BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

156 related articles for article (PubMed ID: 18798724)

  • 1. Review of the application of risk-adjusted charts to analyse mortality outcomes in critical care.
    Cook DA; Duke G; Hart GK; Pilcher D; Mullany D
    Crit Care Resusc; 2008 Sep; 10(3):239-51. PubMed ID: 18798724
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Performance of risk-adjusted control charts to monitor in-hospital mortality of intensive care unit patients: a simulation study.
    Koetsier A; de Keizer NF; de Jonge E; Cook DA; Peek N
    Crit Care Med; 2012 Jun; 40(6):1799-807. PubMed ID: 22610184
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Monitoring the evolutionary process of quality: risk-adjusted charting to track outcomes in intensive care.
    Cook DA; Steiner SH; Cook RJ; Farewell VT; Morton AP
    Crit Care Med; 2003 Jun; 31(6):1676-82. PubMed ID: 12794403
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Which hospitals have significantly better or worse than expected mortality rates for acute myocardial infarction patients? Improved risk adjustment with present-at-admission diagnoses.
    Stukenborg GJ; Wagner DP; Harrell FE; Oliver MN; Heim SW; Price AL; Han CK; Wolf AM; Connors AF
    Circulation; 2007 Dec; 116(25):2960-8. PubMed ID: 18071076
    [TBL] [Abstract][Full Text] [Related]  

  • 5. What is the role of risk-adjusted funnel plots in the analysis of radical cystectomy volume-outcome relationships?
    Mayer EK; Bottle A; Aylin P; Darzi AW; Vale JA; Athanasiou T
    BJU Int; 2011 Sep; 108(6):844-50. PubMed ID: 21884357
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Funnel plots for comparing performance of PCI performing hospitals and cardiologists: demonstration of utility using the New York hospital mortality data.
    Kunadian B; Dunning J; Roberts AP; Morley R; de Belder MA
    Catheter Cardiovasc Interv; 2009 Apr; 73(5):589-94. PubMed ID: 19309714
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Exponentially weighted moving average charts to compare observed and expected values for monitoring risk-adjusted hospital indicators.
    Cook DA; Coory M; Webster RA
    BMJ Qual Saf; 2011 Jun; 20(6):469-74. PubMed ID: 21209145
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Control charts, Cusum techniques and funnel plots. A review of methods for monitoring performance in healthcare.
    Noyez L
    Interact Cardiovasc Thorac Surg; 2009 Sep; 9(3):494-9. PubMed ID: 19509097
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Monitoring risk-adjusted outcomes in congenital heart surgery: does the appropriateness of a risk model change with time?
    Tsang VT; Brown KL; Synnergren MJ; Kang N; de Leval MR; Gallivan S; Utley M
    Ann Thorac Surg; 2009 Feb; 87(2):584-7. PubMed ID: 19161783
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Risk-adjusted survival time monitoring with an updating exponentially weighted moving average (EWMA) control chart.
    Steiner SH; Jones M
    Stat Med; 2010 Feb; 29(4):444-54. PubMed ID: 19908262
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Risk-adjusted clinical quality indicators: indices for measuring and monitoring rates of mortality, complications, and readmissions.
    DesHarnais SI; Forthman MT; Homa-Lowry JM; Wooster LD
    Qual Manag Health Care; 2000; 9(1):14-22. PubMed ID: 11185878
    [TBL] [Abstract][Full Text] [Related]  

  • 12. [Mortality surveillance in an intensive care unit].
    Haagensen R; Smith-Erichsen N
    Tidsskr Nor Laegeforen; 2008 Nov; 128(22):2567-9. PubMed ID: 19023352
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Monitoring excess unplanned return to theatre following colorectal cancer surgery.
    Rasmussen M; Platell C; Jones M
    ANZ J Surg; 2018 Nov; 88(11):1168-1173. PubMed ID: 30306716
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Subgroup mortality probability models: are they necessary for specialized intensive care units?
    Nathanson BH; Higgins TL; Kramer AA; Copes WS; Stark M; Teres D
    Crit Care Med; 2009 Aug; 37(8):2375-86. PubMed ID: 19531946
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Monitoring the performance of intensive care units using the variable life-adjusted display: a simulation study to explore its applicability and efficiency.
    Foltran F; Baldi I; Bertolini G; Merletti F; Gregori D
    J Eval Clin Pract; 2009 Jun; 15(3):506-13. PubMed ID: 19522905
    [TBL] [Abstract][Full Text] [Related]  

  • 16. On-line variable live-adjusted displays with internal and external risk-adjusted mortalities. A valuable method for benchmarking and early detection of unfavourable trends in cardiac surgery.
    Albert AA; Walter JA; Arnrich B; Hassanein W; Rosendahl UP; Bauer S; Ennker J
    Eur J Cardiothorac Surg; 2004 Mar; 25(3):312-9. PubMed ID: 15019654
    [TBL] [Abstract][Full Text] [Related]  

  • 17. The use of statistical process control (risk-adjusted CUSUM, risk-adjusted RSPRT and CRAM with prediction limits) for monitoring the outcomes of out-of-hospital cardiac arrest patients rescued by the EMS system.
    Chen TT; Chung KP; Hu FC; Fan CM; Yang MC
    J Eval Clin Pract; 2011 Feb; 17(1):71-7. PubMed ID: 20807294
    [TBL] [Abstract][Full Text] [Related]  

  • 18. How can we know whether short term trends in a hospital's HSMR are significant?
    Frisch L; Anscombe L; Bamford M
    Stud Health Technol Inform; 2009; 143():149-54. PubMed ID: 19380929
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Prospective validation of the intensive care unit admission Mortality Probability Model (MPM0-III).
    Higgins TL; Kramer AA; Nathanson BH; Copes W; Stark M; Teres D
    Crit Care Med; 2009 May; 37(5):1619-23. PubMed ID: 19325480
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Why try to predict ICU outcomes?
    Power GS; Harrison DA
    Curr Opin Crit Care; 2014 Oct; 20(5):544-9. PubMed ID: 25159474
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.