Changes in prescribing for bipolar disorder between 2009 and 2016: national-level data linkage study in Scotland

Abstract

Background

Patients with bipolar disorder (BD) typically require long-term pharmacological treatment to prevent episodes of depression or mania. However, evidence-based guidelines are often not followed by prescribers and in some countries prescribing of lithium is in decline. Polypharmacy is also common in BD.

Aims

To employ a data linkage approach to describe and evaluate prescribing patterns in BD in Scotland between 2009 and 2016.

Method

By linking prescribing data to electronic Scottish Morbidity Records, we identified a cohort of 23,135 BD patients who were prescribed psychotropic medication between 2009 and 2016. We examined trends in the proportions of patients prescribed each of six drug categories. Random effects logistic models examined change in prescribing over the years of interest.

Results

The most common form of treatment for BD was antidepressant monotherapy (24.96%), with only 5.90% of treated patients receiving lithium monotherapy. Prescribing of antipsychotics and antiepileptics increased from 2009 to 2016 (antipsychotics: odds ratio (OR) = 1.16, 95% CI 1.15-1.18; antiepileptics: OR = 1.34, 95% CI 1.32-1.36), whereas prescribing of lithium decreased (OR = 0.83, 95% CI 0.82-0.85). Prescribing of valproate decreased from 2009-2016 in women, but increased in men (women: OR = 0.93, 95% CI 0.90-0.97; men: OR = 1.11, 95% CI 1.04-1.18).

Conclusions

Antidepressant monotherapy was the most common form of treatment in BD in Scotland and prescribing of lithium has declined between 2009 and 2016. The findings are a cause for concern and represent a gap between treatment guidelines and clinical practice

Introduction

Bipolar Disorder (BD) is a severe affective disorder characterised by episodes of depression and mania or hypomania. It affects 1-2% of the global population and is associated with a wide range of adverse mental and physical health outcomes.^1,2 Many individuals with BD require long-term medication to treat and prevent episodes and to maintain mood stability.

Current pharmacological treatment options for BD are broad and include mood stabilisers (e.g., lithium, sodium valproate), antipsychotics, antidepressants, hypnotics, anxiolytics and antiepileptics.³ Despite the availability of newer treatments, lithium is still considered the most effective treatment for reducing recurrence of episodes and since 2014 has been recommended as a first-line treatment by the National Institute of Health and Clinical Excellence (NICE).³ Prior to this, 2006 guidelines recommended lithium, valproate or olanzapine (an antipsychotic) as first-line treatments.⁴ There is also evidence that lithium has a specific anti-suicidal effect and it may be associated with fewer long-term negative physical health outcomes than other psychotropic medications.^5,6 Moreover, the risk to the foetus of intra-uterine exposure to lithium, as well as the long-term risk of renal failure in lithium-treated individuals, are both lower than previously reported.^7,8 Despite NICE recommendations, however, lithium remains under-prescribed in clinical practice. Indeed, BD has been identified as one of the areas of psychiatry with the widest gap between evidence-based treatment and clinical practice.⁹

Routine healthcare data linkage studies in several countries have identified important changes in the use of lithium over time.^10,11 Using national-level data from Denmark, Kessing and colleagues recently assessed prescription data for BD between 2000 and 2011.¹⁰ Of the four drug categories studied, lithium went from being the most common drug prescribed for BD to the least common, and was replaced by the use of atypical antipsychotics.¹⁰ Similar findings have emerged in Sweden, where lithium prescriptions for BD decreased from 2007 to 2013.¹² In partial contrast with these studies, however, an Italian study found that a drop in lithium prescriptions from 2002-2006 was followed by an increase from 2006-2010, perhaps reflecting changing attitudes among health practitioners.¹³

There has also been an increase in polypharmacy for BD in many countries.¹⁴ Although combination treatments can sometimes be indicated, ‘irrational polypharmacy’, with co-prescription of medications that are redundant, inappropriate or even harmful is well documented. Overall, polypharmacy is thought to occur in up to 85% of BD patients and has been linked to increased risk of medical comorbidities.¹⁴

It is currently unclear whether prescribing changes observed in other countries have also occurred in the UK in recent years. The excellent routine data linkage infrastructure in Scotland facilitates assessment of changes in patterns of prescribing for BD over time at a population level. Here, we used a health informatics approach to conduct a Scottish national-level assessment of prescribing patterns for BD between 2009 and 2016.

