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CMAJ. Jun 8, 2004; 170(12): 1817–1824.
PMCID: PMC419772

Payments for care at private for-profit and private not-for-profit hospitals: a systematic review and meta-analysis

Abstract

Background

It has been shown that patients cared for at private for-profit hospitals have higher risk-adjusted mortality rates than those cared for at private not-for-profit hospitals. Uncertainty remains, however, about the economic implications of these forms of health care delivery. Since some policy-makers might still consider for-profit health care if expenditure savings were sufficiently large, we undertook a systematic review and meta-analysis to compare payments for care at private for-profit and private not-for-profit hospitals.

Methods

We used 6 search strategies to identify published and unpublished observational studies that directly compared the payments for care at private for-profit and private not-for-profit hospitals. We masked the study results before teams of 2 reviewers independently evaluated the eligibility of all studies. We confirmed data or obtained additional data from all but 1 author. For each study, we calculated the payments for care at private for-profit hospitals relative to private not-for-profit hospitals and pooled the results using a random effects model.

Results

Eight observational studies, involving more than 350 000 patients altogether and a median of 324 hospitals each, fulfilled our eligibility criteria. In 5 of 6 studies showing higher payments for care at private for-profit hospitals, the difference was statistically significant; in 1 of 2 studies showing higher payments for care at private not-for-profit hospitals, the difference was statistically significant. The pooled estimate demonstrated that private for-profit hospitals were associated with higher payments for care (relative payments for care 1.19, 95% confidence interval 1.07–1.33, p = 0.001).

Interpretation

Private for-profit hospitals result in higher payments for care than private not-for-profit hospitals. Evidence strongly supports a policy of not-for-profit health care delivery at the hospital level.

Separating issues of funding (i.e., who pays for health care) and delivery (i.e., who owns and administers the institutions providing care) helps to inform debates about health care systems. Funding for health care can come through private sources, primarily administered through insurance companies, or through public payment, by governments using tax dollars. Care can be delivered at private for-profit institutions that are owned by investors; private not-for-profit institutions that are owned by communities, religious organizations or philanthropic groups; or public health care institutions owned and administered by the government.

Canadian hospitals are publicly funded. In terms of delivery, although they are commonly referred to as public institutions, Canadian hospitals are almost all owned and operated by private not-for-profit organizations.1 Canadian policy-makers continue to consider an expansion of private for-profit health care delivery, including private for-profit hospitals.1

We have previously demonstrated higher risk-adjusted death rates among patients receiving care at private for-profit hospitals than among patients at private not-for-profit hospitals in a comprehensive systematic review.2 Uncertainty remains, however, about the economic implications of these forms of health care delivery. Studies evaluating the economics of health care delivery usually evaluate costs, charges or payments for care.3 From the perspective of a service provider, costs represent how much the provider paid to provide care, charges represent how much the provider billed the payer, and payments represent how much the provider received for the care received. In the context of publicly funded health care, the central policy question is how much government will pay for care delivered by private for-profit versus private not-for-profit providers. We therefore undertook a systematic review and meta-analysis to address the following question: is there a difference in payments for patient care received at private for-profit compared with private not-for-profit hospitals?

Methods

We included published and unpublished observational studies and randomized controlled trials that directly compared payments for care at private for-profit and private not-for-profit hospitals. Because we required an estimate of variance to determine the precision of the estimate of the relative payments and to combine studies in our meta-analysis, we excluded from the quantitative meta-analysis studies that did not report (or whose authors could not provide) an estimate of variance for the payments.

Strategies to identify studies included an electronic search of 11 bibliographical databases; consultation with experts; review of our own files; review of reference lists from articles fulfilling our eligibility criteria; use of the “see related articles” feature in PubMed (in June 2003) for publications fulfilling our eligibility criteria; and use of SciSearch (in June 2003) for publications fulfilling 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 iteratively refined the search strategy through testing several search terms and incorporating 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/Inform (1970–2001) and NTIS (National Technical Information Service) (1964–2002). The database search strategies are described in online Appendix 1 (www.cmaj.ca/cgi/content/full/170/12/1817/DC1).

