This document summarizes Rubix Health's progress over 5 days of customer interviews and business model development. On day 5, they conducted 10 interviews for a total of 54. Their product aims to automatically translate physician diagnoses into billable codes. Through interviews, they identified 4 key customer segments and learned coding takes significant physician time. Their MVP and future plans focus on demonstrating value through partnerships with hospitals and physicians to test their natural language processing engine.

1. RUBIX HEALTH
Chaitanya Kanitkar (ck2565)
Abhinav Mishra (anm2147)
Day 5: 10 Interviews
Total Number: 54 Interviews
A Fully-automated Web Platform for transforming a physician’s
diagnosis into billable codes

2. Here’s what we thought
 Direct Distribution Channel is what makes most sense to sell
our product to physicians in hospitals and in private practice.
SquareSpace
&Website
Domain
HIPPA Cloud
Platform for
NLP Engine
and WebApp

3. Customer Segments
Private Practice Physicians
• Much less patients/record to deal with
• Are more willing to use new EMR/EHR
systems with coding inbuilt
• Still spend around half an hour each
day on medical coding
• Less Important
Physicians in Hospitals/ITAdmins
• Many patients to deal with
• Hospitals have spend 30-50 million dollars in
EMR systems (~4-5 years ago)
• Spend around 30mins-1 hr a day on coding
even though they have billers-> priority
• Physicians are required to hire billers and
pay 5-12% of the total payment
• Most Important

4. Here’s what we thought (cont’d)
 Our only channel was the web application running on a
HIPPA Compliant cloud.
 Primarily physicians would buy our product. Billing
departments in hospitals and billing outsourcing companies
were much less of a concern.
 The NLP Engine to translate billable codes would be hard but
with some knowledge is doable in a few months.
 That the main value propositions were simply efficiency/time
and money saved.

5. Business Model Canvas (Day 1)

6. Key
Partners
HIPPA-
Compliant
Cloud
Platform
• Aptible/Tr
ueVault
Hospital
Systems
• Wayne
State/Detr
oit
Medical
Center
Hospital
System
Key Activities
MVP
• Prototype the User Interface/Web
Platform
Advertising
• Emails/connect with hospital systems and
physicians (ex. Wayne State University
School of Medicine)
• Website consolidation
• Prototype sign-up list
Pitch
• Consolidate all work
• Consolidate doctor feedback
• Develop pitch deck
Coding Engine
• Research NLP algorithm to translate
unstructured doctors’ notes into billable
codes
Value
Propositions
Cost Reduction
• Reducing cost of
medical
reimbursement by
eliminating the
need for trained
medical coders
Convenience/Usabili
ty
• Fully automated
and consistent
coding engine that
translates doctors’
EMR diagnoses to
billable CPT/ICD-
10 codes
Customer
Relationships
GET
• Reach out to physicians, visit
hospitals, and get involved in
hospital networks
• Website to gauge & generate
interest in platform
KEEP
• offer consistent and high quality
service
• continually reach out to customers
for feedback
GROW
• Increase involvement in hospital
networks
• Government/larger hospitals
• Expand Services to include EMR and
extended billing service
Customer
Segments
• Private
practice
physicians
• Physician
groups
• Hospital IT
Admins
• Governmen
t
(Medicare/
Medicaid)
Key Resources
Financial Capital
• Friends, family, individual investment,
Angel Investors, Accelerators, VC
Human Capital
• Software Developers/Graphic Design
• Legal Advisor
• Marketing/Sales
• Doctors for testing
Channels
Web Application (Saas)
• Powered by a HIPPA-Compliant
Cloud
Cost Structure
• HIPPA-Compliant Cloud
• Human Resources (Developers, Designers, Marketers)
• Website Maintainence/Domain
Revenue Streams
SAAS
• Monthly/yearly subscription model
• Percentage of Reimbursement