Methods

Data Sources

In Scotland, publicly funded healthcare is administered through 14 National Health Service (NHS) health boards. In each health board, records of outpatient clinic attendance, general/acute hospital admissions, and psychiatric hospital admissions have been recorded in Scottish Morbidity Records (SMR) since 1981. These SMR records contain data obtained through routine clinical encounters, including dates and duration of attendance/admission. Diagnoses are coded using International Classification of Diseases (ICD) 9^th (1981-1995) and 10^th (1995-present) revisions. Date and primary and secondary causes of death (ICD-9/ICD-10) have been recorded in the National Records of Scotland (NRS) deaths register since 1981. Since 1999, information on the date, number, strength, formulation and quantity of prescriptions dispensed in the community in Scotland has been recorded on a Prescribing Information System (PIS).¹⁵ Patient date of birth and sex are included in both SMR and PIS records, and ethnicity, marital status, and Scottish Index of Multiple Deprivation (SIMD) score are sometimes recorded by health professionals.

In Scotland the use of a unique patient identifier, the Community Health Index (CHI) number, facilitates linkage of routine health databases by the Information Services Division (ISD) of NHS Scotland. ISD provide access to linked datasets by approved researchers via the National Services Scotland National Safe Haven, and via four regional Safe Havens located within Aberdeen, Dundee, Edinburgh and Glasgow. These Safe Havens provide secure access to patients’ clinical data as well as a research platform for the collation, management, dissemination and analysis of anonymised Electronic Patient Records.

Working with the ISD, we used SMRs dating back to 1981 for hospital outpatient attendance (SMR00), general/acute hospital admission (SMR01) and psychiatric hospital admissions (SMR04) to identify a cohort of individuals in Scotland with a diagnosis of BD (ICD-10 codes F30, F31, F38.0; ICD-9 codes 296.0-296.1, 296.4-296.89). All individuals in this cohort were linked to the PIS, available from 2009-2016, to obtain information on the date and type of prescriptions received. From the PIS, data on prescriptions for lithium, valproate (both classified as ‘mood stabilisers’), antipsychotics, antiepileptics, hypnotics, anxiolytics and antidepressants were extracted, as these reflect the most common categories of medication prescribed in BD.¹⁶ In the analyses below, hypnotics and anxiolytics were collapsed into a single category, as in the BNF chapter 4.1 ‘Hypnotics and Anxiolytics’. We had a particular interest in prescribing patterns for lithium over time (the first-line treatment according to NICE guidelines) so it was examined separately. Valproate was also examined separately to ascertain any changes in its use in response to recent guidelines relating to risks associated with foetal exposure.¹⁷

Participants

A cohort of 45,276 patients with a diagnosis of BD as defined by ICD codes was identified from SMR00, SMR01 and SMR04 records. Of this cohort, 23,261 individuals, according to the PIS, received at least one prescription of any of the drug categories of interest (hypnotics/anxiolytics, antipsychotics, lithium, valproate, antidepressants or antiepileptics) between 2009 and 2016. Of these, 126 (0.5%) had ICD codes which are typically used to code bipolar disorder type II, or ‘other/unspecified’ bipolar disorders (ICD-10 F31.8; ICD-9 296.8). For greater consistency of bipolar types included, we excluded these patients in order to focus analyses on patients with ICD codes consistent with bipolar disorder type I (n = 23,135). For the current analyses, when examining each year of interest separately, individuals were excluded if their earliest SMR record of BD was during or after the year of interest, or if their year of death, if applicable, was during or before the year of interest. For some analyses, we collapsed across all years of interest: in these cases, the sample consisted of patients whose earliest SMR record of BD was before 2009, whose record of death was after 2009 or not applicable, and who received relevant prescription(s) in any year from 2009-2016.

