WORKING 

 PAPERS

Two Hospital Mergers on Chicago’s North Shore: 

A Retrospective Study

Deborah Haas-Wilson

Christopher Garmon

WORKING PAPER NO. 294

January 2009

___________________________________________________________________________

FTC Bureau of Economics working papers are preliminary materials circulated to stimulate discussion

and critical comment. The analyses and conclusions set forth are those of the authors and do not

necessarily reflect the views of other members of the Bureau of Economics, other Commission staff, or

the Commission itself. Upon request, single copies of the paper will be provided. References in

publications to FTC Bureau of Economics working papers by FTC economists (other than

acknowledgment by a writer that he has access to such unpublished materials) should be cleared with the

author to protect the tentative character of these papers.

______________________________________________________________________________

BUREAU OF ECONOMICS

FEDERAL TRADE COMMISSION

WASHINGTON, DC 20580
 The views expressed in this paper are the authors’ and not necessarily those of the 1

Commission or any individual Commissioner. We are thankful to Michelle Kambara, who

provided outstanding research support and programming assistance to this project. We are also

thankful to anonymous referees for their suggestions which considerably improved the current

draft over previous versions. All remaining errors are the authors’ sole responsibility.

1

Two Hospital Mergers on Chicago’s North Shore: A Retrospective Study

Deborah Haas-Wilson

Smith College

Northampton, MA

Christopher Garmon1

Federal Trade Commission

Washington, DC

Abstract: We provide an in-depth analysis of the price effects of two hospital mergers that

occurred in the north shore suburbs of Chicago in early 2000: Evanston Northwestern

Healthcare’s (ENH) purchase of Highland Park Hospital (HPH) and the merger of St. Therese

Medical Center (STMC) and Victory Memorial Hospital (VMH). Using standard difference-indifferences methods with data from multiple sources, including health insurance data with actual

transactions prices, we find that the ENH/HPH merger led to a large and statistically significant

post-merger price increase. We find no evidence of a price increase after the STMC/VMH

merger. These results are robust across data sources, control groups, and case mix adjustment

methods.
“Building a Strong Foundation: The FTC Year in Review,” Federal Trade Commission, 2

April 2002, page 9. http://www.ftc.gov/os/2002/04/ftcyearreview.pdf

Ibid, page 9. 3

“Everything Old is New Again: Health Care and Competition in the 21 Century,” 4 st

prepared remarks of Chairman Timothy Muris before the 7 Annual Competition in Health Care th

Forum, Chicago, IL, November 7, 2002, pages 19-20.

http://www.ftc.gov/speeches/muris/murishealthcarespeech0211.pdf

“Statement of the Federal Trade Commission, Victory Memorial Hospital/ Provena St. 5

Therese Medical Center, File #0110225,”

http://www.ftc.gov/os/caselist/0110225/040630ftcstatement0110225.htm, accessed on 9/5/2008

2

In April 2002, the Federal Trade Commission announced the Hospital Merger

Retrospectives Project; an initiative to study consummated hospital mergers “to determine

whether particular hospital mergers have led to higher prices.” As described by then-FTC 2

Chairman Timothy Muris in a speech given in the fall of 2002, there were two objectives of the

Hospital Merger Retrospectives Project: to allow the Commission to “consider bringing

enforcement actions against consummated, anticompetitive hospital mergers” and “to update 3

[the Commission’s] prior assumptions about the consequences of particular transactions and the

nature of competitive forces in health care.” One motivating factor for this project was the series 4

of six straight unsuccessful hospital merger challenges made by the FTC, the Department of

Justice, and California’s Attorney General in the mid to late 1990s. This string of six straight

defeats led many in the health economics community to call for a renewed study of hospital

competition and a different approach to hospital merger enforcement (e.g., Capps, Dranove,

Greenstein, and Satterthwaite (2002)). In the Hospital Merger Retrospectives Project, a handful

of consummated hospital mergers were selected for intensive study to better understand hospital

competition and the effects of hospital mergers. 

Two of the hospital mergers chosen for the project occurred in the north shore suburbs of

Chicago in early 2000. On January 1, 2000, Evanston Northwestern Healthcare (ENH)–with a

flagship teaching hospital in Evanston and a community hospital in Glenview–purchased nearby

Highland Park Hospital (HPH). Exactly one month later, Provena St. Therese Medical Center

(STMC) and Victory Memorial Hospital (VMH), both community hospitals located in

Waukegan, combined to form Vista Health. In 2002, the FTC opened investigations of both

mergers as part of the Hospital Merger Retrospectives Project. Ultimately, the investigation of

the Waukegan merger was closed because the Commission found little evidence of

anticompetitive effects. However, the investigation of ENH’s acquisition of HPH led to an 5

administrative complaint by the FTC challenging the transaction as anticompetitive. After a trial

in 2005, an administrative law judge ruled that the acquisition violated antitrust law and this
 Deborah Haas-Wilson served as Complaint Counsel’s (i.e., FTC staff’s) primary 6

economic expert during the administrative trial.

 Apart from material made public in the ENH trial, we will not describe qualitative 7

evidence (e.g., documents, testimony, etc.) gathered in the investigations due to confidentiality.

Also, the effect of each merger on the quality of hospital services is beyond the scope of this

paper.

 We use the term “managed care organizations” to refer to all companies that offer

8

health care plans structured as managed care plans, whether the company offering the plan is

bearing the risk of loss or whether the employer is bearing the risk of loss.

3

decision was upheld by the Commission on appeal in 2007. In 2008, ENH elected to forego 6

further appeals and accept the Commission’s remedy of separate contracting for ENH and HPH

with binding arbitration.

In this paper, we estimate the effect of each merger on the prices the merging hospitals

negotiated with managed care organizations (MCOs). As a first step, we develop a simple 7,8

theoretical model that describes how the merger of competing hospitals can lead to a price

increase in the context of MCO/hospital negotiations. Then, for each merger, we estimate the

post-merger price change relative to a group of control hospitals after controlling for changes in

factors that may vary over time across hospitals (e.g., the severity of the hospital’s patients).

Unlike most of the previous literature on hospital competition and mergers, our estimates are

based on multiple data sources, including data collected directly from the hospitals and MCOs.

For two of the three data sources we use, the data contain the actual prices paid by the MCOs

and patients to the hospitals. 

For the Waukegan merger, we find mixed results: one MCO experienced a relative price

increase after the merger, but three MCOs experienced relative price decreases. Overall, we find

no post-merger change in price relative to controls at the combined STMC/VMH. For the

ENH/HPH acquisition, we find large and statistically significant relative post-merger price

increases for all but one of the MCOs for which we have data. These price increase estimates are

robust to different control groups and case mix adjustments and are consistent with the price

increases estimated using other data sources.

The paper is structured as follows. In section 1, we describe the negotiating process

between hospitals and MCOs and explain how a hospital merger can lead to a price increase or

decrease. Section 2 describes the methods and econometric model used to estimate the price

changes. Section 3 describes the data. Section 4 describes the resulting estimates, including

payer by payer estimates of the relative price change at each of the combined hospitals. Section 5

concludes.
Devers, Casalino, et al. (2003), p.421. 9

 Town and Vistnes (2001). 10

4

1. Hospital/Managed Care Organization Negotiations

Hospitals and MCOs conduct negotiations to determine the price of hospital services.

“Selective contracting” is the term used to describe the contracting strategy in which MCOs

negotiate prices with hospitals and select which hospitals or hospital systems to include in their

networks.

The contracts negotiated between MCOs and hospitals vary across MCOs, products

offered by MCOs (e.g., PPO, HMO, etc.), and hospitals. These contracts between MCOs and

hospitals fulfill multiple purposes, including (1) setting the price or price mechanism that will be

used to determine the price that the MCO will pay for hospital services; (2) setting forth the

extent and the procedures for the MCO to monitor and control the hospital utilization of its

enrollees, such as whether to pre-approve; and (3) spelling out the details of the billing

arrangement between the hospital and MCO. For example, the contract may contain a clause

that prohibits the hospital from “balance billing” enrollees, billing the enrollees for the

difference between a hospital’s list prices and its negotiated prices.

By selectively contracting, the MCO can try to negotiate prices below the hospital’s

charges or what can be thought of as the hospital’s “list prices.” Because the MCO may not

contract with all the hospitals in an area, the MCO can offer a higher volume of patients to

hospitals in return for lower prices from those hospitals. Selective contracting has been called

“one of the major innovations of managed care that changed competitive dynamics in the

hospital sector and increased plans’ negotiating leverage with hospitals.”9

Health care markets have evolved with the increased penetration of managed care

insurance. Selective contracting stimulates competition among those hospitals and physicians

vying for inclusion in MCOs’ provider networks. Under managed care, a hospital’s ability to

negotiate higher prices from MCOs is directly related to the extent to which there are substitutes

for that hospital. Likewise, a key factor in MCOs’ ability to extract price discounts from

hospitals is the MCO’s ability to shift its enrollees from one hospital to another.

A hospital’s bargaining power with MCOs, and thus that hospital’s ability to negotiate

higher prices, depends on the incremental value that hospital brings to the MCO’s network. A

particular hospital’s incremental value depends on (1) the extent to which hospitals outside the

MCO’s network are good substitutes for it or (2) if the MCO’s best alternative is to drop that

particular hospital without replacing it, then its bargaining clout depends on the degree to which

it adds value to the hospitals already in the network. The more important that particular hospital

is to insurers’ revenues (how that particular hospital affects the value of the hospital network

offered to potential enrollees), the greater is that particular hospital’s bargaining power. A10

hospital adds substantial value to the managed care plan’s network when individuals highly
5

value that hospital and there are no close substitutes for that hospital. Therefore, a hospital will

be able to negotiate higher prices with managed care plans in proportion to the degree to which

its withdrawal from the network decreases the value enrollees place on the remaining hospitals

in the network, and thus enrollees’ willingness to pay for insured access to the remaining

hospitals in the network. If the hospital that is threatening to withdraw has a close substitute (in

the minds of the enrollees) and the substitute hospital remains in the network, then its

withdrawal will have a minor effect on enrollees’ willingness to pay for the network. In other

words, the threat of withdrawal may not lead to significantly higher negotiated prices. If,

however, these hospitals merge and there is no other close substitute, then the threat of

withdrawal from the network may lead to significantly higher negotiated prices for the hospital.

To illustrate, consider the following simplified model of hospital/MCO bargaining with

the ENH/HPH acquisition as an example. Let X(ñ,Ö) denote the health plan’s demand or total

membership as a function of the per member premium ñ and hospital network Ö. An MCO’s

costs consist of their payments to hospitals for their members care and the general costs of

claims processing, administration, etc. Thus, for a given hospital network Ö and vector of per

case hospital prices P = {pi i } 0Ö, an MCO will choose ñ to maximize its expected profits:

(1)

where E(xi) is the expectation of the number of cases that will be treated by hospital i given the

MCO’s network Ö and membership X, and c(X) are the other administrative costs of the MCO.

Le i i it ñG be the ñ which solves (1). To ease notation, let x / E(x ) and let R be defined such that:

(2)

i

In other words, R is the MCO’s profit apart from payments to hospital i:

(3)

Consider managed care organization M, hospital system ENH, and independent hospital

HPH. Suppose M’s current hospital network is some subset of all of the hospitals in Chicago. Let

M’s current hospital network be ÖM 1 2 N = {ENH, HPH, H , H , . . . H }. For ease of notation, denote

{H1 2 N, H , . . . H }/-EH. If M is negotiating with ENH to determine the price paid to ENH if ENH

is included in M’s network, M’s expected profit if an agreement is reached is:

(4)

And M’s expected profits if no agreement is reached can be written as:
6

(5)

For ENH, its expected profit if an agreement is reached is:

(6)

where CENH ENH ENH (x ) is ENH’s additional expected cost of treating M’s patients and Ð (-M) is

ENH’s expected profit apart from M’s patients. ENH’s expected profit if no agreement with M is

reached is:

(7)

Assume that M and ENH are both risk neutral and that their negotiation satisfies the

axioms of Nash bargaining. Also assume that the additional expected cost of treating M’s

patients is linear, so that Ci i i i(x ) = c x for all i and

(8)

and

(9)

so that there is a positive net benefit of including each hospital in M’s network. The price

resulting from the negotiation will solve the following problem:

(10)

or

(11)

Using the envelope theorem, the first order necessary condition for a solution to (11) is:

(12)

For ENH ease of notation, denote ÄR = R({ENH,HPH,-EH})-R({HPH,-EH}) and likewise for

ÄR . HPH ÄRi can be thought of as the value that hospital i adds to M’s hospital network. With the

simplifying assumption that all other hospital prices are fixed (e.g., the negotiation between M

and ENH occurs in the context of established contracts for the other hospitals, we can solve (12)

ENH for p :
 This abstracts from M’s patients who might continue to use ENH for emergency or 11

non-covered services when ENH is not included in M’s network.

 This argument assumes that the combined firm continues to negotiate separately to 12

include ENH and HPH in M’s network after the merger. It is also possible that the combined

firm could negotiate on an “all-or-nothing” basis with M, so that if an agreement is not reached,

both ENH and HPH would drop out of M’s network. This could exacerbate the competitive

impact of the merger. 

7

(13)

Likewise, the pre-merger price negotiated between M and HPH (all else fixed) is:

(14)

Now suppose that ENH and HPH merge. The merger may affect price in two ways. First,

the merger may lower costs (e.g., through economies of scale). In this case, the price negotiated

between M and the merged entity for each hospital will be lower than the pre-merger prices, all

else equal. From (13) and (14), the reduction in the price will be half of the reduction in average

costs, since the gain will be split evenly between M and the merged hospital under Nash

bargaining. 

