Affiliations of authors: S.-L. Yao, Merck Research Laboratories, Rahway, NJ; G. Lu-Yao, HealthStat, Princeton, NJ.
Correspondence to: Siu-Long Yao, M.D., Merck Research Laboratories, RY33-640, 126 East Lincoln Ave., Rahway, NJ 07065-0900 (e-mail: siulong_yao{at}merck.com).
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ABSTRACT |
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INTRODUCTION |
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Increases in health care costs coupled with the commercialization of medicine have resulted in many concerns regarding the quality and quantity of care ultimately provided to the individual patient. Many health care providers have been concerned that third-party payers may be inappropriately attempting to decrease lengths of hospital stay or quality of care in an attempt to reduce costs. Indeed, recent reports (3-5) lend some credence to the hypothesis that a decreased length of hospital stay might be detrimental to patient outcomes. Nonetheless, other studies (6-8) have also revealed that substantial errors can occur in the hospital, suggesting that a prolonged length of stay in the hospital may not uniformly benefit the individual patient.
Despite the large number of patients diagnosed with prostate cancer in the United States (approximately 200 000 annually) and the large number of prostatectomies performed annually (>25 000 in Medicare patients alone), there is a notable absence of data that address relationships between hospital load or volume of prostatectomy procedures, short-term patient outcomes, and length of stay of the patient in the hospital for this procedure. We examined the effect of volume of, and changes in volume of, prostatectomy procedures handled by hospitals on short-term patient outcomes and the length of a patient's stay in the hospital. The large and extensive nature of the Medicare database has provided us with an opportunity to qualify and quantify these relationships.
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METHODS |
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Study Population
The data utilized in this study were compiled by the Health Care Financing Administration and represent all Medicare claims filed by hospitals and physicians for the period 1991 through 1994. The diagnostic coding accuracy of the Medicare claims database has been found to be nearly 100% for major surgical procedures (10). To further ensure that all included patients underwent radical prostatectomy, we included in this study only patients who had corroborating hospital and physician claims. Patients were identified by International Classification of Diseases, Ninth Revision, Clinical Modification (11), procedure code 60.5 and physician claims Current Procedural Terminology codes 55810, 55812, 55815, 55840, 55842, or 55845. Since Medicare coverage for nondisabled patients begins at age 65 years, the study population was limited to patients 65 years old or older. Men enrolled in health maintenance organizations or treated at Department of Veterans Affairs hospitals were not included because the completeness of their Medicare claims could not be assured. Overall, this study included more than 92% of Medicare beneficiaries who were 65 years old or older during the study period (12). We collected data on 101 604 prostatectomy procedures from the Medicare claims database from 1991 through 1994.
Definitions of End Points
The main end points for this study were the mean length of stay of patients in the hospital and mortality, surgical complications, and readmission in the 30-day follow-up period. Dates of death were obtained from the Medicare enrollment file, which has an accuracy of more than 90% for males (13). For up to 5% of the patients, date of death within 30 days may not have been independently verified, and unverified dates of death may have been recorded as the last day of the month. Thus, patients who were coded as alive at day 30 and had an unverified date of death occurring between 31 and 60 days after admission could have died within 30 days of surgery. For this reason, we also examined 90-day mortality to determine if the same patterns held. Because relative risks for 30-day mortality and 90-day mortality were nearly identical, only 30-day mortality results are reported.
Hospital claims were used to examine both the risks of surgical complications during the
index hospitalization and readmission within 30 days of initial discharge (14,15). Conditions listed in Appendix Table 1 that were not present
in the Medicare claims during the 12 months preceding prostatectomy were deemed surgical
complications (16). Classification of complications as serious or not
serious was based on consensus of the authors of this report (see Appendix Table 1
for more details). Length of hospital stay was defined as the number of
overnight stays in the hospital. Patients who died during hospitalization (18 of the
101 604 patients) were removed from the length-of-hospital-stay analyses, although their
inclusion did not alter the results. The age and race of the patient, year of surgery, and
comorbidity as well as surgeon specialty and hospital volume were ascertained from the Medicare
database.
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Hospitals were classified into four categories of prostatectomy volumes based on the number
of prostatectomies performed on eligible patients during 1991 through 1994: 1) low volume
(25th percentile or
38 prostatectomy surgeries in the study period; number
of hospitals in this category = 2013); 2) medium-low-volume (26th-50th percentile or 39-74 surgeries in the study period; number of hospitals in this category
= 463); 3) medium-high volume (51st-75th percentile or 75-140
surgeries in the study period; number of hospitals in this category = 257); and 4)
high-volume (
76th percentile or
141 surgeries in the study period;
number of hospitals in this category = 116). Hospitals with accredited graduate training
programs in urology during 1991 through 1994 were categorized as teaching hospitals (17). Comorbidities were identified during the 12-month period before and
during the index surgical admission and included the five most common coexisting conditions for
prostatectomy (diabetes, hypertension, pulmonary disease, renal disease, and cardiac disease) (18).