It is not possible to ascertain reliably from the SMR/PIS data whether those individuals in the BD cohort (identified through SMRs) who did not have any PIS records of any prescriptions (of the selected categories) were still resident and/or receiving treatment in Scotland for each year of interest. Individuals without records of relevant prescriptions may have been resident in Scotland but not receiving psychotropic medication (in the categories of interest), or may no longer be registered with the Scottish NHS and are either receiving treatment elsewhere or have died elsewhere. As a result, our analyses were focussed on individuals with PIS records for the major medication categories of interest. We were unable to estimate how many individuals with BD in Scotland were unmedicated or receiving other psychotropic medications.

For the majority of analyses, we applied the inclusion criterion that an individual must have been consistently prescribed the same medication for a minimum period of 3 months in the year of interest (see ‘Medication variables’).

Medication variables

Prescriptions were coded into six categories of medications: hypnotics/anxiolytics (BNF subsection 4.1 ‘Hypnotics And Anxiolytics’); antipsychotics (BNF chapter 4.2 ‘Drugs used in psychoses and related disorders’, excluding lithium and valproate); lithium (BNF subsection 4.2.3 ‘Drugs used for mania or hypomania’, specific drug codes lithium carbonate or lithium citrate); valproate (BNF subsection 4.2.3 ‘Drugs used for mania or hypomania’, specific drug code valproic acid, or BNF chapter 4.8 ‘Antiepileptic drugs’, specific drug codes (semi)sodium valproate or valproic acid); antidepressants (BNF chapter 4.3 ‘Antidepressant drugs’) or antiepileptics (BNF chapter 4.8 ‘Antiepileptic drugs’, excluding (semi)sodium valproate and valproic acid).

For each year of interest, individuals were coded as having been prescribed a given drug category (from the categories listed above) for an estimated minimum 3-months if a) they received at least 4 prescriptions of the same drug category within a year, and b) the average interval between prescriptions was between 21 and 84 days. This interval was selected based on the estimated typical duration of chronically prescribed prescriptions of around 56 days (between 28 and 84 days):¹⁸ an 84-day window is typically considered a reliable metric of drug exposure; and a 21-day lower cut-off was selected to allow for early collection of prescriptions. Coding was not mutually exclusive: the same individual could meet the criteria for more than one drug category. In the analyses below, ‘treated’ refers to patients meeting these criteria.

We also calculated individuals’ most typical form of treatment, in the form of their modal combination of drug categories across all years of interest. We defined combinations of drug categories as those prescribed together on the same date, thus using a conservative definition of drug category polypharmacy. For prescriptions meeting the above 3-month minimum criteria, each patient’s modal combination of drug categories prescribed on the same date was defined as their modal form of treatment. This modal combination could consist of only one drug category (referred to as ‘monotherapy’, although this may comprise more than one specific drug from the same category) or multiple types (‘polypharmacy’ here referring to prescription of more than one drug category).

The modal form of treatment was also calculated separately for each year from 2009 to 2016. We applied the criterion that the modal combination of drug types must make up at least one third of the individual’s total prescriptions for a given year (distinct prescriptions counted as distinct dates on which prescriptions were received). This was to account for patients who were undergoing a change in their treatment regimen, resulting in ‘trials’ of different combinations. As an example, for an individual who received five prescriptions of lithium and an antidepressant (each time prescribed on the same date, and meeting 3-month minimum criteria) and four of lithium monotherapy within a year, the lithium/antidepressant polypharmacy would be coded as their modal drug combination for that year.

Demographic variables

The BD cohort comprised patients from all 14 NHS Scotland health boards see Table S1). Due to very small numbers of patients for three island-based health boards (Orkney, Shetland and Western Isles), these three were combined for all analyses/tables, both for ease of interpretation, and to minimise risk of identifying individual patients.

