- Email: [email protected]
A variation in the value of colectomy for cancer across hospitals: Mortality, readmissions, and costs
A variation in the value of colectomy for cancer across hospitals: Mortality, readmissions, and costs Justin P. Fox, MD, MHS,a Joshua A. Tyler, MD,b Anita A. Vashi, MD, MPH, MHS,c Renee Y. Hsia, MD, MSc,d and Jonathan M. Saxe, MD,a Dayton, OH, St. Louis, MO, and Palo Alto and San Francisco, CA
Introduction. Although hospital variation in costs and outcomes has been described for patients undergoing operation, the relationship between them is unknown. The purpose of this study was to evaluate this relationship among patients undergoing colon resection for cancer and identify characteristics of ‘‘high-quality, low-cost’’ hospitals. Methods. We identified adult patients who underwent colon resection for cancer in California, Florida, and New York from 2009 to 2010. We estimated hospital-level, risk-standardized 30-day hospital costs, in-hospital mortality rates, and 30-day readmission rates by using hierarchical generalized linear models. Costs were compared between hospitals identified as low, average, and high performers. Results. The final sample included 14,790 patients discharged from 389 hospitals. After adjusting for case mix, variation was noted in risk-standardized costs (median = $26,169, inter-quartile range [IQR] = $6,559), in-hospital mortality (median = 1.8%, IQR = 2.3%), and 30-day readmission (12.2%, IQR = 0.7%) rates. Minimal correlation was noted between a hospital’s costs and outcomes, with similar costs noted across hospital performance groups (low = $25,994 vs average = $26,998 vs high = $25,794, P = .19). High-quality, low-cost hospitals treated a greater percentage of Medicare beneficiaries, approached fewer cases laparoscopically, and trended toward greater volume. Conclusion. Hospital costs are not correlated with outcomes in this population. More work is needed to identify means of providing high-quality care at lesser costs. (Surgery 2014;156:849-60.) From the Department of Surgery,a Boonshoft School of Medicine, Wright State University, Dayton, OH; Section of Colon and Rectal Surgery, Division of General Surgery,b Washington University School of Medicine, St. Louis, MO; VA Palo Alto Healthcare System,c Palo Alto; and Department of Emergency Medicine,d University of California San Francisco, San Francisco, CA
VALUE-BASED PURCHASING is a strategy used by employers, and increasingly the federal government, to use their market power to promote quality and value of health care services. This approach holds health care providers accountable for both the cost and quality of care.1 These programs are based on findings that substantial variation exists The views expressed in this article are those of the authors and do not reflect the official policy of the United States Air Force, Department of Defense, or the United States government. This work was accepted for oral presentation at the annual meeting of the Central Surgical Association in Indianapolis, Indiana; March 2014. Accepted for publication June 18, 2014. Reprint requests: Justin P. Fox, MD, MHS, Miami Valley Hospital, One Wyoming Street, Suite 7000 WCHE, Dayton, OH 45409. E-mail: [email protected]. 0039-6060/$ - see front matter Ó 2014 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.surg.2014.06.011
in the quality of health care provided by US hospitals that is not explained completely by differences in patient populations.2,3 Most commonly, the quality measures being used are conditionspecific, hospital-level mortality and readmission rates.4 Purchasing ‘‘value’’ in health care also suggests obtaining high quality at reasonable costs5; however, the relationship between health care quality and a hospital’s costs of providing care is unclear, with some studies suggesting that greater spending is required to improve outcomes,6 whereas others have found achieving better outcomes reduce costs.7 Among patients undergoing colon resection for cancer, the perioperative outcomes achieved and the hospital’s cost of providing that care are partly related to the hospital where a patient is treated. For example, the average in-hospital mortality and 30-day readmission rate in this population is 1% and 12%, respectively. Previous studies, however, have demonstrated wide variation in these average SURGERY 849
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rates despite adjustments for case mix. In these studies, the in-hospital mortality and 30-day readmission rate vary 3- to 4-fold across hospitals.8,9 Similar to clinical outcomes, a hospital’s costs associated with performing colon resection can fluctuate by as much as $3,000 in the Medicare population alone.10 Although both costs and outcomes have been evaluated, it is unknown whether these outcomes are correlated. Specifically, it is unclear whether greater costs are required for greater quality or may represent additional spending to address poor outcomes in this population. Understanding the relationship between a hospital’s costs of care and outcomes achieved has critical implications for patients, health care payers, and policy makers. If costs and outcomes have a strong, positive correlation, providing highquality health care may require greater health care spending. Conversely, if a strong, negative correlation exists, directing patients towards greaterquality hospitals could simultaneously improve outcomes and lesser costs. To better describe this relationship, we studied patients undergoing colon resection for a diagnosis of cancer to determine the relationship between a hospital’s costs of care relative to the outcomes achieved. Given previous literature showing a high degree of variation in both costs and outcomes, we hypothesized that hospital-level costs would vary across hospitals without a significant relationship to the outcomes achieved. METHODS We conducted a retrospective cohort study using administrative data from the 2009–2010 California (CA), Florida (FL), and New York (NY) state inpatient databases.11 These data are compiled at the state-level from administrative, clinical, and billing information, standardized across states, and made publically available through the Healthcare Cost and Utilization Project (HCUP).12 The inpatient databases are a census of discharges from all acute care, nonfederal, community hospitals. Each discharge abstract contains up to 25 International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) procedure and diagnostic codes, as well as patient demographic, anticipated payer, and discharge disposition data. These states were selected for analysis because of their geographic diversity, availability of encrypted identifiers allowing for the longitudinal study of patients’ health care use including readmissions, and their large populations, which collectively accounted for 24.4% of the US adult population in 2010.13 Importantly,
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because these are state databases, we are able to capture outcomes of readmissions and costs across different hospitals, not only those that occur at the index hospitalization of the procedure. Patient selection. We identified discharges for state residents at least 18 years of age who had a valid encrypted patient identifier and underwent colon resection (ICD-9-CM 17.3x, 45.7x, 45.8, 45.81, 45.82, 45.83) for colon cancer (ICD-9-CM 230.3, 153.x) between July 2009 and September 2010. From this population (N = 22,017), we sequentially excluded discharges where the discharge disposition was recorded as missing or left against medical advice (n = 158). Next, we excluded patients with evidence of metastatic disease (n = 3,480) and those who underwent concurrent liver resection (n = 27). This step was performed because these patients likely represent a subgroup with different mortality and readmission risks for which it would be difficult to adjust in subsequent analyses. Because the focus of this study included an analysis of costs, we excluded patients for whom the total hospital charges were missing (n = 1,715). Finally, we excluded patients treated at hospitals reporting fewer than 15 cases during the study period, less than 1 per month, to focus on hospitals actively performing colon resection for cancer and to allow for a stable estimate of costs and outcomes (n = 1,728; see Appendix for a tabular view of the patient selection process). Outcome measures. We evaluated three hospital-level, risk-standardized outcomes: (1) inhospital mortality; (2) hospital readmission within 30 days; and (3) 30-day hospital costs. These outcomes and the time period studied were selected because of their prominence in current public reporting efforts.4 In-hospital mortality is a defined variable from the state inpatient databases. Among patients who did not die during the initial hospitalization, hospital readmissions were identified from the state inpatient databases by the use of encrypted patient identifiers. To avoid including hospital admissions that may be part of a planned treatment course, we did not include hospital admissions that did not originate in the emergency department or had a primary diagnosis of maintenance radiation or chemotherapy, rehabilitation services, cancer, or normal obstetric delivery. Hospital readmissions that originated in the emergency department were included regardless of primary discharge diagnosis. All readmissions were then attributed to the index hospital where colon resection was performed. To evaluate a hospital’s costs of providing care, we added the total hospital charges from the initial inpatient encounter with charges incurred during
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all subsequent hospital readmissions that met our criteria within 30 days. These charges were then converted to costs using the HCUP cost-to-charge ratio file14 and adjusted for inflation to 2010 US dollars.15 Similar to the hospital readmission measure, hospital cost assessment was limited to those patients who survived the hospitalization. Covariates for description and risk adjustment. At the time of surgery, we recorded a patient’s age, sex, anticipated primary payer (Medicare, Medicaid, Private, Other), and state of residence (CA, FL, or NY). Using primary and secondary procedure coding, we estimated the extent of disease (in situ, invasive node negative, or invasive node positive), anatomic resection (right colon, left colon, total or transverse colon, and other), whether an ostomy was created, whether the surgery was performed during an elective admission, and whether the surgical approach was laparoscopic or open. We assessed the degree of chronic medical comorbidity according to the enhanced-Elixhauser16 algorithm described by Quan et al,17 which identifies 31 chronic medical conditions. A condition was considered present if it was a listed diagnosis during the initial hospitalization for colon resection or at any inpatient discharge in the previous 6 months. Calculating risk-standardized rates. We constructed 2-level (patient and hospital) hierarchical generalized linear models similar to methods used by the Center for Medicare and Medicaid Services18 with a binary distribution specified for in-hospital mortality and hospital readmission and a gamma distribution specified for costs. Next, we entered the aforementioned covariates as independent variables into two separate regression models, one for each dichotomous outcome. Using a backward selection process with a retention P-value of .05, we created the most parsimonious models. All authors then reviewed these variables to ensure they were clinically appropriate and were consistent with existing literature. The final model for inhospital mortality included age, sex, primary payer, 11 chronic conditions, anatomic resection, concurrent ostomy, and surgical approach (c-statistic = 0.885). The final model for 30-day readmission included another 15 chronic conditions, extent of disease, and whether the surgery was performed during an elective admission (c-statistic = 0.646). In addition, the model for hospital costs included variables to account for regional wage variations and a geographic adjustment factor which are available in the HCUP cost-to-charge ratio file.14 The second level of the model included hospital-level random intercepts to account for clustering of patients
