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Adapting Decision Analytic Models to Meet the Needs of the

Health System

Joe Gricar, MSPrakash Navaratnam, RPh, MPH, PhD

Steve Duff, MS

Disclosures

The presenters do not have conflicts that would jeopardize the objectivity or integrity of this presentation

Mr. Gricar has 15 years of experience in health economics / outcomes research with over 21 years in pharmaceutical research and consulting. This includes the design and development of interactive models (budget impact, cost-effectiveness) as well as the design and execution of retrospective database studies. Joe was one of the original authors of the AMCP Format for Formulary Guidelines and served on the executive committee responsible for revision and dissemination from 2000 to 2008. He has also served as a peer-reviewer for Value in Health Regional Issues (Latin and Asia) and the Journal of Medical Economics

In addition to his consulting experience, Mr. Gricar spent 11 years at Parke-Davis, Pfizer, Pharmacia and Express Scripts, including both internal and field-based positions.

Joe received a Bachelor of Chemistry from Eastern Michigan University and a Master’s in Evaluative Clinical Studies from Dartmouth College

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Joe Gricar, MS

Mr. Duff has spent over 15 years providing health economic and reimbursement consulting services to pharmaceutical, biotechnology, medical device, and diagnostic companies. Prior to founding his current firm, Mr. Duff spent eight years as a consultant with Covance Health Economics and Outcomes Services where he focused on medical technology assessment, economic modeling, and development of dossiers, manuscripts, and strategic plans. His clients ranged from small start-ups to Fortune 500 companies with technologies in various stages of development and marketing. In addition to his consulting experience, Mr. Duff also has held various positions in pharmaceutical research and clinical development. He spent seven years in research and development at Kendall McGaw and Allergan, primarily in the field of pharmacokinetics.

Mr. Duff received a Bachelor’s Degree in Biology from the University of California, San Diego and a Master’s Degree in Health Policy and Management from the Harvard University School of Public Health.

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Steve Duff, MS

Dr. Navaratnam has over 25 years of experience in healthcare, first as a clinical pharmacy practitioner and then as a health services researcher and consultant.

His primary research interests have been in the area of pharmaceutical policy, physician decision making, patient reported outcomes and pharmacoeconomic evaluations of therapeutic interventions in various therapeutic areas. He is an adjunct Clinical Assistant Professor at The Ohio State University College of Pharmacy. Dr Navaratnam has authored or co-authored numerous abstracts, posters and manuscripts and currently serves as a senior advisor on HEOR issues for a number of companies.

He is currently a senior partner and Director of Business Development for DataMed Solutions, LLC. .Dr. Navaratnam completed his undergraduate pharmacy training at the University of Wisconsin-Madison and received a Masters in Public Health (MPH) and a Ph.D. in Health Services Administration from The Ohio State University

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Prakash Navaratnam, PhD

Objectives

• Current Modeling Approaches and Issues• Adapting Common Models

– Tier Placement Model– Facility Model– Portfolio Model

• Discussion

• Used when desired information is not available • Synthesizes information from multiple sources

– RCTs, observational studies, claims data, expert opinion, preference studies

• Most commonly estimates clinical and economic outcomes of interest

• Acts as a conceptual framework to aggregate different data elements

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What is a Decision Analysis Model?

When to Use Decision-Analytic Modeling?Criteria Description / Definition

Treatment selection Examine numerous potential treatment options

Patient selection Extrapolate results to a broader patient population

Time periods Vary time horizon and/or extrapolate to longer horizon

Evaluate uncertainty Measure impact of variation in effect size, inadequate power, confounding variables, or data sources

Flexibility Develop analyses to simulate alternative care settings

Timing and cost Produce information more efficiently than primary data collection

Common Economic Models/AnalysesAnalysis Type Costs Effectiveness Effectiveness

MeasureCost Minimization Differ between

alternativesAssumed equal

between alternativesNone included in

analysis

• Two patients diagnosed with heart disease• Total costs: Treatment A = $20,000; Treatment B = $10,000• Same outcomes are achieved with Treatment A and B