7. Here’s what we learned:Confirming the Problem
• 5-12% of total collections going to billers-> lot of money!!!
• Doctors spending 30 mins-1 hour looking up codes every day
• It’s a big headache for doctors, especially for those who are at hospitals as
depending on their dept., they tend to have less control over the billing process

8. Here’s what we learned:Customer Segments!

9. Here’s what we learned:OEM
SalesTeam to
Partner with
Billing
Outsourcing
and EMR
Companies
NLP Engine
gets built and
becomes part
of software
package or
billing
consulting
service
Software is
sold by
distributor
companies

10. Here’s where we Ended: Customer Archetypes
Day 1Start Day 3Day 2 Day 5Day 4
1 Physicians
in hospitals
Value Prop: PlatformAgnostic,Cost Savings, Efficiency
2 Private
Practice
Value Prop: Smarter billing, small monthly cost, easier to test
EMR/
Billing
Companies
3
Competitors Value Prop: Use our NLP Engine as part of
their product, less billing experts needed
4
Hospital Bill
Dept./Informa
tics
Value Prop: Makes dept’s life a lot easier
when teaching new codes to doctors

11. Business Model Canvas (Day 5)

12. Key
Partners
HIPPA-
Compliant
Cloud
Platform
• Aptible/T
rueVault
Hospital
Systems
• Wayne
State/Det
roit
Medical
Center
Hospital
System
• Hospital
Billing
Depts for
testing
Key Activities
MVP
• Prototype the User Interface/Web Platform
Advertising
• Emails/connect with hospital systems and
physicians (ex. Wayne State University School
of Medicine)
• Website consolidation
• Prototype sign-up list
• Generate interest in research circles +
community forums-> crowdfunding
Pitch Customer Discovery
• Consolidate all work
• Consolidate doctor feedback
• Develop pitch deck Interview stakeholders
• Figure out how much physician groups are
actually paying for coders/billers
Coding Engine
• Research NLP algorithm to translate
unstructured doctors’ notes into billable
codes
• Sit with billers, coders, and physicians to see
what these diagnoses look like
Value
Propositions
Cost Reduction
Convenience/Usabilit
y
• Fully automated
and consistent
coding engine that
translates doctors’
EMR diagnoses to
billable CPT/ICD-10
codes
Platform Agnostic
Analytics
• Practice insights
obtained and
analysed to learn
what is successful
in practice
Customer
Relationships
GET
• Reach out to physicians, visit
hospitals, and get involved in
hospital networks hospital
billing depts, interest groups
for interest in testing
• Website to gauge & generate
interest in platform, website:
get early access
• have community forum for
billing
• commit to one or two
practices for dedicated
support
• generate research interest
KEEP
• offer consistent and high
quality service
• continually reach out to
customers for feedback
GROW
• Increase involvement in
hospital networks
• Government/larger hospitals
Customer Segments
Key Resources
Financial Capital
• Friends, family, individual investment, Angel
Investors, Accelerators, VC
Human Capital
• Software Developers/Graphic Design
• Legal Advisor
• Marketing/Sales
• Doctors for testing
Channels
Web Application (SaaS)
• Powered by a HIPPA-Compliant
Cloud
• Website/Forum/Blog
Cost Structure (above and below)
• HIPPA-Compliant Cloud
Revenue Streams (above and below)
***Private practice
physicians -> extend
SaaS into full revenue
life cycle management
Physician groups in
larger hospitals (these
hospitals usually have
separate departments)
Hospital IT Admins and
billing departments at
major hospitals
• Government
(Medicare/Medicaid
)
Consolidate doctor feedback, level of priority
learn about current EMR systems used in hospitals IT dept
Reducing cost of
medical
reimbursement by
eliminating/reducing
trained medical coders
Percentage of Reimbursement (5-8%), may prefer subscription model
Monthly/yearly SaaS subscription model (200-400 dollars),
less than what other EMR companies charge
web application
that requires no
extra installation
and is
independent of
EMR System
used
• Informatics
Departments
• Billing outsourcing
companies
• EMR Companies
EMR Companies: Dr.
Chrono, CareCloud,
EPIC, CureMD,
• ask private practices for alpha testing using EMR
• Human Resources (Developers, Designers,
Marketers)
• Website Maintenance/Domain