Data on marital status and ethnicity were missing for large numbers of patients, as these fields are not consistently completed at the time of clinic/hospital attendance. Two separate coding systems for marital status were employed within and between datasets. To maximise patients with available data, we recoded patients with the first, more detailed system into the second, simpler system, i.e., ‘single’, ‘married or separated’, ‘widowed’ and ‘other’ (including divorce, civil partnership). Ethnicity was recorded as ‘white’; ‘Asian’, ‘black’, or ‘mixed race/other’. Due to small numbers in some categories, we recoded ethnicity as ‘white’ and ‘other’.

Scottish Index of Multiple Deprivation (SIMD) scores provide an index of deprivation based on area-based measures of income, employment, education, housing, health, crime and geographical access.¹⁹ SIMD 2012 quintiles were used here, where 1 corresponds to the most deprived areas, and 5 to the most affluent.

Reported health board, marital status, SIMD quintile and even ethnicity in some instances changed within and/or between years. The modal value for each patient and year was therefore included in analyses conducted by year, and for tables/analyses reporting values across all years, the modal values across 2009-2016 were employed.

Using SMR00, SMR01 and SMR04 records, we identified the date and year when a diagnosis of BD first appeared in each patient’s records: this may not necessarily represent the date of first diagnosis. Date of death, where applicable, was extracted from NRS deaths records. These dates were used to exclude from analyses patients whose first record of BD was in or after a given year of interest, and/or whose year of death (if applicable) was in or before a year of interest.

Results

Most common forms of treatment

Demographic characteristics (where available) are presented for all treated BD patients in Table S1, for each (non-mutually exclusive) drug category. Table 1 presents the 10 most frequent combinations of drug types received by patients across the period of interest (2009-2016). Of the 23,135 individuals in the BD cohort, 20,796 (89.89%) met criteria for being treated for at least one year from 2009 to 2016. The most common form of treatment collapsing across all years of interest was antidepressant monotherapy (24.96%), followed by antipsychotic monotherapy (12.94%). Lithium monotherapy was the fifth most common form of treatment, with only 5.90% of treated patients receiving this as their modal treatment across the period 2009-2016.

Table 1. Ten most common forms of drug treatment among bipolar disorder cohort, 2009-2016.

Rank	Drug combination	N	%
1	Antidepressant	5,191	24.96
2	Antipsychotic	2,690	12.94
3	Hypnotic/anxiolytic	1,436	6.91
4	Antidepressant & antipsychotic	1,287	6.19
5	Lithium	1,226	5.90
6	Antiepileptic	797	3.83
7	Valproate	755	3.63
8	Antipsychotic & valproate	635	3.05
9	Antidepressant & hypnotic/anxiolytic	605	2.91
10	Antidepressant, antipsychotic & hypnotic/anxiolytic	552	2.65
Other	All other combinations	5,622	27.03
Total		20,796	100.00

N and % are for modal drug combinations per patient, across all included years, as a % of all individuals in the BD cohort who were treated* in at least one year from 2009 to 2016. *Treated refers to patients receiving at least 3 prescriptions of the relevant drug category for the year of interest, with an average yearly interval between prescriptions of the same drug class between 21 and 84 days. Combinations of > 1 drug category are determined based on prescriptions meeting the previous criteria, for combinations which are consistently prescribed on the same date. Individuals were excluded if, according to NRS deaths records they died before or during 2009.

The top ten most common forms of treatment separately for each year are displayed in Table S2. The pattern was very similar to that for all years combined, with around 30-40% of patients receiving either antidepressant monotherapy or antipsychotic monotherapy as their modal form of treatment. However, the proportion receiving antidepressant or lithium monotherapy declined gradually from 2009 to 2016.

Table S3 shows the proportion of patients receiving monotherapy (i.e., a single drug category), polypharmacy of two distinct drug categories, and polypharmacy of three or more drug categories in each year of interest. This table highlights that a slight decline in the proportion of patients receiving one or two categories of medication from 2009-2016 was countered by an overall increase in patients prescribed three categories of medication. Trends in polypharmacy were then examined separately for combinations including and not including lithium. The proportion of patients prescribed combinations including lithium fell slightly from 14.1% to 11.9%, while the proportion prescribed combinations not including lithium increased from 27.1% to 31.3%.

