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Review |

Comparison of Mortality Between Private For-Profit and Private Not-For-Profit Hemodialysis Centers:  A Systematic Review and Meta-analysis FREE

P. J. Devereaux, MD; Holger J. Schünemann, MD, PhD; Nikila Ravindran, BSc; Mohit Bhandari, MD, MSc; Amit X. Garg, MD; Peter T.-L. Choi, MD, MSc; Brydon J. B. Grant, MD; Ted Haines, MD; Christina Lacchetti, MHSc; Bruce Weaver, MSc; John N. Lavis, MD, PhD; Deborah J. Cook, MD, MSc; David R. S. Haslam, MD, MSc; Terrence Sullivan, PhD; Gordon H. Guyatt, MD, MSc
[+] Author Affiliations

Author Affiliations: Departments of Medicine (Drs Devereaux, Cook, and Guyatt), Surgery (Dr Bhandari), Anesthesia (Dr Choi), Clinical Epidemiology and Biostatistics (Drs Choi, Haines, Lavis, Cook, and Guyatt, Ms Lacchetti, and Mr Weaver), and Psychiatry and Behavioral Neurosciences (Dr Haslam), McMaster University, Hamilton, Ontario; Departments of Medicine (Drs Schünemann and Grant), Physiology and Biophysics (Dr Grant), and Social and Preventive Medicine (Drs Schünemann and Grant), University at Buffalo, and Veterans Affairs Medical Center (Dr Grant), Buffalo, NY; Faculty of Medicine (Ms Ravindran) and Department of Health Policy Management and Evaluation (Dr Sullivan), University of Toronto, and Institute for Work and Health and Population Health Program, Canadian Institute for Advanced Research (Dr Lavis), Toronto, Ontario; and Division of Nephrology, University of Western Ontario, London (Dr Garg).


JAMA. 2002;288(19):2449-2457. doi:10.1001/jama.288.19.2449.
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Published online

Context Private for-profit and private not-for-profit dialysis facilities provide the majority of hemodialysis care in the United States. There has been extensive debate about whether the profit status of these facilities influences patient mortality.

Objective To determine whether a difference in adjusted mortality rates exists between hemodialysis patients receiving care in private for-profit vs private not-for-profit dialysis centers.

Data Sources We searched 11 bibliographic databases, reviewed our own files, and contacted experts in June 2001–January 2002. In June 2002, we also searched PubMed using the "related articles" feature, SciSearch, and the reference lists of all studies that fulfilled our eligibility criteria.

Study Selection We included published and unpublished observational studies that directly compared the mortality rates of hemodialysis patients in private for-profit and private not-for-profit dialysis centers and provided adjusted mortality rates. We masked the study results prior to determining study eligibility, and teams of 2 reviewers independently evaluated the eligibility of all studies. Eight observational studies that included more than 500 000 patient-years of data fulfilled our eligibility criteria.

Data Extraction Teams of 2 reviewers independently abstracted data on study characteristics, sampling method, data sources, and factors controlled for in the analyses. Reviewers resolved disagreements by consensus.

Data Synthesis The studies reported data from January 1, 1973, through December 31, 1997, and included a median of 1342 facilities per study. Six of the 8 studies showed a statistically significant increase in adjusted mortality in for-profit facilities, 1 showed a nonsignificant trend toward increased mortality in for-profit facilities, and 1 showed a nonsignificant trend toward decreased mortality in for-profit facilities. The pooled estimate, using a random-effects model, demonstrated that private for-profit dialysis centers were associated with an increased risk of death (relative risk, 1.08; 95% confidence interval, 1.04-1.13; P<.001). This relative risk suggests that there are annually 2500 (with a plausible range of 1200-4000) excessive premature deaths in US for-profit dialysis centers.

Conclusions Hemodialysis care in private not-for-profit centers is associated with a lower risk of mortality compared with care in private for-profit centers.

Figures in this Article

More than 20 years ago, Relman and Rennie1 suggested that profit status may affect dialysis practices. Advocates of private for-profit health care delivery argue that for-profit providers can deliver high-quality care more efficiently than not-for-profit providers.2 However, fears that for-profit facilities compromise quality of care to maintain shareholder returns3,4 have precipitated a heated debate about whether the profit status of hemodialysis facilities influences patient mortality.57

Separating issues of funding (ie, who will pay for the health care) and delivery (ie, who owns and administers the institutions providing care) helps to inform debates about health care systems. Both funding and delivery can occur through private or public means. Private funding or delivery can be for profit or not for profit. Private for-profit and private not-for-profit insurance companies use insurance premiums to pay for the health care of the patients they insure. Delivery of care can occur at private for-profit institutions that are owned by investors or at private not-for-profit institutions that are owned by communities, religious organizations, or philanthropic groups. Public funding indicates payment by the government, and public delivery indicates that a health care institution is owned and administered by the government. All public health care institutions are not for profit.

