ETel Telephony Mashup Finalist?

Golleee. I'm a finalist in E-Tel's Telephony Mashup contest in San Francisco.

When I met Dave Nielsen at the mashup camp at MIT last month, he told me that they were sponsoring a mashup competition at the O'Reilly Emerging Telephony Show, and that I should submit something. Since I've been doing way too much business stuff lately, I jumped at the chance to strap on my keyboard and submit an application not to win, but to have some fun, prove a point and to see what happens when you take these wonderful Web technologies and smash them into the telephony world. Although I think the judges had some sort of group dementia when they nominated me as a finalist, I'll take it, just the same.

My business is in consulting and custom development. I'm really not interested in going into this space, so I'm going to post the source code and documentation after the show, so you can take it, extend it, whatever. I'm just doing this to learn and to teach. So, what's the application?

Application name : After Hours Doctor's Office

Business Problem : If a patient is sick after normal office hours, the only choices are to call the answering service to schedule an appointment for the morning, or to go to an emergency room. Many patients are unaware of which is the right choice, so they end up going to the emergency room needlessly, which not only drives up costs for the HMO, but also gives a lower quality of care for the patient and every other patient waiting in the same room. An easy-to-use, triage system to determine the proper course of care would result in faster service, lower costs and healthier patients.

Customer Experience : Mr. Kraus feels sick and dizzy, with a little left side weakness on a Tuesday night. He calls his doctor, Dr. McCarthy, to schedule an appointment for tomorrow. An IVR answers, telling the caller that it's after hours, and asking if the call is because of routine business or because of illness. If illness, it asks if the caller is on a cell phone or not. It then asks for a voice message to be relayed to the doctor, then hangs up.

Immediately after the call is over, the patient gets an SMS message on their cell phone telling him that the call was received, and that we are forwarding the message over to the nurses. If the caller is calling from a PSTN phone, we would do an outbound call back. (I couldn't do this one, because I'm not a real Tell Me developer, and outbound dialing is restricted for those who aren't.) The message is sent to a bank of nurses, who listens to the message to determine if it's urgent or not. If they think it is routine, they indicate that on their console, which results in another message being sent to the cell phone telling the patient that the matter is probably routine, and they would get a call in the morning. If urgent, the patient would get a message like "A nurse thinks you need to speak with a doctor. We are looking for one now - stay near the phone." Urgent issues are forwarded to the doctor as an SMS message to their cell phone with a summary of the call done by the nurse. In this example, the doctor's message would be : Mr. Kraus - 40 WM - left side weakness, nasuea -508 364 9972. The doctor would simply press the send button on his phone to call the patient.

At no time would the patient be more than a few minutes from feedback, and make the prospect of going to the emergency room so slow and painful, that they would prefer to sit and wait for the text message to get back.

The Mashup Components :

1. Tell Me VxML for the inbound calling IVR, the outbound status messages if I was a developer and to record and post the patient voice message.
2. Strike Iron Global SMS for the text messaging between patient, nurse and doctor
3. Amazon Web Services to setup the bank of nurses making determinations of urgency, and to transcribe the original voice mail by the patient for the permanent medical record.
   

Compelling Business Ideas and Notes :

1. Using IVR on the front end gets the critical information from the patient quickly and without asking for new patient behaviors, all without a real human doing anything.
2. Using a bank of amazon turk nurses leverages the tens of thousands of stay at home nurses with small children who wouldn't mind making $3.00 in two minutes by listening to a voice message and determining if it's important or not.
3. A typical doctor might have ten calls a night, which is not enough volume to pay an on-site nurse. A thousand doctors have ten thousand calls a night, which supports an amazon turk community easy.
4. An HMO would pay $300.00 to keep a non-urgent patient out of an emergency room.