| Literature DB >> 35418442 |
Tina Lam1, Nicholas Biggs2, Ting Xia3, John Evans4, Jennifer Stevens5, Mike da Gama2, Dan I Lubman3,6, Suzanne Nielsen3,6.
Abstract
INTRODUCTION: Each year, an estimated two million Australians commence opioids, with 50 000 developing longer-term (persistent) opioid use. An estimated 3%-10% of opioid-naïve patients prescribed opioids following surgery develop persistent opioid use. This study will compare rates of persistent opioid use between two commonly used postoperative opioids, oxycodone and tapentadol, to understand if initial postoperative opioid type is important in determining longer-term outcomes. METHODS AND ANALYSIS: A retrospective data linkage study that analyses administrative data from hospital and community pharmacies. Data will be obtained from at least four pharmacies that service large hospitals with comparable supplies of oxycodone and tapentadol. The study will include at least 6000 patients who have been dispensed a supply of oxycodone or tapentadol to take home following their discharge from a surgical ward. The primary outcome measure will be persistent opioid use at 3 months postdischarge for opioid naïve people who receive either immediate release tapentadol or immediate release oxycodone. Hierarchical logistic regression models will be used to predict persistent opioid use, controlling for covariates including comorbidities. ETHICS AND DISSEMINATION: Ethics approval has been obtained through the Monash University Human Research Ethics Committee (29977). We will present project findings in a peer-reviewed journal article, in accordance with the REporting of studies Conducted using Observational Routinely-collected health Data statement. © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.Entities:
Keywords: Adult surgery; PUBLIC HEALTH; Substance misuse
Mesh:
Substances:
Year: 2022 PMID: 35418442 PMCID: PMC9014068 DOI: 10.1136/bmjopen-2021-060151
Source DB: PubMed Journal: BMJ Open ISSN: 2044-6055 Impact factor: 3.006
Figure 1Flow chart overview of the study design on the persistence of opioid use following surgical admission.
List of variables to be considered
| Variable | Type of pharmacy data | Description/considerations | |
| Hospital | Community | ||
| Age | ✓ | ✓ | Patient age at time of surgery, calculated from date of birth. |
| Sex | ✓ | ✓ | |
| Ward specialty (discharge ward as proxy for surgery type) | ✓ | The ward type will include the type of surgical ward the patient was discharged from—broad categories such as orthopaedic, general medicine, plastics and neurosurgery. | |
| Comorbidities | ✓ | Using Rx risk algorithm. Medication mapped categories include conditions associated with persistence risk such as anxiety, depression, pain and alcohol dependency. | |
| Prior opioid use | ✓ | Any prescribed opioid use in the 12 months prior to surgery | |
| Quantity of opioids supplied | ✓ | ✓ |
Quantity of tablets Dosage of opioid (eg, 5 mg) Total opioid quantity supplied in dispensing (tablet number multiplied by the dosage) Total opioid quantity dispensed in oral morphine equivalent |
| Pain duration | ✓ | Analgesic medications in the 12 months prior to surgery. Duration of continuous analgesia as a proxy for chronic pain. | |
| Socioeconomic status (SES) | ✓ | ✓ | The Socio-Economic Indexes for Areas (SEIFA) is calculated by the Australian Bureau of Statistics using over a dozen census data points such as household income, and proportion of people with postschool qualifications. |
| Socioeconomic status | ✓ | ✓ | Certain Pharmaceutical Benefit Scheme patients hold concession cards such as the ‘Healthcare card’, available to individuals who receive welfare payments or other types of government benefit. |