메뉴 건너뛰기




Volumn 55, Issue 7, 2017, Pages 698-705

Identifying Increased Risk of Readmission and In-hospital Mortality Using Hospital Administrative Data: The AHRQ Elixhauser Comorbidity Index

Author keywords

comorbidity index; Elixhauser comorbidity system; hospital readmission; in hospital mortality; State Inpatient Databases

Indexed keywords

ACQUIRED IMMUNE DEFICIENCY SYNDROME; ACUTE HEART INFARCTION; ACUTE KIDNEY FAILURE; ADMINISTRATIVE CLAIMS (HEALTH CARE); ADULT; AGED; ALCOHOL ABUSE; ANEMIA; ARTICLE; BLOOD CLOTTING DISORDER; CHRONIC OBSTRUCTIVE LUNG DISEASE; COMORBIDITY; CONGESTIVE HEART FAILURE; DEMOGRAPHY; DEPRESSION; DIABETES MELLITUS; DISEASE SEVERITY; DRUG ABUSE; ELECTROLYTE DISTURBANCE; ELIXHAUSER COMORBIDITY INDEX; FEMALE; GROUPS BY AGE; HEALTH CARE COST; HEALTH CARE UTILIZATION; HOSPITAL DISCHARGE; HOSPITAL MORTALITY; HOSPITAL READMISSION; HUMAN; HYPERTENSION; HYPOTHYROIDISM; LENGTH OF STAY; LIVER DISEASE; LYMPHOMA; MAJOR CLINICAL STUDY; MALE; MEDICAID; MEDICALLY UNINSURED; MEDICARE; METASTASIS; MIDDLE AGED; NEUROLOGIC DISEASE; OBESITY; PARALYSIS; PEPTIC ULCER; PERIPHERAL VASCULAR DISEASE; PNEUMONIA; PRIORITY JOURNAL; PRIVATE HEALTH INSURANCE; RESPIRATORY FAILURE; RHEUMATOID ARTHRITIS; RISK ASSESSMENT; SCHIZOPHRENIA; SEPTICEMIA; SEX DIFFERENCE; SOLID MALIGNANT NEOPLASM; VALVULAR HEART DISEASE; VERY ELDERLY; WEIGHT REDUCTION; ADOLESCENT; FACTUAL DATABASE; PROCEDURES; STATISTICAL MODEL; TRENDS; YOUNG ADULT;

EID: 85021320245     PISSN: 00257079     EISSN: 15371948     Source Type: Journal    
DOI: 10.1097/MLR.0000000000000735     Document Type: Article
Times cited : (611)