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within hospitals and permit separation of the within and between hospital variation in outcomes after accounting for patient characteristics. The predictedto-estimated ratio obtained from these models was then multiplied by the mean, unadjusted outcome rate among all hospitals included in the study to yield the risk-standardized rates. Statistical analysis. The relationship between hospital outcomes and costs was assessed in three ways. First, we graphically assessed the data by using bubble charts with 30-day readmission rates on the x-axis; in-hospital mortality on the y-axis; and allowing the size of each ‘‘bubble’’ to vary directly with the 30-day hospital costs (ie, larger bubbles indicate greater costs). This allowed for hospitals performing well on both measures to be readily seen, along with their associated costs of care. Next, we calculated correlation coefficients for the relationship between each outcome and costs, weighting for hospital volume. Finally, we classified hospitals as low, average, and high performers. This was done by stratifying hospitals into quintiles of performance for both in-hospital mortality and 30-day readmission. Hospitals that were in the two lowest quintiles for each outcome were considered ‘‘low performers,’’ whereas those in the top two performing quintiles for both outcomes were considered ‘‘high performers.’’ All other hospitals were considered ‘‘average performers.’’ Risk-standardized 30-day hospital costs were then compared across performance groups with the use of generalized linear models. As an exploratory analysis, we compared selected hospital characteristics, operative variables, and inhospital outcomes between high-quality, low-cost hospitals (hospitals in the top two performing quintiles for both outcomes and costs); lowquality, high-cost hospitals (hospitals in the bottom two performing quintiles for both outcomes and costs); and the remaining hospitals in the sample. In-hospital outcomes included observed complication rates based on a previously described coding algorithm19,20 and duration of stay. All analyses were conducted using SAS version 9.3 (SAS Institute, Cary, North Carolina). Because this study used publicly available data that does not include patient identifiers, it was considered exempt from review by the Wright State University and Washington University in St. Louis Institutional Review Boards. RESULTS The final sample included 14,790 patients who underwent surgery at 389 hospitals in three states. The average patient age was 72.0 years with a similar
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Table I. Description of the sample n Patients Age in years, median (SD) Sex Male Female Missing Primary payer Medicare Medicaid Private Other State of residence California Florida New York Extent of disease In situ Invasive, node negative Invasive, node positive Anatomic resection Right colon Left colon Total or transverse Other Ostomy Elective Laparoscopic Outcomes In-hospital mortality Hospital readmission in 30 days Hospital costs in 2010 US$, mean (interquartile range)
%
14,790 72.0
100.0 13.2
6,907 7,833 50
46.7 53.0 0.3
9,598 921 3,663 608
64.9 6.2 24.8 4.1
5,279 5,264 4,247
35.7 35.6 28.7
239 11,875 2,676
1.6 80.3 18.1
8,527 4,514 1,260 489 1,053 9,592 7,248
57.7 30.5 8.5 3.3 7.1 64.9 49.0
314 1,775 19,031
2.1 12.3 18,597
number of male (46.7%) and female (53.0%) patients. Most patients underwent a right hemicolectomy (57.7%) for invasive, node negative adenocarcinoma (80.3%) during an elective admission (64.9%). The laparoscopic approach was used in 49% of cases. During hospitalization, 314 (2.1%) patients died. Of those who survived to discharge, the 30-day readmission rate was 12.3% and the median 30-day hospital’s costs of care were $19,031 (interquartile range [IQR] = $18,597; see Table I). Variation in hospital-level risk-standardized outcomes. Among the 389 hospitals studied, variation in the risk-standardized outcome rates was noted. The median, risk-standardized in-hospital mortality rate was 1.8% (IQR = 2.3%) and the 30-day readmission rate was 12.2% (IQR = 0.7%). Similarly, there was substantial variation in the risk-standardized 30-day hospital costs. The median 30-day hospital costs for colon resection was $26,169 (IQR = $6,559), with hospitals above the 90th percentile for costs
Table II. Variation in hospital-level riskstandardized outcomes across 389 hospitals in three states
100% max 99% 95% 90% 75% Q3 50% median 25% Q1 10% 5% 1% 0% min Interquartile range
Riskstandardized 30 day readmission rates, %
Riskstandardized in-hospital mortality rates, %
Riskstandardized costs of care (2010 US$)
14.2 14.1 13.4 13.1 12.6 12.2 11.9 11.5 11.4 10.9 10.6 0.7
14.7 8.7 6.9 5.2 3.5 1.8 1.2 0.9 0.9 0.7 0.6 2.3
43,711 41,960 35,120 32,891 28,020 25,113 21,407 18,610 17,252 15,574 14,992 6,613
($34,457) having average costs 70% greater than those below the 10th percentile of costs ($18,160; see Table II). When a hospital’s outcomes are visualized relative to its costs, four groups of hospitals can be identified (see Fig 1). First, there are a group of hospitals that have in-hospital mortality and readmission rates less than the median rate for the overall sample (lower left quadrant in Fig 1). Conversely, some hospitals have in-hospital mortality and readmission rates that appear greater than the median rates (upper right quadrant in Fig 1). Finally, the remaining hospitals perform well on one measure, but worse on the other when compared to the median outcome rates (upper left and lower right quadrants in Fig 1). Most notably, there are both high- and low-cost hospitals within each quadrant. Relationship between hospital’s costs and outcomes. In the overall sample, there was an inverse relationship between a hospital’s costs and the riskstandardized in-hospital mortality rate (volume weighted r2 = 0.02, P-value < .01). However, a positive relationship was noted between a hospital’s costs and the risk-standardized readmission rate (volume weighted r2 = 0.01, P = .05). Although statistically significant in both cases, the magnitude of the relationship was minimal. When hospitals were categorized into low (N = 63), average (N = 263), and high (N = 63) performing, no substantial difference in costs was noted between groups (low performing = $25,994 vs
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Fig 1. Hospital-level variation in risk-standardized in-hospital mortality (y-axis) and 30-day readmission (x-axis) rates where the size of a hospital’s bubble is directly related to its risk-standardized costs of care. The median rate for each outcome is indicated by the dashed lines. Hospitals in the left lower quadrant have rates less than the median for both outcomes whereas those in the right upper quadrant have rates greater than the median for both outcomes. Average costs for selected hospitals are shown to highlight variation in costs relative outcomes. For example, hospital A has 23% lesser 30-day costs than hospital B, but a greater than 6-fold higher mortality rate.
Fig 2. Variation in risk-standardized costs of care (2010 $U.S.) across high (top panel)-, average (middle panel)-, and low (bottom panel)-performing hospitals.
average = $26,998 vs high = $25,794, P = .19) with wide cost variation seen within each group (see Fig 2). These same analyses were performed at the state level and yielded similar findings. In this case, no significant correlation was noted between a hospital’s risk-standardized in-hospital mortality rate, 30-day readmission rate, and 30day hospital costs in California, Florida, or New
York. Similarly, after categorizing hospitals by low, average, and high performing, there was no difference in hospital costs for any state (see Fig 3). Similar findings were obtained when limiting the definition of hospital costs to the initial discharge when surgery was performed. Characteristics of high-quality, low-cost hospitals. As an exploratory analysis, we compared
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Fig 3. Variation in risk-standardized costs of care (2010 $U.S.) across high (left-most box in group)-, average (center box in group)-, and low (right-most box in group)performing hospitals stratified by state (CA, California; FL, Florida; and NY, New York). In these plots, the top edge of the box represents the 75th percentile; the line within the box, the median or 50th percentile; and the lower edge of the box the 25th percentile of hospital’s costs. The ends of the ‘‘whiskers’’ depict the minimum and maximum values, excluding outliers (circles).
selected hospital characteristics between hospitals achieving both high-quality and low costs to lowquality, high-cost hospitals and all other hospitals in the sample. As anticipated, high-quality, low-cost hospitals had the lowest in-hospital mortality (1.1% vs 2.7% vs 3.9%, P < .01), 30-day readmissions (11.6% vs 12.3% vs 12.9%, P < .01), and 30-day hospital costs ($21,439 vs $26,186 vs $32,110, P < .01). High-quality, low-cost hospitals trended toward having a larger percentage of Medicare beneficiaries in their treatment population (70.0% vs 63.5% vs 64.4%, P = .11) and performing fewer laparoscopic cases (36.5% vs 45.5% vs 51.1%, P = .05). In addition, high-quality, low-cost hospitals had a substantially lesser observed complications rate (21.8% vs 22.2% vs 29.8%, P < .01) and a trend toward shorter hospitalizations (8.7 days vs 9.0 days vs 9.8 days, P = .21; Table III). DISCUSSION A hospital’s costs of providing colon resection for cancer is not related to the quality of care achieved when measured by risk-standardized inhospital mortality and 30-day readmission rates. Despite accounting for differences in the patient populations being treated and geographic cost influences, the average costs for providing a colon resection varied nearly 3-fold across hospitals from as low as $15,450 to as high as $47,897. These greater costs, however, did not meaningfully
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correlate with lesser in-hospital mortality or fewer frequent hospital readmissions after discharge. Furthermore, variation in hospital costs was noted within groups of high- and low-performing hospitals. These findings, including the variation in costs of care and its inconsistent relationship with outcomes, were noted in each state included in the study. As the costs of providing cancer care continue to climb, it will become increasingly important to identify best practices which allow for high-quality care to be achieved at less cost. In the current study, we found wide cost variations even among high-quality hospitals. Previous studies have evaluated characteristics of high-quality, low-cost hospitals and described differences in management practices, ownership status, and patient populations.21,22 We found that for patients undergoing colon resection, high-quality, low-cost hospitals treated a greater proportion of Medicare beneficiaries and approached fewer cases via the laparoscopic approach. This raises concerns about the role technology plays in increasing costs of care, particularly in cases where patient benefit has been demonstrated in clinical trials.23,24 Of note, we did find that high-quality, low-cost hospitals tended to have shorter hospitalizations and lesser observed complication rates. While our study and others have focused on characteristics of these hospitals, further research is needed to understand hospital practices that may be used at other institutions. For patients with cancer undergoing surgery, providing both cost and quality data may facilitate more informed health care decision-making.25 The costs of cancer treatment are a known financial burden on patients26 and can impact their treatment decisions.27 Some authors have described these costs as a ‘‘side effect’’ of treatment to be discussed with patients.28 Currently, there is a paucity of data on which to base these conversations, but our findings suggest meaningful conversations could be had. Some private companies are developing patient-centered tools to help patients ‘‘shop for health care’’ according to cost and quality,29 but similar tools are not yet widely, or publicly, available. However, health care payers who already publically report both average costs and similar outcomes, including the Centers for Medicare & Medicaid Services,4,30 have an opportunity to merge these data into a single, patientcentered format. Beginning in 2015, the Centers for Medicare & Medicaid Services will combine hospital costs and outcomes data into a total performance score to
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Table III. Characteristics of high-quality, low-cost hospitals High-quality, low-cost* Hospitals Quality and cost In-hospital mortality (risk standardized) Readmission rate (risk standardized) Median costs, 2010 US$ (risk adjusted) Patient population Average age, y Medicare, % Operative variables Median procedure volume (during study period) Elective, % Laparoscopy rate, % In-hospital outcomes Complication rate (observed), % Duration of stay (observed)
27
All other hospitals 342
Low-quality, high-costy 20
P value — <.01 <.01 <.01
1.1% 11.6% 21,439
2.7% 12.3% 26,186
3.9% 12.9% 32,110
70.7 70.0
70.5 63.5
70.9 64.4
.62 .11
32.0 56.1 36.5
32.0 63.0 45.5
35.0 61.5 51.1
.37 .14 .09
21.8 8.7
22.2 9.0
29.8 9.8
<.01 .21
*Hospitals in the top two performing quintiles for in-hospital mortality, 30-day readmission, and hospital costs. yHospitals in the bottom two performing quintiles for in-hospital mortality, 30-day readmission, and hospital costs.
