The US Mental Health Parity Act encourages primary care (PC) providers to integrate behavioral health, including drug use reduction, into routine PC. QUIT (the Quit Using Drugs Intervention Trial), a multi-component screening and brief intervention (SBI) for diverse drug using adults in PC, reduces risky drug use and improves quality of life (QoL) over 3 months; the findings have been replicated in a subsequent study. Three key evidence gaps are: a) the effectiveness of SBI for people with moderate risk drug use over 6- and 12-months; b) low-cost methods to enhance, sustain, and monitor drug use reductions; and c) implementation barriers, facilitators, and costs of SBI for people with moderate risk drug use in PC. This study is an Effectiveness-Implementation Hybrid Type 1 design consisting of a 3-arm RCT and qualitative research.
QUIT is a four-pronged program: 1) patient screener at reception via tablet-device; 2) brief clinician advice (<5-minute); 3) video doctor reinforcing clinician advice; and 4) two telephone health coaching calls at 2- & 6-weeks. Mobile phone "apps," text-messaging (SMS), and interactive voice response (IVR) tools offer opportunities to enhance, sustain, and monitor effects of SBIs by facilitating patient activation and self-management between coaching sessions during daily routines, and sustaining changes after coaching ends.
QUIT-Mobile augments QUIT with 3 key functions: 1) patient self-monitoring of drug use and related factors (i.e., cravings, pain, physical and mental health symptoms/QoL) twice weekly by app, SMS, or IVR (per patient preference) and weekly from 6 wks to 12mo; 2) weekly automated feedback on goal progress for reducing drug use; and 3) dashboards for coach monitoring of patients' self-monitoring data. These functions aim to: enhance coaching sessions by facilitating goal tracking, problem solving, and patient-coach engagement; and after coaching to sustain patient activation; and monitor patients to prompt coach follow-up if drug use increases.
Self-monitoring is a core element of self-regulation and self-management applied in a range of chronic conditions. SMS, IVR, and apps enable self-monitoring and automated feedback to be cheaply implemented and scaled. The theoretical bases underlying QUIT's cognitive behavioral and motivational interviewing strategies emphasize that self-monitoring and feedback are integral to self-regulation and self-management through self-observation, reflection, self-correction, and reinforcement via self-reward, critique, and feedback.
Effectiveness of QUIT-Mobile and QUIT over 12-months will be examined in a single-blind, 3- arm, RCT with low-income, adult, mainly ethnic minority FQHC PC patients with risky drug use (RDU - based on ASSIST score 4-26; ASAM level 0.5), randomized to 3 conditions (n=200/arm, 600 total): 1) QUIT-Mobile, 2) standard QUIT, and 3) Usual Care (UC). Primary outcomes are drug use reductions measured by self-reports of past 30 days drug use (due to sporadic use patterns of people with moderate/risky drug use) with urine screen validation measured at baseline, 3-, 6-, and 12-months. Subgroups will be compared on outcomes by demographics, drug type, intervention engagement, comorbidities, pain, and clinic-level factors. Secondary outcomes are health services utilization and quality of life. Formative Qualitative Research will be conducted with patients, coaches, FQHC staff (providers, administrators, executives), payers / insurers and policy stakeholders to identify barriers/facilitators to adoption, implementation and sustainability. The Consolidated Framework for Implementation Research (CFIR) will guide this work. Costs will also be monitored, and cost analyses will be conducted.
Study Outcomes:
Primary: Reductions in use of the highest scoring drug on the ASSIST at baseline (that was used in the past 30 days) across time at 3-, 6- and 12- months follow-up, as measured by number of days of drug use in the past 30 days.
Secondary: 1) Improvement of quality of life as measured by the SF-12 physical and mental health scores; 2) costs analyses of the interventions for reducing drug use, including use of health services utilization data from EHR reviews; 3) barriers and facilitators to intervention implementation from qualitative reports with providers and clinic stakeholder, patients, and payer and policy maker stakeholders; 4) drug use reductions measured by timeline follow back (TLFB) of past 30 days use.