Treatment B preferred given its lower cost and equivalent outcomes


MeasureCost Effectiveness May differ between

alternativesMay differ between

alternativesAny: blood pressure; cases cured; death

• Two patients diagnosed with heart disease• Total costs: Treatment A = $20,000; Treatment B = $10,000• Life expectancy after Treatment A is 5 years but only 4 years after Treatment B• Incremental costs of A vs. B = $10,000• Incremental life-years of A vs. B = 1 year• Cost-effectiveness ratio (A vs. B) = $10,000/life-year gained

Treatment A may be preferred to B if CE ratio is less than a threshold


MeasureCost Utility May differ between

alternativesMay differ between

alternativesQuality-adjusted life-

years (QALYs)

• Two patients diagnosed with heart disease• Total costs: Treatment A = $20,000; Treatment B = $10,000• Life expectancy after both Treatment A and B is 5 years• Quality of life (utility) after Treatment A is 0.85 and is 0.80 after Treatment B• Incremental costs of A vs. B = $10,000• Incremental QALYs of A vs. B = 0.25 QALYs• Cost-effectiveness ratio (A vs. B) = $40,000/QALY gained

Treatment A may be preferred to B if CE ratio is less than a threshold

Key Issues Related to Models

ModelComplexity

Transparency

Bias

Uncertainty

Perspective

Interpretability

Relevance

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Model Perspective

Health Plan Perspective• Cost to plan (Rx, medical)• Benefits to plan ↓ hospitalization rates ↓ ER visits ↓ physician visits Facility Perspective

• Cost to facility(technology $)• Benefits to facility

↑ procedure volume ↑ reimbursement ↓ expenses

Patient Perspective• Cost to patient (co-pays)• Indirect costs (lost work days)• Health benefits to patient ↓ symptoms / sick days ↓ need for outside care ↑ in patient/caregiver QoL Clinician Perspective

• Cost to MD (time/opportunity)• Benefits to MD

↑ reimbursement ↑ health for patients

Societal Perspective• All direct & indirect costs• All benefits

Tier Placement Models

Tier Placement Model Description• Similar in many ways to normative models, Tier

Placement models focus on finding the optimal product placement within the clinical pathway – Provides alternative to restricting access to new, high

cost products to avoid high upfront acquisition costs – A Tier Placement model seeks to evaluate the impact

of product placement on the overall pharmacy and medical costs as well as the impact to patient outcomes

Tier Placement Model Business Rationale• Appropriate tier placement can maximize the

cost effectiveness of an individual product’s use within the available product category– This will have an economic and clinical impact to the

health plan and provider– This approach may create an environment in which

patients are treated more aggressively initially to avoid creating medical issues downstream, perhaps improving the patient’s experience

Tier Placement Model ConceptualizationVariable Description

Patient Population Patients diagnosed with disease of interest that are eligible for treatment with new therapy

Comparators Current clinical pathway vs. 1-3 additional approaches (1st line, 2nd line, 3rd line use)

Perspective Health plan

Time Horizon 1 year or more (dependent on disease state)

Type of Analysis Economic and clinical impact upon introducing new product at various alternative clinical pathway points

Unit of Analysis / Results

1. Overall costs and outcomes of interest (by Scenario)

2. Detail on AE's (Total, Lead to Switch)

3. Cost ratios as deemed useful

4. Graphs to demonstrate the impact over time

Sensitivity Analysis One-way and two-way sensitivity analyses

Data Sources Internal information (i.e., market share estimates, cost, etc), literature, data analytics

Software Platform Microsoft Excel

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Tier Placement Model

Inputs•Costs (Med / Rx)•Clinical efficacy and

AE rates•Resources required

for patient switch •Market share

Drivers•Medical resource use

(hospital, ER)•Pharmacy costs•Disease prevalence•At risk sub-population•Event Rates

Outputs•Medical costs (total /

sub-totals)•Pharmacy costs•Outcome measures

(events avoided, etc)•Results in Total,

PMPM, etc

Tier Placement Model Assumptions• The tier model should allow for maximum flexibility and

allow the user to customize the exact placement of each therapy in the clinical pathway

• Data exists that measures the incremental costs required to enforce restricted formulary access

• Substantial data exists to show that the new data is highly efficacious relative to existing products

• The impact of products is measurable for both clinical outcomes and direct cost incurred by the health plan