The second effect is a potential reduction in competition associated with the merger. To

separate this effect from the first effect, assume that ENH’s and HPH’s costs of serving M’s

members do not change with the merger. The merger will not affect the value that ENH and

HPH bring to M’s hospital network. However, the merger may affect the “no agreement” points

of ENH and HPH. Before the merger, if M and ENH failed to reach an agreement, ENH would

lose all of M’s business (see (7) above). After the merger, if M and the merged entity (denote 11

as ENH/HPH) fail to reach an agreement to include ENH in the network, ENH/HPH might not

lose all of M’s business. Some of the M’s patients who would have gone to ENH had it been in

the network, may instead go to HPH. After the merger, these patients are not lost to the

combined firm, so the combined firm will be more aggressive in its negotiations to include ENH

in M’s network than ENH was as an independent hospital.12

To EH formalize this, let ä be the diversion from ENH to HPH. In other words, if ENH is

not in M’s network, äEH is the fraction of M’s patients who would have gone to ENH had it been

in the network who instead go to HPH. After the merger, M and ENH/HPH will negotiate ENH’s

price to solve:

(15)
8

which is the same as (12) above, except for the latter term in the second part of the Nash product

reflecting the internalized diversion of patients from ENH to HPH. Likewise, M and ENH/HPH

will negotiate HPH’s price to solve:

(16)

The first-order conditions for (15) and (16), respectively, can be expressed as:

(17)

and 

(18)

Solving (17) and (18) for pENH (and expressing the result as a function of the pre-merger price for

ENH given in (13)) produces:

Since ÄR - HPH HPH HPH ENH HE ENH c x - c ä x > 0 (because otherwise there would be no net surplus from

including HPH in the network post-merger), the post-merger price for ENH will be greater than

EH the pre-merger price for ENH, as long as ä > 0. In other words, if HPH and ENH are

competitive–in the sense that some of the patients who go to ENH see HPH as ENH’s closest

alternative–then the merger of HPH and ENH will lead to a higher negotiated price for ENH, all

else equal. The post-merger price of HPH behaves analogously.

Because a merger of competing hospitals may lead to a price increase, decrease, or no

change at all, the price effect of any particular hospital merger is an empirical issue. Apart from

this paper and the companion studies from the Hospital Merger Retrospectives Project (Tenn

(2008), Thompson (2009)), only a small number of papers have analyzed the price effects of

hospital mergers retrospectively. Vita and Sacher (2001) found that a merger of two non-profit

Santa Cruz, CA hospitals led to a significant price increase. Using pricing data provided by a

MCO, Capps and Dranove (2004) study a dozen mergers of competing hospitals in the late

1990s and find that three quarters of the mergers resulted in price increases greater than the

median price increase in their sample. Dafny (2005) and Krishnan (2001) also retrospectively

study hospital mergers and find that mergers of competing hospitals increase price on average.

Of these studies, only Capps and Dranove (2004), Tenn (2008), and Thompson (2009) use actual

transactions data taken from MCOs and hospitals. The other studies only use price estimates

derived from publicly available list prices and financial information.
9

There is also a fairly large literature which analyzes the cross-sectional relationship

between competition and hospital pricing. Vogt and Town (2006) survey this literature and

conclude that “the great weight of the literature shows that hospital consolidation leads to price

increases, although a few studies reach the opposite conclusion.” Melnick and Keeler (2007) and

Dranove, Lindrooth, White, and Zwanziger (2008) also find that reductions in hospital

competition lead to higher prices, although the latter paper finds that this relationship has

diminished slightly in recent years. 

2. Methods

Typically, the Department of Justice (DOJ) or the FTC challenges a merger after it has

been proposed, but before it has been consummated. These “prospective” challenges require

predictions about the future competitive effects of the proposed merger. Mergers are only illegal

if they are likely to substantially lessen competition. Since the prospective merger has not yet

taken place, one cannot show that the merger has lessened competition. Rather, one can only

predict whether it is likely to lessen competition. In prospective cases, proxies for future market

power (such as changes in concentration in a well-defined market) are used to assess the likely

impact of the merger on prices and other aspects of conduct and thus, consumers in the future.

In contrast, the mergers of ENH/HPH and STMC/VMH were consummated in early

2000. This permits us to take a “retrospective” look at the mergers, to look back and look for

direct evidence of whether the merger lessened competition, particularly through increased

negotiated prices. Therefore, instead of using structural factors, such as market shares and

market concentration, to predict the effect of the merger, we seek to directly measure the

competitive effects of the merger. In this retrospective analysis, the questions we address are

whether the merging parties obtained or enhanced market power through their mergers, and if so,

whether they exercised that market power in their negotiations with MCOs by negotiating higher

post-merger prices. 

To test the hypothesis that ENH/HPH and/or STMC/VMH obtained or enhanced its

market power, we examine price changes, rather than price levels. In a market with

differentiated products, different price levels are neither necessary, nor sufficient, to demonstrate

the exercise of market power. Established models of monopolistic competition allow that

differentiated products may sell at different prices at the same point in time, even in the long-run

when economic profits are zero. Hospitals offer differentiated products, differentiated by type,

location, and other dimensions. That Hospital A negotiates higher prices for its services than

Hospital B at one point in time is not necessarily evidence of the exercise of market power by

Hospital A. If it costs more for Hospital A to provide its services at its location than it costs

Hospital B to provide its services at its location, Hospital A will have to have higher prices than

Hospital B in equilibrium. So long as the customers of Hospital A value whatever differentiates

it from Hospital B, Hospital A can price its services to cover its higher costs. 

Our objective is to isolate the effect of each merger on the merging hospitals’ prices. As

shown above, it is possible for the merger of competing hospitals to decrease prices by lowering

costs or increase prices by eroding the bargaining position of the MCO (i.e., increase prices
A merger is defined as a change in ownership for a hospital in the Chicago PMSA in

13

which the acquiring party owns at least one other hospital in the Chicago PMSA. Merging

hospitals were excluded back to 1996 even though our data begins in 1998 to eliminate potential

residual effects of mergers on price.

10

through an increase in the hospital’s market power). To isolate the merger’s effect on price, it is

necessary to control for all of the other factors, unrelated to the merger, that could cause a

hospital’s price to change over time. The following is a discussion of these factors and a brief

description of how we control for each.

1. Exogenous Change in Demand and/or Costs Across the Market

Exogenous changes in demand, hospital costs, and/or hospital regulations can cause price

changes. If a demand or cost shock occurred at the same time as the merger, the effect of this

shock could be misinterpreted as the effect of the merger. Therefore, it is important to control for

demand or cost shocks that may have occurred around the time of the merger.

We control for demand and cost shocks by comparing the merging hospitals’ price

changes to those of various control groups of hospitals in the area. In particular, we calculate a

difference in differences: the difference between the merged hospitals’ price change and the

average price change across the control group. We use multiple control groups because hospitals

are highly differentiated across many characteristics, some of which are difficult to quantify.

Thus, there is no hospital or group of hospitals that is identical to ENH, HPH, STMC, or VMH.

Each hospital likely responds to demand and cost shocks differently. Still, if the results are

robust across multiple control groups, we can be confident that the measured net price change at

the merged hospitals adequately controls for demand and cost shocks in the area. 

The first control group we use in the analysis of both mergers is all non-federal general

acute-care hospitals in the Chicago Primary Metropolitan Statistical Area (PMSA). In other

words, we exclude federal facilities (e.g., VA hospitals), non-pediatric specialty hospitals (e.g.,

psychiatric hospitals), and long-term care hospitals. This is the broadest possible group of

hospitals that is likely to experience demand and cost shocks similar to those faced by the

hospitals in question. While we believe this is an appropriate control group for all four hospitals,

there are two potential problems with it that might lead to a biased measure of the merger’s

effect on price.

First, this control group includes hospitals that were also involved in mergers that

occurred during the time period of the data. If either merger led to an increase in market power

with relatively little reduction in cost and, on average, other mergers in Chicago led to similar

results, using all hospitals in the Chicago PMSA as a control group would lead to an

underestimate of the merger’s effect on the merged hospital’s price. To eliminate this bias

somewhat, we also use as a control group all non-federal general acute-care hospitals in the

Chicago PMSA that were not involved in mergers between 1996 and 2002. The use of this

13

control group reduces this bias, but does not completely eliminate it as it does not eliminate
11

second-order rival effects from the control group. For instance, if the ENH/HPH merger

increased ENH’s market power, one would expect other nearby hospitals to increase their prices

in response to the general loss of competition. Thus, even with this control group, our estimate of

the price increase associated with the merger will likely be too low, if the merger increased the

merged hospital’s market power. Alternatively, one could use non-merging hospitals from

outside the Chicago area as controls to avoid the bias from rival effects. In this case, we believe

that using controls from outside Chicago is inferior because there are no healthcare markets in

downstate Illinois that even approximately resemble Chicago. Further, some of the MCOs

operating in Chicago have a limited presence downstate, so available data is limited for

downstate hospitals if used as controls. 

The second problem associated with using all non-federal general acute-care hospitals in

the Chicago PMSA as a control group is that some of the hospitals included may be quite

different from the merging hospitals and may not respond to demand and supply shocks in the

same way. In particular, teaching hospitals have different cost structures than non-teaching

hospitals. ENH is a system with a teaching hospital, so we employ two control groups of

teaching hospitals in the ENH/HPH analysis to account for the cost shocks teaching hospitals

faced in this time period. The first teaching control group is the non-federal general acute-care

hospitals in the Chicago PMSA that had residency programs at the time of the merger. We also

use a second teaching control group that consists of all of the non-federal general acute-care

hospitals in the Chicago PMSA that had more than 0.25 residents and interns per staffed bed

between 1998 and 2002. The threshold of 0.25 residents and interns per staffed bed is the

threshold set by MEDPAC to identify hospitals with extensive teaching programs, like the

teaching program at ENH.

Likewise, STMC and VMH are community hospitals without teaching programs, so

including teaching hospitals in the group of controls used to analyze STMC/VMH may bias the

estimated relative price change. In addition to all of the hospitals in the Chicago PMSA and all

of the non-merging hospitals in the Chicago PMSA, we also use all of the non-teaching nonfederal general acute-care hospitals (i.e., “community hospitals”) in the Chicago PMSA as a

control group for the STMC/VMH price change estimates.

2. Change in the Mix of Patients

If we were to observe that the post-merger average payment per case is greater than the

pre-merger average payment per case at one of the merging hospitals and this change in price is

greater than that across the control groups, we could not conclude that the hospital’s price had

increased, even relative to other hospitals, because this price increase might have been caused by

a random change in the mix of patients seen by the hospital. For instance, open heart surgery

usually costs more than a normal birth because more hospital resources are used for the open

heart surgery than for the normal birth. If the percentage of a hospital’s patients receiving open

heart surgery increased faster than at the controls and the percentage of the hospital’s patients

having normal deliveries decreased faster than at the controls, we would measure a change in the

average payment per case even if there was no change in the relative prices of those services.

Thus, to measure price changes and relative price changes accurately, we must adequately
In 1999, the relative weight for a bone marrow transplant was 10.21. This highlights 14

another advantage of using DRG relative weights to case mix adjust prices: technological

advances that make certain diagnoses relatively less resource intensive to treat are captured by

using the DRG relative weights. 

 In fact, CMS responded to these criticisms by recently reworking the DRG system to 15

better capture patient severity with the new MS-DRGs. 

12

control for the mix of patients or, as it is referred to in the industry and the literature, the case

mix.

To control for changes in case mix, we use three methods. First, we use each patient’s

Diagnosis Related Group (DRG) relative weight as an independent variable. The DRG

classification system consists of roughly 500 groups of diagnoses. These groups are defined so

that, within each group, the resources used to treat patients are similar. This classification system

is the basis for Medicare’s reimbursement to hospitals for inpatient services. In particular, each

year the Center for Medicare and Mediciad Services (CMS) publishes a relative weight for each

DRG representing the cost of treating a case in that DRG relative to the cost of treating the

average case. For example, in fiscal year 2003, the DRG relative weight for a bone marrow

transplant (DRG 481) was 7.13, meaning that a bone marrow transplant used over 7 times the

resources of the average inpatient case. We also use a DRG fixed effects model as an 14

alternative to the DRG weight case mix adjustment.

As a third case mix adjustment method, we use a fixed effects model with dummies for

each APRDRG/SOI pairing. The DRG classification system has two potential drawbacks. First,

since it is designed as the basis for Medicare payments, some have argued that it is not accurate

for diagnoses Medicare beneficiaries rarely have (e.g., obstetric or pediatric diagnoses). Second,

others have argued that the DRG system does not fully capture differences in severity within

each diagnostic category. 3M Health Information Systems created an alternate classification 15

system to address these weaknesses. This classification system is made up of roughly 300 All

Patient Refined Diagnosis Related Groups (APRDRGs). Within each APRDRG, each case is

ranked from 1 to 4 based on its severity of illness (SOI), with 4 being most severe. The SOI

ranking was developed to mirror resource use.

We also include the patient’s length of stay in days as another independent variable in

some alternate specifications as another control for severity. Length of stay is not in our primary

models because it is endogenous (i.e., since many hospital/MCO contracts specify per day

payments, hospitals can increase their price per case by increasing a patient’s length of stay,

unless there are protections against this in the contract). It is also highly correlated with case mix

measures such as DRG weights. 

3. Changes in the Payer Mix

Some have argued that hospitals “cost-shift” by subsidizing the care given to Medicare,
16 http://www.ftc.gov/os/adjpro/d9315/070806opinion.pdf page 83 (accessed on 9/8/08)

13

Medicaid, and indigent patients by charging commercially insured patients more than the cost to

treat them, particularly when (or if) public programs like Medicare and Medicaid do not cover

the full cost of treating their members. Thus another possible reason for a price change to

commercial patients could be a change in the distribution of insurance coverage of a hospital’s

patients. For instance, if a hospital suddenly sees an increase in the proportion of its patients

using Medicare and Medicaid, it may increase its price to commercial insurers to cover its costs

or forgone revenues. To control for this possibility, we include Medicare share plus Medicaid

share as an independent variable.

4. Change in Teaching Intensity

As mentioned before, it is generally recognized that teaching hospitals have higher costs

than non-teaching hospitals. Since teaching hospitals may be affected by demand and cost

shocks differently than non-teaching hospitals, we employ two teaching based control groups in

the ENH/HPH analysis. We also include residents and interns per staffed bed as an independent

variable to capture potential increases in teaching intensity over time that might cause price

changes. 

There are two other factors that might explain price changes that cannot be incorporated

into our econometric model: changes in quality, and adjustments to equilibrium.

5. Changes in Quality

A change in the price negotiated between a hospital and an MCO may reflect a change in

the quality of the services offered by the hospital. There are many aspects of hospital quality and

no standard measure that encompasses all aspects. Further, it is beyond the scope of this paper to

describe the various quality metrics and report their relative changes at the merged hospitals.

