On- and off-label utilisation of antipsychotics in Australia (2000–2021): Retrospective analysis of two medication datasets

Abstract

Objective:

To determine antipsychotic utilisation patterns in Australian adults from 2005 to 2021, with a focus on on-label and off-label prescriptions.

Methods:

We examined antipsychotic dispensing trends in adults from 2005 to 2021 using a 10% sample of the Pharmaceutical Benefits Scheme (PBS) dataset, which contains patient-level information on medicines dispensed throughout Australia. The lack of diagnostic information in PBS was substituted by analysing BEACH (Bettering the Evaluation And Care of Health) dataset, a cross-sectional national survey from 2000 to 2016, consisting of data from general practitioner–patient encounters.

Results:

There were 5.6 million dispensings for 164,993 patients in PBS throughout this period; 69% patients had >1 dispensing, with a median of 6 per patient. Calculating the estimated period of exposure gave a total of 693,562 treatment episodes, with a median duration of 80 days. There were steady increases in both the incidence and prevalence of antipsychotic dispensings, mainly due to oral second-generation antipsychotics. The most commonly prescribed antipsychotics were quetiapine, olanzapine and risperidone, with a significant portion of patients receiving low-dose quetiapine without dose titration. Analysis of diagnostic indications from BEACH indicated that 27% of antipsychotic prescriptions were off-label for indications such as depression, dementia, anxiety and insomnia, at much lower prescribed daily dosages.

Conclusion:

The increasing prescribing and off-label use highlights concerns about chronic adverse effects caused by antipsychotics. The combined analysis of medication dispensings and the diagnostic indications for which they are prescribed is a novel approach and throws a spotlight on the need for additional monitoring of antipsychotics.

Keywords

Antipsychotic off-label prescribing utilisation trends quetiapine clozapine

Introduction

First-generation antipsychotics (FGAs) were the mainstay of schizophrenia treatment until the development of second-generation antipsychotics (SGAs) in the 1990s. SGAs were perceived to have a better adverse effect profile with regard to neurological manifestations and are now the most commonly prescribed antipsychotics (Chokhawala and Stevens, 2022). There has been a steady increase in antipsychotic utilisation over the years, both globally and in Australia, mainly attributed to the SGAs (Hálfdánarson et al., 2017; Harrison and Britt, 2003; Karanges et al., 2014; Stephenson et al., 2013; Su et al., 2020). In contrast, the global burden of schizophrenia, measured in terms of age-standardised incidence rates, decreased slightly from 1990 to 2017, while the age-standardised rate of DALYs (disability-adjusted life years) remained stable (He et al., 2020).

A significant portion of the increased use could be attributed to concomitant polytherapy, regulatory approval for other indications such as bipolar disorder, and ‘off-label’ prescribing for indications that have not been approved for antipsychotic treatment (Alexander et al., 2011). A review of antipsychotic prescribing found 40–75% of all prescriptions to be off-label, and more common among SGAs (McKean and Monasterio, 2012). Among adults, common non-psychotic indications included mood disorders, anxiety disorders, insomnia, agitation, personality disorders, obsessive-compulsive disorder, post-traumatic stress disorder and substance use disorder, while dementia, behavioural issues, depression and insomnia were more common among the elderly (Carton et al., 2015).

This is a concerning trend, since long-term use of antipsychotics leads to adverse effects including weight gain and increased risk of metabolic, cerebrovascular, cardiovascular diseases (Maglione et al., 2011), which could be further exacerbated by behavioural effects of psychiatric disorders. Antipsychotics are usually prescribed at low doses in these off-label indications and there is a common perception that this may prevent adverse effects (Højlund et al., 2019; McKean and Monasterio, 2012). However, studies have reported associations between low-dose use and serious adverse effects including weight gain, sudden cardiac death and diabetes (Berge et al., 2022; Cates et al., 2009; Fernandez et al., 2008; Ray et al., 2009).

Many drug utilisation studies published in Australia have examined the Pharmaceutical Benefits Scheme (PBS) dataset, which covers prescription medication dispensed to eligible Australians (Pearson et al., 2015). An important advantage of analysing such data is the capacity to examine longitudinal data on real-world post-marketing medicine utilisation in a natural patient setting for the whole population; however, being an administrative dataset, it is incomplete and lacks crucial information such as drug dosage, duration and clear indication or diagnostic data. To overcome these limitations, the current study will analyse both the PBS and BEACH datasets. BEACH (Bettering the Evaluation and Care of Health) was a national survey of Australian general practitioner (GP)–patient encounters and provides crucial information on the indications (Britt, 2003), while being representative of all active GPs each year (Britt et al., 2015). Although BEACH is limited to GP-based prescriptions, in contrast to PBS which includes all specialties, it provides a reflection of trends in antipsychotic prescribing, indications and doses in real-world Australian healthcare, a notable gap in most Australian medication datasets. Although it is not possible to link these datasets, the use of information from both can offer two complementary perspectives on antipsychotic utilisation in Australia.

The current study aims to determine the antipsychotic utilisation patterns in adults from 2005 to 2021 from the Australian PBS dataset and analyse on-label and off-label prescription trends from 2000 to 2016 in the BEACH dataset.

Methods

Data sources and patient population

This study was a retrospective pharmacoepidemiologic analysis of data from the Australian 10% PBS sample and BEACH datasets, and included patients aged 18 years and above.

Details on medicines dispensed through the PBS scheme are collected by Services Australia, and a random 10% sample of this dataset is provided to researchers, with deidentified records of a nationally representative set of patients. Selected patients remain in the 10% dataset, thus aiding longitudinal analyses. Information available for analysis includes medication supply date, prescription date, Anatomical Therapeutic Chemical (ATC) code, PBS item code, number of scripts and quantity dispensed, patient year of birth and sex, and authority restriction codes. PBS data was available from April 2005 to December 2021. The authority codes are drug-specific and sometimes used to identify the indication for which the drug is dispensed; we will examine these codes, though our analysis maybe limited since this information was missing in nearly half of our data (2005–2012) as well as for FGAs.

