Denis Agniel1, Daniel Almirall2, Q Burkhart3, Sean Grant4, Sarah B Hunter3, Eric R Pedersen3, Rajeev Ramchand5, Beth Ann Griffin5. 1. RAND Corporation, 1776 Main Street, Santa Monica, CA 90401, USA; Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck St., Boston, MA 02115, USA. Electronic address: Denis_Agniel@rand.org. 2. Institute for Social Research, University of Michigan, 426 Thompson Street, Ann Arbor, MI 48104-2321, USA. 3. RAND Corporation, 1776 Main Street, Santa Monica, CA 90401, USA. 4. RAND Corporation, 1776 Main Street, Santa Monica, CA 90401, USA; Department of Social & Behavioral Sciences, Indiana University Richard M. Fairbanks School of Public Health, 1050 Wishard Blvd, RG 6046, Indianapolis, IN 46202, USA. 5. RAND Corporation, 1200 South Hayes Street, Arlington, VA 22202-5050, USA.
Abstract
BACKGROUND: Adolescents respond differentially to substance use treatment based on their individual needs and goals. Providers may benefit from guidance (via decision rules) for personalizing aspects of treatment, such as level-of-care (LOC) placements, like choosing between outpatient or inpatient care. The field lacks an empirically-supported foundation to inform the development of an adaptive LOC-placement protocol. This work begins to build the evidence base for adaptive protocols by estimating them from a large observational dataset. METHODS: We estimated two-stage LOC-placement protocols adapted to individual adolescent characteristics collected from the Global Appraisal of Individual Needs assessment tool (n = 10,131 adolescents). We used a modified version of Q-learning, a regression-based method for estimating personalized treatment rules over time, to estimate four protocols, each targeting a potentially distinct treatment goal: one primary outcome (a composite of ten positive treatment outcomes) and three secondary (substance frequency, substance problems, and emotional problems). We compared the adaptive protocols to non-adaptive protocols using an independent dataset. RESULTS: Intensive outpatient was recommended for all adolescents at intake for the primary outcome, while low-risk adolescents were recommended for no further treatment at followup while higher-risk patients were recommended to inpatient. Our adaptive protocols outperformed static protocols by an average of 0.4 standard deviations (95 % confidence interval 0.2-0.6) of the primary outcome. CONCLUSIONS: Adaptive protocols provide a simple one-to-one guide between adolescents' needs and recommended treatment which can be used as decision support for clinicians making LOC-placement decisions.
BACKGROUND: Adolescents respond differentially to substance use treatment based on their individual needs and goals. Providers may benefit from guidance (via decision rules) for personalizing aspects of treatment, such as level-of-care (LOC) placements, like choosing between outpatient or inpatient care. The field lacks an empirically-supported foundation to inform the development of an adaptive LOC-placement protocol. This work begins to build the evidence base for adaptive protocols by estimating them from a large observational dataset. METHODS: We estimated two-stage LOC-placement protocols adapted to individual adolescent characteristics collected from the Global Appraisal of Individual Needs assessment tool (n = 10,131 adolescents). We used a modified version of Q-learning, a regression-based method for estimating personalized treatment rules over time, to estimate four protocols, each targeting a potentially distinct treatment goal: one primary outcome (a composite of ten positive treatment outcomes) and three secondary (substance frequency, substance problems, and emotional problems). We compared the adaptive protocols to non-adaptive protocols using an independent dataset. RESULTS: Intensive outpatient was recommended for all adolescents at intake for the primary outcome, while low-risk adolescents were recommended for no further treatment at followup while higher-risk patients were recommended to inpatient. Our adaptive protocols outperformed static protocols by an average of 0.4 standard deviations (95 % confidence interval 0.2-0.6) of the primary outcome. CONCLUSIONS: Adaptive protocols provide a simple one-to-one guide between adolescents' needs and recommended treatment which can be used as decision support for clinicians making LOC-placement decisions.
Authors: Inbal Nahum-Shani; Min Qian; Daniel Almirall; William E Pelham; Beth Gnagy; Gregory A Fabiano; James G Waxmonsky; Jihnhee Yu; Susan A Murphy Journal: Psychol Methods Date: 2012-10-01
Authors: Inbal Nahum-Shani; Ashkan Ertefaie; Xi Lucy Lu; Kevin G Lynch; James R McKay; David W Oslin; Daniel Almirall Journal: Addiction Date: 2017-02-18 Impact factor: 6.526
Authors: Laura Kann; Tim McManus; William A Harris; Shari L Shanklin; Katherine H Flint; Barbara Queen; Richard Lowry; David Chyen; Lisa Whittle; Jemekia Thornton; Connie Lim; Denise Bradford; Yoshimi Yamakawa; Michelle Leon; Nancy Brener; Kathleen A Ethier Journal: MMWR Surveill Summ Date: 2018-06-15