New Review of Cost Effectiveness of Bundled Payments

 
Dr. William Matzner, Simi Valley, California

The cost of healthcare continues to be a topic of intense discussion from kitchen tables, to board rooms, to congressional hearings. Spurred by conversations and allegations, insurance companies and entities such as Medicare and Medicaid have striven to conceive alternate payment approaches besides the traditional fee for service methods on the basis of reducing costs.


Capitation (a system in which providers are given a defined sum per patient regardless of how many services are rendered in a defined period of time) has been around for many years and has been fraught with complaints among providers for inconsistencies between responsibility for and authority over patient interactions. The HMO model has also been attempted in various iterations with its focus on preventive care, but most have not survived, Kaiser Permanente being an exception. Medicare has since developed a method falling between that of full capitation and fee for service—the use of bundled payments or put more descriptively, episode-based payments. In this method, reimbursement of healthcare providers (both hospitals and physicians) is based on the expected costs for clinically defined episodes of care. Since 1984, bundling payment methods have been tried and as of 2012 almost one third of medical reimbursement is now from a bundling system.

In 2018, Medicare introduced a variation called Bundled Payment for Care Improvement Advanced (BPCI Advanced).  In this model there are 48 episodes, 45 inpatient and three outpatient. Again there are four payment models, with model two being the most common.  Several of the medical episodes included in BPCI Advanced include CHF, COPD, Sepsis, Acute MI and Pneumonia. As every physician would know, there is a wide variation in the degree of illness and the course of therapy within these diagnoses, and there is nothing uniform about each case.
For example, Sepsis includes three DRGs which range from uncomplicated to septic shock.  Unlike elective surgery, providers cannot screen these patients to avoid complications, and in fact many of these patients develop complications and/or have significant comorbidities.  All of these variables create significant variations of length in stay (LOS) and other costs associated with each hospitalization. In these cases, where there is a wide variation in costs, a need exists to employ a method to better predict these costs.
That methods exists but seems too seldom used. It is decision tree modeling that offers both the flexibility and complexity of interaction to more accurately predict costs than just a linear model which is commonly used.  Since diseases such as sepsis, COPD and CHF can become a complex affair with many possible outcomes that would affect costs, this type of modeling lends itself to such an analysis. Armed with better predictability results, providers are better able to defend both real costs and to negotiate for more fairly applied payment schemes. 

If your objective is to provide the best decision-making for your organization and take a global view of your business, expanding your sights beyond ROI, and educating other decision-makers, Cost Effectiveness Analysis can make your organization more competitive and more profitable.

William Matzner, MD. is a recognized expert in Healthcare and Neuro Economics. With a Ph.D. in Economics, MBA and Medical Doctor degree, Dr. William Matzner will provide you with expert analysis on health and wellness programming, populations health management, disease management, new program development, facility development, equipment acquisitions, and other healthcare programs, acquisitions and initiatives. For more information about cost effectiveness analysis and improved financial accountability for your organization, visit Dr. Matzner at http://healthcareanalytics.biz. Dr. Matzner is also available for speaking engagements, retreat presentations and topic specific addresses. 

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William Matzner, MD (Simi Valley, California), has been practicing medicine since 1989, Internal Medicine and Reproductive Immunology. M.D. with Honors from Baylor College of Medicine.

QUALITY ADJUSTED LIFE YEARS (QALY)—THE FORGOTTEN DENOMINATOR


William Matzner, MD
Dr. William Matzner, Simi Valley, California
Author’s NOTE: The health promotion and wellness industry has often been asked to illustrate more quantitatively derived results if for no other reason than to justify budgetary increases based solely on the intuitive hypothesis that healthy people work better than unhealthy people. If better measured, wellness programming could stand to gain even broader support, larger budgets and a more prominent seat at the executive table. After all, who among those of us in the wellness business could argue against having a chief health officer in every corporation and organization. It really does make sense, but how many of those do you know? I, frankly, know none. 

Cost Effectiveness Analysis allows us to present highly credible (that’s credible to the actual financial leaders in organizations) economic evaluation that does, as a number of you have asked, take into account actual clinical costs along with more qualitative factors as well. That’s what separates CEA from ROI, the ability for a group of critical evaluators to agree on a range of measures, apply both real and assumed “value” to those measures and then calculate the Cost Effectiveness of programming.

My between the lines read of may articles addressing ROI in wellness is that a fear exists among practitioners that when measured critically, wellness programming will come up short on a purely economic scale. I believe otherwise, that when measured critically, those holding the corporate purse strings will see greater value in wellness spending than they currently, and often grudgingly, allow. Further, well developed Cost Effectiveness Analysis will allow wellness professionals to better allocate spending among more qualitatively valuable and more quantitatively valuable programming. 

Cost Effectiveness Analysis (CE Analysis) has been shown to be a useful tool in medicine to look at the true effectiveness of certain new (or even older) treatments. More recently I have written that it can prove to be a useful and flexible tool for looking at the effectiveness of various programs used in Corporate Health and Wellness programs. And as these corporate Health and Wellness programs become more common, CFOs want data to justify corporate spending for these programs.

At first glance, it appears that CE models developed for these programs involved simply looking at costs and decision tree analysis.  However, the denominator of the CE analysis takes into account the QUALITY of life, not just the prolongation of life delivered by the treatment.

The Quality Adjusted Life Year  (QALY) is a year of life that is lived in perfect health. It takes into account the length of time and the health related quality of life (HRQL). The latter is given a numeric value between 0 and 1. This HRQL can be estimated by a survey or can be calculated from life tables and other published studies.  The value of HRQL has its roots in expected utility theory, a well developed economic theory.