BEACH was a cross-sectional national survey of GP activity wherein every year a new random sample of 1,000 GPs provided details of 100 patient encounters (Britt, 2003; Britt et al., 2016; Britt and Miller, 2015). Data were collected from 1998 to 2016 and included over 1.7 million GP–patient encounters from 17,707 GPs. The dataset contains information on GP and patient characteristics, encounter details, problems managed, and prescribed medications, with access provided through the Menzies Centre for Health Policy and Economics in The University of Sydney. The time period for our data extraction was 2000–2016.

There were 20 PBS-approved antipsychotics with ATC code N05A** dispensed in Australia through the PBS scheme in this period (Supplemental Table 1); cariprazine was dropped from further analyses due to having just 250 dispensings. BEACH contains information for 23 antipsychotics (excluding prochlorperazine, which is primarily indicated for nausea and vomiting, and lithium); for comparability with PBS, analyses were restricted to the 19 antipsychotics we examined in the PBS data. The four non-PBS antipsychotics were rarely used, with a total of 21 prescriptions in the BEACH data (Supplemental Table 2).

Outcome measures

Adult patients with at least one antipsychotic dispensing in PBS, or GP encounters in BEACH where an antipsychotic was prescribed, were considered for the analyses. The main outcome measures were antipsychotic utilisation trends and the associated indications for prescription. Since the datasets are not linked, we analysed the data under two major sections.

Section A: PBS dispensing temporal trends 2005–2021

We analysed the utilisation trends for antipsychotics as a group and by category in the PBS dataset. Details on the antipsychotic dose and formulation were derived from the PBS item codes and categorised based on formulation into oral, long-acting injection (LAI) or short-acting injection (SAI) and based on generation as FGA or SGA. Clozapine is grouped under the S100 Highly Specialised Drugs category and was considered separately since it is approved only for treatment-resistant schizophrenia with heightened monitoring. There were thus six distinct categories: FGA oral, FGA LAI, FGA SAI, SGA oral, SGA LAI and clozapine.

PBS data does not capture the prescribed dose or days of medicine supply and hence we calculated the estimated period of exposure (EPE), an established method of determining the period during which patients had access to the medicine (Brett et al., 2021; Pottegård and Hallas, 2013). The EPE was defined as the number of days within which 75% of patients received their next dispensing and was calculated for each antipsychotic based on its formulation, with differences of more than 180 days between dispensings excluded. Treatment episodes were calculated as the period of continuous dispensings with a particular antipsychotic where the number of days between consecutive dispensings was within the EPE plus 30 days (a grace period to account for variable delays in filling prescriptions). Changes in formulations of a medicine were included in the treatment episode; switching antipsychotics was regarded as a new treatment episode. The number of dispensings within a treatment episode was also calculated. Treatment duration for each episode (i.e. when the patient had access to the medicine) was calculated from the first and last dispensing dates of each treatment episode plus the EPE and was measured in days. Finally, we analysed the utilisation trends for the top dispensed antipsychotics in the PBS data.

Section B: indications and respective dosages from BEACH

Antipsychotic prescriptions were identified from the BEACH dataset and details on the diagnostic indications and the prescribed daily dosages (PDDs) were extracted. We examined all AMH (Australian Medicines Handbook, 2021) issues published during the study period to determine the permitted indications for each antipsychotic. Based on the Australian Medicines Handbook (AMH) guidelines, the indications were grouped into four diagnostic groups:

On-label: indications approved for each individual antipsychotic treatment, including severe mental illnesses such as schizophrenia, schizoaffective disorder, bipolar disorder, mania and psychosis (refer Supplemental Figure 2).

Neurological disorders: intellectual disability, autism, attention-deficit hyperactivity disorder, pervasive developmental disorder, dementia, Alzheimer’s disease, brain injury, Parkinson’s disease, Huntington’s disease, chronic tic disorder, Tourette syndrome and epilepsy.

Other psychological disorders: other non-psychotic disorders such as obsessive-compulsive disorder, conduct disorders, impulsive disorders, self-injury, phobias, PTSD, depression, anxiety, agitation, mood disorders and personality disorder.

General illnesses: eating disorders, insomnia, migraine, chronic pain, substance abuse, hiccup, delirium, vomiting and nausea, neuralgia, cancer and palliative care.

Some antipsychotics are approved for specific sub-groups of an indication (such as quetiapine for treatment-resistant depression and risperidone for behavioural disturbances in dementia) and where detailed information on the sub-groups could not be obtained, we have given the benefit of doubt to the GP and categorised the general indication group as on-label (i.e. depression for quetiapine and dementia for risperidone).

We converted the PDDs for each antipsychotic to their olanzapine equivalents (Leucht et al., 2016).

Statistical analysis

Descriptive statistics were used to analyse antipsychotic utilisation data. Median and interquartile range (IQR) are reported for continuous variables. All analyses were carried out using SAS/STAT version 15.1 of the SAS system for Windows version 9.4.

We analysed incidence and prevalence rates of antipsychotic exposure across the time period. Incidence was calculated as the number of new users dispensed an antipsychotic in a year who were not using any antipsychotic agents in the previous 365 days; we do not report this for 2005 as there is no 1-year look-back period. Period prevalence was calculated as the number of patients dispensed an antipsychotic in a year. Since our dataset is the 10% sample, we then divided both incident and prevalent number of patients for each year by 10% of the estimated resident population of Australia for the respective years, obtained from the Australian Bureau of Statistics (ABS, 2022), to arrive at standardised rates expressed as rate per 1000 population. The average annual growth rate was calculated using the first and last year of dispensings. Due to a change in processing arrangements, public hospital prescriptions of clozapine were captured in PBS only from 2014, leading to an artificial increase in dispensings during this period (Pharmaceutical Benefits Scheme (PBS), 2014). Therefore, we calculated its annual growth from 2015 to 2021.

