Category Archives: Electronic Health Records

Developing population health management programs under risk-based contracts

Risk-based contracts are driving the development of population health management programs (PHMPs) that are designed to achieve the Institute for Healthcare Improvement’s Triple Aim goals. Health systems may need to redesign how they deliver healthcare to meet these goals. Risk-based contracts often give providers both the financial flexibility and incentive to redesign care.

In the article “Population health management program development: The path to the Triple Aim,” Milliman’s Nick Creten and Blaine Miller discuss the following five steps healthcare organizations must address when developing a PHMP in a risk-based contracting environment.

Step 1: Assess population costs, utilization, and risk
Step 2: Identify opportunities
Step 3: Segmentation
Step 4: Intervention development
Step 5: Monitor, assess, and improve

Qualifying APM participant considerations

This paper by Milliman’s Charlie Mills, Pamela Pelizzari, and Christopher Kunkel explores the challenges and opportunities regarding participation in an Advanced Alternative Payment Model (APM) track under the Medicare Access and CHIP Reauthorization Act (MACRA). The authors also discuss why becoming Qualifying APM Participants (QPs) may be desirable to some providers as well as the risks they might encounter through the process.

Here is an excerpt from the article:

Opportunities associated with QP status

Financial opportunities

Despite the potential downsides to participating in Advanced APMs and seeing QP status, there are also potential financial benefits, including the following:

A lump-sum payment equal to 5% of their prior year’s payments for Part B covered professional services. QPs can become eligible for this lump-sum incentive payment for years 2019 through 2024. Overall, this is the primary financial opportunity for QPs.

Insulation from the potential downside of the MIPS adjustment. In general, MIPS is a budget-neutral (i.e., zero-sum) program, with a financial downside of 4% in 2019, growing to 9% in 2022. Because QPs and Partial QPs are excluded from MIPS, they are not exposed to MIPS’s downside and do not have to navigate the hundreds of quality and performance measures that make up MIPS.

Opportunities for shared savings from the Advanced APM. QPs will have the opportunity to share in gains (and will generally be required to share in losses) from the Advanced APMs they participate in.

Higher conversion factor increases starting in 2026. Starting in payment year 2026, QPs will receive a conversion factor increase of 0.75% compared with 0.25% for non-QPs. Over time, this could result in significantly higher payment rates for QPs versus non-QPs.

Clinical integration benefits

Several of the currently available Advanced APMs aim to align incentives across different types of providers. For example, ACOs encourage physicians and hospitals to work together to ensure beneficiaries receive appropriate care that can keep them healthy and out of hospitals. In many cases, however, individual physicians do not see the financial benefits of these programs without entering into what can be complex and time-consuming gainsharing arrangements. By providing a 5% lump-sum incentive payment to QPs, MACRA serves to create an even greater incentive for physicians to participate actively in Advanced APMs.

While other payer Advanced APMs do not contribute to QP threshold calculations until performance year 2019 (incentive payment year 2021), it’s possible that the increased engagement physicians have in Advanced APMs that is due to MACRA will have trickle-down effects on other lines of business and patient populations beyond Medicare fee-for-service. This could serve to improve the quality of care and reduce costs for patients covered by other payers.

Developing a population health management program: Considerations for population segmentation

Predictive analytics can improve medical outcomes by identifying patients needing medical interventions. Population segmentation is a common method used to identify such patients. Individuals are grouped into cohorts to help improve the quality of their care. In this paper, Milliman’s Jordan Paulus and Nick Creten explore four common methods for population segmentation: cost cohort segmentation, condition cohort segmentation, utilization cohort segmentation, and social cohort segmentation.

Regulatory roundup

More healthcare-related regulatory news for plan sponsors, including links to detailed information.

DOL releases annual report to Congress on self-insured group health plans
The Department of Labor (DOL) has released “Annual report to Congress on self-insured group health plans,” which provides detailed statistics currently available on self-insured group health plans filing a Form 5500 and on the sponsors of such plans that issue publicly traded equity or debt.

To download the entire report, click here.

CMS releases discussion paper for HHS-operated risk adjustment methodology meeting
The Center for Consumer Information and Insurance Oversight (CCIIO) of the Centers for Medicare and Medicaid Services (CMS) has released a discussion paper for a meeting to be held on March 31, 2016. The paper, “HHS-operated risk adjustment methodology,” discusses possible changes to the Patient Protection and Affordable Care Act (ACA) program for protecting insurers that cover sicker populations. Possible ideas covered by the discussion paper are how to include high-risk patients in risk adjustment payments made by plans that have healthier enrollees and including prescription drug information in the formula used to calculate payments.

To read the entire paper, click here.

Federal subsidies for health insurance coverage for people under age 65
The Congressional Budget Office (CBO) has released a report, “Federal subsidies for health insurance coverage for people under age 65: 2016 to 2026,” in conjunction with the Joint Committee on Taxation. The two agencies project that the federal subsidies, taxes, and penalties associated with health insurance coverage for people under age 65 will result in a net subsidy from the federal government of $660 billion in 2016.

