Heart Disease and the Internet of Me

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Executive Summary: Heart Disease and the Internet of Me

***Note to Venture Lab peer feedback providers***

Thank you for your time. This is a very comprehensive document, and while we do not expect you to read and process the entire document, we would appreciate feedback on a few key areas that are in BOLD AND ALL CAPS below: SOLUTION, PROCESS, CUSTOMER SEGMENTS, REVENUE MODEL, CUSTOMER ENGAGEMENT, BUSINESS MODEL CANVAS (BMC). The rest of the material is to provide context and will add insight to your overall comprehension of our proposed solution.


Cardiovascular disease is the leading cause of premature death in the world and will account for about 20 million (approx. 30% of all deaths) worldwide by 2015 (WHO). Due to the asymptotic nature of many cardiovascular diseases more than 30% of all cases go undiagnosed in the US and the numbers are even higher in developing nations.

Cardiovascular disease (CVD) is comprises of a very large set of conditions and diseases. From a medical perspective, heart disease includes coronary vascular disease (the vessels supplying blood), myocardial functional disease (the actual muscle of the heart), valvular disease (the flow of blood through the heart) and arrhythmias (cardiac electrical signal generation and propagation throughout the heart). Congestive heart failure (CHF) indicates poor performance of the heart and develops when significant muscle damage or dysfunction occurs.

Exhibit 1


We believe a proactive approach will be most effective in solving this pervasive problem. Hence aim to focus on surveillance, detection, early diagnosis and ongoing monitoring to detect exacerbation of CVD using technology. It is also in line with WHO’s 3 pronged approach to managing CVD globally.

Exhibit 2

With advances in medical science, technology, connectivity and years of research there are multiple programs and solutions available to for diagnosis and management of CVD.


We looked at existing solutions and created a mind map of the many possibilities (Exhibit 3). There are a wide variety of solutions available which address different populations of diagnoses and undiagnosed people.

However, the root cause of these diseases is often an accumulation of personal decisions, genetic causes, and environmental influences. Earlier diagnosis/detection leads to earlier intervention, better patient management, and prevention of hospitalization, morbidity, and readmissions following discharge.

Exhibit 3


We enable a person to create a personal cardiovascular health profile by connecting all biometric devices and other health data in a consolidated profile available on your personal device or on the cloud. The data collected is analyzed and your cardiovascular health is displayed through easily understood visuals and dashboard metrics. We also convert this data into meaningful information and provide the patient with their CVD risk index. This information can easily be shared with you’re your doctor, healthcare team or your family. 


We will constantly and automatically accumulate personal data from a wide variety of devices (biometric sensors, ingestible / implantable devices, self-entry, etc.). We will store this data accumulated

  1. Run algorithms, create metadata
  2. This information will be disaplayed to the patient in a visualize dashboard
  3. We will also enable different tools to run tests


Our key customer segments are:

  • 50+ patients
  • The worried well (healthy individuals who monitor their health actively)
  • Caregivers
  • Diagnosed CVD / diabetic patients


  • Insurance companies (will not share data with insurance company)
  • Employers (will not share data with employer)
  • Revenue share with 3rd party app providers to integrate with our solution
  • Revenue share with device manufacturers to integrate with our solution
  • Sell to healthcare providers/ACO’s to help them improve health outcomes for their patients
  • Advertising


  • Maintaining a vibrant presence in the mobile health industry by managing our brand identity in various social media networks and health organizations
  • Partnerships with health-related enterprises
  • Through cardiac focus groups


Two of our team members are healthcare professionals, Lukasz who is a cardiologist and Abba who is a nurse. They provided their perspective on key stakeholders below:

Healthcare providers

  •  Healthcare providers see many patients in a day so there's a need for a solution that can provide convenience, ease-of-use, efficiency, and peace of mind and thus, allow them to be more productive.
  • Healthcare providers also want to augment their capabilities so solutions that are capable of diagnosing diseases and predicting possible adverse events would be very helpful.
  • Real-time information can help healthcare providers make decisions regarding the care of their patients.
  • Caregivers (professional, family member, or both):
  • Sometimes there is a need to have extra assistance regarding the use of health technologies with older patients, so we will train their caregivers in the use of the healthcare solution. These caregivers are usually trusted by the patients and they are with them most of the time. Also, some patients are more than happy to have someone take charge of their healthcare needs so this would be an ideal situation for us to train caregivers in the use of the solution.
  • Currently physicians have to collect health information from different sources before taking clinical decision. A tool that could support them in this process could decrease risk of error and improve their effectiveness.
  • There are number of personal tools which monitor patient activity (incl. medical diagnostic instruments, health applications, activity tracking tools, life-style applications), most of the information collected this was never reached the eye of the physician. The proposed solution will change this, but allowing caregivers to have a deep view into all health&activity information.


  • Patients and their loved ones find it hard at times to understand the effects of their health condition so being able to provide real-time data and giving them updates as necessary will help in making them more aware and make more sense of their situation.
  • There are patients who will take steps to change their behavior only after they face facts and figures about their state of health.
  • Reduction of risk factors of CVD requires continues patient involvement and effort to make many small changes everyday. Giving a wider perspective of the current status and the desired therapeutic goal will help to increase motivation and self-confidence.
  • The patient perception of his/her own health status is often distorted by confounding factors, such as current symptoms, level of medical experience, social background. Having an objective snapshot of health related parameters can help optimize individual performance and facilitate better decisions.