Our 6 search strategies identified 7535 unique citations. Ten teams of 2 people independently screened the titles and abstracts of each citation and identified all citations that might contain a comparison of interest. This process yielded 788 full-text publications, identified by either screener, which we selected for full review (Fig. 1).

figure 34FF1
Fig. 1: Methodological steps of our systematic review.

We masked the results by blacking them out in the tables and text of all publications selected for full review. To determine eligibility, 10 teams of 2 reviewers independently evaluated masked articles that they had not assessed during the screening process. The kappa value for agreement on article eligibility was 0.75. The consensus process to resolve disagreements required reviewers to discuss the reasoning for their decisions; in all cases, a realization of error by 1 reviewer completed the process. When both reviewers were uncertain as to whether a study was eligible, we contacted the author to clarify information.

Two reviewers independently abstracted the following data from all studies meeting eligibility criteria: sampling method, source of data, case mix, type of hospitals evaluated (e.g., general acute care, psychiatric), dates when data collection was initiated and completed, duration of patient follow-up, number of hospitals and patients evaluated, patient source of payment (e.g., public, private insurance) and potential confounders adjusted for in the analyses. Reviewers resolved disagreements by consensus using the process described above. Our overall agreement was 89% for the data abstraction. We attempted to contact the authors of all eligible studies to obtain or confirm data.

Before undertaking this systematic review we considered studies methodologically strong if they adjusted for the following factors: age, sex, ethnicity, income, education, primary diagnosis (case mix), comorbid conditions, severity of illness, market competition (the concentration of hospitals in a region), patient source of payment and hospital teaching status. We also considered analyses to be overadjusted if investigators adjusted for a variable that was under the control of hospital administrators, could vary by profit status and could possibly affect payments for care. For example, we considered an analysis overadjusted if it adjusted for staffing levels or the skill level of the hospital staff. Our quality assessment of studies included whether the study appropriately adjusted for any of the factors listed above and avoided overadjustment.

Before the analysis, we specified several hypotheses to explain variability in the direction and magnitude of effect across studies. We hypothesized that the effect size may differ depending on whether the hospitals evaluated were specialty or general hospitals; whether the payments for care were per discharge or per day; whether the payments for care were related to the hospital stay or included a period of time after hospital discharge; whether the analysis adjusted for potential confounders or was unadjusted; whether the patient source of payment was public or mixed (public and private); whether the patient population was adult or pediatric; and whether the data collection occurred before 1984 (when US Medicare switched from reimbursement based on the costs of care to reimbursement based on a patient's diagnosis).

For each study we computed the relative payments for care at private for-profit hospitals relative to private not-for-profit hospitals (see online Appendix 2 at www.cmaj.ca/cgi/content/full/170/12/1817/DC2). If a study reported 2 or more analyses with variance data, we included the adjusted analysis over an unadjusted analysis, and the analysis based on payments per discharge over that based on payments per day. We pooled these relative payments for care using a random effects model4 by weighting the natural logarithm of the relative payments by the inverse of their variances. Relative to the fixed effects model, the random effects model allows for between-study variation in the effect measure in addition to within-study variation. The random effects model generally results in wider confidence intervals than the fixed effects model. Although the random effects model still gives greater weight to studies with smaller variance than to studies with larger variance, the relative weight assigned to large studies is reduced compared with the weight assigned to those studies in the fixed effects model.

We calculated an I2 as a measure of heterogeneity for the main analysis. An I2 value represents the percentage of total variation across studies that is caused by heterogeneity rather than by chance. We considered a low I2 value as 25% or lower and a high I2 value as 75% or higher.5 We conducted a visual examination of funnel plots for evidence of publication bias.6

The Hamilton Health Sciences Research Ethics Board in Hamilton, Ontario approved the study protocol.

