Abstract

Background: The hospital market is stratified between the “have” and the “have not” hospitals. Whether financial disparities among hospitals are associated with disparities in patient safety problems is unknown. Methods: We used the Healthcare Cost and Utilization Project (HCUP) State Inpatient Database for Florida from 1996-99 (373,814 discharges at 188 hospitals) to examine whether financial pressure at hospitals is associated with the rate of patient safety events (e.g., preventable adverse events, medical errors) among elderly Medicare fee-for-service (FFS) patients. We used the newly released Agency for Healthcare Research and Quality (AHRQ) Patient Safety Indicators (2003) and conducted regression analyses in which we controlled for the patients' risks of adverse outcomes. Results: We estimate that patients treated at the financially distressed hospitals are 13.7 percent more likely to have a surgery-related patient safety event than are patients treated at highly profitable hospitals (P = 0.034). Patients treated at the financially distressed hospitals also are 18.3 percent more likely to have a nursing-related patient safety event than are patients at highly profitable hospitals (P = 0.001). Furthermore, the patients treated at financially distressed hospitals are 24.1 percent more likely to die during their hospitalization than are patients treated at a highly profitable hospital (P < 0.001). Among the patients with potentially preventable complications (N = 25,392; 6.8 percent of all surgeries), those treated at financially distressed hospitals have a 26 percent higher probability of not being rescued and of dying than do patients treated at highly profitable hospitals (P = 0.027). We also found that women are more likely to have surgery- and nursing-related patient events than are men, while black patients are more likely to suffer surgery-related and nursing-related adverse events or death during hospitalization, compared with white patients. Hispanics are more likely to have nursing-related patient safety events, while other non-Hispanic racial minorities are more likely to have failure to rescue and to die during hospitalization, compared with whites. Conclusions: The finding that patients treated at financially distressed hospitals are more likely to have adverse patient safety events suggests that any cost-cutting efforts should be carefully designed and managed.

Introduction

A recent survey found that at least 10 percent of adults reported that they or a family member had experienced a mistake in a hospital or doctor's office, with more than half of the mistakes reported to be very serious. ¹ The Committee on the Quality of Health Care in America was established in 1998 by the Institute of Medicine (IOM) to address this problem, and its first report, To Err Is Human, estimated that between 44,000 and 98,000 Americans die each year as a result of medical mistakes, making medical error the ninth leading cause of death in the United States. ² Thus, this report attracted considerable attention and resulted in increased efforts to improve the safety of health care in this country.

In fact, the IOM Committee recommended nothing less than a 50 percent reduction in medical errors over the five years that followed its report. Moreover, the Medicare Payment Advisory Commission (MEDPAC) has recommended that Medicare set up goals and payment schemes to improve patient safety at hospitals for Medicare patients. While hospital mortality for Medicare patients declined between 1995 and 2002, MEDPAC has been concerned with the increase in patient safety problems for Medicare patients during the same period. ³ Variations in the quality of care received by Medicare beneficiaries have been documented recently in two additional studies. ^{4, 5} Such recommended reductions in patient safety errors will require large financial investments in monitoring systems, training programs, systems redesigns, and additional staffing. This presents a dilemma, since many hospitals are already distressed financially as a result of the steep price discounts afforded to managed care plans and the Medicare payment cuts implemented by the Balance Budget Act of 1997. Although the 1999 Balanced Budget Refinement Act (BBRA) generally increased payments to providers, the reduction in annual hospital payment updates for prospective payment system hospitals was not corrected by the BBRA provisions. Thus, some hospitals may find it difficult to make major financial investments aimed at improved patient safety. In fact, the hospital market is now stratified between the “have” and “have not” hospitals, according to financial analysts interviewed for Medicare's 2003 market update. ⁶ In this study, for example, we found that 25 percent of Florida Medicare FFS patients had major surgeries at the financially distressed “have-not” hospitals with average profits of 8 percent during 1996-99. Conversely, another 25 percent of the same Florida Medicare patient group had major surgeries at the more affluent “have” hospitals, which showed average profits of 17 percent. Such financial disparities may eventually lead to disparities in patient safety for Medicare beneficiaries. We will attempt in this paper to answer the critical question: What type of an association exists between hospital operating margins (i.e., profits) and patient safety for Medicare beneficiaries?

