Interrupted time series analysis is increasingly used to evaluate the impact of large-scale health interventions. While segmented regression is a common approach, it is not always adequate, ...especially in the presence of seasonality and autocorrelation. An Autoregressive Integrated Moving Average (ARIMA) model is an alternative method that can accommodate these issues.
We describe the underlying theory behind ARIMA models and how they can be used to evaluate population-level interventions, such as the introduction of health policies. We discuss how to select the shape of the impact, the model selection process, transfer functions, checking model fit, and interpretation of findings. We also provide R and SAS code to replicate our results.
We illustrate ARIMA modelling using the example of a policy intervention to reduce inappropriate prescribing. In January 2014, the Australian government eliminated prescription refills for the 25 mg tablet strength of quetiapine, an antipsychotic, to deter its prescribing for non-approved indications. We examine the impact of this policy intervention on dispensing of quetiapine using dispensing claims data.
ARIMA modelling is a useful tool to evaluate the impact of large-scale interventions when other approaches are not suitable, as it can account for underlying trends, autocorrelation and seasonality and allows for flexible modelling of different types of impacts.
Background and aims
Pregabalin is a gamma‐aminobutyric acid (GABA) analogue, used to treat neuropathic pain and epilepsy. Pregabalin was registered in Australia in 2005, and subsidized publically in ...2013. We aimed to describe Australian patterns of pregabalin use and intentional poisoning, and identify people potentially at high risk of misuse.
Design and setting
Population‐based retrospective cohort study of dispensings in the 10% sample of Australian Pharmaceutical Benefits Scheme (July 2012–February 2017); intentional poisoning calls to New South Wales Poisons Information Centre (NSWPIC) (2004–2016); intentional poisonings in two Australian toxicology service databases; and poisoning fatalities in NSW coronial records (2005–2016).
Participants
A total of 122 572 people dispensed pregabalin, people with intentional pregabalin overdoses managed by NSWPIC and the toxicology services and pregabalin‐associated deaths referred to the NSW coroner.
Measurements
Trends in dispensing, poisoning, death; demographics and patient characteristics, proportion of users at high risk of misuse (latent class analysis, LCA) and characteristics of high‐risk users.
Findings
Pregabalin dispensing increased by 73 424 per year 95% confidence interval (CI) = 61726–85 121 P < 0.001 between 2013 and 2016. NSWPIC received 1158 reports of intentional pregabalin poisonings, with a 53.8% increase per year, 2005–2016 (95% CI = 44.0–64.2%, P < 0.001). We identified 88 pregabalin‐associated deaths, 57.8% yearly increase (95% CI = 30.0–91.6%, P < 0.001). Patients overdosing on pregabalin commonly co‐ingested opioids, benzodiazepines and illicit drugs, and had high rates of psychiatric and substance use comorbidities; 14.7% of pregabalin users were classed by the LCA as at high risk of misuse, and were more likely to be younger, male, co‐prescribed benzodiazepines or opioids, have more individual prescribers and higher pregabalin strengths dispensed.
Conclusions
There has been a dramatic increase in pregabalin use, poisonings and deaths in Australia since it became subsidized publicly in 2013. One in seven Australians dispensed pregabalin appears to be at high risk of misuse.
Chemotherapy side effects are often reported in clinical trials; however, there is little evidence about their incidence in routine clinical care. The objective of this study was to describe the ...frequency and severity of patient-reported chemotherapy side effects in routine care across treatment centres in Australia.
We conducted a prospective cohort study of individuals with breast, lung or colorectal cancer undergoing chemotherapy. Side effects were identified by patient self-report. The frequency, prevalence and incidence rates of side effects were calculated by cancer type and grade, and cumulative incidence curves for each side effect computed. Frequencies of side effects were compared between demographic subgroups using chi-squared statistics.
Side effect data were available for 449 eligible individuals, who had a median follow-up of 5.64 months. 86% of participants reported at least one side effect during the study period and 27% reported a grade IV side effect, most commonly fatigue or dyspnoea. Fatigue was the most common side effect overall (85%), followed by diarrhoea (74%) and constipation (74%). Prevalence and incidence rates were similar across side effects and cancer types. Age was the only demographic factor associated with the incidence of side effects, with older people less likely to report side effects.
