Medicare: Increasing Hospital-Physician Consolidation Highlights Need for Payment Reform
Released: 2015-12-18T00:00:00

Letter

Background

E/M Office Visits and Other Services with Total Payment Rates that Vary Across Settings

E/M office visits are frequently performed services during which a physician or other provider assesses a patient’s health and begins managing his or her care. These services are predominantly performed in two settings—physician offices and HOPDs. Medicare FFS paid for approximately 250 million E/M office visits in 2013.

Under Medicare’s payment policy, Medicare’s total payment rate is higher when an E/M office visit is provided in an HOPD rather than in a physician office. When the service is provided in a physician office, Medicare makes a single payment to the physician at Medicare’s physician fee schedule non-facility rate. When the service is provided in an HOPD, Medicare makes two payments—one payment at the physician fee schedule facility rate and another payment to the hospital, typically at the hospital outpatient prospective payment system (OPPS) rate. The total of these two payment rates is higher than Medicare’s total payment rate when the service is provided in a physician office. For example, in 2013, the total Medicare payment rate for a mid-level E/M office visit for an established patient—billed under Healthcare Common Procedure Coding System (HCPCS) code 99213—was $51 higher when the service was performed in an HOPD instead of a physician office (see table 1).

While CMS modified the manner in which Medicare pays for E/M office visits after 2013, large differences in total payment rates continue to exist for E/M office visits. Beginning in 2014, CMS made the OPPS payment rate the same for all the HCPCS codes for E/M office visits. However, the new uniform OPPS payment rate combined with the physician fee schedule facility payment rate for E/M office visits provided in HOPDs continues to exceed the payment rate for the same services performed in physician offices. For example, in 2015, Medicare’s total payment rate for E/M office visits ranged from $58 to $86 higher when performed in an HOPD compared to a physician office, depending on the specific HCPCS code billed.

Many other services, such as imaging and surgical services, are also reimbursed at a higher rate by Medicare when performed in HOPDs versus other settings. For example, Medicare’s total payment rate for magnetic resonance imaging of the lumbar spine without dye (HCPCS code 72148) was about $29 higher when performed in an HOPD compared to a physician office in 2013. Furthermore, Medicare’s total payment rate for cataract surgery (HCPCS code 66984) was about $760 higher when performed in an HOPD compared to an ambulatory surgical center in 2013.

Some industry groups argue that higher payment rates for services performed in HOPDs are justified because hospitals treat sicker patients, incur higher costs due to the need to furnish emergency services, and provide services that are unavailable elsewhere in the community for vulnerable populations, such as those dually eligible for Medicare and Medicaid. However, in separate reports, MedPAC and the Department of Health and Human Services (HHS) Office of Inspector General have recommended or suggested that Congress eliminate or reduce differences in Medicare total payment rates across settings for various services, including E/M office visits, imaging services, and surgical services. To date, legislation fully addressing these recommendations has not been enacted.

Billing Practices after Vertical Consolidation between Hospitals and Physicians

Recent research suggests that hospitals and physicians are increasingly vertically consolidated, which allows services to shift from physician offices to HOPDs. When hospitals and physicians vertically consolidate, the hospital-owned practice must meet certain criteria to gain what is known as provider-based status, which allows the hospital to bill the HOPD rate, thereby increasing Medicare’s total payment rate for the same service. For example, the physician practice and hospital must be financially and clinically integrated. Further, although exceptions exist, physician practices are generally required to be within 35 miles of the hospital to gain provider-based status. If a practice meets these conditions, Medicare’s total payment rate for the same service can be substantially higher despite the fact that the practice’s location, the physicians who practice there, and the beneficiaries served could be the same as before consolidation occurred.

Data Indicate an Increase in Vertical Consolidation between Hospitals and Physicians from 2007 through 2013

Our analysis of AHA survey data shows that from 2007 through 2013, the number of vertically consolidated hospitals increased by 21 percent. Specifically, out of the approximately 4,700 surveyed hospitals included in our study, 1,408 or 30 percent of the hospitals reported having a vertical consolidation arrangement with physicians in 2007. This number increased to 1,707 or 36 percent in 2013—an average annual increase of 3.3 percent (see fig. 1).