We are aware of just one recent study that addresses this question in terms of mortality, but not in terms of general patient safety. Shen (2003) examined the effect of financial pressures on patient outcomes and found that financial pressures adversely affect patient outcomes. ⁷ That study used data from an earlier period (1985-94), however, and the scope is limited to death following treatment for acute myocardial infarction. To get a better picture of patient safety, we examined a broad spectrum of patient safety measures relevant to all major surgeries: surgery-related patient safety events, nursing-related patient safety events, death rates for all patients, and failure to rescue a patient following a potentially preventable complication. Among Medicare FFS surgery patients during the four year period from 1996-99, we found that these patient safety events were 13 percent to 26 percent more likely to occur at financially distressed hospitals (those with negative profit margins), than at highly profitable hospitals (those with more than a 10 percent profit margin).

Method

Hospital data

Our primary source of data was the Healthcare Cost and Utilization Project (HCUP) State Inpatient Database for Florida, which included all inpatient discharges for all general acute-care hospitals. We focused on all elderly (age >64 years) Medicare FFS major surgery discharges from all general acute care Florida hospitals from 1996-99. As a result, our sample consisted of 373,814 elderly Medicare FFS major surgery hospitalizations over the 4-year period in 188 hospitals.

The financial hospital characteristics were obtained from the audited annual cost reports that each Florida hospital submitted to the Florida Agency for Health Care Administration from 1995-98. From these cost reports we calculated each hospital's operating margin. Also known as the profit margin, the operating margin is equal to the ratio of the hospital's net operating profits to the hospital's net operating revenues. Table 1 shows the variation in hospital operating margins across hospitals by year. All other hospital characteristics were obtained from the American Hospital Association's Annual Survey 1996-99. The descriptive statistics for these hospital characteristics are included in Table 3.

Table 1

Operating margins for study sample of Florida hospitals^a.

Table 3

Descriptive statistics.

Results

Table 1 represents the distribution of operating margins for the hospitals in our sample. The top row shows the operating margins at the 25^th percentile by year. The same row indicates that one-quarter of the hospitals had profit margins less than -1.34 percent (in other words, losses greater than 1.34 percent) during 1996. By 1999, one-quarter of the hospitals in the sample had profit margins less than -5.98 percent (alternatively, losses greater than 5.98 percent).

The second row shows that the median profit margin was 3.42 percent for 1996, which rose to 5.86 percent for 1997, and declined to 3.12 percent for 1999. The third row shows that the hospitals in the highest profit quartile remained highly profitable through the 4-year study period. The operating margin at the 75th percentile was 10.30 percent for 1996, and 9.22 percent for 1999. In summary, profit margins declined systematically for the most part from 1997-99, but the declines were much more severe among hospitals in the lowest profit quartile.

In Table 2, we have presented the rate of patient safety events by level of hospital operating margin. As described previously, hospital-year observations are divided into four profit categories: less than 0 percent, 0 percent to 5 percent, 5 percent to 10 percent, and greater than 10 percent. These categories correspond very closely to the patient quartiles of the data and enable us to compare hospitals with losses (i.e., financially distressed hospitals) to hospitals with positive margins. We refer to hospitals with 10 percent or higher margins as “highly profitable” hospitals. The first column in Table 2 shows that over the 4-year period from 1996 to 1999, there were 182 hospital-years with operating margins higher than 10 percent and 218 hospital-years with operating margin losses. Table 2 also reveals that for each of the four patient safety events considered, the rates of occurrence were highest among those hospitals with negative operating margins (i.e., hospitals that lost money).

Table 2

Unadjusted rates of patient safety events, 1996-99.

It is important to note that there is variation in the financial performance of hospitals over the course of the study period. Specifically, 71 percent of hospitals moved from one margin category to another in at least one year. In fact, 43 percent of the hospitals moved from one category to another in at least 2 of the 3 years. Only 29 percent of the hospitals remained in the same margin category throughout the 4 years of the study.

Table 3 presents the descriptive statistics on the hospital and patient characteristics in our sample. In the analysis, the unit of observation is a major surgery discharge.

During the study period, 2.5 percent of the 373,814 major surgery patients had at least one of the surgery-related patient safety events, while 7.9 percent of the surgery patients had at least one of the nursing-related patient safety events. Overall, 2.6 percent of the patients represented in the sample died during hospitalization. Among all major surgery patients, 6.8 percent had a potentially preventable complication. The rate of failure to rescue, the in-hospital death rate for those patients that suffer potentially preventable complications, was 11.3 percent (25,392 major surgery patients had potentially preventable complications). Fifteen percent of major surgery hospitalizations took place at teaching hospitals. Fifty-two percent of major surgery hospitalizations occurred at not-for-profit hospitals, while 35 percent occurred at for-profit hospitals and only 13 percent took place at public hospitals.

