Discharge pathways and relapse following treatment from early intervention in psychosis services

Implementing and Evaluating a National Integrated Digital Registry and Clinical Decision Support System in Early Intervention in Psychosis Services (Early Psychosis Informatics Into Care): Co-Designed Protocol

BACKGROUND

Early intervention in psychosis (EIP) services are nationally mandated in England to provide multidisciplinary care to people experiencing first-episode psychosis, which disproportionately affects deprived and ethnic minority youth. Quality of service provision varies by region, and people from historically underserved populations have unequal access. In other disease areas, including stroke and dementia, national digital registries coupled with clinical decision support systems (CDSSs) have revolutionized the delivery of equitable, evidence-based interventions to transform patient outcomes and reduce population-level disparities in care. Given psychosis is ranked the third most burdensome mental health condition by the World Health Organization, it is essential that we achieve the same parity of health improvements.

OBJECTIVE

This paper reports the protocol for the program development phase of this study, in which we aimed to co-design and produce an evidence-based, stakeholder-informed framework for the building, implementation, piloting, and evaluation of a national integrated digital registry and CDSS for psychosis, known as EPICare (Early Psychosis Informatics into Care).

METHODS

We conducted 3 concurrent work packages, with reciprocal knowledge exchange between each. In work package 1, using a participatory co-design framework, key stakeholders (clinicians, academics, policy makers, and patient and public contributors) engaged in 4 workshops to review, refine, and identify a core set of essential and desirable measures and features of the EPICare registry and CDSS. Using a modified Delphi approach, we then developed a consensus of data priorities. In work package 2, we collaborated with National Health Service (NHS) informatics teams to identify relevant data currently captured in electronic health records, understand data retrieval methods, and design the software architecture and data model to inform future implementation. In work package 3, observations of stakeholder workshops and individual interviews with representative stakeholders (n=10) were subject to interpretative qualitative analysis, guided by normalization process theory, to identify factors likely to influence the adoption and implementation of EPICare into routine practice.

RESULTS

Stage 1 of the EPICare study took place between December 2021 and September 2022. The next steps include stage 2 building, piloting, implementation, and evaluation of EPICare in 5 demonstrator NHS Trusts serving underserved and diverse populations with substantial need for EIP care in England. If successful, this will be followed by stage 3, in which we will seek NHS adoption of EPICare for rollout to all EIP services in England.

CONCLUSIONS

By establishing a multistakeholder network and engaging them in an iterative co-design process, we have identified essential and desirable elements of the EPICare registry and CDSS; proactively identified and minimized potential challenges and barriers to uptake and implementation; and addressed key questions related to informatics architecture, infrastructure, governance, and integration in diverse NHS Trusts, enabling us to proceed with the building, piloting, implementation, and evaluation of EPICare.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/50177.

Using Electronic Health Records to Facilitate Precision Psychiatry

The use of clinical prediction models to produce individualized risk estimates can facilitate the implementation of precision psychiatry. As a source of data from large, clinically representative patient samples, electronic health records (EHRs) provide a platform to develop and validate clinical prediction models, as well as potentially implement them in routine clinical care. The current review describes promising use cases for the application of precision psychiatry to EHR data and considers their performance in terms of discrimination (ability to separate individuals with and without the outcome) and calibration (extent to which predicted risk estimates correspond to observed outcomes), as well as their potential clinical utility (weighing benefits and costs associated with the model compared to different approaches across different assumptions of the number needed to test). We review 4 externally validated clinical prediction models designed to predict psychosis onset, psychotic relapse, cardiometabolic morbidity, and suicide risk. We then discuss the prospects for clinically implementing these models and the potential added value of integrating data from evidence syntheses, standardized psychometric assessments, and biological data into EHRs. Clinical prediction models can utilize routinely collected EHR data in an innovative way, representing a unique opportunity to inform real-world clinical decision making. Combining data from other sources (e.g., meta-analyses) or enhancing EHR data with information from research studies (clinical and biomarker data) may enhance our abilities to improve the performance of clinical prediction models.

Predictors of relapse and engagement in care one year after ending services in an urban safety net coordinated specialty care program for first episode psychosis

OBJECTIVE

This study aimed to identify risk factors for relapse (psychiatric emergency department visits or hospitalization) and lack of follow-up with outpatient psychiatric care in the 12 months after ending services in an urban safety net coordinated specialty care (CSC) program for first episode psychosis (FEP).