• Decision maker is interested in the total impact of product and not just pharmacy costs

Tier Placement Model Pros• Detailed model that that can be used to

determine “optimal” product placement in clinical pathway

• Allows decision-makers to make choices about expanding or contracting access using information that aligns with clinical pathways

• This approach uses the EXACT same underlying modeling structure for each product (more consistency in the modeling programming allowing for ease of QA and revisions)

Tier Placement Model Cons• Model requires more flexibility making this

approach more complicated • Assumptions regarding the impact of treating

naïve patients vs. “failed” patients may need to be made

• How to address patients that fail due to AE’s—do you deal with these patients differently (patient memory in the model)?

• Case Study introduction– New product launched into a market with

several existing therapy options– New product

• More expensive acquisition cost• Clinical trials show improved patient outcomes • Current options have proven safety profiles in real world

setting– Typical plan approach might be to add new product

at 2nd/3rd tier with restrictions

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Tier Placement Case Study

• Questions– Is this the best economic and clinical approach for

the plan?• Do restrictions to the product actually decrease the overall

costs to the plan or just lower acquisition costs? • How do the economics of using the product on 1st tier

compare to 2nd, 3rd or off-formulary?– What is the impact on patient outcomes? (Does

providing restrictive access to superior products result in increasing medical resource use?)

– Are there additional burdens to the plan?

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Tier Placement Case Study

Tier Placement Model Case Study

Current Scenario

Health plan spends

$300M to treat HTN annually

30,000 patients

treated with a 1st line Tx

New agent has superior efficacy but

is $0.30 more per day

Tier Placement Model Case Study

Scenario (Desired vs. Actual)DESIRED RESULT: Pharmacy costs are maintained close to current levels (~0.7% increase)

ACTUAL RESULT: Overall costs are decreased by 4% vs. using new agent as first line therapy. Event rates are also lower (7%)

Facility Models

Facility Model General Description• Similar to normative models in many ways but

emphasizes the facility perspective• Can be simple accounting of facility revenues

and expenses before and after introduction of a new technology

• More complex versions can integrate other perspectives and interactions

Facility Model Business Rationale• As organizations evolve to take on greater

financial risk, a clearer understanding of the impact of facility economics and provider behavior on health plans will be crucial for decisionmaking

Facility Model Pros• More granular understanding of facility resource

use and economics• Evaluation of how financial drivers of clinician

decisionmaking may impact health plan• Exploration of how new technologies can impact

(enhance/detract) facility efficiency

Facility Model Cons• Largely excludes non-financial domains (QOL,

value, patient satisfaction, etc.)• May require extensive data collection/analysis• Behaviors (clinicians, patients, etc.) are

multifactorial and may not adhere closely to model assumptions

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Facility Model

Inputs•Practice patterns and

resource use•Expenses and

reimbursement•Impact of new technology

or policy•Optional: health plan and

clinician perspectives

Drivers•Reimbursement policy•Importance and

magnitude of disruption points

•Changes in reaction to disruption

Outputs•Profit/loss•Efficiency/throughput•Budget impact

Facility Model Case Study• Case Study introduction

– An episodic infectious disease may eventually require outpatient surgery

– Most surgical cases are conducted in the hospital outpatient department (HOPD); occasionally in an ambulatory surgery center (ASC)

– A new device/procedure allows treatment in a physician office setting (OFFICE)

– Procedure tends to be safer and requires less work by the clinician than current technology

Facility Model Case Study• Assumptions

– Health plan likely will cover technology/procedure but payment levels have yet to be set by plan

– All else being equal, health plans prefer that surgery is performed in the least intensive/costly setting

– Clinicians take into account both clinical AND financial factors when making a decision to adopt a new technology/procedure

Facility Model Case Study• Questions

– What is the economic impact on the plan of current practice patterns and reimbursement?

– What resources and expenses are incurred in different settings; how do patients flow through the facility and in what volume; what is the revenue?

– What are likely disruption points with the new approach—shorter OR/recovery room times, less nurse time required for monitoring—and how might clinicians and facilities respond to these changes?

Facility Model Case Study**KEY QUESTIONS**

What should the health plan pay for the new device/procedure?

