A Carle Illinois College of Medicine (CI MED) student is the software architect behind an emergent technology platform that expands modern psychiatric care beyond the clinic or hospital. The system has potential to augment traditional visit-based clinical care, not just in psychiatry, but in many other medical specialties.
It was created by first-year medical student Aditya Vaidyam and a team at Harvard. It’s called the LAMP Platform (Learn, Assess, Manage, Prevent), and it’s designed to make psychiatric care possible whenever and wherever it’s needed most.
“This kind of clinical model can really change the depth of care delivered to individual patients, but also allow a psychiatric care team to work with many more patients, too,” Vaidyam said. “It’s a health care delivery and resource allocation puzzle that we’re trying to solve with this model, and the end goal is increased access to quality care. Better care for more people.”
The LAMP Platform taps into patient data from off-the-shelf mobile and wearable technology (smart devices), mental health and fitness apps, and cognitive games like those built into the LAMP system itself. LAMP’s machine-learning algorithms then analyze the data to detect changes in a patient’s mental health status. The system detects patterns around emerging or recurring problems that can inform both population research and direct individual patient care.
LAMP was originally developed for neuropsychiatric research purposes under the direction of Dr. John Torous at Beth Israel Deaconess Medical Center/Harvard, but its use has expanded to help augment clinical care. The LAMP Platform is part of a new approach that combines asynchronous telemedicine with digital phenotyping. It takes virtual medicine to the next level, allowing patients to report changes or symptoms as they happen outside the clinical encounter. ‘Digital phenotyping’ tracks patient biomarkers (heart rate, sleep patterns, etc.) and interactions with mobile devices and cognitive games to yield vast amounts of data that can be analyzed to help predict relapse or even to suggest personalized interventions to fit the patient.
For example, the LAMP system can be in used a clinical setting to monitor or reduce symptoms in patients who are at risk for developing schizophrenia. “The first visit would start with the psychiatrist to discuss the treatment plan and objectives, like any normal outpatient psych visit. Then, the patient would spend some time with what our team calls the digital navigator, to educate the patient on using the mental health app, like our mindLAMP app,” Vaidyam said. The incoming patient data may be monitored daily or weekly to alert the psychiatrist to any changes that signal reason for concern. Between the initial visit and a follow-up visit, all the data are being captured and analyzed in real time. The psychiatrist can then use the data to spark a follow-up discussion and to make more informed decisions about adjusting the patient’s treatment plan.
The open-source LAMP Platform is free and is being used by researchers in the US and abroad to study important mental health issues that impact large segments of the population. Research findings have the potential to shape mental health care across the globe. “The research studies we run broadly cover global mental health, college mental health, early onset schizophrenia in young adults, relapse detection, and many more. So essentially our team is looking at what clinical care in psychiatry looks like for the next decade and beyond,” Vaidyam said.
Although LAMP was developed specifically for mental health, Vaidyam foresees broad application of the system’s data analysis tools across other medical specialties and care settings. “It has the potential to help triage care needs; maybe urgent care physicians or telehealth physicians use the data to lessen the load on ERs, or maybe primary care providers use the data to dynamically reschedule their patient load based on estimated patient health risks.”
The LAMP system is fully compliant with U.S. health information privacy standards, but Vaidyam says the data protections in commercially available mental health apps can vary widely. The issue can create a trust gap among patients who are wary of how their data are used and relayed. To help patients and providers make informed decisions about which apps they’re comfortable with, the team created a database that uses a peer-based systematic review-like rating model.
Vaidyam hopes to form collaborations with scientists at the University of Illinois Urbana-Champaign, Carle Health, CI MED, and private industry to leverage technology to use the LAMP platform to inform health decisions. “The doors are always open for any individuals and organizations to join!”
To learn more about Asynchronous Telemedicine and Digital Phenotyping, watch this presentation by Aditya Vaidyam as part of Carle Illinois College of Medicine’s RISE lecture series.