In addition, AHA survey data also show that the number of vertically consolidated physicians nearly doubled between 2007 and 2013, with faster growth toward the end of this time period. Specifically, the number of these physicians increased from over 95,000 in 2007 to almost 182,000 in 2013—an average annual increase of 11.3 percent (see fig. 1). From 2010 to 2013, the number of vertically consolidated physicians grew at an average annual rate of 13.9 percent, compared to a rate of 8.8 percent from 2007 to 2010.

Although the increase in the number of vertically consolidated physicians occurred across a broad range of hospitals from 2007 through 2013, relatively few hospitals accounted for a large number of these physicians. AHA’s survey data show that the number of vertically consolidated physicians increased across all regions of the country; in both urban and rural areas; and among hospitals of different sizes. However, relatively few hospitals accounted for a large number of vertically consolidated physicians. For example, the 372 out of 1,707 vertically consolidated hospitals that had more than 100 vertically consolidated physicians accounted for 84 percent of all vertically consolidated physicians but only 22 percent of vertically consolidated hospitals in 2013 (see fig. 2).

Researchers and industry representatives whom we interviewed offered numerous potential explanations for the recent increases in vertical consolidation. Some stated that the trend could partially be explained by higher Medicare payment rates for services performed in HOPDs compared to other settings, the desire among some hospitals to gain market share, and changes in health care payment and delivery systems. For example, accountable care organizations, bundled payment models, and Medicare’s Hospital Readmissions Reduction Program—which penalizes hospitals for high rates of readmissions—provide incentives to vertically consolidate in order to improve care for beneficiaries, maximize payments, and minimize penalties. Researchers and industry representatives whom we interviewed also mentioned that the increasing challenges associated with managing a private physician practice, including financial and regulatory burdens, could also explain some of the increase in vertical consolidation. Some of these researchers and representatives added that hospitals and physicians may be vertically consolidating to enhance care coordination and improve efficiency.

Vertical Consolidation Associated with Higher Utilization of Medicare E/M Office Visits in Hospital Outpatient Departments Percentage of Medicare E/M Office Visits Performed in HOPDs Higher in Counties with Higher Levels of Vertical Consolidation

The percentage of E/M office visits—as well as the number of E/M office visits per beneficiary—performed in HOPDs, rather than physician offices, was generally higher in counties with higher levels of vertical consolidation in 2007 through 2013. The beneficiaries from counties with relatively high levels of vertical consolidation were not sicker, on average, than beneficiaries in counties with lower levels of consolidation.

Our analysis of AHA and Medicare claims data shows that the percentage of E/M office visits performed in HOPDs was generally higher in counties with higher levels of vertical consolidation in 2013. Specifically, after dividing counties into five equal groups based on their 2013 level of consolidation, we found that the median percentage of E/M office visits performed in HOPDs in the group of counties with the lowest levels of vertical consolidation was 4.1 percent. In contrast, this rate was 14.1 percent for the counties with the highest levels of consolidation (see fig. 3).

For years 2007 to 2012, the percentage of E/M office visits performed in HOPDs was also generally higher in counties with higher levels of vertical consolidation, though the association was weaker compared to 2013. For example, the median percentage of E/M office visits performed in HOPDs in the group of counties with the lowest level of vertical consolidation was 3.9 percent in 2007, compared to a median of 7.3 percent in the counties with the highest levels of consolidation.

As part of our analysis, we also calculated the number of E/M office visits in each county on a per beneficiary basis. We found that the number of E/M office visits performed in HOPDs per 100 Medicare beneficiaries was also generally higher in counties with higher levels of vertical consolidation each year from 2007 through 2013. For example, in 2013 the number of E/M office visits performed in HOPDs per 100 beneficiaries was 26 for the counties with low levels of vertical consolidation, whereas the number was substantially higher—82 services per 100 beneficiaries— in counties with the highest level of vertical consolidation. We found similar correlations in 2007 through 2012. (See app. III for additional analyses of the number of E/M office visits performed in HOPDs in counties with different levels of vertical consolidation from 2007 through 2013.)

