Voxiva provides the technology platform, professional services and support needed for designing and deploying a mobile-based health solution for consumers. When you read that, think beyond the now-hip smartphone app market. Less than a fifth of mobile handsets out there are smartphones. So to reach the remainder, the solution has to encompass relatively simpler mechanisms like feature-phone data entry, SMS and IVR.

There are a number of unique design challenges for creating an engaging public health solution that can work across any/most devices and be delivered through multiple channels to a varied set of end-users. It needs to work synchronously across web, mobile, email. It should support data entry across all kinds of user interfaces (feature phones, smartphones, different mobile operating systems, multiple-languages, etc). It needs to deliver real-time alerts (SMS, voice, email, web portal) and provide real-time analysis for decision-makers. And obviously be scalable and dependable with near-100% uptime. What appears to be a simplistic low-end IT solution on the surface is really a huge undertaking to communicate with an end-user population that is as diverse as it can be.

Voxiva’s real impressive achievement is doing a lot of what they do in international market- specially developing countries. They have created a HIV/AIDS mHealth solution for Rwanda Ministry of Health, disease surveillance solution for Peruvian military, diabetes management program in Mexico, and plenty of others. In US, their most famous offering was Text4Baby (see Multiplyd’s previous review on it), an SMS-based maternal health education service launched in early 2010. Since then, they have diversified into Text2Quit (smoking cessation) and Care4Life (diabetes management). Simple interventions, but designed for massive implementation and adoption. Which is why Voxiva continues to stand out.

According to the National Association for Home Care, about 12 million people in this country receive care from more than 33,000 home health care providers. The market is made up of few large, publicly traded companies (see LHCG, AFAM, AMED stocks for example) and many small/mid-size players. The challenges faced by these companies are typical of those with field-based employees: scheduling the visits, then figuring out if their employee actually visited the patient, if they did then what was the real time and mileage, ensuring the data collected during visit is archived and accurate, etc.

Which brings me to CellTrak. It was founded in 2006 and delivers mobile-based automation to Home Healthcare agencies. I think it’s a brilliant application of healthcare information technology for alleviating self-reported information issues and paper-processes in a niche market. Given that everyone carries a phone today, using mobile modules to increase compliance and productivity makes a lot of sense for a field-based business. Some examples of the modules available:

• Care Plan Management
• GPS and Directions
• Time and Attendance
• Travel Time and Mileage
• Supply Management
• Alerting and Messaging
• Scheduling
• Nurse Care
• Wound Care

Solving logistical issues like location, time capture, attendance, inventory etc. is pragmatic. But providing modules around clinical care is the more interesting strategy from my perspective. Usually, software solutions that enable care documentation and collaboration are associated with either care-delivery enterprises (e.g. fixed location hospitals using EHRs) or with patients themselves (e.g. PHRs). Neither of those have a particularly critical need to be consumable in a mobile form-factor- that is just a nice-to-have functionality. CellTrak has found a special need where the inherent care delivery workflow necessitates even the clinical Healthcare IT solution to be exclusively mobile. It is a good example of the hidden corners within the complex maze of healthcare system which require thinking outside the traditional bounds.

Other examples of using exclusively mobile-based electronic health records are mostly restricted to public health context in developing countries (see ChildCount for example). That skew is mostly due to the field-based nature of public health and mobile being the primary means of connectivity in emerging economies. With CellTrak, we see the same technology paradigm tackling the problems of a conventional health industry segment in a developed country.

CellTrak partners with some EHR (Cerner, Allscripts) and wireless providers (AT&T, T-Mobile, Sprint, Verizon) currently. I expect that the future iterations of most enterprise EHRs would include incorporating a solution like CellTrak which enables running operations in the field and  seamlessly connects health information to/from a mobile workforce.

Child Count is an mHealth platform developed by the Millennium Villages Project aimed at empowering communities to improve child survival and maternal health. It facilitates the activities of field-based community health care workers in Africa.  Using any standard phone, these workers are able to use text messages to register patients and report their health status to a central web dashboard that provides a real-time view of the overall community health. This enables an automated system that helps reduce gaps in treatment (sms-based rapid diagnosis, follow-up reminders etc.).

ChildCount is open-source. It’s built with RapidSMS, a  framework that manages data collection, complex workflows, and group coordination using basic mobile phones. This short video does a good job of explaining the overall project and technology.

