 2019

Num

ber

of

Cal

ls

Buprenorphine Codeine Fentanyl

Heroin Methadone Morphine

Other opioids Oxycodone

Source: Alcohol and Drug Information Service (ADIS), NSW Health. Includes calls to ADIS, Opioid Treatment Line, Stimulant Treatment Line, Cannabis Caution and the Drug & Alcohol Specialist Advisory Service Notes: Alcohol and Drug Information Service (ADIS) is a NSW state-wide telephone service providing education, information, referral, crisis counselling and support about illegal drugs such as heroin, ice and cannabis, as well as legal drugs such as alcohol. ADIS is available to all residents of NSW. The data shown in this figure is the number calls related to alcohol and/or methamphetamine. The data shown in this figure includes calls to Alcohol and Drug Information Service (ADIS) as well as the St Vincent’s Opioid Treatment Line, Stimulant Treatment Line, calls to ADIS directly related to the NSW Police Force Cannabis Cautioning Scheme, and health professional calls to the Drug and Alcohol Specialist Advisory Service.

Over the period 2012 to 2019, heroin remained the main opioid of concern among opioid-related phone calls to NSW Alcohol and Drug Information Service (Figure 39).


Figure 40: Total opioid- and codeine combination analgesic-related phone calls to the Poisons Information Centre from NSW callers, NSW, 2015 to 2019

0

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2000

2500

2015 2016 2017 2018 2019

Num

ber

of

calls

Codeine combination analgesics Total opioids

Source: NSW Poisons Information Centre Note: All age groups and exposure types were included. ‘Codeine combination analgesics’ include combinations with antihistamines, paracetamol, aspirin and ibuprofen. Calls are presented as unique episodes (i.e., call backs regarding the same patient are excluded)

Total opioid-related calls to the Poisons Information Centre from NSW callers decreased between 2017 (2,197 calls) and 2019 (1,718 calls) (Figure 40). This is likely to be the result of the rescheduling of over-the-counter codeine in 2018 to a prescription only (S4) substance, also effecting the codeine combination products. This is demonstrated by the decrease in codeine combination analgesic-related calls over this period from 1,221 (2017) to 663 (2019), noting that the total opioid-related calls include the codeine combination analgesic-related calls, which clearly drive this change.

Note that Figure 40 and Figure 41 include calls from exposures of various intent types. In 2019, the main intent types include: deliberate-self poisoning (43%); therapeutic error (29%); other intentional (10%); accidental (6%); adverse reaction (6%); and recreational (4%).


Figure 41: Phone calls to the Poisons Information Centre from NSW callers, by selected opioids, NSW, 2015 to 2019

Morphine Tapentadol

Fentanyl Heroin Methadone

Buprenorphine Buprenorphine + Naloxone Codeine

25

50

75

100

25

50

75

100

25

50

75

100

Num

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of

calls

Oxycodone Oxycodone + Naloxone Tramadol

2015 2016 2017 2018 2019 2015 2016 2017 2018 2019 2015 2016 2017 2018 2019

200

300

400

500

Source: NSW Poisons Information Centre Notes: All age groups and exposure types were included. Different formulations of drugs such as buprenorphine are included in the one substance group. ‘Codeine’ in the above figure refers to single ingredient products

Following the listing of tapentadol on the PBS in 2014, there was a marked increase in tapentadol-related calls to the Poisons Information Centre from NSW callers between 2015 and 2019 (Figure 41). There were also slight reductions in calls relating to fentanyl and single ingredient codeine products between 2015 and 2019.


3. Limitations of the dataThis report draws on multiple sources of data in order to support a comprehensive, balanced and up-to-date understanding of the evidence around opioid use and harms in NSW. Each source of data has a number of limitations. A brief overview of the limitations of the data used to inform this report is presented below.

Pharmaceutical Benefits Scheme (PBS) dataThe PBS analyses in this report do not contain Anatomical Therapeutic Classification code N07BC (“Drugs used in opioid dependence”), which includes prescriptions for methadone and buprenorphine for this purpose. This means that the prescriptions for these two opioids will be under numerated in this analysis. All methadone and buprenorphine measures in this report should be assumed to be for the treatment of pain. This same selection criterion has been used by the AIHW in their report Opioid harm in Australia and comparisons between Australia and Canada (AIHW, 2018).