determine for the purpose of reimbursement penalties or rewards under the value-based purchasing program.1 Specifically, this score will be derived from patient satisfaction scores, process measure adherence, clinical outcomes, and Medicare spending per beneficiary.31 Greater performance and lesser costs will increase a hospitals total performance scores. In this formula, greater cost hospitals could ‘‘lose points’’ in the efficiency domain, but gain points by achieving greater quality. Conversely, low-quality hospitals would ‘‘lose points’’ in the quality domain but recoup points for being low cost. Although a composite measure of cost and quality simplifies hospital performance into a single number, it also poses a problematic question: how much should low quality be offset by low costs? For example, based on Fig 1, we found hospital A has 23% lesser 30-day costs than hospital B, but a greater than 6-fold greater mortality rate. The extent to which the lesser costs offset the poor quality could lead hospital’s A and B to have similar total performance scores. More research is needed to develop methods by which a hospital’s costs and outcomes can be concurrently measured and communicated to minimize this potential. This study should be viewed in the context in the several limitations. First, we defined costs based on those experienced at the hospital during the index admission and subsequent readmissions. This did not capture cost data from any emergency department visits or surgeon’s office encounters. We focused on hospital costs because our outcomes were hospital-based, current efforts focus
on disclosing hospital costs, and the availability of data. Although this limitation could affect our findings on the variation of costs in either direction, the absolute costs of our estimates are therefore necessarily conservative. Second, these findings should be viewed within the 30-day time period, consistent with current quality measurement efforts. The relationship between outcomes and costs may be altered if shorter or longer time periods are used. Similarly, evaluating different outcomes in lieu of mortality or readmission may influence the relationship between costs and ‘‘quality.’’ As mentioned, we selected these outcomes based on the commonality of the outcomes across current quality measurement efforts. Third, it is possible that some patients (eg, Veterans Affairs patients) may receive their primary care at a federal hospital and only received their primary surgery at a non-federal hospital due to lack of surgical capacity at their primary place of care. These patients, therefore, may appear to have low costs of care when they may, in fact, be readmitted to their primary Veterans Affairs or federal hospital for complications. Finally, we cannot exclude that some variation in charges, and ultimately costs, may be related to factors for which we do not have variables and therefore cannot include in the riskstandardized models. In conclusion, hospital costs of care and quality for patients undergoing colon resection for cancer varies widely without a substantial correlation between these outcomes. Efforts focused on purchasing value in this population should consider directly assessing costs in the setting of quality.
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REFERENCES 1. Centers for Medicare & Medicaid Services (CMS), HHS. Medicare and Medicaid programs: Hospital Outpatient Prospective Payment and Ambulatory Surgical Center Payment Systems and Quality Reporting Programs; Hospital ValueBased Purchasing Program; organ procurement organizations; quality improvement organizations; Electronic Health Records (EHR) Incentive Program; provider reimbursement determinations and appeals. Final rule with comment period and final rules. Fed Regist 2013;78:74825-5200. 2. Ghaferi AA, Birkmeyer JD, Dimick JB. Variation in hospital mortality associated with inpatient surgery. N Engl J Med 2009;361:1368-75. 3. Jha AK, Li Z, Orav EJ, Epstein AM. Care in U.S. hospitals--the Hospital Quality Alliance program. N Engl J Med 2005; 353:265-74. 4. Centers for Medicare and Medicaid Services. Hospital Compare. Available from http://www.medicare.gov/ hospitalcompare/search.html. 5. Porter ME. What is value in health care? N Engl J Med 2010; 363:2477-81. 6. Stukel TA, Fisher ES, Alter DA, et al. Association of hospital spending intensity with mortality and readmission rates in Ontario hospitals. JAMA 2012;307:1037-45. 7. Birkmeyer JD, Gust C, Dimick JB, Birkmeyer NJ, Skinner JS. Hospital quality and the cost of inpatient surgery in the United States. Ann Surg 2012;255:1-5. 8. Fox JP, Desai MM, Krumholz HM, Gross CP. Hospital-level outcomes associated with laparoscopic colectomy for cancer in the minimally invasive era. J Gastrointest Surg 2012;16:2112-9. 9. Hansen DG, Fox JP, Gross CP, Bruun JS. Hospital readmissions and emergency department visits following laparoscopic and open colon resection for cancer. Dis Colon Rectum 2013;56:1053-61. 10. Miller DC, Gust C, Dimick JB, Birkmeyer N, Skinner J, Birkmeyer JD. Large variations in Medicare payments for surgery highlight savings potential from bundled payment programs. Health Aff (Millwood) 2011;30:2107-15. 11. Healthcare Cost and Utilization Project (HCUP). Overview of the State Inpatient Databases (SID). Available from http://www.hcup-us.ahrq.gov/db/state/siddbdocumenta tion.jsp. 12. Agency for Healthcare Research and Quality. Overview of HCUP. Available from http://www.hcup-us.ahrq.gov/over view.jsp. 13. The Website Services & Coordination Staff UCB. Census Bureau Home Page. Available from http://www.census.gov/#. 14. HCUP-US Cost-to-Charge Ratio Files. Available from http://www.hcup-us.ahrq.gov/db/state/costtocharge.jsp. 15. How BLS Measures Price Change for Medical Care Services in the Consumer Price Index. Available from http://www. bls.gov/cpi/cpifact4.htm. 16. Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care 1998; 36:8-27. 17. Quan H, Sundararajan V, Halfon P, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 2005;43:1130-9. 18. Krumholz HM, Wang Y, Mattera JA, et al. An administrative claims model suitable for profiling hospital performance based on 30-day mortality rates among patients with an acute myocardial infarction. Circulation 2006;113:1683-92. 19. Ghaferi AA, Birkmeyer JD, Dimick JB. Complications, failure to rescue, and mortality with major inpatient surgery in Medicare patients. Ann Surg 2009;250:1029-34.
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20. Iezzoni LI, Daley J, Heeren T, et al. Identifying complications of care using administrative data. Med Care 1994;32: 700-15. 21. Jiang HJ, Friedman B, Begun JW. Factors associated with high-quality/low-cost hospital performance. J Health Care Finance 2006;32:39-52. 22. Jha AK, Orav EJ, Epstein AM. Low-quality, high-cost hospitals, mainly in South, care for sharply higher shares of elderly black, Hispanic, and Medicaid patients. Health Aff (Millwood) 2011;30:1904-11. 23. Clinical Outcomes of Surgical Therapy Study Group. A comparison of laparoscopically assisted and open colectomy for colon cancer. N Engl J Med 2004;350:2050-9. 24. Veldkamp R, Kuhry E, Hop WC, et al. Laparoscopic surgery versus open surgery for colon cancer: short-term outcomes of a randomised trial. Lancet Oncol 2005;6:477-84. 25. Huckman RS, Kelley MA. Public reporting, consumerism, and patient empowerment. N Engl J Med 2013;369:1875-7. 26. Elkin EB, Bach PB. Cancer’s next frontier: addressing high and increasing costs. JAMA 2010;303:1086-7. 27. Lee MC, Bhati RS, von Rottenthaler EE, et al. Therapy choices and quality of life in young breast cancer survivors: a short-term follow-up. Am J Surg 2013;206:625-31. 28. Ubel PA, Abernethy AP, Zafar SY. Full disclosure---out-ofpocket costs as side effects. N Engl J Med 2013;369:1484-6. 29. Castlight Health. Available from http://www.castlight health.com/solutions/. 30. Centers for Medicare & Medicaid Services. Medicare Provider Utilization and Payment Data. 2014. Available from http://www.cms.gov/Research-Statistics-Data-and-Systems/ Statistics-Trends-and-Reports/Medicare-Provider-ChargeData/index.html. 31. Centers for Medicare & Medicaid Services. National Provider Call: Hospital Value-Based Purchasing. Available from http://www.cms.gov/Outreach-and-Education/Outre ach/NPC/Downloads/HospVBP_FY15_NPC_Final_030520 13_508.pdf.
