Team 09 presented their business model for an AI/NLP solution to extract clinical information like problems and allergies from unstructured clinical notes. They interviewed over 100 potential customers and refined their business model. Key elements include partnerships with EHR integration partners and EHR vendors, a sales force channel, and revenue from software licenses and support services. The solution aims to provide up to 20x faster patient chart review and 10x faster problem list entry.
Patent Search - Before beginning and conducting searchTT Consultants
Tips for conducting patent search, patent strategies and criteria for patent search. What are the main things needed to be on focus if you want to survive this dynamic era of patent search strategies.
Leverage Big Data Analytics to Enhance Clinical Trials from Planning to Execu...Saama
Nikhil Gopinath, Senior Solutions Engineer for the Life Sciences at Saama, spoke at EyeforPharma's Clinical Trial Innovation Summit event in February 2017. These slides are from his "Leverage Big Data Analytics to Enhance Clinical Trials from Planning to Execution" presentation.
Patent Search - Before beginning and conducting searchTT Consultants
Tips for conducting patent search, patent strategies and criteria for patent search. What are the main things needed to be on focus if you want to survive this dynamic era of patent search strategies.
Leverage Big Data Analytics to Enhance Clinical Trials from Planning to Execu...Saama
Nikhil Gopinath, Senior Solutions Engineer for the Life Sciences at Saama, spoke at EyeforPharma's Clinical Trial Innovation Summit event in February 2017. These slides are from his "Leverage Big Data Analytics to Enhance Clinical Trials from Planning to Execution" presentation.
Who’s Keeping Score? A Quantitative Approach to Trial FeasibilitySaama
Luke Stewart, Product Manager at Saama, spoke at ExL's Trial Protocol Optimization even on July 18. With most trials failing to meet enrollment timelines, current approaches for feasibility are failing to identify and minimize risk. Sponsors must arm themselves with the right tools to own this analysis throughout the trial lifecycle. We will discuss a quantitative approach that operationalizes feasibility score tracking.
INTIENT Pharmacovigilance equips companies with a centralized platform to collect, manage and learn from the entire spectrum of patient safety data, embedding artificial intelligence, machine learning, robotic process automation and advanced analytics in each step. Visit https://accntu.re/2vTyhY5 to learn more.
The clinical development data deluge is reaching critical mass for pharmaceuticals. Use of varied data for targeted outcomes remains difficult, despite studies that generate evidence of the risk-benefit profile of investigational products. New technologies are federating the ability to leverage analytic-ready data for innovations in clinical operations and clinical science. With the application of clinical data-as-a-service and meta-data core, centralized clinical data lakes have the power to improve data quality, evidence generation, and time-to-insights.
Karim Damji and Benzi Mathews presented this deck at the Clinical Trial Innovation Summit held in Boston on April 24-26.
Karim Damji, SVP Product Management and Marketing at Saama discusses how to spend less time wrangling your data. Learn about the latest technological advances have enabled a platform-based approach to help solve complex problems in a data source-agnostic manner. Improve data processing, standardization and creation of analytics-ready datasets. Introduce machine learning capabilities to improve predictions of risks. Enhance the user experience through the use of a conversational experience. Create executive summaries embedded with relevant persona-based insights.
Course - Machine Learning Basics with R Persontyle
This course is meant to be a fast-paced, hands-on introduction to Machine Learning using R. The course will be focusing mainly on basics of Machine Learning methods and practical implementation of these methods to solve real-world problems. This course aims to develop basic understanding of supervised learning methods, through the use of the R programming platform. It describes the different types of learning and the two main categories of their applications: Classification and Regression.
For corporate bookings or to organize on-site training email hello@persontyle.comor call now +44 (0)20 3239 3141
www.persontyle.com
The Quality “Logs”-Jam: Why Alerting for Cybersecurity is Awash with False Po...Mark Underwood
What happens when the (Observe) Plan-Do-Check-Adjust cycle is undermined by lapses in data integrity? Observations are questioned. Plans may be ill-conceived. Actions may be undertaken that undermine rather than enhance. “Checks” can fail. Adjustments may be guesswork. In cybersecurity, the results of poor data integrity can be expensive outages, ransom requests, breaches, fines -- even bankruptcy (think Cambridge Analytica). But data integrity issues take many forms, ranging from benign to malicious. The full range of these issues is surveyed from a cybersecurity perspective, where logs and alerts are critical for defenders -- as well as quality engineers . Techniques borrowed from model-based systems engineering and ontology AI to are identified that can mitigate these deleterious effects on PDCA.
