Opioid sales and opioid-related poisonings in Switzerland: A descriptive population-based time-series analysis

Increased Use and Large Variation in Strong Opioids and Metamizole (Dipyrone) for Minor and Major Musculoskeletal Injuries Between 2008 and 2018: An Analysis of a Representative Sample of Swiss Workers

PURPOSE

Musculoskeletal (MSK) injuries are a major contributing factor for chronic pain. To date, little is known how pain medication use in MSK injuries has changed over time. We assessed pain medication prescription for MSK injuries in a representative sample of Swiss workers between 2008 and 2018.

METHODS

Retrospective analysis of the Swiss Accident Insurance Fund (Suva) data. We calculated annual pain medication use, treatment days, and costs associated with pain medication use in minor and major MSK injuries.

RESULTS

In total, 1,921,382 cases with MSK injuries with ≥ 1 pain medication were analyzed. Whereas MSK injuries with ≥ 1 pain medication increased by 9.4%, we observed a larger increase in metamizole (+ 254%), strong opioids (+ 88.4%), coxibs (+ 85.8%), and paracetamol (+ 28.1%). Strong opioids were increasingly used in minor (+ 91.4%) and major (+ 88.3%) injuries. The increase in metamizole (+ 390.6%) and coxibs (+ 115.5%) was larger in minor injuries compared to major injuries (+ 238.7% and + 80.6%, respectively). Medical expenses decreased in all medications except for strong opioids where a substantial increase was observed (+ 192.4% in minor; + 34% in major injuries).

CONCLUSIONS

We observed a disproportionate increase in metamizole, strong opioids, coxibs, and paracetamol prescriptions even in minor MSK injuries between 2008 and 2018. Whereas treatment costs decreased for all pain medications, there was a substantial increase in strong opioids. A more liberal prescription practice of opioids conflict with current evidence-based practice recommendations and need to be addressed by physicians and policy makers.

Factors influencing pain medication and opioid use in patients with musculoskeletal injuries: a retrospective insurance claims database study

Opioid use is only recommended in selected cases of musculoskeletal (MSK) injuries. We assessed factors associated with increased opioid use in MSK injuries. In a retrospective analysis of over four million workers with MSK injuries using the Swiss National Accident Insurance Fund (Suva) database, we analyzed risk factors by multivariate logistic regression. Injury severity was associated with pain medication, opioid, and strong opioid use. Whereas fractures, contusions, and ruptures had higher odds for any pain medication use, increased odds for strong opioids were observed in fractures, superficial injuries, and other injuries. Injuries of the shoulders, elbow, chest, back/spine, thorax, and pelvis/hips showed high odds for opioid use (odds ratio (OR) > 2.0). Injuries of the shoulders had higher odds for strong opioid use (OR 1.136; 95% CI 1.040-1.241). The odds for using strong opioids increased from 2008 OR 0.843 (95% confidence interval (CI) 0.798-0.891) to 2018 OR 1.503 (95% CI 1.431-1.578), compared to 2013. Injury severity, type of injury, and injured body parts influenced the use of pain medication and overall opioid use in musculoskeletal injuries. Strong opioids were more often used in fractures but also in superficial and other minor injuries, which indicates that other factors play a role when prescribing strong opioids.

Hospitalisations Related to Adverse Drug Reactions in Switzerland in 2012-2019: Characteristics, In-Hospital Mortality, and Spontaneous Reporting Rate

INTRODUCTION

Adverse drug reactions (ADRs) contribute to morbidity, and serious ADRs may cause hospitalisation and death. This study characterises and quantifies ADR-related hospitalisations and subsequent in-hospital deaths, and estimates the spontaneous reporting rate to regulatory authorities in Switzerland, where healthcare professionals are legally obliged to report ADRs.

METHODS

This retrospective cohort study from 2012 to 2019 analysed nationwide data from the Federal Statistical Office. ICD-10 coding rules identified ADR-related hospitalisations. To estimate the reporting rate, individual case safety reports (ICSRs) collected in the Swiss spontaneous reporting system during the same period were considered.

RESULTS

Among 11,240,562 inpatients, 256,550 (2.3%) were admitted for ADRs, 132,320 (51.6%) were female, 120,405 (46.9%) were aged ≥ 65 (median of three comorbidities, interquartile range [IQR] 2-4), and 16,754 (6.5%) were children/teenagers (0 comorbidities, IQR 0-1). Frequent comorbidities were hypertension (89,938 [35.1%]), fluid/electrolyte disorders (54,447 [21.2%]), renal failure (45,866 [17.9%]), cardiac arrhythmias (37,906 [14.8%]), and depression (35,759 [13.9%]). Physicians initiated 113,028 (44.1%) of hospital referrals, and patients/relatives 73,494 (28.6%). Frequently ADR-affected were the digestive system (48,219 [18.8%], e.g. noninfective gastroenteritis and colitis), the genitourinary system (39,727 [15.5%], e.g. acute renal failure), and the mental/behavioural state (39,578 [15.4%], e.g. opioid dependence). In-hospital mortality was 2.2% (5669). Since ICSRs indicated 14,109 hospitalisations and 700 in-hospital deaths, estimated reporting rates were 5% and 12%, respectively.

CONCLUSIONS

This 8-year observation in Switzerland revealed that 2.3%, or roughly 32,000 admissions per year, were caused by ADRs. The majority of ADR-related admissions were not reported to the regulatory authorities, despite legal obligations.

Opioid-related harms and care impacts of conventional and AI-based prescription management strategies: insights from leveraging agent-based modeling and machine learning

Introduction

Like its counterpart to the south, Canada ranks among the top five countries with the highest rates of opioid prescriptions. With many suffering from opioid use disorder first having encountered opioids via prescription routes, practitioners and health systems have an enduring need to identify and effectively respond to the problematic use of opioid prescription. There are strong challenges to successfully addressing this need: importantly, the patterns of prescription fulfillment that signal opioid abuse can be subtle and difficult to recognize, and overzealous enforcement can deprive those with legitimate pain management needs the appropriate care. Moreover, injudicious responses risk shifting those suffering from early-stage abuse of prescribed opioids to illicitly sourced street alternatives, whose varying dosage, availability, and the risk of adulteration can pose grave health risks.

Methods

This study employs a dynamic modeling and simulation to evaluate the effectiveness of prescription regimes employing machine learning monitoring programs to identify the patients who are at risk of opioid abuse while being treated with prescribed opioids. To this end, an agent-based model was developed and implemented to examine the effect of reduced prescribing and prescription drug monitoring programs on overdose and escalation to street opioids among patients, and on the legitimacy of fulfillments of opioid prescriptions over a 5-year time horizon. A study released by the Canadian Institute for Health Information was used to estimate the parameter values and assist in the validation of the existing agent-based model.

Results and discussion

The model estimates that lowering the prescription doses exerted the most favorable impact on the outcomes of interest over 5 years with a minimum burden on patients with a legitimate need for pharmaceutical opioids. The accurate conclusion about the impact of public health interventions requires a comprehensive set of outcomes to test their multi-dimensional effects, as utilized in this research. Finally, combining machine learning and agent-based modeling can provide significant advantages, particularly when using the latter to gain insights into the long-term effects and dynamic circumstances of the former.