13. Why you should invest in us
 significant interest and need has been seen form multiple
customer segments
 minimally invasive and no IT infrastructure overhaul
 huge economic potential in terms of cost and time savings
for all customer segments
 opportunities to partner with smaller EMR startups as a
distribution channel (estimated 9 billion dollar market)
 NLP engine research can be catalyzed by initial funding and
testing at smaller practices and hospitals

14. What we need to do next
 develop functioning and detailed MVP to demonstrate basic
features
 generate significant interest in research communities through
website, blog, early access button
 shadow billers and coders to learn extensively the entire process
 get physicians directly involved as stakeholders in company
 NLP research: figure out details of algorithm
 partner with 1 or 2 hospital departments for testing purposes

15. Direct Distribution Channel:Website
 www.rubixhealth.com (community forum not included yet)
pl

16. THANKYOU!!

17. APPENDIX

18. Business Model Canvas (Day 1)

19. Key
Partners
HIPPA-
Compliant
Cloud
Platform
• Aptible/Tr
ueVault
Hospital
Systems
• Wayne
State/Detr
oit
Medical
Center
Hospital
System
Key Activities
MVP
• Prototype the User Interface/Web
Platform
Advertising
• Emails/connect with hospital systems and
physicians (ex. Wayne State University
School of Medicine)
• Website consolidation
• Prototype sign-up list
Pitch
• Consolidate all work
• Consolidate doctor feedback
• Develop pitch deck
Coding Engine
• Research NLP algorithm to translate
unstructured doctors’ notes into billable
codes
Value
Propositions
Cost Reduction
• Reducing cost of
medical
reimbursement by
eliminating the
need for trained
medical coders
Convenience/Usabili
ty
• Fully automated
and consistent
coding engine that
translates doctors’
EMR diagnoses to
billable CPT/ICD-
10 codes
Customer
Relationships
GET
• Reach out to physicians, visit
hospitals, and get involved in
hospital networks
• Website to gauge & generate
interest in platform
KEEP
• offer consistent and high quality
service
• continually reach out to customers
for feedback
GROW
• Increase involvement in hospital
networks
• Government/larger hospitals
• Expand Services to include EMR and
extended billing service
Customer
Segments
• Private
practice
physicians
• Physician
groups
• Hospital IT
Admins
• Governmen
t
(Medicare/
Medicaid)
Key Resources
Financial Capital
• Friends, family, individual investment,
Angel Investors, Accelerators, VC
Human Capital
• Software Developers/Graphic Design
• Legal Advisor
• Marketing/Sales
• Doctors for testing
Channels
Web Application (Saas)
• Powered by a HIPPA-Compliant
Cloud
Cost Structure
• HIPPA-Compliant Cloud
• Human Resources (Developers, Designers, Marketers)
• Website Maintanence/Domain
Revenue Streams
SAAS
• Monthly/yearly subscription model
• Percentage of Reimbursement

