Medicare Shared Savings Program accountable care organizations spent less on surgical care by reducing inpatient surgery, increasing outpatient surgery, and reducing spending on postacute care after inpatient surgery.
Objectives: Surgical care among older adults is costly. Although Medicare accountable care organizations (ACOs) are designed around primary care, there are reasons to believe that participation may also affect spending on surgery. This study examines the impact that Medicare Shared Savings Program ACO alignment has on spending for inpatient and outpatient surgical care.
Study Design: We conducted a retrospective cohort study using national Medicare claims (2008-2015).
Methods: Among a 20% random national sample of beneficiaries, we identified adults 65 years or older enrolled in fee-for-service Medicare, distinguishing between those aligned and unaligned with a Medicare Shared Savings Program ACO. We then measured payments for surgical services made on their behalf. Finally, we fit multivariable regression models to evaluate the association between ACO alignment and spending for inpatient and outpatient surgical care.
Results: We identified 37,249,845 beneficiary-year observations, of which 2,950,188 (7.9%) were aligned with an ACO. After adjustment for patient factors, ACO alignment was associated with $181 lower spending per beneficiary-year (95% CI, –$243 to –$118; P < .001). ACO alignment was associated with 2.9% fewer inpatient surgical episodes per year (incidence rate ratio, 0.97; 95% CI, 0.96-0.98; P < .001), but 2.3% more outpatient episodes per year (incidence rate ratio, 1.02; 95% CI, 1.02-1.03; P < .001). Among inpatient surgical episodes, average payments were $956 lower for ACO-aligned beneficiaries (95% CI, –$1218 to –$694; P < .001).
Conclusions: Medicare Shared Savings Program ACO alignment was associated with savings on surgical care. These savings resulted from increased outpatient surgery and reduced use of inpatient surgery, as well as reduced spending per inpatient surgical episode. Greater focus on surgical care may improve the ability of ACOs to control health care spending.
Am J Accountable Care. 2020;8(3):12-19
Surgery is highly prevalent in older adults and, as the population ages, accounts for an increasing share of health care spending in the United States.1 In fact, recent estimates suggest that more than half of total annual Medicare payments are attributable to surgical care.2 Moreover, there is considerable variation in spending on surgery across geographic regions that cannot be explained by differences in disease incidence or severity,3,4 suggesting an opportunity for CMS to reduce spending growth and maintain (or even enhance) quality. One major initiative that may help achieve this is Medicare’s Shared Savings Program accountable care organization (ACO) model.
Although Medicare ACOs are designed around the provision of primary care services, participation may influence spending on surgery in several ways. Medicare ACOs use shared accountability and collective incentives to encourage deeper clinical integration among physicians, hospitals, and other health care providers.5 Because they are held accountable for all costs of aligned beneficiaries, participating primary care providers (PCPs) may consider how costly surgeons are in their referral decisions. Further, when an aligned beneficiary undergoes surgery, participating PCPs’ focus on care coordination may smooth care transitions during the surgical episode, reducing costly readmissions. The potential of shared savings payments may motivate participating surgeons to be more cost conscious. In response, they may raise their thresholds for intervention or shift care to lower-cost settings (eg, ambulatory surgery centers) when surgery is deemed necessary.
To understand what impact, if any, the ACO model has had on surgical spending, we analyzed national Medicare data over 2008 to 2015. After identifying all inpatient and outpatient surgical episodes that occurred in our sample, we measured total spending made on the behalf of beneficiaries during these episodes. We then fit multivariable regression models to evaluate for differences in surgical spending, as well as the probability of undergoing surgery, between beneficiaries who are either aligned or unaligned with an ACO.
Data Source and Study Population
We analyzed claims data from the Medicare Provider and Analysis Review, Carrier, and Outpatient Research Identifiable Files (RIFs) over 2008 to 2015 for a 20% national sample of beneficiaries. We restricted this cohort to beneficiaries who were 65 years or older and enrolled in fee-for-service Medicare. To be included, a beneficiary needed continuous Part A and Part B coverage throughout a given study year or until death during that year. We excluded beneficiaries participating in Medicare managed care plans, as well as those who resided outside the United States or Puerto Rico due to the incomplete availability of their claims. Finally, we excluded beneficiaries who did not receive any primary care services in a given study year (12.5% of otherwise eligible beneficiaries) because they would have been ineligible for ACO alignment according to Medicare policy.6
Our exposure of interest was beneficiary alignment to a Medicare Shared Savings Program ACO. To distinguish beneficiaries who were aligned to an ACO from those who were not, we used the Shared Savings Program Beneficiary-level RIF. Specifically, we defined a time-varying indicator, set to 1 during a given study year if a patient was aligned to an ACO that year. It took the value of 0 otherwise. For 2012, corresponding to the first year of the Shared Savings Program, there were 2 ACO start dates. For beneficiaries aligned to an ACO that year with an April 1 start date, our indicator took the value of 0.75; for those aligned to an ACO that year with a July 1 start date, our indicator took the value of 0.5.