Since 1973, the US government has, through Medicare, funded the care of patients receiving dialysis.8 Currently in the United States, private for-profit (approximately 75%) and private not-for-profit (approximately 20%) facilities provide most hemodialysis care.9 Public institutions deliver the small remaining proportion of hemodialysis care.

Our study addresses issues of health care delivery, rather than health care funding. Accurate understanding of the impact of alternative health care delivery systems requires a systematic, comprehensive, and unbiased accumulation and summary of the available evidence. We therefore undertook a systematic review and meta-analysis to address the following question: what is the relative impact of private for-profit vs private not-for-profit delivery of hemodialysis care on patient mortality?

This systematic review is part of a series of reviews we are undertaking comparing health outcomes, appropriateness and quality of care, and costs in private for-profit and private not-for-profit health care institutions. We have previously reported on hospital mortality rates in private for-profit and private not-for-profit hospitals.10Figure 1 outlines the methodological steps for this systematic review. The Hamilton Health Sciences Research Ethics Board in Hamilton, Ontario, approved this study protocol.

Figure 1. Flowchart of Methodological Steps in the Systematic Review
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Data Sources

We undertook 6 strategies to identify potentially eligible studies. Our search included 11 electronic bibliographic databases, our own files, and contact with experts. We further searched PubMed using the "related articles" feature, SciSearch, and the reference lists of all studies that fulfilled our eligibility criteria.

A medical librarian used all the studies of which we were initially aware to identify Medical Subject Heading terms and key words for the search. In each database, the librarian undertook an iterative process to refine the search strategy through testing of several search terms and incorporation of new search terms as new relevant citations were identified. The search included the following databases: EMBASE (1980-2001), MEDLINE (1966-2001), HealthSTAR (1975-2001), CINAHL (1982-2001), BIOETHICSLINE (1973-2000), Wilson Business Abstracts (1997-2001), EconLit (1969-2001), Cochrane Library (2001, issue 3), Dissertation Abstracts Ondisc (1861-2001), ABI (Abstracted Business Information)/Inform (1970-2001), and NTIS (National Technical Information Service) (1964-2002). Complete descriptions of the database search strategies are available from the authors.

Study Selection

Eligibility Criteria. We included published and unpublished observational studies and randomized controlled trials that directly compared the mortality rates of hemodialysis patients in private for-profit and private not-for-profit dialysis centers. Eligible observational studies had to provide adjusted mortality rates or mortality rates from matched cases.

Screening Process. Our 6 search strategies identified 7045 unique citations. Teams consisting of 2 individuals independently screened the titles and abstracts of each citation and identified all citations for full review where there was any possibility that the study contained a comparison in which we were interested. This screening process yielded 779 full-text publications identified by one or both screeners for full review (Figure 1).

Assessment of Study Eligibility. We masked the results (ie, we obscured them from the tables and text using a black marker) of all publications selected for full review. To determine eligibility, teams of 2 reviewers independently evaluated masked articles that they had not assessed during the screening process. When disagreements occurred, the reviewers discussed the reasoning for their decisions, and if one reviewer realized she or he had made an error then the process was complete. This occurred in all cases of disagreement, and, therefore, plans for an independent review of cases of substantive disagreement proved unnecessary. Our agreement on study eligibility was excellent (κ = 0.91; 95% confidence interval [CI], 0.85-0.97).

Data Extraction

Teams of 2 reviewers independently abstracted the following data from all studies meeting eligibility criteria: sampling method, source of data (eg, administrative database, patient chart), type of dialysis facilities evaluated (ie, freestanding, hospital-based, or both), dates when data collection was initiated and completed, duration of patient follow-up, number of private for-profit and private not-for-profit dialysis facilities and patients evaluated, mortality, potential confounders adjusted for in the analyses, and the primary intent of the study (ie, to compare outcomes in private for-profit vs private not-for-profit dialysis facilities or other). Reviewers resolved disagreements by consensus using the process described earlier. Our overall agreement was 98% for data abstraction. We successfully contacted all authors to obtain missing data, and in all instances authors were able to provide all the information we requested.

Data Synthesis

Prior to undertaking this study, we considered it appropriate to adjust for the following factors: age, sex, race, income, education, cause of end-stage renal disease (eg, diabetes, hypertension, chronic glomerulonephritis), comorbid conditions (eg, cancer, congestive heart failure, coronary artery disease), number of years receiving dialysis, market share of the dialysis facility (ie, competition), and whether the dialysis facility was part of a multinational chain corporation. We considered it ideal if measurement of these factors, particularly comorbid conditions that could result from suboptimal dialysis (eg, hypertension), was undertaken when patients initiated dialysis treatments. We considered analyses to be overadjusted if the investigators adjusted for variables that were under the control of the facility administrators, could be influenced by profit status, and could possibly affect mortality. These variables included hemoglobin or hematocrit levels after June 1989 (when Medicare authorized reimbursement for erythropoietin11), duration of dialysis treatments, staffing levels (ie, number of staff per dialysis treatment), skill level of the dialysis staff (eg, aids/technicians vs registered nurses), quality of equipment, and reuse of dialyzers.