The association we found between higher levels of vertical consolidation and higher utilization of E/M office visits in HOPDs remained even after controlling for differences in county-level characteristics and other market factors that could affect the setting in which E/M office visits are performed. Specifically, we developed a regression model that controlled for county characteristics that do not change over relatively short periods of time, such as whether a county is urban or rural, and county characteristics that could change over time, such as the level of competition among hospitals and physicians within counties. Our regression model’s results were similar to our initial results: the level of vertical consolidation in a county was significantly and positively associated with a higher number and percentage of E/M office visits performed in HOPDs—that is, as vertical consolidation increased in a given county, the number and percentage of E/M office visits performed in HOPDs in that county also tended to be higher. (See app. I and app. II for more information on our regression model and results.)

Medicare Beneficiaries in Counties with Higher Levels of Vertical Consolidation Were Not Sicker Than Those in Counties with Lower Levels of Consolidation

Beneficiaries from counties with higher levels of vertical consolidation were not sicker, on average, than beneficiaries from counties with lower levels of consolidation. Specifically, beneficiaries from counties with higher levels of vertical consolidation tended to have either similar or slightly lower median risk scores, death rates, rates of end-stage renal disease, and rates of disability compared to those from counties with lower levels of consolidation (see table 2). Further, counties with higher levels of consolidation had a lower percentage of beneficiaries dually eligible for Medicaid, who tend to be sicker and have higher Medicare spending than Medicare beneficiaries who are not dually eligible for Medicaid. This suggests that areas with higher E/M office visit utilization in HOPDs are not composed of sicker than average beneficiaries.

As we previously stated, the extent of vertical consolidation grew from 2007 through 2013. Coinciding with that growth, we found that E/M office visits were performed more frequently in the higher paid HOPD setting in counties with higher levels of vertical consolidation. Such excess payments are inconsistent with Medicare’s role as an efficient purchaser of health care services. According to CMS, the agency does not have the statutory authority to equalize total payment rates between HOPDs and physician offices. Further, CMS lacks the authority to return the associated savings to the Medicare program. Therefore, absent legislative intervention, the Medicare program will likely pay more than necessary for E/M office visits.

Conclusions

From 2007 through 2013, the number of vertically consolidated physicians nearly doubled, with faster growth in more recent years. Regardless of what has driven hospitals and physicians to vertically consolidate, paying substantially more for the same service when performed in an HOPD rather than a physician office provides an incentive to shift services that were once performed in physician offices to HOPDs after consolidation has occurred. Our findings suggest that providers responded to this financial incentive: E/M office visits were more frequently performed in HOPDs in counties with higher levels of vertical consolidation. We found this association in both our analysis of E/M office visit utilization in counties with varying levels of vertical consolidation and in our regression analyses. Further, our analysis of 2013 health status data suggests that beneficiaries from counties with higher levels of vertical consolidation, where we found more E/M office visits performed in HOPDs, were not sicker, on average, than beneficiaries who lived in counties with lower levels of consolidation, where we found fewer E/M office visits performed in HOPDs.

While vertical consolidation has potential benefits, we found that the rise in vertical consolidation exacerbates a financial vulnerability in Medicare’s payment policy: Medicare pays different rates for the same service, depending on where the service is performed. Although Medicare aims to be an efficient purchaser of health care services, CMS has stated that the agency currently lacks the authority to equalize payment rates between settings. Further, CMS lacks the authority to return the associated savings to the Medicare program. Until the disparity in payment rates for E/M office visits is addressed, Medicare could be expending more resources than is necessary.

Matter for Congressional Consideration

In order to prevent the shift of services from physician offices to HOPDs from increasing costs for the Medicare program and beneficiaries, Congress should consider directing the Secretary of HHS to equalize payment rates between settings for E/M office visits—and other services that the Secretary deems appropriate—and to return the associated savings to the Medicare program.

Agency and Third- Party Comments and Our Evaluation

HHS provided technical comments on a draft of this report, which we incorporated where appropriate. In addition, we provided two organizations—the American Medical Association and AHA—the opportunity to review our draft because these organizations represent the types of providers and care settings that were the main focus of our report. The American Medical Association had no comments. AHA did not comment on the main finding of our report—that higher levels of vertical consolidation were associated with more E/M office visits being performed in HOPDs instead of physician offices. Further, AHA noted several reasons why, in their opinion, a service performed in an HOPD should receive a higher Medicare reimbursement compared to when the same service is performed in other settings. AHA did comment on two specific aspects of our report—our characterization of beneficiary health status and reasons why vertical consolidation occurs. A summary of these comments and our response are below.