However, substantial quality evidence was presented at the ENH/HPH trial and the judge and the

Commission concluded that “ENH failed to show that quality improved across the combined

ENH system and relative to other hospitals.”16

6. Adjustment to Equilibrium

Models designed to estimate the effect of a structural change, such as a merger, typically

assume that the market is in equilibrium before and after the structural change, but this may not

always be true. If the market is not in equilibrium before the structural change, but is in

equilibrium after the structural change, part of the effect that is measured is the adjustment to the

equilibrium. In the administrative trial following the FTC’s complaint, ENH argued that the

price increase that occurred after the merger was unrelated to the merger and instead due to an
 For instance, see 17 http://www.ftc.gov/os/adjpro/d9315/050527respposttrialbrief.pdf

page 40.

One way potentially to test for pre-merger sub-optimal behavior would be to look at the 18

pre-merger price growth rate at ENH and compare this to the pre-merger price growth rate at

control hospitals to see if it was less. Our data only goes back to 1998, two years before the

merger, so we cannot investigate this.

 The ALJ’s public decision 19

(http://www.ftc.gov/os/adjpro/d9315/051021idtextversion.pdf ) and the Commission’s public

decision (http://www.ftc.gov/os/adjpro/d9315/070806opinion.pdf ) list qualitative evidence that

ENH was not behaving sub-optimally pre-merger. (Links accessed 9/8/08)

 Illinois Health Facilities Planning Board, “Hospital Capital Expenditure and Financial 20

Information Report for 1999,” March 2001, http://www.idph.state.il.us/pdf/capexpendrept.pdf

(Link accessed 9/8/08)

14

adjustment to equilibrium. In other words, ENH was pricing sub-optimally before the merger 17

and optimally after the merger. How likely is it that such an adjustment to equilibrium could bias

our price change estimates? In this case, there are a number of general factors that suggest that

we cannot immediately rule this out:

1. Most quasi-experiments similar to the empirical analysis of this paper have a “treatment”

group and a “control” group. In a case in which the treatment group has many members, it would

be unlikely that all or even most members would behave sub-optimally pre-treatment and

optimally post-treatment. However, in this case, our treatment group is a singleton. It is possible

that we selected a merger in which at least one of the hospitals was not behaving optimally premerger.

2. The usual argument against the likelihood of sub-optimal behavior by a firm is that capital

markets tend to discipline such behavior. For instance, if a firm with market power is not

minimizing its costs, there is a strong incentive for the owners (or other owners purchasing the

firm) to install better management. In this case, the hospitals are not investor-owned, so there are

no investors that could reap benefits by purchasing the firm and installing better management.

3. Closely related to (2), if a firm that is behaving sub-optimally is involved in a merger that

increases its market power, it has more to lose by continuing its old behavior. So it is not

completely implausible to think that a merger and an adjustment to an equilibrium could occur at

the same time.

Given our data, it is impossible to rule out an adjustment to equilibrium as a potential

bias in our price measurement with the data alone. We have seen no evidence to suggest that 18

ENH was behaving sub-optimally pre-merger. Also, ENH was the most profitable hospital in 19

the state of Illinois in 1999, the year before the merger. While it is possible they simply had 20
 ENH and HPH data are pooled pre and post-merger since ENH and HPH observations 21

in the MCO and cost report data cannot be distinguished post-merger. STMC and VMH data are

pooled pre and post-merger to conceal the identity of the MCOs. 

15

more market power than they were aware of in 1999, this suggests that they were not poorly

managed. ENH’s management also did not change after the merger. For these reasons, we do not

believe the ENH/HPH results reflect an adjustment to equilibrium.

Empirical Model

The econometric model we estimate is the following:

(20)

where i indexes episodes of inpatient care (i.e., cases) and h indexes hospitals.

The variables are defined as follows:

Pricei /the total allowed amount for case i (expressed in log form)

Pos it / a dummy variable equal to 1 in the post-merger period. In the MCO data, Post is defined

specific to each MCO using the effective date of the first post-merger contract (or the

merger date if no post-merger contract was signed by 12/31/2002). In the state data, Post

= 1 for 2001 and 2002, with year 2000 treated as a transition year and excluded from the

data set.

Ca isemix / the measure of case mix; either the DRG weight of the case i (expressed in log

form), the set of DRG dummies, or the set of APRDRG/SOI dummies. As an alternate

specification, length of stay (LOS) is also paired with each case mix measure, producing

six methods of controlling for case mix variation.

Pub hlic / Medicare share + Medicaid share of hospital h (from the Medicare Cost Reports)

(expressed in log form), where the public share is matched to the case based on the

discharge date.

Teachh / residents and interns per bed at hospital h (from the Medicare Cost Reports) (expressed

in log form), where the teaching intensity is matched to the case based on the discharge

date.

D /vec MH tor of hospital dummy variables. (D is the dummy variable for the merging hospital in

question. )

21

Plani / vector of dummy variables indicating the patient’s plan (PPO, HMO, or Indemnity).

(Only included in the MCO data analysis.)

T / vector of year dummy variables

The model parameters are estimated using ordinary least squares. The standard errors are

estimated using clustered robust Huber/White estimates of variance to address the possibility of
In Stata terminology, we specify cluster(hospital). 22

Actually, what is reported is e -1 in percentage form.

23 â2

 To protect the identity of the MCOs, their names are masked when reporting the 24

results. Also, we do not report sample sizes or overall results in the MCO data analysis to avoid

indirectly identifying the MCOs.

 Our measure of price does not include outpatient revenues due to the difficulty of 25

adjusting outpatient visits for changes in case mix. Attempts to include outpatient price changes

into the estimation of ENH/HPH’s relative price change during the ENH/HPH trial resulted in

price increase estimates that were very similar to the inpatient-only price increase estimates. See 

Opinion of the Commission in the Matter of Evanston Northwestern Healthcare Corporation,

page 38 http://www.ftc.gov/os/adjpro/d9315/070806opinion.pdf (Accessed on 9/15/08).

16

cross-hospital heteroskedasticity and within-hospital autocorrelation. In other words, cases

22

from the same hospital may not be independent and the observations from different hospitals,

while likely independent, may have error terms which are not identically distributed. We are

primarily 2 interested in the estimate of â ; roughly speaking, the estimate of the difference

between the price change at the merging hospital and the average price change across the

controls. These estimates are reported in the results below.23

3. Data

To study the pricing behavior of ENH, HPH, STMC, VMH, and other Chicago area

hospitals, we employ three distinct sources of data and price measurement methods. Our primary

data are claims data from 5 of the largest MCOs in the Chicago area representing more than 50%

of the insured managed care members in the Chicago area. In this data, each record is a claim, 24

which roughly corresponds to a procedure or a service (e.g., MRI, pharmacy, surgical procedure,

etc.). Each record contains demographic information about the patient (e.g., age, gender, marital

status, etc.), diagnostic and procedural information about the episode of care (e.g., dates of

service, diagnosis codes, procedure codes, discharge status, etc.), and payment information. The

payment information includes the billed amount (i.e., the list price of the service or “billed

charges”) and the allowed amount (i.e., the total amount that the MCO and the patient together

owe the hospital for that service; usually this is less than the billed amount if the MCO has a

contract with the hospital). The allowed amount is often broken up into the amount paid by the

MCO and the amounts (i.e., co-pays, deductibles, etc.) paid by the patient. Some data sets also

indicate if the patient has secondary health insurance that has paid part of the claim.

Our measure of price in this data is the allowed amount per inpatient episode of care

(e.g., inpatient admission). We will refer to this as the allowed amount per case. We do not use

25

the allowed amount per procedure because procedures are too heterogeneous and there is no

accepted method to compare them. Further, a hospital can increase revenues by increasing the

number of procedures while keeping the per procedure price constant. In order to calculate the
 In particular, we use 3M Health Information Systems’ Core Grouping software to 26

group cases into DRGs and APRDRGs.

17

allowed amount per case, the payment information in the claim-level data has to be aggregated

up to each case. In this data, cases are identified using the patient’s member identification

number and the dates of service. For each member ID, each group of records with strictly

overlapping dates of service (e.g., the beginning date of service for one record is before the end

date of service for another record) is defined as a case. 

The amount paid per case is the standard measure of price for inpatient services used in

the hospital competition literature. However, using this price measure with the MCO’s data

introduces problems because the MCO’s data is not organized by case and MCO’s do not

typically pay hospitals on an case-by-case basis. For instance, the standard classifications

systems used to group inpatient cases according to resource use (Diagnosis Related Groups

(DRGs) and All Patient Refined Diagnosis Related Groups (APRDRGs)) were not used as the

basis for payments between MCOs and hospitals in the Chicago area for most services around

the time of the mergers, with the exception of obstetric cases and occasionally cardiovascular

cases. Contracts between MCOs and hospitals in the Chicago area usually specified a per day

payment for a class of service (e.g., $1,000/day for a medical/surgical bed and $1,500/day for an

intensive care unit bed) or a simple discount off of list price for all or most services. Therefore,

the MCOs data either does not have any standard classification system (e.g., DRGs) in its data

or, if it is included, it may be incomplete. 

We use the demographic and diagnostic information in the claims data to group cases

into DRGs and APRDRGs. In doing so, we encounter a number of challenges. In order to

26

classify a case into a DRG or APRDRG, usually one needs the age and gender of the patient and

the correct diagnostic and procedure codes for the patient’s stay. If, within the records associated

with a case, some of this information is internally inconsistent (e.g., some records indicate a

male while others indicate a female; all of the records indicate a male, but the diagnosis is an

obstetrics diagnosis; etc.), then classifying the case into a DRG or APRDRG is impossible.

These internal inconsistencies occur in a relatively large fraction of the data, as illustrated in

Appendix A (Description of Inpatient MCO Data). For instance, 11% of the observations from

Chicago PMSA hospitals are from internally inconsistent cases. Of the remaining cases without

internal inconsistencies, almost 27% have some other type of coding error. These problems are

most likely due to coding errors that do not impact the payments between the MCO and the

hospital. However, since the presence of these inconsistencies makes it difficult to classify some

cases, we have discarded the problematic cases from our sample. It is possible that the nonrandom exclusion of these problematic observations and cases could bias our results. If a bias

exists, it most likely would lead to an underestimate of the relative price increase at ENH/HPH.

Unlike the data overall, the observations (i.e., claims) thrown out because of internally

inconsistent information show a general price decrease, but a larger price decrease at the control

hospitals (-71%) than at ENH/HPH (-59%). Of the remaining cases, those thrown out due to

other coding errors show a relatively large price increase for ENH/HPH (40%) and a price

decrease for the control hospitals (-16%).
 The Net and Gross revenues from the Cost Reports also include revenues from all 27

patients, not just commercially insured patients. To investigate whether this introduces a bias, we

also measure price using all cases in the Universal Dataset, in addition to cases for commercially

insured patients. 

This approach also implicitly assumes that the variance in actual payments is 28

proportional to the variance in list prices. This is likely a reasonable assumption since Medicare

payments are based in part on DRG relative weights, meant to reflect relative resource use, that

18

Given the issues with our primary source of data, we feel it is useful to analyze price with

other sources of data as a check on our primary results. The second data source we use is the

Illinois Department of Public Health’s Universal Dataset. This data set contains all of the

inpatient hospital discharges in the state of Illinois. It is similar to the MCO’s data in that it

contains demographic, diagnostic/procedural, and billing information for each inpatient case.

Unlike the MCO’s data, each record in the Universal Dataset is a case and the IDPH audits the

information received from the hospital before including it. The data also contains DRGs, the

most commonly used inpatient classification system. Thus, the Universal Dataset does not suffer

from the aggregation and consistency problems of the MCO’s data. However, the Universal

Dataset does not contain actual payment information. It only contains the total billed amount

(i.e., list price) for each case. 

In order to approximate the amount actually received by the hospital for each case, we

combine the billing information in the Universal Dataset with revenue information taken from

Medicare’s Hospital Cost Reporting Information System (aka, the Medicare Cost Reports). The

Cost Reports include a hospital’s total billed charges (i.e., total list price revenue, called Gross

Revenue) and the hospital’s total actual revenues after contractual discounts (called Net

Revenue). For each inpatient case in the Universal Dataset, we multiply the billed amount by the

ratio of Net Revenue to Gross Revenue from the Cost Report associated with that case’s hospital

and discharge date. In other words, we use cost report information to approximate the amount of

each case’s list price that the hospital actually received. Other recent articles examining hospital

competition have used this approach to measure prices (e.g., Gaynor and Vogt (2003)).

The primary shortcoming of this approximation of price originates from the Net and

Gross revenue figures taken from the Cost Reports. These revenues are for all of the services a

hospital offers (e.g., they include both inpatient and outpatient revenue) while the Universal

Dataset only lists inpatient cases. Thus, it is possible that the use of this Net/Gross ratio from 27

the Cost Reports could bias our price change estimates and relative price change estimates.

Using confidential information on ENH/HPH’s pre and post-merger net and gross inpatient and

outpatient revenues, public information on gross inpatient and outpatient revenues from the

Illinois Hospital Association and public information on net inpatient and outpatient revenues for

the Midwest region from AHRQ’s Medical Expenditure Panel Survey, we believe the bias

introduced by the use of the Net/Gross ratio from the cost reports is small and, if anything,

results in a slight underestimate of all hospitals’ price changes and the ENH/HPH price change

relative to the average control price change.28
are calculated using charges. Thus it is generally assumed that list prices reflect relative resource

use even if they are not actual prices.

 Including those not listed in Table 1. 29

19

Finally, as a second check on our primary results, we also report unadjusted price

changes from the data submitted by the hospitals to the FTC and compare these changes to

published healthcare inflation measures. These price changes do not control for case mix and

other changes and are not measured relative to a control group, but they provide useful

background and context for the primary results based on the MCO’s data. 

To summarize, we use three distinct, yet complementary data sources to investigate the

price change at the hospitals in question following the merger. The advantage of the MCO data

is that it contains actual transaction prices. The disadvantage is that a relatively large portion of

the data is unusable because of aggregation and consistency issues. The Universal Dataset has

none of these issues, but it does not contain actual prices, so prices must be approximated using

Cost Report information. As seen in the following section, both of these sets of price change

estimates are consistent with the raw price changes calculated from data taken directly from the

hospitals. 

