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Trial registered on ANZCTR


Registration number
ACTRN12620000924954
Ethics application status
Approved
Date submitted
29/06/2020
Date registered
17/09/2020
Date last updated
22/05/2023
Date data sharing statement initially provided
17/09/2020
Type of registration
Prospectively registered

Titles & IDs
Public title
Persistent opioid use and opioid-related harm after hospital admissions for surgery and trauma in New Zealand- a population-based retrospective cohort study
Scientific title
Persistent opioid use and opioid-related harm after hospital admissions for surgery and trauma in New Zealand- a population-based retrospective cohort study
Secondary ID [1] 301151 0
None
Universal Trial Number (UTN)
Trial acronym
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Trauma 317379 0
Surgery 318399 0
Pain 318400 0
Condition category
Condition code
Public Health 315479 315479 0 0
Epidemiology
Anaesthesiology 315480 315480 0 0
Pain management
Injuries and Accidents 315481 315481 0 0
Fractures
Emergency medicine 315482 315482 0 0
Other emergency care
Surgery 315483 315483 0 0
Other surgery

Intervention/exposure
Study type
Observational
Patient registry
False
Target follow-up duration
Target follow-up type
Description of intervention(s) / exposure
Surgical and trauma patients discharged with an opioid prescription from any New Zealand public hospitals between 1st January 2007 and 31st December 2019 will be assessed using the National Minimum Data Set, the National Non-admitted Patient Collection and the NZ Pharmaceutical collection.
Intervention code [1] 317522 0
Not applicable
Comparator / control treatment
no control group, non-intervention study
Control group
Uncontrolled

Outcomes
Primary outcome [1] 323722 0
Persistent use of opioids after trauma or surgery as assessed via pharmacy dispensing claimant database (Pharmaceutical collection). Persistent opioid use will be defined as additional pharmacy claims for one or more opioid prescriptions 91 days to 365 days after date of hospital discharge
Timepoint [1] 323722 0
Persistent opioid use will be defined as additional pharmacy claim for one or more opioid prescription 91 days to 365 days after the date of hospital discharge. Patients who filled one or more opioid prescriptions within 90 days after the hospital discharge date but did not fill between 91 and 365 days will be considered as non-persistent opioid users, as the duration of use is time-limited so cannot be considered as chronic (persistent) use.
Secondary outcome [1] 382720 0
All-cause mortality at 6 months and 12 months after persistent opioid use, is defined as the presence of a date of death for any cause recorded in the MORT database.
Timepoint [1] 382720 0
We will follow all patients from the last date of when persistent opioid outcome occurs for a maximum of 365 days either until the end of the follow-up period if no event occurs or the date of death,
Secondary outcome [2] 382721 0
Mortality due to opioid overdose will be defined as the presence of a date of death and opioid overdose as the cause of death as recorded in the MORT database. These episodes of related harm will be identified via ICD-10AM codes present during patients’ subsequent admission after the hospital discharge date and specific ACC codes for non-fatal opioid overdose.
Timepoint [2] 382721 0
We will follow all patients from the last date of when persistent opioid outcome occurs for a maximum of 365 days either until the end of the follow-up period if no event occurs or the date of death,
Secondary outcome [3] 384991 0
Hospital admission related to opioid overdose and toxicity during the follow-up period.

This secondary outcome will be assessed through linkage of medical records via the NMDS and National NNPAC to account for both prolonged and acute hospital admissions.
Timepoint [3] 384991 0
We will follow all patients from the last date of when persistent opioid outcome occurs for a maximum of 180 days either until the end of the follow-up period if no event occurs, hospital admission related to overdose and toxicity, or the date of death,
Secondary outcome [4] 384992 0
We will also measure Days Alive Out of Hospital to 180 days (DAOH180). This is an outcome that will be used for measuring the quality of post-operative care.
Timepoint [4] 384992 0
We will follow up with all patients from the date of persistent opioid use for a maximum of 180 days until death or the end of follow-up occurs.
Secondary outcome [5] 413411 0
All-cause hospital admission during the follow-up period. This secondary outcome will be assessed through the linkage of medical records via the NMDS and National NNPAC to account for both prolonged and acute hospital admissions.
Timepoint [5] 413411 0
We will follow all patients from the last date of when persistent opioid outcome occurs for a maximum of 180 days either until the end of the follow-up period if no event occurs, any cause of hospital admission, or the date of death,