DISCUSSION Dr Mark Hemmila (Ann Arbor, MI): Dr Fox and colleagues conclude that there is a substantial variation in risk-standardized cost---median $26,000 and interquartile range of $6,500---however, there is minimal correlation of cost to hospital outcome. Costs were similar across the low-, average-, and high-performance groups in the paper. I have three questions for Dr Fox. In the paper, it was covered, but not so much here. I was surprised to see that your high-performance, low-cost group had an absolute difference of 10 percentage points less of patients who had an operation performed laparoscopically. What do you think accounted for better outcomes and reduced cost in this group? Second, based on your data analysis, if you were a payor, how would you proceed? Do you have any payment data relative to cost? In the end, it’s the payments made relative to the outcomes achieved that determines the value of the surgical service provided, not necessarily the costs. Costs are borne by the hospital.
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Third, what accounted for the differences in charges among the high-quality, low-cost hospitals versus the average or low performers? Was it the operating room costs, or postdischarge costs? It does not seem to be related to the duration of stay because both groups were the same. Dr Justin P. Fox: I am going to start with the comment toward the end of the second question, where when we look at value in health care, it’s very much like beauty. It is in the eye of the beholder. Different people will say that quality should be measured with different outcomes and maybe disagree with mortality and readmission rates. What outcomes we may be measuring may not be as important to the patient. Patients may, if you ask them, identify different outcomes that are important to put in that quality threshold. Considering cost, it’s the cost to who? You’re absolutely right. The cost to the hospital? The cost to the patient? Or what’s being actually paid out? And these are all the challenges in studying value in health care. The value is very much dependent on what perspective you are looking at from. There were some additional things that I realized I wanted to present but did not have the space to do so. We had grouped hospitals, trying to get to the idea of who are the high-quality, low-cost hospitals versus all the others. There are some characteristics we can look at. In the paper, this is very much an exploratory analysis but raises some interesting points. Here in the table, you can see quality and cost by design were different between the two groups of hospitals. You can see the demographics here. We talked about the comment on the laparoscopy rate, where it appeared that high-quality, lowcost hospitals approached fewer of their cases laparoscopically than did all the other hospitals. The outcomes here were the observed outcomes. I went back and risk standardized those, and the risk-standardized complication rate and length of stay was substantially less in the highquality, low-cost group versus the others. I apologize about that. Although statistically relevant, the absolute magnitude difference between the percentages was smaller. To get specifically to the laparoscopy rate, what is the role there? To be honest with you, it’s tough to say. I think it does speak to the point that was brought up, the discussion from the last presentation, that if you maximize potentially enhanced recovery pathways in this patient population, you may still be able to get patients out a little earlier, which was shown, again, with the length of stay
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being a little bit shorter, and maybe that influences your costs as well. As far as line item charges, we don’t have that for these data right now, but I’m working on some specific things to look at, OR times and specific charges, like do not high-quality, low-cost hospitals, but the other group, do they have more use of ancillary services and other things driving up costs? We are working on that now. Dr Gerald Larson (Louisville, KY): This, with the Affordable Care Act now coming into play, is being presented and discussed more and more in the media. We recently had an article in our local paper about the cost of splenectomy at three different hospitals, and the range was quite wide, and the hospital administrator said several explanations. One was that you just can’t look at one procedure in terms of the coverage plan that an insurance policy might provide. But you are defining high quality. How are you defining high quality? Is it mainly the readmission rate and the mortality? And let me then go from colectomy to a different example: inguinal hernia repair. A hospital could have a very low mortality, the readmission rate could be zero, but the surgeon could do a mediocre or poor job, and the recurrence rate on that inguinal hernia might be 20% in 5 years or 10 years. Don’t you have to include more factors when you are describing or defining high quality? Dr Justin P. Fox: I agree with you. First, the way we defined high-quality and low-cost hospital in this paper. We took the risk-standardized readmission, in-hospital mortality, and cost data, stratified the hospitals by quintiles of performance. If you were in the top two quintiles for each of those outcomes, you are considered high quality, low cost. Everybody else was put into the other group. There are different ways to do this and different payors actually have their own method of identifying the high quality, low cost. This was the way we chose to do it here. As far as getting to how do you define high quality, I think that it needs to be procedure-specific. I think when we try to group a bunch of procedures together, it’s problematic from a method standpoint. For the hernia example, in-hospital mortality, I hope for any outpatient inguinal hernia is very low. The readmission rate should be low as well. Looking at those as a definition of quality for an inguinal hernia probably doesn’t mean as much as maybe for things like esophagectomy, Whipple, and maybe even colectomy. In that case, I think there are potentially other things that need to be examined for procedures like that.
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Dr Gerald Larson (Louisville, KY): Then I have one other practical question and maybe extension of this situation. As patients now might be spending their own money for the first 2 or $3,000, whatever that deductible is, they might go shopping, and they’ll find out their research indicates that they should go to hospital A, but they find out that their family doctor and their surgeon, whom he recommends, or the patient might actually want to go to, they don’t go to hospital A, they work at hospital B or C. So you have this inherent conflict. How do you see that playing out? Dr Justin P. Fox: I think there’s two important things there. They are both great points, the first being there are no data with which you can have this discussion with patients right now. What is being reported out at least publicly, using Ohio for an example, if you go to the Ohio Department of Public Health Web site, you can see for common procedures, at least listed by diagnosis-related group (DRG), which, if you are not in the medical field, and even if you are, understanding what the DRG means to you is difficult. And then they list what the average charge is for that DRG for your given hospital. That has nothing to do with what’s going to come out of your pocket. There are some private companies right now that have tried to reverse-engineer people’s hospital bills based on their insurance. One of them is Castlight in California, which is a private company making their service available largely to employers so that patients can try to understand what their out-of-pocket costs will be, not just what the average charge is. Even if they see the average charge is cheaper at hospital A versus hospital B, that may not be true for them. The next thing, I think it’s to quality and what’s actually important to patients. What may be important to patients is going to providers or surgeons or where their family practice doctor practices is more important to them and they’re worth spending that money. And so I think that that, right or wrong, is maybe a decision that patients have to make as this information becomes more available, and hopefully more tailored toward the individual patient. Dr Gerald Fried (Montreal): Just two brief questions to get back to what Jerry Larson was just asking. If we have a model of cost and quality when we talk about colectomy, which is for cancer, then 5-year survival or some measure of the actual reason that you are doing the surgery has to go into the quality initiative, because if you get a person out without killing them and they don’t get readmitted, but your 5-year survival is twice as bad as
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the hospital down the street, that’s an important aspect of quality that we as surgeons, physicians, must put on the table. The second point that I would like to make is I think when you look at two groups that have equivalent quality, and one is being able to provide that for substantially less cost, it really is very informative to try to look at dissecting where those cost differences come and to try to actually look at how we can then use that information to perhaps inform best practices. There may be actual true efficiencies and costs that we could then communicate without impacting quality and actually make sure that the money that we spend is well spent. Dr Justin P. Fox: I agree. In terms of defining the quality, again, this is why I think value is in the eyes of the beholder and what you put in defining quality. Do you put a composite measure? Do you look at individual measures? That is important. For cancer surgery, if we put things like 5-year survival, which is very important, certainly, for any cancer surgery, in that model and you pin it back to the hospital, we have to assume that there are things within the hospital’s control that can account for that survival, regardless of that, chemotherapy, radiation therapy, depending on what kind of cancer we are talking about, what type of adjuvant therapy is going into it, too, which may also impact the quality. If we do that, which I’m not saying right or wrong, I think it would potentially encourage more collaboration between the hospitals and the other providers, which may be a good thing and also important to the patients, making that data available. Dr Justin P. Fox: I think that the data that we have, whether it’s the ACS NSQIP data or the HCUP data used here, or really any administrative database, you can get to a certain level of granularity, and then you kind of hit a wall. My next step is to look at individual line item charges to try to figure out where some of the differences are in charges. I think, really, it’s going to come down to it would be nice to say, your hospital provides high quality at a low cost. We would like to learn how you do that. Being able to collaborate between the providers, whether it’s surgeons, physicians, and the hospital administration to say, why is it that we provide high quality and low cost? What is it that we would do that’s different? And I think in that collaboration, maybe being encouraged by outside monitoring, when that comes together, we will really be able to maybe streamline some processes and identify some things that can be translated across hospitals.
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Dr Ashraf Mansour (Grand Rapids, MI): I think everybody in the audience here suspects that the next step is going to be physicians and surgeons, everybody is going to have a report card. I don’t know where it is going to be taken, but these data already are being collected in the state of Michigan. I don’t know if it’s elsewhere. Can you comment? Dr Justin P. Fox: Comment on the physician-level or surgeon-level outcomes? In the state of Pennsylvania, for example, for coronary artery bypass grafting, and I believe in California as well, individual mortality rates, the surgeon-level mortality rates are being
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publicly reported. You can look them up in the Web site now. I know Michigan does quite a lot with surgical outcomes research. My personal bias, I have some hesitancy in that because there’s a lot that goes into mortality, in particular in the perioperative period above and beyond what’s done in the operating room for the perioperative care. I very much believe it’s a team effort, and that when you pin it down to the surgeon level, I think it causes some problems, and it kind of leaves other people out of the mix that maybe should be included.