METHODS

The study population (n = 143) were individuals with FEP who had any CSC care between 2014 and 2021. To identify risk factors for relapse and follow up after exit, multivariable logistic regression was performed using data from electronic health records and linked insurance claims data.

RESULTS

Individuals with any emergency department visit or hospitalization 12 months prior to ending CSC (aOR = 4.69, 95 % CI 1.78-12.34) and those who were using cannabis at last CSC contact (aOR = 4.06, 95 % CI 1.56-10.56) had a higher risk of relapse after ending CSC services. Cannabis use at last contact was also associated with lower rates of outpatient psychiatric follow-up (aOR = 0.32, 95 % CI 0.12-0.94), while CSC duration in months had a small positive association with post-CSC psychiatric follow-up. There were no differences in relapse or follow-up by race or ethnicity, primary diagnosis, or medication usage.

CONCLUSIONS

Prior relapse during CSC predicted relapse in the 12 months after ending CSC services, but not outpatient follow up. Cannabis use predicted both a higher rate of relapse and a lower rate of follow up after ending services. There were no differences by race or ethnicity in our sample, suggesting that once individuals engaged in FEP care there were no evident disparities in the observed outcomes.

What happens after early intervention? Mapping early intervention in psychosis care pathways in the 12 months after discharge

AIM

Early intervention services are the established and evidence-based treatment option for individuals with first-episode psychosis. They are time-limited, and care pathways following discharge from these services have had little investigation. We aimed to map care pathways at the end of early intervention treatment to determine common trajectories of care.

METHODS

We collected health record data for all individuals treated by early intervention teams in two NHS mental health trusts in England. We collected data on individuals' primary mental healthcare provider for 52 weeks after the end of their treatment and calculated common trajectories of care using sequence analysis.

RESULTS

We identified 2224 eligible individuals. For those discharged to primary care we identified four common trajectories: Stable primary care, relapse and return to CMHT, relapse and return to EIP, and discontinuity of care. We also identified four trajectories for those transferred to alternative secondary mental healthcare: Stable secondary care, relapsing secondary care, long-term inpatient and discharged early. The long-term inpatient trajectory (1% of sample) accounted for 29% of all inpatient days in the year follow-up, with relapsing secondary care (2% of sample and 21% of inpatient days), and Relapse and return to CMHT (5% of sample, 15% of inpatient days) the second and third most frequent.

CONCLUSIONS

Individuals have common care pathways at the end of early intervention in psychosis treatment. Understanding common individual and service features that lead to poor care pathways could improve care and reduce hospital use.

Discharge destinations for young people with a first episode of psychosis after attending an early intervention for psychosis service

OBJECTIVE

Early intervention for psychosis services result in superior outcomes in the domains of symptomatic and functional recovery, hospitalisation and employment compared to standard services; however, the optimal duration of care with these services is unknown. Knowledge on the discharge destinations, specifically the proportion discharged to high- and low-intensity services, could provide insights into the proportion of who may require a longer tenure of care. This study aimed to determine (1) the discharge destinations from early intervention for psychosis services and (2) baseline and intra-episode factors associated with discharge to the secondary care/adult mental health service.

METHODOLOGY

This study was conducted at the Early Psychosis Prevention and Intervention Centre in Melbourne and included all young people treated by the service with a first episode of psychosis over a 6-year period. Discharge destinations were categorised according to high-intensity services, namely, secondary mental health care, or lower intensity services, such as private practitioners or primary care.

RESULTS

A total of 1101 young people with a first episode of psychosis were included in the study, of whom 58.8% were male and the median age was 20.0 years (interquartile range: 17-22). After a median of 95.4 weeks (interquartile range: 66.7-105.7), 36.6% were discharged to the adult mental health services, which was associated with being not in employment, education or training at presentation (odds ratio = 1.71, 95% confidence interval [1.23, 2.37]); experiencing a relapse (odds ratio = 1.76, 95% confidence interval [1.24, 2.49]); and being admitted to a mental health unit (odds ratio = 3.98, 95% confidence interval [2.61, 6.09]). Young people who lived with their parents were less likely to be discharged to secondary care services (odds ratio = 0.52, 95% confidence interval [0.37, 0.73]), as were those who were achieving symptomatic remission within 12 weeks (odds ratio = 0.60, 95% confidence interval [0.43, 0.83]). Migrant status and the duration of untreated psychosis were not associated with discharge destination.