4. Results:

Table 1 below lists the payer-by payer change in net revenue per case at ENH/HPH, and

STMC/VMH between 1999 and 2002. At ENH and HPH, most MCOs experienced a raw price

increase in excess of 50 percent and, for some MCOs, their net revenue per case at ENH and

HPH doubled between 1999 and 2002. Overall, across all managed care plans , ENH/HPH’s net

29

revenue per case increased almost 50 percent between 1999 and 2002, greatly exceeding the

increase in the national hospital inflation measures and the local medical care CPI. At STMC

and VMH, some MCOs experienced large increases in net revenue per case, but others

experienced decreases, so that overall, prices increased 4 percent between 1999 and 2002.

While suggestive, these raw price changes and their comparison to inflation measures, on

their own, cannot form the basis of any conclusions about the actual effects of these mergers. For

instance, it is possible that ENH/HPH’s large price increases may have resulted from a “bad

draw” of severe patients in 2002, or from increased costs associated with an expanding teaching

program, or from a localized cost shock affecting teaching hospitals in the Chicago area (which

may not be fully reflected in the national hospital inflation indices or even the Chicago area

medical care index, which includes non-hospital medical prices). 

As described in section 2, we estimated a difference-in-differences model to control for

these and other factors which are unrelated to changes in market power. The model’s postmerger price increase estimates, based on the MCO data, at ENH and HPH overall are presented
 After the merger, ENH eliminated HPH’s independent tax identification, so patients at 30

HPH cannot be distinguished from patients at the legacy ENH hospitals, preventing the

estimation of case mix adjusted price increases separately at ENH and HPH.

 While the payer names are masked, the payers listed in Tables 2 and 3 are the same as

31

the first five payers in Table 1.

 The complete coefficient estimates from the model on which these price changes are

32

based are listed in Appendix B.

 To protect the identity of the MCOs, we cannot discuss the MCO characteristics that 33

may have led to this variance.

20

in Table 2. Each of the four sections of the table contains the estimated price increases relative 30

to the listed control group. The rows of the table list the MCOs (i.e., payers) from which we

31

received usable data and the columns list the six case mix adjustment methods we employed. 

Even after controlling for factors unrelated to the merger that may affect raw price

increase estimates, we find that four of the five MCOs experienced large and statistically

significant relative price increases at ENH/HPH after the merger in excess of the mean price

increase they experienced with other hospitals. The only MCO that did not experience a relative

price increase at ENH/HPH was Payer C. The other MCOs received price increases at least ten

percentage points greater than other Chicago area hospitals on average, with Payer D

experiencing the largest relative price increase, in excess of 50 percentage points. These results

are highly robust to different control groups and case mix adjustment methods.

In contrast, the relative post-merger price changes at STMC/VMH were mixed, as seen in

Table 3. After controlling for changes in case mix and other factors, the estimated relative price

changes indicate that three MCOs (Payers B, C, and E) experienced a relative price decrease at

STMC/VMH after the merger. Only one MCO (Payer D) experienced a price increase at

STMC/VMH significantly greater than at other hospitals. Payer A’s post-merger price increase

at STMC/VMH was higher than it experienced at non-merging Chicago-area hospitals on

average, but not materially different from the average price change at community hospitals in the

Chicago area.32

One interesting aspect of the price change estimates from the MCO data is their variance

across MCOs, suggesting that some MCOs may be more vulnerable to hospital mergers than

others. For instance, Payer D was the only MCO to experience a relative price increase at

STMC/VMH and experienced the largest price increase (both raw and adjusted) after the

ENH/HPH merger. On the other hand, Payer C was the only MCO that avoided a price increase

at ENH/HPH and had a relatively modest 5-9 percentage price decrease at STMC/VMH.33

The results using the alternate IDPH/Cost Report data are consistent with the estimated

price increases from the MCO data. As seen in Table 4, the post-merger price increase at
 Commission’s public decision, page 17. 34

http://www.ftc.gov/os/adjpro/d9315/070806opinion.pdf (Accessed 11/3/08)

21

ENH/HPH was 10 to 17 percentage points greater than the average control price increase

according to the IDPH/Cost Report data. This difference is statistically significant and robust to

all of the control groups, case mix adjustment methods, and patient populations. Table 5 lists the

relative post-merger price change estimates at STMC/VMH according to the IDPH/Cost Report

data. These are negative and generally modest and not statistically significant for all control

groups. In particular, the price decrease relative to community hospitals is between 2 and 5

percentage points and is not statistically significant for privately insured patients, corroborating

the mixed, slightly negative price change estimates from the MCO data.

5. Conclusion:

Overall, the estimates from the MCO data show large and statistically significant postmerger price increases at ENH/HPH for all but one MCO that cannot be explained by changes in

market conditions unrelated to the merger. These results are highly robust to various control

groups, case mix adjustment methods, and alternative data sources. This strongly suggests that

ENH/HPH increased its market power with the merger, giving it the ability to negotiate higher

prices with most MCOs. This is consistent with the majority of non-econometric evidence

presented in the ENH trial. Indeed, ENH executives, in documents written shortly after the

merger, claimed that the price increases were due to the merger and the increased market power

of the combined entity:

Some $24 million of revenue enhancements have been achieved - mostly via

managed care renegotiations [and] none of this could have been achieved by either

Evanston or Highland Park alone. The ‘fighting unit’ of our three hospitals and 1600

physicians was instrumental in achieving these ends.34

However, the results for STMC/VMH, if anything, show the opposite effect with three

MCOs receiving relative price decreases and only one MCO receiving a significant relative price

increase post-merger. The overall results from the IDPH/Cost Report data suggest no change in

price or a slight reduction in price post-merger. Overall, we find no empirical evidence that the

merger between STMC and VMH led to higher prices.
22

Table 1: Percentage Change in Inpatient Net Revenue per Case,

FY99 to FY02

Payer ENH/HPH STMC/VMH

A 88.7% 38.2%

B 57.9%

C 6.8% -6.3%

D 130.9% 45.4%

E 81.4%

F 77.3%

G 80.1% -9.2%

H 137.2%

I 62.3% 0.1%

J 43.6%

K 99.4%

L 20.9%

M 79.9% 13.8%

N 80.3%

Overall Managed Care 49.0% 4.0%

Source: Hospital Data

Inflation Measures:

Hospital CPI 27.8%

Hospital PPI (private patients) 14.9%

Chicago Medical Care CPI 13.8%
23

Table 2: Estimated Post-Merger Percentage Price Increase at Evanston Northwestern

Healthcare/Highland Park Hospital

Source: MCO data Significance level: *** = 1%; ** = 5%; * = 10%

Case Mix = APRDRGSOI APRDRGSOI

w/LOS

DRG DRG

w/LOS

Weights Weights

w/LOS

Control = Chicago PMSA Hospitals

Payer A 23.1*** 25.6*** 21.0*** 25.0*** 22.3*** 26.0***

Payer B 17.2*** 24.0*** 18.1*** 24.9*** 21.3*** 25.1***

Payer C -0.8 -0.9 0.0 -1.0 0.4 -1.4

Payer D 55.7*** 62.5*** 56.2*** 62.7*** 58.6*** 64.7***

Payer E 11.0*** 12.1*** 12.3*** 14.0*** 15.4*** 16.0***

Control = Non-Merging Chicago PMSA Hospitals

Payer A 35.1*** 34.4*** 32.7*** 33.7*** 33.1*** 32.7***

Payer B 26.5*** 29.2*** 30.2*** 33.0*** 30.1*** 30.6***

Payer C 3.8* 1.8 4.3* 1.6 5.5** 1.5

Payer D 64.9*** 74.5*** 65.5*** 74.8*** 68.9*** 79.9***

Payer E 20.1*** 20.5*** 21.9*** 23.1*** 28.0*** 28.4***

Control = Chicago PMSA Teaching Hospitals

Payer A 24.9*** 26.3*** 22.7*** 25.9*** 24.0*** 26.9***

Payer B 16.3*** 23.9*** 17.3*** 24.8*** 20.2*** 24.3***

Payer C -0.8 -1.4 0.1 -1.4 0.3 -1.8

Payer D 50.1*** 56.3*** 49.4*** 56.1*** 51.2*** 57.4***

Payer E 12.2*** 13.0*** 12.9*** 14.3*** 13.9*** 14.4***

Control = Chicago PMSA Major Teaching Hospitals 

Payer A 30.4*** 29.6*** 28.5*** 29.7*** 29.0*** 29.9***

Payer B 17.8*** 25.8*** 18.6*** 26.6*** 20.2*** 24.1***

Payer C 0.2 -2.1 1.1 -2.1 1.4 -2.5

Payer D 48.7*** 55.7*** 46.7*** 54.0*** 48.0*** 56.2***

Payer E 15.2* 15.1* 16.1* 16.6* 14.5 14.3
24

Table 3: Estimated Post-Merger Percentage Price Increase at St. Therese Medical

Center/Victory Memorial Hospital

Source: MCO data Significance level: *** = 1%; ** = 5%; * = 10%

Case Mix = APRDRGSOI APRDRGSOI

w/LOS

DRG DRG

w/LOS

Weights Weights

w/LOS

Control = Chicago PMSA Hospitals

Payer A 6.1** 4.0 6.1** 4.4* 6.6*** 3.8

Payer B -15.6*** -20.8*** -14.3*** -20.0*** -13.1*** -19.2***

Payer C -6.7*** -6.2*** -6.9*** -6.1*** -6.4*** -7.7***

Payer D 18.9*** 17.3*** 18.8*** 19.9*** 21.6*** 19.8***

Payer E -21.7*** -22.5*** -21.1*** -21.9*** -18.0*** -18.2***

Control = Non-Merging Chicago PMSA Hospitals

Payer A 10.7*** 8.7*** 10.9*** 9.5*** 10.3*** 7.0***

Payer B -11.6*** -16.9*** -8.8*** -14.9*** -7.6*** -13.7***

Payer C -5.4*** -5.3*** -5.6*** -5.3*** -5.0*** -7.0***

Payer D 28.4*** 25.0*** 25.7*** 26.9*** 28.1*** 26.8***

Payer E -19.7*** -20.6*** -19.9*** -20.8*** -16.7*** -17.1***

Control = Chicago PMSA Community Hospitals

Payer A 4.3 3.6 4.4 3.9 4.3 2.6

Payer B -16.0*** -19.4*** -14.6*** -18.3*** -11.5** -15.5***

Payer C -8.1*** -7.1*** -8.2*** -7.0*** -7.6*** -8.8***

Payer D 26.9*** 23.6*** 23.2*** 26.1*** 28.9*** 26.9***

Payer E -20.8*** -21.2*** -22.7*** -22.8*** -17.8*** -17.7***
25

Table 4: Estimated Post-Merger Percentage Price Increase at Evanston Northwestern

Healthcare/Highland Park Hospital

Source: IDPH and Cost Report data Significance level: *** = 1%; ** = 5%; * = 10%

Case Mix = APRDRGSOI APRDRGSOI

w/LOS

DRG DRG

w/LOS

Weights Weights

w/LOS

Control = Chicago PMSA Hospitals

All Patients 15.5*** 16.6*** 15.0*** 16.5*** 14.2*** 16.8***

Private Pay

Patients

15.2*** 15.7*** 15.3*** 15.6*** 13.7*** 14.1***

Control = Non-Merging Chicago PMSA Hospitals

All Patients 15.1*** 15.9*** 15.4*** 16.0*** 14.2*** 16.3***

Private Pay

Patients

16.9*** 16.4*** 17.3*** 16.3*** 14.7*** 13.6***

Control = Chicago PMSA Teaching Hospitals

All Patients 14.2*** 15.0*** 13.9*** 15.0*** 13.1*** 15.5***

Private Pay

Patients

13.3*** 13.5*** 13.7*** 13.6*** 11.9*** 12.0***

Control = Chicago PMSA Major Teaching Hospitals 

All Patients 16.7*** 16.0*** 16.4*** 15.9*** 15.7*** 16.2***

Private Pay

Patients

13.3*** 12.1*** 14.0*** 12.2*** 12.0*** 10.6***
26

Table 5: Estimated Post-Merger Percentage Price Increase at St. Therese Medical

Center/Victory Memorial Hospital

Source: IDPH and Cost Report data Significance level: *** = 1%; ** = 5%; * = 10%

Case Mix = APRDRGSOI APRDRGSOI

w/LOS

DRG DRG

w/LOS

Weights Weights

w/LOS

Control = Chicago PMSA Hospitals

All Patients -6.8*** -7.5*** -7.2*** -7.4*** -7.3*** -7.5***

Private Pay

Patients

-5.5*** -6.3*** -5.6*** -6.3*** -5.5*** -6.3***

Control = Non-Merging Chicago PMSA Hospitals

All Patients -6.6*** -7.2*** -6.9*** -7.1*** -7.1*** -7.0***

Private Pay

Patients

-3.7** -4.7*** -3.9** -4.7*** -3.9** -5.0***

Control = Chicago PMSA Community Hospitals

All Patients -4.0* -3.9* -4.8** -4.0** -5.4* -4.8**

Private Pay

Patients

-2.0 -2.2 -2.6 -2.3 -2.6 -2.7
27

References:

Capps, C., Dranove, D., Greenstein, S., and Satterthwaite, M. (2002), “Antitrust Policy and

Hospital Mergers: Recommendations for a New Approach,” The Antitrust Bulletin,

Winter 2002, pp. 677-714

Capps, C. and Dranove, D. (2004), “Hospital Consolidation and Negotiated HMO Prices,”

Health Affairs, v23 (#2, March/April), pp. 175-181

Dafny, L. (2005), “Estimation and Identification of Merger Effects: An Application to Hospital

Mergers,” NBER Working Paper #11673

Devers, K., Casalino, L., et al. (2003), “Hospitals’ Negotiating Leverage with Health Plans: How

and Why Has It Changed?” HSR: Health Services Research, v38, pp. 419-446

Dranove, D., Lindrooth, R., White, W., and Zwanziger, J., “Is the Impact of Managed Care on

Hospital Prices Decreasing?” Journal of Health Economics, v27, pp. 362-376

Gaynor, M. and Vogt, W. (2003), “Competition Among Hospitals,” Rand Journal of Economics,

v34 (#4, Winter 2003), pp. 764-785

Krishnan R. (2001), “Market Restructuring and Pricing in the Hospital Industry,” Journal of

Health Economics, v20(#2:March), pp. 213-237

Melnick, G. and Keeler, E. (2007), “The Effects of Multi-Hospital Systems on Hospital Prices,”

Journal of Health Economics v26, pp.400-413 

Town, R. and Vistnes, G. (2001), “Hospital Competition in HMO Networks,” Journal of Health

Economics v20, pp.733-753

Tenn, S. (2008), “The Price Effects of Hospital Mergers: A Case Study of the Sutter-Summit

Transaction,” FTC Working Paper #293

Thompson, A. (2009), “The Effect of Hospital Mergers on Inpatient Prices: A Study of the New

Hanover-Cape Fear Transaction,” FTC Working Paper #295

Vita, M. and Sacher, S. (2001), “The Competitive Effects of Not-for-Profit Hospital Mergers: A

Case Study,” Journal of Industrial Economics, v49(March), pp.63-84

Vogt, W.B. and Town, R. (2006), “How has Hospital Consolidation Affected the Price and

Quality of Hospital Care?” Robert Wood Johnson Foundation Research Synthesis Report

#9 http://www.rwjf.org/pr/product.jsp?id=15231
Appendix A: Description of Inpatient MCO Data (All MCOs)

All ambiguous hospital names are excluded

Observation = row of unprocessed data

Admissions are groups of observations with a common member ID and strictly overlapping dates of service (i.e., the periods defined by the admission date 

 and discharge date strictly overlap).