Tornamos público o nosso Culture Code: o manual de coisas que acreditamos, praticamos e valorizamos no trabalho dentro da RD.
Confira no material quais são os valores que temos para continuar crescendo rápido e com liberdade para nossos talentos.
Who’s Keeping Score? A Quantitative Approach to Trial FeasibilitySaama
Luke Stewart, Product Manager at Saama, spoke at ExL's Trial Protocol Optimization even on July 18. With most trials failing to meet enrollment timelines, current approaches for feasibility are failing to identify and minimize risk. Sponsors must arm themselves with the right tools to own this analysis throughout the trial lifecycle. We will discuss a quantitative approach that operationalizes feasibility score tracking.
INTIENT Pharmacovigilance equips companies with a centralized platform to collect, manage and learn from the entire spectrum of patient safety data, embedding artificial intelligence, machine learning, robotic process automation and advanced analytics in each step. Visit https://accntu.re/2vTyhY5 to learn more.
The clinical development data deluge is reaching critical mass for pharmaceuticals. Use of varied data for targeted outcomes remains difficult, despite studies that generate evidence of the risk-benefit profile of investigational products. New technologies are federating the ability to leverage analytic-ready data for innovations in clinical operations and clinical science. With the application of clinical data-as-a-service and meta-data core, centralized clinical data lakes have the power to improve data quality, evidence generation, and time-to-insights.
Karim Damji and Benzi Mathews presented this deck at the Clinical Trial Innovation Summit held in Boston on April 24-26.
Karim Damji, SVP Product Management and Marketing at Saama discusses how to spend less time wrangling your data. Learn about the latest technological advances have enabled a platform-based approach to help solve complex problems in a data source-agnostic manner. Improve data processing, standardization and creation of analytics-ready datasets. Introduce machine learning capabilities to improve predictions of risks. Enhance the user experience through the use of a conversational experience. Create executive summaries embedded with relevant persona-based insights.
Course - Machine Learning Basics with R Persontyle
This course is meant to be a fast-paced, hands-on introduction to Machine Learning using R. The course will be focusing mainly on basics of Machine Learning methods and practical implementation of these methods to solve real-world problems. This course aims to develop basic understanding of supervised learning methods, through the use of the R programming platform. It describes the different types of learning and the two main categories of their applications: Classification and Regression.
For corporate bookings or to organize on-site training email hello@persontyle.comor call now +44 (0)20 3239 3141
www.persontyle.com
The Quality “Logs”-Jam: Why Alerting for Cybersecurity is Awash with False Po...Mark Underwood
What happens when the (Observe) Plan-Do-Check-Adjust cycle is undermined by lapses in data integrity? Observations are questioned. Plans may be ill-conceived. Actions may be undertaken that undermine rather than enhance. “Checks” can fail. Adjustments may be guesswork. In cybersecurity, the results of poor data integrity can be expensive outages, ransom requests, breaches, fines -- even bankruptcy (think Cambridge Analytica). But data integrity issues take many forms, ranging from benign to malicious. The full range of these issues is surveyed from a cybersecurity perspective, where logs and alerts are critical for defenders -- as well as quality engineers . Techniques borrowed from model-based systems engineering and ontology AI to are identified that can mitigate these deleterious effects on PDCA.
Tornamos público o nosso Culture Code: o manual de coisas que acreditamos, praticamos e valorizamos no trabalho dentro da RD.
Confira no material quais são os valores que temos para continuar crescendo rápido e com liberdade para nossos talentos.
Strategic Consulting Partners in Life Science for a High Performing Paperless Lab
- Do you need to increase productivity and effectiveness of your lab operations?
- Do you want to reduce time to market and boost collaboration ?
- Are you concerned about data quality / data integrity issues?
- Do you need to replace your lab informatics systems and feel overwhelmed by the complexity of the market?
- Do you need to align consistent processes throughout the organisation?
With our success-proven seven-step program we have realized up to 30% efficiency improvements for major European Life Science companies lab operations.
