Brown2020

Emerging infectious diseases that start with a fever or a rash can pose a risk to public health because they might not be recognized at the early stages when containment or treatment is possible. After September 11, our fears were stoked by anthrax. Then came SARS, and we still wait anxiously for bird flu.

A patent recently issued to Health Hero Network describes a simple but powerful idea that addresses the pandemic challenge by enabling near-real-time syndromic surveillance that can be adapted on the fly. Easy-to-navigate survey devices collect data from hospital waiting rooms, school nurses, and other points of care. The survey script can be changed and updated remotely by public health authorities based on the latest information. The devices report data to central computers that look for any unusual patterns and then alert public health authorities immediately so that they can investigate further.

Disease outbreaks that look like the flu at the beginning can be hard to detect early because flu-like symptoms are common and are not always reported. The first cases of an outbreak may be spread out over many different clinics, hospitals, and schools in a metropolitan area. Unusual patterns might emerge only when looking at a broader cross section of a region. The other challenge is that we may not know what data is relevant and important at the beginning stages of an outbreak. Where it might have been fever, rash, and working in a mail room for one threat, it might be diarrhea and travel to a specific region or eating a particular food in another threat.

While many efforts have been discussed and may even be underway to facilitate early detection of outbreaks by sifting through electronic medical records and pharmacy data, the most important information might be missed because no one knew to ask the right question. When we do figure out what question to ask, we won’t have time to add fields to medical records or change forms. Our public health authorities need the ability to change the script as soon as they learn new information.

Despite the simplicity of the approach, it is not easy to organize health systems around new ways of doing things. On the other hand, maybe we won’t need to. Public health surveys could be pushed to iPhone users, for example. There just might be enough iPhones out there by now to provide a statistically significant sample size enabling highly sensitive early detection of potential public health emergencies. If you want to read the patent, you can find the full text here.

Originally filed in 1996, this patent is among the first to describe online auctions.

United States Patent: 7,277,867
Issued: October 2, 2007

Abstract

The invention presents a method for conducting an on-line bidding session to accumulate a collective bid for a property. The bidding session is conducted over a computer network that includes a central computer, a number of remote computers, and communication lines connecting the remote computers to the central computer. According to the method, at least one bidding group is registered in the central computer. The bidding group can be an association, institution, or group of investors formed for the purpose of bidding together for the property. The bidding group has a total bid for the property which is tracked in the central computer. The central computer receives bids entered from the remote computers by members of the bidding group. Each bid includes an individual bid amount which is contributed to the total bid of the group to accumulate the collective bid for the property.

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If you can model a disease like diabetes, then you can build better systems and devices like insulin pumps to help control it. You also can teach people how to control it better themselves.

United States Patent: 7,167,818
Issued: January 23, 2007
Assignee: Health Hero Network Inc.

Abstract

A system and method for predicting the effect of patient self-care actions on a disease control parameter. A future disease control parameter value X(t.sub.j) at time t.sub.j is determined from a prior disease control parameter value X(t.sub.i) at time t.sub.i based on an optimal control parameter value R(t.sub.j) at time t.sub.j, the difference between the prior disease control parameter value X(t.sub.i) and an optimal control parameter value R(t.sub.i) at time t.sub.i, and a set of differentials between patient self-care parameters having patient self-care values S.sub.M(t.sub.i) at time t.sub.i and optimal self-care parameters having optimal self-care values O.sub.M(t.sub.i) at time t.sub.i. The differentials are multiplied by corresponding scaling factors K.sub.M. The system includes an input device for entering the patient self-care values S.sub.M(t.sub.i). A memory stores the optimal control parameter values R(t.sub.i) and R(t.sub.j), the prior disease control parameter value X(t.sub.i), the optimal self-care values O.sub.M(t.sub.i), and the scaling factors K.sub.M. A processor in communication with the input device and memory calculates the future disease control parameter value X(t.sub.j). A display is connected to the processor to display the future disease control parameter value X(t.sub.j) to a patient.
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