Our quality assessment of studies included whether the study appropriately adjusted for any of the factors listed herein and avoided overadjustment as described, as well as identification of the source of data (data from individual chart reviews was considered superior to data from administrative databases).

Prior to the analysis, we specified several hypotheses to explain variability (ie, heterogeneity) in the direction and magnitude of effect among studies. We hypothesized that the effect size may differ based on whether the primary intent of the study was to compare outcomes in private for-profit vs private not-for-profit dialysis facilities; whether the study was restricted to dialysis facilities that were freestanding, hospital-based, or included both types of institutions; whether there was adjustment for market competition; whether there was overadjustment for the variables described; and whether we had to compute a corrected relative risk (RR) using the methods proposed by Zhang and Yu (Box).12

Box. Computation of Relative Risks (RRs)

Only 1 of the studies included in our systematic review directly provided an RR.22 For the other studies, we had to convert some other measure of effect size to RR.

For 3 studies,16,20,21 we generated estimates of 2 × 2 (profit status × mortality) tables and used these to estimate ln(RR) and its variance. Plough et al16 reported information that enabled us to generate five 2 × 2 tables, 1 for each severity group. We used these tables to calculate an RR of 1-year mortality (private for-profit [PFP] relative to private not-for-profit [PNFP]) for each severity group; we then calculated a pooled estimate for the study using a meta-analytic method.13 Irvin20 reported a risk difference of 5.86%. McClellan et al21 provided a linear regression analysis from which we were able to infer a risk difference of 0.73%. For these studies, we generated patient-level 2 × 2 tables consistent with those risk differences.

The study by Garg et al18 used a Cox proportional hazards model with patient as the unit of analysis. In this case, we computed the RR at 1 year, using the following formula:
Graphic Jump LocationImage not available.
where HR = hazard ratio (PFP relative to PNFP) and pPNFP = death in PNFP units at 1 year.
Farley17 and the 2 remaining studies by Irvin19,23 used logistic regression, with patient as the unit of analysis. Because the death rates were greater than 10%, we could not use the coefficient for PFP relative to PNFP status as an estimate of ln(RR) because this can "exaggerate a risk association or treatment effect."12 Therefore, we computed the corrected RR (and confidence interval) using the method of Zhang and Yu,12 which yields an estimate that better represents the true RR:
Graphic Jump LocationImage not available.
where P0 is the proportion of PNFP patients who died. P0 was reported by Farley (19%),17 but for Irvin's studies,19,23 we had to use the overall proportions of patients who died (32.6% for Irvin19; 28.3% for Irvin23) as estimates of P0. These were overestimates, so the corrected RRs we used are conservative (ie, closer to a value of 1 than they would be with the correct proportions).

Two of our RR estimates are derived from analyses that were not reported in the original studies. We report these estimates for McClellan et al21 and Port et al22 based on models with public hemodialysis facilities excluded. In the latter case,22 profit status also had to be added to the model.

For each study, we computed the RR of mortality in private for-profit dialysis centers relative to private not-for-profit dialysis centers. Two independent reviewers blinded to the study results selected studies to pool in our primary pooled analysis on the basis of the following criteria: studies in which patients were likely to be included twice had to be separated in their time of enrollment by at least 2 years. For example, if one study completed enrollment on January 1, 1990, the next study could not begin enrolling before 1992. The purpose of this criterion was to limit the extent to which 2 studies used results from the same patients. If studies did have overlapping enrollment as described, the reviewers chose the largest study that adjusted for age, sex, race, and comorbidity (including diabetes). The reviewers independently agreed on which studies to pool in the primary meta-analysis.

We pooled these RRs using a random-effects model13 and tested for heterogeneity using a χ2 test. Data management and analysis were performed using SPSS software, version 11 (SPSS Inc, Chicago, Ill), and a meta-analysis program written by one of the authors (B.W.). We conducted a visual examination of funnel plots for evidence of publication bias.14,15

We identified 7 publications reporting 8 observational studies that met our eligibility criteria.1623 We also identified 12 publications that we believed might be eligible but required further information and/or data from the authors. After successfully contacting all authors, we confirmed that the majority of these studies had grouped private not-for-profit and public dialysis facilities together and that the authors either no longer had the data or could not rerun the analyses excluding the public institutions; these studies were excluded from our systematic review (Table 1).2435

Table Graphic Jump LocationTable 1. Excluded Publications Initially Thought to Be Possibly Eligible*

Table 2 presents the study characteristics and Table 3 presents the study methods of the 8 observational studies included in our systematic review. Table 3 lists the variables adjusted for in the analysis of each individual study. We successfully contacted all authors to clarify and obtain missing information. All studies were conducted in the United States and included data from January 1, 1973, through December 31, 1997. Three of the studies assessed only freestanding facilities and the remaining 5 evaluated both freestanding and hospital-based dialysis centers. The 8 studies included more than 500 000 patient-years of data and assessed a median of 1342 facilities per study. The most common duration of patient follow-up was 1 year.

