Risk Adjusting Survival Outcomes in Hospitals That Treat Patients With Cancer Without Information on Cancer Stage.

IMPORTANCE: Instituting widespread measurement of outcomes for cancer hospitals using administrative data is difficult owing to lack of cancer-specific information such as disease stage. OBJECTIVE: To evaluate the performance of hospitals that treat patients with cancer using Medicare data for outcome ascertainment and risk adjustment and to assess whether hospital rankings based on these measures are altered by the addition of cancer-specific information. DESIGN, SETTING, AND PARTICIPANTS: Risk-adjusted cumulative mortality rates of patients with cancer were captured in Medicare claims data from 2005 through 2009 nationally and assessed at the hospital level. Similar analyses were conducted using Surveillance, Epidemiology, and End Results (SEER)-Medicare data for the subset of the United States covered by the SEER program to determine whether the inclusion of cancer-specific information (only available in cancer registries) in risk adjustment altered measured hospital performance. Data were from 729 279 fee-for-service Medicare beneficiaries treated for cancer in 2006 at hospitals treating 10 or more patients with each of the following cancers, according to Medicare claims: lung, prostate, breast, colon, and other. An additional sample of 18 677 similar patients were included from the SEER-Medicare administrative data. MAIN OUTCOMES AND MEASURES: Risk-adjusted mortality overall and by cancer category, stratified by type of hospital; measures of correlation and agreement between hospital-level outcomes risk adjusted using Medicare data alone and Medicare data with SEER data. RESULTS: There were large survival differences between different types of hospitals that treat Medicare patients with cancer. At 1 year, mortality for patients treated by hospitals exempt from the Medicare prospective payment system was 10% lower than at community hospitals (18% vs 28%) across all cancers, and the pattern persisted through 5 years of follow-up and within specific cancer categories. Performance ranking of hospitals was consistent with or without SEER-Medicare disease stage information (weighted κ ≥ 0.81). CONCLUSIONS AND RELEVANCE: Potentially important outcome differences exist between different types of hospitals that treat patients with cancer after risk adjustment using information in Medicare administrative data. This type of risk adjustment may be adequate for evaluating hospital performance, since the additional adjustment for data available only in cancer registries does not seem to appreciably alter measures of performance.

Outcome--more than just operative mortality.

Historical reviews of outcome following major operations for cancer have focused on the readily measurable, operative mortality. The interrelationship of surgeon and institutional volume to improved perioperative outcome has been confirmed. More current studies now relate long term cancer survival to other issues of specialization, volume, payor and institution. The challenge is to determine what volume thresholds are sufficient for acceptable outcomes.

Long-term survival is superior after resection for cancer in high-volume centers.

BACKGROUND: A number of studies have demonstrated that surgical resection at high-volume centers is associated with improved short-term perioperative outcome. Whether long-term results after resection of visceral malignancies are superior at high-volume centers is largely unknown. METHODS: All patients who were subjected to pancreatectomy or hepatectomy for cancer in the years 1995 and 1996 were identified in the National Medicare database. Data extracted and examined include demographics, comorbidities, and long-term survival. All survival was confirmed through 2001, providing actual 5-year survival. Long-term survival was examined as related to hospital volume. RESULTS: In the study period, there were 2592 pancreatectomies and 3734 hepatectomies performed at 1101 and 1284 institutions, respectively. High-volume center was defined as >25 cases/y. By this definition, there were 10 high-volume centers for pancreatectomy and 12 centers for hepatectomy performing 11% (n = 291) of the pancreatectomies and 12% (n = 474) of the hepatectomies in this study period. Comparison by log-rank demonstrated superior survival for patients resected at high-volume centers (pancreatectomy: P = 0.001; hepatectomy: P = 0.02). This was confirmed by multivariate analysis. All analyses included an adjustment for within-center correlation. CONCLUSION: Superior long-term survival is associated with complex visceral resections for cancer at high-volume centers.

Using patients as their own controls for cost evaluation of phase I clinical trials.

PURPOSE: Little is known about the cost of phase I trials in cancer patients compared with that of standard treatments, yet the former is often assumed to be greater than the latter. Our objective was to utilize a new approach, using patients as their own controls, to compare in a pilot study the costs of care for patients on phase I trials with those incurred for standard treatment. PATIENTS AND METHODS: We retrospectively assessed the direct medical costs (DMCs) of 59 patients participating in one of two phase I trials (TRIAL) in solid tumors conducted at Memorial Hospital (MH): (1). perillyl alcohol, and (2). flavopiridol with paclitaxel. Paired-control DMCs were those accrued by the same patient while receiving standard chemotherapy regimens just before (PRE; n = 41) or after (POST; n = 29) the trial at MH, averaged per day. RESULTS: For the 41 PRE patients, the median and mean DMCs per day for the clinical trial versus standard treatment were (US dollars) US dollars 123 v US dollars 133 and US dollars 219 v US dollars 267, respectively. For the 29 POST patients, the median and mean DMCs for the clinical trial versus standard treatment were US dollars 157 v US dollars 152 and US dollars 226 v US dollars 226, respectively. Using a linear mixed model, there was no significant difference between TRIAL and standard treatment DMCs (P =.54). CONCLUSION: Using patients as their own controls represents a new, efficient method for evaluating the cost of phase I trials, and it warrants further study. The results of our pilot study do not suggest that phase I trials always cost payers more than standard treatment.

The influence of hospital and surgeon volume on in-hospital mortality for colectomy, gastrectomy, and lung lobectomy in patients with cancer.

BACKGROUND: This study explores the volume-mortality relationship for 3 groups of cancer procedures to determine whether higher-volume hospitals, higher-volume surgeons, or both are associated with lower in-hospital mortality. METHODS: New York's Statewide Planning and Research Cooperative System was used to identify more than 32,000 hospital inpatients with a cancer diagnosis who underwent colectomy, lobectomy of the lung, or gastrectomy between January 1, 1994, and December 31, 1997. The association of in-hospital mortality rates with provider (hospital and surgeon) volume was examined after adjusting for differences in age, demographics, organ metastasis, socioeconomic status, and comorbidities. RESULTS: For hospital volume for gastrectomy, the highest-volume quartile had an absolute risk-adjusted mortality rate that was 7.1% lower (P <.0001) than the lowest-volume quartile, although the overall mortality rate for the procedure was only 6.2%. For surgeon volume for colectomy, the highest- and lowest- volume quartiles differed by 1.9% (P <.0001), although the procedure mortality rate was only 3.5%. For hospital volume for lung lobectomy, the absolute difference in mortality was 1.7%. Patients undergoing operations performed by high-volume surgeons in high-volume hospitals usually had significantly lower risk-adjusted mortality rates than did patients who had low-volume surgeons or who were in low-volume hospitals, or both. CONCLUSIONS: For all 3 procedure groups, the risk-adjusted in-hospital mortality is significantly lower when the procedures are performed by high-volume providers.