Public Health interventions are often based on simple logic, but have far-reaching effects. Screening regularly for malnutrition, malaria, diarrhea, etc. requires relatively simple documentation and measurements- making it perfect for sms-based communication. Even keeping a simple registry of births, deaths, immunization status enables local health teams and organizations optimize their efforts. Care delivery organizations in developed countries should also think about integrating the mobile platform into their services- its a great way to interact and keep in touch with patients. Medication adherence is a good example. NCPIE‘s 2007 report states that poor medication adherence is almost a crisis, costing $177B annually. Almost any population care management topic (outreach, screening, compliance, etc) would be a good use case.

Child Count is in good company -there are many interesting mHealth applications out there that deserve mention. The mHealth wikipedia page has a good running list of some applications. I’ll continue to post about what I discover and like.

It’s a public private partnership that provides this educational program. The list  is impressive: CTIA,  HMHB, Johnson & Johnson, WellPoint, Pfizer and CareFirst BCBS, BabyCenter, George Washington University and MTV Networks among others. U.S. government partners include the White House Office of Science and Technology Policy, the Department of Health and Human Services and the Department of Defense Military Health System. The mobile health platform is provided by Voxiva and fifteen U.S. carriers have agreed to carry the program’s text messages at no cost for two full years.

91% of US residents have a cellphone, compared to 22% that have internet connectivity. Educating pregnant women and new moms with information they need to take care of own and baby’s health is a powerful preventive measure. So there is reach and utility in this idea, no doubt.

Note: Found interesting background about Voxiva. They started in 1999 with the idea that mobile phones were going to play an important part in health going forward. They now have a technology platform and provide mobile health solutions in about 14 countries (mostly developing countries like India, Mexico, Rwanda, Peru). They market and sell to public health agencies and government providers usually, but are moving into pharma and provider networks now. An insightful interview with their founder here.

At the heart of the model are a set of ordinary and differential equations that represent the physiological pathways relevant to diseases and their complications. The ‘variables’ in this model include signs, symptoms, patient behaviors (including adherence), provider behaviors, provider performance, encounters (e.g.  ER visits, office visits, admissions), protocols, guidelines, tests, treatments, etc. Basically, it tries to incorporate all aspects of diseases and healthcare system that are needed to analyze downstream clinical outcomes, utilization and costs.

A more loaded one-line description of Archimedes (taken from his original paper in 2002): “It’s an object-oriented, continuous-time, full simulation model for addressing a wide range of clinical, procedural, administrative, and financial decisions in health care at a high level of biological, clinical, and administrative detail.” Phew. I’ll confess that I don’t know what exactly is under the hood. But I know enough about the informatics field to believe that this approach is viable and very exciting.

This YouTube video explains how the model can be used to run virtual clinical trials. Kasier has already backed the findings of Archimedes to change their diabetes care delivery.  I think there are fantastic, unlimited opportunities for applying such a fundamental model to medicine- personalized health predictions, public health, health policy, cost-effectiveness and what not.  As a startup, they are doing fine. With an impressive list of partners/clients, and a $15.6M RJWF grant (2007), they have a good runway and momentum. They have all the right ingredients to be a change agent for next-generation Healthcare IT.

Jan 2011 Update: The FDA and Archimedes entered into a research agreement to understand the benefits of weight loss compared to the long-term risks of cardiovascular outcomes in patients treated with weight loss drugs.

In case you didn’t know, Google.org is the philanthropic arm of Google, and it was formed with the commitment of 1% of Google.com’s profits to address some of world’s most urgent problems (read the famous 2004 IPO letter by Larry and Sergey where they mention it). The site humbly admits that the Flutrends system is experimental. Nevertheless, it’s impressive that in some instances Flutrends was actually predicting flu before CDC.

Of course, not all people who search for flu have flu necessarily, but the power of this analysis comes from the coverage and promptness, not the granular accuracy. The basic idea of harnessing the collective thought (a.k.a. search needs) of the population to predict/monitor health events is fantastic. And this is just the beginning, IMHO. When a population is connected real-time and discussing what they think/want/need, abstracting that information can yield powerful insights- not just for prediction and monitoring, but for most aspects of healthcare (diagnosis, prognosis, news, followup etc).

The concept is applicable to domains outside of healthcare too. Take twitter for example. Twitter is another platform with mass adoption where people are having real-time conversations about what they are thinking/doing. Just look at what intelligent twitter mashups did for getting real-time snow report of the Feb’09 storm in UK or the Dec’08 Ice Storm in New Hampshire. There are health related examples too- the feb’09 salmonella-in-peanut-butter recall could be tracked promptly on a Twitter feed (btw, this slideshare presentation by PF Anderson at the University of Michigan explains ‘Twitter for Health’ in detail. Thanks to Christine Gorman for the link).