Table Graphic Jump LocationTable 2. Characteristics of Studies Included in the Systematic Review*
Table Graphic Jump LocationTable 3. Methods of Studies Included in the Systematic Review*

Our quality assessment of studies revealed that all studies appropriately adjusted for many important determinants of mortality (including age, race, and cause of end-stage renal disease), 2 studies had overadjustments (including staffing levels and skill levels),17,21 and only 1 study obtained data from patient charts.18

Six studies showed a statistically significant increase in adjusted mortality in for-profit facilities,1720,22,23 1 showed a nonsignificant trend toward increased mortality in for-profit facilities,21 and 1 showed a nonsignificant trend toward decreased mortality in for-profit facilities (Figure 2).16

Figure 2. Relative Risk (RR) of Mortality in Hemodialysis Patients
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Our primary meta-analysis pooled 4 studies and demonstrated that private for-profit dialysis centers were associated with an increased risk of death (RR, 1.08; 95% CI, 1.04-1.13; P<.001) that, with the exception of 1 study, was highly consistent across studies (P = .08 for heterogeneity) (Figure 2).16,17,19,22 None of our predefined hypotheses to explain potential sources of heterogeneity demonstrated a statistically significant difference between the subgroup summary estimates. One study by Plough et al16 completely confounded profit status with whether facilities were freestanding or hospital-based (ie, the investigators compared private for-profit freestanding facilities with private not-for-profit hospital centers). For several reasons (see "Comment"), this very different study design could explain the difference in results across studies. The difference between the estimate of effect by Plough et al (RR, 0.71; 95% CI, 0.49-1.02)16 and those of the other 3 studies (RR, 1.09; 95% CI, 1.07-1.11)17,19,22 was statistically significant (P = .02). In the 3 unconfounded studies, the increased RR of 1.09 for mortality associated with care in a for-profit facility was significant (P<.001) and consistent (P = .50 for heterogeneity).17,19,22

We undertook 2 other sensitivity analyses that we planned a priori. Pooling the results of all 8 studies demonstrated that private for-profit dialysis facilities were associated with an increased risk of death (RR, 1.09; 95% CI, 1.05-1.12; P<.001; P = .004 for heterogeneity). Pooling the 3 studies that had restricted evaluation to freestanding dialysis units also demonstrated a statistically significant higher risk of death in private for-profit dialysis centers (RR, 1.11; 95% CI, 1.02-1.21; P = .02; P = .004 for heterogeneity).18,20,23 Funnel plots did not suggest publication bias.

Principal Findings

Our systematic review identified 8 studies that assessed adjusted mortality rates of hemodialysis patients in private for-profit and private not-for-profit dialysis centers. Six of the studies demonstrated a statistically significant increased risk of death in private for-profit dialysis facilities. Approximately 20% to 25% of US in-center hemodialysis patients die each year,36 and our meta-analysis found a pooled RR of death of 8%, suggesting that private for-profit dialysis facilities may be responsible for a substantial number of excess deaths.

Strengths and Weaknesses of This Review

We are unaware of any prior systematic reviews or meta-analyses that have compared mortality rates of hemodialysis patients in private for-profit and private not-for-profit dialysis facilities. We undertook a very broad search to identify studies for our systematic review. We masked study results prior to determining study eligibility. We conducted all review procedures in duplicate and demonstrated a high degree of agreement in our eligibility decisions, data abstraction, and meta-analysis decisions. Our search identified 8 eligible observational studies with large sample sizes. We were successful in confirming and obtaining information from authors. In summary, our systematic review of these observational studies is methodologically rigorous37 and transparently reported.38

Our systematic review has several limitations. We did not identify any randomized controlled trials. However, since it is unlikely that patients will ever be randomized to private for-profit and private not-for-profit health care delivery systems, the large studies in our systematic review represent the strongest feasible study design (ie, observational studies with adjustment for potential confounders) for answering our question. All included studies adjusted for age, race, and cause of end-stage renal disease. The last variable also provided some adjustment for comorbidity (eg, diabetes and hypertension).

Adjustment based on data from administrative databases is limited by the comprehensiveness and quality of the data. Careful data abstraction from individual patient charts represents a superior approach to account for important clinical confounders, particularly related to comorbidity. Only 1 study used data abstracted from individual patient charts; this study demonstrated the largest increase in mortality (RR increase of 18%).18

Another limitation of our systematic review was that in studies that combined private not-for-profit facilities with public facilities, many authors either did not have the data any longer or could not rerun analyses without data from the public dialysis facilities. However, 2 authors did rerun their analyses to remove the public institutions, and the results strengthened our systematic review.21,22

Pooling data from private not-for-profit and public dialysis centers is questionable. Theoretical reasons for potential differences in outcomes between public hospitals and private not-for-profit hospitals that provide dialysis include the public hospitals' funding disadvantage and the possibility that public hospitals use some of the funds they receive for dialysis to help subsidize the care of other patients within their institutions.