20. Business Model Canvas (Day 2)

21. Key
Partners
HIPPA-
Compliant
Cloud
Platform
• Aptible/Tru
eVault
Hospital
Systems
• Wayne
State/Detro
it Medical
Center
Hospital
System
EMR
Companies
• Examples
include:
• Dr. Chronos
• CareCloud
• Cerner
• EPIC
• CureMD
Key Activities
MVP
• Prototype the User Interface/Web
Platform
Advertising
• Emails/connect with hospital systems
and physicians (ex. Wayne State
University School of Medicine)
• Website consolidation
• Prototype sign-up list
Pitch Customer Discovery
• Consolidate all work
• Consolidate doctor feedback
• Develop pitch deck Interview
stakeholders
• Figure out how much physician groups
are actually paying for coders/billers
Coding Engine
• Research NLP algorithm to translate
unstructured doctors’ notes into billable
codes
Value
Propositions
Cost Reduction
• Reducing cost of
medical
reimbursement by
eliminating the
need for trained
medical coders
Convenience/Usabili
ty
• Fully automated
and consistent
coding engine that
translates doctors’
EMR diagnoses to
billable CPT/ICD-
10 codes
Platform Agnostic
• web application
that requires no
extra installation
and is
independent of
EMR System used
Analytics
• Practice insights
obtained and
analyzed to learn
what is successful
in practice
Customer
Relationships
GET
• Reach out to physicians, visit
hospitals, and get involved in
hospital networks
• Website to gauge & generate
interest in platform
• Showcase MVP to physicians
KEEP
• offer consistent and high
quality service
• continually reach out to
customers for feedback
GROW
• Increase involvement in
hospital networks
• Government/larger hospitals
• Expand Services to include
EMR and extended billing
service the whole revenue
life cycle management
(future)
Customer Segments
• Private practice
physicians -> extend
SaaS into full
revenue life cycle
management
• Physician groups in
larger hospitals
(these hospitals
usually have
separate
departments)
• Hospital IT Admins
and billing
departments at
major hospitals
• Government
(Medicare/Medicaid
)
Key Resources
Financial Capital
• Friends, family, individual investment,
Angel Investors, Accelerators, VC
Human Capital
• Software Developers/Graphic Design
• Legal Advisor
• Marketing/Sales
• Doctors for testing
Channels
Web Application (Saas)
• Powered by a HIPPA-
Compliant Cloud
Cost Structure
• HIPPA-Compliant Cloud
• Human Resources (Developers, Designers, Marketers)
• Website Maintenance/Domain
Revenue Streams
SAAS
• Monthly/yearly subscription model
• Percentage of Reimbursement

22. Business Model Canvas (Day 3)

23. Key
Partners
HIPPA-
Compliant
Cloud Platform
• Aptible/Tru
eVault
Hospital
Systems
• Wayne
State/Detroi
t Medical
Center
Hospital
System
EMR
Companies
• Examples
include:
• Dr. Chronos
• CareCloud
• Cerner
• EPIC
• CureMD
Key Activities
MVP
• Prototype the User Interface/Web
Platform
Advertising
• Emails/connect with hospital systems and
physicians (ex. Wayne State University
School of Medicine)
• Website consolidation
• Prototype sign-up list
Pitch Customer Discovery
• Consolidate all work
• Consolidate doctor feedback
• Develop pitch deck Interview stakeholders
• Figure out how much physician groups are
actually paying for coders/billers
Coding Engine
• Research NLP algorithm to translate
unstructured doctors’ notes into billable
codes
• Sit with billers, coders, and physicians to
see what these diagnoses look like and
how are the codes are inputted to doc
Value
Propositions
Cost Reduction
Convenience/Usabilit
y
• Fully automated
and consistent
coding engine that
translates doctors’
EMR diagnoses to
billable CPT/ICD-10
codes
Platform Agnostic
Analytics
• Practice insights
obtained and
analysed to learn
what is successful
in practice
Customer
Relationships
GET
• Reach out to physicians, visit
hospitals, and get involved in
hospital networks
• Website to gauge & generate
interest in platform, website:
get early access
KEEP
• offer consistent and high
quality service
• continually reach out to
customers for feedback
GROW
• Increase involvement in
hospital networks
• Government/larger hospitals
Customer Segments
Key Resources
Financial Capital
• Friends, family, individual investment,
Angel Investors, Accelerators, VC
Human Capital
• Software Developers/Graphic Design
• Legal Advisor
• Marketing/Sales
• Doctors for testing
Channels
Web Application (SaaS)
• Powered by a HIPPA-Compliant
Cloud
Cost Structure
• HIPPA-Compliant Cloud
• Human Resources (Developers, Designers, Marketers)
• Website Maintenance/Domain
Revenue Streams
SAAS
Private practice
physicians -> extend
SaaS into full revenue
life cycle management
Physician groups in
larger hospitals (these
hospitals usually have
separate departments)
• Hospital IT Admins
and billing
departments at
major hospitals
• Government
(Medicare/Medicaid
)
Showcase MVP
Consolidate doctor feedback, level of priority
learn about current EMR systems used in hospitals IT dept
Reducing cost of
medical
reimbursement by
eliminating/reducing
trained medical coders
• Government/ Larger Hospitals
• Expand Services to include
EMR and extended billing
service the whole revenue life
cycle management (future)
Percentage of Reimbursement (5-8%), may prefer subscription model
Monthly/yearly SaaS subscription model (200-400 dollars), less
than what other EMR companies charge
web application
that requires no
extra installation
and is
independent of
EMR System
used
• Informatics
Departments

