Promoting domestic medical travel to high-quality providers could improve clinical outcomes and reduce long-term healthcare costs.
To investigate whether domestic medical travel (DMT; traveling outside of one’s home region but within the United States for medical care) and surgeon volume affect clinical outcomes and costs for patients undergoing elective cardiovascular procedures.
Retrospective, cross-sectional analysis of patient discharge data from US academic medical centers.
Patients were classified as medical travelers if they received elective, nonemergent care more than 250 miles from home. High-volume surgeons (HVSs) were those above the 75th percentile compared with other study surgeons in the annual number of cardiovascular surgeries performed. Multivariable regression models were fit to test the relationships among complications, mortality, length of stay (LOS), cost, DMT status, and surgeon volume, controlling for sociodemographic and clinical factors.
Patients who traveled to HVSs were more likely to be male, white, have lower severity of illness, and have health insurance through an indemnity plan or preferred provider organization with coverage outside of the patient’s home region. Patients who traveled to HVSs had shorter LOS and fewer complications than those who received care from local, low-volume surgeons. There was no significant difference in mortality between travelers and nontravelers.
Patients who travelled to HVSs for elective cardiovascular procedures had outcomes similar to or better than those of patients who received care locally from low-volume surgeons. We found no increase in complications or LOS, despite potentially complex logistical arrangements required by travelers. More work is needed to evaluate the potential of DMT to improve the value of care provided for selected procedures.
Am J Manag Care. 2013;19(10):825-832Our results confirm previous research that high-volume providers—both hospitals and surgeons—offer better outcomes for elective cardiovascular procedures than low-volume providers, and expand on previous work by determining that traveling outside of one’s home region does not negatively affect the quality of care received during the hospital stay. These findings suggest that promoting domestic travel to high-quality providers could:
Substantial variation in healthcare utilization and spending across the United States is a signal of the inefficiencies that permeate the healthcare system.1 Unsustainable growth in healthcare spending led to the passing of the 2010 Patient Protection and Affordable Care Act, with the goals of slowing spending growth and reducing variation in the quality of care. However, legislation alone is not sufficient to eliminate the inefficiencies; healthcare policy makers, providers, and payers must continue to take innovative steps to solve the problems plaguing the healthcare system.2-4 Because of their reputation for providing high-quality care, many academic medical centers (AMCs) cater to international and domestic patients searching for the best care in the world. The same prestige that attracts these patients to AMCs also attracts top surgeons who want to practice, teach, and conduct research in world-renowned medical centers. Advanced skill sets coupled with the large volume of patients at AMCs allow top surgeons to refine their technique by treating more patients—ultimately allowing high-volume surgeons (HVSs) to provide care that results in better outcomes.5-8
Traveling domestically to high-volume providers may also improve the effectiveness and efficiency of care provided within the United States. However, only recently has the concept of structured domestic medical travel (DMT) received much attention. Payers have begun contracting with centers of excellence at the national level to provide certain treatments. For example, Lowe’s, a national home improvement chain, forged an agreement with the Cleveland Clinic, U.S. News and World Report’s top-ranked hospital for cardiology and heart surgery, to provide cardiac surgery for its employees.9 Regionalization of medical care has historically been reserved for procedures with insufficient volume to support providers in suburban and rural markets; but if travel to high-volume providers also increases the value of care, a broader range of treatments could be regionalized, increasing national competition based on both quality and economics.10
Many studies have found an association between patient outcomes and provider—both hospital and surgeon—volume.5-8 For someprocedures, high-volume providers have lower in-hospital mortality, length of stay (LOS), and complication rates than their low-volume counterparts.5,11-15 Even small differences in individual patient outcomes can have a substantial impact on healthcare costs at the national level.12 Increases in patient volume lead to improvements in outcomes, which then improve the provider’s reputation and lead to further increases in patient volume. This cycle can help to further improve quality of care. Regionalization of healthcare also has the potential to substantially reduce costs.16,17 When research and education are excluded, AMCs may actually have lower costs than community hospitals for 3 reasons: economies of scale, expertise, and avoidance of adverse events.16 Higher volumes are one component that allows AMCs to achieve economies of scale and improve patient outcomes. This leads to lower costs for the initial treatment and reduces the risk of postdischarge complications, further reducing long-term healthcare costs.
