S238. PATIENT ENGAGEMENT TO EARLY INTERVENTION IN PSYCHOSIS SERVICES: RETROSPECTIVE ANALYSIS OF ENGAGEMENT PATTERNS
Bibliographic record
Abstract
Abstract Background Within outpatient mental health services there exists an important awareness of the difficulties in engaging and maintaining contact with patients, as well as the understanding of the negative effects of disengagement, including worse patient outcomes and increased healthcare burden. Despite the importance of engagement on service delivery and recovery outcomes, few studies have examined rates and predictors of engagement in the early phase psychosis population. Although better than community care, it has been reported that an average of 30% of patients disengage from specialized early intervention services for psychosis (EIS). We examined rates of disengagement to a 5 year EIS for psychosis, including potential individual risk factors for disengagement at entry to service. Methods This cross-sectional cohort study examined engagement to services to a single EIS site from November 2006 to November 2016. Disengagement was determined retrospectively on review of medical records, defined as not attending to clinic services despite repeated attempts by clinicians/clinic for a three month time frame. Gender, age at clinic entry, ethnicity, Positive and Negative Syndrome Scale (PANSS), Drug Attitude Inventory (DAI-30), General Assessment of Function (GAF), Social and Occupational Functioning Assessment Scale (SOFAS), WHO-ASSIST version 3.0, and the Psychological General Well Being (PGWB)scale at entry to service were examined between groups. . Descriptive statistical and survival analyses for time to disengagement were conducted on the patient data set. Results 331 patient records were complete (with above scales) from entry to service to discharge or loss to follow-up. Patients were found to fall into 3 categories with regard to patterns of engagement. The first category we named “engagers” as they remained committed to their care throughout the program and comprised 50% of the sample. The second group were labeled the disengagers (20% of the group) and these were individuals who disengaged at some point in the program and did not return, in contrast to “intermittent engagers“ who comprised 30% of the sample. Intermittent engagers were patients who at some point during their care would meet criteria for disengagement but would re-engage later (still within the 5 years from entry to EIS) and complete the program. Absolute disengagement by the disengager group was predominantly prior to 12 months of treatment (78% of the group) with a survival analysis showing a median time to absolute disengagement of 8 months. The 3 groups though defined based on their engagement status, did not significantly differ in age, gender and ethnicity. Additionally, the clinician reported scores GAF and SOFAS did not differ between the groups. Patterns of substance use differed between the groups. There was a trend toward higher tobacco use in the two groups showing disengagement. Cannabis use did not differ significantly between groups but the pattern of use was highest in the disengagers followed by the engagers and then intermittent engagers. Alcohol use was significantly different between the groups with 81% of the disengagers having problem levels of alcohol use (WHO ASSIST v. 3.0 score above 4), however, there was no correlation between alcohol score and time to disengagement. Discussion Our retrospective study found a surprisingly large portion of the patient population will wax and wane in their commitment to health services but ultimately maintain attendance to complete the program, suggesting that patients should not be discharged early from EIS for psychosis. Substance use patterns and functional measures may identify patients who are at risk of early disengagement from EIS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".