CONCLUSION

These findings indicate that there is a sizable, identifiable minority who may benefit from a longer episode of care with early intervention for psychosis services.

Five-year illness trajectories across racial groups in the UK following a first episode psychosis

PURPOSE

Psychosis disproportionally affects ethnic minority groups in high-income countries, yet evidence of disparities in outcomes following intensive early intervention service (EIS) for First Episode Psychosis (FEP) is less conclusive. We investigated 5-year clinical and social outcomes of young people with FEP from different racial groups following EIS care.

METHOD

Data were analysed from the UK-wide NIHR SUPEREDEN study. The sample at baseline (n = 978) included White (n = 750), Black (n = 71), and Asian (n = 157) individuals, assessed during the 3 years of EIS, and up to 2 years post-discharge (n = 296; Black [n = 23]; Asian [n = 52] and White [n = 221]). Outcome trajectories were modelled for psychosis symptoms (positive, negative, and general), functioning, and depression, using linear mixed effect models (with random intercept and slopes), whilst controlling for social deprivation. Discharge service was also explored across racial groups, 2 years following EIS.

RESULTS

Variation in linear growth over time was accounted for by racial group status for psychosis symptoms-positive (95% CI [0.679, 1.235]), negative (95% CI [0.315, 0.783]), and general (95% CI [1.961, 3.428])-as well as for functioning (95% CI [11.212, 17.677]) and depressive symptoms (95% CI [0.261, 0.648]). Social deprivation contributed to this variance. Black individuals experienced greater levels of deprivation (p < 0.001, 95% CI [0.187, 0.624]). Finally, there was a greater likelihood for Asian (OR = 3.04; 95% CI [2.050, 4.498]) and Black individuals (OR = 2.47; 95% CI [1.354, 4.520]) to remain in secondary care by follow-up.

CONCLUSION

Findings suggest variations in long-term clinical and social outcomes following EIS across racial groups; social deprivation contributed to this variance. Black and Asian individuals appear to make less improvement in long-term recovery and are less likely to be discharged from mental health services. Replication is needed in large, complete data, to fully understand disparities and blind spots to care.

Neglecting the care of people with schizophrenia: here we go again

Specialist early intervention teams consider clinician-patient engagement and continuity of care to be a driving philosophy behind the treatment they provide to people who have developed schizophrenia or a related psychotic illness. In almost all countries where this service model has been implemented there is a dearth of available data about what is happening to patients following time-limited treatment. Information on discharge pathways in England indicates that some early intervention specialists are discharging most of their patients from all psychiatric services after only 2 or 3 years of input. Some ex-patients will be living in a state of torment and neglect due to an untreated psychosis. In the UK, general practitioners should refuse to accept these discharge pathways for patients with insight-impairing mental illnesses.

What happens after early intervention in first-episode psychosis? Limitations of existing service models and an agenda for the future

PURPOSE OF REVIEW

Early intervention in first-episode psychosis (FEP) improves symptomatic and functional outcomes while programs last. However, these gains may not be sustained over time and not all individuals benefit equally from such programs. This review examines the efficacy of FEP programs, as well as step-down practices and long-term outcomes to identify ways to extend the gains made in FEP programs.

RECENT FINDINGS

FEP programs improve outcomes while services last, but effects diminish over time. Step-down and discharge practices vary widely with little randomized evidence guiding practice. Extending the duration of FEP programs for all does not consistently improve outcomes, but there is some encouraging evidence that targeted psychosocial interventions after program end may extend symptomatic and functional benefits. Members of marginalized groups and individuals with poorer outcomes during the FEP period may benefit from further specialized intervention after FEP.

SUMMARY

Step down practices from FEP programs should be structured and tailored to individual needs, and benefit from sustained connections to community resources. Psychosocial interventions like social skills training, peer support, and supported education and employment may help extend the benefit of FEP programs after more intensive services end.

Psychosis Relapse Prediction Leveraging Electronic Health Records Data and Natural Language Processing Enrichment Methods

BACKGROUND

Identifying patients at a high risk of psychosis relapse is crucial for early interventions. A relevant psychiatric clinical context is often recorded in clinical notes; however, the utilization of unstructured data remains limited. This study aimed to develop psychosis-relapse prediction models using various types of clinical notes and structured data.

