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.