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Appendix. Discharge selection process All discharges for state residents at least 18 years of age with a valid patient identifier who underwent colon resection for colon cancer between July 2009 and September 2010 Excluding discharges with missing discharge disposition Remaining Excluding discharges where the patient was transferred to another facility Remaining Excluding discharge where patient left against medical advice Remaining Selecting the first discharge for patients with more than one qualifying discharge meeting the aforementioned criteria Remaining Excluding patients with evidence of metastatic disease Remaining Excluding patients with a concurrent liver resection Remaining Excluding patients with missing total charges data Remaining Excluding patients treated at hospitals reporting fewer than 15 colon resections during the study period Final
N
%
22,017
100.00
19 21,998 113 21,885 26 21,859 119
0.09 99.91 0.51 99.49 0.12 99.88 0.54
21,740 3,480 18,260 27 18,233 1,715 16,518 1,728
99.46 16.01 83.99 0.15 99.85 9.41 90.59 10.46
14,790
89.54
Introduction. Although hospital variation in costs and outcomes has been described for patients undergoing operation, the relationship between them is unknown. The purpose of this study was to evaluate this relationship among patients undergoing colon resection for cancer and identify characteristics of ‘‘high-quality, low-cost’’ hospitals. Methods. We identified adult patients who underwent colon resection for cancer in California, Florida, and New York from 2009 to 2010. We estimated hospital-level, risk-standardized 30-day hospital costs, in-hospital mortality rates, and 30-day readmission rates by using hierarchical generalized linear models. Costs were compared between hospitals identified as low, average, and high performers. Results. The final sample included 14,790 patients discharged from 389 hospitals. After adjusting for case mix, variation was noted in risk-standardized costs (median = $26,169, inter-quartile range [IQR] = $6,559), in-hospital mortality (median = 1.8%, IQR = 2.3%), and 30-day readmission (12.2%, IQR = 0.7%) rates. Minimal correlation was noted between a hospital’s costs and outcomes, with similar costs noted across hospital performance groups (low = $25,994 vs average = $26,998 vs high = $25,794, P = .19). High-quality, low-cost hospitals treated a greater percentage of Medicare beneficiaries, approached fewer cases laparoscopically, and trended toward greater volume. Conclusion. Hospital costs are not correlated with outcomes in this population. More work is needed to identify means of providing high-quality care at lesser costs. (Surgery 2014;156:849-60.) From the Department of Surgery,a Boonshoft School of Medicine, Wright State University, Dayton, OH; Section of Colon and Rectal Surgery, Division of General Surgery,b Washington University School of Medicine, St. Louis, MO; VA Palo Alto Healthcare System,c Palo Alto; and Department of Emergency Medicine,d University of California San Francisco, San Francisco, CA
VALUE-BASED PURCHASING is a strategy used by employers, and increasingly the federal government, to use their market power to promote quality and value of health care services. This approach holds health care providers accountable for both the cost and quality of care.1 These programs are based on findings that substantial variation exists The views expressed in this article are those of the authors and do not reflect the official policy of the United States Air Force, Department of Defense, or the United States government. This work was accepted for oral presentation at the annual meeting of the Central Surgical Association in Indianapolis, Indiana; March 2014. Accepted for publication June 18, 2014. Reprint requests: Justin P. Fox, MD, MHS, Miami Valley Hospital, One Wyoming Street, Suite 7000 WCHE, Dayton, OH 45409. E-mail: [email protected]. 0039-6060/$ - see front matter Ó 2014 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.surg.2014.06.011
in the quality of health care provided by US hospitals that is not explained completely by differences in patient populations.2,3 Most commonly, the quality measures being used are conditionspecific, hospital-level mortality and readmission rates.4 Purchasing ‘‘value’’ in health care also suggests obtaining high quality at reasonable costs5; however, the relationship between health care quality and a hospital’s costs of providing care is unclear, with some studies suggesting that greater spending is required to improve outcomes,6 whereas others have found achieving better outcomes reduce costs.7 Among patients undergoing colon resection for cancer, the perioperative outcomes achieved and the hospital’s cost of providing that care are partly related to the hospital where a patient is treated. For example, the average in-hospital mortality and 30-day readmission rate in this population is 1% and 12%, respectively. Previous studies, however, have demonstrated wide variation in these average SURGERY 849
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rates despite adjustments for case mix. In these studies, the in-hospital mortality and 30-day readmission rate vary 3- to 4-fold across hospitals.8,9 Similar to clinical outcomes, a hospital’s costs associated with performing colon resection can fluctuate by as much as $3,000 in the Medicare population alone.10 Although both costs and outcomes have been evaluated, it is unknown whether these outcomes are correlated. Specifically, it is unclear whether greater costs are required for greater quality or may represent additional spending to address poor outcomes in this population. Understanding the relationship between a hospital’s costs of care and outcomes achieved has critical implications for patients, health care payers, and policy makers. If costs and outcomes have a strong, positive correlation, providing highquality health care may require greater health care spending. Conversely, if a strong, negative correlation exists, directing patients towards greaterquality hospitals could simultaneously improve outcomes and lesser costs. To better describe this relationship, we studied patients undergoing colon resection for a diagnosis of cancer to determine the relationship between a hospital’s costs of care relative to the outcomes achieved. Given previous literature showing a high degree of variation in both costs and outcomes, we hypothesized that hospital-level costs would vary across hospitals without a significant relationship to the outcomes achieved. METHODS We conducted a retrospective cohort study using administrative data from the 2009–2010 California (CA), Florida (FL), and New York (NY) state inpatient databases.11 These data are compiled at the state-level from administrative, clinical, and billing information, standardized across states, and made publically available through the Healthcare Cost and Utilization Project (HCUP).12 The inpatient databases are a census of discharges from all acute care, nonfederal, community hospitals. Each discharge abstract contains up to 25 International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) procedure and diagnostic codes, as well as patient demographic, anticipated payer, and discharge disposition data. These states were selected for analysis because of their geographic diversity, availability of encrypted identifiers allowing for the longitudinal study of patients’ health care use including readmissions, and their large populations, which collectively accounted for 24.4% of the US adult population in 2010.13 Importantly,
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because these are state databases, we are able to capture outcomes of readmissions and costs across different hospitals, not only those that occur at the index hospitalization of the procedure. Patient selection. We identified discharges for state residents at least 18 years of age who had a valid encrypted patient identifier and underwent colon resection (ICD-9-CM 17.3x, 45.7x, 45.8, 45.81, 45.82, 45.83) for colon cancer (ICD-9-CM 230.3, 153.x) between July 2009 and September 2010. From this population (N = 22,017), we sequentially excluded discharges where the discharge disposition was recorded as missing or left against medical advice (n = 158). Next, we excluded patients with evidence of metastatic disease (n = 3,480) and those who underwent concurrent liver resection (n = 27). This step was performed because these patients likely represent a subgroup with different mortality and readmission risks for which it would be difficult to adjust in subsequent analyses. Because the focus of this study included an analysis of costs, we excluded patients for whom the total hospital charges were missing (n = 1,715). Finally, we excluded patients treated at hospitals reporting fewer than 15 cases during the study period, less than 1 per month, to focus on hospitals actively performing colon resection for cancer and to allow for a stable estimate of costs and outcomes (n = 1,728; see Appendix for a tabular view of the patient selection process). Outcome measures. We evaluated three hospital-level, risk-standardized outcomes: (1) inhospital mortality; (2) hospital readmission within 30 days; and (3) 30-day hospital costs. These outcomes and the time period studied were selected because of their prominence in current public reporting efforts.4 In-hospital mortality is a defined variable from the state inpatient databases. Among patients who did not die during the initial hospitalization, hospital readmissions were identified from the state inpatient databases by the use of encrypted patient identifiers. To avoid including hospital admissions that may be part of a planned treatment course, we did not include hospital admissions that did not originate in the emergency department or had a primary diagnosis of maintenance radiation or chemotherapy, rehabilitation services, cancer, or normal obstetric delivery. Hospital readmissions that originated in the emergency department were included regardless of primary discharge diagnosis. All readmissions were then attributed to the index hospital where colon resection was performed. To evaluate a hospital’s costs of providing care, we added the total hospital charges from the initial inpatient encounter with charges incurred during
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all subsequent hospital readmissions that met our criteria within 30 days. These charges were then converted to costs using the HCUP cost-to-charge ratio file14 and adjusted for inflation to 2010 US dollars.15 Similar to the hospital readmission measure, hospital cost assessment was limited to those patients who survived the hospitalization. Covariates for description and risk adjustment. At the time of surgery, we recorded a patient’s age, sex, anticipated primary payer (Medicare, Medicaid, Private, Other), and state of residence (CA, FL, or NY). Using primary and secondary procedure coding, we estimated the extent of disease (in situ, invasive node negative, or invasive node positive), anatomic resection (right colon, left colon, total or transverse colon, and other), whether an ostomy was created, whether the surgery was performed during an elective admission, and whether the surgical approach was laparoscopic or open. We assessed the degree of chronic medical comorbidity according to the enhanced-Elixhauser16 algorithm described by Quan et al,17 which identifies 31 chronic medical conditions. A condition was considered present if it was a listed diagnosis during the initial hospitalization for colon resection or at any inpatient discharge in the previous 6 months. Calculating risk-standardized rates. We constructed 2-level (patient and hospital) hierarchical generalized linear models similar to methods used by the Center for Medicare and Medicaid Services18 with a binary distribution specified for in-hospital mortality and hospital readmission and a gamma distribution specified for costs. Next, we entered the aforementioned covariates as independent variables into two separate regression models, one for each dichotomous outcome. Using a backward selection process with a retention P-value of .05, we created the most parsimonious models. All authors then reviewed these variables to ensure they were clinically appropriate and were consistent with existing literature. The final model for inhospital mortality included age, sex, primary payer, 11 chronic conditions, anatomic resection, concurrent ostomy, and surgical approach (c-statistic = 0.885). The final model for 30-day readmission included another 15 chronic conditions, extent of disease, and whether the surgery was performed during an elective admission (c-statistic = 0.646). In addition, the model for hospital costs included variables to account for regional wage variations and a geographic adjustment factor which are available in the HCUP cost-to-charge ratio file.14 The second level of the model included hospital-level random intercepts to account for clustering of patients