METHODS

Clinical data were extracted from the electronic health records of the Ajou University Medical Center in South Korea. The study population included patients with psychotic disorders, and outcome was psychosis relapse within 1 year. Using only structured data, we developed an initial prediction model, then three natural language processing (NLP)-enriched models using three types of clinical notes (psychological tests, admission notes, and initial nursing assessment) and one complete model. Latent Dirichlet Allocation was used to cluster the clinical context into similar topics. All models applied the least absolute shrinkage and selection operator logistic regression algorithm. We also performed an external validation using another hospital database.

RESULTS

A total of 330 patients were included, and 62 (18.8%) experienced psychosis relapse. Six predictors were used in the initial model and 10 additional topics from Latent Dirichlet Allocation processing were added in the enriched models. The model derived from all notes showed the highest value of the area under the receiver operating characteristic (AUROC = 0.946) in the internal validation, followed by models based on the psychological test notes, admission notes, initial nursing assessments, and structured data only (0.902, 0.855, 0.798, and 0.784, respectively). The external validation was performed using only the initial nursing assessment note, and the AUROC was 0.616.

CONCLUSIONS

We developed prediction models for psychosis relapse using the NLP-enrichment method. Models using clinical notes were more effective than models using only structured data, suggesting the importance of unstructured data in psychosis prediction.

Taking the next step: Improving care transitions from a first-episode psychosis service

AIMS

First-episode services (FES) improve outcomes in recent onset psychosis, but there is growing concern about how patients fare after discharge from these time-limited services.

METHODS

A quality improvement approach (QI) was used to improve patient engagement in the discharge planning process (disposition), and successful engagement in care 3 months after discharge from the FES (transfer). Data from 144 consecutive discharges over 62 months are presented. A planning phase was followed by recurrent Plan-Do-Study-Act cycles (PDSA) that included the introduction of proactive efforts targeting disposition planning (with patients and families) and follow-up to facilitate transfer after discharge. Fisher's exact test was used to compare disposition and transfer outcomes across the QI phases.

RESULTS

This QI approach was sustained through a three-fold escalation in discharge volume. Transfer status at 3 months was significantly different between the pre- and post PDSA phases (p = .02). A greater proportion were confirmed transfers post-PDSA (54.3 vs. 37%), but of those with known status at 3 months, similar proportions were successfully transferred (76, 73%). Patients discharged post-PDSA were less likely to have unknown treatment status (26 vs. 51%). Disposition outcomes were also significantly improved post-PDSA (p = .03). Patients were more likely to engage with discharge planning (69.7 vs. 48.6%) and less likely to be lost to follow-up (13.8 vs. 25.7%), or to refuse assistance (11.0 vs. 20.0%).

CONCLUSION

This QI approach offers a feasible way to improve disposition and transfer after FES and can be built upon in efforts to sustain functional gains in onward pathways.

Profiles and trajectories of mental health service utilisation during early intervention in psychosis

BACKGROUND

Early intervention in psychosis services (EIS) support individuals experiencing a first episode of psychosis. Support required will vary in response to the remittance and reoccurrence of symptoms, including relapses. Characterising individuals who will need more intensive support can inform care planning. This study explores service utilisation profiles and their trajectories of service use in a sample of individuals referred to EIS.

METHOD

We analysed service utilisation during the 3 years following referral to EIS (n = 2363) in West London between 2011 and 2020. Mental health service utilisation data were submitted to model-based clustering. Latent growth models were then estimated for identified profiles. Profiles were compared regarding clinical and demographic characteristics and onward pathways of care.

RESULTS

Analyses revealed 5 profiles of individuals attending EIS based on their service utilisation over 3 years. 55.5% of the sample were members of a low utilisation and less clinically severe profile. The distinct service use patterns of these profiles were associated with Health of the Nations Outcome Scale scores at treatment initiation (at total, subscale, and individual item level), along with age and gender. These patterns of use were also associated with onward care and ethnicity.

CONCLUSIONS

Profiles and trajectories of service utilisation call for development of integrated care pathways and use of more personalised interventions. Services should consider patient symptoms and characteristics when making clinical decisions informing the provision of care. The profiles represent typical patterns of service use, and identifying factors associated with these subgroups might help optimise EIS support.

