Importance Instituting widespread measurement of outcomes for cancer hospitals using administrative data is difficult due to the lack of cancer specific information such as disease stage. Objective To evaluate the performance of hospitals that treat cancer patients using Medicare data for outcome ascertainment and risk adjustment, and to assess whether hospital rankings based on these measures are influenced by the addition of cancer-specific information. Design Risk adjusted cumulative mortality of patients with cancer captured in Medicare claims from 2005–2009 nationally were assessed at the hospital level. Similar analyses were conducted in the Surveillance, Epidemiology and End Result (SEER)-Medicare data for the subset of the US covered by the SEER program to determine whether the exclusion of cancer specific information (only available in cancer registries) from risk adjustment altered measured hospital performance. Setting Administrative claims data and SEER cancer registry data Participants Sample of 729,279 fee-for-service Medicare beneficiaries treated for cancer in 2006 at hospitals treating 10+ patients with each of the following cancers, according to Medicare claims: lung, prostate, breast, colon. An additional sample of 18,677 similar patients in SEER-Medicare administrative data. Main Outcomes and Measures Risk-adjusted mortality overall and by cancer type, 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 outcome differences between different types of hospitals that treat Medicare patients with cancer. At one year, cumulative mortality for Medicare-prospective-payment-system exempt hospitals was 10% lower than at community hospitals (18% versus 28%) across all cancers, the pattern persisted through five years of follow-up and within specific cancer types. Performance ranking of hospitals was consistent with or without SEER-Medicare disease stage information (weighted kappas of at least 0.81). Conclusions and Relevance Potentially important outcome differences exist between different types of hospitals that treat cancer patients after risk adjustment using information in Medicare administrative data. This type of risk adjustment may be adequate for evaluating hospital performance, as the additional adjustment for data only available in cancer registries does not seem to appreciably alter measures of performance.

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Urban safety net providers are under pressure to improve primary care productivity. In a survey of ambulatory care facilities in New York City, productivity (measured as the number of primary care visits per provider hour) increases with exam rooms per physician but has no association with computerized information systems or tightly controlled reimbursement. Also, sample facilities rely heavily on residents, which makes these facilities sensitive to medical education policies and raises questions about quality of care for the poor. We conclude that urban safety net providers will have difficulty making the productivity improvements demanded by a more competitive health system.

Patients with evidence of tumor response on paclitaxel had a QoL benefit not observed in nonresponders, and this response was associated with a trend for lower overall costs.

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