Risk-Adjusted Mortality Rates as a Quality Proxy Outperform Volume in Surgical Oncology-A New Perspective on Hospital Centralization Using National Population-Based Data

被引:25
作者
Baum, Philip [1 ,2 ]
Lenzi, Jacopo [3 ]
Diers, Johannes [2 ]
Rust, Christoph [4 ,5 ]
Eichhorn, Martin E. [1 ,6 ]
Taber, Samantha [7 ]
Germer, Christoph-Thomas [2 ,8 ]
Winter, Hauke [1 ,6 ]
Wiegering, Armin [2 ,8 ,9 ]
机构
[1] Univ Heidelberg Hosp, Dept Thorac Surg, Thoraxklin, Roentgenstr 1, D-69126 Heidelberg, Germany
[2] Univ Hosp Wuerzburg, Dept Gen Visceral Transplant Vasc & Pediat, Wurzburg, Germany
[3] Univ Bologna, Dept Biomed & Neuromotor Sci, Bologna, Italy
[4] Univ Regensburg, Dept Econometr, Regensburg, Germany
[5] Vienna Univ Econ & Business, Dept Finance Accounting & Stat, Vienna, Austria
[6] German Ctr Lung Res DZL, Translat Lung Res Ctr Heidelberg TLRC, Heidelberg, Germany
[7] HELIOS Klin Emil Behring, Dept Thorac Surg, Heckeshorn Lung Clin, Berlin, Germany
[8] Univ Wurzburg, Comprehens Canc Ctr Mainfranken, Wurzburg, Germany
[9] Univ Wurzburg, Theodor Boveri Inst, Bioctr, Wurzburg, Germany
关键词
PANCREATIC SURGERY; OUTCOMES; CARE; GERMANY; IMPACT; TIME;
D O I
10.1200/JCO.21.01488
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
PURPOSE Despite a long-known association between annual hospital volume and outcome, little progress has been made in shifting high-risk surgery to safer hospitals. This study investigates whether the risk-standardized mortality rate (RSMR) could serve as a stronger proxy for surgical quality than volume. METHODS We included all patients who underwent complex oncologic surgeries in Germany between 2010 and 2018 for any of five major cancer types, splitting the data into training (2010-2015) and validation sets (2016-2018). For each surgical group, we calculated annual volume and RSMR quintiles in the training set and applied these thresholds to the validation set. We studied the overlap between the two systems, modeled a market exit of low-performing hospitals, and compared effectiveness and efficiency of volume- and RSMR-based rankings. We compared travel distance or time that would be required to reallocate patients to the nearest hospital with low-mortality ranking for the specific procedure. RESULTS Between 2016 and 2018, 158,079 patients were treated in 974 hospitals. At least 50% of high-volume hospitals were not ranked in the low-mortality group according to RSMR grouping. In an RSMR centralization model, an average of 32 patients undergoing complex oncologic surgery would need to relocate to a low-mortality hospital to save one life, whereas 47 would need to relocate to a high-volume hospital. Mean difference in travel times between the nearest hospital to the hospital that performed surgery ranged from 10 minutes for colorectal cancer to 24 minutes for pancreatic cancer. Centralization on the basis of RSMR compared with volume would ensure lower median travel times for all cancer types, and these times would be lower than those observed. CONCLUSION RSMR is a promising proxy for measuring surgical quality. It outperforms volume in effectiveness, efficiency, and hospital availability for patients. (C) 2022 by American Society of Clinical Oncology
引用
收藏
页码:1041 / +
页数:11
相关论文
共 5 条
  • [1] Impact of hospital type on risk-adjusted, traffic-related 30-day mortality: a population-based registry study
    Ydenius, Viktor
    Larsen, Robert
    Steinvall, Ingrid
    Backstrom, Denise
    Chew, Michelle
    Sjoberg, Folke
    BURNS & TRAUMA, 2021, 9
  • [2] Hospital Surgical Volume and 3-Year Mortality in Severe Prognosis Cancers: A Population-Based Study Using Cancer Registry Data
    Taniyama, Yukari
    Tabuchi, Takahiro
    Ohno, Yuko
    Morishima, Toshitaka
    Okawa, Sumiyo
    Koyama, Shihoko
    Miyashiro, Isao
    JOURNAL OF EPIDEMIOLOGY, 2021, 31 (01) : 52 - 58
  • [3] Risk of Post-Discharge Venous Thromboembolism and Associated Mortality in General Surgery: A Population-Based Cohort Study Using Linked Hospital and Primary Care Data in England
    Bouras, George
    Burns, Elaine Marie
    Howell, Ann-Marie
    Bottle, Alex
    Athanasiou, Thanos
    Darzi, Ara
    PLOS ONE, 2015, 10 (12):
  • [4] A Pancreaticoduodenectomy Risk Model Derived From 8575 Cases From a National Single-Race Population (Japanese) Using a Web-Based Data Entry System The 30-Day and In-hospital Mortality Rates for Pancreaticoduodenectomy
    Kimura, Wataru
    Miyata, Hiroaki
    Gotoh, Mitsukazu
    Hirai, Ichiro
    Kenjo, Akira
    Kitagawa, Yuko
    Shimada, Mitsuo
    Baba, Hideo
    Tomita, Naohiro
    Nakagoe, Tohru
    Sugihara, Kenichi
    Mori, Masaki
    ANNALS OF SURGERY, 2014, 259 (04) : 773 - 780
  • [5] Short and Long-Term Mortality After Appendectomy in Sweden 1987 to 2006. Influence of Appendectomy Diagnosis, Sex, Age, Co-morbidity, Surgical Method, Hospital Volume, and Time Period. A National Population-Based Cohort Study
    Andersson, Roland E.
    WORLD JOURNAL OF SURGERY, 2013, 37 (05) : 974 - 981