Trends in prescriptions of different drug categories by year

The proportion of treated patients receiving each of the six categories of medication (whether alone or in combination with other drug categories) in each year from 2009 to 2016 is displayed in Figure 1. There was a steady increase in the percentage of patients treated with antipsychotics (from 45.77% to 51.10%) and antiepileptics (from 15.20% to 23.24%), alongside a decline in the percentage receiving lithium prescriptions (from 25.98% to 21.95%). The overall percentage treated with antidepressants, hypnotics/anxiolytics and valproate remained relatively stable over time.

Figure 1.

Trends in the proportion of treated bipolar disorder (BD) patients treated with each medication category across each year from 2009-2016. Data for each year include patients whose first Scottish Morbidity Record of BD occurs before the year of interest and whose date of death (if applicable) occurs after the year of interest.

We were also interested in examining whether prescribing of valproate has declined in women of childbearing age over the 2009-2016 period, in light of guidance highlighting the risks associated with foetal exposure. Figure 2 shows an overall decline in prescriptions of valproate among women of childbearing age, whereas the proportion of men in the same age range prescribed valproate increased.

Figure 2.

Trends in the proportion of treated bipolar women of childbearing age (18-50 years) and men of the same age range treated with valproate across each year from 2009-2016. Data for each year includes patients whose first Scottish Morbidity Record of BD occurs before the year of interest and whose date of death (if applicable) occurs after the year of interest

To examine change in the odds of prescriptions of each drug category across the years of interest, adjusted for available sociodemographic characteristics, we used random effects logistic models with standard errors clustered by patient. As data on sociodemographic variables such as ethnicity and marital status was missing for large numbers of patients, the models summarised in Table 2 adjusted only for age and sex, to maximise numbers (n = 20,300). Further models additionally adjusted for SIMD score, ethnicity, marital status and health board, among the subset of patients with data on these covariates (n = 9,322), and are presented in Supplementary Table S4. Multivariable random effects logistic models were employed as we were interested in examining the influence of time-invariant sociodemographic predictors (sex, ethnicity) on binary outcomes. As patients often showed little variability in predictors and outcomes across years of interest, it was not appropriate to use patients as their own controls as in fixed effects models.²⁰

Table 2. Associations between patient age, sex and year of prescription on odds of receiving prescriptions of each medication category (n = 20,300).

	Hypnotic/anxiolytic		Antipsychotic		Lithium		Valproate		Antidepressant		Antiepileptic
	OR (95% CI)	p	OR (95% CI)	p	OR (95% CI)	p	OR (95% CI)	p	OR (95% CI)	p	OR (95% CI)	p
Age (in 2009)	1.01 (1.00, 1.01)	0.003	0.93 (0.93, 0.94)	<0.001	1.01 (1.01, 1.02)	<0.001	0.95 (0.95, 0.96)	<0.001	1.05 (1.05, 1.06)	<0.001	0.97 (0.96, 0.97)	<0.001
Sex (ref = Male)	2.73 (2.39, 3.12)	<0.001	0.59 (0.48, 0.72)	<0.001	0.59 (0.49, 0.71)	<0.001	0.36 (0.29, 0.45)	<0.001	9.21 (7.45, 11.38)	<0.001	1.78 (1.49, 2.14)	<0.001
Year	0.99 (0.98, 1.00)	0.228	1.16 (1.15, 1.18)	<0.001	0.83 (0.82, 0.85)	<0.001	1.09 (1.07, 1.12)	<0.001	1.00 (0.99, 1.01)	0.801	1.34 (1.32, 1.36)	<0.001
Sigma	4.60 (4.50, 4.71)		5.91 (5.76, 6.06)		14.88 (14.56, 15.20)		15.41 (15.13, 15.70)		5.97 (5.82, 6.13)		7.55 (7.40, 7.71)
Rho	0.87 (0.86, 0.87)		0.91 (0.91, 0.92)		0.99 (0.98, 0.99)		0.99 (0.99, 0.99)		0.92 (0.91, 0.92)		0.95 (0.94, 0.95)
LR test (rho = 0)	48,525.16	<0.001	67,937.79	<0.001	77,654.44	<0.001	60,149.17	<0.001	66,206.15	<0.001	51,812.65	<0.001