Development and external validation of an admission risk prediction model after treatment from early intervention in psychosis services

Early Intervention in psychosis (EIP) teams are the gold standard treatment for first-episode psychosis (FEP). EIP is time-limited and clinicians are required to make difficult aftercare decisions that require weighing up individuals' wishes for treatment, risk of relapse, and health service capacity. Reliable decision-making tools could assist with appropriate resource allocation and better care. We aimed to develop and externally validate a readmission risk tool for application at the point of EIP discharge. All persons from EIP caseloads in two NHS Trusts were eligible for the study. We excluded those who moved out of the area or were only seen for assessment. We developed a model to predict the risk of hospital admission within a year of ending EIP treatment in one Trust and externally validated it in another. There were n = 831 participants in the development dataset and n = 1393 in the external validation dataset, with 79 (9.5%) and 162 (11.6%) admissions to inpatient hospital, respectively. Discrimination was AUC = 0.76 (95% CI 0.75; 0.77) in the development dataset and AUC = 0.70 (95% CI 0.66; 0.75) in the external dataset. Calibration plots in external validation suggested an underestimation of risk in the lower predicted probabilities and slight overestimation at predicted probabilities in the 0.1-0.2 range (calibration slope = 0.86, 95% CI 0.68; 1.05). Recalibration improved performance at lower predicted probabilities but underestimated risk at the highest range of predicted probabilities (calibration slope = 1.00, 95% CI 0.79; 1.21). We showed that a tool for predicting admission risk using routine data has good performance and could assist clinical decision-making. Refinement of the model, testing its implementation and further external validation are needed.

Specialised early intervention teams (extended time) for recent-onset psychosis

BACKGROUND

Psychosis is an illness characterised by the presence of hallucinations and delusions that can cause distress or a marked change in an individual's behaviour (e.g. social withdrawal, flat or blunted effect). A first episode of psychosis (FEP) is the first time someone experiences these symptoms that can occur at any age, but the condition is most common in late adolescence and early adulthood. This review is concerned with FEP and the early stages of a psychosis, referred to throughout this review as 'recent-onset psychosis.' Specialised early intervention (SEI) teams are community mental health teams that specifically treat people who are experiencing, or have experienced, a recent-onset psychosis. SEI teams provide a range of treatments including medication, psychotherapy, psychoeducation, educational and employment support, augmented by assertive contact with the service user and small caseloads. Treatment is time limited, usually offered for two to three years, after which service users are either discharged to primary care or transferred to a standard adult community mental health team. Evidence suggests that once SEI treatment ends, improvements may not be sustained, bringing uncertainty about the optimal duration of SEI to ensure the best long-term outcomes. Extending SEI has been proposed as a way of providing continued intensive treatment and continuity of care, of usually up to five years, in order to a) sustain the positive initial outcomes of SEI; and b) improve the long-term trajectory of the illness.

OBJECTIVES

To compare extended SEI teams with treatment as usual (TAU) for people with recent-onset psychosis. To compare extended SEI teams with standard SEI teams followed by TAU (standard SEI + TAU) for people with recent-onset psychosis.

SEARCH METHODS

On 3 October 2018 and 22 October 2019, we searched Cochrane Schizophrenia's study-based register of trials, including registries of clinical trials.

SELECTION CRITERIA

We selected all randomised controlled trials (RCTs) comparing extended SEI with TAU for people with recent-onset psychosis and all RCTs comparing extended SEI with standard SEI + TAU for people with recent-onset psychosis. We entered trials meeting these criteria and reporting usable data as included studies.

DATA COLLECTION AND ANALYSIS

We independently inspected citations, selected studies, extracted data and appraised study quality. For binary outcomes we calculated the risk ratios (RRs) and their 95% confidence intervals (CIs). For continuous outcomes we calculated the mean difference (MD) and their 95% CIs, or if assessment measures differed for the same construct, we calculated the standardised mean difference (SMD) with 95% CIs. We assessed risk of bias for included studies and created a 'Summary of findings' table using the GRADE approach.