Many patients must travel if they want to receive care from an HVS. Traveling outside of one’s home region, however, raises potential problems for both the patient and provider. The provider might have incomplete information about the patient’s severity of illness (SOI) and comorbid medical conditions that could affect the patient’s recovery and risk of complications. The provider must also coordinate ollow-up care such as physician visits and home healthcare near where the patient lives, which can be more difficult for patients who have traveled a distance for their care. Additionally, the patient might need temporary lodging near the hospital until he or she can return home. It is not known whether the benefits of being treated by a high-volume provider outweigh the challenges associated with traveling outside of one’s home region for care.
The goals of this study were to identify the characteristics of patients who travel to HVSs for elective cardiovascular procedures; to determine whether domestic medical travelers have better outcomes than patients seen locally by lowvolume surgeons (LVSs); and to determine whether domestic medical travelers have outcomes similar to those of patients seen locally by HVSs.
This study was a retrospective, crosssectional analysis of patient discharge data from AMC members of UHC’s Clinical Database. UHC is an alliance of 115 AMCs and more than 250 of their affiliated hospitals. The Clinical Database is populated with administrative data recorded in UB-04 billing forms, which collect patient-specific information for all patients discharged from participating hospitals. UHC uses a standardized data submission process to ensure data integrity and comparability. The study sample was drawn from all discharges between October 2009 and September 2010 of AMC members in UHC’s Clinical Database. The sample was limited to patients 18 years and older who were discharged after elective, nonemergent cardiac valve replacement and other major cardiothoracic procedures, defined by the Medicare Severity Diagnosis Related Groups 216 through 218.
The outcomes examined in this study included in-hospital mortality, LOS, complications, and direct cost of hospital care. In-hospital mortality was a dichotomous variable (the patient did or did not die during the hospital stay). LOS was measured as the number of days the patient was hospitalized. Complications was a binary variable that indicated whether or not the patient had at least 1 of the following: postoperative stroke, aspiration pneumonia, gastrointestinal hemorrhage, catheter-associated urinary tract infection, postoperative or intraoperative shock due to anesthesia, reopening of surgical site, mechanical complications due to device/implant/graft (except organ transplant), acute myocardial infarction occurring during the hospital stay, postoperative coma or stupor, nosocomial pneumonia, complications relating to anesthetic agents or other central nervous system depressants, wound infection, and sepsis. Direct cost of hospital care was calculated by subtracting non—patient care costs (overhead) from the total wage index–adjusted cost attributed to each patient. Overhead was defined as costs allocated to those categories found in the general service cost centers within Schedule B of the Medicare cost report, excluding nursing administration, central services and supply, and pharmacy. Cases from a few participating institutions that do not submit cost data to the Clinical Database were excluded from the cost analysis. All other characteristics were available for the entire study population.
Patients were classified as domestic medical travelers based on the straight-line distance between the patient’s home (longitude and latitude derived from the patient’s zip code) and the zip code of the hospital where the patient’s surgery was performed. Domestic medical travel was classified as a dichotomous variable indicating whether or not the patient traveled 250 miles or more.
Surgeon volume was based on the total number of cardiac valve replacement and other major cardiothoracic procedures performed during the study period. Quartiles of surgeon volume were created, and surgeons were classified into 2 categories: HVS, which included those with volume in the top quartile of the study population; and LVS, which included those in the lower 3 quartiles. An additional variable was an interaction between DMT (yes/no) and surgeon volume, and resulted in 3 main categories: travel to HVS, nontravel to HVS, and nontravel to LVS. A fourth category—travel to LVS—was also observed, but this group was so small that it was not included in the study.
Demographic characteristics, patient admission complexity, and hospital characteristics were included in the analysis. Demographic characteristics included patient age, sex, race/ethnicity (white, black, Hispanic, and other), and primary payer. Primary payer was classified based on the relative restrictiveness of insurance coverage and included 5 categories: (1) indemnity, preferred provider organizations (PPOs), and self-pay in full; (2) in-network health maintenance organizations and exclusive provider organizations; (3) Medicaid and self-pay charity; (4) Medicare fee-for-service; and (5) Medicare managed care.
Patient admission complexity was measured with 3 variables: admission SOI, admission risk of mortality (ROM), and the number of comorbidities present on admission. The number of comorbidities was based on the presence of the International Classification of Diseases, 9th Revision, Clinical Modification diagnosis codes using version 3.6 of the Agency for Healthcare Research and Quality’s comorbidity software.18 Admission SOI and ROM were determined using 3M’s all-patient refined diagnosis-related-group grouper, examining only diagnosis codes that were not present on admission. Patients were assigned to 1 of 4 categories (minor, moderate, major, and extreme) for each variable.