This research has produced the first Australian estimates of self-reported incidence of chemotherapy side effects in routine clinical care. Chemotherapy side effects in routine care are common, continue throughout chemotherapy and can be serious. This work confirms the importance of observational data in providing clinical practice-relevant information to decision-makers.
Objective
To estimate the prevalence of polypharmacy among Australians aged 70 years or more, 2006–2017.
Design, setting and participants
Analysis of a random 10% sample of Pharmaceutical Benefits ...Scheme (PBS) data for people aged 70 or more who were dispensed PBS‐listed medicines between 1 January 2006 and 31 December 2017.
Main outcome measures
Prevalence of continuous polypharmacy (five or more unique medicines dispensed during both 1 April – 30 June and 1 October – 31 December in a calendar year) among older Australians, and the estimated number of people affected in 2017; changes in prevalence of continuous polypharmacy among older concessional beneficiaries, 2006–2017.
Results
In 2017, 36.1% of older Australians were affected by continuous polypharmacy, or an estimated 935 240 people. Rates of polypharmacy were higher among women than men (36.6% v 35.4%) and were highest among those aged 80–84 years (43.9%) or 85–89 years (46.0%). The prevalence of polypharmacy among PBS concessional beneficiaries aged 70 or more increased by 9% during 2006–2017 (from 33.2% to 36.2%), but the number of people affected increased by 52% (from 543 950 to 828 950).
Conclusions
The prevalence of polypharmacy among older Australians is relatively high, affecting almost one million older people, and the number is increasing as the population ages. Our estimates are probably low, as we could not take over‐the‐counter or complementary medicines or private prescriptions into account. Polypharmacy can be appropriate, but there is substantial evidence for its potential harm and the importance of rationalising unnecessary medicines, particularly in older people.
Background and aims
Globally, codeine is the most‐used opioid. In December 2016, Australia announced that low‐strength codeine (≤ 15 mg) would be re‐scheduled and no longer available for purchase ...over‐the‐counter; this was implemented in February 2018. We aimed to evaluate the effect of this scheduling change on codeine misuse and use and misuse of other opioids.
Design and setting
Interrupted time–series analysis of monthly opioid exposure calls to New South Wales Poisons Information Centre (NSWPIC, captures 50% of Australia's poisoning calls), January 2015– January 2019 and monthly national codeine sales, March 2015–March 2019. We incorporated a washout period (January 2017 – January 2018) between the announcement and implementation, when prescriber/consumer behaviour may have been influenced.
Participants
Intentional opioid overdoses resulting in a call to NSWPIC.
Measurements
We used linear segmented regression to identify abrupt changes in level and slope of fitted lines. Codeine poisonings and sales were stratified into high strength (> 15 mg per dose unit) and low strength (≤ 15 mg). Only low‐strength formulations were re‐scheduled.
Findings
We observed an abrupt −50.8 percentage 95% confidence interval (CI) = −79.0 to −22.6% level change in monthly codeine‐related poisonings and no change in slope in the 12 months after February 2018. There was no increase in calls to the NSWPIC for high‐strength products, level change: –37.2% (95% CI = −82.3 to 8%) or non‐codeine opioids, level change: –4.4% (95% CI = −33.3 to 24.4%). Overall, the re‐scheduling resulted in a level change in opioid calls of −35.8% calls/month (95% CI = −51.2 to −20.4%). Low‐strength codeine sales decreased by 87.3% (95% CI = −88.5 to −85.9%), with no increase in high‐strength codeine sales in the 14 months following re‐scheduling, −4.0% (95% CI = −19.6 to 14.6%).
Conclusions
Codeine re‐scheduling in Australia appears to have reduced codeine misuse and sales.
Aims
To report Australian population trends in subsidized prescribed opioid use, total costs to the Australian government to subsidize these medicines and opioid‐related harms based on ...hospitalizations and accidental poisoning deaths.
