Antipsychotic utilization trajectories three years after initiating or reinitiating treatment of schizophrenia: A state sequence analysis approach

Longitudinal trajectories of substance use disorder treatment use: A latent class growth analysis using a national cohort in Chile

BACKGROUND AND AIMS

Longitudinal studies have revealed that substance use treatment use is often recurrent among patients; the longitudinal patterns and characteristics of those treatment trajectories have received less attention, particularly in the global south. This study aimed to disentangle heterogeneity in treatment use among adult patients in Chile by identifying distinct treatment trajectory groups and factors associated with them.

DESIGN

National-level registry-based retrospective cohort.

SETTING AND PARTICIPANTS

Adults admitted to publicly funded substance use disorder treatment programs in Chile from November 2009 to November 2010 and followed for 9 years (n = 6266).

MEASUREMENTS

Monthly treatment use; type of treatment; ownership of the treatment center; discharge status; primary substance used; sociodemographic.

FINDINGS

A seven-class treatment trajectory solution was chosen using latent class growth analysis. We identified three trajectory groups that did not recur and had different treatment lengths: Early discontinuation (32%), Less than a year in treatment (19.7%) and Year-long episode, without recurrence (12.3%). We also identified a mixed trajectory group that had a long first treatment or two treatment episodes with a brief time between treatments: Long first treatment, or immediate recurrence (6.3%), and three recurrent treatment trajectory groups: Recurrent and decreasing (14.2%), Early discontinuation with recurrence (9.9%) and Recurrent after long between treatments period (5.7%). Inpatient or outpatient high intensity (vs. outpatient low intensity) at first entry increased the odds of being in the longer one-episode groups compared with the Early discontinuation group. Women had increased odds of belonging to all the recurrent groups. Using cocaine paste (vs. alcohol) as a primary substance decreased the odds of belonging to long one-episode groups.

CONCLUSIONS

In Chile, people in publicly funded treatment for substance use disorder show seven distinct care trajectories: three groups with different treatment lengths and no recurring episodes, a mixed group with a long first treatment or two treatment episodes with a short between-treatment-episodes period and three recurrent treatment groups.

Speech markers to predict and prevent recurrent episodes of psychosis: A narrative overview and emerging opportunities

Preventing relapse in schizophrenia improves long-term health outcomes. Repeated episodes of psychotic symptoms shape the trajectory of this illness and can be a detriment to functional recovery. Despite early intervention programs, high relapse rates persist, calling for alternative approaches in relapse prevention. Predicting imminent relapse at an individual level is critical for effective intervention. While clinical profiles are often used to foresee relapse, they lack the specificity and sensitivity needed for timely prediction. Here, we review the use of speech through Natural Language Processing (NLP) to predict a recurrent psychotic episode. Recent advancements in NLP of speech have shown the ability to detect linguistic markers related to thought disorder and other language disruptions within 2-4 weeks preceding a relapse. This approach has shown to be able to capture individual speech patterns, showing promise in its use as a prediction tool. We outline current developments in remote monitoring for psychotic relapses, discuss the challenges and limitations and present the speech-NLP based approach as an alternative to detect relapses with sufficient accuracy, construct validity and lead time to generate clinical actions towards prevention.

Evolution of the profiles of new psychotropic drug users before and during the COVID-19 crisis: an original longitudinal approach through multichannel sequence analysis using the French health-care database

The COVID-19 pandemic has had a substantial impact on mental health. An increase in the use of anxiolytic, hypnotic, and antidepressant drugs has been highlighted in France, but with no information at the individual level (trajectories) or concerning patient characteristics. The objective of this study was to describe the profile of new psychotropic drug users since the beginning of the pandemic. We formed two historical cohorts using the Pays-de-la-Loire regional component of the National Health Data System (SNDS): a "COVID-19 crisis cohort" (2020-2021) and a "control cohort" (2018-2019). We analyzed reimbursements for psychotropic medications (anxiolytics, antidepressants, hypnotics, mood stabilizers, and antipsychotics) using a multichannel sequence analysis and performed clustering analysis of sequences. The proportion of new consumers of psychotropic drugs was higher in the COVID-19 crisis cohort (18.0%) than that in the control cohort (16.0%). In the COVID-19 cohort, three clusters of psychotropic drug users were identified, whereas four clusters were identified in the control cohort. A time lag in treatment initiation was observed in the COVID-19 crisis cohort (September) compared with the control cohort (July). This study is one of the first to analyze the profile of psychotropic treatment users during the COVID-19 crisis. Our analysis sheds light on changes in patterns of psychotropic drug use during the COVID-19 pandemic, possibly associated with changes in prescribing conditions and mental health conditions during the crisis. This study also provides an example of the application of an innovative longitudinal analysis methodology in the field of pharmacoepidemiology.

