LifeStance Health has been selected as a test site to participate in a research study entitled Enhancing Mental Health Care by Scientifically Matching Patients to Providers’ Strengths. This interventional, randomized study is sponsored by the University of Massachusetts, Amherst and is in collaboration with the Patient-Centered Outcomes Research Institute, State University of New York - University at Albany, and Outcome Referrals Inc.
Research has shown that mental health care providers differ significantly in their ability to help patients. In addition, providers demonstrate different patterns of effectiveness across symptom and functioning domains. For example, some providers are reliably effective in treating numerous patients and problem domains, others are reliably effective in some domains (e.g., depression, substance abuse) yet appear to struggle in others (e.g., anxiety, social functioning), and some are reliably ineffective, or even harmful, across patients and domains. Knowledge of these provider differences is based largely on patient-reported outcomes collected in routine mental health care settings.
Unfortunately, provider performance information is not systematically used to refer or assign a particular patient to a scientifically based best-matched provider. Mental health care systems continue to rely on random or purely pragmatic case assignment and referral, which significantly "waters down" the odds of a patient being assigned/referred to a high performing provider in the patient's area(s) of need and increases the risk of being assigned/referred to a provider who may have a track record of ineffectiveness. This research aims to solve the existing non-patient-centered provider-matching problem.
Specifically, the investigators aim to demonstrate the comparative effectiveness of a scientifically based patient-provider match system compared with status quo pragmatic case assignment. The investigators expect significantly better treatment outcomes (e.g., symptoms, quality of life) in the scientific match group and higher patient satisfaction with treatment.
The importance of this work for patients cannot be understated. Far too many patients struggle to find the right provider, which unnecessarily prolongs suffering and promotes health care system inefficiency. A scientific match system based on routine outcome data uses patient-generated information to direct this patient to this provider in this setting. In addition, when based on multidimensional assessment, it allows a wide variety of patient-centered outcomes to be represented (e.g., symptom domains, functioning domains, quality of life).