Results

We identified 8 publications of observational studies that met our eligibility criteria.7,8,9,10,11,12,13,14We also identified 10 publications that we believed might be eligible but which required additional data from the authors. We were able to contact 9 of the 10 authors and to confirm that 6 of these studies had no measure of variance, 3 grouped private not-for-profit and public not-for-profit hospitals together and the authors either no longer had the data or could not rerun the analyses excluding the public hospitals, and 1 study had data on charges for care and did not have data on payments for care; these 10 studies were excluded from our systematic review (Table 1).15,16,17,18,19,20,21,22,23,24 All 10 excluded studies found higher payments or charges for care at private for-profit hospitals than at not-for-profit hospitals; in 6 of the 10, the differences were statistically significant.15,16,17,21,22,24

Table thumbnail
Table 1

Table 2 presents the study characteristics and Table 3 the study methodology of the 8 observational studies included in our systematic review. We obtained or confirmed data with the investigators for 7 studies; the sole author of the remaining study had died.8 All studies were conducted in the United States and included data from 1980 until Dec. 31, 1994. The 8 studies included over 350 000 patients and assessed a median of 324 hospitals per study.

Table thumbnail
Table 3
Table thumbnail
Table 2

Our quality assessment of studies revealed that 6 of the 8 studies appropriately adjusted or matched cases for many important determinants of payment for care (e.g., case mix). For 2 studies the authors were unable to provide an estimate of variance for their adjusted analyses, which we required to combine studies in our meta-analysis; instead, we report their unadjusted analyses for which there was an estimate of variance.7,9 The statistical significance of the findings of these 2 studies did not change between the unadjusted and adjusted analyses.7,9

Five of the 8 studies showed statistically significant higher payments for care at private for-profit hospitals,9,11,12,13,14 1 showed statistically significant lower payments for care at private for-profit hospitals,8 1 showed a nonsignificant trend toward higher payments for care at private for-profit hospitals7 and 1 showed a nonsignificant trend toward lower payments for care at private for-profit hospitals (Fig. 2).10 Funnel plots did not suggest publication bias.

figure 34FF2
Fig. 2: Relative payments for care at private for-profit (PFP) and private not-for-profit (PNFP) hospitals. Note: CI = confidence interval. *The studies are in chronological order by midpoint of the data collection period. †Approximation from ...

Our primary meta-analysis demonstrated that private for-profit hospitals were associated with higher payments for care (relative payments for care 1.19, 95% confidence interval [CI] 1.07–1.33, p = 0.001). There was large heterogeneity across the study results (I2 = 90%). The lone study, by Kauer, that showed statistically significant higher payments for care at private not-for-profit hospitals compared hospitals owned by not-for-profit organizations but run by a for-profit firm with hospitals owned and operated by private for-profit organizations.8 Because this study design is different than that of the other studies, we undertook a heterogeneity test that evaluated the difference between Kauer's estimate of payments for care (relative payments for care 0.93, 95% CI 0.88–0.99) and the estimate from the other studies (relative payments for care 1.24, 95% CI 1.11–1.39), and this test was statistically significant (p = 0.048). Even without Kauer's study, large heterogeneity across the study results (I2 = 86%) persisted. Only 1 of our predefined hypotheses (specialty versus general hospitals) helped to explain some of the persistent heterogeneity (p = 0.02 for the difference between these subgroup summary estimates). Pooled estimates from both the 3 studies that evaluated specialty hospitals and the 5 studies that evaluated general hospitals showed higher payments for care at private for-profit hospitals (relative payments for care 1.48, 95% CI 1.15–1.89, and 1.11, 95% CI 1.00–1.23, respectively).

The 2 studies with the most extensive adjustment for potential confounders — the study by Sloan and associates12 and the study by Keeler and associates13 — reported statistically significant higher payments for care at the private for-profit hospitals than at the private not-for-profit hospitals (relative payments for care 1.51, 95% CI 1.17–1.94, and 1.13, 95% CI 1.09–1.16, respectively).

Interpretation

We identified 8 observational studies that compared payments for care at private for-profit and private not-for-profit hospitals. These studies altogether involved more than 350 000 patients and included a median of 324 hospitals each. Five of the studies and our pooled analysis demonstrated statistically significant higher payments for care at private for-profit hospitals than at private not-for-profit hospitals.

Our systematic review has several strengths. We undertook a comprehensive search using 6 strategies to identify studies for our review, masked study results before determining study eligibility, conducted eligibility decisions and data abstraction in duplicate and demonstrated a high degree of agreement. For 7 of the 8 studies the investigators provided or confirmed data.

