Antipsychotic prescribing for vulnerable populations: a clinical audit at an acute Australian mental health unit at two-time points

Offenders and non-offenders with schizophrenia spectrum disorders: the crime-preventive potential of sufficient embedment in the mental healthcare and support system

Background

Suffering from schizophrenia spectrum disorder (SSD) has been well-established as a risk factor for offending. However, the majority of patients with an SSD do not show aggressive or criminal behavior. Yet, there is little research on clinical key features distinguishing offender from non-offender patients. Previous results point to poorer impulse control, higher levels of excitement, tension, and hostility, and worse overall cognitive functioning in offender populations. This study aimed to detect the most indicative distinguishing clinical features between forensic and general psychiatric patients with SSD based on the course of illness and the referenced hospitalization in order to facilitate a better understanding of the relationship between violent and non-violent offenses and SSD.

Methods

Our study population consisted of forensic psychiatric patients (FPPs) with a diagnosis of F2x (ICD-10) or 295.x (ICD-9) and a control group of general psychiatric patients (GPPs) with the same diagnosis, totaling 740 patients. Patients were evaluated regarding their medical (and, if applicable, criminal) history and the referenced psychiatric hospitalization. Supervised machine learning (ML) was used to exploratively evaluate predictor variables and their interplay and rank them in accordance with their discriminative power.

Results

Out of 194 possible predictor variables, the following 6 turned out to have the highest influence on the model: olanzapine equivalent at discharge from the referenced hospitalization, a history of antipsychotic prescription, a history of antidepressant, benzodiazepine or mood stabilizer prescription, medication compliance, outpatient treatment(s) in the past, and the necessity of compulsory measures. Out of the seven algorithms applied, gradient boosting emerged as the most suitable, with an AUC of 0.86 and a balanced accuracy of 77.5%.

Discussion

Our study aimed to identify the most influential illness-related predictors, distinguishing between FPP and GPP with SSD, thus shedding light on key differences between the two groups. To our knowledge, this is the first study to compare a homogenous sample of FPP and GPP with SSD regarding their symptom severity and course of illness using highly sophisticated statistical approaches with the possibility of evaluating the interplay of all factors at play.

Prevalence of High-dose Antipsychotic Prescribing in Schizophrenia: A Clinical Audit in a Regional Queensland Mental Health Service

Background

Antipsychotic medication is widely recognized as a critical intervention in both acute and ongoing treatments of schizophrenia. Guidelines endorse the routine practice of monotherapy with antipsychotic medication at the minimum effective dose. Despite the recommendations, high-dose antipsychotic prescribing and polytherapy appear to be common practice.

Objective

The objective of this study was to determine the prevalence of high-dose antipsychotic prescribing in adult patients with schizophrenia in a regional Queensland hospital and to know if the prescribing practices are in keeping with the international guidelines and with the local policy introduced in December 2017.

Methods

This was a cross-sectional survey/clinical audit of 358 adult patients with schizophrenia open to the service in both community and inpatient settings. The individual prescribing practices of psychiatrists were also examined.

Results

A minority (15%) were prescribed high doses (high-dose single agent and high dose by polytherapy) and 20% were prescribed polytherapy (including high dose and within normal dose range).

Conclusion

Eighty-five percent of the patients with the diagnosis of schizophrenia open to the service were prescribed antipsychotic within the dose range. In this respect, prescribing was aligned with current evidence-based guidelines.

Psychotropic medication use in people living with severe and persistent mental illness in the Australian community: a cross-sectional study

BACKGROUND

Psychotropic polypharmacy and high-dose prescribing may play a role in therapy, however, with associated risks. The aim of this study was to describe current prescribing practices and use of four psychotropic medication groups (antipsychotics, antidepressants, mood stabilisers and benzodiazepines), focusing on polypharmacy (across and within groups) and high-dose prescribing in adults experiencing severe and persistent mental illness (SPMI) in the Australian community.

METHODS

318 people taking psychotropic medication for SPMI had a medication review undertaken by a community pharmacist. Participants were recruited as part of an RCT from three Australian states/territories between September 2020-July 2021. All psychotropic medication and daily doses were recorded and reviewed for alignment with current clinical guidelines. Univariate and multiple logistic regression models investigated factors associated with antipsychotic, antidepressant, and mood stabiliser polypharmacy, and antipsychotic and antidepressant high-dose therapy. Variables included age, gender, geographic location, self- reported mental illness(es), hospital admission(s) in previous 6-months and prescriber type.

