Dr Bradbury Stars HEDIS and HL7 Deck v10 FINAL 01-19-2015

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A Discussion of Stars, HEDIS, HL7, and Health Plan Operations

Felix J. Bradbury, RN, MSHA, ScD, FACHE

Accenture | Digital Health | Advanced Analytics

Thursday, January 22, 2015


Overview: Typical MA Plan issues we see in today’s market Chronic DRIP syndrome – Data Rich

Information Poor. Failure to treat data and analytics as

assets Lack of a road map for the development

of an analytics strategy Data management issues: lack of data

governance and provenance Lack of clear use cases and

understanding what question to ask Operational challenges in executing

even when you have the data and the answers

Poor execution tactics Quality is an afterthought and not a core

competency of the organization. No clear line-of-sight between actions and

expected outcomes. Failure to understand ramifications of C-suite

short-term cost saving initiatives on member

and provider perceptions. Failure to invest in quality as a long-term

strategic asset. Insufficient understanding of, and focus on,

the needs of the customer. No processes for conducting root cause

analysis. Propensity to find the easy answer rather than the correct one.

Failure to hold people accountable for poor performance.

Failure to oversee or manage delegated vendor performance.

Key questions to ask within your organization

What are the best practices we see across the industry?

What are the operational factors that may influence member perception and your plan’s Stars results?

So, what are most plans missing?

What is the CMS Stars program and how does is affect payers and providers?


1. The Patient Protection and Affordable Care Act (PPACA) requires the Centers for Medicare & Medicaid Services (CMS) to provide quality bonus payments to Medicare Advantage plans that achieve 4, 4.5, or 5 stars on a 5-star quality rating system developed by CMS.

2. CMS’ intention with the Stars program is to drive improvements in health outcomes, operational efficiency, and the quality of care and service delivered to MA beneficiaries.

3. A nationwide Quality Bonus Payment (QBP) Demonstration Project was put in place that extended Star bonuses to plans with 3 and 3.5 stars, but only for a limited time.

A brief history of the CMS Quality Bonus Payment program (“Stars”) is outlined on the next two

slides.

Excellent performance

Above average performance

Average performance

Below average performance

Poor performance



What do the Star Plan Ratings Measure?

Medicare Health PlansStaying healthyManaging chronic (long-term) conditionsRatings of health plan responsiveness and

careHealth plan member complaints and

appealsHealth plan telephone customer service

Medicare Drug Plans• Drug plan customer service• Drug plan member complaints and

Medicare audit findings• Member experience with drug plan• Drug pricing and patient safety

Star ratings measure Medicare Advantage plans across 9 “domains” of care and service.


Financial Impact of 2015 Star Ratings on 2016 Bids

Based on the 2015 Rating results, 325 reported contracts with a total enrollment of ~11.7M earned a Stars bonus of $20.2M. However, these same plans lost an estimated $2.2B in potential revenue to the tune of $22 pmpm or $185 PMPY .


MA Payers Direct impact to MA plan revenue that may

be worth many millions 5 Star plans have significant strategic

advantage: Opportunity to market throughout the

entire year. Larger revenue stream compared to

plans of same size that are <5 Stars. Ability to “show off” their performance.

Poor performers are identified by CMS by a Low Performance Icon (LPI)

Multiple efforts to move members from poor performing plans to higher performing plans.

MA Physician Providers Higher degree of collaboration and alignment

between payers and physician providers: Incentives are aligned w/ Stars, and go

beyond just HEDIS to include both medication adherence and patient satisfaction.

Payers identify and contract with providers that help them achieve their Stars results.

Physicians with risk-sharing contracts do better when the plan does better.

Payers are also starting to pass risk back to providers and terming contracts with providers who do not help them to drive stars performance.

Gainsharing win-wins: Plan does better and physician does better.

Potential reduction in hassles as plans may “Gold card” top performing providers: Elimination of Pre-cert hassles.

How does Stars impact payers and providers?Both payers and providers have some skin in the Stars game.



Get the question right first: What are the key questions you want to answer?

Do you have 3-5 clear use cases in mind?

Data: Do you know what data are needed? Do you have the right data? Are the data useable, i.e., accurate, credible?

What is the impact to the analysis of the data you don’t have?

