In this chapter, we presented the results of exploratory analyses to identify issues related to constructing and using episodes of care the purposes of measurement and aligning incentives to deliver high quality care. The episodes of care were constructed for convenience using by two commercial episode groupers, Symmetry ETGs and Thomson MEGs.
We found that beneficiaries with the nine conditions we examined experienced an average of 10 episodes of any kind during the measurement year, most of which were not related to nine conditions of focus in this study. Many of the unrelated episodes were common among a large proportion of beneficiaries across the nine study conditions, such as hypertension, congestive heart failure, and fungal skin infections. It is unclear whether physicians and other providers would view a beneficiary's multiple episodes as defined in this study as distinct issues to be managed separately or as related issues to be managed jointly.
We found that standardized payments per episode varied widely both across and within the nine conditions, In addition, there was an inverse relationship was observed between standardized episode payments and the coefficient of variation. We used fairly broad groupings of patients based on the nine conditions. Heterogeneity within a condition might be reduced if subgroups of patients were created. For example, instead of grouping together all diabetics, separating them into categories based on the degree of advancement of their disease. There is also a need to understand the key sources of variation in standardized payments and which sources need to be accounted for in the episode construction or patient group creation, versus which are sources of variation you could seek to eliminate through the application of episodes for performance measurement or financial incentives.
Beneficiaries who experienced a greater total number of episodes (both related and unrelated to conditions of focus) had higher average standardized payments per episode and more providers involved in the delivery of care for each episode related to the conditions of focus. This suggests the need to not only risk-adjust for the severity of the specific condition of focus, but also the other conditions experienced by the beneficiary.
Across the nine conditions, there was no standard care pattern of types of providers and settings involved for the related episodes. Even for patients with the same condition, there was substantial variation in care trajectories. Often care cuts across three settings of care for any given condition. During a single episode of care, the care provided was often dispersed among multiple specialists, but usually involved a single primary care physician (PCP). These PCPs may offer a foundation for coordinating the care across an episode.
Care patterns showed variation across the three states we examined. Some of the variation that was observed is likely related to differences in the supply of different types of health care providers in different geographic health care markets. For example, inpatient rehabilitation facility (IRF) care was more common for episodes in Texas, where these types of facilities are relatively numerous. In Oregon and Florida, the use of IRFs was less common than in Texas, but use of SNFs was more common. The implications of these supply-related variations in care patterns are not clear.
A significant fraction of episodes could be assigned to a provider for most of the attribution rules we studied. However, we did observe variation in what proportion of the episodes could be assigned depending on the rule and the type of condition. Some conditions are addressed primarily in an ambulatory setting and in these types of episodes, a facility-based rule led to a smaller share of episodes being assigned. For other conditions, an individual provider may represent only a small fraction of total episode payments (e.g., physicians in an AMI episode represent only 6.5% of total costs, whereas the facility represents 66.4%), and in this situation, rules that would assign the episode to this single physician may not be as appropriate. These findings illustrate that a single approach to attributing episodes to providers may not be appropriate.
Variation existed across the three states in the average number of episodes per beneficiaries, both overall and for beneficiaries with each of the nine conditions focus, average standardized payments for episodes related to the nine conditions, the involvement of different post-acute care providers, and the percent of episodes for which beneficiaries received care outside of their state of residence. The mean number of total episodes of all types per beneficiary varied widely among the three states in our analysis, averaging 6.1 episodes per beneficiary in Oregon, 6.9 in Texas and 8.0 in Florida. The average standardized payment per episode for the episodes related to the nine conditions varied in a consistent pattern across the nine conditions, and Oregon consistently had lower average per-episode payments than Florida or Texas. The reasons behind these geographic variations in per episode payments and frequency of episodes are unclear.
These results suggest that the optimal way in which episodes would be constructed would depend on how they would be applied and on policy considerations, such as promoting improved coordination among providers in the delivery of care across a patient's care trajectory within an episode. Because this study relied on the use of two existing commercially available episode groupers, what we observed in the data analyses we performed was influenced by how each of the grouper tools constructs an episode, and those reading this report should bear this in mind. For example, distinguishing between acute events and chronic episodes is an important consideration. There are chronic episodes with acute exacerbations (such as ischemic heart disease with a heart attack), strictly chronic episodes (ongoing management of diabetes), and strictly acute episodes (such as hip fracture), and the policy considerations are likely to differ depending on the type of episode being considered and the application.