Category Archives: Early Identification

NICE’s Early Value Assessment for Medtech

The explosion in digital health products has left National Health Service commissioners in the UK wondering how they can possibly sift out what works and what provides maximum benefit for the service and for patients.

The Early Value Assessment for Medtech will offer a rapid assessment of digital products, devices and diagnostics for clinical effectiveness and value for money. The goal of this new approach is that the service and patients will be able to benefit sooner.

Early Value Assessment is being designed to draw in the most promising and impactful medical technologies where the evidence base is still emerging, starting with digital products, in areas where there is greatest need.  Whether its empowering patients to better manage their own health and seek clinical advice, reducing admissions and waiting lists or supporting clinicians and other front-line staff to provide better quality care this new program will help to alleviate system pressures as the NHS recovers from the COVID pandemic.

In this accelerated approach, the first two pilot digital health topics will begin their early value assessments this month (June) with a view to publishing findings in October. This is much faster than a full NICE Medtech evaluation meaning benefits will be realized sooner, while companies generate more evidence required for a full NICE evaluation at a later stage.  

The first two pilots are digital apps for depression and anxiety in children and others will quickly follow in adult mental health, early cancer diagnosis, cardiovascular disease and other areas that support elective recovery following the pandemic.

In this ‘fast-track’ approach, NICE is working closely with NHS England and all its system partners to help develop commercial and data collection arrangements to support the technologies that go through early value assessment in adoption and scaling and to make this new program of work deliver on the potential of digital health for patients.

Source: NHS Blog

Columbia University Psychiatry Develops a Mobile Depression App

A major gap in diagnosing and managing major depression is that the frontline in the recognition of depression is staffed by primary care clinicians. Since depression is one of the leading causes of disability worldwide, busy PCPs can benefit from the latest tools and information to assist them in the assessment and treatment of patients who present with symptoms.

The app known as Columbia Psychiatry Pathways — supports and strengthens the ability of clinicians to provide critical mental health services in an outpatient setting. It was co-developed by Columbia Psychiatry faculty John Mann, MD and Ravi N. Shah, MD. in collaboration with avoMD, a next-gen clinical decision support platform, as an interactive smartphone application that provides point-of-care treatment algorithms for major depression. 

This clinical decision support tool, is available as a mobile and desktop app. It has been developed for use by psychiatrists, primary care physicians, nurse practitioners, physician assistants, medical students, residents, and trainees in outpatient settings as they treat patients with major depression. The evidence-based platform updates prior depression treatment guidelines and uses algorithms that focus on faster medication adjustments with emphasis on the best-tolerated generic antidepressants. It measures symptom severity using built-in calculators based on the Columbia Depression Scale and includes screenings for bipolar disorder and suicide risk. 

The division of primary care at Columbia welcomes the Psychiatry Pathways app and highlight that ‘it is challenging to treat major depression, especially in a primary care setting, especially in a patient with comorbid conditions. A point of care app that can serve as virtual consult can help to validate a PCP’s knowledge in the best possibl care for patients.’

Sources:

Columbia Psychiatry

avoMD

Study to Evaluate Apple Devices For Identifying Early Parkinson’s Disease

Apple Watch PD App

A recent study presented at the virtual International Congress of Parkinson’s Disease and Movement Disorders 2021, demonstrated that Apple Watches and iPhones can differentiate between individuals with early, untreated Parkinson’s disease (PD) and healthy controls.

The 12-month study included 132 individuals at 17 Parkinson’s Study Group sites, 82 with PD and 50 controls. Ages of the participants were approximately the same in the PD and control groups (63.3 years vs 60.2 years, respectively), but male to female ratios differed between the groups. There were more men in the PD cohort (56% men vs 44% women) and more women in the control cohort (36% vs 64%; P =.03).

Participants with PD were untreated, were no more than 2 years out from diagnosis (mean disease duration, 10.0 ±7.3 months), and were in Hoehn and Yahr stage 1 or 2. Apple Watches and iPhones were provided to participants, all of whom underwent in-clinic assessments at baseline and at months 1, 3, 6, 9, and 12. The assessments included motor and cognitive tasks using the devices, which contained motion sensors.

The phone also contained an app that could assess verbal, cognitive, and other abilities. Participants also wore a set of inertial sensors (APDM Mobility Lab) while performing the MDS-UPDRS Part III motor examination. In addition, there were bi-weekly at-home tasks. Questions and tests on the watch assessed symptoms of mood, fatigue, cognition, and falls as well as cognitive performance involving perceptual, verbal, visual spatial, and fine motor abilities. Both the watch and iPhone were used to gauge gait, balance, and tremor.

The authors concluded that “the WATCH-PD trial is one of the first multi-center, prospective, longitudinal digital markers studies in untreated early PD patients. Preliminary analyses show that devices can differentiate between individuals with early, untreated PD and controls. Further analyses of longitudinal data may provide additional insights including the utility of wearable and mobile devices for measuring functional outcomes in clinical trials.”

Source:

J. Adams, E. Dorsey, T. Ruiz Herrero, WATCH-PD: Wearable Assessments in the Clinic and Home in Parkinson’s Disease: Baseline Analyses [Abstract 364]. Mov Disord. 2021; 36 (suppl 1). https://www.mdsabstracts.org/abstract/watch-pd-wearable-assessments-in-the-clinic-and-home-in-parkinsons-disease-baseline-analyses/. Accessed September 25, 2021.