evolving technologies that can improve specialty patient outcomes april 3, 2013

Evolving Technologies that can Improve Specialty Patient

OutcomesApril 3, 2013

Growing Patient Care ModelPharmaceutical Distribution Channel Specialty Drug Trend Continues to Accelerate

“Specialty Drug Trend Across the Pharmacy and Medical Benefit” – artemetrx a PSG Company January 2013

TECHNOLOGY SUPPORT DEMAND

Enhanced Reporting Requirements Status Code PENDING Reason Codes

Status assigned to a patient who has been referred to the SP but has not yet received a shipment of product from that SP

P1 1 - New referral

Assigned to a patient immediately after receipt of the referral from Fingolimod® Support Center. Indicates that the SP just received the referral but has not yet determined whether or not the SP can service that patient referral (i.e., is a network provider).

P22 - Processing Benefit Investigation SP has determined that it can service the patient and is in the process of verifying benefits.

P3 3 - Processing Prior Authorization SP has determined that a prior authorization (PA) is required and the SP is working with the prescriber to complete the PA or is waiting to receive notification that the PA was approved.

P44 - Order Cleared - Ready to be shipped

SP has completed the benefit investigation (BI) and all required REMS activities (i.e., authorization number received, patient counseling) but has not yet shipped the product.

P5 5 - Patient Decision SP has completed the BI but progress has been stopped at the request of the patient or patient approval is required to move forward.

P6 6 - Prescriber Decision SP has completed the BI but progress has been stopped at the request of the prescriber or prescriber approval is required to move forward.

P7 7 - Clinical Reason

SP has completed the BI, but progress has been stopped due to a clinical reason (e.g., patient hospitalization). Treatment with the product is still under consideration. Note that if the patient has not received product from this SP, or any other SP, any clinical reason reported would not constitute an adverse event (AE). If, however, the SP is servicing the patient for the first time, but another SP had provided product, and the patient or the prescriber reports an AE, this AE must be reported per policy.

P8 8 - Unable to contact patient SP has not been able to contact the patient to relay critical information or conduct patient counseling but is continuing to attempt contact.

P99 - Processing waiting on inventory

SP has completed the BI, all required REMS activities and cleared the order but does not have sufficient product inventory.

P1010 - Processing - Foundation Review (Possible revision) SP is awaiting notification that the patient is approved for financial support.

P11 11 - Delay in Treatment Initiation SP has completed the BI and may have completed the required REMS activities, but the product will not be shipped because initiation of treatment will be/was delayed

P15 15 - Other To be used only when no other code adequately describes the PENDING status code.

HUB vs. Social Media• Roger’s Bell Curve – Technology Adoption Lifecycle

HUB Model: One Stop ShoppingNew Prescription Referral Management

SP Distribution Network Triage Management

Benefit Investigations

Prior Authorization Support & Re-Certifications

PAP Coordination Support

Copay Assistance

Claims Assistance

Clinical Services

Nurse Hotline Support

Telephonic & Home Injection Training

Persistency and Compliance Support

Web-portal for Providers & Patients

Big Data & Dynamic Reporting

Mobile Connectivity

Advancing the Analytics Maturity Curve• “Flash forward to today: technologists, investors, providers, and policy makers all exalt the potential of digital health. Like

genomics, the big idea – or leap of faith — is that through the more complete collection and analysis of data, we’ll be able to essentially “compute” healthcare – to the point, some envision, where computers will become the care providers, and doctors will at best be customer service personnel, like the attendants at PepBoys, interfacing with libraries of software driven algorithms.”

PREDICTIONWhat will happen?

MONITORINGWhat’s happening

now?

ANALYSISWhy did it happen?

REPORTINGWhat happened?

BUSINESS VALUE

COM

PLEX

ITY

LOW

HIG

H

HIGH

BUSINESSS INTELLIGENCE TECHNOLOGIES

Predictive Analytics: Modeling

Inferential Statistics: Dashboards

Dimensional Analysis: OLAP & Visualization

Reporting: Query & Search Tools

“Turning Information Into Impact: Digital Health’s Long Road Ahead” – Forbes December 2012

Consumer Driven Ecosystem & mHealth

“Innovation – A Look at mHealth’s Moving Target” – Rick Krohn/David Metcalf HIMSS March 2013