For those who consider it appropriate to pool private and public not-for-profit institutions, the results of the majority of studies that combined these 2 types of facilities support the results of our systematic review. Seven of these 13 studies (including 2 very large US Renal Data System [USRDS] studies) demonstrated a statistically significant lower risk of death in not-for-profit dialysis centers compared with private for-profit centers,3033 and 4 demonstrated a trend favoring not-for-profit centers (Table 1).24,27,32 In contrast, only 2 of these 13 studies demonstrated a statistically significant lower risk of death in patients receiving dialysis care in private for-profit hospitals compared with not-for-profit hospitals,30 and 2 others demonstrated trends in favor of for-profit facilities (Table 1).35 The 1 publication with 2 studies that showed a statistically significant result in favor of for-profit facilities was restricted to hospitals. Furthermore, they were the only 2 studies that restricted their samples to dialysis units with less than 25% of patients with high-efficiency/high-flux dialysis, and included an overadjustment for reuse of dialyzers.30

Although formal tests of heterogeneity may lack power, aside from 1 study by Plough et al,16 the results of eligible studies are very consistent (Figure 2), strengthening the inferences from this systematic review. The results of Plough et al raise challenges in interpretation because profit status was completely confounded with hospital and freestanding facilities (the authors compared private for-profit freestanding facilities with private not-for-profit hospital-based centers). Hospital-based hemodialysis may be associated with higher mortality than dialysis in freestanding facilities, irrespective of profit status.24

Significance of This Systematic Review

Our systematic review demonstrated an increased risk of death in private for-profit dialysis centers (RR, 1.08; 95% CI, 1.04-1.13). Several studies have demonstrated mechanisms through which this increased risk of death may be occurring. Studies (including 1 in our systematic review) have demonstrated that private for-profit dialysis centers employ fewer personnel per dialysis run and less-highly skilled personnel (ie, more licensed practical nurses, aids, and technicians compared with registered nurses).17,27,39 Other studies have also demonstrated that patients at private for-profit dialysis facilities have shorter durations of dialysis treatment.27,28 Shorter durations of dialysis treatment are associated with higher mortality.27,28

In a health care system in which funding is relatively fixed, as with dialysis care in the United States, the private for-profit facilities face a difficult economic challenge. Shareholders expect 10% to 15% returns on their investments3 and taxes may account for 5% to 6% of total expenses.40 Private for-profit facilities must generate these profits and pay taxes while endeavoring to provide the same quality care as private not-for-profit centers that are free of these expenses. Given that nurse and technician wages account for approximately 70% of total dialysis costs, it is understandable that private for-profit centers may try to minimize staff and the skill (and, thus, reimbursement) level of staff.17,27,39

How many deaths might realistically be avoided if private not-for-profit facilities delivered all dialysis care in the United States? There are approximately 208 000 patients receiving in-center hemodialysis in the United States each year, of whom approximately 75% receive their dialysis in for-profit facilities.9 Making a conservative estimate of the proportion who die each year, 20%,36 and using our pooled estimate of an 8% (95% CI, 4%-13%) relative increase in mortality in for-profit facilities, one can estimate that were these patients to receive their dialysis in private not-for-profit facilities, approximately 2500 deaths (range, 1200-4000) could be avoided each year.

Many countries face choices about the optimal methods of health care delivery. For instance, Canada is currently undergoing intense debate concerning the relative merits of private for-profit vs private not-for-profit health care delivery. Our results suggest the inadvisability of introducing private for-profit dialysis centers into the Canadian health care system.

A previous systematic review suggested that private for-profit hospitals increase mortality relative to private not-for-profit hospitals.10 Together with the results of this review, these data provide compelling evidence that profit status can have an important impact on the outcomes of medical care.