Methods
We utilized three national aggregated data sources including dispensing claims from the Pharmaceutical Benefits Scheme, opioid‐related hospitalizations from the National Hospital Morbidity Database and accidental poisoning deaths from the Australian Bureau of Statistics.
Results
Between 1992 and 2012, opioid dispensing episodes increased 15‐fold (500 000 to 7.5 million) and the corresponding cost to the Australian government increased 32‐fold ($8.5 million to $271 million). Opioid‐related harms also increased. Opioid‐related hospitalizations increased from 605 to 1464 cases (1998–2009), outnumbering hospitalizations due to heroin poisonings since 2001. Deaths due to accidental poisoning (pharmaceutical opioids and illicit substances combined) increased from 151 to 266 (2002–2011), resulting in a rise in the death rate of 0.78 to 1.19 deaths/100 000 population over 10 years. Death rates increased 1.8 fold in males and 1.4 fold in females.
Conclusions
The striking increase in opioid use and related harms in Australia is consistent with trends observed in other jurisdictions. Further, there is no evidence to suggest these increases are plateauing. There is currently limited evidence in Australia about individual patterns of opioid use and the associated risk of adverse events. Further research should focus on these important issues so as to provide important evidence supporting effective change in policy and practice.
Aim
The aim of this paper is to investigate 25‐year trends in community use of prescribed opioid analgesics in Australia, and to map these trends against major changes to opioid registration and ...subsidy.
Methods
We obtained dispensing data from 1990 to 2014 from two sources: dispensing claims processed under Australia's national drug subsidy programme, the Pharmaceutical Benefits Scheme, including under co‐payment records from 2012; and estimates of non‐subsidized medicine use from a survey of Australian pharmacies (until 2011). Utilization was expressed in defined daily doses (DDD)/1000 population/day.
Results
Opioid dispensing increased almost four‐fold between 1990 and 2014, from 4.6 to 17.4 DDD/1000 pop/day. In 1990, weak, short‐acting or orally administered opioids accounted for over 90% of utilization. Use of long‐acting opioids increased over 17‐fold between 1990 and 2000, due primarily to the subsidy of long‐acting morphine and increased use of methadone for pain management. Between 2000 and 2011, oxycodone, fentanyl, buprenorphine, tramadol and hydromorphone use increased markedly. Use of strong opioids, long‐acting and transdermal preparations also increased, largely following the subsidy of various opioids for noncancer pain. In 2011, the most dispensed opioids were codeine (41.1% of total opioid use), oxycodone (19.7%) and tramadol (16.1%); long‐acting formulations comprised approximately half, and strong opioids 40%, of opioid dispensing.
Conclusions
Opioid utilization in Australia is increasing, although these figures remain below levels reported in the US and Canada. The increased use of opioids was largely driven by the subsidy of long‐acting formulations and opioids for the treatment of noncancer pain.
Pharmaceutical claims data are often used as the primary information source to define medicine exposure periods in pharmacoepidemiological studies. However, often critical information on directions ...for use and the intended duration of medicine supply are not available. In the absence of this information, alternative approaches are needed to support the assignment of exposure periods. This study summarises the key methods commonly used to estimate medicine exposure periods and dose from pharmaceutical claims data; and describes a method using individualised dispensing patterns to define time‐dependent estimates of medicine exposure and dose. This method extends on important features of existing methods and also accounts for recent changes in an individual's medicine use. Specifically, this method constructs medicine exposure periods and estimates the dose used by considering characteristics from an individual's prior dispensings, accounting for the time between prior dispensings and the amount supplied at prior dispensings. Guidance on the practical applications of this method is also provided. Although developed primarily for application to databases, which do not contain duration of supply or dose information, use of this method may also facilitate investigations when such information is available and there is a need to consider individualised and/or changing dosing regimens. By shifting the reliance on prescribed duration and dose to determine exposure and dose estimates, individualised dispensing information is used to estimate patterns of exposure and dose for an individual. Reflecting real‐world individualised use of medicines with complex and variable dosing regimens, this method offers a pragmatic approach that can be applied to all medicine classes.