RESULTS

806 psychotropic medications were prescribed for the 318 participants. Mood stabiliser polypharmacy was recorded in 19.0% of participants prescribed mood stabilisers; antipsychotic polypharmacy in 18.4% of participants prescribed antipsychotics; antidepressant polypharmacy in 11.3% of those prescribed antidepressants; and three participants (5.1%) were prescribed two benzodiazepines concurrently. Almost 18.6% of the cohort was receiving high-dose treatment; 18 participants were prescribed high-dose antipsychotics and 39 high-dose antidepressants, with two participants prescribed both. Adjusted logistic regression for polypharmacy found male gender, psychiatrist as sole prescriber, or multiple prescribers, were associated with antipsychotic polypharmacy. The adjusted model for high-dose therapy found psychiatrist as sole prescriber was significantly associated with antipsychotic and antidepressant high-dose prescribing.

CONCLUSION

Psychotropic polypharmacy was common in this community cohort experiencing SPMI. Whilst polypharmacy is not always inappropriate, it is a complex construct with potential benefits alongside potential risks. Benefits and harms need to be balanced however this practice is not supported by clear guidance to assist health practitioners. This study highlights the important need for regular medication reviews and strengthened communication between consumers and all healthcare professionals involved in community mental health care, to support safe and effective use of psychotropic medications.

Machine-Learning for Prescription Patterns: Random Forest in the Prediction of Dose and Number of Antipsychotics Prescribed to People with Schizophrenia

Objective

We aimed to predict antipsychotic prescription patterns for people with schizophrenia using machine learning (ML) algorithms.

Methods

In a cross-sectional design, a sample of community mental health service users (SUs; n = 368) with a primary diagnosis of schizophrenia was randomly selected. Socio-demographic and clinical features, including the number, total dose, and route of administration of the antipsychotic treatment were recorded. Information about the number and the length of psychiatric hospitalization was retrieved. Ordinary Least Square (OLS) regression and ML algorithms (i.e., random forest [RF], supported vector machine, K-nearest neighborhood, and Naïve Bayes) were used to estimate the predictors of total antipsychotic dosage and prescription of antipsychotic polytherapy (APP).

Results

The strongest predictor of the total dose was APP. The number of Community Mental Health Centers (CMHC) contacts was the most important predictor of APP and, with APP omitted, of dosage. Treatment with anticholinergics predicted APP, emphasizing the strong correlation between APP and higher antipsychotic dose. RF performed better than OLS regression and the other ML algorithms in predicting both antipsychotic dose (root square mean error = 0.70, R² = 0.31) and APP (area under the receiving operator curve = 0.66, true positive rate = 0.41, and true negative rate = 0.78).

Conclusion

APP is associated with the prescription of higher total doses of antipsychotics. Frequent attenders at CMHCs, and SUs recently hospitalized are often treated with APP and higher doses of antipsychotics. Future prospective studies incorporating standardized clinical assessments for both psychopathological severity and treatment efficacy are needed to confirm these findings.

Risk factors associated with readmissions of patients with severe mental disorders under treatment with antipsychotics

BACKGROUND

The aim of this study was to assess the risk of readmission in patients with severe mental disorders, compare it between patients using different types of antipsychotics and determine risk factors for psychiatric readmission.

METHODS

Medical records of a non-concurrent cohort of 625 patients with severe mental disorders (such as psychoses and severe mood disorders) who were first discharged from January to December 2012 (entry into the cohort), with longitudinal follow-up until December 2017 constitute the sample. Descriptive statistical analysis of characteristics of study sample was performed. The risk factors for readmission were assessed using Cox regression.