We similarly calculated the prevalence rates per 1000 population by age and sex for each year and by antipsychotic categories, and then plotted the median rate for all years in a tornado plot to illustrate differences by these characteristics.

Ethics approval

This study was approved by the University of Sydney Human Research Ethics committee (Project number 2022/445) on 1 July 2022. Deidentified patient information was provided and patient consent was not required. STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) guidelines were followed (Von Elm et al., 2008).

Results

Section A: PBS dispensing temporal trends 2005–2021

In this study period, there were 164,993 patients dispensed at least one antipsychotic prescription, of whom 48% were males and 42.8% were aged 65 years and above during a dispensing (Table 1). The median age at first dispensing of any antipsychotic was 53 years (IQR, 34–77 years). There were more than 5.6 million dispensings, and 69% of the patients had more than 1 dispensing, with a median of 6 per patient (IQR, 2–29). There were 693,562 treatment episodes, with a median of 2 episodes per patient (IQR, 1–5). The median duration of a treatment episode was 80 days (IQR, 55–212 days). There was a steady increase in antipsychotic volume in this period, with an annual growth rate of 6.6%.

Table 1.

PBS dispensing patterns by antipsychotic categories, 2005-2021

Parameter	Any AP	FGA	SGA	FGA LAI	FGA Oral	FGA SAI	SGA LAI	SGA Oral	Clozapine
Total patients, n (%)^a	164,993	53,598 (32.49)	134,905 (81.76)	4376 (2.65)	39,775 (24.11)	14,932 (9.05)	9226 (5.59)	134,119 (81.29)	2553 (1.55)
Male	79,562 (48.22)	25,829 (15.65)	65,019 (39.41)	2572 (1.56)	18,959 (11.49)	7096 (4.30)	5642 (3.42)	64,500 (39.09)	1675 (1.02)
Female	85,431 (51.78)	27,769 (16.83)	69,886 (42.36)	1804 (1.09)	20,816 (12.62)	7836 (4.75)	3584 (2.17)	69,619 (42.20)	878 (0.53)
<65^b	101,549 (61.55)	25,305 (15.34)	90,151 (54.64)	3869 (2.34)	20,962 (12.70)	2532 (1.53)	8520 (5.16)	89,454 (54.22)	2438 (1.48)
⩾65^b	70,614 (42.80)	29,516 (17.89)	50,934 (30.87)	799 (0.48)	19,719 (11.95)	12,415 (7.52)	1062 (0.64)	50,623 (30.68)	263 (0.16)
Number of dispensings, n (%)	5,613,960	467,056 (8.32)	5,146,904 (91.68)	97,545 (1.74)	348,263 (6.20)	21,248 (0.38)	378,258 (6.74)	4,467,381 (79.58)	301,265 (5.37)
Patients with >1 dispensing	113,198 (68.61)	23,794 (14.42)	101,210 (61.34)	3463 (2.10)	17,901 (10.85)	4442 (2.69)	8685 (5.26)	99,982 (60.60)	2451 (1.49)
Dispensings per patient, median (IQR)	6 (2–29)	2 (1–5)	9 (2–36)	8 (4–18)	4 (2–9)	2 (2–3)	16 (7–35)	9 (4–25)	57 (24–98)
Annual growth rate, %	6.66	–1.24	7.77	1.99	–2.67	8.84	14.73	6.72	1.7^c
Treatment episodes, n	693,562	122,598	570,964	18,700	90,325	13,573	28,094	536,137	6733
Episodes per patient, median (IQR)	2 (1–5)	2 (1–3)	2 (1–5)	3 (1–6)	2 (1–3)	1 (1–1)	3 (1–5)	2 (1–5)	2 (1–3)
Duration per episode in days, median (IQR)	80 (55–212)	67 (52–135)	89 (55–234)	135 (86–305)	67 (59–130)	18 (18–18)	129 (36–352)	86 (55–224)	281 (79–1031)

AP: antipsychotic; FGA: first-generation antipsychotics; SGA: second-generation antipsychotics; LAI: long-acting injection; SAI: short-acting injection; IQR: interquartile range.

Percentages are expressed out of the total “Any AP” category.

Numbers do not add up to the whole, since it represents age at dispensing and will change over time.

Due to a change in processing arrangements, public hospital prescriptions of clozapine were captured in PBS only from 2014, leading to an artificial increase in dispensings during this period (PBS, 2014).

Therefore, we calculated its annual growth from 2015-2021.

The majority of the dispensings (92%) were for SGAs, with 82% of the patients being dispensed an SGA at some point (Table 1). Oral formulations accounted for 91%; oral SGAs had an annual growth in dispensings of 6.7% while oral FGAs decreased by –2.7%. Median dispensings per patient were more in case of the LAI forms, with longer treatment duration per episode.

We plotted the prevalence rates per 1000 population by age and sex in a tornado plot (Figure 1) by antipsychotic categories, and dispensing differences are apparent between the different formulations. Males less than 50 years had consistently higher prevalence rates than females across all categories, with this markedly reversing over 50 years. FGAs were much more likely to be used in the elderly population.

Figure 1.

Tornado plot of prevalence by age and sex, calculated as rate per 1000 population using 10% of the Australian Bureau of Statistics population for each year.

There has been a steady increase in both the incidence and prevalence of any antipsychotic dispensing between 2005 and 2021 (Figures 2 and 3). This rise is closely reflected by the rise in SGA oral formulations, whereas FGAs had a slow decline in both incidence and prevalence.