Are there reimbursement levels that can balance needs of all stakeholders (plan, facility, clinician,

and patient)?

Facility Model Case Study**KEY QUESTIONS**

What should the health plan pay for the new device/procedure?

Are there reimbursement levels that can balance needs of all stakeholders (plan, facility, clinician, and patient)?

Many ways to answer these questions; a facility model may help inform the decision or the

consequences of the decision

Facility Model Case Study

Current Scenario

Health plan spends $10M

on this procedure annually

80% HOPD20% ASC

0% OFFICE

2,000 procedures performed annually in

plan


Scenario 1 (Desired)Due to a less complicated procedure for clinician, health plan covers new technology and procedure but at a greatly reduced payment level to current scenario

DESIRED RESULT: 30%-40% reduction in plan expenses—savings of $3M-$4M


Scenario 1 (Desired)

Health plan spends $6M-$7M on this procedure annually

20% HOPD60% ASC

20% OFFICE

2,000 procedures performed

annually in plan


Scenario 1 (Actual)

Due to much lower payment, new technology is minimally adopted with only a minor shift out of the HOPD setting

ACTUAL RESULT: Instead of 30%-40% reduction in expenses, achieve only a 7% reduction


Scenario 1 (Actual)

Health plan spends $9.3M

on this procedure annually

75% HOPD25% ASC

0% OFFICE


annually in plan


Scenario 2Although procedure is less complicated, plan adopts only minimal decrease in procedure payment; facilities enjoy efficiencies and greater profitability; widespread product adoption and setting shifts ensue including marketing to patients that would not have otherwise received the procedure


Scenario 2

Health plan experiences 10% increase; spends

$11M on this procedure annually

10% HOPD50% ASC

40% OFFICE


annually in plan


Scenario 3

Although procedure is less complicated, plan adopts only moderate decrease in procedure payment; facilities enjoy efficiencies and greater profitability; reasonable product adoption and setting shifts ensue


Scenario 3Health plan

experiences 17% decrease;

spends $8.3M on this

procedure annually

30% HOPD40% ASC

30% OFFICE


annually in plan

Portfolio Models

• Seek to optimize the mix of products and services offered to meet desired end-points over a distinct time window

• Conceptually similar to portfolio management models derived from finance—that is, how do you optimize your ‘ROI’ of the mix of products or services for a particular ‘portfolio’?

• ROI for a health plan may be to be more efficient (minimize costs or improve outcomes or both)

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Portfolio Model Description

• There is increasing pressure on health plans to ensure that the products and services offered to their patients yield optimal returns for the investments made by the health plan and/or realized value savings for health plan clients (such as the government)

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Portfolio Model Business Rationale

Portfolio Model ConceptualizationVariable Description

Patient Population Patients within a therapeutic area

Comparators Depends on health plan definitions of cost/revenue centers. Comparators could be surgical, medical and pharmaceutical.

Perspective Health plan or providers

Time HorizonThe time horizon will be based on the wishes of the health plan. By definition, a portfolio model should take a longer time perspective than traditional normative models. As in a financial portfolio model, the greatest ROIs are realized in a longer time window. Minimum of 1 year, optimally 3-5 years.

Type of Analysis Longitudinal economic and clinical impact over time

Unit of Analysis / Results

• Financial: Overall portfolio ROI or average ROI per service/procedure/medication

• Outcomes: Mortality/morbidity end-point such as ROI per event averted (based on established benchmarks)

Sensitivity Analysis Probabilistic sensitivity analyses

Data Sources Internal information (market share estimates, cost, etc), literature, data analytics

Software Platform Microsoft Excel

• The portfolio model consists of distinct products and services which can be priced in a discrete manner and can be tracked over time

• A detailed understanding of the patterns of care and the relative impact of competing interventions on each other (for instance, does a surgical procedure impact medical and medications utilization downstream?)