RESULTS

Males represented 51.5% of the cohort, and 75.6% of the patients had no partner. Most patients (89.9%) lived with relatives, and 64.7% did not complete elementary school. Only 17.1% used more than one antipsychotic, 34.2% did not adhere to the treatment, and 13.9% discontinued the medication due to unavailability in public pharmacies. There was a need to change the antipsychotic due to the lack of therapeutic response (11.2% of the patients) and adverse reactions to the antipsychotic (5.3% of the patients). Cox regression showed that the risk of readmission was increased by 25.0% (RR, 1.25; 95% CI, 1.03-1.52) when used typical antipsychotics, compared to those who used atypical ones, and by 92.0% (RR, 1.92; 95% CI, 1.63-2.27) when patients did not adhere to maintenance treatment compared to those who adhered.

CONCLUSIONS

Use of atypical antipsychotics and adherence to treatment were associated with a lower risk of psychiatric readmissions.

Antipsychotic Polypharmacy and High-Dose Antipsychotic Regimens in the Residential Italian Forensic Psychiatric Population (REMS)

Few data exist regarding treatment with antipsychotics in forensic psychiatric patient populations with high social dangerousness. We performed a secondary analysis of 681 patients treated with at least one antipsychotic, extracted from a 1-year observational retrospective study, conducted on 730 patients treated in the Italian Residencies for Execution of Security Measures (REMS) (96.4% of the REMS population). We aimed at investigating antipsychotic polypharmacy (prescription of two or more concomitant antipsychotics) and high dose/very high-dose antipsychotics, as well as the possible factors associated with such therapeutic regimens. High dose/very high-dose antipsychotics were defined as a prescribed daily dose to WHO-defined daily dose ratio greater than 1.5 or 3.0, respectively. Binary logistic regression analysis was used in three models to test possible predictors of antipsychotic polypharmacy, high-dose antipsychotics, and very high-dose antipsychotic prescription. Antipsychotic polypharmacy resulted in n = 308 (45.2%) of the patients, n = 346 (50.8%) received high-dose antipsychotics, and n = 96 (14.1%) very high-dose antipsychotics. The multivariate analysis disclosed an association between antipsychotic polypharmacy and male gender (odds ratio (OR): 2.75 and 95% CI: 1.34–5.65), long-acting injectable (LAI) antipsychotic prescription (OR: 2.62 and 95% CI: 1.84–3.74), and aggressive behavior in REMS (OR: 1.63 and 95% CI: 1.13–2.36). High-dose antipsychotics were also associated with male gender (OR: 2.01 and 95% CI: 1.02–3.95), LAI antipsychotic prescription (OR: 2.78 and 95% CI: 1.95–3.97), and aggressive behavior in REMS (OR: 1.63 and 95% CI: 1.12–2.36). The use of antipsychotic polypharmacy and high-dose antipsychotics is frequent in the REMS population. These results might depend on regulatory and organizational aspects of the REMS system, including variability in structures, lack of a common model of care, and lack of stratified therapeutic security.

Prescription patterns in psychiatric compulsory care: polypharmacy and high-dose antipsychotics

BACKGROUND

Antipsychotic polypharmacy and prescription of high-dose antipsychotics are often used for the treatment of psychotic symptoms, especially in compulsory psychiatric care although there is lack of evidence to support this practice and related risks for patients.

AIMS

We aimed to investigate prescription patterns in patients with psychosis under compulsory psychiatric treatment in Cyprus and to identify predictors for pharmaceutic treatment patterns.

METHOD

This was a nationwide, descriptive correlational study with cross-sectional comparisons, including 482 patients with compulsory admission to hospital. Sociodemographic and clinical data were collected. Psychotic symptoms were assessed with the Positive and Negative Syndrome Scale (PANSS). Prescribed medication patterns, including use of medication pro re nata (PRN, when required), were recorded.

RESULTS

Antipsychotic polypharmacy with a PRN schema was reported in 33.2% (n = 160) of the participants. Polypharmacy without a PRN schema was reported in 5.6% (n = 27) of the participants. We found that 27.2% (n = 131) of the participants were prescribed high-dose antipsychotics without PRN included; and 39.2% (n = 189) prescribed high-dose antipsychotics with PRN included. In the logistic regression analyses, predictors for prescription of high-dose antipsychotics were male gender, positive psychiatric history, receiving state benefits and a negative history of substance use. Male gender was the only predictor for polypharmacy without a PRN schema whereas male gender, negative family psychiatric history, receiving state benefits and the total score on the positive symptoms PANSS subscale were predictors for polypharmacy with a PRN schema included.