Hospital characteristics included geographic region—Northeast (23 hospitals), South (19 hospitals), Midwest (24 hospitals), and West (4 hospitals). In addition, a variable indicating whether the hospital was ranked in the top 20 on the cardiology and heart surgery specialty honor roll in the U.S. News & World Report 2011 Best-Hospitals list19 was included as another proxy for quality, since it has been shown to be associated with improved outcomes.20-23
SAS Enterprise Guide 4 and SAS version 9.2 (SAS Institute Inc, Cary, North Carolina) were used for data extraction from the Clinical Database and all statistical analyses. Chi-square tests were used to assess the correlation between
status as a domestic medical traveler and mortality and complications. One-way analysis of variance was used to test the association between status as a domestic medical traveler and LOS and direct costs. Binary logistic regression models were fit to test the relationship between DMT status and surgeon volume with mortality and complications, controlling for patient demographic characteristics, patient admission complexity, and hospital characteristics. Generalized linear regression models with gamma distributions and log link functions were fit to test the relationship between DMT status and surgeon volume with LOS and direct cost, controlling for patient demographic characteristics, patient admission complexity, and hospital characteristics.24
Institutional review board approval was obtained before beginning data collection, and no personal health information was used in this study.
The sample included 13,182 patients who underwent elective cardiac valve replacement or another major cardiothoracic procedure and were discharged from 70 hospitals between October 2009 and September 2010. There were 1399 travelers to HVSs (10.6%), 9275 nontravelers to HVSs (70.4%), and 2508 nontravelers to LVS (19.3%). shows the demographic characteristics, patient admission complexity, and hospital characteristics of the study population. Travelers had less severe admission SOI and ROM (P <.001) and fewer comorbidities than nontravelers. Across all patients, a larger proportion of patients traveling to HVSs were treated at cardiology honor roll hospitals (P <.001). Similarly, HVSs were more likely to practice at high-volume hospitals than were LVSs (P <.001; Table 1 and ).
Bivariate tests comparing clinical outcomes showed significant differences across the 3 groups (travelers to HVSs and nontravelers to HVSs and LVSs). The LOS for travelers to HVSs was 7.5 days (standard deviation, 4.9 days), compared with 8.5 days for nontravelers to HVSs and 9.9 days for nontravelers to LVSs (P <.001; Table 1). In-hospital mortality and complications showed similar patterns. Direct costs were significantly lower for patients treated by HVSs than for those treated by LVSs, and direct costs for nontravelers to HVSs were lower than those for travelers (P <.001; Table 1). The differences in payer distribution among the 3 groups are also noteworthy; a higher proportion of the traveler group (46%) was covered by an indemnity plan or otherwise less restrictive payer than the nontraveler groups (30% and 23%). Additionally, a much larger proportion of nontravelers to LVSs (24%)were covered by Medicaid or charity care than were patients treated by HVSs (4% and 8% for travelers and nontravelers,
respectively; Table 1).
and the eAppendix show results of the multivariable models predicting healthcare outcomes. After controlling for patient demographic and clinical factors and hospital characteristics, travelers to HVSs were 36% less likely to have a complication than patients treated by LVSs. There was no difference in mortality, LOS, or costs between travelers to HVSs and patients seen by LVSs. Compared with patients treated by LVSs, nontravelers to HVSs were less likely to have a complication and had shorter LOS and lower direct costs of care.
We then simulated the outcomes for the 3 travel designations (traveler to HVS, nontraveler to HVS, and nontraveler to LVS) for the modal characteristics of the sample: white, male, mean age 61.5 years, 2.19 complications, indemnity/PPO payer, South region of patient origin, Midwest region of care, major SOI/minor ROM, high-volume hospital, and cardiology honor roll status. reports the predicted outcomes by travel status, showing the magnitude of differences in outcomes for the modal patient characteristics. For the modal patient, travelers had the lowest risk of complications (3.7% vs 4.5% for nontravelers to HVSs and 5.6% for nontravelers to LVSs), but similar LOS and a slightly higher likelihood of mortality than nontravelers to HVSs. Travelers had shorter LOS and lower likelihood of mortality than nontravelers to LVSs.