The primary outcome was per beneficiary spending on surgery, which we calculated for each study year. Our secondary outcome was the occurrence of a surgical episode within a given study year. To measure per beneficiary spending on surgery, we first determined whether a beneficiary underwent a surgical procedure within a given year. We did this using Health Care Procedure Coding System (HCPCS) codes for surgery on the integumentary (10000-19999), musculoskeletal (20000-29999), respiratory (30000-32999), cardiovascular (33000-37799, 93451-93662), hemic and lymphatic (38000-38999), mediastinum and diaphragm (39000-39999), digestive (40000-49999), urinary (50000-53999), male (54000-55899) and female genital (55900-59999), endocrine (60000-60999), nervous (61000-64999), ocular (65000-68999), and auditory (69000-69999) systems to identify relevant claims in the Carrier RIF.
Next, we used appropriate Place of Service and Type of Service codes appearing on a beneficiary’s claims to distinguish between inpatient and outpatient procedures, as well as outpatient procedures carried out in hospital outpatient departments vs freestanding ambulatory surgery centers vs the physician’s office. We excluded surgical procedures that took place in a skilled nursing facility or extended-stay rehabilitation facility.
We then summed all payments for claims filed on a beneficiary’s behalf during the surgical episode. For inpatient procedures, we summed all payments for claims beginning 3 days prior to admission and extending 90 days after discharge. Any beneficiary who had an inpatient surgical episode that would extend into the next calendar year was required to have Medicare eligibility for the months included in the episode window, and spending within that window was included in the study year of the index procedure. We further categorized the major components of payments, including those for the index hospitalization, readmissions, professional payments, and postacute care.
Given that postoperative complications and planned readmissions are uncommon following outpatient procedures,7,8 we defined the outpatient surgical episode as including all claims for services delivered within a 3-day window around the index outpatient procedure. For measurement purposes, if a beneficiary underwent an outpatient procedure within 90 days of discharge from a surgical admission, we considered it part of the inpatient episode. We summed all surgical episode payments made on behalf of a given beneficiary each study year and inflation-adjusted these payments to 2015 US dollars using the Consumer Price Index.9
For our initial analytic step, we compared ACO-aligned and -unaligned beneficiaries across a variety of sociodemographic characteristics, including age, sex, race, urban/rural residence, and socioeconomic class (measured at the beneficiary zip code level).10 We also compared beneficiaries with respect to their level of comorbid illness (based on CMS’ Hierarchical Condition Categories).11 To determine whether observed differences were significant, we used parametric and nonparametric tests where appropriate.
With the beneficiary-year serving as our unit of analysis, we fit multivariable linear models regressing per beneficiary spending on our ACO indicator to evaluate for differences between aligned and unaligned beneficiaries. Next, to understand the extent to which differences in procedure mix may drive differences in surgical spending, we repeated the analysis of inpatient spending, including indicators for each diagnosis-related group (DRG) as fixed effects. We then used negative binomial regression to measure the association between the number of surgical procedures a beneficiary undergoes in a given study year and their ACO alignment status. To explore mechanisms for savings, we fit separate models, including only beneficiaries who underwent an inpatient surgical episode, and examined the association between ACO alignment and the components of inpatient spending (as defined previously). We estimated all models with robust standard errors to account for potential correlation of observations.12 In our models, we included ACO fixed effects, with unaligned beneficiaries considered part of a single group. We also included the sociodemographic and comorbid illness variables described previously, hospital referral region,13 and year fixed effects.
Finally, we performed 3 sensitivity analyses to examine the influence of ACO characteristics on the association between per beneficiary spending on surgery and alignment. Given emerging data suggesting that physician-led ACOs are associated with greater savings than hospital-led ACOs and hospital-physician collaborations,14 we first repeated our models including an interaction between our exposure and ACO leadership structure. We distinguished the latter using the Leavitt Partners ACO Database.15,16 Second, because ACO savings may increase with more experience participating as an ACO,14 we repeated our models including an interaction term between our exposure and an ACO’s duration of participation in the Shared Savings Program. For our third sensitivity analysis, we examined the effects of early (contract start date in 2012 or 2013) versus late (2014 or 2015) ACO model adoption on performance.
As an additional robustness check, we repeated outpatient surgical spending models to account for the type of outpatient procedure performed. We did this by adjusting models with groupings of HCPCS codes according to organ site and surgical specialty (see eAppendix Table 1 [eAppendix available at ajmc.com]).