Decision Support

Engagement

Care Coordination

Convenience

Retail Clinics

Individual

PCP

Transparency

Access

Content

Worksite Clinics

PHR/EHR/HRA Dataflow

Price/Quality Information

Remote Monitoring

DiagnosticsCare Gaps

Wellness/ Coaching/ Incentives

Care Management

Rise In Customer Channels

“SANS Critical Security Controls v4.0” winter-2012-poster

EVOLVING TECHNOLOGIES THAT CAN IMPROVE SPECIALTY PATIENT OUTCOMES

4:15 – 5:30

Sean CreehanPresidentcreehan & company

© creehan & company

EnterprisePartner

Collaboration

Analytics MyShare

Technology Portfolio Technology-Enabled Services

Infrastructure

interchange

Evidence Quality Cost

Coordination Engagement Reporting

6 Critical Success Factors Driving Technology Needs … and Opportunities


Protocol Development

Data Collection

Protocol Execution

Data Access Challenges

Applying the Data

Patient Care Story

Decision Support

Data Interoperability

Transactional & Trend Data

Supporting Technology Initiatives

Care Management

Evidence


Service Levels

Channel Interactions

Variable Workflows

Redundant Processes

TherapeuticComplexity

TherapeuticAccuracy

Systematic Escalations

Channel Process Integration

Electronic Monitoring & Stops

Referral ManagementOrder Management

Quality



Clinical Success

Spend and Trend Mgt

Labor Activity Costs

Lower Fee More Service

Consolidated Channel

Restricted Networks

Risk Share Management

Stakeholder Facing Tools

Improved Contract Administration

Cost

AnalyticsA/R Management



Disparate Partners

Objective Management

Collaborative Care vs. Data

Duplicate Efforts

Referral Coordination

Patient Data Management

Web & Interoperability

Trusted Data Sourcing

Pharma, ACO PA, Case Mgt

Partner CollaborationInterchange

Coordination



Channel Synergy

Systems Integration

Consistent Data Capture

Care Standards

Cost & Convenience

Channel Partner Integration

Web & Mobile

Multi-Method Engagement

Patient Preference

MyShareTelephony Enablement

Engagement



MetricsReporting

Metrics Definitions

Cost of Care Reporting

Patient De-identified

Patient Identified

Defined Metrics Reporting

Multi-dimensional Reporting

Stakeholder-Driven Reporting

Service Level Reporting

Enterprise ReportingAnalyticsSMART Services

Reporting



An integrated technology portfolio is paramount for the next generation of Specialty Pharmacy.


Evidence Quality Cost

Coordination Engagement Reporting

Evolving Technologies That Can Improve Specialty Patient Outcomes

Cardinal HealthSpecialty Solutions

PathWare™ Demonstration

Bruce Feinberg, DOVP/CMO, Cardinal Health

© Copyright 2013. Cardinal Health. All rights reserved. CARDINAL HEALTH, the Cardinal Health LOGO and ESSENTIAL TO CARE are trademarks or registered trademarks of Cardinal Health.

PathWare™ DemonstrationPathWare™ Decision Support Tool

• MACRO and client specific such as IDN

• PathWare ™ is a decision support tool not EMR

• End to end transaction support tool

• Enables communication between IDN, PBM, MD and CardinalHealth

• Evidence based (deep Evidence based literature such as: NCCN, ASCO, Compendia, FDA labeling, Global Literature)

• Clinical Content Management in real time

• Measures physician compliance to pathways in real time

• Cost of regimens

• Contains patient education materials, consent forms and chemotherapy orders

EMR • MICRO and patient specific

• Day-to-Day operational tool for management of patient information and flow such as frequency of use, data input and output, encounter time, encounter frequency

• Definitive record keeper patient of encounter information

• Billing and claims information

• Daily documentation and ordering


Clinical Pathways – More Precise Treatment Options

Clinical Pathways

ASCOFDA LabelNCCN Compendia


Poonacha T K , Go R S JCO 2011;29:186-191

NCCN Distribution of Evidence


Patient Selection

DiagnosisBenefits

Verification

Supporting Literature

Treatment Summary

ClinicalData

Capture

Protocol SelectionAuthorization

and Alerts

PathWare™ Decision Support Tool

Drug Shortages

PathWareTM

Solutions

Specialty Pharmacy

Site of

Care

PathWareTM is the end to end decision support

tool connecting the Payer, Provider, PBM, Specialty Pharmacy and Cardinal in the

treatment ecosystem. (consider removing)


ANSI-EDI

PathWare™ Decision Transaction Solutions

Specialty Pharmacy

PBM

Payor

Claim (POS)

Claim (837)

RetailPharmacy

ePrescribe

PathWare™

ProviderDashboard

PayorDashboard

PBMDashboard

Decision Support

Drug Interaction

Authorizations

Eligibility Formulary Drug History

Eligibility (270/271)

Formulary & Benefit ePA

NCPDP-EDI

InfusionPharmacy


PathWare™ Screens


Pathway Guiding Principles• Our pathway programs are independent from our

commercial relationships

• Our pathways are collaboratively developed with the participating physicians

• Our pathways are designed to deliver the best clinical outcome for the patient

• Our pathways incorporate quality indicators developed in cooperation with participating physicians

