BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

247 related articles for article (PubMed ID: 17200477)

  • 1. Enhancement of claims data to improve risk adjustment of hospital mortality.
    Pine M; Jordan HS; Elixhauser A; Fry DE; Hoaglin DC; Jones B; Meimban R; Warner D; Gonzales J
    JAMA; 2007 Jan; 297(1):71-6. PubMed ID: 17200477
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Modifying ICD-9-CM coding of secondary diagnoses to improve risk-adjustment of inpatient mortality rates.
    Pine M; Jordan HS; Elixhauser A; Fry DE; Hoaglin DC; Jones B; Meimban R; Warner D; Gonzales J
    Med Decis Making; 2009; 29(1):69-81. PubMed ID: 18812585
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Combining administrative and clinical data to stratify surgical risk.
    Fry DE; Pine M; Jordan HS; Elixhauser A; Hoaglin DC; Jones B; Warner D; Meimban R
    Ann Surg; 2007 Nov; 246(5):875-85. PubMed ID: 17968182
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Impact of the present-on-admission indicator on hospital quality measurement: experience with the Agency for Healthcare Research and Quality (AHRQ) Inpatient Quality Indicators.
    Glance LG; Osler TM; Mukamel DB; Dick AW
    Med Care; 2008 Feb; 46(2):112-9. PubMed ID: 18219238
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Incorporating Present-on-Admission Indicators in Medicare Claims to Inform Hospital Quality Measure Risk Adjustment Models.
    Triche EW; Xin X; Stackland S; Purvis D; Harris A; Yu H; Grady JN; Li SX; Bernheim SM; Krumholz HM; Poyer J; Dorsey K
    JAMA Netw Open; 2021 May; 4(5):e218512. PubMed ID: 33978722
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Using automated clinical data for risk adjustment: development and validation of six disease-specific mortality predictive models for pay-for-performance.
    Tabak YP; Johannes RS; Silber JH
    Med Care; 2007 Aug; 45(8):789-805. PubMed ID: 17667314
    [TBL] [Abstract][Full Text] [Related]  

  • 7. The hazards of using administrative data to measure surgical quality.
    Fry DE; Pine MB; Jordan HS; Hoaglin DC; Jones B; Meimban R
    Am Surg; 2006 Nov; 72(11):1031-7; discussion 1061-9, 1133-48. PubMed ID: 17120944
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Laboratory values improve predictions of hospital mortality.
    Pine M; Jones B; Lou YB
    Int J Qual Health Care; 1998 Dec; 10(6):491-501. PubMed ID: 9928588
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Comparison of 30-day mortality models for profiling hospital performance in acute ischemic stroke with vs without adjustment for stroke severity.
    Fonarow GC; Pan W; Saver JL; Smith EE; Reeves MJ; Broderick JP; Kleindorfer DO; Sacco RL; Olson DM; Hernandez AF; Peterson ED; Schwamm LH
    JAMA; 2012 Jul; 308(3):257-64. PubMed ID: 22797643
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Risk adjustment for coronary artery bypass graft surgery: an administrative approach versus EuroSCORE.
    Ugolini C; Nobilio L
    Int J Qual Health Care; 2004 Apr; 16(2):157-64. PubMed ID: 15051710
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Adding Laboratory Data to Hospital Claims Data to Improve Risk Adjustment of Inpatient/30-Day Postdischarge Outcomes.
    Pine M; Fry DE; Hannan EL; Naessens JM; Whitman K; Reband A; Qian F; Schindler J; Sonneborn M; Roland J; Hyde L; Dennison BA
    Am J Med Qual; 2017; 32(2):141-147. PubMed ID: 26917809
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Predictions of hospital mortality rates: a comparison of data sources.
    Pine M; Norusis M; Jones B; Rosenthal GE
    Ann Intern Med; 1997 Mar; 126(5):347-54. PubMed ID: 9054278
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Relationship between Medicare's hospital compare performance measures and mortality rates.
    Werner RM; Bradlow ET
    JAMA; 2006 Dec; 296(22):2694-702. PubMed ID: 17164455
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Challenges and benefits of adding laboratory data to a mortality risk adjustment method.
    McCullough E; Sullivan C; Banning P; Goldfield N; Hughes J
    Qual Manag Health Care; 2011; 20(4):253-62. PubMed ID: 21971023
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Comparison of risk-adjustment models using administrative or clinical data for outcome prediction in patients after myocardial infarction or coronary bypass surgery in Korea.
    Park HK; Yoon SJ; Ahn HS; Ahn LS; Seo HJ; Lee SI; Lee KS
    Int J Clin Pract; 2007 Jul; 61(7):1086-90. PubMed ID: 17537190
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Risk-adjusting hospital inpatient mortality using automated inpatient, outpatient, and laboratory databases.
    Escobar GJ; Greene JD; Scheirer P; Gardner MN; Draper D; Kipnis P
    Med Care; 2008 Mar; 46(3):232-9. PubMed ID: 18388836
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Disability as a covariate in risk adjustment models for predicting hospital deaths.
    Iezzoni LI
    Ann Epidemiol; 2014 Jan; 24(1):17-22. PubMed ID: 24262999
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Accuracy of hospital report cards based on administrative data.
    Glance LG; Dick AW; Osler TM; Mukamel DB
    Health Serv Res; 2006 Aug; 41(4 Pt 1):1413-37. PubMed ID: 16899015
    [TBL] [Abstract][Full Text] [Related]  

  • 19. The effect of publicly reporting hospital performance on market share and risk-adjusted mortality at high-mortality hospitals.
    Baker DW; Einstadter D; Thomas C; Husak S; Gordon NH; Cebul RD
    Med Care; 2003 Jun; 41(6):729-40. PubMed ID: 12773839
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Identifying in-hospital venous thromboembolism (VTE): a comparison of claims-based approaches with the Rochester Epidemiology Project VTE cohort.
    Leibson CL; Needleman J; Buerhaus P; Heit JA; Melton LJ; Naessens JM; Bailey KR; Petterson TM; Ransom JE; Harris MR
    Med Care; 2008 Feb; 46(2):127-32. PubMed ID: 18219240
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 13.