We are lab-experienced chemists with a solid background in business administration and management, a passion for sustainable process improvements and in-depth knowledge of lab informatics. Originating from the renowned "Vialis paperless lab solutions" team, PEPR-Consulting continues its tradition of successful strategic management consulting for the life science industry.
Our strengths are the deep understanding of your lab processes, current GxP requirements and a broad and independent knowledge of lab informatics solutions available today and the trends shaping the future lab environment.
We have a unique profile for a CRO providing distinctive and innovative dual expertise by combining clinical research implementation with the development of customized IT applications specific to the pharmaceutical industry.
Lower Total Cost of Care and Gain Valuable Patient Insights through Predictiv...Perficient, Inc.
Learn how predictive analytics for healthcare can enable your organization to make proactive decisions that can have a profound impact for both patients and care providers. We discuss current and emerging healthcare trends and the positive impact that predictive analytics can have on your organization by:
Optimizing Resource Utilization: Better allocate nurses, clinicians, diagnostic machinery and other resources by predicting future admission volumes
Enhancing Patient Care: Proactively treat patients by more accurately predicting the chance of a chronic condition or the response to medications and therapies
Improving Clinical Outcomes: Analyze treatment success rates to improve treatment plans, minimizing complications and readmissions
Increasing Income and Revenue: Prevent fraudulent behavior and identify opportunities to collect missing income
User Group Kickoff and New Product Roadmap - HAS Session 12Health Catalyst
This session will be highly interactive, targeted primarily at existing Health Catalyst clients. First, our “three amigos” will introduce the concept of three user groups focused around analytics, deployment, and clinical knowledge assets, and solicit your feedback and input on the best way to collaborate and share best practices. Then we will introduce our new product category offerings, and solicit your interactive input and priorities as a guide to our future product roadmap.
Unleash Enterprise Innovation with Sogeti’s Industry SolutionsCapgemini
Sogeti’s industry solutions, built on Hewlett Packard Enterprise ConvergedSystem for Microsoft Analytic Platform System (APS) and Power BI, create a proven platform for visualizing, modeling and reporting data insights for industries including Healthcare and Retail.
Learn how to unite structured inpatient and outpatient data. Find out how to converge real-time inventory visualization and notifications from external sources and Social Media. Learn to capture and analyze data to improve your decision-making.
Presented at Discover London 2015.
[Case Study] Physician, Know Thy User: Using Personas to Target Content and U...Scott Abel
Presented by Joe Sokohl at Documentation and Training Life Sciences, June 23-26, 208 in Indianapolis.
Ever have a project fail? You met with your project team, you talked with the customer, you reviewed technical requirements. But did you talk to your users? Just as one diagnosis doesn’t fit all patients, one application’s approach doesn’t work for all users. Know who accesses your information and uses your applications. Only then choose your features. Using a case study of a multinational project covering four countries, 10 business units, and tens of thousands of content elements, we’ll explore personas, scenarios, and other user-centered techniques. We’ll look at identifying users as well as segregating content according to users and regulatory needs.
What was involved in this cases study?
First we analyzed the 10 business units and their approaches and definitions of business goals. Next we analyzed industry standards for medical devices and their usage.
But that wasn’t enough. We interviewed 40 people in 4 countries, and created an information architecture prototype. We then tested this prototype in hospitals, doctors’ offices, and on site where medical devices were in use.
Based on this contextual inquiry, we refined the architecture and our understanding of the users. Decisions were then made on what type of content would be both appropriate and legal for each user and in each country.
Only with a solid understanding of the users and their goals could we define a flexible, extensible, and usable information and content architecture.
Challenges of Software Testing in the Life SciencesAdam Sandman
Inflectra partner SmarteSoft presented the challenges in testing in the life sciences, covering pharmaceuticals, providers (hospitals, etc.) and payers (insurance companies, health plans, etc.).