Internally inconsistent admissions are admissions with conflicting age, gender, hospital, product, primary diagnosis, and/or primary procedure information.

1 # of inpatient observations 11,099,118

2 Observations not associated with providers in the Chicago PMSA 2,272,451

3 Observations only identified at the system level 405,097

4 Observations with ambiguous hospital names 455,678

5 Observations from Chicago PMSA hospitals (=1-2-3-4) 7,965,892 72% Percentage of 1 

6 Observations w/o member ids, admission dates, or discharge dates 407

7 Observations from internally inconsistent admissions 874,861 11% Percentage of 5

8 Remaining observations (=5-6-7) 7,090,624

9 Admissions associated with these observations 1,620,746

10 Admissions w/ COB 29,387

11 Admissions w/ admit dates before 1/1/1998 or after 12/31/2002 284,327

12 Admissions where product is ambiguous 8,047

13 Denied admissions 195,717 12% Percentage of 9

14 Admissions with LOS <= 0 146,686 9% Percentage of 9

15 Net Admissions (NA)* 1,022,264 63% Percentage of 9

DRG = 470 (Ungroupable) 168,921 17% Percentage of 15

DRG = 469 (Principal diagnosis invalid as discharge diagnosis) 176 0% Percentage of 15

Principal Diagnosis Problems:

 Invalid diagnosis code 6,510 1% Percentage of 15

 Sex conflict 7,092 0% Percentage of 15

 Age conflict 2,314 0% Percentage of 15

 E-code as principal diagnosis 23 0% Percentage of 15

 Non-specific principal diagnosis 25,405 2% Percentage of 15

 Manifestation as principal diagnosis 50 0% Percentage of 15

 Questionable admission 789 0% Percentage of 15

 Unacceptable principal diagnosis 3,569 0% Percentage of 15

Secondary Diagnosis Problems:

 Invalid diagnosis code 7,529 1% Percentage of 15

 Sex conflict 7,221 1% Percentage of 15

 Age conflict 8,135 1% Percentage of 15

 No secondary diagnosis when one is required 522 0% Percentage of 15

Procedure Problems:

 Invalid procedure code 58,529 6% Percentage of 15

 Sex conflict 2,893 0% Percentage of 15

16 Remaining Admissions* 764,408 75% Percentage of 15

APRDRG = 956 (Ungroupable) or 955 (Principal diagnosis invalid as discharge diagnosis) 13,410 1% Percentage of 15

No HCRIS data available for this admission 3,723 0% Percentage of 15

Remaining Admissions 747,275 73% Percentage of 15

* Does not reflect the sum or difference of the preceding lines since an admission can have more than one problem

A1
B1

Appendix B: Coefficient Estimates and Standard Errors

DV = (log) Allowed

Hospital, plan, year, and case mix dummy coefficients (where applicable) are not shown

Standard errors in parentheses

* p<0.1, ** p<0.05, *** p<0.01

Evanston Northwestern Healthcare/Highland Park

Payer A

Chicago PMSA hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post -0.0368 -0.0215 -0.0351 -0.0200 -0.0489 -0.0288 

 (0.0297) (0.0310) (0.0302) (0.0320) (0.0314) (0.0330) 

post*ENHHP 0.2075*** 0.2275*** 0.1906*** 0.2232*** 0.2010*** 0.2309***

 (0.0212) (0.0209) (0.0208) (0.0213) (0.0223) (0.0227) 

public -0.0424** -0.0318* -0.0257 -0.0205 -0.0364 -0.0261 

 (0.0179) (0.0184) (0.0172) (0.0190) (0.0247) (0.0213) 

teach 0.0882 0.1658** 0.0839 0.1708** 0.0832 0.1819** 

 (0.1051) (0.0786) (0.0997) (0.0737) (0.1002) (0.0733) 

los 0.6933*** 0.7084*** 0.6452***

 (0.0175) (0.0174) (0.0179) 

case mix 0.6148*** 0.3126***

 (0.0177) (0.0173) 

--------------------------------------------------------------------------------------------------------------------
B2

Non-merging Chicago PMSA hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post -0.0595 -0.0327 -0.0547 -0.0284 -0.0723 -0.0368 

 (0.0500) (0.0523) (0.0486) (0.0524) (0.0509) (0.0541) 

post*ENHHP 0.3007*** 0.2956*** 0.2827*** 0.2903*** 0.2856*** 0.2827***

 (0.0295) (0.0286) (0.0284) (0.0296) (0.0329) (0.0369) 

public -0.0529*** -0.0330* -0.0295 -0.0161 -0.0447** -0.0290* 

 (0.0162) (0.0173) (0.0177) (0.0189) (0.0169) (0.0156) 

teach -1.9142*** -1.2001* -1.8729** -1.1322 -1.7205** -0.8135 

 (0.6551) (0.6659) (0.6967) (0.6990) (0.7600) (0.8206) 

los 0.6857*** 0.7042*** 0.6542***

 (0.0222) (0.0226) (0.0243) 

case mix 0.6048*** 0.2999***

 (0.0227) (0.0197) 

--------------------------------------------------------------------------------------------------------------------

Chicago PMSA major teaching hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post -0.0560 -0.0272 -0.0582 -0.0265 -0.0783 -0.0390 

 (0.0510) (0.0544) (0.0522) (0.0570) (0.0535) (0.0588) 

post*ENHHP 0.2655*** 0.2590*** 0.2504*** 0.2599*** 0.2544*** 0.2618***

 (0.0484) (0.0435) (0.0465) (0.0425) (0.0482) (0.0450) 

public -0.0483*** -0.0304** -0.0345*** -0.0183 -0.0489*** -0.0334***

 (0.0138) (0.0142) (0.0114) (0.0127) (0.0112) (0.0100) 

teach -0.3317 -0.0665 -0.3375 -0.0874 -0.3563 -0.0015 

 (0.8017) (0.6286) (0.7499) (0.5806) (0.7439) (0.6013) 

los 0.7310*** 0.7493*** 0.6778***

 (0.0307) (0.0314) (0.0322) 

case mix 0.6131*** 0.3177***
B3

 (0.0262) (0.0253) 

--------------------------------------------------------------------------------------------------------------------

Chicago PMSA teaching hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post -0.0247 -0.0037 -0.0243 -0.0041 -0.0407 -0.0138 

 (0.0346) (0.0364) (0.0359) (0.0385) (0.0375) (0.0404) 

post*ENHHP 0.2222*** 0.2336*** 0.2046*** 0.2305*** 0.2148*** 0.2386***

 (0.0292) (0.0288) (0.0279) (0.0286) (0.0287) (0.0291) 

public -0.0503*** -0.0334* -0.0315* -0.0200 -0.0507*** -0.0370** 

 (0.0156) (0.0184) (0.0159) (0.0192) (0.0159) (0.0159) 

teach 0.0770 0.1588** 0.0826 0.1718** 0.0822 0.1856** 

 (0.0988) (0.0765) (0.0909) (0.0696) (0.0927) (0.0723) 

los 0.7165*** 0.7302*** 0.6709***

 (0.0217) (0.0225) (0.0233) 

case mix 0.6169*** 0.3097***

 (0.0237) (0.0229) 

--------------------------------------------------------------------------------------------------------------------
B4

Payer B

Chicago PMSA hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post -0.0385 -0.0333 -0.2058*** -0.2065*** -0.0781 -0.0409 

 (0.0724) (0.0803) (0.0379) (0.0350) (0.0731) (0.0847) 

post*ENHHP 0.1588*** 0.2153*** 0.1662*** 0.2224*** 0.1931*** 0.2240***

 (0.0207) (0.0198) (0.0215) (0.0206) (0.0216) (0.0218) 

public -0.0127 -0.0161 0.0013 -0.0054 -0.0070 -0.0080 

 (0.0733) (0.0613) (0.0706) (0.0634) (0.0540) (0.0515) 

teach -0.0358 0.0025 -0.0538 -0.0077 -0.0728 -0.0132 

 (0.1122) (0.1159) (0.1125) (0.1164) (0.1163) (0.1277) 

los 0.6689*** 0.6886*** 0.6503***

 (0.0577) (0.0583) (0.0652) 

case mix 0.6485*** 0.3529***

 (0.0603) (0.0407) 

--------------------------------------------------------------------------------------------------------------------

Non-merging Chicago PMSA hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post -0.1629 -0.1806 -0.1805 -0.1921 -0.3749*** -0.3813***

 (0.1163) (0.1148) (0.1204) (0.1158) (0.1326) (0.1248) 

post*ENHHP 0.2351*** 0.2565*** 0.2640*** 0.2848*** 0.2631*** 0.2673***

 (0.0551) (0.0501) (0.0558) (0.0499) (0.0676) (0.0616) 

public -0.0887* -0.0687 -0.0554 -0.0503 -0.0330 -0.0226 

 (0.0487) (0.0449) (0.0509) (0.0446) (0.0566) (0.0554) 

teach -0.8167 -0.5840 -1.0525 -0.7553 -0.6700 -0.2977 

 (1.0176) (0.9188) (1.0338) (0.9206) (1.2635) (1.1635) 

los 0.5536*** 0.5764*** 0.5179***

 (0.0449) (0.0454) (0.0508) 
B5

case mix 0.5425*** 0.3027***

 (0.0300) (0.0371) 

Chicago PMSA major teaching hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.1329 0.1416 0.1376 0.1411 -0.1885** -0.1502***

 (0.0765) (0.0825) (0.0833) (0.0907) (0.0773) (0.0477) 

post*ENHHP 0.1642*** 0.2297*** 0.1703*** 0.2356*** 0.1839*** 0.2157***

 (0.0354) (0.0348) (0.0371) (0.0355) (0.0416) (0.0334) 

public -0.1342** -0.0999* -0.1061** -0.0842 -0.0785 -0.0572 

 (0.0490) (0.0513) (0.0488) (0.0563) (0.0473) (0.0488) 

teach -0.7379 -0.8422 -0.7669 -0.8634 -0.8025 -0.8460 

 (0.7570) (0.7338) (0.7416) (0.7319) (0.7816) (0.7473) 

los 0.8030*** 0.8249*** 0.7987***

 (0.0747) (0.0736) (0.0722) 

case mix 0.7480*** 0.4099***

 (0.0649) (0.0414) 

--------------------------------------------------------------------------------------------------------------------

Chicago PMSA teaching hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0085 0.0132 -0.1964*** -0.1925*** -0.0371 0.0064 

 (0.0783) (0.0857) (0.0425) (0.0335) (0.0775) (0.0900) 

post*ENHHP 0.1513*** 0.2139*** 0.1599*** 0.2213*** 0.1840*** 0.2174***

 (0.0208) (0.0217) (0.0221) (0.0231) (0.0226) (0.0242) 

public -0.0676 -0.0540 -0.0547 -0.0465 -0.0604 -0.0531 

 (0.0639) (0.0542) (0.0615) (0.0573) (0.0447) (0.0423) 

teach -0.0269 0.0148 -0.0564 -0.0031 -0.0677 0.0006 

 (0.1275) (0.1352) (0.1293) (0.1390) (0.1324) (0.1481) 

los 0.7473*** 0.7658*** 0.7405***

 (0.0610) (0.0611) (0.0636) 
B6

case mix 0.6910*** 0.3607***

 (0.0650) (0.0470) 

--------------------------------------------------------------------------------------------------------------------

Payer C

Chicago PMSA hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post -0.0055 0.0024 -0.0045 0.0027 -0.0034 0.0040 

 (0.0076) (0.0065) (0.0081) (0.0065) (0.0087) (0.0071) 

post*ENHHP -0.0078 -0.0094 -0.0003 -0.0097 0.0035 -0.0140 

 (0.0124) (0.0106) (0.0122) (0.0104) (0.0124) (0.0107) 

public 0.0009 0.0012 0.0068 0.0030 0.0114 0.0021 

 (0.0209) (0.0182) (0.0205) (0.0177) (0.0206) (0.0188) 

teach -0.0504 -0.0277 -0.0441 -0.0265 -0.0407 -0.0273 

 (0.0721) (0.0571) (0.0715) (0.0569) (0.0755) (0.0600) 

los 0.9263*** 0.9374*** 0.8849***

 (0.0108) (0.0106) (0.0123) 

case mix 0.5635*** 0.1504***

 (0.0215) (0.0179) 

--------------------------------------------------------------------------------------------------------------------

Non-merging Chicago PMSA hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0046 0.0103 0.0052 0.0114 0.0048 0.0127 

 (0.0117) (0.0087) (0.0126) (0.0087) (0.0133) (0.0099) 

post*ENHHP 0.0369* 0.0178 0.0421* 0.0157 0.0539** 0.0149 

 (0.0214) (0.0122) (0.0225) (0.0120) (0.0244) (0.0115) 

public 0.0170 0.0160 0.0243 0.0189 0.0301 0.0160 

 (0.0306) (0.0254) (0.0313) (0.0244) (0.0307) (0.0218) 

teach -1.0554*** -0.6576*** -1.0761*** -0.6483*** -1.2077** -0.7450***

 (0.3635) (0.1685) (0.3918) (0.1746) (0.4515) (0.2423) 
B7

los 0.9041*** 0.9161*** 0.8712***

 (0.0185) (0.0179) (0.0203) 

case mix 0.5782*** 0.1740***

 (0.0316) (0.0299) 

