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Volumn 8, Issue 5, 2013, Pages 229-235

Mortality predictions on admission as a context for organizing care activities

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CARDIOPULMONARY ARREST; CLINICAL LABORATORY; COMMUNITY HOSPITAL; FEMALE; HOSPITAL PATIENT; HOSPITAL READMISSION; HOSPITALIZATION; HUMAN; INTENSIVE CARE UNIT; MAJOR CLINICAL STUDY; MALE; MEDICAL HISTORY; MORTALITY; PALLIATIVE THERAPY; PRIORITY JOURNAL; RESUSCITATION; RETROSPECTIVE STUDY;

EID: 84877670149     PISSN: 15535592     EISSN: 15535606     Source Type: Journal    
DOI: 10.1002/jhm.1998     Document Type: Article
Times cited : (28)

References (38)
  • 1
    • 0032213382 scopus 로고    scopus 로고
    • Importance of time to reperfusion for 30-day and late survival and recovery of left ventricular function after primary angioplasty for acute myocardial infarction
    • Brodie BR, Stuckey TD, Wall TC, et al. Importance of time to reperfusion for 30-day and late survival and recovery of left ventricular function after primary angioplasty for acute myocardial infarction. J Am Coll Cardiol. 1998;32:1312-1319.
    • (1998) J Am Coll Cardiol , vol.32 , pp. 1312-1319
    • Brodie, B.R.1    Stuckey, T.D.2    Wall, T.C.3
  • 2
    • 0035829842 scopus 로고    scopus 로고
    • Early goal-directed therapy in the treatment of severe sepsis and septic shock
    • Rivers E, Nguyen B, Havstad S, et al. Early goal-directed therapy in the treatment of severe sepsis and septic shock. N Engl J Med. 2001;345:1368-1377.
    • (2001) N Engl J Med , vol.345 , pp. 1368-1377
    • Rivers, E.1    Nguyen, B.2    Havstad, S.3
  • 3
    • 1542315556 scopus 로고    scopus 로고
    • Association of outcome with early stroke treatment: pooled analysis of ATLANTIS, ECASS, and NINDS rt-PA stroke trials
    • ATLANTIS, ECASS, NINDS rt-PA Study Group Investigators
    • ATLANTIS, ECASS, NINDS rt-PA Study Group Investigators. Association of outcome with early stroke treatment: pooled analysis of ATLANTIS, ECASS, and NINDS rt-PA stroke trials. Lancet. 2004;363:768-774.
    • (2004) Lancet , vol.363 , pp. 768-774
  • 4
    • 55349107824 scopus 로고    scopus 로고
    • Handoffs causing patient harm: a survey of medical and surgical house staff
    • Kitch BT, Cooper JB, Zapol WM, et al. Handoffs causing patient harm: a survey of medical and surgical house staff. Jt Comm J Qual Patient Saf. 2008;34:563-570.
    • (2008) Jt Comm J Qual Patient Saf , vol.34 , pp. 563-570
    • Kitch, B.T.1    Cooper, J.B.2    Zapol, W.M.3
  • 5
    • 84877642057 scopus 로고    scopus 로고
    • National Hospice and Palliative Care Organization. NHPCO facts and figures: hospice care in America 2010 Edition. Accessed October 3
    • National Hospice and Palliative Care Organization. NHPCO facts and figures: hospice care in America 2010 Edition. Available at: http://www.nhpco.org. Accessed October 3, 2011.
    • (2011)
  • 6
    • 77949902396 scopus 로고    scopus 로고
    • End-of-life discussions, goal attainment, and distress at the end of life: predictors and outcomes of receipt of care consistent with preferences
    • Mack JW, Weeks JC, Wright AA, Block SD, Prigerson HG. End-of-life discussions, goal attainment, and distress at the end of life: predictors and outcomes of receipt of care consistent with preferences. J Clin Oncol. 2010;28:1203-1208.
    • (2010) J Clin Oncol , vol.28 , pp. 1203-1208
    • Mack, J.W.1    Weeks, J.C.2    Wright, A.A.3    Block, S.D.4    Prigerson, H.G.5
  • 7
    • 0003525850 scopus 로고    scopus 로고
    • Committee on Quality of Health Care in America, Institute of Medicine (IOM).Washington, DC:National Academies Press
    • Committee on Quality of Health Care in America, Institute of Medicine (IOM).Crossing the Quality Chasm: A New Health System for the 21st Century.Washington, DC:National Academies Press;2001.