Team Networks - 2022 Technology, Innovation & Great Power CompetitionStanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, networks
Team LiOn Batteries - 2022 Technology, Innovation & Great Power CompetitionStanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, LiOn Batteries
Team Quantum - 2022 Technology, Innovation & Great Power CompetitionStanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, Quantum
Team Disinformation - 2022 Technology, Innovation & Great Power CompetitionStanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, Disinformation
Team Wargames - 2022 Technology, Innovation & Great Power CompetitionStanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, Wargames
Team Acquistion - 2022 Technology, Innovation & Great Power Competition Stanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, Acquistion
Team Climate Change - 2022 Technology, Innovation & Great Power Competition Stanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, climate
Team Army venture capital - 2021 Technology, Innovation & Great Power Competi...Stanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, Army venture capital
Team Army venture capital - 2021 Technology, Innovation & Great Power Competi...Stanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve Blank, Army Venture capital
Team Catena - 2021 Technology, Innovation & Great Power CompetitionStanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, economic coercion,
Team Apollo - 2021 Technology, Innovation & Great Power CompetitionStanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, space force
Team Drone - 2021 Technology, Innovation & Great Power CompetitionStanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, c3i, command and control
Team Short Circuit - 2021 Technology, Innovation & Great Power CompetitionStanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, semiconductors
Team Aurora - 2021 Technology, Innovation & Great Power CompetitionStanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, Army venture capital
Team Conflicted Capital Team - 2021 Technology, Innovation & Great Power Comp...Stanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, venture capital
Lecture 8 - Technology, Innovation and Great Power Competition - CyberStanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, hacking for defense, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, Michael Sulmeyer, cybercom,USCYBERCOM
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Safalta Digital marketing institute in Noida, provide complete applications that encompass a huge range of virtual advertising and marketing additives, which includes search engine optimization, virtual communication advertising, pay-per-click on marketing, content material advertising, internet analytics, and greater. These university courses are designed for students who possess a comprehensive understanding of virtual marketing strategies and attributes.Safalta Digital Marketing Institute in Noida is a first choice for young individuals or students who are looking to start their careers in the field of digital advertising. The institute gives specialized courses designed and certification.
for beginners, providing thorough training in areas such as SEO, digital communication marketing, and PPC training in Noida. After finishing the program, students receive the certifications recognised by top different universitie, setting a strong foundation for a successful career in digital marketing.
1. Team 09
Stephane Meystre
Jeremiah Jones
Greg Jones
Unlocking the unstructured data in the
Electronic Health Record, producing actionable
information
TAM of 900k users at $3.85B
Targeting 30k users at $60M
2. -2-
Team members
Stephane Meystre, C-level
• Physician, Faculty in Biomedical Informatics (U of Utah)
• Clinacuity, Inc. Founder and CEO
• Long experience with NLP and clinical narratives
Jeremiah Jones, Industry expert
• Engineer and MBA, Resident Venture Developer for U of
Utah
• Co-founded multiple businesses (Techuity, Sentius, Madra
...)
• Experienced business leader specialized in tech
commercialization
Greg Jones, PI:
• Engineer and MBA, Associate Director SCI and AVP for
Research
• Clinacuity, Inc. Director
• Extensive software dev, business creation and
commercialization
We talked to 106 customers (86 face-to-face)
Weekly average of about 12 interviews
5. -5-
What we did
We talked to > 100 potential customers or experts related to our
business:
19
Healthcar
e
executive
s
40
EHR
users
8
Vendors
23
Industry
executiv
es
16
R&D,
coder
s, etc.
6. -6-
What we did
We talked to > 100 potential customers or experts related to our
business:
19
Healthcar
e
executive
s
40
EHR
users
8
Vendors
23
Industry
executiv
es
16
R&D,
coder
s, etc.
7. -7-
LaunchPad Central
Va lu e Pr op osit ion s
Up to 20x faster patient chart
review
10x faster problem list entry
Lower risk of m issed inform ation
(5x m ore com plete problem list)
Meaningful use certification
com pliance (for the problem list)
Cu st ome r Re la t ion sh ip s
Personal assistance (sales &
support)
Cu st ome r Se g me n t s
EHR user - Hospital - Inpatient -
Specialist
EHR user - Hospital - Outpatient -
Specialist
EHR user - Hospital - Outpatient -
Prim ary care
EHR user - Hospital - Inpatient -
Prim ary care
CIO, CMIO
EHR user - Practice - Specialist
EHR user - Practice - Prim ary
care
EHR vendor busdev (as optional
feature)
Case m anagers/Coders
Ch a n n e ls
Sales force
Partners (EHR vendors/resellers)
What we did: Value Proposition
8. -8-
What we found: Value Proposition for EHR users
• Obtaining a complete overview of a a patient takes far too
long from at least 10 minutes to …“a complex patient
sometimes takes up to 1 week to review!”
