RecruitingACTRN12619000838112

The Actionable Intime Insights (AI2) Study: Implementing a digital model for timely and needs-based interventions in mental health services by applying algorithms to health care data

Employing a just-in-time adaptive care early intervention approach for a transformational change in the way mental illness is observed, managed and followed-up: The Actionable Intime Insights (AI2) Study

Sponsor

Flinders University

Enrollment

100 participants

Start Date

Sep 1, 2018

Study Type

Interventional

Conditions

Relapse Schizophrenia Bipolar Disorder Medication error

Summary

We are recruiting participants aged over 18 years old to participate in a 2-year internet based study, called the Actionable Intime Insights (AI2) Study . The study aims to explore whether the use of patients Medicare Benefit Scheme (MBS) and Pharmaceutical Benefit Scheme (PBS) claims data held in My Health Record, can unveil more sufficient ways for clinicians and other healthcare professionals to provide optimal health care to patients with a chronic mental illness. Specifically, when people go to visit their doctors, they typically lodge a MBS or PBS claim to subsidise some of the payment costs. However, to date, there has not been a successful way of monitoring and managing the MBS and PBS data. We hope that we can be the first to provide a long-term sustainable solution to this problem, with the implementation of our novel digital application called the Actionable Intime Insights (AI2) application. We believe the AI2 application will help transform the way clinicians and patients interact with each other and ultimately improve patient’s well-being and outcomes.

Eligibility

Sex: Both males and femalesMin Age: 18 Yearss

Plain Language Summary

Simplified for easier understanding

For people living with a chronic mental illness, navigating the healthcare system can be complicated. Medicare and pharmaceutical benefit claims (the records created when you visit a doctor or fill a prescription) hold a wealth of information about a person's healthcare journey — but this data has never been used effectively to improve mental health care in real time. The AI2 Study is building and testing a digital application that allows clinicians to access and make sense of their patients' claims data held in My Health Record. The idea is that patterns in this data — such as missed appointments or medication changes — could alert care teams to patients who might need more support before a crisis occurs. Participants will be involved in the study for two years, using the app as part of their routine mental health care. Adults aged 18 and over with a chronic mental health diagnosis (as defined by DSM-5 criteria) are eligible. People who have not been formally diagnosed with a mental health condition, or who are unlikely to engage with the study, are not eligible. If successful, this digital tool could transform the way mental health services identify and respond to patients' needs, moving from reactive to proactive care.

This is a simplified summary. Always discuss eligibility with your doctor before enrolling in a clinical trial.

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Interventions

This is a pilot intervention study that will aim to gauge the feasibility and potential efficacy of using an innovative digital data analytics application (The Actionable Intime Insights [AI2] Application). to support healthcare professionals provide more effective and undemanding ways of monitoring, managing, and treating patients with a chronic mental illness. It will run for 12 months. Essentially, AI2 is a digital cloud based application service for healthcare professionals and patients that is centralised around the use of MyHealthRecord data. This digital health system contains information such as: medicines (prescription and dispense records, PBS), and Medicare Benefit Schedule (MBS) claims. The methodological premise behind the AI2 study intervention is to use this data as a way to monitor and manage patients, providing real-time visualisation algorithms that identify patients at-risk of relapse and re-hospitalisation. The AI2application is designed so that each MBS and PBS claim made by the patient is visually displayed as an event in a vertical axis, and placed against a time scale (with the day/month and year) on a horizontal axis. In addition to the event (e.g. GP visit), an accompanying simple notes entry box is also included which allows for clinicians to annotate certain insights or predicted outcomes. The additional benefit of adding the notes initiative into the AI2 application is that it adds a contextual backdrop to the documented events, which, in turn, could facilitate the clinicians to identify and develop effective strategies and post-treatment plans. When participants (people with serious mental illness) log into the AI2 system they will see at first glance their individual profile which will include their personal details (i.e. date of birth, phone number, email address, Medicare number, My Health Record account access, and when they joined). Patients will also have access to their own individual historic timeline of MBS and PBS events on a horizontal platform, and a separate tab that will allow them to connect and disconnect with various healthcare professionals. Patients are not expected to interact with AI2 directly beyond creating an account, but are welcome to view their information. After creating an account, participants will be randomly allocated to either the intervention (50% of participants) or control (50% of participants) group. If an alert is triggered by the AI2 system for a participant in the intervention group (a missed prescription, a missed appointment), the patient will be send an SMS explaining that they have missed this event and are encouraged to contact their clinician. If an alert is triggered for the control group, no SMS will be sent. After consenting to participate, the only tasks required of participants are to sign up to the AI2 system, have their My Health Record data transferred to the AI2 system, and agree to fill in a post study questionnaire. Our in-house psychiatrists acting as study ‘Monitors’ are trained on how to use the AI2 system, how to correctly interpret the algorithms, and how to specify appropriate intervention pathways when participants are identified at risk of relapse and hospitalisation. Once the trial commences, the clinician Monitors will spend dedicated time engaging with the AI2 system to identify patterns within the data for individual participants that may indicate potential relapse or risk of hospitalisation. These patterns are displayed in dashboard view in a traffic light colour coded reference (Red = people at high risk, urgent action required, Yellow = people at moderate risk, action required, Green = people not at risk, no action required).