Relman AS, Rennie D. Treatment of end-stage renal disease: free but not equal.  N Engl J Med.1980;303:996-998.
Hassan MM. Let's end the nonprofit charade.  N Engl J Med.1996;334:1055-1057.
Nudelman PM, Andrews LM. The "values added" of not-for-profit health plans.  N Engl J Med.1996;334:1057-1059.
Woolhandler S, Himmelstein DU. When money is the mission—the high costs of investor-owned care.  N Engl J Med.1999;341:444-446.
Garg PP, Powe NR. Profit-making in the treatment of chronic kidney disease: truth and consequences.  Semin Dial.2001;14:153-156.
Bander SJ, Hakim R, Lazarus MJ, Lindenfeld S. The for-profit providers.  Nephrol News Issues.2000;14:13-15.
Nissenson AR, Owen Jr WF. Ownership of dialysis facilities and patients' survival.  N Engl J Med.2000;342:1054-1055.
Meyer KB, Kassirer JP. Squeezing more cost and care out of dialysis: our patients would pay the price.  Am J Med.2002;112:232-234.
US Renal Data System.  USRDS 2001 Annual Data Report: Atlas of End-Stage Renal Disease in the United StatesBethesda, Md: National Institute of Diabetes and Digestive and Kidney Diseases; 2001.
Devereaux PJ, Choi PT-L, Lacchetti C.  et al.  A systematic review and meta-analysis of studies comparing mortality rates of private for-profit and private not-for-profit hospitals.  CMAJ.2002;166:1399-1406.
De Lissovoy G, Powe NR, Griffiths RI.  et al.  The relationship of provider organizational status and erythropoietin dosing in end stage renal disease patients.  Med Care.1994;32:130-140.
Zhang J, Yu KF. What's the relative risk? a method of correcting the odds ratio in cohort studies of common outcomes.  JAMA.1998;280:1690-1691.
Fleiss JL. The statistical basis of meta-analysis.  Stat Methods Med Res.1993;2:121-145.
Egger M, Davey Smith G. Misleading meta-analysis: lessons from "an effective, safe, simple" intervention that wasn't.  BMJ.1995;310:752-754.
Copas JB, Shi JQ. A sensitivity analysis for publication bias in systematic reviews.  Stat Methods Med Res.2001;10:251-265.
Plough AL, Salem SR, Shwartz M, Weller JM, Ferguson CW. Case mix in end-stage renal disease: differences between patients in hospital-based and free-standing treatment facilities.  N Engl J Med.1984;310:1432-1436.
Farley DO. Effects of Competition on Dialysis Facility Service Levels and Patient Selection [dissertation]. Santa Monica, Calif: RAND; 1993.
Garg PP, Frick KD, Diener-West M, Powe NR. Effect of the ownership of dialysis facilities on patients' survival and referral for transplantation.  N Engl J Med.1999;341:1653-1660.
Irvin RA. Ownership and mortality in the dialysis industry: multivariate regression analysis. In: Irvin RA. Quality of Care, Asymmetric Information, and Patient Outcomes in US For-Profit and Not-For-Profit Renal Dialysis Facilities [dissertation]. St Louis, Mo: Washington University; 1988:55-80.
Irvin RA. Ownership and mortality in the dialysis industry: propensity score analysis. In: Irvin RA. Quality of Care, Asymmetric Information, and Patient Outcomes in US For-Profit and Not-For-Profit Renal Dialysis Facilities [dissertation]. St Louis, Mo: Washington University; 1988:81-107.
McClellan WM, Soucie JM, Flanders WD. Mortality in end-stage renal disease is associated with facility-to-facility differences in adequacy of hemodialysis.  J Am Soc Nephrol.1998;9:1940-1947.
Port FK, Wolfe RA, Held PJ. Ownership of dialysis facilities and patients' survival.  N Engl J Med.2000;342:1053-1054.
Irvin RA. Quality of care differences by ownership in United States renal dialysis facilities.  ASAIO J.2000;46:775-778.
Held PJ, Pauly MV, Diamond L. Survival analysis of patients undergoing dialysis.  JAMA.1987;257:645-650.
Schlesinger M, Cleary PD, Blumenthal D. The ownership of health facilities and clinical decisionmaking: the case of the ESRD industry.  Med Care.1989;27:244-258.
Held PJ, Pauly MV, Bovbjerg RR, Newmann J, Salvatierra Jr O. Access to kidney transplantation: has the United States eliminated income and racial differences?  Arch Intern Med.1988;148:2594-2600.
Held PJ, Garcia JR, Pauly MV, Cahn MA. Price of dialysis, unit staffing, and length of dialysis treatments.  Am J Kidney Dis.1990;15:441-450.
Held PJ, Levin NW, Bovbjerg RR, Pauly MV, Diamond LH. Mortality and duration of hemodialysis treatment.  JAMA.1991;265:871-875.
Held PJ, Wolfe RA, Gaylin DS, Port FK, Levin NW, Turenne MN. Analysis of the association of dialyzer reuse practices and patient outcomes.  Am J Kidney Dis.1994;23:692-708.
Collins AJ, Ma JZ, Constantini EG, Everson SE. Dialysis unit and patient characteristics associated with reuse practices and mortality: 1989-1993.  J Am Soc Nephrol.1998;9:2108-2117.
US Renal Data System.  USRDS 1996 Annual Data Report: Atlas of End-Stage Renal Disease in the United StatesBethesda, Md: National Institute of Diabetes and Digestive and Kidney Diseases; 1996.
Ebben JP, Dalleska F, Ma JZ, Everson SE, Constantini EG, Collins AJ. Impact of disease severity and hematocrit level on reuse-associated mortality.  Am J Kidney Dis.2000;35:244-249.
US Renal Data System.  USRDS 1997 Annual Data Report: Atlas of End-Stage Renal Disease in the United StatesBethesda, Md: National Institute of Diabetes and Digestive and Kidney Diseases; 1997.
Port FK, Wolfe RA, Hulbert-Shearon TE.  et al.  Mortality risk by hemodialyzer reuse practice and dialyzer membrane characteristics: results from the USRDS dialysis morbidity and mortality study.  Am J Kidney Dis.2001;37:276-286.
McCullough KP, Held PJ, Gillespie BW, Young EW, Bragg JL, Port FK. Survival among dialysis patients in for-profit and not-for-profit hemodialysis (HD) facilities [abstract].  ASAIO J.2001;47:158.
US Renal Data System.  USRDS 1999 Annual Data Report: Atlas of End-Stage Renal Disease in the United StatesBethesda, Md: National Institute of Diabetes and Digestive and Kidney Diseases; 1999.
Oxman A, Guyatt G, Cook D, Montori V. Summarizing the evidence. In: Guyatt G, Rennie DI. Users' Guides to the Medical Literature. Chicago, Ill: AMA Press; 2002:155-176.
Stroup DF, Berlin JA, Morton SC.  et al.  Meta-analysis of observational studies in epidemiology: a proposal for reporting.  JAMA.2000;283:2008-2012.
Hirth RA, Chernew ME, Orzol SM. Ownership, competition, and the adoption of new technologies and cost-saving practices in a fixed-price environment.  Inquiry.2000;37:282-294.
Friedman BS, Hattis PA, Bogue RJ. Tax exemption and community benefits of not-for-profit hospitals.  Adv Health Econ Health Serv Res.1990;11:131-158.