• Maintaining the problem list is too time-consuming
9. -9-
What we found: Value Proposition for EHR users
• Obtaining a complete overview of a a patient takes far too
long from at least 10 minutes to …“a complex patient
sometimes takes up to 1 week to review!”
• Maintaining the problem list is too time-consuming
10x faster
coded
problem entry
up to 25x faster
patient chart
review
10. -10-
What we found: Value Proposition for EHR users
• Obtaining a complete overview of a a patient takes far too
long from at least 10 minutes to …“a complex patient
sometimes takes up to 1 week to review!”
• Maintaining the problem list is too time-consuming
10x faster
coded
problem entry
up to 25x faster
patient chart
review
VPs each validated by more than 30 potential customers: This
would be big! …Could be enormously valuable! …Would be
very valuable …Would be most useful! …etc.
11. -11-
What we did: Value Proposition for EHR users
Automatically extracts problems and allergies in real-time from
all narrative text documents in the EHR
Congestive heart failure
Renal insufficiency
Allergy to cephalosporins
CliniWiz
14. -14-
LaunchPad Central
Va lu e Pr op osit ion s
Up to 20x faster patient chart
review
10x faster problem list entry
Lower risk of m issed inform ation
(5x m ore com plete problem list)
Meaningful use certification
com pliance (for the problem list)
Cu st ome r Re la t ion sh ip s
Personal assistance (sales &
support)
Cu st ome r Se g me n t s
EHR user - Hospital - Inpatient -
Specialist
EHR user - Hospital - Outpatient -
Specialist
EHR user - Hospital - Outpatient -
Prim ary care
EHR user - Hospital - Inpatient -
Prim ary care
CIO, CMIO
EHR user - Practice - Specialist
EHR user - Practice - Prim ary
care
EHR vendor busdev (as optional
feature)
Case m anagers/Coders
Ch a n n e ls
Sales force
Partners (EHR vendors/resellers)
What we found: Customer Segments
15. -15-
What we found: Customer Segments
Complex customer segments in healthcare organizations
Physicians,
NPs, PAs
User
16. -16-
What we found: Customer Segments
Complex customer segments in healthcare organizations
Physicians,
NPs, PAs
EHR Liaison
CMIO,
Tech.
Assess.
Committee
Physician
Leaders
CIO,
IT committee
Finance
Director
CFO COO
Purchasing,
Legal
ITS
Decision-Maker
Economic Buyer
Saboteur
Influencer
User
17. -17-
What we found: Customer Segments
Complex customer segments in healthcare organizations
Physicians,
NPs, PAs
EHR Liaison
CMIO,
Tech.
Assess.
Committee
Physician
Leaders
CIO,
IT committee
Finance
Director
CFO COO
Purchasing,
Legal
ITS
Decision-Maker
Economic Buyer
Saboteur
Influencer
User
Inpatient -
Specialist
Inpatient –
Medicine/Ped.
Outpatient –
Specialist
Outpatient –
Primary care
18. -18-
What we found: Customer Segments
Complex customer segments in healthcare organizations
Physicians,
NPs, PAs
EHR Liaison
CMIO,
Tech.
Assess.
Committee
Physician
Leaders
CIO,
IT committee
Finance
Director
CFO COO
Purchasing,
Legal
ITS
Decision-Maker
Economic Buyer
Saboteur
Influencer
User
Inpatient -
Specialist
Inpatient –
Medicine/Ped.
Outpatient –
Specialist
Outpatient –
Primary care
19. -19-
What we found: Customer Segments
Customer archetype: Inpatient EHR user –
Specialist Interventional Radiologist
Male, 40-65 years old
Attending physician, specialist
Not the buyer, but the
champion
Motivations: Less time using
EHR and more with patient;
Easy clinical documentation;
High risk patient care; See
more patients; Optimize
revenue.