Our systematic review has several limitations. We did not identify any randomized controlled trials. It is unlikely that patients will ever be randomly assigned to private for-profit and private not-for-profit health care delivery systems. Therefore, the strongest realistic design for addressing our question is an observational study.

The main limitation of observational data is the potential for confounding. Six of the 8 observational studies adjusted for potential confounders. The statistical significance of the findings within the 2 studies for which we present the unadjusted analyses did not vary between the unadjusted and adjusted analyses.7,9 The 2 studies with the most extensive adjustment for potential confounders both reported statistically significant higher payments for care at the private for-profit hospitals (relative payments for care 1.51 and 1.13).12,13 For example, the study by Sloan and associates adjusted for age, sex, education, ethnicity, marital status, income, community living, number of activities of daily living, cognitive awareness, bladder/bowel control, comorbidity, primary diagnosis at index admission, market characteristics (population per square mile, Herfindahl index, Medicare hospital wage index, Health Maintenance Organization market share, hospital beds per 100 population), year of index admission, number of hospital beds and hospital teaching status.12

Another limitation of our systematic review was that we were unable to include 6 studies because the investigators failed to provide an estimate of variance, 3 studies because the investigators either no longer had the data or could not rerun their analyses to remove the public not-for-profit hospitals, and 1 study because the investigators had only charges and not payment data. All 10 of these studies, however, showed higher payments or charges for care at private for-profit hospitals than at not-for-profit hospitals, and in 6 of the 10, the differences were statistically significant.

Our pooled analysis showed significant variability in the direction and magnitude of effect among the studies. It is common practice to pool results with significant heterogeneity, but one may question the advisability of doing so. Although the inference that private for-profit hospitals result in higher payments for care is secure, heterogeneity in results suggests that the magnitude of the effect may differ according to circumstances. In the presence of unexplained heterogeneity, inferences associated with pooled estimates are weaker; nonetheless, these estimates provide the best available estimate of the average effect.25 We present these results as we believe they constitute useful information for decision-makers.

Our pooled analysis and 5 of the studies included in our systematic review demonstrated statistically significant higher payments for care at private for-profit hospitals than at private not-for-profit hospitals, whereas only 1 study demonstrated the opposite.8 These results are completely consistent with those of studies that we were unable to include because of technical reasons (Table 1). The lone study demonstrating lower payments for care at private for-profit hospitals compared them with hospitals owned by private not-for-profit organizations but run by a private for-profit firm.8In essence, this is a comparison between different modes of for-profit management.

Why would private for-profit hospitals have higher payments for care than private not-for-profit hospitals? One potential explanation could be that they are providing superior care. However, our previous meta-analysis involving over 38 million patients demonstrated that private for-profit hospitals have higher risk-adjusted mortality rates.2 Our meta-analysis involving over 500 000 patients receiving hemodialysis also revealed higher risk-adjusted mortality rates at private for-profit dialysis facilities.26

The likely explanation is the necessity to generate revenues to satisfy investors, a requirement absent in private not-for-profit hospitals. Private for-profit hospitals are also burdened with a 6% absolute increase in the proportion of hospital spending devoted to administration as compared with private not-for-profit hospitals.27 Further, executive bonus incentives are over 20% higher at private for-profit than at private not-for-profit hospitals.28

We offer 2 reasons why our results may actually underestimate the association between private for-profit hospitals and higher payments for care. First, all but 2 of the studies in our systematic review adjusted for case mix. Therefore, our results do not capture any increase in payments for care resulting from inappropriate upcoding of patient diagnoses to enhance reimbursement. Private for-profit hospitals manifest higher upcoding of patient diagnoses than do private not-for-profit hospitals.29

Second, the studies in our systematic review did not explicitly address issues of fraud (e.g., performance of unnecessary surgeries, billing for services not provided, inappropriate detainment of psychiatric patients for billing purposes),30 which can increase both the direct costs of care and the indirect costs related to investigating and prosecuting offenders. The multimillion-dollar fraud lawsuits in the United States have overwhelmingly been against private for-profit hospitals.31,32 It is likely, therefore, that we are underestimating the true association between private for-profit hospitals and higher payments for care.