What assumptions have you made in the data?

Analytics: Do you have an analytic approach? Do you have the right staff and the right tools to do data mining and analytics?

After you perform the analytics, do you know how to interpret the results and make them actionable?

Execution: Do you have an actionable strategy for executing on the results? What are the actionable opportunities to execute against?

How are you evaluating competing analytic priorities for resources?

Impact Monitoring and Evaluation: Have you implemented program monitoring processes for tracking performance before you implement your strategy?

Are you tracking both the outcomes and the steps required to achieve the outcomes?

Before undertaking analytic and quality improvement projects, organizations need to have a clear sense of the business and clinical questions they are trying to answer.


5 Star plans:

1. Demonstrate an approach, discipline and degree of rigor by which Star Rating improvement actions are executed and managed.

2. Treat data and analytics as strategic assets.

3. Recognize the keys to success are through partnering with the provider community and supporting physicians in doing what they do best: provide care to patients. Some plans use P4P but are careful to treat their providers as partners and collaborators and not as vendors.

4. Implement effective, robust Care Management: Case Management, Concurrent Review, PA, and Disease Management – these areas also provide input into benefits design.

5. Leverage a high touch concierge member service that supports the member and helps overcome barriers to care up to and including providing transportation to the PCP, lab, or pharmacy – transportation will always be cheaper than an ER visit and an acute inpatient admission.

6. Use predictive analytics to identify and stratify risk and ensure members receive the right level of care, at the right time, in the right setting and at the right price.

7. Recognize that support for quality comes from the CEO and cannot be delegated to the Quality Department.

8. Understand that quality is as a core competency across the entire organization and a critical part of their culture of success.


Accenture is global organization; we are able to leverage best practices developed in other industries and use them to solve complex problems within the healthcare industry. Here’s what we’ve observed as best practices from top-tier plans across our book of business; these are the things 5 Star plans do better than their competition to achieve their top-tier Stars ratings.


Executing and pulling the right value levers

Copyright © 2012 Accenture All rights reserved.

5 Star Rating

Improve Clinical Outcomes

Improve Member Perceptions and

Recollections

Improve Star Specific

Operational Metrics

Goal Business Intent How Measured Improvement Levers

HEDIS

Rx Mgmt / Med Adherence Scores

Readmission Rate

CAHPS Survey

Health Outcomes Survey

Customer Service/Internal

Operations Scores

Appeals Process & Outcomes Scores

Optimize HEDIS Submission Data

Drive members to close gaps in care (e.g., seek preventive care and take medications as directed)

Drive providers to close gaps in care for their patients

Close care gaps that lead to readmissions

Leverage existing member touch points to improve member satisfaction and deliver key messages

Leverage general and targeted marketing to deliver key messages and improve member perceptions

Provide full suite of Foreign Lang & TTY/TDD capability

Manage key service and operations metrics to be within target ranges

Drive members to best, safest drugs within a class

Improve member recollection of care delivered and health management messages received

Ensure accuracy of information available to members via portal and via customer service reps

Improve internal IRR for Appeals Decisions

Continually monitor IRE misalignment and adjust policy if deemed warranted

Continually monitor, understand, and fix root causes of member dissatisfaction


What are the operational factors that may influence member perception and your plan’s Stars results

1. Changes in plan design and barriers to access (changes in deductibles, co-insurance)

2. Failure to align benefits to needs of members with chronic conditions, e.g. co-pays for diabetic supplies.

3. Prior auth timeliness that does not meet market norms, e.g., 14 days for routine auths

4. Significant changes to prior auth guidelines, e.g., such as requiring auth for ostomy supplies when no one else does.

5. Claims payment timeliness that does not meet market norms, e.g., 30 days

6. Use of a large proportion of non-captive sales agents (as opposed to captive agents who are employees of the plan)

7. Use of MSRs who are not well-trained in any one product.

8. Significant changes to the provider network, e.g., network shrinkage.

9. Significant changes in pharmacy tiering, e.g., changing from a 3 tier to a 4 tier formulary.

10. Significant changes in member demographics, enrollments, or disenrollments.

11. Major IT system changes. E.g., legacy to Facets claims systems swap, or implementation of a DSS.

12. High staff turnover rates and lack of continuity of quality of service, e.g., turnover >20%/year.

13. Changes in the plans labor force due to hiring freezes, layoffs, etc.

14. Changes in delegated vendors and failure to monitor delegated vendors.

Below is a comprehensive list of factors that can influence your Stars ratings but do not appear obvious in any claims or survey data. These factors all have an impact on provider and patient perception regarding the quality of care and quality of services received. High CTMs are a proxy for operational issues within the plan.