Influenced by: Department
chair, Peers, Scientific
knowledge (journals, web)
20. -20-
EHR integration partner (e.g., Sansoro Health)
Provider of clinical data (for training and testing)
e.g., hospital
EHR vendor
Financial m anagem ent
Software developm ent and testing
AI/NLP developm ent and testing
Custom integrations
Custom er engagem ent and support
Ke y Re sou r ce s
Software developers
IP rights
EHR integration
Com puting pow er (IaaS)
Sales and Field Engineers
What we found: Key Resources
23. -23-
LaunchPad Central
Ke y Pa r t n e r s
EHR integration partner (e.g., Sansoro Health)
Provider of clinical data (for training and testing)
e.g., hospital
EHR vendor
Ke y Act ivit ie s
Financial m anagem ent
Software developm ent and testing
AI/NLP developm ent and testing
Custom integrations
Custom er engagem ent and support
Ke y Re sou r ce s
Software developers
IP rights
EHR integration
Com puting pow er (IaaS)
What we found: Key Partners
24. -24-
Integration with commercial EHRs:
Partners for integration and sales channels:
What we found: Key Partners
End user (EHR user)
Buyer
(CFO,
CIO)
Epic App
Store?
Development and Channel
partner
R&D,G&A
,S
Profit Reseller
fee
[30%]
Discount
[10%]
$15,000 $15,00
0
$15,000 $5,000
Final price: $45,000
25. -25-
Here is what we will do next
• The pain is more severe than we thought
• This is a viable business, and we plan to
pursue as a “GO with minimal pivot”
• Next step is STTR Phase II grant application, with
– Further business model investigation and refinement
– Integration into an EHR (Epic EpicCare, with Sansoro Health, at
the Huntsman Cancer Institute and University of Utah Hospital)
– Improvement of accuracy and processing speed
– Improvement of generalizability and adaptability
– Development of an advanced visualization interface for the local
adaptation of the system
– Code review, robustness, and delivery improvements
– Market analysis and communication
27. -27-
LaunchPad Central
Ke y Pa r t n e r s
EHR integration
partner
(TransformativeMed
Cloud-based
computing (e.g.,
Amazon EC2)
Provider of
clinical data (for
training and
Ke y Act ivit ie s
Software
development
Installation and
local adaptation
Evaluation and
testing
Va lu e Pr op os it ion s
Complete rapid
overview of
patient facts
Improved
convenience and
usability to
Improved
performance with
faster problem
Lower risk of
missed
information
Meaningful use
certification
support
Cu s t om e r Re la t ion s h ip s
Personal
assistance (sales
& support)
Cu s t om e r Se g m e n t s
Hospital EHR
users
Physician group
EHR users
CIO, CMIO
Case
managers/Coders
Clinical trial
researchers
Retrospective
clinical
researchers
EHR vendors (as
optional feature)
Ke y Re s ou r ce s
Software
developers
IP rights
EHR integration
Computing power
Ch a n n e ls
Sales force
Partners (EHR
vendors/resellers)
Cos t St r u ct u r e
Software development (HR)
Installation and support (HR)
License royalties
Re ve n u e St r e a m s
Sale (fixed price determined by install. size, savings,
and avoided penalties)
Service fee (installation, local adaptation, support)
Royalties
Sublicense fees
Business Model Canvas Evolution - 2
28. -28-
LaunchPad Central
Ke y Pa r t n e r s
EHR integration
partner
(TransformativeMed
Cloud-based
computing (e.g.,
Amazon EC2)
Provider of
clinical data (for
training and
EHR vendor
Ke y Act ivit ie s
Software
development
Installation and
local adaptation
Evaluation and
testing
Va lu e Pr op os it ion s
Enable up to
20x faster
patient chart
10x faster
problem list entry
Lower risk of
missed
information (5x
Meaningful use
certification
compliance (for
Cu s t om e r Re la t ion s h ip s
Personal
assistance (sales
& support)
Cu s t om e r Se g m e n t s
Hospital EHR
users
Physician group
EHR users
CIO, CMIO
Clinical trial
researchers
EHR vendor
busdev (as
optional feature)
Retrospective
clinical
researchers
Case
managers/Coders
Ke y Re s ou r ce s
Software
developers
IP rights
EHR integration
Computing power
Ch a n n e ls
Sales force
Partners (EHR
vendors/resellers)