The primary goals of this study were to characterize nonemergent patients who traveled outside of their home regions for elective cardiovascular procedures and to determine whether outcomes differed between patients who traveled and those who did not travel. We found differences in the types of patients who traveled outside of their home regions for care compared with those who sought care locally. Patients who traveled were more likely to be male and white, and to have a primary payer that covered a portion of care outside of their home region rather than a Medicaid-type program. Many state Medicaid programs have managed care plans that restrict the hospitals and surgeons included in the network, and 71% of Medicaid enrollees were in a managed care plan in 2008, which would limit where these patients can seek care.25 Even when a patient with such coverage has multiple surgeons to choose from within a geographic region, financial resources still dictate where they seek care and how far they can travel. The fact that patients with Medicaid coverage are disproportionately seen by lower-volume surgeons suggests a disparity in accessing high-quality care—a finding that demands further exploration.
Our results demonstrate that patients undergoing elective cardiovascular procedures performed by HVSs are less likely to have complications and more likely to have shorter hospital stays and lower direct costs of care. Patients who traveled for elective cardiovascular procedures had lower SOI and ROM scores and fewer comorbidities categories than those who did not travel, particularly compared with those treated by LVSs. More work is needed to determine whether these differences are due to urgency of care or lack of access (eg, restrictive innetwork health insurance coverage, limited financial resources to travel). Furthermore, our results demonstrate that socioeconomic status is an important predictor of who travels for care. If no HVS is available near an individual’s home, those without financial resources are unlikely to obtain the highest quality of care. This is an area of great concern, highlighting another potentially important disparity in access to high-quality care. Our results suggest that the logistical complexities of coordinating postdischarge care at a distance do not increase a patient’s LOS, contrary to our a priori hypothesis. There is some evidence, however, that travelers’ care is more resource intensive than that of their local counterparts. While their LOS was similar, travelers had higher direct costs of care than local patients, possibly because needed diagnostic information was not provided by the patient’s home physician or because presurgical testing normally performed in the outpatient setting was done after admission. Additional research is needed to understand the underlying drivers of the higher direct costs of care for DMT patients. Identification of these factors will allow providers to better coordinate care, increasing efficiency in the delivery of regionalized care.
We defined DMT as travel of more than 250 miles from one’s home region for medical care, reasoning that travel of this distance would likely require an overnight stay. The mean distance traveled, however, was 773 miles. A sensitivity analysis was used to test a different cutoff point—150 miles—instead of 250 miles as the definition of DMT, but the analysis did not produce results substantially different from thosefound using the original definition. Our definition of DMT did not take into account the availability of ther HVSs, so we were unable to distinguish between travel due to lack of access and travel in search of quality. More work is needed to determine whether this distinction should be included, as well as how patients decide whether and where to travel.
While patients with indemnity or PPO insurance coverage or who paid out of pocket in full for surgery were most likely to travel to an HVS, there is a growing business for payers and intermediaries negotiating with hospitals with high-volume physicians at the national level for particular types of care (eg, heart surgery, joint replacements) that include incentives for patients to travel to these providers. Intermediaries have begun working with insurers and employers to negotiate discounted rates for surgeries, with packages that include reduced or waived coinsurance payments and deductibles, covered travel costs for a patient’s companion, and other travel benefits. While the focus of these arrangements has been on reducing the costs of care, they ultimately require an equal focus on quality to produce sustained reductions in healthcare spending. The vast majority of patients (90%) who traveled were seen at the top cardiology and heart surgery hospitals, as identified by U.S. News and World Report’s annual rankings,19 suggesting that medical travelers actively seek out providers with a national reputation. Recent growth in consumer-driven health plans, which shift more of the decision making to the patient and encourage consumers to take a more active role in selecting physicians, signals a potential paradigm shift in the healthcare market. Our results suggest that patients should actively seek out high-volume providers and use this designation as a predictor of healthcare outcomes. The highvolume surgeon and hospital designations used in this study capture different components of the quality of care provided. Benefits provided by HVSs may be related to the surgeon’s technical skills and experience in performing cardiac surgery, while benefits associated with high-volume hospitals may be more closely related to the hospital’s nursing care and other environmental factors.