IndependenceIndependence

CollaborativeCollaborative

Best Patient Outcome

Best Patient Outcome

We believe properly designed pathway programs will create sustainable reimbursement that rewards innovation based on clinical data while delivering excellent

clinical care


Program Patient Inclusion Ramp

Per 1MM lives commercial plan (<65 years), treatment naïve patients


Reduction in Treatment Variability

1. Clinical Pathways has been effective in reducing treatment variability.

2. The cost of therapies utilized before, but not after pathways represents a 4% savings

Nu

mb

er o

f d

isti

nct

co

mb

inat

ion

% of Patients

After implementation annual spend

$54,080,164

Saving of Pre-pathways regimens no longer used

$ 2,279,267

Percent Savings 4%

*Analysis used patient line of therapy starts during each period. “Pre-pathways” contains the 12 mo prior to Aug 2008, and “after implementation” contains the 12 mo ending Jul 2010. #Limited to anti-neoplastics for Breast, Colon and Lung Cancer in “after implementation” period.@Categories are not distinct and total will sum to >100%

Reduced Variability Has Been Observed in the Participating Physician Population


Rank Drug Combination Cost$1 bevacizumab + carboplatin + paclitaxel protein-bound $236,5092 bevacizumab + trastuzumab + vinorelbine $138,5123 bevacizumab + doxorubicin liposomal $129,0704 bevacizumab + cisplatin + docetaxel $114,1195 bevacizumab + paclitaxel + paclitaxel protein-bound + trastuzumab $109,4646 irinotecan + oxaliplatin $104,8657 bevacizumab + carboplatin + doxorubicin + gemcitabine $103,4638 bevacizumab + carboplatin + docetaxel + paclitaxel $93,1559 bevacizumab + interferon alfa-2b + irinotecan $63,86810 carboplatin + cyclophosphamide + docetaxel + trastuzumab $55,77411 bevacizumab + carboplatin $55,23612 fluorouracil + oxaliplatin + paclitaxel $53,89813 doxorubicin + trastuzumab $52,74414 bevacizumab + interferon alfa-2b + pemetrexed $51,27315 cetuximab + irinotecan + oxaliplatin $49,21816 bevacizumab + carboplatin + fluorouracil + oxaliplatin + paclitaxel $46,45817 paclitaxel + paclitaxel protein-bound $45,92318 cetuximab + fluorouracil $43,28719 fluorouracil + oxaliplatin + pemetrexed $41,82120 bevacizumab + gemcitabine + trastuzumab $41,083

All other $1,050,846Total Cost Avoidance $2,680,586

30

Reduced Variability Accounted For Significant Cost Avoidance (2M Covered Lives)

Drug combination costs associated with chemotherapy (breast, colon, lung)


ER & Hospital Visits Declined Under PathwaysThe percentage of chemotherapy patients visiting the ER during a given line of therapy has declined from better than 36% prior to pathways to under 32% after pathways

• 2800 Chemotherapy Patients on Average per month• 36% ER/Hospitalization rate prior to Pathways• 32% ER/Hospitalization rate post to Pathways• The reduction in ER/Hospital related visits =~$4MM


Evolving Technologies That Can Improve Specialty Patient

Outcomes

Chad Malone, MDVice President, Medical Affairs

Remedy Informatics

Basic Research

Preclinical Res Clinical Res

Health Care

Outcomes ResComparative Res

Outcomes and comparative effectiveness

informed basic research

Genomics informed biomarker

discovery and drug

development

Genomics informed

clinical trials

Genomics- and outcomes-informed patient

stratification

Outcomes informed preclinical research

Outcomes informed cost-benefit analysis

Evidence-Based Research & Healthcare Delivery

Ontologically Driven Data Harmonization

‘Omics Data

Reports/Dashboards

Biospecimen Data

Clinical Trials Management

Quality Improvement

Pedigree Charts

Disease Associations

National Registries

Claims Data

Cohort Selection

University Partners

PI Study Data

Imaging

Clinical Trials

Longitudinal PatientReported Data

Epic Data

Principal Investigators

Query & Reporting

Aggregate,

Map,Harm

onize

Workfl

ow

Mgt

Data

visualization

Patient

PortalStudy Management

EDC

Web

Serv

ices

Biospecim

en

man

agem

en

t

MosaicRepository

MosaicOntology

ACO Data

Mosaic Repository

Learning Products Lead to Patient Specific Care

• All about continuous learning

• More data, better results lead to competitive advantage

• Must be customizable to each specialty

• Cross specialty and cross institution collaboration is the home run here

Thomas Morrow MDAuthor of

Tomorrow’s MedicineManaged Care

Evolving Technologies That Can Improve Specialty Patient Outcomes

Personal Health Assistant in Specialty Pharmacy

Disclaimer

Dr. Morrow: • is a full time employee of of a Genentech but no company products will be

discussed during this presentation. The opinions expressed during this discussion are his alone and do not reflect the opinions of his full time employer.