Cos t St r u ct u r e
Software development (HR)
Installation and support (HR)
License royalties
Re ve n u e St r e a m s
Sale (fixed price determined by install. size, savings,
and avoided penalties)
Service fee (installation, local adaptation, support)
Royalties
Sublicense fees
Business Model Canvas Evolution - 3
30. -30-
LaunchPad Central
Ke y Pa r t n e r s
EHR integration
partner
(TransformativeMed
Provider of
clinical data (for
training and
EHR vendor
Ke y Act ivit ie s
Financial
management
Software
development and
testing
AI/NLP
development and
testing
Custom
integrations
Customer
engagement and
support
Freedom to
operate and IP
protection
Va lu e Pr op os it ion s
Enable up to 20x
faster patient
chart review
10x faster
problem list entry
Lower risk of
missed
information (5x
Meaningful use
certification
compliance (for
Cu s t om e r Re la t ion s h ip s
Personal
assistance (sales
& support)
Cu s t om e r Se g m e n t s
EHR user -
Hospital -
Inpatient -
EHR user -
Hospital -
Inpatient -
EHR user -
Hospital -
Outpatient -
EHR user -
Hospital -
Outpatient -
EHR user -
Practice - Primary
care
EHR user -
Practice -
Specialist
CIO, CMIO
EHR vendor
Ke y Re s ou r ce s
Software
developers
IP rights
EHR integration
Computing power
(IaaS)
Sales and Field
Engineers
AI/NLP
scientists
Ch a n n e ls
Sales force
Partners (EHR
vendors/resellers)
Cos t St r u ct u r e
Software development (HR)
Installation and support (HR)
License royalties
Re ve n u e St r e a m s
Sale (fixed price determined by install. size, savings,
and avoided penalties)
Service fee (installation, local adaptation, support)
Royalties
Sublicense fees
Business Model Canvas Evolution - 5
31. -31-
LaunchPad Central
Ke y Pa r t n e r s
EHR integration
partner (e.g.,
TransformativeMed
Provider of
clinical data (for
training and
EHR vendor
Ke y Act ivit ie s
Financial
management
Software
development and
testing
AI/NLP
development and
testing
Custom
integrations
Customer
engagement and
support
Freedom to
operate and IP
protection
Va lu e Pr op os it ion s
Enable up to 20x
faster patient
chart review
10x faster
problem list entry
Lower risk of
missed
information (5x
Meaningful use
certification
compliance (for
Cu s t om e r Re la t ion s h ip s
Personal
assistance (sales
& support)
Cu s t om e r Se g m e n t s
EHR user -
Hospital -
Inpatient -
EHR user -
Hospital -
Outpatient -
EHR user -
Hospital -
Outpatient -
EHR user -
Hospital -
Inpatient -
EHR user -
Practice -
Specialist
EHR user -
Practice - Primary
care
CIO, CMIO
EHR vendor
Ke y Re s ou r ce s
Software
developers
IP rights
EHR integration
Computing power
(IaaS)
Sales and Field
Engineers
AI/NLP scientists
HIPAA-
compliant data
store
Ch a n n e ls
Sales force
Partners (EHR
vendors/resellers)
Cos t St r u ct u r e
Software development (HR)
Installation and support (HR)
License royalties
Re ve n u e St r e a m s
Sale (fixed price determined by install. size, savings,
and avoided penalties)
Service fee (installation, local adaptation, support)
Royalties
Sublicense fees
Business Model Canvas Evolution - 6
32. -32-
LaunchPad Central
Ke y Pa r t n e r s
EHR integration
partner (e.g.,
Sansoro Health)
Provider of
clinical data (for
training and
EHR vendor
Ke y Act ivit ie s
Financial
management
Software
development and
testing
AI/NLP
development and
testing
Custom
integrations
Customer
engagement and
support
Freedom to
operate and IP
protection
Va lu e Pr op os it ion s
Up to 20x
faster patient
chart review
10x faster
problem list entry
Lower risk of
missed
information (5x
Meaningful use
certification
compliance (for
Cu s t om e r Re la t ion s h ip s
Personal
assistance (sales
& support)
Cu s t om e r Se g m e n t s
EHR user -
Hospital -
Inpatient -
EHR user -
Hospital -
Outpatient -
EHR user -
Hospital -
Outpatient -
EHR user -
Hospital -
Inpatient -
EHR user -
Practice -
Specialist
EHR user -
Practice - Primary
care
CIO, CMIO
EHR vendor
Ke y Re s ou r ce s
Software
developers
IP rights
EHR integration
Computing power
(IaaS)
Sales and Field
Engineers
AI/NLP scientists