What key ingredient are we missing which supports an improved member experience?

In most plans, the analytic insights used to drive sales and marketing are not tied to member services or Medical Management Operations. Key insights in one area are not shared and executed across the organization

Sales and Marketing Data

Public Health / Societal Medical CareLinking analytic insights from Sales

to Med Ops

We miss this ingredient

ClaimsMed Ops Data


Data, Analytics, and Curing the DRIP syndrome

Top performing companies cure the Data Rich Information Poor syndrome by treating data and analytics as strategic

assets

18

The raw inputs Consumable product


1. Develop simple descriptive measures that describe the factors that influence risks of member dissatisfaction:

• Having to call member Services for any reason• Prolonged hold times• Multiple hand-offs• Misinformation given• MSR fails to do as stated/no follow-through• Language barriers/difficult to understand• MSR does not have a phone “smile”• Member COC does not match handbook• Provider directory obsolete• Change in formulary tiering• Prolonged prior auth turnaround times

2. Identify actionable factors3. Identify value levers to drive change4. Measure impact

Using analytics to improve member experience

Significant AND actionable factors which contribute to risk of a poor experience

Non-actionable factorsNon-actionable factorsSignificant BUT Non-actionable factors

Non-significant AND non-actionable factorsNon-significant AND non-actionable factorsNon-significant AND non-actionable factors


Claims data are only the tip of the analytic value ice berg*

*Sociodemographic data provide a substantial ability to model the sort of consumers that are more likely to do X as opposed to Y, such as take their medicine, or go to the ER, or be more proactive in managing their health. However, the research indicates sociodemographic data only go so far; after a certain volume of data, no additional lift is conferred. In contrast, detailed data on consumers’ individual anonymized transactions improve insights dramatically over just using sociodemographic data.

Claims data (~7%)

Sociodemographic Data (~50%)

Anonymized consumertransactional data(~80%)

Value


Sources of sociodemographic and transactional data US Census LexisNexis Health Data GNiP Accurint

Axciom Experian Transunion Equifax

As noted on slide 2, sociodemographic data provide a substantial ability to model the sort of consumers that are more likely to do X as opposed to Y, such as take their medicine, or go to the ER, or be more proactive in managing their health. However, the research indicates sociodemographic data only go so far; after a certain volume of data, no additional lift is conferred. In contrast, detailed data on consumers’ individual anonymized transactions improve insights dramatically over just using sociodemographic data.

In order to get value from these data, you have to have a rules engine that accurately maps the external ‘ deep sea’ profiling data patient-level data.


1. Line staff are an often ignored but invaluable resource with deep insights into both problems and solutions. Successful plans use inputs from line staff to understand root causes and fix the problems and not just the symptoms – and then they test to make sure the “fixes” are persistent.

2. Many insights can be gleaned by mapping out workflows in key areas such as prior authorization or claims and then interviewing staff to determine what are the issues that impact their performance on a day-to-day basis. Examples include network downtimes, numerous paper handoffs, break times that are not aligned with peak demand times, staffing shortages, training deficits, etc.

3. In order to ensure accuracy of information, and reduce CTMs associated with misinformation, top tier plans train their member services reps to be experts on one product. Top tier plans also evaluate which Member Services Reps (MSRs) have the highest aptitude for 1st call resolution and then using that MSR’s skillsets to help establish and implement best-practices across the Member Services area.

4. Analytic tools such as Discrete Event Simulation (DES) is powerful tool for pinpointing bottlenecks in any organizational process and can be used to provide insights for effectively eliminating the bottleneck. Examples of where DES may be used to reduce non-value added turn-around-times (TAT) include claims processing, appeals processing, credentialing, prior authorizations processing, and enrollment.