24. Business Model Canvas (Day 4)

25. Key
Partners
HIPPA-
Compliant
Cloud
Platform
• Aptible/T
rueVault
Hospital
Systems
• Wayne
State/Det
roit
Medical
Center
Hospital
System
Key Activities
MVP
• Prototype the User Interface/Web Platform
Advertising
• Emails/connect with hospital systems and
physicians (ex. Wayne State University School
of Medicine)
• Website consolidation
• Prototype sign-up list
Pitch Customer Discovery
• Consolidate all work
• Consolidate doctor feedback
• Develop pitch deck Interview stakeholders
• Figure out how much physician groups are
actually paying for coders/billers
Coding Engine
• Research NLP algorithm to translate
unstructured doctors’ notes into billable
codes
• Sit with billers, coders, and physicians to see
what these diagnoses look like and how are
the codes are inputted to doc
Value
Propositions
Cost Reduction
Convenience/Usabilit
y
• Fully automated
and consistent
coding engine that
translates doctors’
EMR diagnoses to
billable CPT/ICD-10
codes
Platform Agnostic
Analytics
• Practice insights
obtained and
analysed to learn
what is successful
in practice
Customer
Relationships
GET
• Reach out to physicians, visit
hospitals, and get involved in
hospital networks
• Website to gauge & generate
interest in platform, website:
get early access
• have community forum for
billing
• commit to one or two
practices for dedicated
support
KEEP
• offer consistent and high
quality service
• continually reach out to
customers for feedback
GROW
• Increase involvement in
hospital networks
• Government/larger hospitals
Customer Segments
Key Resources
Financial Capital
• Friends, family, individual investment, Angel
Investors, Accelerators, VC
Human Capital
• Software Developers/Graphic Design
• Legal Advisor
• Marketing/Sales
• Doctors for testing
Channels
Web Application (SaaS)
• Powered by a HIPPA-Compliant
Cloud
Cost Structure
• HIPPA-Compliant Cloud
• Human Resources (Developers, Designers, Marketers)
• Website Maintenance/Domain
Revenue Streams
***Private practice
physicians -> extend
SaaS into full revenue
life cycle management
Physician groups in
larger hospitals (these
hospitals usually have
separate departments)
Hospital IT Admins and
billing departments at
major hospitals
• Government
(Medicare/Medicaid
)
Consolidate doctor feedback, level of priority
learn about current EMR systems used in hospitals IT dept
Reducing cost of
medical
reimbursement by
eliminating/reducing
trained medical coders
Percentage of Reimbursement (5-8%), may prefer subscription model
Monthly/yearly SaaS subscription model (200-400 dollars), less
than what other EMR companies charge
web application
that requires no
extra installation
and is
independent of
EMR System
used
• Informatics
Departments
• Billing outsourcing
companies
• EMR Companies
EMR Companies: Dr.
Chrono, CareCloud,
EPIC, CureMD,
• ask private practices for alpha testing using EMR