To delineate the impact of change in hospital volume for prostatectomy procedures on short-term patient outcomes and length of stay of the patient in the hospital, we employed a longitudinal study design, in which each hospital was used as the unit of analysis. The prostatectomy surgical volume in 1991 through 1992 constituted the baseline volume, whereas the volume in 1993 through 1994 was used as the second-phase volume. Based on the difference between second-phase and baseline volumes, hospitals were classified into three different categories: 1) those showing a relative increase in volume (the change in volume was in the upper 25th percentile), 2) those showing relatively no change in volume (the change in volume was in the 25th-75th percentile), and 3) those showing a relative decrease in volume (the change in volume was in the lowest 25th percentile). Hospitals with no prostatectomy procedures in the baseline period or in the second-phase period were excluded from the longitudinal analyses. A total of 2403 hospitals were included in the longitudinal analyses.
Statistical Methods
All statistical tests of significance were two-sided. For the cross-sectional analyses,
descriptive statistics regarding rates of complications, readmission, and mortality in each hospital
volume category were age-adjusted by use of the entire study cohort as the standard population.
Odds ratios (as estimates of relative risks) were derived from the logistic regression and were
used to assess the effects of hospital volume on short-term outcomes. Covariates included age
(65-69 years, 70-74 years, or 75 years), race (Caucasian, African-American, or other),
surgeon specialty (urology or other), prostatectomy volume (low, medium-low, medium-high, or
high), teaching status of the hospital (yes or no), comorbidity (yes or no), and year of surgery
(1991, 1992, 1993, or 1994). To assess volume relatedness, we used linear regressions to conduct
trend tests (trends in prostatectomy volume versus patient outcome, e.g., length of stay in the
hospital) (19).
Analysis of variance was used to assess the impact of changes in hospital volume on the change in outcomes and length of hospital stay in the longitudinal analyses. Differences in length of hospital stay between the baseline and second-phase periods constituted the dependent variable, whereas the change in volume (increased, unchanged, or decreased) was designated as the independent variable. Mathematical manipulation and/or transformation of the data prior to statistical analyses was not required because of the large sample sizes and the central limit theorem. Prostatectomy surgical volume during 1991 through 1994 (low, medium-low, medium-high, or high) was included as a covariate. To ensure that the patterns observed in this study were not unduly influenced by outliers, we conducted several subanalyses in which hospitals with fewer than five prostatectomy procedures in any of the two periods or hospitals with extreme lengths of stay were eliminated. Since the results did not differ by the removal of the outliers, the results for all 2403 eligible hospitals are reported.
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RESULTS |
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DISCUSSION |
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The findings from this study demonstrate that, compared with high-volume hospitals, low-volume, medium-low-volume, and medium-high-volume hospitals had higher rates of readmission, higher rates of serious complications, and higher mortality rates. In contrast, volume changes within an individual hospital had little influence on these end points at that same hospital.
As opposed to the influence of surgical volume on patient outcomes, the relationship between surgical volume and the length of the patient's stay in the hospital was evident, irrespective of whether relationships were examined between hospitals or within the same hospital over time. In the cross-sectional analyses, the length of stay in the hospitals with volumes in the 25th percentile was approximately 3 days longer than that in hospitals with volumes in the 75th percentile. In the longitudinal analysis examining the impact of change in volume on patient outcome at the same hospital, the differences in the length of patients' stay between the 25th and 75th percentile hospital volumes were approximately 2.2 days. These 2- to 3-day differences in length of stay could result in substantial cost savings for hospitals in the 25th percentile of volume who are able to achieve volumes comparable to those of hospitals in the 75th percentile.
Previous studies (22-31) utilized cross-sectional analyses to advance the hypothesis that increasing volume may improve outcomes and reduce length of hospital stay for conditions other than prostate cancer. The cross-sectional analysis in this study confirms that hospitals with higher volumes generally have better outcomes and shorter lengths of stay and supports the results of both previous studies of conditions other than prostate cancer and of the longitudinal analysis in this study. It is interesting, however, that, in the cross-sectional analysis, hospital volume beyond 140 cases a year was actually associated with a modest increase, rather than the expected decrease, in length of stay in the hospital. One possible explanation for this observation may be that very large volumes could exceed hospital capacity, resulting in a decrease in efficiency; nonetheless, other reasons for this phenomenon may exist.
There has been a lack of data, however, addressing the impact of changes in individual hospital volumes on patient outcomes and length of patient's stay at that same hospital for both prostate cancer and other conditions. The results obtained in this study suggest that increasing a hospital's surgical volume can facilitate a decrease in the length of a patient's stay in the hospital without having an adverse impact on patient outcomes at that same hospital. Such a finding may have important implications for the manner in which the treatment of prostate cancer and health care in general should be provided in the future.
