The Connected Health Conference and its predecessor events, the Partners HealthCare’s Connected Health Symposium and the Personal Connected Health Alliance’s Connected Health Conference (a HIMSS event), aim to frame digital health advancements in the context of improving clinical care delivery as well as personal engagement.
It’s “personal” engagement because the conference recognizes that “patient” engagement only occurs in a healthcare setting. Improving health and well-being must be part of our everyday lives – or, as this year’s conference theme put it, part of “the connected life journey.”
In particular, this year’s Connected Health Conference examined digital health’s impact on getting older – a process that speakers such as AARP CMO Dr. Charlotte Yeh attempted to destigmatize by emphasizing the positive aspects of aging, including learning and building social connections. Get it right, Yeh said, and aging makes us happier – and happiness has been linked to better health and longevity.
With that in mind, here’s a recap of various digital health solutions discussed at the conference, along with Chilmark Research’s assessment of the maturity of these solutions.
Condition management: Almost mature. Multiple speakers highlighted the potential of chronic condition management solutions to provide targeted engagements and interventions, especially those that draw upon principles of behavioral science as opposed to marketing. Plus, Livongo Health announced a partnership with Alaska’s Medical Park Family Care that is notable because providers approached the vendor, with both stakeholders then approaching the payer together; this could be a sign of a shift, as payers or large employers typically initiate the conversation (and may not even get providers involved at all). If there’s a caveat, it’s solution sprawl; Dr. Adrienne Boissy of the Cleveland Clinic noted that the hospital has 27 different apps for engaging with patients; that number has to go down.
Providers don’t want artificial intelligence but, rather, the output of AI – clinical decision support, diagnostics, more personally tailored care plans, 30-day readmission risk scores, and so on – but that hasn’t stopped vendors from promoting the use of AI and machine learning.
Telehealth: Getting there. As Carla Kriwet of Philips noted, the holdup for telehealth adoption is not the maturity of the technology; it’s the clinical culture that still emphasizes in-person visits and the related struggle to define telehealth’s value-add. (Kriwet didn’t mention the regulatory and reimbursement challenges, which Twitter users in the audience were quick to point out). Plus, telehealth requires broadband access, which millions of Americans still lack. That said, physicians are a bit more bullish on telehealth and other technologies at the point of care, AMA President Dr. David Barbe said, pointing to AMA survey data he shared on stage at the Connected Health Conference.
Decision support: Getting there, slowly. Providers don’t want artificial intelligence but, rather, the output of AI – clinical decision support, diagnostics, more personally tailored care plans, 30-day readmission risk scores, and so on – but that hasn’t stopped vendors from promoting the use of AI and machine learning. The baseline ongoing challenge, of course, is bringing disparate data sets together to let AI algorithms do their thing, and then deploying them at the point of care in a timely manner, which is no small task when those data sets include months-old claims and years-old HHS reports. Oh, and don’t forget data streams from remote patient monitoring devices. Smart vendors and providers are using an API approach to address this data deluge, but progress has been slow.
Chat bots: Getting there, slowly. Conversations with bots allow engagement solutions to scale, especially for low-acuity care as well as general wellness and mood. But for every Conversa Health (where chat bot responses come from a database that also identifies whether a particular response must automatically trigger an escalation to higher-acuity care), there’s an Ada Health (where users must escalate on their own, for a $25 fee). Here, the market has yet to separate the wheat from the chaff, as is evidenced by Ada Health’s latest $47 million funding round.
Blockchain: Emerging. There is certainly potential for blockchain to provide secure data sharing, and use cases are beginning to pop up. Hashed Health is addressing provider licensure in the state of Illinois, which will help the state store up-to-date credentialing information and share it with payers; the hope is to eliminate the bottlenecks in an often-manual process. Meanwhile, MintHealth, promises a personal health record platform powered by blockchain. The presence of a unique global identifier, which blockchain enables, could let patients manage their records better than previous PHRs; plus, MintHealth plans to sell to commercial payers, who have clear financial incentives to better engage members. Even if these efforts fall flat – and, let’s face it, PHRs have a poor track record by placing too much burden on the patient – they have at least demonstrated practical examples of blockchain in healthcare.
Virtual reality: Incubating. Qualcomm and ForwardXP announced a VR simulation at the Connected Health Conference that lets users experience stroke symptoms, in an effort to help them better identify warning signs. While this could be an effective educational tool for medical professionals, we’re not sold on its viability for consumers, who would either need to use it on their own VR devices or travel to an educational session somewhere with a VR device. In one session, Dr. Brennan Spiegel of Cedars-Sinai Health System cautioned against “overpromising and under-delivering” with VR. Pain management is an effective clinical use case; giving patients the 21st century equivalent of a ViewFinder probably isn’t.
Wearables: Incubating (still). Wearables provide data such as steps taken, exercises completed, hours of sleep, but they don’t yet provide insight – and that hasn’t changed since I wrote about it for CIO.com way back in 2014. One reason is the separation between wearable information and clinical workflows, which hampers the ability of wearable data to reliably contribute to decision support. Another is the accuracy of the data; we still earn “steps” for folding laundry or doing dishes, but not for riding a bicycle, so physicians can’t be blamed for viewing wearable data with a dose of skepticism. Finally, for all their talk, consumer device makers such as Apple, Fitbit, Google, and Samsung have yet to crack the chronic condition management market – only Nokia has, and its market share lags substantially.
The smart home: Not even close. Speakers mentioned a number of futuristic use cases, ranging from home-based robot caregivers to fall alert sensors tied to home security systems to sensors that monitor water usage, detect abnormalities, and alert caregivers of potential problems. No one mentioned which healthcare stakeholders would subsidize the high cost of this technology, train end users (including caregivers), or monitor data and escalate a case as needed. Nor did anyone mention the ROI for such technology deployments, or the impact on clinical outcomes.
Closing Thought
Ultimately, the goal of these solutions is to meet the needs of people managing their health, whether on their own or through the clinical experience. As such, these solutions need to ease their way into clinical workflows and everyday life and prove their potential to play a part in the connected life/care journey. Until then, they will simply remain stuck in the technology hype cycle.
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