We have confirmed previous research showing that highvolume providers are associated with better outcomes5-8,11 for elective cardiovascular procedures, and expanded on previous work by determining that traveling outside of one’s home region does not negatively affect quality of care, at least for a subset of cardiovascular procedures. These findings support the notion that domestic travel to HVSs can result in better outcomes for elective cardiovascular care than being treated by local LVSs. Although travelers have higher hospital costs than patients seen locally by HVSs, more work is needed to understand the reasons for these differences, such as whether care is shifted from outpatient to inpatient settings for medical travelers and whether there are hidden costs associated with traveling for both the patient and the surgeon.
Although these results are important, the study has limitations. This study specifically evaluated outcomes for patients undergoing elective cardiovascular procedures such as heart valve replacement procedures and open and closed heart valvotomy procedures. Our results, therefore, might not be directly generalizable to other procedures. Future research should evaluate the relationship between travel distance, hospital and surgeon volume, and outcomes for patients undergoing other treatments such as other cardiovascular procedures, total hip and total knee arthroplasties, and cancer treatments, understanding that the cut points for defining high-volume versus low-volume hospitals and surgeons are likely to differ across treatments. Previous research has demonstrated a volume-outcome relationship for coronary-artery bypass graft procedures11 and cancer resections,11,13 amongothers; however, the association with travel distance has not been studied. Furthermore, although we defined a domestic medical traveler as one who travels more than 250 miles from his or her home residence, the definition of travel might also differ by the type of treatment. Nevertheless, these findings—including differences in the characteristics of patients who travel for care versus patients who obtain care locally and differences in resource intensity among travelers and nontravelers—provide a foundation for future work in this area of growing importance.
Because the data were retrieved from UHC’s Clinical Database, the study was restricted to surgeons practicing at AMCs. Therefore, the average patient volume per surgeon was likely higher than it would have been if community and other hospitals had been included. For this reason, our findings with regard to high- and low-volume providers cannot be directly applied to other studies, even though we followed a known methodology11,12 to examine the volume/outcome relationship.
Patients who travel outside of their home region for elective cardiovascular procedures are different from patients who receive care closer to home. In addition to having a lower severity of illness than nontravelers, the higher proportion of medical travelers with less restrictive health insurance coverage suggests that these patients are also likely to be of higher socioeconomic status. Our results demonstrate that patients who travel to an HVS for elective cardiovascular procedures have outcomes similar to, if not better than, those of patients who receive care locally from HVSs, with no increase in complications or LOS despite the potentially complex logistical arrangements required by DMT. These results provide preliminary evidence that DMT to high-volume, high-quality providers across the United States could be a potential strategy for improving the value of care provided for procedures such as elective heart surgery, but more work is needed to evaluate its full potential. For payers—private and public—facilitating access to the highest quality of care may lead to decreased need for costly and avoidable follow-up care in the future. For policy makers, DMT could be a mechanism for slowing the growth in healthcare spending for certain high-cost procedures like elective heart surgery. If DMT is proven to be successful in the private insurance market, the socioeconomic barriers preventing publicly insured patients from pursuing DMT would need to be addressed. Thinking strategically about where patients should be treated to promote the best results could increase the future value and efficiency of our currently fractured healthcare system. Author Affiliations: From UHC (JDL, SFH, SJM), Chicago, IL; Center for Health Management and Policy Research (TJJ), Department of Health Systems Management (SFH, SJM), Department of Health Systems Management (ANG), Rush University, Chicago, IL; National Center for Healthcare Leadership (ANG), Chicago, IL.
Funding Source: None.
Author Disclosures: The authors (JDL, TJJ, SFH, SJM, ANG) report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.
Authorship Information: Concept and design (JDL, TJJ, SFH, SJM, ANG); acquisition of data (JDL, SFH, SJM); analysis and interpretation of data (JDL, TJJ, SFH, SJM, ANG); drafting of the manuscript (JDL, TJJ); critical revision of the manuscript for important intellectual content (JDL,TJJ, SFH, SJM, ANG); statistical analysis (JDL, TJJ, SFH, SJM, ANG); administrative, technical, or logistic support (JDL, ANG); and supervision (TJJ, ANG).
Address correspondence to: Jacob D. Langley, MS-HSM, UHC, 155 North Wacker Dr, Chicago, IL 60606. E-mail: firstname.lastname@example.org. Wennberg JE. Understanding geographic variations in health care delivery. New Engl J Med. 1999;340(1):52-53.
2. Forgione DA, Smith PC. Medical tourism and its impact on the US health care system. J Health Care Finance. 2007;34(1):27-35.
