Prediction of hospital readmission for heart failure: development of a simple risk score based on administrative data
Rocha, E.
Revista Portuguesa de Cardiologia Orgao Oficial da Sociedade Portuguesa de Cardiologia 18(9): 855-856
1999
ISSN/ISBN: 0870-2551 PMID: 10610100 Document Number: 505466
Document emailed within 1 workday
Related Documents
Baig, M.; Zhang, E.; Robinson, R.; Ullah, E.; Whitakker, R. 2018: Evaluation of Patients at Risk of Hospital Readmission (PARR) and LACE Risk Score for New Zealand Context Studies in Health Technology and Informatics 252: 21-26Huntington, M.K.; Guzman, A.I.; Roemen, A.; Fieldsend, J.; Saloum, H. 2013: Hospital-to-Home: a hospital readmission reduction program for congestive heart failure South Dakota Medicine: the Journal of the South Dakota State Medical Association 66(9): 370-373
Mahajan, S.M.; Heidenreich, P.; Abbott, B.; Newton, A.; Ward, D. 2018: Predictive models for identifying risk of readmission after index hospitalization for heart failure: a systematic review European Journal of Cardiovascular Nursing: Journal of the Working Group on Cardiovascular Nursing of the European Society of Cardiology 17(8): 675-689
Sittiparn, W.; Siwadune, T. 2017: Risk Score for Prediction of Postpartum Hemorrhages in Normal Labor at Chonburi Hospital Journal of the Medical Association of Thailand 100(4): 382-388
Schroeder, S.D. 2009: Public reporting of 30-day risk-standardized readmission measures for acute myocardial infarction, heart failure and pneumonia South Dakota Medicine: the Journal of the South Dakota State Medical Association 62(12): 488
Mahajan, S.; Burman, P.; Hogarth, M. 2016: Analyzing 30-Day Readmission Rate for Heart Failure Using Different Predictive Models Studies in Health Technology and Informatics 225: 143-147
Jenghua, K.; Jedsadayanmata, A. 2011: Rate and predictors of early readmission among Thai patients with heart failure Journal of the Medical Association of Thailand 94(7): 782-788
Kongsgaard, U.E.; Smith-Erichsen, N. 1987: Septic severity score. A simple method for the evaluation of intensive care patients with multiple organ failure Tidsskrift for den Norske Laegeforening: Tidsskrift for Praktisk Medicin Ny Raekke 107(1): 4-7
Mitani, K. 2007: Community based treatment of heart failure--cooperation between physicians in private practice and in the hospital Nihon Rinsho. Japanese Journal of Clinical Medicine 65(Suppl 5): 571-575
Mocan, T.; Agoşton-Coldea, L.; Gatfossé, M.; Rosenstingl, S.; Mocan, L.C.; Dumitraşcu, D.L. 2008: A new prediction score for myocardial infarction: MINF SCORE Romanian Journal of Internal Medicine 46(2): 145-151
Szekér, S.; Vathy-Fogarassy, Ág. 2018: The Effect of Latent Binary Variables on the Uncertainty of the Prediction of a Dichotomous Outcome Using Logistic Regression Based Propensity Score Matching Studies in Health Technology and Informatics 248: 1-8
Holcomb, J. 2000: The role of administrative data in measurement and reporting of quality of hospital care Texas Medicine 96(10): 48-52
Bari, M.A.; Islam, M.S.; Paul, G.K.; Chanda, S.K.; Siddique, S.R.; Khan, T.A. 2012: Metabolic syndrome is a risk factor for development of heart failure in acute myocardial infarction Mymensingh Medical Journal: Mmj 21(4): 633-638
Keesukphan, P.; Chanprasertyothin, S.; Ongphiphadhanakul, B.; Puavilai, G. 2007: The development and validation of a diabetes risk score for high-risk Thai adults Journal of the Medical Association of Thailand 90(1): 149-154
Guan, V.; Probst, Y.; Neale, E.; Martin, A.; Tapsell, L. 2016: Development of an At-Risk Assessment Approach to Dietary Data Quality in a Food-Based Clinical Trial Studies in Health Technology and Informatics 227: 34-40
Sattar, N.; Welsh, P.; Sarwar, N.; Danesh, J.; Di Angelantonio, E.; Gudnason, V.; Davey Smith, G.; Ebrahim, S.; Lawlor, D.A. 2010: NT-proBNP is associated with coronary heart disease risk in healthy older women but fails to enhance prediction beyond established risk factors: results from the British Women's Heart and Health Study Atherosclerosis 209(1): 295-299
De Luca, A.; Agabiti, N.; Fiorelli, M.; Sacchetti, M.L.; Tancioni, V.; Picconi, O.; Cardo, S.; Guasticchi, G. 2003: Implementation of a surveillance system for stroke based on administrative and clinical data in the Lazio region (Italy): methodological aspects Annali di Igiene: Medicina Preventiva e di Comunita 15(3): 207-214
Rattanaumpawan, P.; Wongkamhla, T.; Thamlikitkul, V. 2016: Accuracy of ICD-10 Coding System for Identifying Comorbidities and Infectious Conditions Using Data from a Thai University Hospital Administrative Database Journal of the Medical Association of Thailand 99(4): 368-373
Holzmann, M.J.; Bandstein, N.; Johansson, M.; Ljung, R. 2014: HEART-score does not improve the risk assessment Lakartidningen 111(25-26): 1132-1133
Eggerth, A.; Hayn, D.; Veeranki, S.; Stieg, J.ör.; Schreier, G.ün. 2018: Utilising Information of the Case Fee Catalogue to Enhance 30-Day Readmission Prediction in the German DRG System Studies in Health Technology and Informatics 255: 40-44