The PBS dataset does not contain information on all prescriptions and pharmaceuticals dispensed in NSW. Examples of prescriptions and pharmaceuticals not included in the dataset are: privately dispensed prescriptions; over the counter medications, such as codeine prior to February 2018; and opioids dispensed during a hospital admission or at hospital discharge. Of note, NSW and the ACT are the only two jurisdictions where PBS data from public hospitals is not recorded (under the Public Hospital Pharmaceutical Reforms).

The specific condition(s) for which opioids are prescribed are not recorded in the PBS dataset.

Information about how the drug is intended to be administered (for example, how often the drug is taken and for how long) is not recorded. In addition, this analysis assumes that all medication dispensed is taken.

In this dataset, there is no record of co-administration of other drugs which may interact with opioids, for example, pregabalin or benzodiazepines.

Dispensed records are not available until the claim has been processed, meaning some claims can be delayed in appearing in the PBS dataset. Given the data was extracted more than six months after the end of the study period any effect of this delay is likely to be minimal.

Survey dataSurvey data usually provides the responses of individuals who voluntarily completed a survey. In most cases, a sample of the population was measured and then results weighted to make an estimation about the whole population. Sampling error can occur when the survey group does not accurately reflect the population. This can occur purely by chance or can be a result of the design of the study.

For example, certain populations that may be more difficult to interview, such as people living in regional areas, homeless people, and those in clinical and institutional settings, may be excluded from the survey. Certain groups of respondents may also choose not to participate or provide inaccurate or incomplete responses. For example, people may be unwilling to report their use of illicit drugs. In these cases, bias may be introduced into the results of the study. However, if similar survey methods are used over time and the coverage of the sampling frame does not decline, then trends in the results over time should be reliable.

Surveys that focus on specific population groups, such as people who inject drugs, may not be representative of the general population. However, because of their targeted nature, these surveys may provide an opportunity to obtain much more comprehensive information from the population group of interest.

When reported findings are based on self-reported data, estimates of illicit drug use and related behaviours are likely to be underestimates of actual use.


Routinely collected dataRoutinely collected data, or administrative data, contains information collected by services or organisations such as hospitals or police as part of their ongoing activities. While these data sources usually have good service or population coverage, they are often not designed for surveillance purposes. If a service does not ask for or record specific information, it is not possible to routinely report on that information using this source. There can also be a bias toward those people who access a service frequently or easily, or where services or organisations have prioritised certain activities. There may be a significant delay in the availability of data due to administrative processes.

Routinely collected data are useful for examining harms at the state level and trends over time, however, there may be challenges in identifying specific groups at higher risk. For example, detailed information is not routinely collected on gender identity or sexual preference in administrative hospital data, which means that information cannot be reported for lesbian, gay, bisexual, transgender, intersex and queer (LGBTIQ) communities.

For specific details of the data used in this report, please refer to the original sources, or for NSW Health data presented, please refer to Appendix C.


Appendix A: Data sources and descriptions

Data source Data description Data custodian

National Drug Strategy Household Survey

Survey conducted every two to three years since 1985. Household survey of non-institutionalised persons aged 14 years and over.

Australian Institute of Health and Welfare

Illicit Drug Reporting System

Annual interview of a sentinel group of people who regularly inject drugs, conducted in Australian capital cities.

National Drug and Alcohol Research Centre

NSW Health Pathology Forensic & Analytical Science Service

The NSW Health Pathology Forensic & Analytical Science Service is the provider of Forensic Medicine, Forensic Science and Analytical Science Services to the NSW Government. The Service currently provides analytical services to NSW Police Force, NSW Coronial Jurisdiction, NSW Road and Maritime Services, NSW Health, Local Government Bodies and private industry.

NSW Health Pathology

National Wastewater Drug Monitoring Program

Collection and analysis of wastewater samples across Australia to detect and measure the presence of 13 illicit and licit drugs, with reports published three times per year. In December 2019, 53 wastewater sites were monitored nationally, covering approximately 43% of the Australian population.