By use of both cross-sectional and longitudinal analyses to examine the relationships between hospital volume of prostatectomies, short-term outcomes, and length of hospital stay, this study was able to simultaneously address both between-hospital biases (e.g., geographic variation, socioeconomic factors, patient selection, regional differences, accessibility, and quality of anesthesia or other types of care) and within-hospital limitations (e.g., period or time effects) inherent in each type of analyses. Analyzing the data longitudinally decreases the contribution of factors other than volume, since each hospital serves as its own control. Nonetheless, as noted in the "Results" section, the length of stay in the hospital decreased during the duration of this study, irrespective of changes in volume, implying that volume is not the only driver of length of stay. In any case, the use of both methods of analyis strengthens the corroborating results obtained, since the inherent weaknesses of either method alone are more likely to be complemented and minimized.
One of the major strengths of this study lies in its inclusivity and population-based nature, which make the results more easily generalizable and applicable to the majority of patients treated in various clinical settings. The conclusions of previous studies (25-31) with regard to several other conditions, some of which failed to identify a relationship between surgical volume, patient outcome, and length of a patient's stay in the hospital (22-24), have often been limited by sample size restrictions, geographic confinement, notable selection biases, or the nature of the medical condition or intervention studied. Because the majority of publications that describe relationships between surgical volume, patient outcomes, and/or the length of the patient's stay in the hospital are derived from teaching hospital cohorts, their applicability to the majority of providers, who are neither high-volume providers nor teaching institutions, may be more tenuous.
Our results imply that the number of surgeries performed at a hospital may be at least one important driver of length of stay at that same hospital. However, the actual aspect of surgical volume that influences the length of the patient's hospital stay is much less clear. One of the many possible explanations as to how the volume drives the length of stay could obviously be "practice makes perfect." It is also possible, however, that higher volume hospitals have a greater ability to afford and efficiently implement new advances (e.g., through a greater capacity to disseminate information regarding newer methods of management for pain or other aspects of the procedure, etc., and/or the acquisition of new equipment). Further research will be necessary to determine the aspect of the hospital surgical volume that drives the length of stay of the patient in the hospital.
Could length of hospital stay be driving the volume rather than the converse as we have hypothesized? It seems implausible that good hospitals would necessarily have a shorter length of stay and that a shorter length of stay would attract more patients and result in higher volumes, especially in the current health care environment where patients more often than not complain that their stay in the hospital is too short.
Although it is possible that patients could be forced by third-party payers toward hospitals with shorter lengths of stay, resulting in the appearance that shorter length of stay causes an increase in volume, Medicare (the only third-party payer in this study) has never implemented or suggested such a policy. In addition, managed care participants were not part of the population studied here, further minimizing the possibility that the relationship between volume and length of stay could be explained by market pressures.
Another possible explanation for the observed relationship between hospital surgical volume and the length of the patient's hospital stay could be due to biased patient selection. However, subanalyses revealed that hospitals with lower volumes actually have a propensity to treat younger patients (with similar comorbidities), which in theory would tend to make outcomes better rather than worse at these low-volume hospitals. Consequently, it is less likely that factors such as age and comorbidity could account for the observed relationship between surgical volume and the length of the patient's hospital stay.
In applying the results of this study, it is important to note that the data were acquired over a period in the history of radical prostatectomy that may differ from that which exists today. For example, subsequent changes in both the associated technologies as well as the mean length of hospital stay might either increase or decrease the applicability of the results today.
Although a prospective, randomized trial might better alleviate any concerns of unrecognized biases and more definitively establish the relationship between volume, outcomes, and length of hospital stay, the ethics and feasibility of performing such a study would likely be prohibitive. In the absence of such a trial, the large population-based nature of the current data may provide substantial insights into the relationships between volume, outcomes, and length of hospital stay. This is principally because the data can be examined for both independent and dose-response relationships in both a cross-sectional and longitudinal within-hospital fashion while maintaining generalizability for the population at large.
In summary, our results suggest that the prostatectomy surgical volume is associated with both outcome and length of hospital stay and that augmented decreases in length of stay, with either equivalent or improved outcomes, might be achieved by volume-related increases in the number of surgeries performed. The findings extend the results of previous studies that found an association between surgical volume, patient outcomes, and the length of hospital stay for conditions other than prostate cancer but which did not examine the effects of changes in volume on outcomes and length of stay at the same hospital. Whereas policies implemented to uniformly limit length of hospital stay may result in suboptimal outcomes (32,33), the findings from this study suggest that decreasing the length of stay through increased volume in a particular hospital may not be accompanied by increases in adverse outcomes. The application of such a principle could greatly reduce the costs, while maintaining or improving the quality of health care.
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NOTES |
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Manuscript received February 21, 1999; revised September 9, 1999; accepted September 21, 1999.
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