AHA gave several reasons why a service performed in an HOPD should receive a higher Medicare reimbursement compared to when the same service is performed in other settings, such as physician offices. For example, AHA commented that HOPD payment rates are based on audited cost reports and should not be based on physician payment rates. We acknowledge that it might be inappropriate to equalize the total Medicare payment rate for all services. However, Medicare aims to be a prudent purchaser of health care services, and that goal is not achieved if Medicare’s total payment rate for certain services—such as E/M office visits—is substantially higher simply because hospitals have acquired physician practices. Other entities such as MedPAC have also suggested that Medicare base its payments for services on the lowest cost, clinically appropriate setting.

AHA stated that it disagreed with what it interpreted our report to show— that overall, patients treated at HOPDs are not sicker than those treated at physician offices. Our report does not make such an assertion, but does include our finding that beneficiaries residing in counties with higher levels of vertical consolidation were not sicker, on average, than beneficiaries residing in counties with lower levels of consolidation. Given that counties with higher levels of vertical consolidation had more E/M office visits performed in HOPDs, our evidence suggests that areas with higher E/M office visit utilization in HOPDs were not composed of sicker than average beneficiaries.

AHA commented that vertical integration—what our report terms vertical consolidation—is an essential ingredient for successful implementation of the Patient Protection and Affordable Care Act and that we failed to adequately account for reasons other than payment differentials that drive vertical consolidation. Our report notes multiple reasons, identified by the researchers and industry experts we interviewed, as to why hospitals and physicians might vertically consolidate. These potential reasons include certain payment and delivery changes associated with the Patient Protection and Affordable Care Act. While we identified multiple factors that may be contributing to increases in vertical consolidation, a full analysis of the causes or the appropriateness of vertical consolidation between hospitals and physicians was outside the scope of our work.

We are sending copies of this report to the appropriate congressional committees, the Secretary of HHS, and the CMS administrator. In addition, the report is available at no charge on the GAO website at http://www.gao.gov.

If you or your staffs have any questions about this report, please contact me at (202) 512-7114 or cosgrovej@gao.gov. Contact points for our Offices of Congressional Relations and Public Affairs may be found on the last page of this report. GAO staff who made key contributions to this report are listed in appendix V.

Appendix I: Scope and Methodology

This appendix describes the scope and methodology used to examine our two objectives: (1) trends in vertical consolidation between physicians and hospitals from 2007 through 2013 and (2) the extent to which higher levels of vertical consolidation were associated with more evaluation & management (E/M) office visits being performed in hospital outpatient departments (HOPD) instead of physician offices from 2007 through 2013.

Examining Trends in Vertical Consolidation between Hospitals and Physicians

To examine trends in vertical consolidation between hospitals and physicians, we used survey data from the American Hospital Association (AHA) Annual Survey Database,TM in which hospitals report what types of relationships they have with physicians and the number of physicians in those relationships, and Medicare Provider Analysis and Review (MedPAR) files, which contain information on Medicare inpatient discharges for short-term acute care hospitals, from 2007 through 2013. First, we used MedPAR data to identify hospitals that served at least one Medicare beneficiary from 2007 through 2013. We then took that list of hospitals—which are identified using their Centers for Medicare & Medicaid Services Certification Number—and, using the AHA Annual Survey Database,TM determined whether each hospital was vertically consolidated with physicians in each year from 2007 through 2013. Similar to previous research on vertical consolidation, we considered a hospital to be vertically consolidated if it had one of three types of relationships with physicians—an integrated salary, foundation, or equity model. (See table 3 for a description of these three arrangements.)

To identify the number of vertically consolidated hospitals, we counted the number of hospitals with any one of these three types of relationships. To identify the number of vertically consolidated physicians, we implemented edits to modify reported counts of vertically consolidated physicians that we believed were likely duplicative and then summed the number of physicians. We identified duplicative survey responses as those where hospitals reported more than 10 vertically consolidated physicians and also reported the same number of vertically consolidated physicians as another hospital in the same hospital system. In such instances, we assumed that the total number of vertically consolidated physicians associated with a hospital system was reported multiple times by more than one hospital.

Additionally, based on a review of pertinent literature, we identified and interviewed industry representatives and academic researchers. To better understand hospitals’ perspectives on vertical consolidation, we interviewed officials from AHA. Similarly for physicians, we interviewed the American Medical Association and Medical Group Management Association. We also interviewed numerous academic researchers to better understand issues such as the various types of hospital-physician relationships, possible data sources to track vertical consolidation, and health care system policies that could be driving consolidation.