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Portfolio Model Assumptions

• Powerful models that can be useful in planning and resource allocation over time

• Allows decision-makers to weed out potentially unnecessary procedures or medications

• Ability to simulate a new technology or service to determine the impact on the overall portfolio

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Portfolio Model Pros

• Model requires a very detailed understanding of patterns of care and resource utilization and the impact of competing technologies on patient flows and outcomes

• Model can become quite complex, especially if there are a large number of competing technologies (products and services) within the portfolio

• There may be a perception that the model is overtly bottom-line driven, especially if the end-points are purely financial

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Portfolio Model Cons

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Portfolio Model

Inputs•Costs of services•Costs of procedures•Costs for medications•Ancillary costs•Overhead allocation

Drivers•Reimbursement

scheme•Member attrition•Prevalence•Regulations•Technological

changes

Outputs•ROI PMPY•ROI per event averted

Portfolio Model Case Study• Case Study introduction

– A health plan administrator is concerned about escalating costs in managing a therapeutic area where disease prevalence is low but optimal outcomes are difficult to achieve

– The health plan administrator would like to know which cost center (surgical, medical or pharmaceutical) has the highest ROI in terms of patient outcomes

– He/she hopes that it would be possible to use this information to prioritize care and to cut costs

Portfolio Model Case Study• Assumptions

– It is possible to track complete financial, clinical and outcome inputs and outputs over the desired time horizon

– Care pathways and drivers are well delineated and understood

– Patients have access to all three alternative cost centers and outcomes are realized for all three alternatives within the time frame for the model

– There are well established benchmarks to gauge performance (such as past performance, industry benchmarks or published regional or national data)

Portfolio Model Case Study• Questions

– What is the acceptable overall ROI per unit outcome to compare alternative cost centers?

– Is there an ROI threshold for services or procedures deemed to be optimal vs. sub-par?

– Are there other stakeholder interests not explicitly modeled which should be taken into consideration?

Portfolio Model Case Study

Actinic Keratosis Portfolio Model

• Calculate ROI: ROI= Revenue - Expenses Expenses

• ROI can be calculated on an annualized basis• Outcomes: Cases averted= Benchmark value – Actual cases

normalized to the plan population. Can be annualized as above.• Alternatives: ROI can also be characterized as a financial value using

net present value calculations (NPV)

Portfolio Model Case Study

3 Year Actinic Keratosis Portfolio Model

Surgical (Cryotherapy)ROI-1%/BCC case averted

Medical (Phototherapy)

ROI-6%/BCC case averted

Pharmaceutical(Topical agents)ROI-10%/BCC case averted

Normative Models--SWOTSTRENGTHS--Address broader domains such as QOL, value--Has strong foundation in economic theory--Adaptable to a variety of healthcare technologies (services, medications, devices)--Provides a simpler representation of complex issues in healthcare

WEAKNESSES--Often have limited relevance to decision at hand--Transparency can be a problem --End points may be difficult to understand (ICER, QALYs)--Overtly reliant on threshold cut-offs--Uncertainty sensitivity analyses may be difficult to understand

OPPORTUNITIES--Widely used and accepted modeling approaches--Can be used to simulate impact of new technologies

THREATS--May not be as adaptable to address newer reimbursement schemes (risk-sharing)--Difficult to incorporate social equity and political considerations

Adaptive Models--SWOTSTRENGTHS--Addresses variety of issues often neglected by normative models --Highly adaptable--Highly salient to the needs of the organization--Uncertainty impacts better understood

WEAKNESSES--Information needs may be great--Models can be very complex--Tend to omit issues such as QOL--More bottom line focused

OPPORTUNITIES--Necessary in light of changing reimbursement/payment climate--Limited budgets: Shift to more pragmatic models to show value--Provides ability to pro-actively engage manufacturers or providers--Can simulate impact of new technologies

THREATS--Not well established: May have limited buy-in--Requires moderate investment --Models designed for internal decision-making: May not be as useful to show value to other stakeholders--Potential conflict of efficiency versus patient centric value

Summary• Existing normative models are useful but may

not always address real-world needs of decisionmakers

• Adaptive models provide new perspective and may help to inform health plan decisions

• As with any type of model, there are challenges and limitations and issues that each can address optimally

Summary

Introduction of new technology

Tier

Portfolio

Facility

Prioritization of competing technologies

and cost control

Tier

Portfolio

Facility

Environmental disruption

Portfolio

Facility

Intra-organizational changes

Portfolio

Scenarios that may benefit from adaptive models

Contact Information

Joe [email protected]

212-260-0589

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