HIPAA-compliant
data store
Ch a n n e ls
Sales force
Partners (EHR
vendors/resellers)
Cos t St r u ct u r e
Software development (HR)
Installation and support (HR)
License royalties
Re ve n u e St r e a m s
Sale (fixed price determined by install. size, savings,
and avoided penalties)
Service fee (installation, local adaptation, support)
Royalties
Sublicense fees
Business Model Canvas Evolution - 7
33. -33-
LaunchPad Central
Ke y Pa r t n e r s
EHR integration
partner (e.g.,
Sansoro Health)
Provider of
clinical data (for
training and
EHR vendor
Ke y Act ivit ie s
Financial
management
Software
development and
testing
AI/NLP
development and
testing
Custom
integrations
Customer
engagement and
support
Freedom to
operate and IP
protection
Va lu e Pr op os it ion s
Up to 20x
faster patient
chart review
10x faster
problem list entry
Lower risk of
missed
information (5x
Meaningful use
certification
compliance (for
Cu s t om e r Re la t ion s h ip s
Personal
assistance (sales
& support)
Cu s t om e r Se g m e n t s
EHR user -
Hospital -
Inpatient -
EHR user -
Hospital -
Outpatient -
EHR user -
Hospital -
Outpatient -
EHR user -
Hospital -
Inpatient -
CIO, CMIO
EHR user -
Practice -
Specialist
EHR user -
Practice - Primary
care
EHR vendor
Ke y Re s ou r ce s
Software
developers
IP rights
EHR integration
Computing power
(IaaS)
Sales and Field
Engineers
AI/NLP scientists
HIPAA-compliant
data store
Ch a n n e ls
Sales force
Partners (EHR
vendors/resellers)
Cos t St r u ct u r e
Software development (HR)
Installation and support (HR)
License royalties
Re ve n u e St r e a m s
Sale (fixed price determined by install. size, savings,
and avoided penalties)
Service fee (installation, local adaptation, support)
Royalties
Sublicense fees
Business Model Canvas Evolution - 8
34. -34-
LaunchPad Central
Ke y Pa r t n e r s
EHR integration
partner (e.g.,
Sansoro Health)
Provider of
clinical data (for
training and
EHR vendor
Ke y Act ivit ie s
Financial
management
Software
development and
testing
AI/NLP
development and
testing
Custom
integrations
Customer
engagement and
support
Freedom to
operate and IP
protection
Va lu e Pr op os it ion s
Up to 20x
faster patient
chart review
10x faster
problem list entry
Lower risk of
missed
information (5x
Meaningful use
certification
compliance (for
Cu s t om e r Re la t ion s h ip s
Personal
assistance (sales
& support)
Cu s t om e r Se g m e n t s
EHR user -
Hospital -
Inpatient -
EHR user -
Hospital -
Outpatient -
EHR user -
Hospital -
Outpatient -
EHR user -
Hospital -
Inpatient -
CIO, CMIO
Ke y Re s ou r ce s
Software
developers
IP rights
EHR integration
Computing power
(IaaS)
Sales and Field
Engineers
AI/NLP scientists
HIPAA-compliant
data store
Ch a n n e ls
Sales force
Partners (EHR
vendors/resellers)
Cos t St r u ct u r e
Software development (HR)
Installation and support (HR)
License royalties
Re ve n u e St r e a m s
Sale (fixed price determined by install. size, savings,
and avoided penalties)
Sale (variable price, as portion of additional revenue)
Service fee (installation, local adaptation, support)
Royalties
Business Model Canvas Evolution - 9
35. First Pass Canvas
Low Fidelity MVP
Product/Market Fit
Left-side of the Canvas
Market Opportunity
High Fidelity MVP
Metrics That Matter
Right-side of the Canvas
Problem/Solution validation
Investment Readiness Level – Where we started
IRL 2
36. Investment Readiness Level – Where we ended
First Pass Canvas
Low Fidelity MVP
Product/Market Fit
Left-side of the Canvas
Market Opportunity
High Fidelity MVP
Metrics That Matter
Right-side of the Canvas
Problem/Solution validation
IRL 6-7
P
P
P P P P
PP
Editor's Notes
4 ney: 2 don’t use the PL, 1 has someone else enter the data (nurse), 1 already developed his own tool to select codes faster
Mention this was a functioning system
Say that WE discovered this ecosystem
Briefly: not considered as medical device
Pause after this one
Indirect channels, with partners
(example for 50 users hospital yearly fee)
Validated hypotheses in most Canvas building blocks