Examining the Extent to Which Higher Levels of Vertical Consolidation Were Associated with More E/M Office Visits Being Performed in Hospital Outpatient Departments

Bivariate Analyses and Variable Construction

To attribute E/M office visits to a given county, we used the beneficiary county of residence that was listed on the Carrier and Outpatient file claims. To determine the total number of E/M office visits that were performed in a given county, we combined the number of E/M office visits from the Carrier file and the number of E/M office visits associated with professional claims in the Medicare Outpatient file. To determine the number of E/M office visits performed in HOPDs in a given county, we summed the number of services billed in the Medicare Outpatient file, including services provided by critical access hospitals. The number of E/M office visits performed in physician offices was calculated by subtracting the number of HOPD services from the total number of services. To calculate the number of services per Medicare beneficiary in a given county, we used the Medicare Denominator file to identify fee-for- service (FFS) beneficiaries.

To calculate the level of vertical consolidation in each county, we used the AHA Annual Survey DatabaseTM and MedPAR claims. First, we calculated the share of MedPAR services that were delivered by vertically consolidated hospitals in each zip code in which a beneficiary received at least one service. We then created a weighted average hospital level vertical consolidation measure using all the zip codes a hospital served in a year. Finally, we created a weighted average county level vertical consolidation measure based on the hospitals that served each county. To calculate control variables for our regression analyses, we used a similar process. Specifically, we calculated variables for profit status, public vs. private ownership, hospital size, teaching status, whether a hospital belonged to a system, and Herfindahl-Hirschman Indexes (HHI) for hospital and physician market concentration.

To determine how the level of vertical consolidation in a county was associated with the setting in which E/M office visits were provided before controlling for other factors, we conducted a bivariate analysis for every year from 2007 through 2013. Specifically, we ranked counties into quintiles based on the level of consolidation in each county in 2013. In the bottom quintile were the 20 percent of counties with the lowest levels of vertical consolidation; such counties were considered to have low levels of vertical consolidation. In order, the next four quintiles were considered to have medium-low, medium, medium-high, and high levels of vertical consolidation. For 2007 through 2012, we used the same thresholds to sort counties into the five levels of consolidation. Within each of the five county groups for each year, we then calculated the 1) median and mean percentage of E/M office visits that were performed in HOPDs and physician offices and 2) the median and mean number of E/M office visits per beneficiary performed in HOPDs, physician offices, and in total.

To determine whether counties with higher levels of vertical consolidation had sicker or healthier beneficiaries, we calculated descriptive statistics for beneficiaries who lived in a given county in 2013 using the Medicare denominator file. Specifically, for each county, we calculated the mean and median risk score, age, and the percentage of beneficiaries that died, had end-stage renal disease, were disabled, and were dually eligible for Medicare and Medicaid. Similar to the bivariate analysis described above, we then we ranked counties into quintiles based on the level of vertical consolidation in 2013. Within the quintiles, we calculated the median and mean values for each of the variables.

Panel-Data Regression Model

We developed an econometric model to analyze the effect of vertical consolidation on the setting where beneficiaries received E/M office visits from 2007 through 2013. Specifically, we analyzed how the level of vertical consolidation affected 1) the percentage of E/M office visits performed in HOPDs, 2) the number of E/M office visits performed in HOPDs per beneficiary, and 3) the total number of E/M office visits per beneficiary. Our analysis used data for 3,121 U.S. counties from 2007 through 2013.

Dependent Variables

Yit=log (rit/(1−rit))

Where rit represents the proportion of E/M office visits that were provided in an HOPD, and the i and t subscripts represent the county and year, respectively. This formulation has the advantage of allowing the dependent variable to range over all values for any value of r between zero and one.

For our models analyzing the number of E/M office visits performed in HOPDs per beneficiary and the total number of E/M office visits per beneficiary, our dependent variables were the logarithm of the number of services per beneficiary.

Explanatory Variables

Our key explanatory variable was the level of vertical consolidation.

Our hypothesis was that higher levels of vertical consolidation would be associated with a higher percentage and number of E/M office visits being performed in HOPDs.