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within hospitals and permit separation of the within and between hospital variation in outcomes after accounting for patient characteristics. The predictedto-estimated ratio obtained from these models was then multiplied by the mean, unadjusted outcome rate among all hospitals included in the study to yield the risk-standardized rates. Statistical analysis. The relationship between hospital outcomes and costs was assessed in three ways. First, we graphically assessed the data by using bubble charts with 30-day readmission rates on the x-axis; in-hospital mortality on the y-axis; and allowing the size of each ‘‘bubble’’ to vary directly with the 30-day hospital costs (ie, larger bubbles indicate greater costs). This allowed for hospitals performing well on both measures to be readily seen, along with their associated costs of care. Next, we calculated correlation coefficients for the relationship between each outcome and costs, weighting for hospital volume. Finally, we classified hospitals as low, average, and high performers. This was done by stratifying hospitals into quintiles of performance for both in-hospital mortality and 30-day readmission. Hospitals that were in the two lowest quintiles for each outcome were considered ‘‘low performers,’’ whereas those in the top two performing quintiles for both outcomes were considered ‘‘high performers.’’ All other hospitals were considered ‘‘average performers.’’ Risk-standardized 30-day hospital costs were then compared across performance groups with the use of generalized linear models. As an exploratory analysis, we compared selected hospital characteristics, operative variables, and inhospital outcomes between high-quality, low-cost hospitals (hospitals in the top two performing quintiles for both outcomes and costs); lowquality, high-cost hospitals (hospitals in the bottom two performing quintiles for both outcomes and costs); and the remaining hospitals in the sample. In-hospital outcomes included observed complication rates based on a previously described coding algorithm19,20 and duration of stay. All analyses were conducted using SAS version 9.3 (SAS Institute, Cary, North Carolina). Because this study used publicly available data that does not include patient identifiers, it was considered exempt from review by the Wright State University and Washington University in St. Louis Institutional Review Boards. RESULTS The final sample included 14,790 patients who underwent surgery at 389 hospitals in three states. The average patient age was 72.0 years with a similar
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Table I. Description of the sample n Patients Age in years, median (SD) Sex Male Female Missing Primary payer Medicare Medicaid Private Other State of residence California Florida New York Extent of disease In situ Invasive, node negative Invasive, node positive Anatomic resection Right colon Left colon Total or transverse Other Ostomy Elective Laparoscopic Outcomes In-hospital mortality Hospital readmission in 30 days Hospital costs in 2010 US$, mean (interquartile range)
%
14,790 72.0
100.0 13.2
6,907 7,833 50
46.7 53.0 0.3
9,598 921 3,663 608
64.9 6.2 24.8 4.1
5,279 5,264 4,247
35.7 35.6 28.7
239 11,875 2,676
1.6 80.3 18.1
8,527 4,514 1,260 489 1,053 9,592 7,248
57.7 30.5 8.5 3.3 7.1 64.9 49.0
314 1,775 19,031
2.1 12.3 18,597
number of male (46.7%) and female (53.0%) patients. Most patients underwent a right hemicolectomy (57.7%) for invasive, node negative adenocarcinoma (80.3%) during an elective admission (64.9%). The laparoscopic approach was used in 49% of cases. During hospitalization, 314 (2.1%) patients died. Of those who survived to discharge, the 30-day readmission rate was 12.3% and the median 30-day hospital’s costs of care were $19,031 (interquartile range [IQR] = $18,597; see Table I). Variation in hospital-level risk-standardized outcomes. Among the 389 hospitals studied, variation in the risk-standardized outcome rates was noted. The median, risk-standardized in-hospital mortality rate was 1.8% (IQR = 2.3%) and the 30-day readmission rate was 12.2% (IQR = 0.7%). Similarly, there was substantial variation in the risk-standardized 30-day hospital costs. The median 30-day hospital costs for colon resection was $26,169 (IQR = $6,559), with hospitals above the 90th percentile for costs
Table II. Variation in hospital-level riskstandardized outcomes across 389 hospitals in three states
100% max 99% 95% 90% 75% Q3 50% median 25% Q1 10% 5% 1% 0% min Interquartile range
Riskstandardized 30 day readmission rates, %
Riskstandardized in-hospital mortality rates, %
Riskstandardized costs of care (2010 US$)
14.2 14.1 13.4 13.1 12.6 12.2 11.9 11.5 11.4 10.9 10.6 0.7
14.7 8.7 6.9 5.2 3.5 1.8 1.2 0.9 0.9 0.7 0.6 2.3
43,711 41,960 35,120 32,891 28,020 25,113 21,407 18,610 17,252 15,574 14,992 6,613
($34,457) having average costs 70% greater than those below the 10th percentile of costs ($18,160; see Table II). When a hospital’s outcomes are visualized relative to its costs, four groups of hospitals can be identified (see Fig 1). First, there are a group of hospitals that have in-hospital mortality and readmission rates less than the median rate for the overall sample (lower left quadrant in Fig 1). Conversely, some hospitals have in-hospital mortality and readmission rates that appear greater than the median rates (upper right quadrant in Fig 1). Finally, the remaining hospitals perform well on one measure, but worse on the other when compared to the median outcome rates (upper left and lower right quadrants in Fig 1). Most notably, there are both high- and low-cost hospitals within each quadrant. Relationship between hospital’s costs and outcomes. In the overall sample, there was an inverse relationship between a hospital’s costs and the riskstandardized in-hospital mortality rate (volume weighted r2 = 0.02, P-value < .01). However, a positive relationship was noted between a hospital’s costs and the risk-standardized readmission rate (volume weighted r2 = 0.01, P = .05). Although statistically significant in both cases, the magnitude of the relationship was minimal. When hospitals were categorized into low (N = 63), average (N = 263), and high (N = 63) performing, no substantial difference in costs was noted between groups (low performing = $25,994 vs
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Fig 1. Hospital-level variation in risk-standardized in-hospital mortality (y-axis) and 30-day readmission (x-axis) rates where the size of a hospital’s bubble is directly related to its risk-standardized costs of care. The median rate for each outcome is indicated by the dashed lines. Hospitals in the left lower quadrant have rates less than the median for both outcomes whereas those in the right upper quadrant have rates greater than the median for both outcomes. Average costs for selected hospitals are shown to highlight variation in costs relative outcomes. For example, hospital A has 23% lesser 30-day costs than hospital B, but a greater than 6-fold higher mortality rate.
Fig 2. Variation in risk-standardized costs of care (2010 $U.S.) across high (top panel)-, average (middle panel)-, and low (bottom panel)-performing hospitals.
average = $26,998 vs high = $25,794, P = .19) with wide cost variation seen within each group (see Fig 2). These same analyses were performed at the state level and yielded similar findings. In this case, no significant correlation was noted between a hospital’s risk-standardized in-hospital mortality rate, 30-day readmission rate, and 30day hospital costs in California, Florida, or New
York. Similarly, after categorizing hospitals by low, average, and high performing, there was no difference in hospital costs for any state (see Fig 3). Similar findings were obtained when limiting the definition of hospital costs to the initial discharge when surgery was performed. Characteristics of high-quality, low-cost hospitals. As an exploratory analysis, we compared
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Fig 3. Variation in risk-standardized costs of care (2010 $U.S.) across high (left-most box in group)-, average (center box in group)-, and low (right-most box in group)performing hospitals stratified by state (CA, California; FL, Florida; and NY, New York). In these plots, the top edge of the box represents the 75th percentile; the line within the box, the median or 50th percentile; and the lower edge of the box the 25th percentile of hospital’s costs. The ends of the ‘‘whiskers’’ depict the minimum and maximum values, excluding outliers (circles).
selected hospital characteristics between hospitals achieving both high-quality and low costs to lowquality, high-cost hospitals and all other hospitals in the sample. As anticipated, high-quality, low-cost hospitals had the lowest in-hospital mortality (1.1% vs 2.7% vs 3.9%, P < .01), 30-day readmissions (11.6% vs 12.3% vs 12.9%, P < .01), and 30-day hospital costs ($21,439 vs $26,186 vs $32,110, P < .01). High-quality, low-cost hospitals trended toward having a larger percentage of Medicare beneficiaries in their treatment population (70.0% vs 63.5% vs 64.4%, P = .11) and performing fewer laparoscopic cases (36.5% vs 45.5% vs 51.1%, P = .05). In addition, high-quality, low-cost hospitals had a substantially lesser observed complications rate (21.8% vs 22.2% vs 29.8%, P < .01) and a trend toward shorter hospitalizations (8.7 days vs 9.0 days vs 9.8 days, P = .21; Table III). DISCUSSION A hospital’s costs of providing colon resection for cancer is not related to the quality of care achieved when measured by risk-standardized inhospital mortality and 30-day readmission rates. Despite accounting for differences in the patient populations being treated and geographic cost influences, the average costs for providing a colon resection varied nearly 3-fold across hospitals from as low as $15,450 to as high as $47,897. These greater costs, however, did not meaningfully
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correlate with lesser in-hospital mortality or fewer frequent hospital readmissions after discharge. Furthermore, variation in hospital costs was noted within groups of high- and low-performing hospitals. These findings, including the variation in costs of care and its inconsistent relationship with outcomes, were noted in each state included in the study. As the costs of providing cancer care continue to climb, it will become increasingly important to identify best practices which allow for high-quality care to be achieved at less cost. In the current study, we found wide cost variations even among high-quality hospitals. Previous studies have evaluated characteristics of high-quality, low-cost hospitals and described differences in management practices, ownership status, and patient populations.21,22 We found that for patients undergoing colon resection, high-quality, low-cost hospitals treated a greater proportion of Medicare beneficiaries and approached fewer cases via the laparoscopic approach. This raises concerns about the role technology plays in increasing costs of care, particularly in cases where patient benefit has been demonstrated in clinical trials.23,24 Of note, we did find that high-quality, low-cost hospitals tended to have shorter hospitalizations and lesser observed complication rates. While our study and others have focused on characteristics of these hospitals, further research is needed to understand hospital practices that may be used at other institutions. For patients with cancer undergoing surgery, providing both cost and quality data may facilitate more informed health care decision-making.25 The costs of cancer treatment are a known financial burden on patients26 and can impact their treatment decisions.27 Some authors have described these costs as a ‘‘side effect’’ of treatment to be discussed with patients.28 Currently, there is a paucity of data on which to base these conversations, but our findings suggest meaningful conversations could be had. Some private companies are developing patient-centered tools to help patients ‘‘shop for health care’’ according to cost and quality,29 but similar tools are not yet widely, or publicly, available. However, health care payers who already publically report both average costs and similar outcomes, including the Centers for Medicare & Medicaid Services,4,30 have an opportunity to merge these data into a single, patientcentered format. Beginning in 2015, the Centers for Medicare & Medicaid Services will combine hospital costs and outcomes data into a total performance score to
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Table III. Characteristics of high-quality, low-cost hospitals High-quality, low-cost* Hospitals Quality and cost In-hospital mortality (risk standardized) Readmission rate (risk standardized) Median costs, 2010 US$ (risk adjusted) Patient population Average age, y Medicare, % Operative variables Median procedure volume (during study period) Elective, % Laparoscopy rate, % In-hospital outcomes Complication rate (observed), % Duration of stay (observed)
27
All other hospitals 342
Low-quality, high-costy 20
P value — <.01 <.01 <.01
1.1% 11.6% 21,439
2.7% 12.3% 26,186
3.9% 12.9% 32,110
70.7 70.0
70.5 63.5
70.9 64.4
.62 .11
32.0 56.1 36.5
32.0 63.0 45.5
35.0 61.5 51.1
.37 .14 .09
21.8 8.7
22.2 9.0
29.8 9.8
<.01 .21
*Hospitals in the top two performing quintiles for in-hospital mortality, 30-day readmission, and hospital costs. yHospitals in the bottom two performing quintiles for in-hospital mortality, 30-day readmission, and hospital costs.
