Glooko launches web-based Population Tracker for payers and health systems to identify at-risk patients – February 21, 2014

Yesterday, Glooko announced the launch of Population Tracker, a new web-based software for payers and health systems. The system uses flags on an online dashboard to alert care managers when patients are experiencing risky high and low blood glucose trends. In the first version of the tool, patients will be flagged if they have experienced any of the following in the last 30 days:

• 25% of blood glucose readings >250 mg/dl
• 10% of blood glucose readings <70 mg/dl
• A single reading >400 mg/dl
• A single reading <50 mg/dl

Patients remotely upload their blood glucose information to Glooko’s cloud-based platform using the company’s simple universal cable (compatible with 29 glucose meters) and mobile app (Android and iOS). Population Tracker then aggregates the data in a single dashboard and presents flags if any of the above occur (see picture below). The flags show up on the top of the dashboard – Glooko told us that providers did not want the intrusiveness of email or texts. The first version of the system only contains the aforementioned four flags, though future systems could allow for customization. The company told us that the biggest challenge in developing the product was identifying the first set of flags – certainly, we imagine clinician, payer, and health system opinions varied widely on what cutoffs to use.

Glooko will provide payers and health systems with this software in exchange for a monthly/per-patient fee. The system is in soft launch now and will be rolled out officially at HIMSS next week. The first health systems to use the new product will be Scripps and Joslin and several payers/health systems are in the pipeline to follow. This payer-focused business model is one that WellDoc has also adopted with its BlueStar system, and we look forward to seeing which forward-thinking payers jump on board.

We most like that the system enables diabetes care and support between in-clinic visits, a major unmet need. In addition, Population Tracker can really help payers and health system identify patients in trouble before a severe event occurs – such proactive management has the potential to keep patients out of the hospital and save a lot of money for the healthcare system in the long run (severe hypoglycemia in type 1s in 2009 cost $1 billion in the US alone). Of course, Population Tracker rests on patients actually uploading their glucose data and care managers actually looking at the dashboard – both factors are certainly easier with Glooko’s system, but they are not a given by any means. That said, the focus on payers and health systems could enable some valuable incentive programs to ensure patients and providers actually use Population Tracker (e.g., if you upload once a month, you get $100 off your premium).

• Population Tracker is part of Glooko’s FDA-cleared system (cloud-based platform, mobile app, and universal MeterSync cable). This new tool required an “additional notes to file.”
• The time-in-range flags (25% >250 mg/dl and 10% <70 mg/dl) will only be triggered if the 30-day value exceeds the cutoff points. In a scenario where a patient’s 30-day time in range is 5% <70 mg/dl, though the last seven days have 15% of values <70 mg/dl, there would not be an alert. However, if there was even one reading <50 mg/dl, a ‘marked low’ alert would be triggered. We imagine different providers and payers will prefer different cutoff points, meaning customization will be a key addition in future generations of Population Tracker.
• This news follows the January announcement of Glooko’s innovative partnership with Joslin. As a reminder, the two organizations will jointly develop and deploy a new web/mobile-based diabetes management platform. The system will combine an in-development “Virtual Joslin” service with Glooko's existing universal MeterSync download cable/mobile app/web platform. Notably, "Virtual Joslin" will allow care teams to remotely monitor, coach, and guide diabetes patients between in-clinic consultations. In addition, the system will use pattern recognition algorithms to predict when patients are at risk for severe hypoglycemia or other complications, thereby triggering provider interventions Joslin and Glooko are actively developing the first module of this system, and a concept is expected at ADA 2014 in San Francisco.

Figure 1: Population Tracker Example Dashboard

--by Adam Brown and Kelly Close