26. Market Opportunity
Total Available Healthcare IT Market:
$53.8 bn/year
• Growing at an annual rate of 16%
(MarketResearch.com)
ServedAvailable Market for Medical
Records and Health Info IT: $7.8bn/year
• Number of jobs * average salary
=205,000*$38,000 (U.S. Bureau of Labor
Statistics)
• Number of jobs projected to increase 22%
from 2012-2022. Higher demand for coders
due to increasingly aging population expected
to increase salaries as well.
Target Market : $4.8bn/year
• Medical/surgical hospitals, physicians’ offices,
outpatient facilities
• Number of jobs * average salary per category
• (http://www.medicalbillingandcoding.org/jobs
/)
TAM:
$53.8 bn
SAM:
$7.8 bn
Target:
$4.8 bn

27. Value Proposition for Hospitals/IT Admin
Problem:
The medical coding and
billing reimbursement
process is
• costly
• inefficient,
• time-consuming.
Solution:
• Platform agnostic
software
• Fully automated
technology
• Reduce cost by
lowering billing staff or
saving physicians’ time
spent in coding
Value Proposition:
• Cloud-based/web app
that automates coding
process using NLP
engine.
• Translates doctor’s
diagnoses into billable
codes
• Increases flexibility
for current EMR
software
• No infrastructure
overhaul
• Analytics for practice

28. Value Proposition for Private Practices
Problem:
The medical coding and
billing reimbursement
process is
• costly (5-12% cut)
• inefficient,
• time-consuming (30-45
days).
Solution:
• Platform agnostic
software
• Fully automated
technology
• Reduce cost by
lowering billing staff
Value Proposition:
• Cloud-based/web app
that automates coding
process using NLP
engine.
• Translates doctor’s
diagnoses into billable
codes
• Increases flexibility
for current EMR
software
• Allows private
practices to transition
to other EMR software
without having to pay
for billing part
• replace human coders
• Analytics for practice

29. Initial MVP

30. Initial MVP

31. Distribution Channels
Direct Channel : Website
MVP and Get Early Access Email Popup
Community Forum for discussing billing
Web Application Portal
OEM: EMR Companies
Examples include EPIC, CureMD, or
billing oursourcing company such as
Empire
Provide NLP Billing engine built into EMR
Product
NoWeb Portal

32. Direct Distribution Channel
SquareSpace
&Website
Domain
HIPPA Cloud
Platform for
NLP Engine
andWebApp
~$110/year ~$150/month
Using our predicted monthly subscription cost of around 200-300 dollars
per month this leaves us with around 100 dollars per customer

33. OEM Distribution Channel
SalesTeam to
Partner with
Billing
Outsourcing
and EMR
Companies
NLP Engine
gets built and
becomes part
of software
package or
billing
consulting
service
Software is
sold by
distributor
companies
5-10% of each
payment goes to us
~9 billion dollar market for EMR
Software and 31.6% market share for
billing outsourcing

34. Customer Relationships Petal Diagram

35. CustomerWorkflow
Patient EMR
• contains written diagnosis by
doctors
• doctors will not need to add
any codes by looking it up
online or in software
Rubix Health
•upload EMR as PDF/Word
document to portal
•NLP Engine will scan through
document and generate codes
•EMRs sorted by date/patient on
portal for easy use
Reimbursement
• biller/coder does not have to do
anything except look at codes and
write form
•less billers/coders needed
• send form to insurance companies

36. Customer Relationships: GET (Direct)
 Website: Put more relevant terms that are searched for when
searching for medical billing (track through Google)
 Get Early Access popup right at the top of website for easy way to
get customers to sign up (similar to Robinhood)
 Community Forum: Empowers physicians and other experts in the
field to discuss and share problems in medical billing
 Blog:To tell our insights and provide a social forum
 Continue to talking to physicians in private practices and hospitals
 Commit to one-two groups for actually developing and testing the
product