Australian Criminal Intelligence Commission

NSW Public Health Rapid, Emergency, Disease and Syndromic Surveillance system

The NSW Public Health Rapid, Emergency, Disease and Syndromic Surveillance (PHREDSS) system provides daily monitoring of most unplanned presentations to NSW public hospital emergency departments (EDs) and all emergency Triple Zero (000) calls to NSW Ambulance.

Centre for Epidemiology and Evidence, NSW Ministry of Health

NSW Admitted Patient Data Collection and Combined Admitted Patient Epidemiology Data

This collection records all admitted patient services provided by NSW Public Hospitals, Public Psychiatric Hospitals, Public Multi-Purpose Services, Private Hospitals, and Private Day Procedures Centres.


Alcohol and Other Drugs Treatment Services National Minimum Data Set

The Alcohol and Other Drugs Treatment Services National Minimum Data Set (AODTS NMDS) contains information about alcohol and other drug treatment services, the clients who use these services, the types of drug problems for which treatment was sought, and the types of treatment provided. There was under-reporting for the 2015-2016 financial year owing to changes in the Community Health and Outpatient Care program data collection system.

Australian Institute of Health and Welfare

Alcohol and Drug Information Service

Alcohol and Drug Information Service (ADIS) is a NSW statewide telephone service providing education, information, referral, crisis counselling and support about illegal drugs such as heroin, ice and cannabis, as well as legal drugs such as alcohol. ADIS is available to all residents of NSW.

The data from this service also includes the St Vincent’s Opioid Treatment Line, Stimulant Treatment Line, calls to ADIS directly related to the NSW Police Force Cannabis Cautioning Scheme, and health professional calls to the Drug and Alcohol Specialist Advisory Service.

St Vincent’s Hospital Network


Data source Data description Data custodian

Justice Health and Forensic Mental Health Network

Justice Health & Forensic Mental Health Network (JH&FMHN) triages all patients entering NSW Correctional Centres. The Reception Screening Assessment (RSA) was completed by a registered nurse or enrolled nurse on the Justice Health electronic Health System. Junee and Parklea Correctional Health are not included in this data extract.

Justice Health and Forensic Mental Health Network

NSW Poisons Information Centre

The NSW Poisons Information Centre (PIC) provides call centre data on exposure calls to the service.

The NSW PIC is a call centre staffed by pharmacists and scientists, who provide poisons information. The Centre also employs clinical toxicologists who provide specialist expertise in the medical management of human poisoning and envenoming.

NSW Poisons Information Centre

Cause of death unit record file (NSW)

The Cause of Death Unit Record File (COD URF) is provided by the Australian Coordinating Registry for COD URF on behalf of Australian Registries of Births, Deaths and Marriages, Australian Coroners and the National Coronial Information System.

The cause of death was compiled and coded by the Australian Bureau of Statistics (ABS) based on data from the data custodians that was correct at that point in time.



Appendix B: Reference listABS, 2015 – Australian Bureau of Statistics, 2015. General Social Survey: Summary Results, Australia, 2014. ABS cat. no. 4159.0. Canberra: ABS

ACIC, 2020 – Australian Criminal Intelligence Commission, 2020. National Wastewater Drug Monitoring Program – 10th Report. Prepared by the University of Queensland (Tscharke B, O’Brien J, Reeks T, Elisei G, Lin J, Grant S, Mueller J & Thomas K) and University of South Australia (Ghetia M, Bade R, Chen J, Nguyen L, Gerber C & White J). Australian Criminal Intelligence Commission. Available at: www.acic.gov.au/publications/reports/national-wastewater-drug-monitoring-program-tenth-report

AIHW, 2018 – Australian Institute of Health and Welfare, 2018. Opioid harm in Australia and comparisons between Australia and Canada. Cat. no. HSE 210. Canberra: AIHW.

AIHW, 2020 – Australian Institute of Health and Welfare, 2020. National Drug Strategy Household Survey 2019. Drug Statistics series no. 32. PHE 270. Canberra: AIHW.

ANSPS, 2014-18 – Heard S, Iversen J, Geddes L & Maher L, 2019. Australian Needle Syringe Program Survey National Data Report 2014-2018: Prevalence of HIV, HCV and injecting and sexual behaviour among NSP attendees. Sydney: Kirby Institute, UNSW Sydney. ISSN: 1448-5915.