    • (2001) Crossing the Quality Chasm: A New Health System for the 21st Century
  • 8
    • 77950859539 scopus 로고    scopus 로고
    • The surviving sepsis campaign: results of an international guideline-based performance improvement program targeting severe sepsis
    • Levy MM, Dellinger RP, Townsend SR, et al. The surviving sepsis campaign: results of an international guideline-based performance improvement program targeting severe sepsis. Intensive Care Med. 2010;36:222-231.
    • (2010) Intensive Care Med , vol.36 , pp. 222-231
    • Levy, M.M.1    Dellinger, R.P.2    Townsend, S.R.3
  • 9
    • 0031012761 scopus 로고    scopus 로고
    • A prediction rule to identify low-risk patients with community-acquired pneumonia
    • Fine MJ, Auble TE, Yealy DM, et al. A prediction rule to identify low-risk patients with community-acquired pneumonia. N Engl J Med. 1997;336:243-250.
    • (1997) N Engl J Med , vol.336 , pp. 243-250
    • Fine, M.J.1    Auble, T.E.2    Yealy, D.M.3
  • 10
    • 33750619219 scopus 로고    scopus 로고
    • The simple clinical score predicts mortality for 30 days after admission to an acute medical unit
    • Kellett J, Deane B. The simple clinical score predicts mortality for 30 days after admission to an acute medical unit. Q J Med. 2006;99:771-781.
    • (2006) Q J Med , vol.99 , pp. 771-781
    • Kellett, J.1    Deane, B.2
  • 11
    • 33846021262 scopus 로고    scopus 로고
    • Enhancement of claims data to improve risk adjustment of hospital mortality
    • Pine M, Jordan HS, Elixhauser A, et al. Enhancement of claims data to improve risk adjustment of hospital mortality. JAMA. 2007;297:71-76.
    • (2007) JAMA , vol.297 , pp. 71-76
    • Pine, M.1    Jordan, H.S.2    Elixhauser, A.3
  • 12
    • 34547566315 scopus 로고    scopus 로고
    • Using automated clinical data for risk adjustment
    • Tabak YP, Johannes RS, Silber JH. Using automated clinical data for risk adjustment. Med Care. 2007;45:789-805.
    • (2007) Med Care , vol.45 , pp. 789-805
    • Tabak, Y.P.1    Johannes, R.S.2    Silber, J.H.3
  • 13
    • 42449097690 scopus 로고    scopus 로고
    • Risk-adjusting hospital inpatient mortality using automated inpatient, outpatient, and laboratory databases
    • Escobar GJ, Greene JD, Scheirer P, Gardner MN, Draper D, Kipnis P. Risk-adjusting hospital inpatient mortality using automated inpatient, outpatient, and laboratory databases. Med Care. 2008;46:232-239.
    • (2008) Med Care , vol.46 , pp. 232-239
    • Escobar, G.J.1    Greene, J.D.2    Scheirer, P.3    Gardner, M.N.4    Draper, D.5    Kipnis, P.6
  • 14
    • 77952421241 scopus 로고    scopus 로고
    • The Kaiser Permanente inpatient risk adjustment methodology was valid in an external patient population
    • van Walraven C, Escobar GJ, Green JD, Forster AJ. The Kaiser Permanente inpatient risk adjustment methodology was valid in an external patient population. J Clin Epidemiol. 2010;63:798-803.
    • (2010) J Clin Epidemiol , vol.63 , pp. 798-803
    • van Walraven, C.1    Escobar, G.J.2    Green, J.D.3    Forster, A.J.4
  • 15
    • 77950310857 scopus 로고    scopus 로고
    • An improved medical admissions risk system using multivariable fractional polynomial logistic regression modeling
    • Silke B, Kellett J, Rooney T, Bennett K, O'Riordan D. An improved medical admissions risk system using multivariable fractional polynomial logistic regression modeling. Q J Med. 2010;103:23-32.