CONCLUSIONS

A high frequency of polypharmacy and use of medication PRN beyond clinical guidelines has been reported for the first time in psychiatric compulsory care in Cyprus; revision in antipsychotic prescription is needed.

Factors predicting high-dose and combined antipsychotic prescribing in New Zealand: High-dose antipsychotic prescribing

OBJECTIVE

Guidelines recommend using antipsychotic monotherapy at the lowest effective dose, however high-dose and antipsychotic polypharmacy prescribing (APP) remain commonplace. The aim of this study was to determine the prevalence and patterns of high-dose antipsychotic prescribing and APP among mental health service users in New Zealand (NZ).

METHODS

A retrospective audit of service users discharged from inpatient (n=657), or registered with community (n=1560), mental health services at Auckland District Health Board was undertaken. Case notes were reviewed and data on demographics, antipsychotic routes and doses were collected. Outcomes measures included: frequency of total high-dose prescribing, high-dose monotherapy, APP, high-dose APP, and factors associated with these prescribing practices. Logistic regression models were used to examine the relationships between explanatory and outcome variables.

RESULTS

Of the service users prescribed an antipsychotic (n = 2217), 14% were prescribed a high-dose antipsychotic. The frequency of high-dose monotherapy, APP, and high-dose APP was 3%, 26% and 11%, respectively. Being male, Māori, on compulsory treatment, having a schizophrenia diagnosis, or being prescribed polypharmacy were associated with high-dose antipsychotics. Olanzapine was most frequently prescribed in both high dosing (55%) and APP (40%).

CONCLUSIONS

There is a high prevalence of high-dose prescribing and APP in this NZ setting.

Antipsychotic Polypharmacy and High-Dose Antipsychotics in Involuntary Patients: a Seven-Year Audit of Discharge Prescriptions in an Acute Care Unit

Antipsychotic polypharmacy (APP) is a psychopharmacological practice in which two or more antipsychotics are prescribed simultaneously. Despite the absence of evidence to support it, it is highly prevalent in clinical settings. Another recurrent practice strongly associated with APP is the prescription of high-dose antipsychotics (HDAs). Compulsory treatment is a legal means to impose treatment on an individual suffering from mental illness who refuses therapeutic intervention. Compulsory treatment has been associated with APP and HDAs and rates of both have been proposed to represent indicators of the quality of prescribing. We aimed to perform an antipsychotic prescription audit in a vulnerable psychiatric population, at the psychiatry department of a district hospital in Portugal, across 7 years. We evaluated APP and HDAs in 403 compulsorily admitted patients by reviewing their files at discharge. We used logistic regression to search for factors associated with APP and HDAs. APP was found in 70.5% of individuals, whereas HDAs were found in 51.4%. After adjustment, APP was significantly associated with male gender (Odds Ratio[OR] = 1.85 [1.04; 3.30] 95% Confidence Interval [CI]), involuntary outpatient treatment (OR = .40 [.18; .82] 95% CI), activation of the hospital social services (OR = 1.91 [1.08; 3.38] 95%CI), prescription of antidepressants (OR = .43 [.22; .82] 95%CI) and long-acting injectables (LAI) (OR = 28.29 [13.13; 60.97] 95%CI). HDAs were associated with male gender (OR = 1.76 [1.06; 2.94] 95%CI), the prescription of LAI (OR = 12.92 [6.93; 24.09] 95%CI) and oral first-generation antipsychotics (OR = 2.90 [1.51; 5.60] 95%CI).

Start low, go fast? Antipsychotic titration patterns at an inpatient psychiatric hospital

Introduction

Antipsychotics are commonly used to treat psychotic symptoms and severe mental illnesses. Treatment guidelines recommend antipsychotics be titrated quickly to therapeutic effect in the acute setting but acknowledge that determining the optimal dose is complicated by a delay between treatment initiation and therapeutic response. The purpose of this study was to evaluate antipsychotic titration patterns in an inpatient psychiatric hospital.