Dean L, 2012. Codeine Therapy and CYP2D6 Genotype. [Updated 2017 Mar 16]. In: Pratt V, McLeod H, Rubinstein W, et al., editors. Medical Genetics Summaries [Internet]. Bethesda (MD): National Center for Biotechnology Information (US). Available from: www.ncbi.nlm.nih.gov/books/NBK100662/

HealthStats NSW, 2015 – Centre for Epidemiology and Evidence. HealthStats NSW Method Paper – Confidence Intervals. June 2015. Sydney: NSW Ministry of Health. Available at: www.healthstats.nsw.gov.au/Resources/Confidence_Intervals.pdf. Accessed 23 May 2019.

HealthStats NSW, 2019 – Centre for Epidemiology and Evidence. HealthStats NSW Method Paper – Reporting of hospitalisation-related indicators on HealthStats NSW Impact of changes to emergency department admissions. April 2019. Sydney: NSW Ministry of Health. Available at: www.healthstats.nsw.gov.au/Resources/ED-admissions.pdf. Accessed 24 May 2019.

IDRS NSW, 2019 – Swanton R, Gibbs D & Peacock A, 2019. New South Wales Drug Trends 2019: Key findings from the Illicit Drug Reporting System (IDRS) Interviews. Sydney, Australia: National Drug and Alcohol Research Centre, UNSW Sydney.

NDARC, 2014 – Nielsen S, Degenhardt L, Hoban B, & Gisev N, 2014. Comparing opioids: A guide to estimating oral morphine equivalents (OME) in research. Technical Report No. 329. Sydney, Australia: National Drug and Alcohol Research Centre, UNSW Sydney.

TGA, 2015 – Pharmacovigilance and Special Access Branch, Therapeutic Goods Administration. Safety Review – Codeine use in children and ultra-rapid metabolisers. Publication # R15/746324, October 2015. Available at: www.tga.gov.au/sites/default/files/codeine-use-children-and-ultra-rapid-metabolisers.pdf. Accessed 20 August 2020.

Vadivelu N & Hines RL, 2008. Management of chronic pain in the elderly: focus on transdermal buprenorphine. Clinical Interventions in Aging, 3(3):421-430. doi:10.2147/cia.s1880


Appendix C: Case selection for PBS and NSW Health data

Pharmaceutical Benefits SchemeSourcePharmaceutical Benefits Scheme. Data provided by the Technology Assessment and Access Division, Department of Health, Australian Government. Data analysed by Clinical Quality and Safety Branch, Centre for Alcohol and Other Drugs, NSW Ministry of Health. Data extracted 2 July 2019

AcknowledgementsFor their assistance in the analysis of PBS data we thank:

• Kevin Monahan from the Australian Institute of Health Welfare

• Chloe Burns from the Australian Department of Health

Case selection and analysis

• The data extract was for prescriptions with Anatomical Therapeutic Classification code N02A (“Opioids”) dispensed to NSW residents from 1 July 2013 to 31 March 2019, although only records between 1 January 2014 and 31 December 2018 are included in these analyses. Date was based on date of supply (when the prescription was dispensed).

• These include the following opioids drug groups (drugs are analysed by the active opioid ingredient) and their associated item codes:– Buprenorphine 08865N, 08866P, 8867Q, 10746N,

10755C, 10756D, 10770W, 10948F, 10949G, 10953L, 10957Q, 10959T, 10964C, 10970J

– Codeine (Includes codeine, codeine + paracetamol, and codeine + aspirin drug preparations) 04286N, 05063L, 01215Y, 03316M,

04275B, 08785J, 04170L, 04171M, 10186D

– Fentanyl 05401G, 05402H, 05403J, 05404K,

05405L, 05406M, 05407N, 05408P, 05409Q, 05410R, 05411T, 05412W, 05265D, 05277R, 05278T, 05279W, 05280X, 05437E, 05438F, 05439G, 05440H ,05441J, 08878G, 08891Y, 08892B, 08893C, 08894D, 10600X, 10601Y, 10602B, 10603C, 10604D, 10606F, 10607G, 10608H, 10610K, 10611L, 10612M, 10613N, 10684H, 10697B, 10698C, 10713W, 10722H, 10729Q, 10737D, 10738E, 10739F