Our model controlled for horizontal physician and horizontal hospital concentration, using HHIs. We hypothesized that greater concentration of market power among physicians would lead to E/M office visits being provided in physician offices rather than HOPDs, all else being equal. In contrast, we hypothesized that greater concentration of market power among hospitals would lead to E/M office visits being provided in HOPDs rather than physician offices, all else being equal.

Our model included hospital characteristic variables to account for possible differences in hospital size and institutional arrangements. Specifically, our model included variables for the following hospital characteristics: profit status, public vs. private ownership, hospital size, teaching status, and whether a hospital belonged to a system.

Our model included time fixed effects (a dummy variable for each year in the analysis). In addition, we included county fixed effects (a dummy variable for each of the 3,121 counties in the analysis). These county fixed effects assist in controlling for unobserved heterogeneity.

Model Specification

The regression analysis used a panel data model for 3,121 U.S. counties for the years 2007 through 2013 as follows:

Yit is the dependent variable for county i in year t. For the model analyzing the percentage of E/M office visits performed in HOPDs, the dependent variable is the logit transformation of the percentage of is the percentage of E/M office visits in an HOPD. For our models analyzing the number of E/M office visits performed in HOPDs per beneficiary and the total number of E/M office visits per beneficiary, services in an HOPD setting—that is, Yit=log (rit/(1−rit)), where ri t, Yit=log (sit), where sit, is the number of services per Medicare beneficiary. c is a fixed effect or dummy variable for county i. fis a fixed effect or dummy variable for year t. are the hospital-characteristic variables and market structure variables, such as horizontal physician HHI, horizontal hospital HHI, and vertical consolidation, associated with county i at time t, and α are the parameters associated with each of these variables. εit are the error terms.

We used xtivreg2 in STATA to estimate our models. Our parameter estimates are consistent given the assumptions of our model. Our standard errors are robust to heteroskedasticity and clustering at the county level.

The hospital characteristics, the horizontal hospital HHI, and the vertical consolidation measures were calculated using MedPAR data, while the dependent variable was calculated using Outpatient and Carrier file data. This separation reduced the likelihood that these market characteristics were correlated with unobserved determinants of the setting where beneficiaries received E/M office visits. However, the physician HHI measure was calculated using Carrier file data, so we tested this variable for endogeneity.

Limitations

Our study has some limitations. While the response rate for the AHA Annual Survey DatabaseTM was high for each year—about 76 percent— the data on vertical consolidation was self-reported by hospitals. In the process of examining the AHA Annual Survey Database,TM we identified responses that we believe were likely duplicative. However, our ability to identify and fix duplicative responses is limited because we were not able to directly contact survey respondents based on our data licensing agreement. Second, because the AHA Annual Survey DatabaseTM does not contain identifying information for vertically consolidated physicians, we used hospital inpatient markets to proxy vertically consolidated physician markets. Although this is a limitation, we conducted a sensitivity analysis with HOPD markets, and our results held. Further, we believe there are several reasons why vertically consolidated physician markets should substantially overlap with hospital inpatient markets. For example, physician practices generally must be located within 35 miles of its parent hospital to bill as an HOPD, and many payment reforms—such as accountable care organizations, bundled payments, and Medicare’s Hospital Readmissions Reduction Program—reward hospitals for managing their patients across inpatient and outpatient settings. Third, vertically consolidated hospitals varied widely in terms of the number of vertically consolidated physicians associated with them. While our bivariate and regression analyses only consider a hospital vertically consolidated if it has more than 10 vertically consolidated physicians, we were unable to make our measure of vertical consolidation reflect the intensity of vertical consolidation relationships—that is, the number of vertically consolidated physicians per hospital—because of data limitations. Finally, time lags may occur between vertical consolidation and our measures of how often E/M office visits are performed in an HOPD. A hospital can purchase physician practices and not convert them to HOPDs immediately or ever. Consequently, these lags may be long and variable, and we have no systematic data to measure the timing of these possible effects.

Data Reliability and Audit Standards

We took several steps to ensure that the data used to produce this report were sufficiently reliable. Specifically, we assessed the reliability of the Centers for Medicare & Medicaid Services data and the AHA Annual Survey DatabaseTM we used by interviewing officials responsible for overseeing these data sources. We also reviewed relevant documentation and examined the data for obvious errors, such as missing values and values outside of expected ranges. We determined that the data were sufficiently reliable for the purposes of this report.