MAIN RESULTS

We included three RCTs, with a total 780 participants, aged 16 to 35 years. All participants met the criteria for schizophrenia spectrum disorders or affective psychoses. No trials compared extended SEI with TAU. All three trials randomly allocated people approximately two years into standard SEI to either extended SEI or standard SEI + TAU. The certainty of evidence for outcomes varied from low to very low. Our primary outcomes were recovery and disengagement from mental health services. No trials reported on recovery, and we used remission as a proxy. Three trials reported on remission, with the point estimate suggesting a 13% increase in remission in favour of extended SEI, but this included wide confidence intervals (CIs) and a very uncertain estimate of no benefit (RR 1.13, 95% CI 0.97 to 1.31; 3 trials, 780 participants; very low-certainty evidence). Two trials provided data on disengagement from services with evidence that extended SEI care may result in fewer disengagements from mental health treatment (15%) in comparison to standard SEI + TAU (34%) (RR 0.45, 95% CI 0.27 to 0.75; 2 trials, 380 participants; low-certainty evidence). There may be no evidence of a difference in rates of psychiatric hospital admission (RR 1.55, 95% CI 0.68 to 3.52; 1 trial, 160 participants; low-certainty evidence), or the number of days spent in a psychiatric hospital (MD -2.70, 95% CI -8.30 to 2.90; 1 trial, 400 participants; low-certainty evidence). One trial found uncertain evidence regarding lower global psychotic symptoms in extended SEI in comparison to standard SEI + TAU (MD -1.90, 95% CI -3.28 to -0.52; 1 trial, 156 participants; very low-certainty evidence). It was uncertain whether the use of extended SEI over standard SEI + TAU resulted in fewer deaths due to all-cause mortality, as so few deaths were recorded in trials (RR 0.38, 95% CI 0.09 to 1.64; 3 trials, 780 participants; low-certainty evidence). Very uncertain evidence suggests that using extended SEI instead of standard SEI + TAU may not improve global functioning (SMD 0.23, 95% CI -0.29 to 0.76; 2 trials, 560 participants; very low-certainty evidence). There was low risk of bias in all three trials for random sequence generation, allocation concealment and other biases. All three trials had high risk of bias for blinding of participants and personnel due to the nature of the intervention. For the risk of bias for blinding of outcome assessments and incomplete outcome data there was at least one trial with high or unclear risk of bias.

AUTHORS' CONCLUSIONS

There may be preliminary evidence of benefit from extending SEI team care for treating people experiencing psychosis, with fewer people disengaging from mental health services. Evidence regarding other outcomes was uncertain. The certainty of evidence for the measured outcomes was low or very low. Further, suitably powered studies that use a consistent approach to outcome selection are needed, but with only one further ongoing trial, there is unlikely to be any definitive conclusion for the effectiveness of extended SEI for at least the next few years.

Smartphone-delivered self-management for first-episode psychosis: the ARIES feasibility randomised controlled trial

OBJECTIVES

To test the feasibility and acceptability of a randomised controlled trial (RCT) to evaluate a Smartphone-based self-management tool in Early Intervention in Psychosis (EIP) services.

DESIGN

A two-arm unblinded feasibility RCT.

SETTING

Six NHS EIP services in England.

PARTICIPANTS

Adults using EIP services who own an Android Smartphone. Participants were recruited until the recruitment target was met (n=40).

INTERVENTIONS

Participants were randomised with a 1:1 allocation to one of two conditions: (1) treatment as usual from EIP services (TAU) or (2) TAU plus access to My Journey 3 on their own Smartphone. My Journey 3 features a range of self-management components including access to digital recovery and relapse prevention plans, medication tracking and symptom monitoring. My Journey 3 use was at the users' discretion and was supported by EIP service clinicians. Participants had access for a median of 38.1 weeks.

PRIMARY AND SECONDARY OUTCOME MEASURES

Feasibility outcomes included recruitment, follow-up rates and intervention engagement. Participant data on mental health outcomes were collected from clinical records and from research assessments at baseline, 4 months and 12 months.

RESULTS

83% and 75% of participants were retained in the trial at the 4-month and 12-month assessments. All treatment group participants had access to My Journey 3 during the trial, but technical difficulties caused delays in ensuring timely access to the intervention. The median number of My Journey 3 uses was 16.5 (IQR 8.5 to 23) and median total minutes spent using My Journey 3 was 26.8 (IQR 18.3 to 57.3). No serious adverse events were reported.

CONCLUSIONS

Recruitment and retention were feasible. Within a trial context, My Journey 3 could be successfully delivered to adults using EIP services, but with relatively low usage rates. Further evaluation of the intervention in a larger trial may be warranted, but should include attention to implementation.

TRIAL REGISTRATION

ISRCTN10004994.