– Hydromorphone 08420E, 08421F, 08422G, 08423H,

08424J, 11467M, 05115F, 05116G, 08541M, 08542N, 08543P, 09299K, 09406C, 09407D, 09408E, 09409F

– Methadone 01606M, 05399E, 05400F, 01609Q

– Morphine 02839K, 02840L, 02841M, 08349K,

08491X, 08492Y, 08493B, 08494C, 01607N, 01644M, 01645N, 01647Q, 05168B, 05170D, 10864T, 10869C, 10874H, 10878M, 02122Q, 02123R, 02124T, 05237P, 05238Q, 05239R, 08146R, 08305D, 08306E, 08454Y, 08490W, 01646P, 01653B, 01654C, 01655D, 01656E, 04349X, 05391R, 05393W, 05394X, 08035X, 08453X, 08489T, 08669G, 08670H, 02332R, 05392T, 05395Y, 05396B

– Oxycodone (includes oxycodone and oxycodone + naloxone preparations) 05191F, 05197M, 08464L, 08501K, 08502L,

05190E, 08644Y, 02481N, 02622B, 05195K, 08385H, 08386J, 08387K, 08388L, 09399Q, 09400R, 08000C, 08934F, 08935G, 08936H, 10757E, 10758F, 10776E, 11102H, 11111T, 08681X

– Tapentadol 10091D, 10092E, 10094G, 10096J,

10100N


– Tramadol 05232J, 08455B, 08611F, 05231H,

08582Q, 05150C, 08843K, 02527B, 08523N, 08524P, 08525Q

• Data were analysed:– As age and sex standardised rates of

prescriptions and people per 100 population by calendar year For all opioids, for select opioids (codeine

+ paracetamol, 50mg oxycodone tablets, fentanyl patches)

– As age and sex standardised oral morphine equivalent (OME) and defined daily dose (DDD) per 1,000 people per day For all opioids, for select opioids (codeine

+ paracetamol, 50mg oxycodone tablets, fentanyl patches)

By socioeconomic status, LHD, remoteness

• Inclusion criteria:– Date of supply between 1 January 2014 and

31 December 2018– Records with complete data recorded– Records with postcodes mappable to

remoteness, LHD and ABS postal areas within NSW

Notes

• PBS data include prescriptions that were priced under the PBS co-payment thresholds

• Prescriptions of buprenorphine and methadone under code N07BC (“Drugs used in opioid dependence”) were not included in this analysis, so rates of these opioids will be lower than the true population incidence.

• Geographic analysis is based on patient postcode proportionally assigned to: – NSW Local Health District (2010 boundaries)– Statistical area 2 (SA2), used for ABS SEIFA

mapping (2016 boundaries)– Australian Statistical Geography Standard

(ASGS) Remoteness Structures (2011 boundaries)

• Socioeconomic status was estimated using ABS Index of Relative Socioeconomic Disadvantage 2016 (IRSD) as a proxy. Deciles were converted to quintiles, where 1 = highest socioeconomic disadvantage and 5 = lowest socioeconomic disadvantage.

CalculationsCalculating OME:

OME / 1000 population / day = mass (mg) ✕ units dispensed ✕ 1000 ✕ conversion factor

population ✕ days

Calculating DDD:

DDD / 1000 population / day = mass (mg) ✕ units dispensed ✕ 1000

DDD (mg) ✕ population ✕ days

HospitalisationsSourceNSW Combined Admitted Patient Epidemiology Data (CAPED) and ABS population estimates (SAPHaRI). Centre for Epidemiology and Evidence, NSW Ministry of Health.

Data extracted 28 July 2020.

Case selection and analysis

• Data were analysed:- as age-standardised rates per 100,000

population- by age, sex, remoteness area, Aboriginal

status, socioeconomic status and ICD-10-AM code category (mental health or poisoning).

- for total opioid-related hospitalisations.

• Inclusion criteria: - episode end dates from 1 July 2010 to

30 June 2019- in persons aged 16 years and over- in NSW residents attending a NSW public

hospital- where the primary or secondary diagnoses

included the following poisoning or mental/behavioural disorders International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM) codes: all opioids: T40.0-T40.4, T40.6 and

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