Applying sequence analysis to uncover 'real-world' clinical pathways from routinely collected data: a systematic review

OBJECTIVES

This systematic review aims to elucidate the methodological practices and reporting standards associated with sequence analysis (SA) for the identification of clinical pathways in real-world scenarios, using routinely collected data.

STUDY DESIGN AND SETTING

We conducted a methodological systematic review, searching five medical and health databases: MEDLINE, PsycINFO, CINAHL, EMBASE and Web of Science. The search encompassed articles from the inception of these databases up to February 28, 2023. The search strategy comprised two distinctive sets of search terms, specifically focused on sequence analysis and clinical pathways.

RESULTS

19 studies met the eligibility criteria for this systematic review. Nearly 60% of the included studies were published in or after 2021, with a significant proportion originating from Canada (n = 7) and France (n = 5). 90% of the studies adhered to the fundamental SA steps. The optimal matching (OM) method emerged as the most frequently employed dissimilarity measure (63%), while agglomerative hierarchical clustering using Ward's linkage was the preferred clustering algorithm (53%). However, it is imperative to underline that a majority of the studies inadequately reported key methodological decisions pertaining to SA.

CONCLUSION

This review underscores the necessity for enhanced transparency in reporting both data management procedures and key methodological choices within SA processes. The development of reporting guidelines and a robust appraisal tool tailored to assess the quality of SA would be invaluable for researchers in this field.

Trajectories of Service Contact before Suicide in People with Substance Use Disorders-A National Register Study

OBJECTIVE

This study aimed to identify trajectories of service use during the last year before suicide death and the characteristics associated with the trajectories in patients with substance use disorders.

METHODS

This study used a national registry data linkage, which included all patients with substance use disorders who died by suicide in Norway between 2010 and 2018. In- and outpatient contacts with mental health or substance use services during the last year before suicide death was analyzed by week using Sequence State Analysis and cluster analysis to identify trajectories. Logistic regression was used to measure the association between the characteristics and the trajectories.

RESULTS

We identified four trajectories of service contact. A brief contact trajectory (n = 366) with a low proportion of weeks in contact (M weeks = 8.3), associated with less psychosis or bipolar disorder (aOR = 0.13 (0.08-0.22)) and higher age. A regular contact trajectory (n = 160), with a higher proportion of contact (M weeks = 47.9), associated with psychosis or bipolar disorder (aOR = 3.66 (2.10-6.47)) and depressive or anxiety disorder (aOR = 3.11 (1.93-5.13)). An intermittent contact trajectory (n = 195) with most contacts with outpatient substance use disorder services (M weeks = 9.7). A continuous contact trajectory (n = 109) with a high proportion of inpatient contact (M weeks = 44.5), strongly associated with psychosis or bipolar disorder (aOR = 6.08 (3.26-11.80)).

CONCLUSION

Longitudinal descriptions of service use reveal different trajectories that are important to consider when developing policies or interventions to reduce the risk of suicide death in patients with substance use disorders.

Discovering patterns in outpatient neurology appointments using state sequence analysis

BACKGROUND

Outpatient services in the UK, and in particular outpatient neurology services, are under considerable pressure with an ever-increasing gap between capacity and demand. To improve services, we first need to understand the current situation. This study aims to explore the patterns of appointment type seen in outpatient neurology, in order to identify potential opportunities for change.

METHODS

We use State Sequence Analysis (SSA) on routinely collected data from a single neurology outpatient clinic. SSA is an exploratory methodology which allows patterns within sequences of appointments to be discovered. We analyse sequences of appointments for the 18 months following a new appointment. Using SSA we create groups of similar appointment sequence patterns, and then analyse these clusters to determine if there are particular sequences common to different diagnostic categories.

RESULTS

Of 1315 patients 887 patients had only one appointment. Among the 428 patients who had more than one appointment a 6 monthly cycle of appointments was apparent. SSA revealed that there were 11 distinct clusters of appointment sequence patterns. Further analysis showed that there are 3 diagnosis categories which have significant influence over which cluster a patient falls into: seizure/epilepsy, movement disorders, and headache.

CONCLUSIONS

Neurology outpatient appointment sequences show great diversity, but there are some patterns which are common to specific diagnostic categories. Information about these common patterns could be used to inform the structure of future outpatient appointments.