determine for the purpose of reimbursement penalties or rewards under the value-based purchasing program.1 Specifically, this score will be derived from patient satisfaction scores, process measure adherence, clinical outcomes, and Medicare spending per beneficiary.31 Greater performance and lesser costs will increase a hospitals total performance scores. In this formula, greater cost hospitals could ‘‘lose points’’ in the efficiency domain, but gain points by achieving greater quality. Conversely, low-quality hospitals would ‘‘lose points’’ in the quality domain but recoup points for being low cost. Although a composite measure of cost and quality simplifies hospital performance into a single number, it also poses a problematic question: how much should low quality be offset by low costs? For example, based on Fig 1, we found hospital A has 23% lesser 30-day costs than hospital B, but a greater than 6-fold greater mortality rate. The extent to which the lesser costs offset the poor quality could lead hospital’s A and B to have similar total performance scores. More research is needed to develop methods by which a hospital’s costs and outcomes can be concurrently measured and communicated to minimize this potential. This study should be viewed in the context in the several limitations. First, we defined costs based on those experienced at the hospital during the index admission and subsequent readmissions. This did not capture cost data from any emergency department visits or surgeon’s office encounters. We focused on hospital costs because our outcomes were hospital-based, current efforts focus
on disclosing hospital costs, and the availability of data. Although this limitation could affect our findings on the variation of costs in either direction, the absolute costs of our estimates are therefore necessarily conservative. Second, these findings should be viewed within the 30-day time period, consistent with current quality measurement efforts. The relationship between outcomes and costs may be altered if shorter or longer time periods are used. Similarly, evaluating different outcomes in lieu of mortality or readmission may influence the relationship between costs and ‘‘quality.’’ As mentioned, we selected these outcomes based on the commonality of the outcomes across current quality measurement efforts. Third, it is possible that some patients (eg, Veterans Affairs patients) may receive their primary care at a federal hospital and only received their primary surgery at a non-federal hospital due to lack of surgical capacity at their primary place of care. These patients, therefore, may appear to have low costs of care when they may, in fact, be readmitted to their primary Veterans Affairs or federal hospital for complications. Finally, we cannot exclude that some variation in charges, and ultimately costs, may be related to factors for which we do not have variables and therefore cannot include in the riskstandardized models. In conclusion, hospital costs of care and quality for patients undergoing colon resection for cancer varies widely without a substantial correlation between these outcomes. Efforts focused on purchasing value in this population should consider directly assessing costs in the setting of quality.
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REFERENCES 1. Centers for Medicare & Medicaid Services (CMS), HHS. Medicare and Medicaid programs: Hospital Outpatient Prospective Payment and Ambulatory Surgical Center Payment Systems and Quality Reporting Programs; Hospital ValueBased Purchasing Program; organ procurement organizations; quality improvement organizations; Electronic Health Records (EHR) Incentive Program; provider reimbursement determinations and appeals. Final rule with comment period and final rules. Fed Regist 2013;78:74825-5200. 2. Ghaferi AA, Birkmeyer JD, Dimick JB. Variation in hospital mortality associated with inpatient surgery. N Engl J Med 2009;361:1368-75. 3. Jha AK, Li Z, Orav EJ, Epstein AM. Care in U.S. hospitals--the Hospital Quality Alliance program. N Engl J Med 2005; 353:265-74. 4. Centers for Medicare and Medicaid Services. Hospital Compare. Available from http://www.medicare.gov/ hospitalcompare/search.html. 5. Porter ME. What is value in health care? N Engl J Med 2010; 363:2477-81. 6. Stukel TA, Fisher ES, Alter DA, et al. Association of hospital spending intensity with mortality and readmission rates in Ontario hospitals. JAMA 2012;307:1037-45. 7. Birkmeyer JD, Gust C, Dimick JB, Birkmeyer NJ, Skinner JS. Hospital quality and the cost of inpatient surgery in the United States. Ann Surg 2012;255:1-5. 8. Fox JP, Desai MM, Krumholz HM, Gross CP. Hospital-level outcomes associated with laparoscopic colectomy for cancer in the minimally invasive era. J Gastrointest Surg 2012;16:2112-9. 9. Hansen DG, Fox JP, Gross CP, Bruun JS. Hospital readmissions and emergency department visits following laparoscopic and open colon resection for cancer. Dis Colon Rectum 2013;56:1053-61. 10. Miller DC, Gust C, Dimick JB, Birkmeyer N, Skinner J, Birkmeyer JD. Large variations in Medicare payments for surgery highlight savings potential from bundled payment programs. Health Aff (Millwood) 2011;30:2107-15. 11. Healthcare Cost and Utilization Project (HCUP). Overview of the State Inpatient Databases (SID). Available from http://www.hcup-us.ahrq.gov/db/state/siddbdocumenta tion.jsp. 12. Agency for Healthcare Research and Quality. Overview of HCUP. Available from http://www.hcup-us.ahrq.gov/over view.jsp. 13. The Website Services & Coordination Staff UCB. Census Bureau Home Page. Available from http://www.census.gov/#. 14. HCUP-US Cost-to-Charge Ratio Files. Available from http://www.hcup-us.ahrq.gov/db/state/costtocharge.jsp. 15. How BLS Measures Price Change for Medical Care Services in the Consumer Price Index. Available from http://www. bls.gov/cpi/cpifact4.htm. 16. Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care 1998; 36:8-27. 17. Quan H, Sundararajan V, Halfon P, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 2005;43:1130-9. 18. Krumholz HM, Wang Y, Mattera JA, et al. An administrative claims model suitable for profiling hospital performance based on 30-day mortality rates among patients with an acute myocardial infarction. Circulation 2006;113:1683-92. 19. Ghaferi AA, Birkmeyer JD, Dimick JB. Complications, failure to rescue, and mortality with major inpatient surgery in Medicare patients. Ann Surg 2009;250:1029-34.
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20. Iezzoni LI, Daley J, Heeren T, et al. Identifying complications of care using administrative data. Med Care 1994;32: 700-15. 21. Jiang HJ, Friedman B, Begun JW. Factors associated with high-quality/low-cost hospital performance. J Health Care Finance 2006;32:39-52. 22. Jha AK, Orav EJ, Epstein AM. Low-quality, high-cost hospitals, mainly in South, care for sharply higher shares of elderly black, Hispanic, and Medicaid patients. Health Aff (Millwood) 2011;30:1904-11. 23. Clinical Outcomes of Surgical Therapy Study Group. A comparison of laparoscopically assisted and open colectomy for colon cancer. N Engl J Med 2004;350:2050-9. 24. Veldkamp R, Kuhry E, Hop WC, et al. Laparoscopic surgery versus open surgery for colon cancer: short-term outcomes of a randomised trial. Lancet Oncol 2005;6:477-84. 25. Huckman RS, Kelley MA. Public reporting, consumerism, and patient empowerment. N Engl J Med 2013;369:1875-7. 26. Elkin EB, Bach PB. Cancer’s next frontier: addressing high and increasing costs. JAMA 2010;303:1086-7. 27. Lee MC, Bhati RS, von Rottenthaler EE, et al. Therapy choices and quality of life in young breast cancer survivors: a short-term follow-up. Am J Surg 2013;206:625-31. 28. Ubel PA, Abernethy AP, Zafar SY. Full disclosure---out-ofpocket costs as side effects. N Engl J Med 2013;369:1484-6. 29. Castlight Health. Available from http://www.castlight health.com/solutions/. 30. Centers for Medicare & Medicaid Services. Medicare Provider Utilization and Payment Data. 2014. Available from http://www.cms.gov/Research-Statistics-Data-and-Systems/ Statistics-Trends-and-Reports/Medicare-Provider-ChargeData/index.html. 31. Centers for Medicare & Medicaid Services. National Provider Call: Hospital Value-Based Purchasing. Available from http://www.cms.gov/Outreach-and-Education/Outre ach/NPC/Downloads/HospVBP_FY15_NPC_Final_030520 13_508.pdf.