Figures

Figure 1. Flowchart of Methodological Steps in the Systematic Review
Graphic Jump Location
Figure 2. Relative Risk (RR) of Mortality in Hemodialysis Patients
Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Excluded Publications Initially Thought to Be Possibly Eligible*
Table Graphic Jump LocationTable 2. Characteristics of Studies Included in the Systematic Review*
Table Graphic Jump LocationTable 3. Methods of Studies Included in the Systematic Review*

References

Relman AS, Rennie D. Treatment of end-stage renal disease: free but not equal.  N Engl J Med.1980;303:996-998.
Hassan MM. Let's end the nonprofit charade.  N Engl J Med.1996;334:1055-1057.
Nudelman PM, Andrews LM. The "values added" of not-for-profit health plans.  N Engl J Med.1996;334:1057-1059.
Woolhandler S, Himmelstein DU. When money is the mission—the high costs of investor-owned care.  N Engl J Med.1999;341:444-446.
Garg PP, Powe NR. Profit-making in the treatment of chronic kidney disease: truth and consequences.  Semin Dial.2001;14:153-156.
Bander SJ, Hakim R, Lazarus MJ, Lindenfeld S. The for-profit providers.  Nephrol News Issues.2000;14:13-15.
Nissenson AR, Owen Jr WF. Ownership of dialysis facilities and patients' survival.  N Engl J Med.2000;342:1054-1055.
Meyer KB, Kassirer JP. Squeezing more cost and care out of dialysis: our patients would pay the price.  Am J Med.2002;112:232-234.
US Renal Data System.  USRDS 2001 Annual Data Report: Atlas of End-Stage Renal Disease in the United StatesBethesda, Md: National Institute of Diabetes and Digestive and Kidney Diseases; 2001.
Devereaux PJ, Choi PT-L, Lacchetti C.  et al.  A systematic review and meta-analysis of studies comparing mortality rates of private for-profit and private not-for-profit hospitals.  CMAJ.2002;166:1399-1406.
De Lissovoy G, Powe NR, Griffiths RI.  et al.  The relationship of provider organizational status and erythropoietin dosing in end stage renal disease patients.  Med Care.1994;32:130-140.
Zhang J, Yu KF. What's the relative risk? a method of correcting the odds ratio in cohort studies of common outcomes.  JAMA.1998;280:1690-1691.
Fleiss JL. The statistical basis of meta-analysis.  Stat Methods Med Res.1993;2:121-145.
Egger M, Davey Smith G. Misleading meta-analysis: lessons from "an effective, safe, simple" intervention that wasn't.  BMJ.1995;310:752-754.
Copas JB, Shi JQ. A sensitivity analysis for publication bias in systematic reviews.  Stat Methods Med Res.2001;10:251-265.
Plough AL, Salem SR, Shwartz M, Weller JM, Ferguson CW. Case mix in end-stage renal disease: differences between patients in hospital-based and free-standing treatment facilities.  N Engl J Med.1984;310:1432-1436.
Farley DO. Effects of Competition on Dialysis Facility Service Levels and Patient Selection [dissertation]. Santa Monica, Calif: RAND; 1993.
Garg PP, Frick KD, Diener-West M, Powe NR. Effect of the ownership of dialysis facilities on patients' survival and referral for transplantation.  N Engl J Med.1999;341:1653-1660.
Irvin RA. Ownership and mortality in the dialysis industry: multivariate regression analysis. In: Irvin RA. Quality of Care, Asymmetric Information, and Patient Outcomes in US For-Profit and Not-For-Profit Renal Dialysis Facilities [dissertation]. St Louis, Mo: Washington University; 1988:55-80.
Irvin RA. Ownership and mortality in the dialysis industry: propensity score analysis. In: Irvin RA. Quality of Care, Asymmetric Information, and Patient Outcomes in US For-Profit and Not-For-Profit Renal Dialysis Facilities [dissertation]. St Louis, Mo: Washington University; 1988:81-107.