General recommendations for Stars and operational improvementHere’s are some recommendations that are based on best-practices gleaned from top-tier Medicare plans across the country.


Appendices

Felix Bradbury, RN, BScN, MSHA, ScD, FACHE

Dr. Felix Bradbury, FACHE is a Senior Principal with Accenture in global Health Analytics and is based in Houston, Texas. Dr. Bradbury has had a diverse career spanning 30 years. He established a Medical Management Reporting Department for a national commercial payer, led medical economics division for a Medicaid and Medicare Advantage payer and served as VP of analytics, risk management, and reporting for a national disease management company. He has served on product advisory boards for McKesson Payer Solutions, IHCIS, and Symmetry and successfully implemented predictive models and P4P programs for commercial and Medicare payers. He has published research in the areas of program monitoring and evaluation for care management initiatives, human resource management, and the use of discrete event simulation in medical management operations.

Dr. Bradbury is an oncology RN by training and holds a Masters in Health Administration with an emphasis in biostatistics and a Doctor of Science in Health Systems Management and Cost-Effectiveness Research from Tulane University Medical Center, School of Public Health and Tropical Medicine in New Orleans where he completed a post-doctoral fellowship in medical informatics through the Ochsner Health Plan and Clinic in New Orleans. He is currently pursuing a masters in applied economics with an emphasis in health care economics at Johns Hopkins.

Dr. Bradbury is board certified in executive healthcare management as well as a Fellow and board member of the American College of Health Care Executives; he currently serves on the editorial review board for the Journal of Healthcare Management and hosts a blog on healthcare analytics for Accenture.

• Health plan operations• Program monitoring and evaluation

analytics• Quality management for payers and

providers• Medical management operations• Economics/Informatics/Decision

support systems engineering• Predictive Modeling/Forecast models• Medical Epidemiology• DES modeling for health plan

operations

• Commercial, Medicare, and Medicaid payers including one national association

• Cost-effectiveness analytics for Population Health Management

• Healthcare Provider/ Oncology RN • Florida OIG: Fraud, waste and

abuse• P4V/P4P• CDC Epidemiology and notifiable

disease surveillance• Oncology/ICU RN for a regional

medical centre.

Background:

Functional Expertise: Industry Expertise:

• SVP, Medical Management Operations/Stars Quality Management for a national Medicare Advantage payer based in Florida. Ran P/L for medical management operations including concurrent review, prior authorizations, case/disease management, and quality management. Developed and implemented Stars reporting tools for each contract and each department within the plan. Plan went from NCQA Accredited to Commendable in 2012.

• VP, Risk Management, Reporting, and Analytics for a national disease management company. Developed and enhanced ROI analytics, performance metrics, and program monitoring and evaluation infrastructure for clients, one of whom won the C. Everett Koop Award. Developed analytics for a national diesel manufacturer as well as a model for risk factors of medication non-compliance that showed which factors were most important in determining employees’ medication possession ratios.

• VP of Medical Management Operations and Medical Statistics for large Medicaid/Medicare Advantage payer. Oversaw the consolidation, organization, and manipulation of health information to support medical expenditure and utilization analyses. Identified risks and opportunities associated with future profitability, client retention, and clinical outcomes. Developed a readmission predictive model for a national MA plan that used administrative claims data to identify recently discharged members most at risk of an acute readmission. Developed trend analytics used to identify key drivers of readmission trend at the line of business, DRG, provider, POS, and facility levels. Used administrative data to identify actionable opportunities of significant over- and under- utilization by PCPs and specialists.

• Director of Medical Management Reporting Department within the Medical Economics Division of a large commercial payer. This department implemented core analytical programs including a predictive model, a pharmacy gain sharing project, and a pay-for-performance system. Chaired the predictive modeling selection committee for a national commercial carrier. Engineered cost-benefit analytical processes to support medical management resource allocation.

• Director of Health Services and Quality: Developed analytic tools to help concurrent review teams improve their operational performance, and reduce bed days as compared against Milliman’s Optimal Recovery Guide. Created conjoint marketing analytics to help CEO determine the key characteristics of successful markets and which markets he should go into first to grow the business.

A Selection of Experiences:

Dr Bradbury Stars HEDIS and HL7 Deck v10 FINAL 01-19-2015

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