International Validity of the HOSPITAL Score to Predict 30-Day Potentially Avoidable Hospital Readmissions

被引:180
作者
Donze, Jacques D. [1 ,2 ,3 ]
Williams, Mark V. [4 ]
Robinson, Edmondo J. [5 ]
Zimlichman, Eyal [6 ]
Aujesky, Drahomir [1 ]
Vasilevskis, Eduard E. [7 ,8 ,9 ]
Kripalani, Sunil [7 ,8 ]
Metlay, Joshua P. [10 ]
Wallington, Tamara [11 ]
Fletcher, Grant S. [12 ]
Auerbach, Andrew D. [13 ]
Schnipper, Jeffrey L. [2 ,3 ]
机构
[1] Univ Hosp Bern, Div Gen Internal Med, CH-3010 Bern, Switzerland
[2] Brigham & Womens Hosp, Div Gen Med, Boston, MA 02115 USA
[3] Harvard Univ, Sch Med, Boston, MA USA
[4] Univ Kentucky, Ctr Hlth Serv Res, Lexington, KY 40506 USA
[5] Christiana Care Hlth Syst, Value Inst, Wilmington, DE USA
[6] Chaim Sheba Med Ctr, IL-52621 Tel Hashomer, Israel
[7] Vanderbilt Univ, Med Ctr, Sect Hosp Med, Nashville, TN USA
[8] Vanderbilt Univ, Med Ctr, Ctr Clin Qual & Implementat Res, Nashville, TN USA
[9] Vet Affairs Tennessee Valley Geriatr Res Educ & C, Nashville, TN USA
[10] Massachusetts Gen Hosp, Div Gen Internal Med, Boston, MA 02114 USA
[11] William Osler Hlth Syst, Toronto, ON, Canada
[12] Univ Washington, Harborview Med Ctr, Dept Med, Seattle, WA 98104 USA
[13] Univ Calif San Francisco, Div Hosp Med, San Francisco, CA 94143 USA
基金
瑞士国家科学基金会; 美国国家卫生研究院;
关键词
ATRIAL-FIBRILLATION; ANTICOAGULATED PATIENTS; MEDICAL PATIENTS; BLEEDING RISK; VALIDATION; MODELS; CHADS(2);
D O I
10.1001/jamainternmed.2015.8462
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
IMPORTANCE Identification of patients at a high risk of potentially avoidable readmission allows hospitals to efficiently direct additional care transitions services to the patients most likely to benefit. OBJECTIVE To externally validate the HOSPITAL score in an international multicenter study to assess its generalizability. DESIGN, SETTING, AND PARTICIPANTS International retrospective cohort study of 117 065 adult patients consecutively discharged alive from the medical department of 9 large hospitals across 4 different countries between January 2011 and December 2011. Patients transferred to another acute care facility were excluded. EXPOSURES The HOSPITAL score includes the following predictors at discharge: hemoglobin, discharge from an oncology service, sodium level, procedure during the index admission, index type of admission (urgent), number of admissions during the last 12 months, and length of stay. MAIN OUTCOMES AND MEASURES 30-day potentially avoidable readmission to the index hospital using the SQLape algorithm. RESULTS Overall, 117 065 adults consecutively discharged alive from a medical department between January 2011 and December 2011 were studied. Of all medical discharges, 16 992 of 117 065 (14.5%) were followed by a 30-day readmission, and 11 307 (9.7%) were followed by a 30-day potentially avoidable readmission. The discriminatory power of the HOSPITAL score to predict potentially avoidable readmission was good, with a C statistic of 0.72 (95% CI, 0.72-0.72). As in the derivation study, patients were classified into 3 risk categories: low (n = 73 031 [62.4%]), intermediate (n = 27 612 [23.6%]), and high risk (n = 16 422 [14.0%]). The estimated proportions of potentially avoidable readmission for each risk category matched the observed proportion, resulting in an excellent calibration (Pearson.2 test P = .89). CONCLUSIONS AND RELEVANCE The HOSPITAL score identified patients at high risk of 30-day potentially avoidable readmission with moderately high discrimination and excellent calibration when applied to a large international multicenter cohort of medical patients. This score has the potential to easily identify patients in need of more intensive transitional care interventions to prevent avoidable hospital readmissions.