Eligibility
Key inclusion criteria
The study population includes all opioid-naïve patients (of any age) who had a surgical procedure and/or were presented to the hospital with trauma in one of NZ’s 39 public hospitals between 1st January 2007 and 31st December 2019.
Minimum age
No limit
Maximum age
No limit
Sex
Both males and females
Can healthy volunteers participate?
No
Key exclusion criteria
1) those who have evidence of a surgical procedure and/or traumatic event in 365 days prior to the index date; 2) those who underwent more than one surgical procedure type on the day of surgery; and 3) those with evidence of opioid use disorders (e.g. overdose, misuse or dependence) or opioid prescriptions in 180 days prior to the index date.

Study design
Purpose
Natural history
Duration
Longitudinal
Selection
Defined population
Timing
Retrospective
Statistical methods / analysis
Descriptive statistics will be used to describe baseline characteristics and the outcomes of interest. Continuous variables will be described using the mean and standard deviation or median and interquartile range as appropriate, depending on data distribution. Categorical variables will be described using frequency distributions and percentages. Kolmogorov–Smirnov and Shapiro-Wilk tests of normality will be used to assess the distribution of continuous variables. Parametric and non-parametric bivariate tests (e.g. Student's t-test, Mann-Whitney U test or Chi-Square test) will be used to compare the characteristics of individuals who may or may not exhibit persistent opioid use after surgery or trauma.
A multivariable logistic regression model will be used to examine the association between potential predictors and persistent opioid use after surgery/trauma. Forward and backward conditional models will be used to minimise multicollinearity. Adjusted odds ratios (aOR) with 95% confidence intervals (95% CI) will be reported for modifiable risk factors and ethnicity. We used the Wald test, adjusted by the degree of freedom, to assess the relative effect size of the non-modifiable risk factors in the multivariable analysis and reported the aOR and 95% CI of the ten risk factors with the largest effect size. Quantile regression will be used to assess differences in DAOH between persistent and non-persistent opioid users, adjusted for relevant risk factors. The particular percentile used will 1% (0.01) to 10.0% (0.1) of both surgical or trauma cohort.
We will calculate the crude rate of each outcome of interest for both persistent and non-persistent opioid user groups. To compute the rates, we will divide the total number of outcome events by total follow-up time. These will be reported as cases per 1000 person-days with confidence intervals derived from a Poisson or negative binomial distribution as appropriate. Cox multivariable regression models will be used to estimate the risk of all-cause mortality, opioid-related mortality, all-cause hospitalisation, and opioid-related hospitalisation associated with persistent use of opioids in the 180 to 360 days after the index date for all patients. Hazard ratios and 95% confidence intervals will be reported. The proportional hazards assumption of the Cox model will be tested using a regression strategy where the covariates from the final model are entered first and then following up that model by adding the relevant interaction terms between the time measure and the covariates. We will also visually inspect the Kaplan-Meier (KM) curves of relevant covariates from the regression strategy. A two-sided p-value < 0.05 will be considered statistically significant for all statistical tests. We will undertake all analyses using SPSS v29 IBM corporation, Armonk NY, USA

Recruitment
Recruitment status
Completed
Date of first participant enrolment
Anticipated
2/11/2020
Actual
17/03/2021
Date of last participant enrolment
Anticipated
1/03/2021
Actual
1/09/2021
Date of last data collection
Anticipated
1/05/2021
Actual
30/09/2021
Sample size
Target
500000
Accrual to date
Final
524945
Recruitment outside Australia
Country [1] 22553 0
New Zealand
State/province [1] 22553 0