McClellan WM, Soucie JM, Flanders WD. Mortality in end-stage renal disease is associated with facility-to-facility differences in adequacy of hemodialysis.  J Am Soc Nephrol.1998;9:1940-1947.
Port FK, Wolfe RA, Held PJ. Ownership of dialysis facilities and patients' survival.  N Engl J Med.2000;342:1053-1054.
Irvin RA. Quality of care differences by ownership in United States renal dialysis facilities.  ASAIO J.2000;46:775-778.
Held PJ, Pauly MV, Diamond L. Survival analysis of patients undergoing dialysis.  JAMA.1987;257:645-650.
Schlesinger M, Cleary PD, Blumenthal D. The ownership of health facilities and clinical decisionmaking: the case of the ESRD industry.  Med Care.1989;27:244-258.
Held PJ, Pauly MV, Bovbjerg RR, Newmann J, Salvatierra Jr O. Access to kidney transplantation: has the United States eliminated income and racial differences?  Arch Intern Med.1988;148:2594-2600.
Held PJ, Garcia JR, Pauly MV, Cahn MA. Price of dialysis, unit staffing, and length of dialysis treatments.  Am J Kidney Dis.1990;15:441-450.
Held PJ, Levin NW, Bovbjerg RR, Pauly MV, Diamond LH. Mortality and duration of hemodialysis treatment.  JAMA.1991;265:871-875.
Held PJ, Wolfe RA, Gaylin DS, Port FK, Levin NW, Turenne MN. Analysis of the association of dialyzer reuse practices and patient outcomes.  Am J Kidney Dis.1994;23:692-708.
Collins AJ, Ma JZ, Constantini EG, Everson SE. Dialysis unit and patient characteristics associated with reuse practices and mortality: 1989-1993.  J Am Soc Nephrol.1998;9:2108-2117.
US Renal Data System.  USRDS 1996 Annual Data Report: Atlas of End-Stage Renal Disease in the United StatesBethesda, Md: National Institute of Diabetes and Digestive and Kidney Diseases; 1996.
Ebben JP, Dalleska F, Ma JZ, Everson SE, Constantini EG, Collins AJ. Impact of disease severity and hematocrit level on reuse-associated mortality.  Am J Kidney Dis.2000;35:244-249.
US Renal Data System.  USRDS 1997 Annual Data Report: Atlas of End-Stage Renal Disease in the United StatesBethesda, Md: National Institute of Diabetes and Digestive and Kidney Diseases; 1997.
Port FK, Wolfe RA, Hulbert-Shearon TE.  et al.  Mortality risk by hemodialyzer reuse practice and dialyzer membrane characteristics: results from the USRDS dialysis morbidity and mortality study.  Am J Kidney Dis.2001;37:276-286.
McCullough KP, Held PJ, Gillespie BW, Young EW, Bragg JL, Port FK. Survival among dialysis patients in for-profit and not-for-profit hemodialysis (HD) facilities [abstract].  ASAIO J.2001;47:158.
US Renal Data System.  USRDS 1999 Annual Data Report: Atlas of End-Stage Renal Disease in the United StatesBethesda, Md: National Institute of Diabetes and Digestive and Kidney Diseases; 1999.
Oxman A, Guyatt G, Cook D, Montori V. Summarizing the evidence. In: Guyatt G, Rennie DI. Users' Guides to the Medical Literature. Chicago, Ill: AMA Press; 2002:155-176.
Stroup DF, Berlin JA, Morton SC.  et al.  Meta-analysis of observational studies in epidemiology: a proposal for reporting.  JAMA.2000;283:2008-2012.
Hirth RA, Chernew ME, Orzol SM. Ownership, competition, and the adoption of new technologies and cost-saving practices in a fixed-price environment.  Inquiry.2000;37:282-294.
Friedman BS, Hattis PA, Bogue RJ. Tax exemption and community benefits of not-for-profit hospitals.  Adv Health Econ Health Serv Res.1990;11:131-158.
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