Figure 2.

Incidence rates of antipsychotics by different categories from 2006 to 2021, calculated as rate per 1000 population using 10% of the Australian Bureau of Statistics population for each year.

Figure 3.

Prevalence rates of antipsychotics by different categories from 2005 to 2021, calculated as rate per 1000 population using 10% of the Australian Bureau of Statistics population for each year.

Overall statistics for any oral SGA and for individual drugs are given in Table 2. Oral SGAs were dispensed to 134,443 people with nearly 4.8 million scripts being filled. Nearly 75% had more than one dispensing, with a median of 2 (IQR, 1–5) treatment episodes per person and a median episode duration of 86 (IQR, 55–225) days.

Table 2.

PBS dispensing patterns for oral SGAs, 2005-2021.

Oral SGA	Total patients, n (%)^a	Sex, n (%)^$		Age, n (%)^$		Dispensings			Treatment episodes
Oral SGA	Total patients, n (%)^a	Male	Female	<65^b	⩾65^b	Total, n (%)^a	Patients with >1 dispensing, n (%)^a	Dispensings per patient, median (IQR)	Total, n (%)^a	Episodes per patient, median (IQR)	Duration per treatment episode in days, median (IQR)
Any	134,443	64,728 (48.2)	69,715 (51.9)	89,761 (66.8)	50,733 (37.7)	4,768,646	100,219 (74.5)	8 (2–33)	542,870	2 (1–5)	87 (55–229)
Amisulpride	5328 (4.0)	3022 (2.3)	2306 (1.7)	4950 (3.7)	580 (0.4)	149,493 (3.1)	3936 (2.9)	6 (2–28)	16,655 (3.1)	2 (1–4)	107 (52–269)
Aripiprazole	15,124 (11.3)	7368 (5.5)	7756 (5.8)	13,938 (10.4)	1529 (1.1)	303,257 (6.4)	10,548 (7.9)	5 (1–18)	36,296 (6.7)^c	2 (1–3)	92 (40–244)^c
Asenapine	2772 (2.0)	1078 (0.8)	1694 (1.3)	2618 (2.0)	198 (0.1)	26,425 (0.6)	1563 (1.2)	2 (1–8)	4795 (0.9)	1 (1–2)	86 (60–203)
Brexpiprazole	2017 (1.5)	964 (0.7)	1053 (0.8)	1828 (1.4)	210 (0.2)	21,391 (0.5)	1464 (1.0)	4 (2–13)	3160 (0.6)	1 (1–2)	86 (38–222)
Clozapine	2553 (1.9)	1675 (1.3)	878 (0.7)	2438 (1.8)	263 (0.2)	301,265 (6.3)	2451 (1.8)	85 (27–116)	6733 (1.2)	2 (1–3)	281 (79–1031)
Lurasidone	4480 (3.3)	1961 (1.5)	2519 (1.9)	4200 (3.1)	343 (0.3)	66,881 (1.4)	3218 (2.4)	5 (2–15)	7858 (1.4)	1 (1–2)	84 (37–219)
Olanzapine	53,436 (39.8)	27,632 (20.6)	25,804 (19.2)	40,391 (30.0)	15,329 (11.4)	1,694,786 (35.5)	39,581 (29.4)	6 (2–28)	148,300 (27.3)^c	2 (1–4)	79 (34–226)^c
Paliperidone	3905 (2.9)	2269 (1.7)	1636 (1.2)	3619 (2.7)	364 (0.3)	55,857 (1.2)	2505 (1.9)	3 (1–10)	5597 (1.0)^c	2 (1–3)	88 (36–269)^c
Quetiapine	67,907 (50.5)	31,616 (23.5)	36,291 (27.0)	54,587 (40.6)	15,504 (11.5)	1,392,858 (29.2)	44,706 (33.3)	5 (1–19)	203,780 (37.5)	2 (1–5)	81 (55–204)
Risperidone	47,642 (35.4)	22,768 (16.9)	24,874 (18.5)	19,296 (14.4)	29,346 (21.8)	705,057 (14.8)	34,136 (25.4)	5 (2–14)	104,107 (19.2)^c	2 (1–3)	111 (59–273)^c
Ziprasidone	2675 (2.0)	1129 (0.8)	1546 (1.2)	2523 (1.9)	215 (0.2)	51,376 (1.0)	1854 (1.4)	4 (1–16)	5,589 (1.0)	1 (1–3)	105 (44–263)

SGA: second-generation antipsychotic; IQR: interquartile range.

Percentages are expressed out of the total “Any” category.

Numbers do not add up to the whole, since it represents age at dispensing and changes over time.

Some treatment episodes include combined oral and LAI forms as defined in the Methods section.

The incidence and prevalence of individual oral SGAs are presented in Figures 4 and 5, respectively. Quetiapine has the steepest increase in both measures in this period, surpassing all other SGAs. The number of scripts dispensed for each oral SGA is shown in Figure 6, with similar results.

Figure 4.

Incidence rates of oral second-generation antipsychotics (SGAs) from 2006 to 2021, calculated as rate per 1000 population using 10% of the Australian Bureau of Statistics population for each year.

Figure 5.

Prevalence rates of oral second-generation antipsychotics (SGAs) from 2005 to 2021, calculated as rate per 1000 population using 10% of the Australian Bureau of Statistics population for each year.

Figure 6.

Number of dispensings of oral second-generation antipsychotics (SGAs) from 2005 to 2021.