Methods

This study is a retrospective chart review of adult patients admitted to a teaching hospital and initiated on an antipsychotic for treatment of psychosis between January and December 2018. Patients were excluded if they had substance-induced psychosis, delirium, were prescribed >1 antipsychotic, or had no antipsychotic dose changes. The primary outcome was the average titration rate of the newly initiated antipsychotic. Secondary outcomes included differences in titration rate between involuntary and voluntary admissions and other antipsychotic characteristics.

Results

Of 149 patients included, the majority had a primary diagnosis of schizophrenia. Antipsychotics were titrated on average every 2 days regardless of admission type. Eighteen percent of patients were titrated to guideline-recommended maximum doses, and it took, on average, 3 days for patients to reach their final dose during hospitalization. Average length of stay was 9 days, and 43.6% of patients were readmitted within 1 year.

Discussion

Antipsychotics are titrated rapidly in the inpatient setting despite a lack of evidence regarding the impact of titration rate on clinical outcomes. Further studies comparing slow versus rapid titration strategies are needed to elucidate the impact of this on patient outcomes.

High-dose antipsychotic therapy and reflective prescribing: development of an online tool for rapid, easy calculation of antipsychotic total daily dose

OBJECTIVE

Safe and effective antipsychotic prescribing is a fundamental skill in psychiatric practice; however, antipsychotic medications are not without risk. These risks are increased when antipsychotics are prescribed in high doses, with or without polypharmacy. Decision-making regarding antipsychotic prescribing can be hampered by a lack of readily available or easily approachable tools for calculating and interpreting total daily doses, especially when antipsychotic polypharmacy is involved. Our objective was to create an accessible method for calculating antipsychotic total daily dosing.

METHODS

We have developed an online calculator for determining antipsychotic total daily dose using information on recommended maximum total daily dosing based on the British National Formulary.

RESULTS

This calculator is free, easy to implement and allows for users to input a large variety of possible antipsychotic dosing regimens.

CONCLUSIONS

It is hoped that this tool will allow clinicians to readily review their prescribing practice, inform decision-making and improve patient safety outcomes. Further research may be appropriate to determine the impact of this tool on these intended goals.

Is higher psychotropic medication burden associated with involuntary treatment under the Mental Health Act? A four-year Australian cohort study

BACKGROUND

Involuntary treatment for individuals who lack sufficient capacity to make informed decisions regarding treatment has been associated with increased rates of injectable antipsychotics, antipsychotic polytherapy, and/or high doses. However, little is known about non-antipsychotic psychotropic prescription, or psychotropic medication burden as a more encompassing approach for people treated involuntarily. The aim of this study was to examine the relationship between Mental Health Act (MHA) status and psychotropic polypharmacy and/or high-dose medication prescribing practices in an Australian inpatient mental health unit.

METHODS

A retrospective cohort study of 800 adults discharged from a large metropolitan Queensland mental health unit was undertaken. Data was collected for 200 individuals, discharged on at least one psychotropic medicine, at four time periods; Cohort 1 (on or before 31st January 2014), Cohort 2 (2015), Cohort 3 (2016) and Cohort 4 (2017). The number of prescribed medicines and total daily doses were recorded and reviewed for alignment with current clinical guidelines. Participant demographics and clinical characteristics were compared by individual MHA status using chi-square test for categorical variables and analysis of variance for continuous variables. Associations between MHA status and prescribing practices (psychotropic polypharmacy and/or high-dose prescribing) were assessed using bivariate and multivariate binomial logistic regression models. Age, gender, birth country, year of admission, admissions in previous 12 months, primary diagnosis, ECT/clozapine treatment, and other psychotropic medications were adjusted as covariates.

RESULTS

Regression analysis found that compared to their voluntary counterparts, individuals treated involuntarily were 2.7 times more likely to be prescribed an antipsychotic at discharge, 8.8 times more likely to be prescribed more than one antipsychotic at discharge and 1.65 times more likely to be prescribed high-dose antipsychotic treatment at discharge. The adjusted model also found that they were half as likely to be prescribed an antidepressant at discharge.

CONCLUSION

Implicit review of justifications for increased psychotropic medication burden (antipsychotic polypharmacy and high-doses) in those treated involuntarily is required to ensure clinical outcomes and overall quality of life are improved in this vulnerable group. Clearly documented medication histories, reconciliation at discharge and directions for medication management after discharge are necessary to ensure quality use of medicines.