Many countries, like Canada, are debating choices about private for-profit and private not-for-profit health care delivery. How important is a relative increase in payment for care of 19%? Canada currently spends $120 billion annually on health care, and hospital care accounts for 32% of overall expenditures.33 If we were to convert half of our hospitals to private for-profit institutions, our results suggest that we would pay approximately an extra $3.6 billion annually.

Given the differences in the structure of Canadian and US health care systems, one might question the applicability of our results to Canada. The structure of US health care has, however, changed significantly over time (e.g., the introduction of prospective payment systems for Medicare patients and managed health care). The 5 studies that demonstrated statistically significant higher payments for care at private for-profit hospitals included data from 1983 through to the end of 1994, and thus included results from both before and after these changes. Furthermore, these 5 studies had variations in their sources of payments (i.e., Medicare, private insurance or both). These findings suggest that the higher payments for care at private for-profit hospitals are manifest within a variety of health care contexts. Finally, should Canada open the door to private for-profit hospitals, the very same large US hospital chains that have generated the data included in this systematic review will soon be purchasing Canadian private for-profit hospitals. In summary, it is likely that our results are generalizable to the Canadian context.

For-profit hospitals result in both higher mortality rates and greater payments for care than do not-for-profit hospitals. The evidence strongly supports a policy of not-for-profit health care delivery at the hospital level.

β See related article page 1814

Supplementary Material

[Online Appendix 1]
[Online Appendix 2]

Acknowledgments

We wish to acknowledge the outstanding work of Deborah Maddock and Laurel Raftery, who coordinated the study, and Neera Bhatnagar, the librarian who undertook the searches involved in the study. We also thank all the authors of the studies included in our systematic review who confirmed information, provided information and performed additional analyses for our systematic review.

Footnotes

Fast-tracked article

This article has been peer reviewed.

Contributors: Dr. P.J. Devereaux contributed significantly to the concept and design, data acquisition, data analysis and interpretation of the data. He also wrote the first draft of the manuscript. Ms. Diane Heels-Ansdell and Ms. Christina Lacchetti contributed significantly to the systematic review's concept and design, data acquisition, data analysis and interpretation of the data. Dr. Ted Haines, Dr. Karen Burns, Clinical Clerk Nikila Ravindran, Ms. Heather McDonald, Dr. Rakesh Patel, Dr. Mohit Bhandari, Dr. Holger Schünemann and Dr. Peter Choi contributed significantly to the systematic review's concept and design, data acquisition and interpretation of the data. Dr. S.D. Walter contributed significantly to the data analysis and interpretation of the data. Clinical Clerk Samuel Stone contributed significantly to the systematic review's data acquisition and interpretation of the data. Dr. Deborah Cook, Dr. Ahmed Bayoumi, Dr. John Lavis, Dr. Terrence Sullivan, Dr. Greg Stoddart and Dr. Gordon Guyatt contributed significantly to the systematic review's concept and design and interpretation of the data.

All authors provided critical revisions to the manuscript and gave final approval of the submitted manuscript.

This study was supported by an Atkinson Foundation Research Grant and a Hamilton Health Sciences Research Development Grant. Dr. P.J. Devereaux is supported by a Canadian Institutes of Health Research, Senior Research Fellowship Award. Dr. Karen Burns is supported by a Canadian Lung Association and Merck Frosst Postdoctoral Fellowship Award. Dr. Deborah Cook is a Chair of the Canadian Institutes for Health Research. Dr. Mohit Bhandari is supported by the Detweiller Fellowship from the Royal College of Physicians and Surgeons of Canada, and a Department of Clinical Epidemiology and Biostatistics, McMaster University, Clinical Scientist Fellowship Award. Dr. Peter Choi is supported by a Vancouver Coastal Health Research Institute Mentored Clinician Scientist Award. Dr. Ahmed Bayoumi is supported by a Career Scientist Award from the Ontario HIV Treatment Network. Dr. John Lavis holds a Canada Research Chair in Knowledge Transfer and Uptake.

Competing interests: None declared.

Correspondence to: Dr. P.J. Devereaux, McMaster University, Faculty of Health Sciences, Department of Clinical Epidemiology and Biostatistics, Rm. 2C8, 1200 Main St. W, Hamilton ON L8N 3Z5; fax 905 526-1353; ac.retsamcm@jpilihp

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