Coefficients are for random effects logit models with standard errors clustered by patient. Year tests the linear effect of advancing year from 2009 – 2016. Models are adjusted for age, sex and year (results for a model additionally adjusted for SIMD score, ethnicity, marital status and hospital board of residence are displayed in Supplementary Table S4). LR = likelihood ratio; OR = odds ratio.

The odds of being prescribed antipsychotics, valproate and antiepileptics all increased with each advancing year from 2009–2016 (Table 2), whereas the odds of treatment with lithium declined with increasing year (OR = 0.83; 95% CI 0.82-0.85). Increases in year were not reliably associated with prescriptions of antidepressants or of hypnotics/anxiolytics. In the fully adjusted models (Table S4), ORs were slightly attenuated, but the significance and direction of results were unchanged.

Overall, odds of receiving valproate increased over the years of interest in both partially and fully adjusted models (OR = 1.09; 95% CI 1.07, 1.12; OR = 1.09; 95% CI 1.06, 1.12). However, as we were interested in whether different trends were observed in women of childbearing age compared to men of a similar age, the model was repeated for valproate including a sex*year interaction term, for individuals aged 18-50 years. Among the 8,898 individuals included in this analysis (adjusted for age and sex), the interaction was significant (OR = 0.88 (95% CI 0.82-0.93), p<0.001) and so stratified analyses examined trends in women and men in the 18-50 year age range separately, adjusted for age. For men (n=3,407), each advancing year from 2009 to 2016 was associated with increased odds of being treated with valproate (OR = 1.11 (95% CI 1.04 -1.18), p=0.001) while for women of the same age range (n=5,491), each year was associated with a decrease in odds of receiving valproate (OR = 0.93 (95% CI 0.90-0.97), p<0.001).

Discussion

We sought to make use of large-scale, national level routine health data in Scotland to investigate trends in prescribing for BD between the years 2009-2016. Our findings demonstrate the feasibility of a routine data linkage approach and are of considerable clinical interest in light of treatment guidelines for BD.

It is notable that antidepressant monotherapy was the most common form of treatment across all years, occurring in almost one in four BD patients. This is an area for concern because most treatment guidelines for BD, including those from NICE in 2006 and 2014, caution against the use of antidepressants without mood stabiliser cover in BD because of the risk of mood destabilisation and the potential to precipitate hypomania or mania.^3,4 While there is evidence to suggest antidepressants alongside mood stabilisers or antipsychotics are not associated with more BD-related hospital readmissions,^21,22 heightened risk of mania in BD patients treated with antidepressants as monotherapy has been clearly documented in large samples.²²

The percentage of BD patients receiving lithium declined from 26% in 2009 to 22% in 2016, and less than 6% of BD patients were on lithium monotherapy during this time. This low use of lithium and the trend towards decreasing lithium use contrast with the most recent NICE guidelines which encourage the first-line use of lithium and indeed state that all BD patients should be informed that lithium is the most effective long-term treatment.³ Clearly, the use of lithium in BD can be complex (and not all patients will be suitable candidates) but overall these figures highlight a significant deviation between recommended treatment and clinical practice. Of note, recent data from England highlighted poor adherence to lithium monitoring guidelines by practitioners,²³ further suggesting a need to improve competencies around lithium use. In contrast to the pattern for less year-on-year lithium prescribing, we found that the odds of being prescribed antipsychotics, valproate and antiepileptics increased with each year between 2009 and 2016.

