PRTFs: Psychiatric Residential Treatment Facilities

1. Atypical antipsychotics and Admission to psychiatric Residential Treatment Facilities: Using Directed Acyclic Graphs to establish causal relationships using secondary dataRoderick A. Rose, PhDPaul lanier, Phdaugust 21, 2019

2. PRTFs: Psychiatric Residential Treatment Facilities • 24 hour psychiatric care facility for youth with behavioral disorders, esp. sed. • Not necessarily consistent with systems of care (least restrictive?), but possibly a last resort for some • Research: • LCA study: children with no caregivers; substantial maltreatment history. • Children involved in child welfare system more likely to be admitted (mh disorders  abuse/neglect; beh disorders  placement instability) • COSt: In NC the cost of TREATING 2,100 youth rose from $50M to $97M between 2009 and 2011. • Diversion of youth who should not be in a PRTF is a valid policy goal

3. Rose & Lanier, 2017 • Examined Association between time-to-admission to a prtf and foster care placement characteristics, investigation findings and services provided, prior services, demographics • A key finding was H = 8.7 for antipsychotic prescription (prior to admission) • Descriptive study, no causal inferences • Rose, R. A. & Lanier, P. (2017). A longitudinal study of child maltreatment and mental health predictors of admission to psychiatric residential treatment facilities. International Journal of Environmental Research and Public Health 14(10), 1141-1156. doi:10.3390/ijerph14101141 A common theme throughout CW evaluation is causal inference (claiming a program does somethingrather than is associated with something) without randomized assignment

4. Second-generation antipsychotic drugs For irritability from ASD in children 5+: Risperidone • Also known as atypical antipsychotics • Including Clozapine, Risperidone, Olanzapine, Quetiapine, Aripiprazole, Ziprasidone, Asenapine (others) • Growth in use & approvals for children • Not approved for use for adhd • 1/7 of prescribed youth had adhd as their only MH diagnosis • typically for aggression management For schizophrenia in children 13+: Quetiapine, Aripriprazole, Risperidone, Paliperidone For bipolar or manic/mixed in children 10+: Quetiapine, Aripriprazole, Risperidone ADHD: None

5. SGAs: The context for foster youth Less than half of youth on Medicaid received psychosocial counseling prior to SGA 55% of foster parents reported they did not believe they were primarily responsible for monitoring Little research has been conducted on the benefits and risks in youth populations SGA scripts associated with placement stability and permanency, but do not impact time to placement

6. SGAs: The benefits/the positives Improvement in patients with schizophrenia, bipolar, disruptive behaviors, tics associated with Tourettes + Fewer pyramidal side effects than First Generation Antipsychotic Drugs May be effective at short-run improvement in symptoms of disorders May be effective when done concurrently with psychosocial counseling

7. SGAs: The risks/the negatives _ Opposing mechanism of action relative to stimulants typically prescribed for ADHD Cardiovascular risks are high and relatively higher for children; weight gain Breast enlargement in males Diabetic risk 3x among youth prescribed SGAs relative to other psychotropics

8. Research Questions • What is the hazard of being prescribed an sga among foster youth diagnosed with adhd? • What is the unadjusted hazard of admission to a prtf among youth with adhdand an sga relative to those without an sga? • What is the hazard of admission to a prtf among youth diagnosed with adhdand an sga relative to those without an sga, controlling for demographics and co-occurring conditions? These are causal questions

9. causality Theory Data Assumptions are the force behind causal inference, not statistics Statistics are just numbers; we use assumptions to imbue them with causal meaning Methods

10. Directed acyclic graphs for causal inferenceMethods – results – discussion

11. Example: Causal FrameworksDirected Acyclic Graph (DAG) A Antecedent Y Outcome C Cause Confounder(s) Adapted from Vanderweele 2015; Figure 2.2