    • (2010) Q J Med , vol.103 , pp. 23-32
    • Silke, B.1    Kellett, J.2    Rooney, T.3    Bennett, K.4    O'Riordan, D.5
  • 17
    • 79961031001 scopus 로고    scopus 로고
    • Derivation and validation of a model to predict daily risk of death in hospital
    • Wong J, Taljaard M, Forster AJ, Escobar GJ, von Walraven C. Derivation and validation of a model to predict daily risk of death in hospital. Med Care. 2011;49:734-743.
    • (2011) Med Care , vol.49 , pp. 734-743
    • Wong, J.1    Taljaard, M.2    Forster, A.J.3    Escobar, G.J.4    von Walraven, C.5
  • 18
    • 79958774841 scopus 로고    scopus 로고
    • Prediction of hospital mortality from admission laboratory data and patient age: a simple model
    • Asadollahi K, Hasting IM, Gill GV, Beeching NJ. Prediction of hospital mortality from admission laboratory data and patient age: a simple model. Emerg Med Australas. 2011;23:354-363.
    • (2011) Emerg Med Australas , vol.23 , pp. 354-363
    • Asadollahi, K.1    Hasting, I.M.2    Gill, G.V.3    Beeching, N.J.4
  • 19
    • 80054911570 scopus 로고    scopus 로고
    • Predicting death: an empirical evaluation of predictive tools for mortality
    • Siontis GCM, Tzoulaki I, Ioannidis JPA. Predicting death: an empirical evaluation of predictive tools for mortality. Arch Intern Med. 2011;171:1721-1726.
    • (2011) Arch Intern Med , vol.171 , pp. 1721-1726
    • Siontis, G.C.M.1    Tzoulaki, I.2    Ioannidis, J.P.A.3
  • 20
    • 77954954080 scopus 로고    scopus 로고
    • Length of stay predictions: improvements through the use of automated laboratory and comorbidity variables
    • Liu V, Kipnis P, Gould MK, Escobar GJ. Length of stay predictions: improvements through the use of automated laboratory and comorbidity variables. Med Care. 2010;48:739-744.
    • (2010) Med Care , vol.48 , pp. 739-744
    • Liu, V.1    Kipnis, P.2    Gould, M.K.3    Escobar, G.J.4
  • 21
    • 79551509338 scopus 로고    scopus 로고
    • Intra-hospital transfers to a higher level of care: contribution to total hospital and intensive care unit (ICU) mortality and length of stay (LOS)
    • Escobar GJ, Greene JD, Gardner MN, Marelich GP, Quick B, Kipnis P. Intra-hospital transfers to a higher level of care: contribution to total hospital and intensive care unit (ICU) mortality and length of stay (LOS). J Hosp Med. 2011;6:74-80.
    • (2011) J Hosp Med , vol.6 , pp. 74-80
    • Escobar, G.J.1    Greene, J.D.2    Gardner, M.N.3    Marelich, G.P.4    Quick, B.5    Kipnis, P.6
  • 22
    • 78049334037 scopus 로고    scopus 로고
    • An automated model to identify heart failure patients at risk for 30-day readmission or death using electronic medical record data
    • Amarasingham R, Moore BJ, Tabak YP, et al. An automated model to identify heart failure patients at risk for 30-day readmission or death using electronic medical record data. Med Care. 2010;48:981-988.
    • (2010) Med Care , vol.48 , pp. 981-988
    • Amarasingham, R.1    Moore, B.J.2    Tabak, Y.P.3
  • 24
    • 0345040873 scopus 로고    scopus 로고
    • Classification and regression by randomForest
    • Liaw A, Wiener M. Classification and regression by randomForest. R News. 2002;2:18-22.
    • (2002) R News , vol.2 , pp. 18-22
    • Liaw, A.1    Wiener, M.2
  • 28
    • 0034675048 scopus 로고    scopus 로고
    • Risk stratification and therapeutic decision making in acute coronary syndromes
    • Ohman EM, Granger CB, Harrington RA, Lee KL. Risk stratification and therapeutic decision making in acute coronary syndromes. JAMA. 2000;284:876-878.
    • (2000) JAMA , vol.284 , pp. 876-878
    • Ohman, E.M.1    Granger, C.B.2    Harrington, R.A.3    Lee, K.L.4
  • 29
    • 80054913367 scopus 로고    scopus 로고
    • Why is a good clinical prediction rule so hard to find?
