Bruce L Jacobs1, Jonathan G Yabes2, Samia H Lopa3, Dwight E Heron4, Chung-Chou H Chang5, Justin E Bekelman6, Joel B Nelson3, Julie P W Bynum7, Amber E Barnato8, Jeremy M Kahn9. 1. Department of Urology, University of Pittsburgh, Pittsburgh, PA; Center for Research on Health Care, University of Pittsburgh, Pittsburgh, PA. Electronic address: jacobsbl2@upmc.edu. 2. Center for Research on Health Care, University of Pittsburgh, Pittsburgh, PA; Division of General Internal Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA. 3. Department of Urology, University of Pittsburgh, Pittsburgh, PA. 4. Department of Radiation Oncology, University of Pittsburgh, Pittsburgh, PA. 5. Division of General Internal Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA; Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA. 6. Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA; Division of General Internal Medicine, Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA. 7. Department of Medicine, Division of Geriatric and Palliative Medicine, University of Michigan, Ann Arbor, MI. 8. Dartmouth Institute for Health Policy and Clinical Practice, Lebanon, NH; Geisel School of Medicine at Dartmouth, Hanover, NH. 9. Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA.
Abstract
OBJECTIVE: To develop prostate cancer-specific physician-hospital networks to define hospital-based units that more accurately group hospitals, providers, and the patients they serve. METHODS: Using Surveillance, Epidemiology, and End Results-Medicare, we identified men diagnosed with localized prostate cancer between 2007 and 2011. We created physician-hospital networks by assigning each patient to a physician and each physician to a hospital based on treatment patterns. We assessed content validity by examining characteristics of hospitals anchoring the physician-hospital networks and of the patients associated with these hospitals. RESULTS: We identified 42,963 patients associated with 344 physician-hospital networks. Networks anchored by a teaching hospital (compared to a nonteaching hospital) had higher median numbers of prostate cancer patients (117 [interquartile range {71-189} vs 82 {50-126}]) and treating physicians (7 [4-11] vs 4 [3-6]) (both P <0.001). On average, patients traveled farther to networks anchored by a teaching hospital (49 miles [standard deviation] [207] vs 41 [183]; P <.001). Hospitals known as high-volume centers for robotic prostatectomies, proton-beam therapy, and active surveillance had network rates for these procedures well above the mean. Hospitals known as safety net providers served higher proportions of minorities. CONCLUSION: We empirically developed prostate-cancer specific physician-hospital networks that exhibit content validity and are relevant from a clinical and policy perspective. They have the potential to become targets for policy interventions focused on improving the delivery of prostate cancer care.
OBJECTIVE: To develop prostate cancer-specific physician-hospital networks to define hospital-based units that more accurately group hospitals, providers, and the patients they serve. METHODS: Using Surveillance, Epidemiology, and End Results-Medicare, we identified men diagnosed with localized prostate cancer between 2007 and 2011. We created physician-hospital networks by assigning each patient to a physician and each physician to a hospital based on treatment patterns. We assessed content validity by examining characteristics of hospitals anchoring the physician-hospital networks and of the patients associated with these hospitals. RESULTS: We identified 42,963 patients associated with 344 physician-hospital networks. Networks anchored by a teaching hospital (compared to a nonteaching hospital) had higher median numbers of prostate cancer patients (117 [interquartile range {71-189} vs 82 {50-126}]) and treating physicians (7 [4-11] vs 4 [3-6]) (both P <0.001). On average, patients traveled farther to networks anchored by a teaching hospital (49 miles [standard deviation] [207] vs 41 [183]; P <.001). Hospitals known as high-volume centers for robotic prostatectomies, proton-beam therapy, and active surveillance had network rates for these procedures well above the mean. Hospitals known as safety net providers served higher proportions of minorities. CONCLUSION: We empirically developed prostate-cancer specific physician-hospital networks that exhibit content validity and are relevant from a clinical and policy perspective. They have the potential to become targets for policy interventions focused on improving the delivery of prostate cancer care.
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