In Table 4, we present the results from the logistic regressions described above. We construct indicator variables for four ranges of hospital margins. The omitted category includes highly profitable hospitals with margins of more than 10 percent. The lowest category includes those hospitals with losses (negative margins).

Table 4

Estimated odds ratio of a patient safety event^a.

In column 1, we see that major surgery patients at the financially distressed hospitals are 13.7 percent more likely to experience a surgery-related patient safety event than are patients at highly profitable hospitals with margins exceeding 10 percent (P = 0.034). The probability of a patient safety event at hospitals with margins ranging from 0 percent to 5 percent, and from 5 percent to 10 percent, is not significantly different from that of highly profitable hospitals with margins exceeding 10 percent.

Column 2 of Table 4 reveals that as hospital operating margins decline, the probability of a nursing-related patient safety event increases. In particular, patients treated at financially distressed hospitals have 18.3 percent higher odds of having a nursing-related patient safety event than patients treated at highly profitable hospitals (P = 0.001). Column 3 shows that as hospital operating margins decline, the probability of patient death increases. The probability of an in-hospital death is 24.1 percent higher among patients treated at financially distressed hospitals, than among those patients treated at highly profitable hospitals (P < 0.001). In column 4, the sample is restricted to those surgeries that involved a potentially preventable complication (N = 25,392; 6.8 percent of all surgeries). Among patients with complications, those treated at financially distressed hospitals have 26 percent higher odds of not being rescued and of dying than patients at highly profitable hospitals (P = 0.027).

In Table 4 we also see that patients treated at teaching hospitals have a significantly higher risk of a surgery-related patient safety event and of death. This is consistent with the fact that teaching hospitals often perform new, complex, and high-risk surgeries. Next, Table 4 shows that patients treated at large hospitals (defined as hospitals with more than 200 beds) have a lower risk of a surgery-related or nursing-related patient safety event. We also found that not-for-profit hospitals have a lower risk of death and failure to rescue than do public hospitals. We found no difference, however, between public, for-profit, and not-for-profit hospitals, in terms of surgery-related and nursing-related safety events. Thus, our overall findings suggest that it is the hospital's financial circumstances and not the form of ownership that has the larger correlation with patient safety.

Table 4 further indicates that the probability of adverse patient safety events vary by gender, race, and ethnicity. We found that women are significantly more likely to have surgery-related patient safety events (18 percent greater likelihood) and nursing-related adverse patient safety events (50 percent greater probability). Blacks are more likely than whites to have surgery-related patient safety events (24 percent greater likelihood), nursing-related patient safety events (45 percent greater probability), as well as failure to rescue (26.4 percent higher odds). Similarly, Hispanics are significantly more likely than whites to a have a nursing-related problem (17 percent greater likelihood). Other non-Hispanic racial minorities (e.g., Asians) are significantly more likely to die (24 percent greater probability) or experience a failure to rescue than are whites (28 percent greater likelihood). Finally, the year dummies in Table 4 show that the probability of nursing-related patient safety events declined while the probability of death increased during the study period. Additional variables absent from Table 4 but included in the models are 9 dummy variables for age groups, 17 dummies for Major Diagnostic Categories, and 18 indicators for Health Service Areas.

Discussion

We found that financially distressed hospitals have worse patient safety rates than highly profitable hospitals across all four measures of patient safety. One would expect the higher rates of nursing-related patient safety events at distressed hospitals to be related to higher patient-to-nurse staffing ratios. In fact, previous studies have indicated that reductions in nursing staff are associated with increased rates of complications and deaths. ^{11, 15, 16, 17} Needleman et al. found that among surgical patients, a lower “proportion of care provided by registered nurses” was associated with higher rates of urinary tract infection and “failure to rescue” incidents following a complication ¹¹ Kovner et al. found that lower rates of registered nurse hours per adjusted inpatient day were associated with higher rates of pneumonia for routine and emergency patient admissions. ¹⁷