3. Horowitz MD, Rosensweig JA, Jones CA. Medical tourism: globalization of the healthcare marketplace. MedGenMed. 2007;9(4):33.
4. Merritt MG Jr, Railey CJ, Levin SA, Crone RK. Involvement abroad of US academic health centers and major teaching hospitals: the developing landscape. Acad Med. 2008;83(6):541-549.
5. Birkmeyer JD, Stukel TA, Siewers AE, Goodney PP, Wennberg DE, Lucas FL. Surgeon volume and operative mortality in the United States. New Engl J Med. 2003;349(22):2117-2127.
6. Dimick JB, Pronovost PJ, Cowan JA Jr, Lipsett PA, Stanley JC, Upchurch GR Jr. Variation in postoperative complication rates after high-risk surgery in the United States. Surgery. 2003;134(4):534-540.
7. Flood AB, Scott WR, Ewy W. Does practice make perfect? part I: the relation between hospital volume and outcomes for selected diagnostic categories. Med Care. 1984;22(2):98-114.
8. Halm EA, Lee C, Chassin MR. Is volume related to outcome in health care? a systematic review and methodologic critique of the literature. Ann Intern Med. 2002;137(6):511-520.
9. The Cleveland Clinic. Lowe’s expands heart healthcare benefits with Cleveland Clinic [press release]. my.clevelandclinic.org/news/2010/lowes_expands_heart_healthcare_benefits.aspx. Published February 16, 2010. Accessed October 21, 2011.
10. Feldstein PJ. The emergence of market competition in the US health care system: its causes, likely structure, and implications. Health Policy. 1986;6(1):1-20.
11. Birkmeyer JD, Siewers AE, Finlayson EV, et al. Hospital volume and surgical mortality in the United States. New Engl J Med. 2002; 346(15):1128-1137.
12. Birkmeyer JD, Skinner JS, Wennberg DE. Will volume-based referral strategies reduce costs or just save lives? Health Aff (Millwood). 2002;21(5):234-241.
13. Birkmeyer JD, Sun Y, Wong SL, Stukel TA. Hospital volume and late survival after cancer surgery. Ann Surg. 2007;245(5):777-783.
14. Dudley RA, Johansen KL, Brand R, Rennie DJ, Milstein A. Selective referral to high-volume hospitals: estimating potentially avoidable deaths. JAMA. 2000;283(9):1159-1166.
15. Fong Y, Gonan M, Rubin D, Radzymer M, Brennan MF. Long-term survival is superior after resection for cancer in high-volume centers. Ann Surg. 2005;242(4):540-544.
16. Gordon TA, Burleyson GP, Tielsch JM, Cameron JL. The effects of regionalization on cost and outcome for one general high-risk surgical procedure. Ann Surg. 1995;221(1):43-49.
17. Luft HS, Bunker JP, Enthoven AC. Should operations be regionalized? the empirical relation between surgical volume and mortality. New Engl J Med. 1979;301(25):1364-1369.
18. Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8-27.
19. Best hospitals 2011. U.S. News and World Report. http://health.usnews.com/best-hospitals. Published July 18, 2011. Accessed October 21, 2011.
20. Osborne NH, Ghaferi AA, Nicholas LH, Dimick JB, Mph M. Evaluating popular media and internet-based hospital quality ratings for cancer surgery. Arch Surg. 2011;146(5):600-604.
21. Osborne NH, Nicholas LH, Ghaferi AA, Upchurch GR Jr, Dimick JB. Do popular media and internet-based hospital quality ratings identify hospitals with better cardiovascular surgery outcomes? J Am Coll Surg. 2010;210(1):87-92.
22. Wang OJ, Wang Y, Lichtman JH, Bradley EH, Normand ST, Krumholz HM. “America’s Best Hospitals” in the treatment of acute myocardial infarction. Arch Intern Med. 2007;167(13):1345-1351.
23. Chen J, Radford MJ, Wang Y, Marciniak TA, Krumholz HM. Do “America’s Best Hospitals” perform better for acute myocardial infarction? New Engl J Med. 1999;340(4):286-292.
24. Manning WG, Mullahy J. Estimating log models: to transform or not to transform? J Health Econ. 2001;20(4):461-494.
25. Kaiser Commission on Medicaid and the Uninsured. Medicaid and Managed Care: Key Data, Trends and Issues. Publication #8046. http://www.lindsayresnick.com/Resource_Link /KFF_Medicaid.pdf. February 2010. Accessed August 7, 2013.