Concerns have been raised previously about increased use of low-dose quetiapine in off-label indications, and hence, we decided to analyse quetiapine dispensing over time by dosage. As shown in Figure 7, the prevalence rates of quetiapine 25 mg are the highest among all other dosages. Stand-alone treatment with the 25 mg dosage has also not decreased significantly since 2013. Of the 67,907 people who were dispensed quetiapine at any time point, 49,956 (73.5%) were given the 25 mg dosage; 23,413 (34.5%) were dispensed 25 mg quetiapine without dose titration or in combination with another antipsychotic, with a median treatment duration of 85 days (mean, 198.5 days; IQR, 84–193).

Figure 7.

Prevalence rates of quetiapine dispensing by dosage from 2005 to 2021, calculated as rate per 1000 population using 10% of the Australian Bureau of Statistics population for each year.

We analysed in detail whether clozapine dispensing conforms to the guidelines of being prescribed for treatment-resistant schizophrenia. We found that 431 (16.9%) patients did not have previous PBS dispensings of antipsychotics before being dispensed clozapine. Furthermore, 71% of the clozapine-treated patients were simultaneously dispensed at least one other antipsychotic, with a median concurrent therapy duration of 82 (IQR, 36–236) days.

Since BEACH is based on GP–patient encounters and does not have information on prescribing by psychiatrists and other specialists, we also analysed the extent of prescribing of antipsychotics by different specialties in the 10% PBS dataset. Among the antipsychotic dispensings that had prescriber information (n = 4,865,292), 52% (n = 2,524,167) were prescribed by GPs, 17% (n = 809,349) by psychiatrists, while 31% (1,506,540) were prescribed by other specialties. Nearly 65% of the dispensings prescribed by other specialties were for olanzapine, quetiapine and risperidone; 9% were for clozapine and 10% for FGAs.

We carried out a secondary analysis on authority codes for antipsychotics in PBS from 2013 onwards; 13% dispensings were missing an authority code while 5.5% were unapproved codes (Supplemental Table 3). This prompted us to examine off-label prescribing in the BEACH dataset.

Section B: indications and respective dosages from BEACH

Between 2000 and 2016, there were 20,870 prescriptions in BEACH for drugs with the ATC code N05A** for antipsychotics, of which 10,444 prescriptions were for the antipsychotics of interest (a majority of the remaining prescriptions were for prochlorperazine). There was no data for brexpiprazole since it was approved for use in Australia in 2017. Due to their low prescription counts, we excluded ziprasidone, asenapine and lurasidone from further analyses. SGAs accounted for two-thirds of the prescriptions and the top 3 antipsychotics were again olanzapine, quetiapine and risperidone, comprising 56.7% of these prescriptions. To check comparability with the PBS data, we mapped the number of dispensings per 1000 scripts from PBS and the number of prescriptions per 1000 encounters from BEACH for each drug; similar trends were seen in the overlapping periods (Supplemental Figure 1).

Excluding prescriptions for medication renewal, care plans and unclassifiable problems (Other group) gave a total of 9821 prescriptions for which a clear indication was available. As shown in Table 3, 27% of the antipsychotic prescriptions were off-label. When measured against the total prescription count, SGAs were more likely to be prescribed off-label compared to FGAs (16.5% and 10.6%, respectively). Olanzapine, quetiapine and risperidone among SGAs and chlorpromazine and haloperidol among FGAs had increased off-label prescribing rates. Other non-psychotic psychological disorders were the prominent diagnostic group for off-label prescribing of most antipsychotics; risperidone was the exception, with higher prescribing for neurological disorders. The top off-label indications were depression, dementia, Alzheimer’s disease, substance abuse, anxiety and headache. We did not observe a significant change in off-label prescribing in BEACH over time.

Table 3.

Approval label and diagnostic groups for prescriptions in BEACH.

Antipsychotic	Number of prescriptions, n (%)^a	Off-label prescriptions,^b n (% of drug prescriptions) (% of total prescriptions)	Diagnostic groups^c
Antipsychotic	Number of prescriptions, n (%)^a		Psychosis and bipolar disorder, n (%)	Neurological, n (%)	Other psychological, n (%)	General, n (%)
Any	9821	2667 (27.2)	6464 (65.8)	981 (10.0)	2019 (20.6)	357 (3.6)
FGA	3232 (32.9)	1042 (32.2) (10.6)	2141 (66.2)	307 (9.5)	567 (17.5)	217 (6.7)
Chlorpromazine	444 (4.5)	316 (71.2) (3.2)	104 (23.4)	106 (23.9)	160 (36.0)	74 (16.7)
Flupenthixol	510 (5.2)	65 (12.8) (0.7)	476 (93.3)	7 (1.4)	22 (4.3)	5 (1.0)
Fluphenazine	627 (6.4)	31 (4.9) (0.3)	605 (96.5)	5 (0.8)	17 (2.7)	0 (0)
Haloperidol	602 (6.1)	273 (45.4) (2.8)	252 (41.9)	126 (20.9)	127 (21.1)	97 (16.1)
Pericyazine	183 (1.9)	130 (71.0) (1.3)	29 (15.8)	36 (19.7)	103 (56.3)	15 (8.2)
Thioridazine	122 (1.2)	76 (62.3) (0.8)	57 (46.7)	13 (10.7)	46 (37.7)	6 (4.9)
Trifluoperazine	199 (2.0)	92 (46.2) (0.9)	92 (46.2)	10 (5.0)	78 (39.2)	19 (9.5)
Zuclopenthixol	545 (5.5)	59 (10.8) (0.6)	526 (96.5)	4 (0.7)	14 (2.6)	1 (0.2)
SGA	6589 (67.0)	1625 (24.7) (16.5)	4323 (65.6)	674 (10.2)	1452 (22.0)	140 (2.1)
Amisulpride	168 (1.7)	45 (26.8) (0.5)	144 (85.7)	2 (1.2)	19 (11.3)	3 (1.8)
Aripiprazole	212 (2.2)	63 (29.7) (0.6)	168 (79.2)	7 (3.3)	34 (16.0)	3 (1.4)
Clozapine	473 (4.8)	30 (6.3) (0.3)	454 (96.0)	1 (0.2)	15 (3.2)	3 (0.6)
Olanzapine	2330 (23.7)	707 (30.3) (7.2)	1608 (69.0)	157 (6.7)	527 (22.6)	38 (1.6)
Paliperidone	118 (1.2)	24 (20.3) (0.2)	109 (92.4)	1 (0.8)	8 (6.8)	0 (0)
Quetiapine	1598 (16.3)	428 (26.8) (4.4)	844 (52.8)	70 (4.4)	620 (38.8)	64 (4.0)
Risperidone	1690 (17.2)	328 (19.4) (3.3)	996 (58.9)	436 (25.8)	229 (13.6)	29 (1.7)

FGA: first-generation antipsychotics; SGA: second-generation antipsychotics.