We performed all statistical tests using SAS version 9.4 (SAS Institute) and Stata 14 (StataCorp). We derived all predicted spending and episode counts from our models using the margins postestimation command in Stata. All our statistical tests were 2-tailed, and we considered a P value of less than .05 to be statistically significant. This study was deemed by the University of Michigan Medical School’s institutional review board to be exempt from its oversight.
This study included 37,249,845 beneficiary-year observations, of which 2,950,188 (7.9%) were aligned with a Medicare Shared Savings Program ACO. Table 1 presents the demographic characteristics and unadjusted outcomes for these beneficiaries. Compared with unaligned beneficiaries, those aligned to an ACO tended to be older and come from higher socioeconomic strata (P < .0001 for each comparison). Unadjusted spending for ACO and non-ACO beneficiaries by year is represented in eAppendix Table 2.
Table 2 displays results from our multivariable models, examining the association between per beneficiary spending on surgery and ACO alignment. After accounting for the measured differences described previously, overall spending on surgery was $181 lower per year for ACO-aligned beneficiaries (95% CI, –$243 to –$118; P < .001). This difference was a result of lower inpatient surgical spending for ACO beneficiaries (–$198; 95% CI, –$261 to –$134; P < .001), which was offset by slightly higher average outpatient surgical spending ($17; 95% CI, $8-$26; P < .001). Table 2 demonstrates that these savings were due, in part, to increasing delivery of surgical care in less costly outpatient settings. Specifically, ACO alignment was associated with 2.9% fewer inpatient surgical episodes per year (incidence rate ratio [IRR], 0.97; 95% CI, 0.96-0.98; P < .001) but 2.3% more outpatient surgical episodes per year (IRR, 1.02; 95% CI, 1.02-1.03; P < .001). Among inpatient surgical episodes (Table 3), average payments were $956 lower for ACO-aligned beneficiaries (95% CI, –$1218 to –$694; P < .001).
This increased inpatient episode efficiency was driven by lower payments in each part of the inpatient episode: the index hospitalization, readmissions, postacute care, and professional payments (Table 3). In the model where we adjusted for differences in procedure mix (using indicator variables for each DRG), we found that a significant difference in favor of ACOs remained but was attenuated (Table 3). The index hospitalization component of inpatient episode spending (driven primarily by DRG-based payment to hospitals) was not significantly different in the model adjusting for DRG. The full results of all regression models are available in eAppendix Tables 3 through 8.
The Figure displays the results of the 3 remaining sensitivity analyses. There was no significant association between ACO leadership structure or years of ACO experience on surgical spending. However, ACOs with contract start dates in 2012 realized increased surgical savings relative to later adopters of the ACO model.
Finally, after adjusting for surgical procedure type, ACO alignment was associated with approximately $6 lower outpatient surgical spending per beneficiary per year (eAppendix Table 9).
As a major driver of Medicare spending, surgical care is an important target for ACOs aiming to bend the cost curve. We found that surgical spending was significantly lower for ACO-aligned beneficiaries than for unaligned beneficiaries, representing $181 in savings per beneficiary-year. We identified 2 potential explanations for this spending reduction. First, ACO-aligned beneficiaries underwent fewer costly inpatient procedures than their unaligned counterparts. There was evidence to suggest that ACOs provided more outpatient surgery than non-ACOs, potentially as a mechanism to reduce inpatient surgery use. Second, when ACO-aligned beneficiaries required inpatient surgery, their episode spending was, on average, $956 lower than that of unaligned beneficiaries. This observed increased inpatient episode efficiency for ACO-aligned beneficiaries held across all components of spending, but the bulk of the savings was due to lower payments for postacute care.
To date, most evaluations of Medicare ACOs have focused on changes in spending for general medical care and chronic disease management.14,17-19 Studies of ACO effects on surgical care delivery are more limited, and those that have been published demonstrate underwhelming results. Data suggest that hospital participation in an ACO is not associated with reductions in the use of low-value procedural care,20 improvements in cancer surgery,21 or better postoperative outcomes.22 Moreover, in contrast to our findings, prior empirical work demonstrated comparable inpatient surgical episode spending for ACO and non-ACO hospitals.23 One reason for this discordance relates to the fact that we evaluated surgical spending among ACO beneficiaries more globally, identifying possible drivers of reduced spending that are independent of hospital ACO participation. These include reduced referrals for elective surgery, shifting surgical procedures outside the hospital setting, and improved preventive and perioperative care.