Characterization of antipsychotic utilization before clozapine initiation for individuals with schizophrenia: an innovative visualization of trajectories using French National Health Insurance data

AIMS

Despite recommendations to initiate clozapine after two unsuccessful trials of antipsychotics, clozapine is underprescribed and initiated too late. The aim of this study was to describe different antipsychotic treatment sequences in the 36 months before the initiation of clozapine and to characterize clusters of treatment trajectories.

METHODS

Using the French National Health Insurance database, a historical cohort study of the population in an area in western France was performed. The data from all new users of clozapine with a diagnosis of schizophrenia or schizoaffective disorder in the period of 2017-2018 were evaluated. All outpatient reimbursements for antipsychotics during the 36 months before clozapine initiation were analysed. Successive reimbursements for identical treatments were grouped into treatment trials (TTs), and different trajectories were clustered using a state sequence analysis.

RESULTS

The results showed 1191 TTs for 287 individuals. The mean number of TTs per individual was 3.2. Risperidone, aripiprazole and haloperidol were the main treatments delivered. The frequencies of antipsychotics used differed between monotherapies and combination therapies. A three-cluster typology was identified: one cluster (n = 133) of 'less treated' younger individuals with fewer TTs and shorter TT durations; a second cluster (n = 53) of 'more treated' individuals with higher numbers of TTs and combinations of antipsychotics; and a third cluster (n = 103) of 'treatment-stable' older individuals with longer TT durations.

CONCLUSIONS

The results indicate that the median number of TTs during the 36 months before clozapine prescription was higher than the two recommended. The different trajectories were associated with individual characteristics and treatment differences, suggesting that additional studies of clinical parameters are needed to understand barriers to clozapine prescription.

Short communication: Prevalence of long-acting injectable antipsychotic use in Canadian early intervention services for psychosis

The use of long-acting injectable (LAI) antipsychotic drugs for psychotic disorders in Canada has been historically low compared to other jurisdictions despite advantages of LAIs in improving medication adherence and preventing relapse. In response, treatment recommendations were developed in 2013 by the Canadian Consortium for Early Intervention in Psychosis and other Canadian provincial expert groups. The impact of these guidelines needed to be assessed. To document practices in LAI use in early intervention services (EIS) for psychosis, Canadian EIS were surveyed in 2016 (n = 18) and 2020 (n = 12). Trends and descriptive information were examined using repeated cross-sectional survey data. Eight EIS responded to surveys at both time points allowing for longitudinal comparisons. Outcomes of interest included i) LAI use frequency, ii) timing of LAI starts, and iii) factors influencing LAI use. Cross-sectional analysis identified a significant increase in overall LAI usage (24.7% in 2016; 35.1% in 2020). Longitudinal analysis indicated that patients in the second program year saw the greatest increase in LAI use between 2016 and 2020 (25.6% vs. 36.1%), especially among patients under community treatment orders (65.5% vs. 81.5%). Results support increases in LAI use over time, accessibility, awareness, and increasing comfortability among Canadian clinicians.

Multidimensional analysis of adult patients’ care trajectories before a first diagnosis of schizophrenia

For patients at high-risk for developing schizophrenia, a delayed diagnosis could be affected, among many reasons, by their patterns of healthcare use. This study aims to describe and generate a typology of patients’ care trajectories (CTs) in the 2 years preceding a first diagnosis of schizophrenia, over a medico-administrative database of 3712 adults with a first diagnosis between April 2014 and March 2015 in Quebec, Canada. This study applied a multidimensional approach of State Sequence Analysis, considering together sequences of patients’ diagnoses, care settings and care providers. Five types of distinct CTs have emerged from this data-driven analysis: The type 1, shared by 77.6% of patients, predominantly younger men, shows that this group sought little healthcare, among which 17.5% had no healthcare contact for mental disorders. These individuals might benefit from improved promotion and prevention of mental healthcare at the community level. The types 2, 3 and 4, with higher occurrence of mental disorder diagnoses, represent together 19.5% of the study cohort, mostly middle-aged and women. These CTs, although displaying roughly similar profiles of mental disorders, revealed very dissimilar sequences and levels of care providers encounters, primary and specialized care use, and hospitalizations. Surprisingly, patients of these CTs had few consultations with general practitioners. An increased attentiveness for middle-aged patients and women with high healthcare use for mental disorders could help to reduce delayed diagnosis of schizophrenia. This calls for further consideration of healthcare services for severe mental illness beyond those offered to young adults.