623 prescriptions were for medication renewal, care plans or unclassifiable problems; they were grouped as “Other category” and excluded from the count.

Specific to each antipsychotic and assessed from the Australian Medicines Handbook guidelines (supplementary material 2).

Not drug-specific; off-label prescriptions may overlap between all four groups.

The PDD was lower for off-label indications as a group compared to on-label indications for many oral antipsychotics (Figure 8), especially the top five commonly prescribed for off-label conditions.

Figure 8.

Box plots of prescribed daily dosages for oral antipsychotics in BEACH, grouped by on-label and off-label disorders.

Discussion

We observed increased antipsychotic utilisation in Australia from 2005 to 2021 largely due to oral SGAs, the most common being olanzapine, quetiapine and risperidone. An important finding was the sustained use of both oral and LAI FGAs in the elderly population, who have a higher risk of adverse reactions. Off-label prescribing, seen in both FGAs and SGAs, accounted for around a quarter of prescriptions and was often at lower doses.

The growing popularity of SGAs might be attributed to the RANZCP guidelines, which strongly recommend SGAs over FGAs in the treatment of psychosis and schizophrenia due to lower risk of extrapyramidal effects and possible better effects on negative symptoms (Galletly et al., 2016). The guidelines also recommend LAI SGAs for patients with poor adherence or poor response to oral forms, and this is reflected in their even higher annual growth rate. Pharmaceutical companies have also supported and encouraged increased prescribing of SGAs including for off-label indications; indeed, they have been heavily fined for such practices (McKean and Monasterio, 2012).

Nearly a third of the patients in our study were given a single dispensing of an antipsychotic at some time point, whereas the RANZCP guidelines for schizophrenia recommend continuous treatment with antipsychotics for 2–5 years in case of first-episode psychosis (FEP) (Galletly et al., 2016). Only 6% of patients experience a single FEP with good recovery (Morgan et al., 2014) and they may still require medication for an extended period of time to prevent relapse. Many of these single dispensings may reflect off-label use; indeed, we found 32% of FGA and 25% of SGA prescriptions in BEACH were for off-label disorders.

Ever since its approval, quetiapine prescribing has been on the increase internationally and in Australia (Brett et al., 2017; Hálfdánarson et al., 2017), and this is also reflected in our study, with 50% of patients who received an antipsychotic being dispensed quetiapine at some time point. Furthermore, we found 27% of the quetiapine prescriptions to be off-label in BEACH, with a median daily dosage of 62.5 mg. The Drug Utilisation Sub-Committee (DUSC, 2013) of the Pharmaceutical Benefits Advisory Committee (PBAC) reported in 2013 that the 25 mg dosage, which is not therapeutic, was increasingly being prescribed to patients as a stand-alone treatment or along with an antidepressant. The resulting regulatory restriction on 25 mg repeat dispensings in 2014 led to a transient drop in its dispensing, which was not sustained in 2015 (DUSC, 2016). Our study shows that the prevalence of this dose is at an all-time high, with significant stand-alone treatments. Although adjunctive use with an antidepressant is outside the scope of this study, further research into the 25 mg formulation of quetiapine is needed to assess its off-label use and resulting adverse effects.

Clozapine is recommended only for treatment-resistant schizophrenia after at least two 6-week trials of different antipsychotics (Winckel and Siskind, 2017) and was recently observed to have higher treatment persistence compared to other antipsychotics (Taylor et al., 2022). It had the highest treatment duration in our study, with the lowest off-label prescriptions (6.3%) among SGAs in BEACH. A concerning observation was that in contrast to the RANZCP guidelines, 17.5% of the patients treated with clozapine appeared to be antipsychotic-naive. Concomitant therapy with clozapine and another antipsychotic was also high at 65% and the median concurrent treatment duration indicates that this cannot be solely attributed to treatment switching. Treatment guidelines recommend addition of an SGA with high dopamine affinity to clozapine treatment for those patients who display continued treatment resistance, albeit with careful monitoring and regular review (Galletly et al., 2016). Other studies have raised concerns about antipsychotic polypharmacy and specifically with clozapine (Brett et al., 2021; Gisev et al., 2006; Morrato et al., 2007). We cannot determine whether there was treatment resistance in either of these datasets, but further analysis of clozapine use in Australia may be warranted.

General practitioners play a key role in providing continuing care for patients, from monitoring to maintenance therapy and management of the adverse effects. We found off-label prescribing rates in BEACH to be a little more than 1 in 4 prescriptions and generally at lower doses than for approved indications. This is in the lower range compared to the rates observed in other countries, which range from 23% to 78% (Alexander et al., 2011; Højlund et al., 2021; McKean and Monasterio, 2012). BEACH data do not include prescribing by psychiatrists and other specialties, which account for nearly half of the dispensings in PBS. Our study is also restricted to adults, and it is known that antipsychotic prescribing for affective disorders and other off-label indications is on the increase among children and adolescents (McKean and Monasterio, 2012; Tanana et al., 2022).