A specific example may help. Let us say that we are measuring a wellness program that reduces stress. At first, someone could say that the cost difference in such a program is small with respect to productivity, days lost etc. and that a decision tree will not point you towards implementing such a program. BUT, this doesn’t take into account the difference in effectiveness.  Let us say that a stress free life has a QALY of 1.0. However all the stress that one has at work may be severe enough to cause high blood pressure and release of adrenaline such that life would be less pleasurable and the QALY is reduced to 0.8. This would INCREASE the CE ratio by 20% (1/0.8). This leaves the non treatment side essentially costing 20% MORE, just because the quality is of life during stress is that much less.

The beauty and the flexibility of this approach is that we can turn subjective feelings and data about health and life into a NUMERIC value, and then use this to place in the denominator.

For example, there has been much recent discussion about stress in the workplace and how reducing stress may be an important mission for corporate health and wellness programs. A stress value or measure can easily be built into the model so that a stressful life has less QALY.  In this way the denominator becomes smaller and the CE ratio becomes larger (like adding a cost because the quality of life as a result is less).

The denominator in CE analysis, the QALY, can reflect pain and suffering as a result of problems like COPD or heart disease, the pain and debility of having surgery, or as we have alluded to, the mental and physical stress involved in a job. All these factors lead to a QALY less than one, making any treatment less effective once these subjective measures are taken into account. 

There seem to be two camps of those interested in corporate health and wellness—one that wishes to look at the objective benefits of programs, and another that wishes to emphasis overall well being and less stress. Using the CE approach, we can quantify the subjective benefits and then produce a calculation to show (via the numbers) real measurable benefits to making such programs better. This will give even more validity to the usefulness of Corporate Health and Wellness programs and hopefully to their acceptance by CFOs and their counterparts. 

About William L. Matzner, M.D., PhD, FACP 

Dr. William Matzner works in the area of healthcare economics consulting at Healthcare Analytics, LLC, in California. He graduated Phi Beta Kappa from Stanford University. He received his M.D. with Honors from Baylor College of Medicine. In 1988, he was the Solomon Scholar for Resident Research at Cedar Sinai Medical Center. Dr. Matzner subsequently was awarded a PhD in Neuro Economics from Claremont Graduate University. He is board certified in Internal Medicine and Palliative Medicine. He has researched and published extensively on the issue of reproduction and immunology in medical literature. He has been in private practice since 1989, specializing in Reproductive Immunology and Internal medicine. 

Consulting Website: https://healthcareanalytics.biz 
News: https://hippocratesguild.com/dr-william-matzner 
News: https://medicogazette.com/dr-william-matzner

William Matzner, MD (Simi Valley, California), has been practicing medicine since 1989, Internal Medicine and Reproductive Immunology. M.D. with Honors from Baylor College of Medicine.

RISING COST OF HEALTHCARE IN THE UNITED STATES

William Matzner, MD
William Matzner, MD, Simi Valley, California

A recent article in the Wall Street Journal discussed the continued rise of healthcare cost in the US. By 2025 it is projected that healthcare costs will be at 18% of the GDP.  Yet research has shown that among the Organization for Economic Cooperation and Development (OECD) member countries, the US has lower life expectancy at birth and higher mortality for death from respiratory disease, coronary artery disease and diabetes than the OECD average.

A key question becomes how can we decrease the cost of healthcare while simultaneously maintaining or improving the effectiveness of treatment programs? How can an organization health system, ACO, medical group, insurer, government, measure this so as to compare choices?

This is where Cost Effectiveness Analysis (CEA) can provide clear metrics to help determine how differing approaches to healthcare programming and delivery will affect policy change. In chronic diseases such as Diabetes and Coronary Artery Disease, Markov modeling has shown to be an ideal method to determine the cost effectiveness of different treatment approaches over time. One can compare a newer method or medication, or both, to a more standard treatment and see how the cost effectiveness accumulates over time.

Since CEA uses dollars per Quality Adjusted Life Years (QALY), one can quantitatively analyze how effective different treatments or methods are toward the particular disease. This way, policies can be chosen which not only cost less, but can help patients the most over time. It takes a subjective evaluation like effectiveness and turns it into a measurable metric researchers and policy developers can analyze.

The application of CEA using Markov modeling will provide clearer guidance as to how treatment policies should be elucidated, and in the long run can help reduce healthcare costs overall while maintaining and even improving the quality of healthcare delivery and outcomes. It can also be used to quantitatively monitor the effectiveness of new policies once implemented. 

About William L. Matzner, M.D., PhD, FACP 

Dr. William Matzner works in the area of healthcare economics consulting at Healthcare Analytics, LLC, in California. He graduated Phi Beta Kappa from Stanford University. He received his M.D. with Honors from Baylor College of Medicine. In 1988, he was the Solomon Scholar for Resident Research at Cedar Sinai Medical Center. Dr. Matzner subsequently was awarded a PhD in Neuro Economics from Claremont Graduate University. He is board certified in Internal Medicine and Palliative Medicine. He has researched and published extensively on the issue of reproduction and immunology in medical literature. He has been in private practice since 1989, specializing in Reproductive Immunology and Internal medicine. 

Consulting Website: https://healthcareanalytics.biz 
News: https://hippocratesguild.com/dr-william-matzner 
News: https://medicogazette.com/dr-william-matzner

William Matzner, MD (Simi Valley, California), has been practicing medicine since 1989, Internal Medicine and Reproductive Immunology. M.D. with Honors from Baylor College of Medicine.

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New Review of Cost Effectiveness of Bundled Payments

  Dr. William Matzner, Simi Valley, California The cost of healthcare continues to be a topic of intense discussion from kitchen tables...