Chicago PMSA major teaching hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post -0.0130 -0.0036 -0.0149 -0.0035 -0.0130 0.0001 

 (0.0160) (0.0138) (0.0164) (0.0137) (0.0176) (0.0152) 

post*ENHHP 0.0021 -0.0208 0.0111 -0.0209 0.0142 -0.0253 

 (0.0236) (0.0166) (0.0236) (0.0164) (0.0265) (0.0168) 

public -0.0378 -0.0363 -0.0327 -0.0342 -0.0259 -0.0342 

 (0.0225) (0.0223) (0.0218) (0.0231) (0.0237) (0.0259) 

teach -0.4524* -0.2807** -0.4570* -0.2842** -0.4765 -0.3358* 

 (0.2454) (0.1143) (0.2505) (0.1153) (0.2961) (0.1618) 

los 0.9585*** 0.9699*** 0.9208***

 (0.0125) (0.0121) (0.0181) 

case mix 0.5365*** 0.1331***

 (0.0399) (0.0315) 

--------------------------------------------------------------------------------------------------------------------

Chicago PMSA teaching hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post -0.0015 0.0050 -0.0011 0.0054 0.0017 0.0063 

 (0.0091) (0.0076) (0.0095) (0.0076) (0.0098) (0.0082) 

post*ENHHP -0.0079 -0.0137 0.0010 -0.0140 0.0026 -0.0185 

 (0.0160) (0.0137) (0.0157) (0.0135) (0.0167) (0.0139) 

public -0.0222 -0.0223 -0.0162 -0.0204 -0.0125 -0.0231 

 (0.0165) (0.0156) (0.0164) (0.0159) (0.0167) (0.0181) 

teach -0.0523 -0.0279 -0.0450 -0.0265 -0.0419 -0.0277 

 (0.0692) (0.0567) (0.0691) (0.0566) (0.0741) (0.0595) 
B8

los 0.9422*** 0.9540*** 0.9013***

 (0.0099) (0.0096) (0.0131) 

case mix 0.5763*** 0.1550***

 (0.0278) (0.0227) 

--------------------------------------------------------------------------------------------------------------------

Payer D

Chicago PMSA hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0579 0.0430 0.0672 0.0803* 0.0903* 0.0963** 

 (0.0403) (0.0379) (0.0519) (0.0459) (0.0494) (0.0457) 

post*ENHHP 0.4430*** 0.4857*** 0.4460*** 0.4869*** 0.4613*** 0.4990***

 (0.0442) (0.0407) (0.0453) (0.0418) (0.0442) (0.0411) 

public 0.0107 -0.0277 0.0238 -0.0209 -0.0011 -0.0250 

 (0.0494) (0.0467) (0.0561) (0.0499) (0.0540) (0.0474) 

teach 0.0982 0.0629 0.1335 0.0857 0.1213 0.0762 

 (0.1544) (0.1140) (0.1602) (0.1276) (0.1600) (0.1210) 

los 0.7955*** 0.7977*** 0.7098***

 (0.0198) (0.0207) (0.0233) 

case mix 0.6812*** 0.3659***

 (0.0265) (0.0285) 

--------------------------------------------------------------------------------------------------------------------

Non-merging Chicago PMSA hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0305 0.0225 0.0257 0.0040 0.0247 0.0350 

 (0.0266) (0.0256) (0.0269) (0.0255) (0.0329) (0.0272) 

post*ENHHP 0.5003*** 0.5567*** 0.5040*** 0.5587*** 0.5243*** 0.5870***

 (0.0577) (0.0517) (0.0549) (0.0485) (0.0562) (0.0473) 

public -0.0168 -0.0296 0.0294 -0.0019 -0.0167 -0.0102 

 (0.0742) (0.0643) (0.0722) (0.0577) (0.0616) (0.0516) 
B9

teach 0.2986 -0.3932 0.2524 -0.4464 0.0589 -0.7831 

 (1.0485) (0.8860) (0.8884) (0.7507) (0.8884) (0.7702) 

los 0.7944*** 0.7934*** 0.6983***

 (0.0339) (0.0373) (0.0419) 

case mix 0.6870*** 0.3850***

 (0.0439) (0.0437) 

Chicago PMSA major teaching hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0844 0.0892 0.0867 0.0814 0.0904 0.0479 

 (0.1685) (0.1454) (0.1696) (0.1475) (0.1258) (0.1217) 

post*ENHHP 0.3967*** 0.4428*** 0.3835*** 0.4317*** 0.3923*** 0.4457***

 (0.1199) (0.1114) (0.1240) (0.1151) (0.1181) (0.1113) 

public -0.0143 -0.0044 0.0298 0.0152 -0.0153 -0.0065 

 (0.0835) (0.0689) (0.0915) (0.0650) (0.0818) (0.0669) 

teach 0.7397** 0.4141* 0.8232*** 0.5798** 0.8283*** 0.5594** 

 (0.2697) (0.2271) (0.2469) (0.2185) (0.2326) (0.2362) 

los 0.8557*** 0.8685*** 0.7653***

 (0.0317) (0.0317) (0.0343) 

case mix 0.7208*** 0.4030***

 (0.0630) (0.0526) 

--------------------------------------------------------------------------------------------------------------------

Chicago PMSA teaching hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.1122 0.1228 0.1104 0.1185 0.1213* 0.0878 

 (0.0934) (0.0816) (0.0941) (0.0836) (0.0717) (0.0685) 

post*ENHHP 0.4059*** 0.4468*** 0.4012*** 0.4451*** 0.4136*** 0.4539***

 (0.0772) (0.0698) (0.0769) (0.0708) (0.0726) (0.0682) 

public 0.0141 -0.0130 0.0379 0.0019 -0.0011 -0.0079 

 (0.0584) (0.0537) (0.0677) (0.0570) (0.0609) (0.0539) 
B10

teach 0.1273 0.0768 0.1505 0.0949 0.1487 0.1004 

 (0.1443) (0.1047) (0.1566) (0.1204) (0.1559) (0.1152) 

los 0.8352*** 0.8384*** 0.7523***

 (0.0209) (0.0218) (0.0222) 

case mix 0.7098*** 0.3766***

 (0.0404) (0.0379) 

--------------------------------------------------------------------------------------------------------------------

Payer E

Chicago PMSA hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0328* 0.0443** 0.0310 0.0442** 0.0161 0.0198 

 (0.0184) (0.0184) (0.0197) (0.0195) (0.0213) (0.0216) 

post*ENHHP 0.1043*** 0.1139*** 0.1163*** 0.1312*** 0.1428*** 0.1482***

 (0.0286) (0.0283) (0.0308) (0.0307) (0.0309) (0.0316) 

public -0.0697*** -0.0820*** -0.0769*** -0.0918*** -0.0835*** -0.0879***

 (0.0212) (0.0227) (0.0208) (0.0208) (0.0203) (0.0203) 

teach -0.0510 -0.0159 -0.0373 -0.0015 -0.0194 -0.0062 

 (0.0653) (0.0658) (0.0668) (0.0676) (0.0684) (0.0677) 

los 0.2408*** 0.2416*** 0.0792** 

 (0.0259) (0.0257) (0.0309) 

case mix 0.4928*** 0.4520***

 (0.0407) (0.0377) 

--------------------------------------------------------------------------------------------------------------------

Non-merging Chicago PMSA hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0146 0.0281 0.0175 0.0333 -0.0042 0.0010 

 (0.0291) (0.0295) (0.0303) (0.0301) (0.0376) (0.0388) 

post*ENHHP 0.1827*** 0.1867*** 0.1983*** 0.2075*** 0.2471*** 0.2498***

 (0.0495) (0.0482) (0.0522) (0.0514) (0.0507) (0.0515) 
B11

public -0.0632*** -0.0699*** -0.0733*** -0.0832*** -0.0710*** -0.0736***

 (0.0192) (0.0198) (0.0165) (0.0169) (0.0156) (0.0146) 

teach -1.7452* -1.4693 -1.6606 -1.3855 -2.2105** -2.1269** 

 (0.9486) (0.9185) (1.0015) (0.9685) (1.0312) (1.0111) 

los 0.2543*** 0.2553*** 0.0812* 

 (0.0393) (0.0383) (0.0456) 

case mix 0.5033*** 0.4644***

 (0.0468) (0.0419) 

Chicago PMSA major teaching hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post -0.0301 -0.0091 -0.0208 0.0053 -0.0261 -0.0165 

 (0.0381) (0.0342) (0.0384) (0.0374) (0.0519) (0.0539) 

post*ENHHP 0.1412* 0.1406* 0.1492* 0.1539* 0.1352 0.1338 

 (0.0789) (0.0787) (0.0837) (0.0850) (0.1047) (0.1064) 

public -0.0551*** -0.0646*** -0.0735*** -0.0866*** -0.0776*** -0.0834***

 (0.0155) (0.0175) (0.0155) (0.0177) (0.0260) (0.0258) 

teach 0.8795 1.0038 0.9626 1.0937 0.4423 0.4677 

 (0.9801) (0.9449) (0.9565) (0.9445) (1.1073) (1.1033) 

los 0.2808*** 0.2901*** 0.1117 

 (0.0677) (0.0677) (0.0727) 

case mix 0.6033*** 0.5636***

 (0.0701) (0.0599) 

--------------------------------------------------------------------------------------------------------------------

Chicago PMSA teaching hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0331 0.0482** 0.0346 0.0515** 0.0194 0.0251 

 (0.0218) (0.0219) (0.0223) (0.0224) (0.0267) (0.0281) 

post*ENHHP 0.1150*** 0.1224*** 0.1217*** 0.1340*** 0.1303*** 0.1345***

 (0.0390) (0.0392) (0.0430) (0.0435) (0.0484) (0.0497) 
B12

public -0.0684*** -0.0755*** -0.0857*** -0.0965*** -0.0861*** -0.0900***

 (0.0176) (0.0197) (0.0173) (0.0194) (0.0226) (0.0230) 

teach -0.0492 -0.0122 -0.0356 0.0038 -0.0125 0.0060 

 (0.0663) (0.0662) (0.0658) (0.0662) (0.0720) (0.0710) 

los 0.2537*** 0.2574*** 0.1049** 

 (0.0381) (0.0378) (0.0467) 

case mix 0.5217*** 0.4726***

 (0.0596) (0.0547) 

--------------------------------------------------------------------------------------------------------------------

St. Therese Medical Center/Victory Memorial Hospital

Payer A

Chicago PMSA hospitals 

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post -0.0284 -0.0093 -0.0291 -0.0095 -0.0381 -0.0139 

 (0.0302) (0.0326) (0.0306) (0.0334) (0.0303) (0.0330) 

post*STMCVMH 0.0589** 0.0389 0.0589** 0.0430* 0.0637*** 0.0369 

 (0.0240) (0.0258) (0.0231) (0.0257) (0.0232) (0.0251) 

public -0.0361 -0.0244 -0.0204 -0.0134 -0.0272 -0.0126 

 (0.0233) (0.0218) (0.0217) (0.0222) (0.0322) (0.0300) 

teach 0.1374 0.2195** 0.1292 0.2236*** 0.1309 0.2364***

 (0.0968) (0.0849) (0.0930) (0.0817) (0.0923) (0.0837) 

los 0.6930*** 0.7079*** 0.6449***

 (0.0178) (0.0178) (0.0182) 

case mix 0.6155*** 0.3134***

 (0.0176) (0.0173) 

--------------------------------------------------------------------------------------------------------------------
B13

Non-merging Chicago PMSA hospitals 

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post -0.0230 0.0019 -0.0220 0.0025 -0.0357 -0.0026 

 (0.0481) (0.0518) (0.0476) (0.0525) (0.0482) (0.0527) 

post*STMCVMH 0.1014*** 0.0830*** 0.1039*** 0.0906*** 0.0978*** 0.0679***

 (0.0212) (0.0225) (0.0223) (0.0228) (0.0230) (0.0236) 

public -0.0539*** -0.0349* -0.0302 -0.0187 -0.0422** -0.0242 

 (0.0172) (0.0187) (0.0191) (0.0210) (0.0170) (0.0156) 

teach -2.2749*** -1.4173* -2.2928*** -1.4054* -2.0590** -0.9886 

 (0.6471) (0.7418) (0.7212) (0.7982) (0.8323) (0.9733) 

los 0.6912*** 0.7100*** 0.6584***

 (0.0206) (0.0205) (0.0232) 

case mix 0.6140*** 0.2999***

 (0.0233) (0.0210) 

--------------------------------------------------------------------------------------------------------------------

Chicago PMSA community hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post -0.0514 -0.0404 -0.0616 -0.0521 -0.0728 -0.0606 

 (0.0689) (0.0737) (0.0687) (0.0725) (0.0669) (0.0706) 

post*STMCVMH 0.0425 0.0355 0.0426 0.0378 0.0421 0.0257 

 (0.0264) (0.0307) (0.0311) (0.0338) (0.0304) (0.0339) 

public -0.0122 -0.0240 -0.0059 -0.0238 0.1107 0.1253 

 (0.1016) (0.1040) (0.1110) (0.1152) (0.0969) (0.0891) 

teach 0.4666 0.0623 -0.4713 -0.8245 -0.6230 -1.2225 

 (0.7653) (0.7718) (0.5815) (0.6182) (0.7380) (0.7745) 

los 0.6531*** 0.6690*** 0.5943***

 (0.0197) (0.0191) (0.0174) 

case mix 0.6111*** 0.3185***
B14

 (0.0217) (0.0224) 

--------------------------------------------------------------------------------------------------------------------

Payer B

Chicago PMSA hospitals 

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post -0.0002 0.0184 -0.0018 0.0143 -0.0135 0.0084 

 (0.0161) (0.0136) (0.0171) (0.0138) (0.0166) (0.0139) 

post*STMCVMH -0.1698*** -0.2337*** -0.1540*** -0.2231*** -0.1407*** -0.2129***

 (0.0206) (0.0225) (0.0216) (0.0224) (0.0212) (0.0236) 

public -0.0083 -0.0118 0.0051 -0.0016 -0.0033 -0.0060 

 (0.0745) (0.0643) (0.0720) (0.0666) (0.0561) (0.0552) 

teach -0.0178 0.0261 -0.0350 0.0165 -0.0504 0.0114 

 (0.1071) (0.1092) (0.1068) (0.1091) (0.1106) (0.1198) 

los 0.6686*** 0.6883*** 0.6501***

 (0.0578) (0.0584) (0.0652) 

case mix 0.6486*** 0.3533***

 (0.0603) (0.0407) 