To read the entire report, click here.

Excise tax on high-cost employer-sponsored health coverage
The Congressional Research Service has released the report “Excise tax on high-cost employer-sponsored health coverage: In brief.” The report provides an overview of how the excise tax, or the “Cadillac tax,” is to be implemented. The information in the report is based on statute and guidance issued by the Department of the Treasury and the Internal Revenue Service.

To read the entire report, click here.

Milliman launches new features in Hospital Performance Index

Milliman today announced that its Hospital Performance Index (HPI) software, a benchmarking tool for payers and providers that uses statistical methods to identify opportunities for increased efficiency in patient populations, has added two new capabilities.

The first new feature involves observation status benchmarks, which have become more important over the last two years with the institution of the 72-hour rule. HPI can now produce national and regional averages for observation statistics, allowing for quick comparison of individual facilities to national, regional, and state norms. Custom reporting is also available. With such wide discrepancy in rates regarding observation status by facility throughout the United States, this tool can now shed light on the relative performance of every facility in the country.

The second new feature involves readmission rate benchmarks by diagnosis-related group (DRG). HPI now provides data on the relative readmission rate performance of each hospital in the country, information that is crucial for both hospitals and payers. This new feature will enhance the existing functionality around potentially avoidable admissions and potentially avoidable inpatient days.

“These additions to HPI were very much driven by market demand,” said John Cookson, a principal at Milliman. “Hospitals and payers want more and better data so that they can make smarter decisions, improve efficiency, and contain costs. Now that HPI has information on observation status and readmissions rates, they are in a much better position to accomplish those goals.”

Five healthcare analytic trends

Naugle-AndrewIt goes without question that the U.S. health insurance industry is in a state of flux. Americans are buying individual products through health insurance marketplaces, new insurance carriers have entered the market, and Medicaid has been expanded in 29 states and the District of Columbia. These market changes, in addition to other reform provisions already introduced and others just starting to take hold have subjected the market to an unprecedented level of change.

It is said that insurers like risk but hate uncertainty. What is for certain today is that the old strategies of accepting good risks and repelling poor risks are no longer a recipe for success. To thrive in this new environment, health insurers must make smart decisions using data to keep ahead of the competition.

Within that context, here are five areas where Milliman clients are using data and analytics in innovative ways to bring some order to the chaos:

1. Provider network optimization. Despite bending the cost curve, one of the great lessons of the health maintenance organization (HMO) era was that consumers value choice. For years, preferred provider organizations (PPOs) competed on network size; employers cared more about network disruption affecting their employees than the cost/volume trade-off. In the face of cost pressures, employers and consumers are now starting to accept that smaller networks may be worth the disruption. To meet this need, plans are deploying sophisticated modeling that combines traditional network access and adequacy measures with reimbursement and quality analytics to develop new “smart” networks.

2. Value-based incentive programs. It’s widely accepted that fee-for-service (FFS) reimbursement rewards volume over value. As a replacement for FFS, many payers are promoting value-based incentive strategies that shift reimbursement from fee schedules to bonus pools that pay additional incentives when quality and/or cost targets are met. Analytics are key to selecting measures, setting thresholds, and assessing provider performance. They also aid providers trying to operate under these new risk arrangements, identifying gaps in care, and benchmarking peer performance.

3. New trend dynamics. While predicting the actual numbers requires the proverbial “crystal ball,” the health insurance industry has a reasonably mature understanding of the drivers of healthcare cost trend. But things are getting more complicated as physician practice patterns change, populations age but live longer, millions of new consumers flood into the individual and Medicaid markets, and burgeoning innovation (e.g., telemedicine/telehealth, wearables, smartphones, home visits, retail clinics, etc.) disrupts how and where care is provided. Analytics are key to understanding the “trends in trend” in this new world.

4. Transparency. The healthcare market has earned a reputation for opaqueness. Consumers are more likely to rely on word-of-mouth when selecting a physician, the price of services depends on who’s paying and has little relationship with the actual cost of services, and information on outcomes and quality is kept locked away from prying eyes. Not so in a post-reform world. Consumers can now shop on the basis of price and quality. They can go online and find out how much an appendectomy costs at hospital A or B and which one has a higher success rate. Health plan quality ratings are there for all to see when selecting an exchange plan. Big data and analytics make all of this possible.

5. Care management efficiency. Gone are the days when health insurers had unlimited funding for care management programs. Today, plans must make judicious use of limited administrative dollars to meet medical loss ratio minimums while still managing complex and catastrophic cases. Analytics help plans optimize their care management programs, prospectively identifying those members most likely to benefit from care management, and then enrolling them in the right program.

With many of their traditional performance management tools neutralized by reform, health insurers have had to get smart about how they leverage data and information. They use analytics to design benefit plans, develop marketing strategies and consumer segmentations, select network providers, develop reimbursement strategies, improve clinical quality, and optimize their remaining cost and quality management tools. In today’s market, how a plan leverages analytics, turning data into actionable information, will make the difference between survival and demise.

This article first appeared at Milliman MedInsight.