If hospitals were more likely to respond to financial problems with using cost-cutting measures related to nursing care, rather than those related to physician staff (and/or medical technology investments), we would find that financially distressed hospitals have higher rates of nursing-related patient safety events, but not necessarily higher rates of surgery-related patient safety events. The finding that financially distressed hospitals have higher rates of surgery-related patient safety events (complications due to surgery-related care rather, than nursing-related care) suggests that cuts in nursing staff may not be the only mechanism by which hospital finances affect patient outcomes. Financial pressures may lead to changes in hospital operations (e.g., lower physician staffing levels, or delays in adopting costly medical technology) that affect the quality of care provided by surgeons and anesthesiologists, as well as nurses. Future research should examine the exact mechanism by which financial pressures impact patient safety systemwide. Recall that these surgery-related patient safety events are based on just 12 measurable patient safety indicators. There may be many more preventable patient safety events (as well as near misses) that are occurring at the same time, but that are not measurable in our data. Also, due to data limitations, our patient safety measures do not include medication errors.

We also found that the probability of having adverse patient safety events varies by gender and race. Our results show that women are significantly more likely to have surgery-and nursing-related adverse patient safety events; that blacks are more likely to have surgery-related patient safety events and nursing-related patient safety events, as well as failure to rescue; that Hispanics are more likely to a have a nursing-related problem; and that other non-Hispanic racial minorities are significantly more likely to die or experience failure to rescue than are whites. Other researchers have found similar gender disparities in health care. One recent study, for example, found that women who have contracted the HIV virus are significantly less likely to be prescribed newer, more costly, but more effective medications compared to men. ²⁰ The race and ethnicity results may be explained in part by differences in unobserved severity. Another potential explanation is the segmentation of patients across different quality providers (e.g., high costs may prevent low income patients from obtaining care from higher quality hospitals and/or physicians). More research is needed to identify the sources of disparity in patient safety outcomes across gender and race.

It should be noted that there are several potential limitations of our study. First, lower rates of patient safety events at highly profitable hospitals may be driven, in part, by the ability of the hospitals to attract healthier patients, while avoiding severely ill patients. In order to avoid this selection effect, we focused solely on fee-for-service Medicare patients who were not restricted in their choice of hospitals. There may still be selection bias, however, if some hospitals choose to locate in areas with a relatively young and healthy elderly population. ²¹ We believe we have mitigated this potential selection bias by controlling for an exhaustive list of 30 comorbidities that capture the patient's severity. Second, our results from Florida may not extend to the rest of the country. Florida has a higher proportion of for-profit hospitals—more than 30 percent—compared with less than 10 percent for the nation as a whole. We do not expect this to be a problem, however, since we did not identify a “for-profit effect” on patient safety outcomes in our study. Also, Florida has a higher proportion of Medicare patients than the rest of the nation. Future research should examine the impact of hospital finances on patient outcomes at the national level.

Conclusion

Our results provide insight for those wishing to implement quality-based payments as rewards for quality improvement, as recommended in the 2001 Institute of Medicine report, Crossing the Quality Chasm. ²² Our results suggest that the magnitude of quality improvement may be large, if financial incentives are provided. For Medicare fee-for-service surgery patients, we found that our four broad measures of patient safety events are 13 percent to 26 percent more likely to occur at financially distressed hospitals with negative profit margins, than at highly profitable hospitals with profit margins exceeding 10 percent. Thus, a quality-based payment structure that includes a bonus for quality improvement might possibly induce the desired quality improvements in “have-not” hospitals. While these bonuses may appear expensive in the short-term, the long-term reduction in errors may offset the expense of these added incentives. In fact, the cost savings resulting from reduced errors could be as high as $30 billion annually. ² Future research should strive to examine the effect of quality-based payments on patient safety. Alternatively, policymakers may consider steering patients to “higher quality” hospitals. Finally, the finding that financially distressed hospitals have more adverse patient safety events suggests that any reductions in hospital payments for Medicare beneficiaries and Medicaid recipients should be carefully designed and managed.

Acknowledgments

This research was funded by the Agency for Healthcare Research and Quality (AHRQ). The views in the paper are those of the authors and do not necessarily reflect the views or policies of AHRQ, nor the U.S. Department of Health and Human Services. We thank Jessica Banthin, Joel Cohen, Steve Cohen and an anonymous reviewer for helpful comments, as well as the Florida Agency for Health Care Administration for providing financial data and for contributing data to HCUP.

References

1.

Davis K, Schoenbaum SC, Scott Collins K, et al. Room for improvement: patients report on the quality of their health care. New York: The Commonwealth Fund. 2002 April.