引用
收藏
页码:496 / 502
页数:7
相关论文
共 28 条
  • [1] Inability of Providers to Predict Unplanned Readmissions
    Allaudeen, Nazima
    Schnipper, Jeffrey L.
    Orav, E. John
    Wachter, Robert M.
    Vidyarthi, Arpana R.
    [J]. JOURNAL OF GENERAL INTERNAL MEDICINE, 2011, 26 (07) : 771 - 776
  • [2] [Anonymous], 1992, INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS 1 INT STAT CLASS DIS
  • [3] [Anonymous], 1999, International Classification of Diseases, 10th Revision (ICD-10)
  • [4] Comparison of the CHADS2, CHA2DS2 -VASc and HAS-BLED scores for the prediction of clinically relevant bleeding in anticoagulated patients with atrial fibrillation: The AMADEUS trial
    Apostolakis, Stavros
    Lane, Deirdre A.
    Buller, Harry
    Lip, Gregory Y. H.
    [J]. THROMBOSIS AND HAEMOSTASIS, 2013, 110 (05) : 1074 - 1079
  • [5] Preventability and Causes of Readmissions in a National Cohort of General Medicine Patients
    Auerbach, Andrew D.
    Kripalani, Sunil
    Vasilevskis, Eduard E.
    Sehgal, Neil
    Lindenauer, Peter K.
    Metlay, Joshua P.
    Fletcher, Grant
    Ruhnke, Gregory W.
    Flanders, Scott A.
    Kim, Christopher
    Williams, Mark V.
    Thomas, Larissa
    Giang, Vernon
    Herzig, Shoshana J.
    Patel, Kanan
    Boscardin, W. John
    Robinson, Edmondo J.
    Schnipper, Jeffrey L.
    [J]. JAMA INTERNAL MEDICINE, 2016, 176 (04) : 484 - 493
  • [6] The Predictive Ability of the CHADS2 and CHA2DS2-VASc Scores for Bleeding Risk in Atrial Fibrillation: The MAQI2 Experience
    Barnes, Geoffrey D.
    Gu, Xiaokui
    Haymart, Brian
    Kline-Rogers, Eva
    Almany, Steve
    Kozlowski, Jay
    Besley, Dennis
    Krol, Gregory D.
    Froehlich, James B.
    Kaatz, Scott
    [J]. THROMBOSIS RESEARCH, 2014, 134 (02) : 294 - 299
  • [7] Reporting and Methods in Clinical Prediction Research: A Systematic Review
    Bouwmeester, Walter
    Zuithoff, Nicolaas P. A.
    Mallett, Susan
    Geerlings, Mirjam I.
    Vergouwe, Yvonne
    Steyerberg, Ewout W.
    Altman, Douglas G.
    Moons, Karel G. M.
    [J]. PLOS MEDICINE, 2012, 9 (05)
  • [8] Collins GS, 2015, BMJ-BRIT MED J, V350, DOI [10.1111/1471-0528.13244, 10.1136/bmj.g7594]
  • [9] Readmissions of medical patients: an external validation of two existing prediction scores
    Cooksley, T.
    Nanayakkara, P. W. B.
    Nickel, C. H.
    Subbe, C. P.
    Kellett, J.
    Kidney, R.
    Merten, H.
    Van Galen, L.
    Henriksen, D. P.
    Lassen, A. T.
    Brabrand, M.
    [J]. QJM-AN INTERNATIONAL JOURNAL OF MEDICINE, 2016, 109 (04) : 245 - 248
  • [10] Effect of a Postdischarge Virtual Ward on Readmission or Death for High-Risk Patients A Randomized Clinical Trial
    Dhalla, Irfan A.
    O'Brien, Tara
    Morra, Dante
    Thorpe, Kevin E.
    Wong, Brian M.
    Mehta, Rajin
    Frost, David W.
    Abrams, Howard
    Ko, Francoise
    Van Rooyen, Patrick
    Bell, Chaim M.
    Gruneir, Andrea
    Lewis, Geraint H.
    Daub, Stacey
    Anderson, Geoff M.
    Hawker, Gillian A.
    Rochon, Paula A.
    Laupacis, Andreas
    [J]. JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2014, 312 (13): : 1305 - 1312