• has created this talk from his research concerning VHA for an article published Managed Care and Forbes

http://www.forbes.com/sites/ciocentral/2013/03/13/how-virtual-health-assistants-can-reshape-healthcare/

http://managedcaremag.com/archives/1202/1202.biotech.html



http://managedcaremag.com/archives/1202/1202.biotech.html

The Maasai Warrior in Kenya has better access to data and communication than President Reagan!

Natural Language Processing and the Conversational Interface:

Keys to Artificial Intelligence

• Artificial Intelligence– The ability of a computer or other machine to perform actions

thought to require intelligence.

• Natural Language• Human written or spoken language as opposed to a

computer language. Top Companies:

– Next IT: focusing on the patient interaction– Nuance/VirtuOz: focusing on medical records– Creative Virtual: no obvious medical focus– IBM Watson:

• No commercially available products• Oncology/Cardiac physician decision support

Medical Decisions Occur in a Minute by Minute Basis,

• Patients spend a few hours per year with their physician for a “specialty pharmacy” disorder.

• They spend 5000 hours per year making literally thousands of decisions that affect their health

• They need day to day decision support and guideline/algorithm driven

• Natural Language Equipped Intelligent Agents can full this need

Characteristic Traditional IVR Traditional Web Chatbot Next IT’s Multimodal Virtual Assistant

Input Voice and DTMF tones input via keypad

Text Text, Talk, Tap

Language Processing Decision Tree with limited FAQ based interactions

Searchable FAQ Stochastic NLP engine with an intent based language model

Logic Model Linear with branchesTypically 4x4 or 5x4 model

Silo singular answer based Human Emulation – The model is a combination of decision tree, FAQ and intent model which also incorporates context like a human does.

Channels Phone Web Phone, web, SMS Text, mobile, kiosk, social mediaOutput Voice Text and sometimes voice Voice, Text, Navigation often simultaneously based on channel

Contextual Awareness Minimal: Based upon account, user profile

Minimal Based upon account, user profile

or General Answers

Page AwarenessConversational Awareness

User ProfileEvery question is taken in the context of the entire conversation as well

as other data sources

Proactive Engagement None None Multiple options, dynamic, personalized

language model size 4x4 to 5x4 200-300 in a basic FAQ mode 10s of thousands of intents in a single model

Where placed in organization

IVR’s can be set up to support specific tasks in an organization

Usually isolated to a section of a web site, not the entire site.

Across the entire web site/portal and across multiple channels as well.

Breadth/ Depth minimal on both since a human listening to the phone can only

remember a small number of options

Typically limited to either broad OR deep but not both

Able to cover a very broad domain of knowledge while also having a great deal of depth where applicable.

End Point Simple task General Answer to simple questions Truly conversational

Cost to Build $$ $$ $$$How built Voice Recognition Search Based Chat Recognition

Future enhancements Limits reached Limits almost reached Virtually infinite

Overall Long Term Value $ $$ $$$$$

Monthly Operational Cost to Organization

$$$$$(based on need to divert calls to Live

Agent)

$$$$$(based on need to divert calls to Live

Agent)

$(Virtually all calls can be handled by Virtual Agent limiting the number

of live agents needed)

Automated system choices available to an organization

The Virtual Health Assistant: a disruptive technology

• A New Definition of High Touch• Fulfillment Needs• Patient Education• Disease Treatment Management Programs• A New Level of Data Collection: Treatment Optimization

Evolving Technologies that can Improve Patient Outcomes

David Schaefer – AxelaCare

Home Based, Patient Outcomes, Data Capture and Management

Clinical Outcomes Data for True Managed Care

Home Infusion Therapy Monitoring

Physical AssessmentsDisability / Activities of Daily Living

(ADL)Quality of Life (QOL)

ValidatedOutcomesMeasures

IVIg PatientData Collection

CIDP/GBS/Peripheral Neuropathy Myasthenia Gravis

Primary Immunodeficiency

Outcomes vs.

Dose Over Time

CareatorsCare Support

PhysicianData Review

AdministratorsCoordinatorsResearchers

Dose, Side Effect, ClinicalMonitoring

PharmacistData Review

Patient Assessments

Physical Assessments Nurse Driven Data Collection…

Grip Strength (Jamar Dynamometer) TUGS (Timed Up and Go) Spirometry (FEV, PEF, FVC, Flow Volume Loop) NIF (Negative Inspiratory Force) Double Vision

Clinical Example – IVIG Neuropathy

IVIG Est. Cost Savings - Strategies Comparison

Est. 50% of

Improving, New, and Unstable

13

11

20

44%

Cure(>5 years)

Remission(<5 years)

IVIG - Neuropathy

Evolving Technologies that can Improve Specialty Patient

OutcomesApril 3, 2013

evolving technologies that can improve specialty patient outcomes april 3, 2013

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