The unapproved or missing authority codes percentage in PBS is lower than in BEACH, though we did find a trend for increased unapproved or missing codes in lower dosages of quetiapine and risperidone, but not olanzapine (Supplemental Table 4). One possible explanation for these discordant findings could be that it is not possible to predict the use of incorrect codes by prescribers, and thus, BEACH played a crucial role in identifying off-label prescribing in our study.

Limitations

Our study has some limitations. Private dispensings, medicines dispensed to veterans under the Repatriation PBS and medicines dispensed in public hospitals are not covered in the PBS 10% dataset. Furthermore, PBS is a dispensing dataset and thus only indirectly indicates the actual consumption of medicines. EPE is used to define treatment duration, since number of days of intended medicine supply is not captured in PBS. Finally, the last 2 years of PBS data may have COVID-related perturbations in medicine dispensings for this period, though early results suggest this may not be significant (Kisely et al., 2022).

BEACH is cross-sectional and hence cannot provide information on repeat prescriptions and the progression of disease in the patient. Also, there is no information on whether the off-label prescribing was initiated by the GP or by a specialist. All general practice data including BEACH rely on the perception of GPs with regard to the indication under management, which may depend on their experience and thus have an impact on diagnostic accuracy. Furthermore, an important limitation was the lack of specific information on the disorder condition, such as treatment resistance or behavioural disturbances, for which the drug may have been prescribed; this resulted in the assumption of on-label prescriptions in some cases.

Implications and conclusion

The increasing prescribing and off-label use highlights concerns about chronic adverse effects caused by antipsychotics, which are common and affect many internal systems, with an overall increase in mortality (McKean and Monasterio, 2012; Maglione et al., 2011). Prescribers may be inclined to overlook these adverse effects when prescribing lower doses.

Our study has multiple implications for clinicians and health policymakers. First, off-label usage of antipsychotics at lower doses is seen in a significant proportion of the Australian population and may require review of current policies. Next, recommended guidelines for patient monitoring, especially for metabolic adverse effects, need to be followed for better patient outcomes. Finally, more studies are needed to understand the risk benefit, especially for long-term use in off-label indications, and lower doses where there is limited trial evidence.

Supplemental Material

sj-pdf-1-anp-10.1177_00048674231210209 – Supplemental material for On- and off-label utilisation of antipsychotics in Australia (2000–2021): Retrospective analysis of two medication datasets

Supplemental material, sj-pdf-1-anp-10.1177_00048674231210209 for On- and off-label utilisation of antipsychotics in Australia (2000–2021): Retrospective analysis of two medication datasets by Ramya Padmavathy Radha Krishnan, Christopher Harrison, Nicholas Buckley and Jacques Eugene Raubenheimer in Australian & New Zealand Journal of Psychiatry

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship and/or publication of this article.

ORCID iD

Ramya Padmavathy Radha Krishnan

Supplemental material

Supplemental material for this article is available online.

References

Alexander

Gallagher

Mascola

, et al. (2011) Increasing off-label use of antipsychotic medications in the United States, 1995-2008. Pharmacoepidemiology and Drug Safety 20: 177–184.

Australian Bureau of Statistics (ABS) (2022) Australian Bureau of Statistics: National, State and Territory Population, June 2022. Available at: www.abs.gov.au/statistics/people/population/national-state-and-territory-population/jun-2022 (accessed 16 December 2022).

Australian Medicines Handbook Pty Ltd (2021) Australian Medicines Handbook 2000-2021, 2nd–22nd Edition. Adelaide, SA, Australia: Australian Medicines Handbook Pty Ltd.

Berge

Abri

Andell

, et al. (2022) Associations between off-label low-dose olanzapine or quetiapine and cardiometabolic mortality. Journal of Psychiatric Research 149: 352–358.

Brett

Karanges

Daniels

, et al. (2017) Psychotropic medication use in Australia, 2007 to 2015: Changes in annual incidence, prevalence and treatment exposure. Australian and New Zealand Journal of Psychiatry 51: 990–999.

Brett

Pearson

Daniels

, et al. (2021) A cross sectional study of psychotropic medicine use in Australia in 2018: A focus on polypharmacy. British Journal of Clinical Pharmacology 87: 1369–1377.

Britt

(2003) BEACH – Bettering the Evaluation and Care of Health: A continuous national study of general practice activity. Communicable Diseases Intelligence Quarterly Report 27: 391–393.

Britt

Miller

(2015) BEACH program update. Australian Family Physician 44: 411–414.

Britt

Miller

Bayram

, et al. (2016) A Decade of Australian General Practice Activity 2006–07 to 2015–16. Sydney, NSW, Australia: Family Medicine Research Centre, The University of Sydney.

10.

Britt

Miller

Henderson

, et al. (2015) General Practice Activity in Australia 2014–15. Sydney, NSW, Australia: Family Medicine Research Centre, The University of Sydney.

11.

Carton

Cottencin

Lapeyre-Mestre

, et al. (2015) Off-label prescribing of antipsychotics in adults, children and elderly individuals: A systematic review of recent prescription trends. Current Pharmaceutical Design 21: 3280–3297.

12.

Cates

Jackson

Feldman

, et al. (2009) Metabolic consequences of using low-dose quetiapine for insomnia in psychiatric patients. Community Mental Health Journal 45: 251–254.

13.

Chokhawala

Stevens

(2022) Antipsychotic medications. In: StatPearls. Treasure Island, FL: StatPearls Publishing. Available at: https://www-ncbi-nlm-nih-gov.ezproxy.library.sydney.edu.au/books/NBK519503/

14.