12. Value of dags • A framework for specifying relationship of interest • Connecting theory and lit to specify potential confounding relationships • Connect logic model or theory of change to on-the-ground intent-to-treat conditions typical of implementation • Identifying problems and solutions • Identify opportunities for measurement and follow-up data collection • Assisting in selection of appropriate population and sample • Specification of mechanisms of change and their antecedents • Enabling identification/selection of possible methods

13. Dag for sga PRTF admission Gender Disorder: ADHD Diagnosis of ADHD Admission to PRTF Response SGA Agg Stim Practitioner Tendencies And Characteristics Other conditions S Indicates selection into population & sample

14. Measurement issues: longitudinal • population is foster youth with adhd and no mh diagnosis, sga, or prtf admit from 1/1/2011 to 6/30/2012 • Sample includes members of population not having priorsga, diagnosis of select psychoses, or admission to prtf • After diagnosis of adhd: If response or admission occurs before sga, youth is not in treatment condition; if sga comes first, youth is in treatment • Co-occurring “sga” conditions (conditions for which sga is approved in children) must also occur prior to/on sga & prior to admission Longitudinal Does not eliminate contemporaneous confounding

15. Option 1: covariate control Gender Admission to PRTF Response SGA Agg Stim Practitioner Tendencies And Characteristics Other conditions

16. Option 2: front door criterion Gender Admission to PRTF Response SGA Agg Stim Practitioner Tendencies And Characteristics Other conditions

17. Option 3: ive Gender Admission to PRTF Response SGA Agg Stim Practitioner Tendencies And Characteristics Other conditions

18. caveats • There is no test for confounding • The dag is a framework; theory, hypothesis tests, etc., populate the dag • …thus, bad theory, etc. means the dag will give bad information

19. Additional strategiesgiven measurement challenges • Sensitivity to rules • Sensitivity analysis of impact (monte carlo) • Identify range of confounders needed to alter substantive finding • Propensity score analysis • Select a comparison group of youth with adhd not receiving sga prescriptions who are otherwise equivalent to treated youth with adhd • Will still be highly dependent on measurement

20. Methods (covariate control only) • Medicaid claims data 2011-2018 • Event history analysis (cox ph) estimates hazard rate for time-to-event • Rules • Diagnosis must occur 3 or more times (rough guess) • Sga must be prescribed twice (literature provides good guidance) • Sensitivity tests of diagnosis rule • Diagnosis: 1 or 5

21. Findings: research question 1hazard of sga prescription • Median months since birth to sga prescription is 68 (~5 ¾ years) • On months to sga prescription, a stimulant prescription is predictive of hazard (H = 1.5; p < .01) • co-occurring “sga” condition is predictive (H = 3.3; p < .0001) • also • females have lower hazard of sga prescription (.75, p < .01) • Older children have lower hazard of sga prescription (.87, p < .0001)

22. Findings: research question 2unadjustedhazard of admission to prtf by sga • Median months since birth to admission is 70 (just under 6) • Excluding stimulant • H = 7.8, p < .0001 • With stimulant • H = 7.1, p < .0001 • Stimulant not predictive of hazard

23. Findings: research question 3adjustedhazard of admission to prtf by sga • On months to admission • a stimulant prescription is not predictive of hazard • An sga prescription is predictive of hazard (H = 5.8; p < .0001) • controlling for • Race/ethnicity (no assoc); gender (no assoc); age on start of Medicaid (older youth lower hazard .85, p < .0001); co-occurring “sga” condition (H = 3.2, p < .0001)

24. Limitations • Measurement: diagnosis is problematic • plausible alternatives • Severity: Trauma; physical symptoms; access to psychotherapy, behavioral, or evidence-based interventions. • Response diagnosis would help, but can we assume that a post-sga diagnosis is actually response vs being a previously undiagnosed condition?

25. implications Additional research needed: • use Medicaid data to develop better measures of co-occurring factors such as severity • Conduct analysis using withdrawal from Sga • Conduct analysis on return to prtf • Use advanced qe methods & frameworks • Appropriate counterfactuals