DISCUSSION Dr Mark Hemmila (Ann Arbor, MI): Dr Fox and colleagues conclude that there is a substantial variation in risk-standardized cost---median $26,000 and interquartile range of $6,500---however, there is minimal correlation of cost to hospital outcome. Costs were similar across the low-, average-, and high-performance groups in the paper. I have three questions for Dr Fox. In the paper, it was covered, but not so much here. I was surprised to see that your high-performance, low-cost group had an absolute difference of 10 percentage points less of patients who had an operation performed laparoscopically. What do you think accounted for better outcomes and reduced cost in this group? Second, based on your data analysis, if you were a payor, how would you proceed? Do you have any payment data relative to cost? In the end, it’s the payments made relative to the outcomes achieved that determines the value of the surgical service provided, not necessarily the costs. Costs are borne by the hospital.
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Third, what accounted for the differences in charges among the high-quality, low-cost hospitals versus the average or low performers? Was it the operating room costs, or postdischarge costs? It does not seem to be related to the duration of stay because both groups were the same. Dr Justin P. Fox: I am going to start with the comment toward the end of the second question, where when we look at value in health care, it’s very much like beauty. It is in the eye of the beholder. Different people will say that quality should be measured with different outcomes and maybe disagree with mortality and readmission rates. What outcomes we may be measuring may not be as important to the patient. Patients may, if you ask them, identify different outcomes that are important to put in that quality threshold. Considering cost, it’s the cost to who? You’re absolutely right. The cost to the hospital? The cost to the patient? Or what’s being actually paid out? And these are all the challenges in studying value in health care. The value is very much dependent on what perspective you are looking at from. There were some additional things that I realized I wanted to present but did not have the space to do so. We had grouped hospitals, trying to get to the idea of who are the high-quality, low-cost hospitals versus all the others. There are some characteristics we can look at. In the paper, this is very much an exploratory analysis but raises some interesting points. Here in the table, you can see quality and cost by design were different between the two groups of hospitals. You can see the demographics here. We talked about the comment on the laparoscopy rate, where it appeared that high-quality, lowcost hospitals approached fewer of their cases laparoscopically than did all the other hospitals. The outcomes here were the observed outcomes. I went back and risk standardized those, and the risk-standardized complication rate and length of stay was substantially less in the highquality, low-cost group versus the others. I apologize about that. Although statistically relevant, the absolute magnitude difference between the percentages was smaller. To get specifically to the laparoscopy rate, what is the role there? To be honest with you, it’s tough to say. I think it does speak to the point that was brought up, the discussion from the last presentation, that if you maximize potentially enhanced recovery pathways in this patient population, you may still be able to get patients out a little earlier, which was shown, again, with the length of stay
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being a little bit shorter, and maybe that influences your costs as well. As far as line item charges, we don’t have that for these data right now, but I’m working on some specific things to look at, OR times and specific charges, like do not high-quality, low-cost hospitals, but the other group, do they have more use of ancillary services and other things driving up costs? We are working on that now. Dr Gerald Larson (Louisville, KY): This, with the Affordable Care Act now coming into play, is being presented and discussed more and more in the media. We recently had an article in our local paper about the cost of splenectomy at three different hospitals, and the range was quite wide, and the hospital administrator said several explanations. One was that you just can’t look at one procedure in terms of the coverage plan that an insurance policy might provide. But you are defining high quality. How are you defining high quality? Is it mainly the readmission rate and the mortality? And let me then go from colectomy to a different example: inguinal hernia repair. A hospital could have a very low mortality, the readmission rate could be zero, but the surgeon could do a mediocre or poor job, and the recurrence rate on that inguinal hernia might be 20% in 5 years or 10 years. Don’t you have to include more factors when you are describing or defining high quality? Dr Justin P. Fox: I agree with you. First, the way we defined high-quality and low-cost hospital in this paper. We took the risk-standardized readmission, in-hospital mortality, and cost data, stratified the hospitals by quintiles of performance. If you were in the top two quintiles for each of those outcomes, you are considered high quality, low cost. Everybody else was put into the other group. There are different ways to do this and different payors actually have their own method of identifying the high quality, low cost. This was the way we chose to do it here. As far as getting to how do you define high quality, I think that it needs to be procedure-specific. I think when we try to group a bunch of procedures together, it’s problematic from a method standpoint. For the hernia example, in-hospital mortality, I hope for any outpatient inguinal hernia is very low. The readmission rate should be low as well. Looking at those as a definition of quality for an inguinal hernia probably doesn’t mean as much as maybe for things like esophagectomy, Whipple, and maybe even colectomy. In that case, I think there are potentially other things that need to be examined for procedures like that.
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Dr Gerald Larson (Louisville, KY): Then I have one other practical question and maybe extension of this situation. As patients now might be spending their own money for the first 2 or $3,000, whatever that deductible is, they might go shopping, and they’ll find out their research indicates that they should go to hospital A, but they find out that their family doctor and their surgeon, whom he recommends, or the patient might actually want to go to, they don’t go to hospital A, they work at hospital B or C. So you have this inherent conflict. How do you see that playing out? Dr Justin P. Fox: I think there’s two important things there. They are both great points, the first being there are no data with which you can have this discussion with patients right now. What is being reported out at least publicly, using Ohio for an example, if you go to the Ohio Department of Public Health Web site, you can see for common procedures, at least listed by diagnosis-related group (DRG), which, if you are not in the medical field, and even if you are, understanding what the DRG means to you is difficult. And then they list what the average charge is for that DRG for your given hospital. That has nothing to do with what’s going to come out of your pocket. There are some private companies right now that have tried to reverse-engineer people’s hospital bills based on their insurance. One of them is Castlight in California, which is a private company making their service available largely to employers so that patients can try to understand what their out-of-pocket costs will be, not just what the average charge is. Even if they see the average charge is cheaper at hospital A versus hospital B, that may not be true for them. The next thing, I think it’s to quality and what’s actually important to patients. What may be important to patients is going to providers or surgeons or where their family practice doctor practices is more important to them and they’re worth spending that money. And so I think that that, right or wrong, is maybe a decision that patients have to make as this information becomes more available, and hopefully more tailored toward the individual patient. Dr Gerald Fried (Montreal): Just two brief questions to get back to what Jerry Larson was just asking. If we have a model of cost and quality when we talk about colectomy, which is for cancer, then 5-year survival or some measure of the actual reason that you are doing the surgery has to go into the quality initiative, because if you get a person out without killing them and they don’t get readmitted, but your 5-year survival is twice as bad as
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the hospital down the street, that’s an important aspect of quality that we as surgeons, physicians, must put on the table. The second point that I would like to make is I think when you look at two groups that have equivalent quality, and one is being able to provide that for substantially less cost, it really is very informative to try to look at dissecting where those cost differences come and to try to actually look at how we can then use that information to perhaps inform best practices. There may be actual true efficiencies and costs that we could then communicate without impacting quality and actually make sure that the money that we spend is well spent. Dr Justin P. Fox: I agree. In terms of defining the quality, again, this is why I think value is in the eyes of the beholder and what you put in defining quality. Do you put a composite measure? Do you look at individual measures? That is important. For cancer surgery, if we put things like 5-year survival, which is very important, certainly, for any cancer surgery, in that model and you pin it back to the hospital, we have to assume that there are things within the hospital’s control that can account for that survival, regardless of that, chemotherapy, radiation therapy, depending on what kind of cancer we are talking about, what type of adjuvant therapy is going into it, too, which may also impact the quality. If we do that, which I’m not saying right or wrong, I think it would potentially encourage more collaboration between the hospitals and the other providers, which may be a good thing and also important to the patients, making that data available. Dr Justin P. Fox: I think that the data that we have, whether it’s the ACS NSQIP data or the HCUP data used here, or really any administrative database, you can get to a certain level of granularity, and then you kind of hit a wall. My next step is to look at individual line item charges to try to figure out where some of the differences are in charges. I think, really, it’s going to come down to it would be nice to say, your hospital provides high quality at a low cost. We would like to learn how you do that. Being able to collaborate between the providers, whether it’s surgeons, physicians, and the hospital administration to say, why is it that we provide high quality and low cost? What is it that we would do that’s different? And I think in that collaboration, maybe being encouraged by outside monitoring, when that comes together, we will really be able to maybe streamline some processes and identify some things that can be translated across hospitals.
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Dr Ashraf Mansour (Grand Rapids, MI): I think everybody in the audience here suspects that the next step is going to be physicians and surgeons, everybody is going to have a report card. I don’t know where it is going to be taken, but these data already are being collected in the state of Michigan. I don’t know if it’s elsewhere. Can you comment? Dr Justin P. Fox: Comment on the physician-level or surgeon-level outcomes? In the state of Pennsylvania, for example, for coronary artery bypass grafting, and I believe in California as well, individual mortality rates, the surgeon-level mortality rates are being
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publicly reported. You can look them up in the Web site now. I know Michigan does quite a lot with surgical outcomes research. My personal bias, I have some hesitancy in that because there’s a lot that goes into mortality, in particular in the perioperative period above and beyond what’s done in the operating room for the perioperative care. I very much believe it’s a team effort, and that when you pin it down to the surgeon level, I think it causes some problems, and it kind of leaves other people out of the mix that maybe should be included.
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Appendix. Discharge selection process All discharges for state residents at least 18 years of age with a valid patient identifier who underwent colon resection for colon cancer between July 2009 and September 2010 Excluding discharges with missing discharge disposition Remaining Excluding discharges where the patient was transferred to another facility Remaining Excluding discharge where patient left against medical advice Remaining Selecting the first discharge for patients with more than one qualifying discharge meeting the aforementioned criteria Remaining Excluding patients with evidence of metastatic disease Remaining Excluding patients with a concurrent liver resection Remaining Excluding patients with missing total charges data Remaining Excluding patients treated at hospitals reporting fewer than 15 colon resections during the study period Final
N
%
22,017
100.00
19 21,998 113 21,885 26 21,859 119
0.09 99.91 0.51 99.49 0.12 99.88 0.54
21,740 3,480 18,260 27 18,233 1,715 16,518 1,728
99.46 16.01 83.99 0.15 99.85 9.41 90.59 10.46
14,790
89.54