Drug Utilisation Sub-Committee (DUSC) (2013) Antipsychotics in the middle aged, February 2013 & June 2013. Drug Utilisation Sub-Committee (DUSC) Report. Available at: www.pbs.gov.au/info/industry/listing/participants/public-release-docs/antipsychotics/antipsychotics-middle-aged-2013 (accessed 21 January 2023).

15.

Drug Utilisation Sub-Committee (DUSC) (2016) Antipsychotic medicines: 24 month review of quetiapine 25 Mg. Drug Utilisation Sub-Committee (DUSC) Report. Available at: www.pbs.gov.au/info/industry/listing/participants/public-release-docs/2016-09/antipsychotic-medicines-and-25mg-quetiapine-24-month-review-2016-09 (accessed 21 January 2023).

16.

Fernandez

McCown

Romrell

, et al. (2008) New-onset diabetes mellitus among Parkinsonian patients treated with long-term quetiapine. Drug Target Insights 3: 27–29.

17.

Galletly

Castle

Dark

, et al. (2016) Royal Australian and New Zealand College of Psychiatrists clinical practice guidelines for the management of schizophrenia and related disorders. Australian and New Zealand Journal of Psychiatry 50: 410–472.

18.

Gisev

Bell

McLachlan

, et al. (2006) Psychiatric drug use among patients of a community mental health service: Patterns and implications. Disease Management & Health Outcomes 14: 369–376.

19.

Hálfdánarson

Zoëga

Aagaard

, et al. (2017) International trends in antipsychotic use: A study in 16 countries, 2005–2014. European Neuropsychopharmacology 27: 1064–1076.

20.

Harrison

Britt

(2003) Prescriptions for antipsychotics in general practice. Medical Journal of Australia 178: 468–469.

21.

Liu

, et al. (2020) Trends in the incidence and DALYs of schizophrenia at the global, regional and national levels: Results from the Global Burden of Disease Study 2017. Epidemiology and Psychiatric Sciences 29: e91.

22.

Højlund

Andersen

, et al. (2021) Use of antipsychotics in Denmark 1997–2018: A nation-wide drug utilisation study with focus on off-label use and associated diagnoses. Epidemiology and Psychiatric Sciences 30: e28.

23.

Højlund

Pottegård

Johnsen

, et al. (2019) Trends in utilization and dosing of antipsychotic drugs in Scandinavia: Comparison of 2006 and 2016. British Journal of Clinical Pharmacology 85: 1598–1606.

24.

Karanges

Stephenson

McGregor

(2014) Longitudinal trends in the dispensing of psychotropic medications in Australia from 2009–2012: Focus on children, adolescents and prescriber specialty. Australian and New Zealand Journal of Psychiatry 48: 917–931.

25.

Kisely

Dangelo-Kemp

Taylor

, et al. (2022) The impact of COVID-19 on antipsychotic prescriptions for patients with schizophrenia in Australia. Australian and New Zealand Journal of Psychiatry 56: 642–647.

26.

Leucht

Samara

Heres

, et al. (2016) Dose equivalents for antipsychotic drugs: The DDD method. Schizophrenia Bulletin 42: S90–S94.

27.

McKean

Monasterio

(2012) Off-label use of atypical antipsychotics: Cause for concern? CNS Drugs 26: 383–390.

28.

Maglione

Maher

, et al. (2011) Off-Label Use of Atypical Antipsychotics: An Update. Rockville, MD: Agency for Healthcare Research and Quality.

29.

Morgan

McGrath

Jablensky

, et al. (2014) Psychosis prevalence and physical, metabolic and cognitive co-morbidity: Data from the second Australian national survey of psychosis. Psychological Medicine 44: 2163–2176.

30.

Morrato

Dodd

Oderda

, et al. (2007) Prevalence, utilization patterns, and predictors of antipsychotic polypharmacy: Experience in a multistate Medicaid Population, 1998–2003. Clinical Therapeutics 29: 183–195.

31.

Pearson

Pesa

Langton

, et al. (2015) Studies using Australia’s Pharmaceutical Benefits Scheme data for pharmacoepidemiological research: A systematic review of the published literature (1987-2013). Pharmacoepidemiology and Drug Safety 24: 447–455.

32.

Pharmaceutical Benefits Scheme (PBS) (2014) Australian Statistics on Medicines 2014. Available at: www.pbs.gov.au/info/statistics/asm/asm-2014 (accessed 22 December 2022).

33.

Pottegård

Hallas

(2013) Assigning exposure duration to single prescriptions by use of the waiting time distribution. Pharmacoepidemiology and Drug Safety 22: 803–809.

34.

Ray

Chung

Murray

, et al. (2009) Atypical antipsychotic drugs and the risk of sudden cardiac death. The New England Journal of Medicine 360: 225–235.

35.

Stephenson

Karanges

McGregor

(2013) Trends in the utilisation of psychotropic medications in Australia from 2000 to 2011. Australian and New Zealand Journal of Psychiatry 47: 74–87.

36.

Lai

EC-C

Yang

YHK

, et al. (2020) Incidence, prevalence and prescription patterns of antipsychotic medications use in Asia and US: A cross-nation comparison with common data model. Journal of Psychiatric Research 131: 77–84.

37.

Tanana

Harrison

Nishtala

, et al. (2022) Rates of psychotropic medicine prescribing in paediatric populations in Australian general practice from 2000-2016. European Neuropsychopharmacology 65: 68–78.

38.

Taylor

Dangelo-Kemp

Liu

, et al. (2022) Antipsychotic utilisation and persistence in Australia: A nationwide 5-year study. Australian and New Zealand Journal of Psychiatry 56: 1155–1163.

39.

Von Elm

Altman

Egger

, et al. (2008) The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. Journal of Clinical Epidemiology 61: 344–349.

40.

Winckel

Siskind

(2017) Clozapine in primary care. Australian Prescriber 40: 231–236.

Supplementary Material

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