We conducted this performance audit from February 2014 through December 2015 in accordance with generally accepted government auditing standards. Those standards require that we plan and perform the audit to obtain sufficient, appropriate evidence to provide a reasonable basis for our findings and conclusions based on our audit objectives. We believe that the evidence obtained provides a reasonable basis for our findings and conclusions based on our audit objectives.

Appendix II: Full Regression Results

This appendix provides more detailed results for the models we used to analyze the effect of vertical consolidation on the setting where beneficiaries received E/M office visits from 2007 through 2013.

Counties with higher levels of vertical consolidation were significantly more likely to have a higher proportion of their E/M office visits performed in HOPDs. These counties also had a significantly higher rate of utilization of E/M office visits in HOPDs. However, those same counties also had a significantly lower rate of overall utilization of E/M office visits, although the size of this negative association was smaller. Specifically, all else being equal, our models predict that a county with no vertical consolidation going to completely consolidated would experience: an increase in the percent of E/M office visits performed in HOPDs of 2.7 percentage points on average; an increase in the number of E/M office visits per beneficiary being performed in HOPDs of approximately 30 percent on average; and a decrease in the total number of E/M office visits per beneficiary of less than 2 percent on average.

We used a set of medical service supply variables from the Area Health Resource Files as instruments: the number of federal and non- federal active MDs as a percentage of the total population, total hospital beds per capita, and whether the area was designated as a health care professional shortage area for primary care physicians.

In our models of the percentage of E/M office visits performed in HOPDs and total number of E/M office visits per beneficiary, the C-test accepted the null hypothesis of exogeneity of the physician horizontal Herfindahl-Hirschman Index (HHI) variable, and the Hansen J-statistic accepted the null hypothesis that our instruments were valid. The Sanderson-Windmeijer test also supported our use of these instruments, by rejecting the null hypothesis of weak instruments.

In our model of the number of E/M office visits performed in HOPDs, the Hansen J-statistic accepted the null hypothesis that our instruments were valid, and the Sanderson-Windmeijer test rejected the null hypothesis of weak instruments. However, the C- test rejected the null hypothesis of exogeneity of the physician horizontal HHI variable, so we report our instrumental variable estimates for our log of utilization of E/M office visits performed in HOPDs.

A full set of results is provided in table 4.

Appendix III: Evaluation & Management Office Visit Utilization by Level of Vertical Consolidation, 2007 through 2013

The percentage of E/M office visits—as well as the number of E/M office visits per 100 beneficiaries—performed in HOPDs was generally higher in counties with higher levels of vertical consolidation from 2007 through 2013 (see tables 5 - 11).

Appendix IV: Association between Vertical Consolidation and Overall Utilization of Evaluation & Management Office Visits across All Settings

To examine whether vertical consolidation affected total utilization, we examined the association between vertical consolidation in a county and the total number of evaluation & management (E/M) office visits per beneficiary and found mixed results. Specifically, while counties with the lowest level of vertical consolidation had higher total utilization of E/M office visits compared to counties with the highest levels of vertical consolidation, total utilization of E/M office visits neither increases nor decreases consistently as the level of vertical consolidation increases in a county in our bivariate analysis. For example, in 2013, the median number of total E/M office visits per 100 beneficiaries decreased from 658 among the counties with the lowest levels of vertical consolidation to 580 among counties with a medium level of vertical consolidation; however, among counties with high levels of vertical consolidation, the number increased to 601. Furthermore, unlike our results examining the setting in which E/M office visits were performed, our results changed when we tested an alternative measure of vertical consolidation. For example, using the alternative specification, the median number of total E/M office visits per 100 beneficiaries in counties with the highest level of vertical consolidation was at least 10 services per 100 beneficiaries higher than in counties with the lowest level of consolidation in 4 out of 7 years from 2007 through 2013.

Appendix V: GAO Contact and Staff Acknowledgments

GAO Contact

Staff Acknowledgments

In addition to the contact above, Jessica Farb, Assistant Director; Todd Anderson; Krister Friday; Michael Kendix; Richard Lipinski; Brian O’Donnell; Dan Ries; Said Sariolghalam; Eric Wedum; and Jennifer Whitworth made key contributions to this report.