    • Grady D, Berkowitz SA. Why is a good clinical prediction rule so hard to find?Arch Intern Med. 2011;171:1701-1702.
    • (2011) Arch Intern Med , vol.171 , pp. 1701-1702
    • Grady, D.1    Berkowitz, S.A.2
  • 30
    • 77950494853 scopus 로고    scopus 로고
    • Advance directives and outcomes of surrogate decision making before death
    • Silveira MJ, Kim SYH, Langa KM. Advance directives and outcomes of surrogate decision making before death. N Engl J Med. 2010;362:1211-1218.
    • (2010) N Engl J Med , vol.362 , pp. 1211-1218
    • Silveira, M.J.1    Kim, S.Y.H.2    Langa, K.M.3
  • 32
    • 33846452916 scopus 로고    scopus 로고
    • Survival of critically ill patients hospitalized in and out of intensive care
    • Simchen E, Sprung CL, Galai N, et al. Survival of critically ill patients hospitalized in and out of intensive care. Crit Care Med. 2007;35:449-457.
    • (2007) Crit Care Med , vol.35 , pp. 449-457
    • Simchen, E.1    Sprung, C.L.2    Galai, N.3
  • 33
    • 38549161044 scopus 로고    scopus 로고
    • How decisions are made to admit patients to medical intensive care units (MICUs): a survey of MICU directors at academic medical centers across the United States
    • Walter KL, Siegler M, Hall JB. How decisions are made to admit patients to medical intensive care units (MICUs): a survey of MICU directors at academic medical centers across the United States. Crit Care Med. 2008;36:414-420.
    • (2008) Crit Care Med , vol.36 , pp. 414-420
    • Walter, K.L.1    Siegler, M.2    Hall, J.B.3
  • 34
    • 77956940495 scopus 로고    scopus 로고
    • Rethinking rapid response teams
    • Litvak E, Pronovost P. Rethinking rapid response teams. JAMA. 2010;204:1375-1376.
    • (2010) JAMA , vol.204 , pp. 1375-1376
    • Litvak, E.1    Pronovost, P.2
  • 35
    • 0026888697 scopus 로고
    • Hospital and patient characteristics associated with death after surgery: a study of adverse occurrence and failure to rescue
    • Silber JH, Williams SV, Krakauer H, Schwartz JS. Hospital and patient characteristics associated with death after surgery: a study of adverse occurrence and failure to rescue. Med Care. 1992;30:615-629.
    • (1992) Med Care , vol.30 , pp. 615-629
    • Silber, J.H.1    Williams, S.V.2    Krakauer, H.3    Schwartz, J.S.4
  • 36
    • 70349610473 scopus 로고    scopus 로고
    • Variation in hospital mortality associated with inpatient surgery
    • Ghaferi AA, Birkmeyer JD, Dimick JB. Variation in hospital mortality associated with inpatient surgery. N Engl J Med. 2009;361:1368-1375.
    • (2009) N Engl J Med , vol.361 , pp. 1368-1375
    • Ghaferi, A.A.1    Birkmeyer, J.D.2    Dimick, J.B.3
  • 37
    • 80054764509 scopus 로고    scopus 로고
    • Risk prediction models for hospital readmission: a systematic review
    • Kansagara D, Englander H, Salanitro A, et al. Risk prediction models for hospital readmission: a systematic review. JAMA. 2011;306:1688-1698.
    • (2011) JAMA , vol.306 , pp. 1688-1698
    • Kansagara, D.1    Englander, H.2    Salanitro, A.3
  • 38
    • 84877680045 scopus 로고    scopus 로고
    • Department of Health and Human Services, Centers for Medicare and Medicaid Services, CMS Manual System, Pub 100-04 Medicare Claims Processing, November 3, 2006. Accessed September 5
    • Department of Health and Human Services, Centers for Medicare and Medicaid Services, CMS Manual System, Pub 100-04 Medicare Claims Processing, November 3, 2006. Available at: http://www. cms.gov/Regulations-and-Guidance/Guidance/Transmittals/Downloads/R1104CP.pdf. Accessed September 5, 2012.
    • (2012)


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.