Our results suggest potential strategies that ACOs use to lower surgical spending. One possibility is that our findings result from ACOs shifting care from the inpatient to the outpatient setting for their aligned beneficiaries. Outpatient surgical care delivered in hospital outpatient departments, ambulatory surgery centers, and the physician’s office has been shown to be of comparable quality to inpatient procedural care but substantially less costly.7,8,24 We also found that, after adjusting for outpatient surgical procedure (by organ system or surgical specialty), ACO alignment was associated with slightly lower spending on outpatient surgery. This could provide further evidence that the higher observed outpatient surgical spending in ACOs is due, in part, to case mix. That is, because of a shift of some inpatient procedures to the outpatient setting, ACOs actually spend more on outpatient surgery. It is also notable that the observed inpatient episode efficiency was due, in large part, to lower postacute care payments. This likely reflects the more judicious use of expensive postoperative ancillary services. Similar results were previously demonstrated in the general Medicare population.25 Another potential explanation for these findings is residual differences in case selection by ACO providers. If ACOs select healthier or less-costly patients for inpatient surgery, our results may be somewhat overestimating the effect of ACO participation on surgical spending. However, to mitigate this possibility, we adjusted our models with variables strongly associated with surgical spending, such as age, DRG, and comorbidities.
Our study findings must be considered in the context of several limitations. First, we examined differences in Medicare spending for surgical care and found that ACO participation was associated with reduced spending. However, we did not examine whether this decreased spending had any effect on surgical quality. Overall spending offers an important and quantifiable measure of performance, but it is 1 of several measures that are important to Medicare beneficiaries, policy makers, and society at large. Existing evidence for the impact that Medicare ACOs have on surgical outcomes is mixed, and additional work is needed to more comprehensively understand the relationship between ACO policy and surgical quality. Second, we defined surgical care episodes to include 90 days after discharge from an inpatient surgery and a 3-day window around the time of an outpatient procedure. We chose these definitions because they are widely used in both research and Medicare policy and can be expected to capture the majority of spending associated with surgical care.26 Nonetheless, they may exclude some relevant spending, particularly in the time frame preceding an inpatient surgical admission. Finally, the Medicare Shared Savings Program is a voluntary program, and ACOs participating in this program may differ from physicians and hospitals that do not form ACOs. In order to address this limitation, we controlled for patient factors and used ACO fixed effects in our models to account for time invariant differences in provider groups. Nonetheless, as our sensitivity analysis on early vs late ACO model adopters shows, selection effects remain a potential confounder of the association between ACO participation and surgical spending.
These limitations notwithstanding, our analysis has important policy implications. Medicare Shared Savings Program ACOs have generated modest savings to date, which have fallen short of expectations for some. However, we demonstrate that surgical care is a potential source of savings for ACOs. By performing more outpatient and fewer inpatient procedures and by more efficiently delivering inpatient surgical care, ACOs can reduce surgical spending at a population level. Early data suggest considerable variation in the number of surgeons participating in Medicare Shared Savings Program ACOs.27,28 Heterogeneity in surgeon involvement in ACOs is reflected in the literature on ACO effects on surgical quality and costs. Insofar as attention to surgical care has not been the focus of ACO leaders,29 the increased engagement of surgeons and a focus on improving the value of surgical care may represent an opportunity to magnify the impact of ACO policy.
The authors would like to acknowledge Andrew M. Ryan, PhD, for his comments on earlier versions of this work and his useful suggestions.
Author Affiliations: Dow Division of Health Services Research, Department of Urology, University of Michigan Medical School (PKM, NM, LAH, BKH, JMH), Ann Arbor, MI.
Source of Funding: This work was supported by grants from the National Cancer Institute to Dr Modi (F32CA232332), the National Institute on Aging (NIA) to Dr Hollenbeck (R01AG048071), and the Agency for Healthcare Research and Quality (AHRQ) to Dr Hollingsworth (R01HS024525 and R01HS024728). The views expressed in this article do not represent the views of the US federal government.
Author Disclosures: Dr Hollenbeck has received an NIA grant on accountable care organizations (ACOs). Dr Hollingsworth has received 2 grants from AHRQ (R01HS024525 and R01HS024728) on ACOs. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.
Authorship Information: Concept and design (PKM, NM, LAH, BKH, JMH); acquisition of data (BKH, JMH); analysis and interpretation of data (PKM, NM, LAH, BKH, JMH); drafting of the manuscript (PKM, NM, BKH); critical revision of the manuscript for important intellectual content (PKM, NM, LAH, BKH, JMH); statistical analysis (PKM, NM); obtaining funding (BKH, JMH); administrative, technical, or logistic support (BKH); and supervision (JMH).
Send Correspondence to: John M. Hollingsworth, MD, MS, Dow Division of Health Services Research, Department of Urology, University of Michigan Medical School, 2800 Plymouth Rd, Bldg 16, 1st Floor, Room 112W, Ann Arbor, MI 48109. Email: firstname.lastname@example.org.
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