37. Customer Relationships: GET (OEM)
 Can only be done after development and testing of product
(through partnering with hospitals such asWayne State or
private practices)
 Start with billing consulting companies-> ask how much they
could save through our product.This might be the best place
to start with because they have to hire actual experts
 Get demos from EMR/EHR companies to see where exactly
their products could be lacking (IT invasive?, not as smart?)
 Partner with larger tech companies who are interested in the
healthcare IT sector such as Citrix,VMware, Flatiron

40. Hypothesis & Experiment 1
 Hypothesis: Medical billing is a cumbersome, costly, and time-
consuming process for everyday physicians.
 Experiment:Ask physicians how much time they spend in learning
about CPT, ICD-9, and ICD-10 codes.
 Can they be spending that time elsewhere?
 How much money does a physician/group of physicians spend on
coders/billers?
 Compare responses between doctors in private practice and those
working in hospital groups to see where demand is greatest and how
specifics vary.
 If doctors spend a lot of time (~30 mins/hr per day) and money with
coding and reimbursement-> success

41. Learning from Hypothesis/Experiment 1
 Hypothesis: Medical billing is a cumbersome, costly, and time-consuming process for everyday
physicians.
 Experiment: Ask physicians how much time they spend in learning about CPT, ICD-9, and ICD-10 codes.
 Result: Most physicians, especially those in larger hospitals, are spending on average 20-30 minutes
writing codes themselves
 Around 5-8% of the total payment goes to billers (12% for academic hospitals)
 About 60% of the doctors expressed that the billing process was extremely inefficient (one even said it
was laughable)
 Iteration: Keep collecting insights from other doctors. Also ask more details about why the coding
process itself is cumbersome (for example: does it involve looking up a lot of codes)?
 Iteration Result: It is a cumbersome process because of the details involved in the diagnosis, especially if
a patient has a lot of history (more time with patient-> more reimbursement). Moreover, billing
outsourcing companies are expensive and not preferred by hospitals.
 Second Iteration: Shadow doctors, billers, and coders to be able to visualize the problem.This will help
when it comes to creating the product and the NLP engine itself.

42. Hypothesis & Experiment 2
 Hypothesis: Current EMR/auto-coding solutions do not
eradicate the problem of medical coding for physicians.
They’re only a temporary fix. Doctors and their IT departments
are still not satisfied with these technologies.
 Experiment: Meet current physicians using these new
technologies and ask about whether they like using these new
all-in-one software solutions or not.
 Ask IT admins about the effort required to integrate this new
product into the practice.
 If a majority of physicians and IT admins are using/willing to
change to new EMR technologies-> fail, else-> pass

43. Learning from Hypothesis & Experiment 2
 Hypothesis: Current EMR/auto-coding solutions do not eradicate the problem of
medical coding for physicians.They’re only a temporary fix. Doctors and their IT
departments are still not satisfied with these technologies.
 Experiment: Meet current physicians using these new technologies and ask
about whether they like using these new all-in-one software solutions or not.
 Results: Around 30% of the doctors we spoke to have transitioned to using newer
software systems. However, all of these doctors were in private practice.
 Most Physicians in large hospitals such as NewYork Presbyterian said that the
hospital has already spent 30-50 million dollars in EMR systems. Changing to a
new EMR system is just simply an hassle. More open to using platform with drag
and drop or upload of EMRs.
 Iteration: Show physicians our MVP/Website. Ask if anything needs to be added
or changed to the MVP.Talk to IT departments about our solution and see if it
follows the IT guidelines for the hospital.