--------------------------------------------------------------------------------------------------------------------
B15

Non-merging Chicago PMSA hospitals 

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post -0.0043 0.0169 -0.0096 0.0110 -0.0199 0.0094 

 (0.0262) (0.0258) (0.0251) (0.0247) (0.0267) (0.0255) 

post*STMCVMH -0.1233*** -0.1852*** -0.0920*** -0.1608*** -0.0793*** -0.1470***

 (0.0217) (0.0186) (0.0203) (0.0156) (0.0187) (0.0187) 

public -0.1090** -0.0989** -0.0832 -0.0855* -0.0713 -0.0699 

 (0.0470) (0.0463) (0.0501) (0.0493) (0.0631) (0.0688) 

teach -0.9633 -0.6910 -1.2190 -0.8844 -0.8951 -0.4816 

 (1.0320) (0.9548) (1.0535) (0.9536) (1.2586) (1.1790) 

los 0.5708*** 0.5920*** 0.5358***

 (0.0417) (0.0430) (0.0483) 

case mix 0.5378*** 0.2858***

 (0.0319) (0.0368) 

--------------------------------------------------------------------------------------------------------------------

Chicago PMSA community hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0189 0.0363 0.0075 0.0230 0.0066 0.0218 

 (0.0321) (0.0295) (0.0301) (0.0288) (0.0320) (0.0314) 

post*STMCVMH -0.1747*** -0.2156*** -0.1580*** -0.2025*** -0.1219*** -0.1684***

 (0.0312) (0.0296) (0.0315) (0.0300) (0.0336) (0.0329) 

public 0.1263* 0.0810 0.1219 0.0758 0.0741 0.0485 

 (0.0637) (0.0711) (0.0730) (0.0832) (0.0824) (0.0938) 

teach 3.6310** 2.0813 3.5706* 1.8684 5.6472*** 4.1765** 

 (1.5351) (1.5482) (1.8924) (1.8493) (2.0124) (2.0115) 

los 0.5017*** 0.5194*** 0.4504***

 (0.0411) (0.0422) (0.0493) 

case mix 0.5851*** 0.3712***
B16

 (0.0651) (0.0667) 

--------------------------------------------------------------------------------------------------------------------

Payer C

Chicago PMSA hospitals 

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post -0.0100 -0.0006 -0.0097 -0.0005 -0.0051 0.0035 

 (0.0082) (0.0067) (0.0089) (0.0067) (0.0092) (0.0071) 

post*STMCVMH -0.0693*** -0.0641*** -0.0711*** -0.0631*** -0.0657*** -0.0803***

 (0.0117) (0.0099) (0.0117) (0.0097) (0.0119) (0.0102) 

public 0.0045 0.0038 0.0109 0.0056 0.0157 0.0073 

 (0.0222) (0.0190) (0.0220) (0.0185) (0.0220) (0.0204) 

teach -0.0515 -0.0289 -0.0446 -0.0277 -0.0407 -0.0291 

 (0.0726) (0.0578) (0.0717) (0.0576) (0.0755) (0.0613) 

los 0.9263*** 0.9374*** 0.8848***

 (0.0108) (0.0106) (0.0122) 

case mix 0.5634*** 0.1502***

 (0.0215) (0.0179) 

--------------------------------------------------------------------------------------------------------------------
B17

Non-merging Chicago PMSA hospitals 

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0002 0.0072 0.0010 0.0080 0.0056 0.0136 

 (0.0151) (0.0110) (0.0163) (0.0109) (0.0160) (0.0121) 

post*STMCVMH -0.0552*** -0.0542*** -0.0580*** -0.0549*** -0.0516*** -0.0729***

 (0.0193) (0.0160) (0.0190) (0.0156) (0.0181) (0.0160) 

public 0.0267 0.0221 0.0344 0.0250 0.0417 0.0254 

 (0.0366) (0.0296) (0.0379) (0.0286) (0.0379) (0.0288) 

teach -1.1213*** -0.6854*** -1.1571*** -0.6732*** -1.3033*** -0.7716***

 (0.3917) (0.1806) (0.4215) (0.1863) (0.4778) (0.2623) 

los 0.8968*** 0.9096*** 0.8606***

 (0.0184) (0.0182) (0.0195) 

case mix 0.5946*** 0.1877***

 (0.0297) (0.0275) 

--------------------------------------------------------------------------------------------------------------------

Chicago PMSA community hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post -0.0195 -0.0021 -0.0212 -0.0021 -0.0172 0.0046 

 (0.0207) (0.0172) (0.0223) (0.0173) (0.0224) (0.0179) 

post*STMCVMH -0.0844*** -0.0731*** -0.0858*** -0.0722*** -0.0791*** -0.0921***

 (0.0234) (0.0204) (0.0238) (0.0199) (0.0213) (0.0193) 

public 0.1393** 0.1381** 0.1407** 0.1369** 0.1527** 0.1705** 

 (0.0651) (0.0586) (0.0683) (0.0583) (0.0677) (0.0639) 

teach 1.6241*** 1.4408*** 2.0844*** 1.4342*** 2.1107*** 1.2588***

 (0.3462) (0.3339) (0.3720) (0.3487) (0.2680) (0.3056) 

los 0.8910*** 0.9012*** 0.8449***

 (0.0246) (0.0244) (0.0255) 

case mix 0.5488*** 0.1507***
B18

 (0.0331) (0.0292) 

--------------------------------------------------------------------------------------------------------------------

Payer D

Chicago PMSA hospitals 

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0576* 0.0719*** 0.0706* 0.0727** 0.0545 0.0765** 

 (0.0324) (0.0271) (0.0373) (0.0284) (0.0362) (0.0310) 

post*STMCVMH 0.1732*** 0.1599*** 0.1724*** 0.1813*** 0.1956*** 0.1806***

 (0.0422) (0.0400) (0.0367) (0.0359) (0.0366) (0.0358) 

public 0.0332 -0.0027 0.0463 0.0031 0.0212 0.0014 

 (0.0494) (0.0497) (0.0546) (0.0527) (0.0526) (0.0500) 

teach 0.1671 0.1389 0.2027 0.1611 0.1916 0.1528 

 (0.1959) (0.1625) (0.1998) (0.1736) (0.2015) (0.1689) 

los 0.7951*** 0.7973*** 0.7094***

 (0.0198) (0.0207) (0.0233) 

case mix 0.6810*** 0.3658***

 (0.0267) (0.0287) 

--------------------------------------------------------------------------------------------------------------------
B19

Non-merging Chicago PMSA hospitals 

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0287 0.0353 0.0389 0.0209 0.0189 0.0194 

 (0.0488) (0.0322) (0.0564) (0.0307) (0.0506) (0.0311) 

post*STMCVMH 0.2504*** 0.2230*** 0.2287*** 0.2384*** 0.2474*** 0.2374***

 (0.0190) (0.0187) (0.0238) (0.0223) (0.0189) (0.0183) 

public 0.0070 -0.0219 0.0460 -0.0045 0.0027 -0.0009 

 (0.0691) (0.0663) (0.0686) (0.0614) (0.0552) (0.0503) 

teach -0.0944 -0.7682 -0.0450 -0.7124 -0.3242 -1.1301* 

 (0.9448) (0.7404) (0.8142) (0.6324) (0.8117) (0.6331) 

los 0.7999*** 0.7976*** 0.7022***

 (0.0363) (0.0404) (0.0459) 

case mix 0.7041*** 0.3944***

 (0.0414) (0.0445) 

--------------------------------------------------------------------------------------------------------------------

Chicago PMSA community hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post -0.0228 0.0114 -0.0346 -0.0039 -0.0486 -0.0081 

 (0.0434) (0.0306) (0.0415) (0.0305) (0.0398) (0.0292) 

post*STMCVMH 0.2385*** 0.2122*** 0.2087*** 0.2315*** 0.2536*** 0.2384***

 (0.0202) (0.0182) (0.0298) (0.0257) (0.0207) (0.0211) 

public -0.0031 -0.0660 -0.0209 -0.0907* -0.0169 -0.0830 

 (0.0865) (0.0625) (0.0817) (0.0522) (0.1014) (0.0614) 

teach 5.0704*** 4.3258*** 6.5042*** 4.5570*** 6.9350*** 3.6845***

 (1.0075) (0.7977) (0.8885) (0.7291) (0.5510) (0.6304) 

los 0.7299*** 0.7279*** 0.6385***

 (0.0309) (0.0339) (0.0414) 

case mix 0.6474*** 0.3616***
B20

 (0.0222) (0.0428) 

--------------------------------------------------------------------------------------------------------------------

Payer E

Chicago PMSA hospitals 

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0382 0.0550** 0.0220 0.0401** 0.0124 0.0181 

 (0.0235) (0.0211) (0.0216) (0.0193) (0.0194) (0.0186) 

post*STMCVMH -0.2450*** -0.2552*** -0.2371*** -0.2470*** -0.1982*** -0.2011***

 (0.0319) (0.0329) (0.0241) (0.0247) (0.0245) (0.0248) 

public -0.0558*** -0.0674*** -0.0621*** -0.0760*** -0.0674*** -0.0713***

 (0.0202) (0.0195) (0.0224) (0.0208) (0.0202) (0.0202) 

teach -0.0320 0.0048 -0.0160 0.0224 0.0068 0.0209 

 (0.0686) (0.0713) (0.0706) (0.0743) (0.0732) (0.0728) 

los 0.2406*** 0.2413*** 0.0788** 

 (0.0260) (0.0258) (0.0310) 

case mix 0.4928*** 0.4522***

 (0.0406) (0.0377) 

--------------------------------------------------------------------------------------------------------------------
B21

Non-merging Chicago PMSA hospitals 

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0315 0.0462* 0.0136 0.0296 0.0051 0.0124 

 (0.0288) (0.0272) (0.0288) (0.0263) (0.0272) (0.0259) 

post*STMCVMH -0.2199*** -0.2302*** -0.2218*** -0.2330*** -0.1828*** -0.1871***

 (0.0429) (0.0457) (0.0308) (0.0308) (0.0264) (0.0264) 

public -0.0506*** -0.0567*** -0.0607*** -0.0705*** -0.0550*** -0.0579***

 (0.0168) (0.0167) (0.0153) (0.0148) (0.0146) (0.0144) 

teach -2.2976** -2.0755** -2.2804** -2.0380** -2.9806*** -2.8954***

 (0.8906) (0.8355) (0.9551) (0.8922) (0.8369) (0.8115) 

los 0.2897*** 0.2890*** 0.1217***

 (0.0318) (0.0322) (0.0404) 

case mix 0.5178*** 0.4553***

 (0.0485) (0.0470) 

--------------------------------------------------------------------------------------------------------------------

Chicago PMSA community hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0363 0.0470 0.0179 0.0287 -0.0036 -0.0020 

 (0.0366) (0.0361) (0.0325) (0.0316) (0.0309) (0.0300) 

post*STMCVMH -0.2338*** -0.2385*** -0.2577*** -0.2594*** -0.1958*** -0.1948***

 (0.0543) (0.0577) (0.0326) (0.0332) (0.0278) (0.0276) 

public -0.0304 -0.0813 0.0178 -0.0329 -0.0125 -0.0216 

 (0.0995) (0.0997) (0.0933) (0.0938) (0.0778) (0.0755) 

teach -1.7625 -2.2392** -3.0962** -3.6244*** -2.6442*** -2.7422***

 (1.1401) (1.0906) (1.1981) (1.1753) (0.9003) (0.8833) 

los 0.2359*** 0.2320*** 0.0463 

 (0.0355) (0.0349) (0.0403) 

case mix 0.4563*** 0.4283***
B22

 (0.0389) (0.0381) 

--------------------------------------------------------------------------------------------------------------------

Evanston Northwestern Healthcare/Highland Park: IDPH/Cost Report Data

All Patients

Chicago PMSA hospitals 

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.1209*** 0.1402*** 0.1442*** 0.1467*** 0.0893*** 0.1023***

 (0.0137) (0.0133) (0.0135) (0.0133) (0.0124) (0.0115) 

post*ENHHP 0.1437*** 0.1535*** 0.1401*** 0.1530*** 0.1329*** 0.1549***

 (0.0134) (0.0121) (0.0126) (0.0118) (0.0130) (0.0123) 

public 0.0004 0.0075 0.0003 0.0078 -0.0039 0.0032 

 (0.0235) (0.0173) (0.0237) (0.0168) (0.0273) (0.0200) 

teach -0.0846** -0.0601 -0.0908** -0.0612 -0.0770* -0.0625 

 (0.0411) (0.0385) (0.0415) (0.0385) (0.0426) (0.0411) 

los 0.6964*** 0.7409*** 0.6162***

 (0.0092) (0.0096) (0.0118) 

case mix 0.9671*** 0.6707***

 (0.0098) (0.0147) 

--------------------------------------------------------------------------------------------------------------------

Observations 4260561 4260561 4260561 4260561 4260561 4260561 

--------------------------------------------------------------------------------------------------------------------
B23

Non-merging Chicago PMSA hospitals 

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.1342*** 0.1518*** 0.0888*** 0.0994*** 0.0940*** 0.1084***

 (0.0225) (0.0217) (0.0187) (0.0178) (0.0192) (0.0185) 

post*ENHHP 0.1409*** 0.1479*** 0.1429*** 0.1483*** 0.1324*** 0.1509***

 (0.0273) (0.0186) (0.0285) (0.0188) (0.0292) (0.0181) 

public -0.0098 -0.0040 -0.0090 -0.0034 -0.0134 -0.0114 

 (0.0230) (0.0145) (0.0228) (0.0137) (0.0277) (0.0162) 

teach -0.0904 0.0029 -0.1813 -0.0225 -0.0927 0.0079 

 (0.4377) (0.3346) (0.4710) (0.3429) (0.4822) (0.3484) 

los 0.7018*** 0.7454*** 0.6389***

 (0.0164) (0.0167) (0.0196) 

case mix 0.9489*** 0.6467***

 (0.0163) (0.0239) 

--------------------------------------------------------------------------------------------------------------------

Observations 2227246 2227246 2227246 2227246 2227246 2227246 

--------------------------------------------------------------------------------------------------------------------
B24

Chicago PMSA major teaching hospitals 

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.1097*** 0.1345*** 0.2120*** 0.2184*** 0.2214*** 0.2378***