It is likely that these trends in prescribing for BD in Scotland are the result of a wide range of factors. Changes to medical training may have resulted in younger cohorts of psychiatrists being less likely to initiate lithium therapy. The pharmaceutical industry have also successfully promoted the use of alternatives. Other influences include the demise of traditional lithium clinics and the loss of Quality and Outcomes Framework incentives for lithium monitoring within primary care.²⁴

We identified high rates of polypharmacy overall. In 2016, almost 26% of treated BD patients were treated concurrently with two classes of psychotropic medications and over 17% were treated with three or more (Table S3). The proportion of patients prescribed three or more classes increased overall (from 15% to 17%) between 2009 and 2016: the increase in polypharmacy appears to be most evident in drug combinations (of at least two drug categories) not including lithium, which increased gradually from 27% to 31% of the cohort, whereas polypharmacy including lithium fell (Table S3). These trends suggest the increase in polypharmacy is linked to the declining use of lithium. Although many patients with BD will require more than one class of medication (e.g., a mood stabiliser in combination with an antipsychotic), we suggest that the trend over time for a greater proportion of patients taking multiple classes of psychotropic medications is a major concern. This is particularly relevant given the high rate of cardiometabolic comorbidity observed in BD.²⁵

Despite previously being recommended as a first-line treatment option, valproate is not currently recommended for use in women of childbearing potential due to risks associated with foetal exposure.^3,4 We found that the overall proportion of women prescribed valproate fell over time, likely reflecting better adherence to treatment guidelines and greater clinical awareness of potential risks.²⁶

An important limitation in this study is that classification of individuals into the BD cohort relied on the accuracy of the ICD code diagnoses recorded by healthcare professionals into electronic health records. Such records may be subject to administrative and diagnostic error, or early diagnoses may later be altered. A recent meta-analysis however found the positive predictive value for BD based on administrative data was moderately high, at around 75%.²⁷

A further issue is that the nature of the routine data employed does not permit identification of which patients are no longer registered with the NHS in Scotland and who may be receiving treatment or have died elsewhere. We were unable to determine the proportion of BD patients in Scotland who are not treated in each year of interest. Inconsistent recording of sociodemographic data (e.g., marital status, ethnicity) also meant that these variables might not have been adequately controlled for.

We took the conservative step of excluding from analyses the small number of patients (n=126) with ICD-9/10 codes typically considered to reflect either bipolar II subtype or ‘other/unspecified’ BD.²⁸ The findings are therefore not relevant to prescribing patterns for BDII. In cohorts with larger numbers and/or more reliable distinction of BD subtypes, it will be of interest to compare trends across subtypes, and with disorders with overlapping symptoms such as schizoaffective disorder. Importantly, BDII is more often treated with antidepressants and less often with lithium compared to BDI. Exclusion of these participants here means that the observed trends towards decline in lithium, and high use of antidepressants is unlikely to be driven by the BDII subtype. Despite these limitations, this study demonstrates the feasibility of using Scotland’s data linkage infrastructure to examine prescribing trends at a nationwide level.

Definitions of ‘treated’ and ‘polypharmacy’ vary widely between studies.¹⁴ A strength of this study is that relatively conservative criteria were used for each. Patients were defined as treated only in the presence of evidence of consistent use of a given drug category over at least 3 months; and polypharmacy of drug categories was defined using evidence of consistent prescription of multiple drug categories on the same date. These definitions mean the observed trends likely reflect patients’ established forms of treatment and are unlikely to be biased by brief ‘trials’ of medications or by transitions between medications.

In summary, this national-level analysis of ‘real-world’ prescribing highlights important deviations over time from what is considered best practice pharmacotherapy for BD. Although focused on data from NHS Scotland, this is likely to reflect practice across the UK and internationally. BD is a complex and highly morbid mood disorder but it can be managed effectively by combining medication with psychosocial approaches. Our findings suggest that most patients with BD in Scotland are missing out on optimal treatments (such as lithium) and that many are receiving treatments (such as antidepressant monotherapy) that are at best ineffective and, at worse, detrimental for long-term outcome.