44. Learning from Hypothesis & Experiment 2
 Hypothesis: Current EMR/auto-coding solutions do not eradicate the problem of medical coding for
physicians.They’re only a temporary fix. Doctors and their IT departments are still not satisfied with these
technologies.
 Experiment: Meet current physicians using these new technologies and ask about whether they like using
these new all-in-one software solutions or not.
 Results: Around 30% of the doctors we spoke to have transitioned to using newer software systems. However,
all of these doctors were in private practice.
 Most Physicians in large hospitals such as NewYork Presbyterian said that the hospital has already spent 30-50
million dollars in EMR systems. Changing to a new EMR system is just simply an hassle. More open to using
platform with drag and drop or upload of EMRs.
 Iteration: Show physicians our MVP/Website. Ask if anything needs to be added or changed to the MVP.Talk
to IT departments about our solution and see if it follows the IT guidelines for the hospital.
 Results: MVP is not detailed enough. Need more in terms of showing an example demo, even if it’s not a real
example. However the UI is simple like Dropbox and that was approved.Website looks nice but it is very wordy.
Needs to be more organized.
 Second Iteration: Change website, make it more organized and appealing.Add stuff to blog and finish get
early access feature.

45. Hypothesis & Experiment 3
 Hypothesis: We believe that a SaaS monthly subscription model is
the most appealing payment method for a healthcare provider.
 Experiment: Ask providers are current methods of payment to
other companies and services that the provider utilizes. Do they
want to see any changes?
 Would they rather go with another route (such as percentage cut) ?
 Pass/Fail: Propose the monthly model with a reasonable price (~200
dollars/a month which is on the low end of medical software
companies). If the doctors/providers approve of the number then
pass, else->fail

46. Hypothesis & Experiment 3
 Hypothesis: We believe that a SaaS monthly subscription model is
the most appealing payment method for a healthcare provider.
 Experiment: Ask providers are current methods of payment to
other companies and services that the provider utilizes. Do they
want to see any changes?
 Would they rather go with another route (such as percentage cut) ?
 Pass/Fail: Propose the monthly model with a reasonable price (~200
dollars/a month which is on the low end of medical software
companies). If the doctors/providers approve of the number then
pass, else->fail

47. Learning from Hypothesis & Experiment 3
 Hypothesis: We believe that a SaaS monthly subscription model is the most
appealing payment method for a healthcare provider.
 Experiment: Ask providers are current methods of payment to other companies
and services that the provider utilizes. Do they want to see any changes?
 Results: Private practices who are using EMR/HER software approve of the
monthly subscription model. However, there are some extra hidden costs that
come into play when extra features are needed.
 Larger hospitals use the percentage of the total payment to pay billers and
doctors aren’t pleased with this method. It leads to extra money going to
coders/billers, especially when many of the doctors are doing a lot of the coding
themselves.
 Iteration: Start with monthly model and come up a more concrete number by
taking important factors into account (such as number of EMRs processed, length
of documents, etc.). Ask doctors if that number is reasonable and repeat if it is
not. Also ask doctors what factors should be considered in payment itself.

48. Hypothesis & Experiment 4
 Hypothesis: We believe that billing outsourcing companies and possibly
EMR/EHR companies would be willing to partner with us if the NLP Engine
is truly accurate and intelligent.The payment method that would work best
would be a percentage of the total payment.
 Experiment: Reach out to these companies and present our solution.Ask
how much money it could save them to get an idea whether they could be
possible partners or not?
 Ask how they currently get revenue to get an idea of which payment
method is preferable (might depend on scenario).
 Pass/Fail: If companies say yes or show signs of interest and approval then
pass, else->fail

49. Hypothesis & Experiment 4
 Hypothesis: We believe that aside from visiting customers, our
website will be a major channel for reaching customers, especially if
has social media features (such as forum/blog).
 Experiment: Ask physicians if/how they communicate the pains
they have in the current medical billing process. Ask if they would
like the forum and blog features and whether they would generate
more social awareness on the problems in medical billing.
 Set up analytics engine to see how many people are currently
visiting website.
 Pass/Fail: If doctors say yes and are eager to use the feature->pass,
else->fail