Background and Aims
Alcohol consumption is a leading risk factor for premature mortality globally, but there are limited studies of broader cohorts of people presenting with alcohol‐related problems ...outside of alcohol treatment services. We used linked health administrative data to estimate all‐cause and cause‐specific mortality among individuals who had an alcohol‐related hospital inpatient or emergency department presentation.
Design
Observational study using data from the Data linkage Alcohol Cohort Study (DACS), a state‐wide retrospective cohort of individuals with an alcohol‐related hospital inpatient or emergency department presentation.
Setting
Hospital inpatient or emergency department presentation in New South Wales, Australia, between 2005 and 2014.
Participants
Participants comprised 188 770 individuals aged 12 and above, 66% males, median age 39 years at index presentation.
Measurements
All‐cause mortality was estimated up to 2015 and cause‐specific mortality (by those attributable to alcohol and by specific cause of death groups) up to 2013 due to data availability. Age‐specific and age–sex‐specific crude mortality rates (CMRs) were estimated, and standardized mortality ratios (SMRs) were calculated using sex and age‐specific deaths rates from the NSW population.
Findings
There were 188 770 individuals in the cohort (1 079 249 person‐years of observation); 27 855 deaths were recorded (14.8% of the cohort), with a CMR of 25.8 95% confidence interval (CI) = 25.5, 26.1 per 1000 person‐years and SMR of 6.2 (95% CI = 5.4, 7.2). Mortality in the cohort was consistently higher than the general population in all adult age groups and in both sexes. The greatest excess mortality was from mental and behavioural disorders due to alcohol use (SMR = 46.7, 95% CI = 41.4, 52.7), liver cirrhosis (SMR = 39.0, 95% CI = 35.5, 42.9), viral hepatitis (SMR = 29.4, 95% CI = 24.6, 35.2), pancreatic diseases (SMR = 23.8, 95% CI = 17.9, 31.5) and liver cancer (SMR = 18.3, 95% CI = 14.8, 22.5). There were distinct differences between the sexes in causes of excess mortality (all causes fully attributable to alcohol female versus male risk ratio = 2.5 (95% CI = 2.0, 3.1).
Conclusions
In New South Wales, Australia, people who came in contact with an emergency department or hospital for an alcohol‐related presentation between 2005 and 2014 were at higher risk of mortality than the general New South Wales population during the same period.
Purpose
To describe Australians' prescribed medicine use on a typical day (September 25, 2018).
Methods
We conducted a cross‐sectional study using nationally representative dispensing claims data ...using the Australian Government Department of Human Services random 10% sample of all Australians eligible for prescription medicines subsidised through the Australian Pharmaceutical Benefits Scheme (PBS). Our main outcome measures were the number and proportion of people using at least one prescribed medicine and the specific medicine groups and classes on the day. We estimated the proportion of Australians using these medicines using the mid‐year Australian population as the denominator. We quantified multiple medicine use by calculating the number and proportion of people experiencing polypharmacy (the use of 5 or more unique medicines) and hyper‐polypharmacy (the use of 10 or more unique medicines).
Results
We found that 9.0 million Australians used at least one PBS medicine on September 25, 2018; equating to 27.5 million medicines in use across Australia. “Cardiovascular system”, “nervous system” and “alimentary tract and metabolism” medicines comprised the top three medicine groups. Over 1.8 million people experienced polypharmacy on the day, accounting for 13.6 million dispensed medicines. 1 022 590 (45%) people aged ≥70 years old experienced polypharmacy and 188 930 (8%) experienced hyper‐polypharmacy.
Conclusions
Rates of polypharmacy were high, particularly in the people most susceptible to polypharmacy‐related harm. Strategies to optimise the risk‐benefit ratio of medicines and to reduce polypharmacy through “choosing wisely” and “de‐prescribing” in this age group are needed. Australia's national data provides a benchmark to inform global medicine utilisation practices.
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