Funding & Sponsors
Funding source category [1] 305595 0
Other Collaborative groups
Name [1] 305595 0
Auckland Academic Health Alliance
Country [1] 305595 0
New Zealand
Funding source category [2] 306309 0
University
Name [2] 306309 0
Senior Health Research Scholarship
Country [2] 306309 0
New Zealand
Primary sponsor type
Individual
Name
Amy Chan
Address
University of Auckland
85 PARK RD, GRAFTON
AUCKLAND 1023
New Zealand
Country
New Zealand
Secondary sponsor category [1] 306127 0
None
Name [1] 306127 0
Address [1] 306127 0
Country [1] 306127 0

Ethics approval
Ethics application status
Approved
Ethics committee name [1] 305893 0
The Auckland Health Research Ethics Committee (AHREC)
Ethics committee address [1] 305893 0
University of Auckland, 85 PARK RD, GRAFTON
AUCKLAND 1023
New Zealand
Ethics committee country [1] 305893 0
New Zealand
Date submitted for ethics approval [1] 305893 0
20/01/2020
Approval date [1] 305893 0
15/04/2020
Ethics approval number [1] 305893 0
AH1159

Summary
Brief summary
This study aims to assess how admission to hospitals around New Zealand for surgery or trauma may influence persistent opioid use, and how this may lead to harm (including death) due to adverse effects or from overdose of opioids. We know that rates of opioid use have been on the rise in New Zealand (Health Safety and Quality Commission; HQSC) and elsewhere in the world (e.g. The US, UK and Australia), the HQSC has recently reported that hospital admissions may lead to new opioid use. However, little is known about the contribution that hospital admissions for surgery and trauma may make to persistent opioid use in New Zealand, and its association with serious adverse outcomes.

We will use national databases (National Minimum Data Set, NMDS and National Non-admitted Patient Collection) to identify patients who have been admitted for surgery or trauma between 2007 to 2019. Data on the duration and quantity of opioid use (where available) will be obtained for these individuals for a one-year period using the pharmacy dispensing database and linked to events related to harm secondary to opioid use such as mortality, hospitalisation related to opioid toxicity and overdose from national databases.

This project will allow us to estimate the risk of prolonged opioid use following hospital admission for surgery or trauma and identify individuals at risk of opioid-related harm. The information will help inform future policy, guidelines and interventions, regarding opioid prescribing after surgery or trauma in New Zealand.
Trial website
Trial related presentations / publications
Public notes

Contacts
Principal investigator
Name 101966 0
Dr Amy Chan
Address 101966 0
University of Auckland
85 PARK RD, GRAFTON
AUCKLAND 1023
New Zealand
Country 101966 0
New Zealand
Phone 101966 0
+64 9 923 5524
Fax 101966 0
Email 101966 0
[email protected]
Contact person for public queries
Name 101967 0
Jiayi Gong
Address 101967 0
University of Auckland
85 PARK RD, GRAFTON
AUCKLAND 1023
New Zealand
Country 101967 0
New Zealand
Phone 101967 0
+64 27414716
Fax 101967 0
Email 101967 0
[email protected]
Contact person for scientific queries
Name 101968 0
Jiayi Gong
Address 101968 0
University of Auckland
85 PARK RD, GRAFTON
AUCKLAND 1023
New Zealand
Country 101968 0
New Zealand
Phone 101968 0
+64 274124716
Fax 101968 0
Email 101968 0
[email protected]

Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
No
No/undecided IPD sharing reason/comment
No individual data as this is a retrospective registry based study using encrypted linked data.


What supporting documents are/will be available?




Results publications and other study-related documents

Documents added manually
No documents have been uploaded by study researchers.

Documents added automatically
No additional documents have been identified.