Brainstorming of potential solutions

There were four choices we discussed:

  1. a wearable device, which monitors important body functions and send an alarm only, if action is needed. Otherwise you have carefree life style.
  2. an integrated system where all of the wearable medical electronics and apps can plug in. The organization of "TheInternetOfMe"
  3. alternative ways to get at heart disease - inflammation, hypothyroidism thyroid disease and heart disease 
  4. a social support system

There were four choices we discussed:

  1. a wearable device, which monitors important body functions and send an alarm only, if action is needed. Otherwise you have carefree life style.
  2. an integrated system where all of the wearable medical electronics and apps can plug in. The organization of "TheInternetOfMe"
  3. alternative ways to get at heart disease - inflammation, hypothyroidism thyroid disease and heart disease 
  4. a social support system

We picked the (2) "Internet of Me" solution. Primarly focused on cardiovascular tracking, but the system could be generalizable. Essentially the system would contain the following components:

  • Stage 1 accumulate data (automatically from sensors, ingestible / implantable devices, self-entry, etc.)
  • Stage 2 store data
  • Stage 3 run algorithms, create metadata
  • Stage 4 display on dashboard
  • Stage 5 / Stage 6: different tools to run tests

Then our team had an extended discussion around what this would look like. There were several points of contention:

  1. How frequently should the user interface and engage with the platform? Gerd, Vincent and Shawn were in support of creating an addictive system that hooks the user to keep on coming back (Facebook style). Paul was in favor of a more off the radar system that intervened when there was a problem. Shawn could see value in this as we want to really fit into a patient's lifestyle and not require them to adapt a new tool into their limited time and attention. But we also want to keep them engaged. We thought of giving the user the option of being as engaged as they wanted (opt-in), starting off at a minimal level of engagement in terms of notifications, etc.
  2. How should we monetize / get revenue streams? We discussed several options. Paul had an interesting diagram to help:  
  3. Who are our customers and who should we prove value to? Initially we thought they were consumers/patients. But we thought we could use this as a referral system. We could offer patients the options of paying for the ability to have their data analyzed by an expert. Perhaps a MD or a nurse practitioner. Or it could even serve a clinical decision guidance metric that experts like healthcare professionals could pay for, perhaps through a hospital GPO.
  4. Which patients should we pursue? The worried well are an obvious target, but what about the patients with the real problems, chronic care patients? Perhaps we offer this through an employer. Perhaps through an insurance company. The idea is we need to make it easy for people to join regardless of their profile. 
  5. What types of devices should plug into the system? We wanted to make it generalizable. Some people mentioned AliveCor's pocket ECG. But we need easy ways for people to get their data through sensors or other mechanisms.
  6. What format should we present the data? One interesting idea Vincent had was essentially a customized magazine Flipboard style for each patient based on their profile to give them tips on what to do.
  7. Where should we store the data? Vincent and Shawn were in support of the cloud (AT&T mHealth), Paul and Gerd were in support of a personal storage hard drive. We all supported that the patient should own the data. There was some talk of making it open source. Vincent had a concern of people reverse engineering our algorithms. We were still split at the end of our discussion.
  8. How secure should the data be? If the solution is in the US we may need HIPAA compliance. If not then we may have more flexibility. However we still need to make sure the patient owns the data and that it cannot be accessed by outside parties. HIPAA requires us to trace how the data is transfered between individuals so makes it complicated.
  9. How much data should we collect? We went back and forth. We estimated 3-6 GB would be required for personal data, but is all the data required. Shawn mentioned "smart" data collection instead of collecting every bit of data.


After the product discussion, we discussed two different approaches to our business model, cloud storage and local storage with peer to peer sharing. Please see below for 1) our cloud storage BMC and 2) our local storage / P2P BMC. Pictures of the BMCs pasted below, or can be accessed on the web for easier viewing here: http://canvanizer.com/canvas/6kydlJs3Kmo , http://canvanizer.com/canvas/zDq7OINmDGw

BMC 1: Cloud Storage (Solution we picked to move forward with)

BMC 2: Local Storage / Peer to Peer


As mentioned in the brainstorming section, we collaborated with Vincent Youmans, who was able to provide us with valuable technical insight and feedback. Below is some information from him regarding the technical implementation of our solution in the US and potentially around the world. In the US there are certain restrictions around patient data security (HIPAA requirements). In other parts of the world like the EU, patients cannot own their own data. Regionality is key, but we hope the cloud solution will help with scaling.

HIPPA COMPLIANT cloud solutions include:

  1. ATT mHEALTH. https://mhealth.att.com/ .

    1. They are still in beta: https://mhealth.att.com/dev/status

    2. They include a Justification for their services here: https://mhealth.att.com/dev/why

    3. I have used the system, and I believe the philosophy is sound.

  2. Qualcomm Life  http://www.qualcommlife.com

    1. Appears to be more mature than ATT mHEALTH

    2. Concept is same as ATT mHEALTH.

  3. Verizon

    1. http://www.verizonenterprise.com/industry/healthcare/

  4. LayerdTech

    1. http://www.layeredtech.com/compliant-hosting/hipaa-compliant-hosting/


One of the benefits to using ATT over the other data stores is that they are new and willing to promote projects with the mHEALTH brand name ( marketing strategy).  It is also very inexpensive. Hunderds of transactions per penny. As a typical patient will have 4 to 10 transactions per day, cost per user will be less than $1/month.  


In areas outside the US, and protection of Patient data is “Different as oppose to not nessesary”, then we have other options. In almost all cases, it will be a cloud data store with data encryption. As the project will be running on Mobile Smart Phones, in areas that may or may not have a WiFi or other connection to the Internet, a store and Forward approach will be used.  CouchDB, a noSQL document store with simple replication features is most likely solution.  Host cost is less than ATT, highly secure, but not HIPAA compiant.


The purpose of this section is to demonstrate that this project can scale vertical, and horizontally across geographic regions, at minimal costs by using disruptive trends and technologies.

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