Reducing financial toxicity for Cancer Patients DUKE-VIVOR Data … · 2018. 10. 5. · Miji Sofela...
Transcript of Reducing financial toxicity for Cancer Patients DUKE-VIVOR Data … · 2018. 10. 5. · Miji Sofela...
Duke Health Technology Solutions
Reducing financial toxicity for Cancer Patients DUKE-VIVOR Data Integration Project
10-09-2018
Miji Sofela
➢Analyst with Duke’s Analytics Center of Excellence.
➢Healthcare/Healthcare-IT for 8 years.
Ben Gagosian
➢Co-Founder and CTO of Vivor
➢12 years experience architecting/building enterprise software and managing software teams
Presenters
➢Project methodology
➢Project technology and tools
➢Project challenges and successes
Learning Objectives
OutlineBurden of Cancer
Study Overview
Duke-Vivor collaboration
Project Infrastructure, Implementation and Challenges
Project Status
Questions and Comments
Cost Sharing$
Expensive
Treatment
More targeted
and effective
treatment
Rising out of pocket costs for cancer patients
Increase in premiums over 18 years
0%
50%
100%
150%
200%
250%
300%
1999 2002 2005 2008 2011 2014 2017
Kaiser Employer Health Benefits Survey, 2017
Inflation
Worker earnings
Premiums
Worker contribution
to premiums 270%
224%
47%
64%
Increase in deductibles over 12 years
$-
$200
$400
$600
$800
$1,000
$1,200
$1,400
2006 2008 2010 2012 2014 2016
Kaiser Employer Health Benefits Survey, 2017
Non-adherence
Missed appointments
Bankruptcy
Taking fewer medications
Selling property
Spending savings
Delaying care
Declining tests
Buying less food
Using other people’s medications
Working longer hours
Cutting out vacations
Using credit
Borrowing from friends or family
Replaced prescriptions with over the counter medications
Spread out chemotherapy appointments
Buying less clothing
Reduce financial distress for patients
Increase co-pay assistance enrollments
Sources: Bernard et al., JCO, 2011; Zafar et al., Oncologist, 2013; Ramsey et al., Health Affairs, 2013, Dusetzina et al JCO, 2014
$5000
● Survivors have 2.5x bankruptcy
rate, linked to 2x mortality risk
● Higher co-pays make patients
46% more likely to discontinue
therapy
WHY IT
MATTERS:
● Providers incur bad debt /
charity, hurt patient satisfaction
● Pharma loses billions in revenue
(out-of-pocket cost is #1 non-
clinical barrier to selection)
Cancer patients pay avg out-of-pocket per year
>90% qualify for financial assistance but get any<20%
Financial Toxicity
Foundations
Patients
Providers
Pharma/Biotech
Financial
assistance
platform
Financial AssistancePatient Financial Counselor
Lack of Awareness,
Focus and/or
Infrastructure
Inefficient
Search
Process
Poor
Application
Experience
Manual Pull-
through &
Tracking
WHAT’S
MISSING:
PATIENT ENGAGEMENT
COMPREHENSIVE FINANCIAL ASSISTANCE PLATFORM
Multiple factors keep patients from accessing assistance
• Founded in early 2015• Began partnering with DCI in late 2015• Applied for an NIH STTR Fast-Track
Grant in early 2016• Completed Phase I Study in early 2017• Awarded Fast-Track NIH STTR Grant in
2017
Phase 1 Takeaways
Patient
FCCs
Patients
● 83% of patients agreed Bridge improved
their knowledge about financial aspects of
cancer care
● Self reporting of clinical details is
problematic!
● Need technology to help streamline/track
patient interactions
● Duplicate data entry is time consuming and
error prone
Overview➢ Phase 2 of the project.➢ Long-term, prospective research (over 2 years)➢ Enroll 200 patients with solid tumors or blood cancer.