 (0.0223) (0.0197) (0.0292) (0.0274) (0.0274) (0.0253) 

post*ENHHP 0.1542*** 0.1485*** 0.1521*** 0.1473*** 0.1461*** 0.1498***

 (0.0413) (0.0371) (0.0386) (0.0361) (0.0385) (0.0367) 

public -0.0322* -0.0114 -0.0359** -0.0111 -0.0447** -0.0230 

 (0.0169) (0.0164) (0.0160) (0.0159) (0.0163) (0.0165) 

teach -0.8151 -0.6652 -0.8369 -0.6734 -0.8083 -0.6465 

 (0.4799) (0.4570) (0.4886) (0.4601) (0.4877) (0.4644) 

los 0.7284*** 0.7811*** 0.6507***

 (0.0206) (0.0191) (0.0274) 

case mix 0.9741*** 0.6707***

 (0.0180) (0.0335) 

--------------------------------------------------------------------------------------------------------------------

Observations 1478923 1478923 1478923 1478923 1478923 1478923 

--------------------------------------------------------------------------------------------------------------------
B25

Chicago PMSA teaching hospitals 

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.1316*** 0.1544*** 0.0946*** 0.1075*** 0.1679*** 0.1760***

 (0.0168) (0.0158) (0.0159) (0.0137) (0.0158) (0.0154) 

post*ENHHP 0.1326*** 0.1400*** 0.1301*** 0.1398*** 0.1234*** 0.1439***

 (0.0171) (0.0149) (0.0159) (0.0146) (0.0162) (0.0150) 

public 0.0037 0.0126 0.0023 0.0129 -0.0032 0.0060 

 (0.0256) (0.0195) (0.0258) (0.0191) (0.0291) (0.0217) 

teach -0.0868** -0.0625* -0.0925** -0.0633* -0.0788* -0.0645* 

 (0.0403) (0.0357) (0.0407) (0.0357) (0.0419) (0.0381) 

los 0.7112*** 0.7580*** 0.6280***

 (0.0118) (0.0117) (0.0156) 

case mix 0.9728*** 0.6685***

 (0.0127) (0.0204) 

--------------------------------------------------------------------------------------------------------------------

Observations 2887017 2887017 2887017 2887017 2887017 2887017 

--------------------------------------------------------------------------------------------------------------------
B26

Private Pay Patients

Chicago PMSA hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0665*** 0.0756*** 0.1353*** 0.1352*** 0.0853*** 0.0981***

 (0.0122) (0.0118) (0.0140) (0.0143) (0.0123) (0.0121) 

post*ENHHP 0.1418*** 0.1455*** 0.1426*** 0.1453*** 0.1282*** 0.1315***

 (0.0111) (0.0110) (0.0110) (0.0108) (0.0110) (0.0108) 

public -0.0082 0.0072 -0.0078 0.0089 -0.0147 0.0019 

 (0.0193) (0.0165) (0.0198) (0.0165) (0.0221) (0.0199) 

teach -0.0790** -0.0511 -0.0886** -0.0539 -0.0681* -0.0392 

 (0.0331) (0.0356) (0.0341) (0.0356) (0.0367) (0.0385) 

los 0.6866*** 0.7364*** 0.5982***

 (0.0094) (0.0097) (0.0124) 

case mix 0.9192*** 0.6940***

 (0.0124) (0.0159) 

--------------------------------------------------------------------------------------------------------------------

Observations 1891630 1891630 1891630 1891630 1891630 1891630 

--------------------------------------------------------------------------------------------------------------------
B27

Non-merging Chicago PMSA hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.1167*** 0.1306*** 0.0656*** 0.1372*** 0.0763*** 0.0947***

 (0.0214) (0.0220) (0.0180) (0.0219) (0.0200) (0.0196) 

post*ENHHP 0.1559*** 0.1515*** 0.1594*** 0.1508*** 0.1372*** 0.1278***

 (0.0256) (0.0185) (0.0273) (0.0186) (0.0284) (0.0198) 

public -0.0186 -0.0045 -0.0168 -0.0034 -0.0222 -0.0111 

 (0.0168) (0.0138) (0.0167) (0.0134) (0.0208) (0.0171) 

teach -0.1146 0.0250 -0.1913 0.0063 -0.0289 0.1826 

 (0.4459) (0.3452) (0.4801) (0.3527) (0.4860) (0.3387) 

los 0.6960*** 0.7461*** 0.6224***

 (0.0169) (0.0166) (0.0217) 

case mix 0.9014*** 0.6716***

 (0.0211) (0.0272) 

--------------------------------------------------------------------------------------------------------------------

Observations 969836 969836 969836 969836 969836 969836 

--------------------------------------------------------------------------------------------------------------------
B28

Chicago PMSA major teaching hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0936*** 0.1119*** 0.1937*** 0.2026*** 0.1134*** 0.1371***

 (0.0196) (0.0177) (0.0256) (0.0263) (0.0185) (0.0177) 

post*ENHHP 0.1253*** 0.1139*** 0.1306*** 0.1147*** 0.1134*** 0.1006***

 (0.0263) (0.0227) (0.0273) (0.0227) (0.0245) (0.0196) 

public -0.0282* -0.0084 -0.0304** -0.0085 -0.0402*** -0.0216 

 (0.0142) (0.0132) (0.0138) (0.0128) (0.0136) (0.0135) 

teach -0.4101 -0.2653 -0.4347 -0.2872 -0.3983 -0.2191 

 (0.2680) (0.2474) (0.2829) (0.2511) (0.2692) (0.2271) 

los 0.7234*** 0.7807*** 0.6280***

 (0.0196) (0.0174) (0.0270) 

case mix 0.9524*** 0.7080***

 (0.0188) (0.0332) 

--------------------------------------------------------------------------------------------------------------------

Observations 701663 701663 701663 701663 701663 701663 

--------------------------------------------------------------------------------------------------------------------
B29

Chicago PMSA teaching hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0794*** 0.0929*** 0.0886*** 0.0962*** 0.1695*** 0.1835***

 (0.0160) (0.0149) (0.0163) (0.0147) (0.0170) (0.0175) 

post*ENHHP 0.1250*** 0.1267*** 0.1284*** 0.1275*** 0.1121*** 0.1133***

 (0.0137) (0.0132) (0.0139) (0.0132) (0.0132) (0.0120) 

public -0.0059 0.0117 -0.0071 0.0131 -0.0156 0.0041 

 (0.0211) (0.0189) (0.0213) (0.0191) (0.0231) (0.0220) 

teach -0.0793*** -0.0508* -0.0882*** -0.0530* -0.0676** -0.0380 

 (0.0295) (0.0298) (0.0312) (0.0300) (0.0332) (0.0330) 

los 0.7014*** 0.7529*** 0.6124***

 (0.0124) (0.0119) (0.0169) 

case mix 0.9367*** 0.6968***

 (0.0139) (0.0223) 

--------------------------------------------------------------------------------------------------------------------

Observations 1243497 1243497 1243497 1243497 1243497 1243497 

--------------------------------------------------------------------------------------------------------------------
B30

St. Therese Medical Center/Victory Memorial Hospital: IDPH/Cost Report Data

All Patients

Chicago PMSA hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.1265*** 0.1462*** 0.1497*** 0.1527*** 0.0950*** 0.1087***

 (0.0152) (0.0148) (0.0149) (0.0148) (0.0119) (0.0114) 

post*STMCVMH -0.0706*** -0.0774*** -0.0751*** -0.0769*** -0.0760*** -0.0774***

 (0.0130) (0.0123) (0.0122) (0.0120) (0.0126) (0.0123) 

public 0.0051 0.0121 0.0052 0.0124 0.0010 0.0092 

 (0.0241) (0.0177) (0.0247) (0.0173) (0.0283) (0.0212) 

teach -0.0674 -0.0417 -0.0741 -0.0428 -0.0612 -0.0441 

 (0.0474) (0.0480) (0.0479) (0.0482) (0.0484) (0.0507) 

los 0.6964*** 0.7408*** 0.6161***

 (0.0092) (0.0096) (0.0118) 

case mix 0.9673*** 0.6709***

 (0.0098) (0.0148) 

--------------------------------------------------------------------------------------------------------------------

Observations 4260561 4260561 4260561 4260561 4260561 4260561 

--------------------------------------------------------------------------------------------------------------------
B31

Non-merging Chicago PMSA hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0863*** 0.1018*** 0.1482*** 0.1525*** 0.1627*** 0.1693***

 (0.0189) (0.0174) (0.0212) (0.0215) (0.0211) (0.0213) 

post*STMCVMH -0.0682*** -0.0743*** -0.0719*** -0.0738*** -0.0732*** -0.0731***

 (0.0167) (0.0157) (0.0156) (0.0154) (0.0164) (0.0160) 

public -0.0027 0.0018 -0.0019 0.0022 -0.0060 -0.0039 

 (0.0242) (0.0142) (0.0245) (0.0136) (0.0299) (0.0168) 

teach -0.1364 -0.0383 -0.2272 -0.0617 -0.1390 -0.0369 

 (0.4472) (0.3436) (0.4819) (0.3521) (0.4913) (0.3561) 

los 0.7029*** 0.7463*** 0.6433***

 (0.0168) (0.0171) (0.0195) 

case mix 0.9476*** 0.6383***

 (0.0171) (0.0243) 

--------------------------------------------------------------------------------------------------------------------

Observations 2143928 2143928 2143928 2143928 2143928 2143928 

--------------------------------------------------------------------------------------------------------------------
B32

Chicago PMSA community hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0570*** 0.0673*** 0.1218*** 0.1198*** 0.1379*** 0.1388***

 (0.0204) (0.0213) (0.0236) (0.0249) (0.0243) (0.0257) 

post*STMCVMH -0.0409* -0.0400* -0.0489** -0.0406** -0.0551** -0.0495** 

 (0.0212) (0.0201) (0.0203) (0.0197) (0.0225) (0.0214) 

public -0.0215 -0.0335 0.0012 -0.0281 0.0238 0.0160 

 (0.0723) (0.0638) (0.0702) (0.0629) (0.0754) (0.0682) 

teach -0.5557* -0.3605 0.0187 -0.3188 -0.2537 -0.8013** 

 (0.3205) (0.3372) (0.3082) (0.3330) (0.3211) (0.3580) 

los 0.6611*** 0.6982*** 0.5811***

 (0.0073) (0.0082) (0.0125) 

case mix 0.9594*** 0.6827***

 (0.0140) (0.0163) 

--------------------------------------------------------------------------------------------------------------------

Observations 1353576 1353576 1353576 1353576 1353576 1353576 

--------------------------------------------------------------------------------------------------------------------
B33

Private Pay Patients

Chicago PMSA hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0737*** 0.0832*** 0.1423*** 0.1424*** 0.0918*** 0.1049***

 (0.0119) (0.0118) (0.0168) (0.0169) (0.0117) (0.0118) 

post*STMCVMH -0.0563*** -0.0653*** -0.0580*** -0.0647*** -0.0561*** -0.0646***

 (0.0122) (0.0123) (0.0121) (0.0123) (0.0117) (0.0118) 

public -0.0032 0.0120 -0.0026 0.0137 -0.0094 0.0075 

 (0.0200) (0.0170) (0.0207) (0.0172) (0.0231) (0.0212) 

teach -0.0633 -0.0350 -0.0728 -0.0378 -0.0540 -0.0248 

 (0.0444) (0.0477) (0.0452) (0.0476) (0.0465) (0.0492) 

los 0.6865*** 0.7364*** 0.5982***

 (0.0094) (0.0097) (0.0124) 

case mix 0.9193*** 0.6941***

 (0.0124) (0.0160) 

--------------------------------------------------------------------------------------------------------------------

Observations 1891630 1891630 1891630 1891630 1891630 1891630 

--------------------------------------------------------------------------------------------------------------------
B34

Non-merging Chicago PMSA hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0659*** 0.0760*** 0.0738*** 0.0800*** 0.0849*** 0.1014***

 (0.0169) (0.0164) (0.0165) (0.0163) (0.0184) (0.0186) 

post*STMCVMH -0.0380** -0.0483*** -0.0396** -0.0479*** -0.0395** -0.0513***

 (0.0164) (0.0166) (0.0159) (0.0166) (0.0175) (0.0178) 

public -0.0102 0.0028 -0.0082 0.0037 -0.0129 -0.0024 

 (0.0172) (0.0127) (0.0180) (0.0125) (0.0232) (0.0182) 

teach -0.1758 -0.0301 -0.2551 -0.0481 -0.0882 0.1294 

 (0.4567) (0.3532) (0.4929) (0.3610) (0.4942) (0.3425) 

los 0.6964*** 0.7461*** 0.6297***

 (0.0177) (0.0175) (0.0211) 

case mix 0.8993*** 0.6607***

 (0.0231) (0.0288) 

--------------------------------------------------------------------------------------------------------------------

Observations 909478 909478 909478 909478 909478 909478 

--------------------------------------------------------------------------------------------------------------------
B35

Chicago PMSA community hospitals

--------------------------------------------------------------------------------------------------------------------

 APRDRGSOI APRDRGSOI/los DRG DRG/los weights weights/los 

--------------------------------------------------------------------------------------------------------------------

post 0.0949*** 0.1026*** 0.0549*** 0.0544*** 0.0587*** 0.0674***

 (0.0222) (0.0238) (0.0163) (0.0190) (0.0185) (0.0222) 

post*STMCVMH -0.0204 -0.0224 -0.0264 -0.0229 -0.0266 -0.0275 

 (0.0180) (0.0184) (0.0171) (0.0181) (0.0197) (0.0206) 

public -0.0233 -0.0366 -0.0034 -0.0293 0.0236 0.0110 

 (0.0570) (0.0619) (0.0518) (0.0603) (0.0545) (0.0608) 

teach 0.0867 -0.0501 0.4642* -0.0275 0.4739 -0.1811 

 (0.3067) (0.3371) (0.2716) (0.3280) (0.3132) (0.3860) 

los 0.6517*** 0.6951*** 0.5583***

 (0.0055) (0.0076) (0.0130) 

case mix 0.8902*** 0.6965***

 (0.0192) (0.0172) 

--------------------------------------------------------------------------------------------------------------------

Observations 643159 643159 643159 643159 643159 643159 

--------------------------------------------------------------------------------------------------------------------