A Virtual Nurse to Improve Your Medicine

on June 24, 2015
Reading Time: 3 minutes

Sense.ly logoMany of us have dealt with prerecorded treatment voices at medical centers. And many of us have found it frustrating, and worse if the situation seems bad, before you get to talk to a skilled human being. But the situation is getting a lot better as the virtual “professionals” take advantage of rapidly increasing action to provide both faster treatment and more efficient, lower cost.

One of the most interesting is Sense.ly, a new service built on top of the code designs offered by Expect Lab’s MindMeld service. The goal is to build highly accurate, thorough voice services on top of data, language understanding, machine learning, continuous processing, and user interface over devices.

We’re ready for help. “There’s a lot of need for action,” says Sense.ly CEO Adam Odessy. “One problem is frequency. We need to communicate and limit the amount of direct contact. We focus on long-term process, Natural language is key to developing to virtual nurse. The overall goal is to communicate more and reduce cost. In the end, we always need a nurse or doctor, but we can eliminate a lot of cost.”

MollySense.ly is built around a virtual nurse named Molly–somehow a bit cuter than necessary and with just enough machine-generated language you are certain it isn’t a real human being on the other end. The initial plan is to set up systems for three areas of medicine–medical institutions, including hospitals and other clinic setups; insurance companies, and pharmacy companies.

They all stand to profit, although their roles are different. Medical institutions, obviously, are designed to get treatment to patients and will certainly seem more useful for consumers. Insurance companies hope to collect large amounts of information that shows them what is going on in the field, designed to distribute service–and to lower the costs. The pharmacy is interested in collecting information, often in the form of inquiries from current patients, to monitor, gather information, and distribute drug use.

The effective use is both the cleverness of the human-like robot helper at the clinic with increased ability to collect the most useful information, especially when it can be collected using mobile devices to provide information about patients. A goal is to make it possible for the service to constantly remember data, especially useful with the ill and aging patients.

Three services demonstrate some plans that combine information provided by devices and discussions with Molly:

Congestive heart failure solution: The practice is designed to collect critical information and deliver close CHF information to the caregivers based on devices and conversations. Data tests include daily blood sugar and blood pressure, diet monitoring, and weight tracking.

Diabetes solution: The most effective way to treat diabetes is to collect daily information to keep close track of glucose levels, designed to both improve diabetes itself and lower the risk of heart conditions. The roles of patients and devices include daily glucose measurement, blood pressure, ocular examination, and podiatrist health.

Behavior health solution. This gets a little out of the normal treatment field. The goal is end-to-end behavioral treatment for patients, including automatic assessments defined by clinicians. Steps include reports of daily symptoms, daily photos of patients, compliance monitoring, and regular guidance manuals.

The goal is to use as many technologies as possible, working through phones, tablets, and PCs. The hope is in making Molly’s avatar role as human as possible, with  speech-recognition conversation as normal as possible. Using data collected by patients and by wired or wireless devices is critical. And video and augmented reality sent to patients can help in treatment.

A number of large players are involved in Sense.ly already including the UK National Health Service, University of California San Francisco, Kaiser Permanente, Universidad Nacional Autónoma de Mexico,  Novartis, Allscripts, Panasonic, and Microsoft.

And, of course, the efforts must comply closely with the rules imposed by the government. Everything is built around Health Insurance Portability and Accountability Act requirements and Sense.ly has been working the HIPAA requirements for the past year and a half of development to qualify.

A step is likely to assist the development of programs built on MindMeld and Sense.ly, as well as competitors in the works, is likely to take continuing service from ever more capable devices, phones and watches as well as specialized equipment for IoT services.

Apple is not a part of the Sense.ly project but the company is using the new HealthKit software to help bring in roles for iPhones and Apple Watches. “HealthKit is combining integration,” says Sense.ly’s Odessky. “It provides additional vital signs and better data. We look forward to everything from everything from cameras to observer stuff like FitBit to get more precise information.”

The use of health services from IoT based data studies to devices with ever more accurate information of patients’ medical services is a big deal and it is one of the best ideas for remote devices. Better and more efficient could be a real winner for everyone.