Early Signs Monitoring to Prevent Relapse in Psychosis and Promote Well-Being, Engagement, and Recovery: Protocol for a Feasibility Cluster Randomized Controlled Trial Harnessing Mobile Phone Technology Blended With Peer Support

Background

Relapse in schizophrenia is a major cause of distress and disability and is predicted by changes in symptoms such as anxiety, depression, and suspiciousness (early warning signs [EWSs]). These can be used as the basis for timely interventions to prevent relapse. However, there is considerable uncertainty regarding the implementation of EWS interventions.

Objective

This study was designed to establish the feasibility of conducting a definitive cluster randomized controlled trial comparing Early signs Monitoring to Prevent relapse in psychosis and prOmote Well-being, Engagement, and Recovery (EMPOWER) against treatment as usual (TAU). Our primary outcomes are establishing parameters of feasibility, acceptability, usability, safety, and outcome signals of a digital health intervention as an adjunct to usual care that is deliverable in the UK National Health Service and Australian community mental health service (CMHS) settings. We will assess the feasibility of candidate primary outcomes, candidate secondary outcomes, and candidate mechanisms for a definitive trial.

Methods

We will randomize CMHSs to EMPOWER or TAU. We aim to recruit up to 120 service user participants from 8 CMHSs and follow them for 12 months. Eligible service users will (1) be aged 16 years and above, (2) be in contact with local CMHSs, (3) have either been admitted to a psychiatric inpatient service or received crisis intervention at least once in the previous 2 years for a relapse, and (4) have an International Classification of Diseases-10 diagnosis of a schizophrenia-related disorder. Service users will also be invited to nominate a carer to participate. We will identify the feasibility of the main trial in terms of recruitment and retention to the study and the acceptability, usability, safety, and outcome signals of the EMPOWER intervention. EMPOWER is a mobile phone app that enables the monitoring of well-being and possible EWSs of relapse on a daily basis. An algorithm calculates changes in well-being based on participants’ own baseline to enable tailoring of well-being messaging and clinical triage of possible EWSs. Use of the app is blended with ongoing peer support.

Results

Recruitment to the trial began September 2018, and follow-up of participants was completed in July 2019. Data collection is continuing. The database was locked in July 2019, followed by analysis and disclosing of group allocation.

Conclusions

The knowledge gained from the study will inform the design of a definitive trial including finalizing the delivery of our digital health intervention, sample size estimation, methods to ensure successful identification, consent, randomization, and follow-up of participants, and the primary and secondary outcomes. The trial will also inform the final health economic model to be applied in the main trial.

Trial Registration

International Standard Randomized Controlled Trial Number (ISRCTN): 99559262; http://isrctn.com/ISRCTN99559262

International Registered Report Identifier (IRRID)

DERR1-10.2196/15058

The association between community and service level factors and rates of disengagement in individuals with first episode psychosis

INTRODUCTION

Individuals who experience a first episode of psychosis require early intervention and regular follow-up in order to improve their prognosis and avoid long-term negative outcomes. However, approximately 30% of individuals accessing support will end up disengaging from early intervention (EI) services. Although we know that individual factors can impact rates of disengagement, less is known about potential service and community level factors.

METHODS

Data were gathered from a cohort of individuals attending a specialist youth mental health service in Melbourne, Australia between 1st January 2011 and 7th September 2014. Data were collected from clinical files and electronic medical records using a standardised audit instrument. Cox regression analysis was used to identify whether community level factors were predictors of disengagement.

RESULTS

Data were available for 707 young people experiencing a first episode of psychosis. Individuals residing in neighbourhoods of higher social deprivation were at a higher relative risk of disengaging, with 4.7% increase in engagement for each increase in decile of deprivation. The introduction of a new clinic was not significantly associated with a difference in the proportion of individuals disengaging from the service and distance to service was not significantly associated with disengagement rates.

DISCUSSION

Developing strategies focused on engaging young people with first episode psychosis who reside in more deprived areas may address the higher rates of disengagement these individuals experience. These finding suggest that location may not be a barrier to engagement, however services should be resourced in-line with the population demographic in their specific location.

Specialised early intervention teams (extended time) for first episode psychosis

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:

The primary objective is to compare extended early intervention (EEIP) specialised team care to usual community mental health care for the treatment of people with first episode psychosis (FEP). The secondary objective is to compare the effectiveness of EEIP specialised team care to standard early intervention (SEIP) specialised team care (i.e. to test whether there is a dose‐response effect).