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The American Journal of Managed Care October 2013
Dispensing Channel and Medication Adherence: Evidence Across 3 Therapy Classes
Reethi Iyengar, PhD, MBA, MHM; Rochelle Henderson, PhD, MPA; Jay Visaria, PhD, MPH; and Sharon Glave Frazee, PhD, MPH
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Zhannat Z. Nurgalieva, MD, PhD; Luisa Franzini, PhD; Robert O. Morgan, PhD; Sally W. Vernon, PhD; and Xianglin L. Du, MD, PhD
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Empirical Analysis of Domestic Medical Travel for Elective Cardiovascular Procedures
Jacob D. Langley, MS-HSM; Tricia J. Johnson, PhD; Samuel F. Hohmann, PhD, MS-HSM; Steve J. Meurer, PhD, MBA, MHS; and Andy N. Garman, PsyD
Physician Assistants in American Medicine: The Half-Century Mark
James F. Cawley, MPH, PA-C; and Roderick S. Hooker, PhD, PA
How Do Providers Prioritize Prevention? A Qualitative Study
Jeffrey L. Solomon, PhD; Allen L. Gifford, MD; Steven M. Asch, MD; Nora Mueller, MAA; Colin M. Thomas, MD; John M. Stevens, MD; and Barbara G. Bokhour, PhD
Outcomes Among Chronically Ill Adults in a Medical Home Prototype
David T. Liss, PhD; Paul A. Fishman, PhD; Carolyn M. Rutter, PhD; David Grembowski, PhD; Tyler R. Ross, MA; Eric A. Johnson, MS; and Robert J. Reid, MD, PhD
Performance Measurement for People With Multiple Chronic Conditions: Conceptual Model
Erin R. Giovannetti, PhD; Sydney Dy, MD; Bruce Leff, MD; Christine Weston, PhD; Karen Adams, PhD, MT; Tom B. Valuck, MD, JD; Aisha T. Pittman, MPH; Caroline S. Blaum, MD; Barbara A. McCann, MSW; and Cynthia M. Boyd, MD, MPH

Empirical Analysis of Domestic Medical Travel for Elective Cardiovascular Procedures

Jacob D. Langley, MS-HSM; Tricia J. Johnson, PhD; Samuel F. Hohmann, PhD, MS-HSM; Steve J. Meurer, PhD, MBA, MHS; and Andy N. Garman, PsyD
Promoting domestic medical travel to high-quality providers could improve clinical outcomes and reduce long-term healthcare costs.
Objectives: 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.

Study Design: Retrospective, cross-sectional analysis of patient discharge data from US academic medical centers.

Methods: 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.

Results: 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.

Conclusions: 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):825-832
Our 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:
  • Improve clinical outcomes.
  • Reduce the need for costly and avoidable follow-up care.
  • Reduce long-term healthcare costs and slow the growth in healthcare spending for certain high-cost procedures
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.

METHODS

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.

RESULTS

 
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