Using mHealth to Optimize Pharmacotherapy Regimens

Summary

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Description

Comprehensive early treatment of individuals experiencing schizophrenia has the potential to alter the course of illness and improve long-term outcomes. Psychotropic medications are a critical component of early treatment strategies. First-episode psychosis (FEP) is a critical time to optimize presc...

Comprehensive early treatment of individuals experiencing schizophrenia has the potential to alter the course of illness and improve long-term outcomes. Psychotropic medications are a critical component of early treatment strategies. First-episode psychosis (FEP) is a critical time to optimize prescribing but evidence suggests that prescribing for this population is suboptimal. A contributing factor to these difficulties is thought to be the lack of accurate information about the effects of medications on symptoms, their side effects, as well as their behavioral, cognitive, and emotional correlates. At medication management appointments, prescribers typically rely on patients' recollection of how they were doing over periods of weeks. Such retrospective assessments are problematic as they are vulnerable to the influence of memory difficulties, cognitive biases including recency effects and frequency illusions, and reframing. Recent advances in smartphone technologies (mobile Health; mHealth) may help to overcome many of the limitations of retrospective assessments. This pilot study will be a collaboration with OnTrackNY, an innovative coordinated specialty care (CSC) program for individuals aged 16-30 who are experiencing FEP. OnTrackNY originated as part of the NIMH Recovery After an Initial Schizophrenia Episode (RAISE) Implementation and Evaluatoin Study. The initial phase of this project will use input from stakeholders including patients, front-line providers, clinical leaders, and members of the research team to adapt and refine the mHealth intervention to improve feasibility and clinical utility. A pilot study at 3 OnTrackNY sites will then examine its feasibility and effectiveness by comparing the management and outcomes of 60 patients randomly assigned to the mHealth application or usual care.

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