2.

Kohn LT, Corrigan JM, Donaldson MS, editors. To err is human: building a safer health system. A report of the Committee on Quality of Health Care in America, Institute of Medicine. Washington, DC: National Academy Press; 2000. [PubMed: 25077248]

3.

Report to Congress: Medicare payment policy. Medicare Payment Advisory Commission (MEDPAC). 2004 March.

4.

Jencks S, Huff E, Cuerdon T. Changes in the quality of care delivered to Medicare beneficiaries, 1998-1999 to 2000-2001. JAMA. 2003 Jan 15;289(3):305–12. [PubMed: 12525231]

5.

Baicker K, Chandra A. Medicare spending, the physician workforce, and beneficiaries' quality of care. Health Affairs Web exclusive. 2004 April;7;W4:184–97. [PubMed: 15451981]

6.

Perspectives. Part 1: Is the hospital have/have-not gap worsening? Medicine and Health 2003 Sep. 29;57(5):1. [PubMed: 14558306]

7.

Shen Y. The effect of financial pressure on the quality of care in hospitals. Journal of Health Economics. 2003;22:243–69. [PubMed: 12606145]

8.

Iezzoni L, Daley J, Heeren T. et al. Identifying complications using administrative data. Medical Care. 1994;32(7):700–15. [PubMed: 8028405]

9.

Ball, J, Elixhauser A, Johantgen M, et al. HCUP Quality Indicators, Methods, Version 1.1, Outcome, utilization, and access measures for quality improvement. Healthcare Cost and Utilization Project (HCUP-3) Research Note, Rockville, MD: Agency for Healthcare Research and Quality 1998. AHCPR Publication No. 98-0035.

10.

Miller M, Elixhauser A, Zhan C. et al. Patient safety indicators: using administrative data to identify potential patient safety concerns. Health Serv Res. 2001;36(6):110–32. [PMC free article: PMC1383610] [PubMed: 16148964]

11.

Needleman J, Buerhaus P, Mattke S, et al. Nurse-staffing levels and the quality of care in hospitals. NEJM 2002;346(22):1,715–22. [PubMed: 12037152]

12.

McDonald K, Romano P, Geppert J, et al. Measures of patient safety based on hospital administrative data—the patient safety indicators. Technical Review 5. Rockville, MD: Agency for Healthcare Research and Quality. 2002 Aug. AHRQ Publication No. 02-0038. [PubMed: 20734521]

13.

Romano P S, Geppert J J, Davies S. et al. A national profile of patient safety in U.S. hospitals. Health Aff. 2003;22(2):154–66. [PubMed: 12674418]

14.

Zhan C, Miller M. Excess length of stay, charges, and mortality attributable to medical injuries during hospitalization. JAMA. 2003;290(14):1868–74. [PubMed: 14532315]

15.

Unruh L. Licensed nurse staffing and adverse events in hospitals. Med Care. 2003;41(1):142–52. [PubMed: 12544551]

16.

Aiken LH, Clarke SP, Sloane DM, et al. Hospital nurse staffing and patient mortality, nurse burnout, and job dissatisfaction. JAMA 2002;288(16); 1,987–93. [PubMed: 12387650]

17.

Kovner C, Jones C, Zhan C. et al. Nurse staffing and postsurgical adverse events: an analysis of administrative data from a sample of US hospitals, 1990-96. Health Serv Res. 2002;37(3):611–29. [PMC free article: PMC1434654] [PubMed: 12132597]

18.

Silber J H, Rosenbaum P R, Schwartz J S. et al. Evaluation of the complication rate as a measure of quality of care in coronary artery bypass graft surgery. JAMA. 1995;274:317–23. [PubMed: 7609261]

19.

Elixhauser A, Steiner C, Harris D, Coffey R. Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8–27. [PubMed: 9431328]

20.

Hellinger F J, Encinosa W E. Antiretroviral therapy and health care utilization: a study of privately insured men and women in HIV disease. Health Serv Res. 2004;39(4):949–67. [PMC free article: PMC1361046] [PubMed: 15230936]

21.

Norton E C, Staiger D O. How hospital ownership affects access to care for the uninsured. Rand J Econ. 1994;13(1):171–85. [PubMed: 10132574]

22.

Institute of Medicine. Crossing the quality chasm: a new health system for the twenty-first century. Washington, DC: National Academy Press; 2001.