Payment Reform, The 'Value Equationâ in the Catheterization Laboratory, and How These Will Affect You
Dramatic changes in medical payment and economics began with the passage of the Affordable Care Act in 2010. Cardiologists weighed in on how this law is expected to impact upon their treatment decisions and business economics.
James C. Blankenship, MD, of Geisinger Medical Center in Danville, Pennsylvania stressed that this reform, unlike the previous Clinton Healtcare Plan, “is not going away.” In general, attempts have been made to replace the fee-for-service model with a better value—quality treatment for your dollar. Dr Blankenship pointed out that general practitioners appear to be more involved in the policy decision making processes than specialists, and that this is not good for determining which treatment option should be supported. He presented an overview of 3 new payment methods. These include 1) value-based (more itemized), 2) bundled, and 3) capitation (per person per month). Dr Blankenship generally summed up his recommendations to other practicing cardiologists by presenting the Duffy equation: Value of treatment = appropriateness of treatment x (patient satisfaction + expected quality outcomes)/cost of treatment. He stressed that with enactment of the Affordable Care Act exceptional consideration will need to be particularly devoted to the determination of the appropriateness of treatment towards achieving maximal value.
Dr Larry Dean, MD, of the University of Washington, Seattle, discussed the value of working as a diverse team in cardiovascular medicine. This can include anesthesiologists, cardiologists, and surgeons working together to maximize the benefits of what each specialty has to offer while minimizing health risks. Dr Dean pointed out that working with the heart team can be complex and it is a constant learning process, but that the benefits make it worthwhile.
John A. Spertus, MD, MPH, of the University of Missouri, Kansas City discussed health outcomes science in cardiovascular disease, stating that the US must improve its healthcare quality based on evidence-based medicine and move away from guideline-based treatment built on all too frequently poor quality clinical trials. He is on the board of directors for Health Outcomes Sciences, LLC.
Dr Spertus believes we can cull more significant data from available completed clinical trials by first putting more effort into risk stratification analysis prior to treatment towards determining which patient populations stand to benefit the most from a treatment. For example, the anti-thrombotic bivalirudin is commonly used with percutaneous coronary intervention (PCI). Stratification patient populations into high or low bleeding risk, followed by analysis of treatment outcomes after treatment with bivalirudin reveals that this drug provides great cost-to-benefit relief particularly in the high-risk bleeding patients. This was a shocking experimental result. Dr Spertus stated, that this was shocking most significant experimental observation as “it caused a complete reversal of the risk-treatment paradox for bivalirudin.” He expects that a more thought out experimental analysis of available clinical data will translate to new meaningful clinical discoveries. Also, Dr Spertus emphasized that this type of discovery translates to tremendous monetary savings and better quality of life in the long run as we initially treat with more effective preventative medicine.
Another project that Dr Spertus is working on focuses on making the patient a part of the treatment decision-making process. He compared drug-eluting stents with bare metal stents. The prices and outcome data for both technologies are shared with the patient. For example, drug-eluting stent are more expensive, but have a lower rate of restenosis than bare-metal stents. There are also different rates of repeat stenting associated with each technology to be considered. Dr Spertus stresses that good analysis of available data can be done to result in immediately significant results worthy of translation to clinical practice.
Generally the talks were well received. In summary, there will be new billing rules with the Affordable Care Act, and new skills should ideally be in place for dealing with this. Analysis of currently available clinical data by risk stratification using can reveal treatments that can save a tremendous amount of money and increase the quality of care and this is done best when diverse medical specialties can work together as a team.