Project Outcome➢ Compare stress, financial and symptom burden, and out-of-pocket
expenses of those using Bridge compared to those using existing resources
Patient Outcome➢Mitigate and alleviate the financial burden of Cancer diagnosis and
Treatment
Study Overview
Patient Point of View
Care and Consent of Patient Assistance Enrollment and Financial Relief
Duke/Vivor Technology Partnership
➢Cross platform mobile experience
➢Ability to communicate with patients via text message
➢Accurate and up to date patient profile
➢Standards based drugs and diagnoses (NDC and ICD10)
➢Proper classification of payor types
Phase II technology need
Integration Considerations
Benefits Drawbacks
➢ Interoperability out-of-the-box ➢ Strong foundation in Web standards–
XML, JSON, HTTP, OAuth, etc➢ Concise and easily understood
specifications
➢ New technology that is in various states of maturation depending on hospital system and EMR vendor
➢ Not all data required for the project was available through FHIR
➢ Requires more infrastructure to expose FHIR interface to external software vendors
➢ Higher risk implementation
FHIR - A lightweight REST-based access layer for standard HL7-defined data models
Benefits Drawbacks
➢ Can utilize data from multiple sources (clinical, billing, study)
➢ Complete patient profile needs fulfilled!➢ Utilizes known/existing technology and
processes (ETL, Automate, SFTP)
Custom Reporting- Utilizing data warehouse based reports
➢ Not a true real time interface➢ Very timing/schedule dependent➢ Subject to ETL delays
Project Data RequirementsData Types: ➢MRN
➢Names
➢Demographics
➢Payor type (Medicare, Medicaid, Private Insurance)
➢Diagnosis as ICD codes
➢Medications as NDC codes
Data delivery requirements:➢ As close to real time as possible.
Solution:➢ Custom data extract with a 24hr lag.
Duke-Vivor Collaboration
Duke Cancer Institute ➢Primary Investigator - Dr. Yousuf Zafar, Medical Oncologist, specializes in cancer
cost-related research➢Patient recruitment.
Duke Health Technology Solutions-Analytics Center Excellence➢Technology support for the project.➢REDCap-Clarity-Bridge Data
VivorBridge application.
Project’s DHTS team and infrastructure
Group Resource Effort
DHTS ACE-Research Miji Sofela, Bill Gilbert, Bilikis Akindele
Requirements gathering, Project co-ordination, Base-Sql, REDCap Dynamic Data pull
DHTS ACE-Foundation Jim Pyle ETL process
DHTS integration services Ruth Freeman, Stephen Nixon Automate and SFTP set up
Data Infrastructure
Data Warehouse
23
REDCap REDCAP_SEASchema
Clarity Database
Flat-file Extract
Sftp Destination
Automate file transferExtract Transform Load
REDCap API
sqll
ogi
c
Chronicles
Patient care, Identification and Consenting
Daily ETL
Data source and transformation
RedCap_SEA
MRNs
CLAR_PAT
I.Ds &Demo
Coverage Tables
Payor Info
Order_Med & RX_MED_Mix_Compon
MED_ID,Drug_ID
CLARITY_NDC_CODES & RX_NDC
NDC codes
PAT_ENC_DX & EDG.Current_ICD10_list
ICDs
Developer: Miji Sofela
REDCap_SEA
REDCap
Data Infrastructure: REDCap Extract Service Process
REDCap Extract Service C#/Java
3) Request Metadata and Record
2) Gets all parameters
7) Drops/Create/insert tables
4) Extracts Metadata and Record
6)Logs file updates and email customer
1) Executable Batch file (ETL Tivoli Job)
Developer- Bill Gilbert
REDCap_SEA
DUKE DATAWAREHOUSE
Duke Web services
REDCap Instance
REDCap Instance
REDCap Instance
Data Infrastructure: Aim of the REDCap Extract Service
Bridge App Demo
➢ 58 year old patient➢ Diagnosed with stage 3 Colorectal Cancer➢ Suffering from Neutropenia ➢ Lives with his wife and makes $40,000 a
year➢ Has commercial insurance through
employer➢ Receiving a variety of therapies including
Avastin
• Video Demo in here
Bridge App Demo
➢ 130+ patients enrolled in the prospective research so far.
➢ 65+ patients in intervention arm
➢ 43+ program enrollments
Project Status and Impact.