References (30)
  • 1
    • 0031613172 scopus 로고    scopus 로고
    • Comorbidity measures for use with administrative data
    • Elixhauser A, Steiner C, Harris DR, et al. Comorbidity measures for use with administrative data. Med Care. 1998;36:8-27.
    • (1998) Med Care , vol.36 , pp. 8-27
    • Elixhauser, A.1    Steiner, C.2    Harris, D.R.3
  • 2
    • 0035403769 scopus 로고    scopus 로고
    • Comparison of the performance of two comorbidity measures, with and without information from prior hospitalizations
    • Stukenborg GJ, Wagner DP, Connors AF Jr. Comparison of the performance of two comorbidity measures, with and without information from prior hospitalizations. Med Care. 2001;39:727-739.
    • (2001) Med Care , vol.39 , pp. 727-739
    • Stukenborg, G.J.1    Wagner, D.P.2    Connors, A.F.3
  • 3
    • 84905962173 scopus 로고    scopus 로고
    • The Elixhauser comorbidity method outperforms the Charlson index in predicting inpatient death after orthopaedic surgery
    • Menendez ME, Neuhaus V, van Dijk CN, et al. The Elixhauser comorbidity method outperforms the Charlson index in predicting inpatient death after orthopaedic surgery. Clin Orthop Relat Res. 2014;472:2878-2886.
    • (2014) Clin Orthop Relat Res. , vol.472 , pp. 2878-2886
    • Menendez, M.E.1    Neuhaus, V.2    Van-Dijk, C.N.3
  • 4
    • 67449083886 scopus 로고    scopus 로고
    • A modification of the Elixhauser comorbidity measures into a point system for hospital death using administrative data
    • van Walraven C, Austin PC, Jennings A, et al. A modification of the Elixhauser comorbidity measures into a point system for hospital death using administrative data. Med Care. 2009;47:626-633.
    • (2009) Med Care , vol.47 , pp. 626-633
    • Van-Walraven, C.1    Austin, P.C.2    Jennings, A.3
  • 5
    • 84925970735 scopus 로고    scopus 로고
    • A new Elixhauser-based comorbidity summary measure to predict in-hospital mortality
    • Thompson NR, Fan Y, Dalton JE, et al. A new Elixhauser-based comorbidity summary measure to predict in-hospital mortality. Med Care. 2015;53:374-379.
    • (2015) Med Care , vol.53 , pp. 374-379
    • Thompson, N.R.1    Fan, Y.2    Dalton, J.E.3
  • 6
    • 84891795475 scopus 로고    scopus 로고
    • Analysis of early accountable care organizations defines patient, structural, cost, and quality-of-care characteristics
    • Epstein AM, Jha AK, Orav EJ, et al. Analysis of early accountable care organizations defines patient, structural, cost, and quality-of-care characteristics. Health Aff (Millwood). 2014;33:95-102.
    • (2014) Health Aff (Millwood) , vol.33 , pp. 95-102
    • Epstein, A.M.1    Jha, A.K.2    Orav, E.J.3
  • 7
    • 84860710460 scopus 로고    scopus 로고
    • Adherence and dosing frequency of common medications for cardiovascular patients
    • Bae JP, Dobesh PP, Klepser DG, et al. Adherence and dosing frequency of common medications for cardiovascular patients. Am J Manag Care. 2012;18:139-146.
    • (2012) Am J Manag Care , vol.18 , pp. 139-146
    • Bae, J.P.1    Dobesh, P.P.2    Klepser, D.G.3
  • 8
    • 84908149192 scopus 로고    scopus 로고
    • Hospital and emergency department factors associated with variations in missed diagnosis and costs for patients age 65 years and older with acute myocardial infarction who present to emergency departments
    • Wilson M, Welch J, Schuur J, et al. Hospital and emergency department factors associated with variations in missed diagnosis and costs for patients age 65 years and older with acute myocardial infarction who present to emergency departments. Acad Emerg Med. 2014;21:1101-1108.
    • (2014) Acad Emerg Med. , vol.21 , pp. 1101-1108
    • Wilson, M.1    Welch, J.2    Schuur, J.3
  • 9
    • 84942578393 scopus 로고    scopus 로고
    • Why summary comorbidity measures such as the Charlson comorbidity index and Elixhauser score work
    • Austin SR, Wong YN, Uzzo RG, et al. Why summary comorbidity measures such as the Charlson comorbidity index and Elixhauser score work. Med Care. 2015;53:e65-e72.
    • (2015) Med Care , vol.53 , pp. e65-e72
    • Austin, S.R.1    Wong, Y.N.2    Uzzo, R.G.3
  • 10
    • 0023092594 scopus 로고
    • A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation
    • Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40:373-383.
    • (1987) J Chronic Dis. , vol.40 , pp. 373-383
    • Charlson, M.E.1    Pompei, P.2    Ales, K.L.3
  • 11
    • 0026639706 scopus 로고
    • Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases
    • Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol. 1992;45:613-619.
    • (1992) J Clin Epidemiol. , vol.45 , pp. 613-619
    • Deyo, R.A.1    Cherkin, D.C.2    Ciol, M.A.3
  • 12
    • 79551546685 scopus 로고    scopus 로고
    • Redefining readmission risk factors for general medicine patients
    • Allaudeen N, Vidyarthi A, Maselli J, et al. Redefining readmission risk factors for general medicine patients. J Hosp Med. 2011;6:54-60.
    • (2011) J Hosp Med. , vol.6 , pp. 54-60
    • Allaudeen, N.1    Vidyarthi, A.2    Maselli, J.3
  • 13
    • 77957665221 scopus 로고    scopus 로고
    • Risk factors for 30-day hospital readmission in patients Z65 years of age
    • Silverstein MD, Qin H, Mercer SQ, et al. Risk factors for 30-day hospital readmission in patients Z65 years of age. Proc (Bayl Univ Med Cent). 2008;21:363-372.
    • (2008) Proc (Bayl Univ Med Cent) , vol.21 , pp. 363-372
    • Silverstein, M.D.1    Qin, H.2    Mercer, S.Q.3
  • 14
    • 85021351231 scopus 로고    scopus 로고
    • Rockville, MD: Agency for Healthcare Research and Quality; Accessed March 17, 2016
    • Healthcare Cost and Utilization Project (HCUP). HCUP State Inpatient Databases (SID) 2011-2012. Rockville, MD: Agency for Healthcare Research and Quality; 2016. Available at: www.hcup-us.ahrq.gov/sidoverview.jsp. Accessed March 17, 2016.
    • (2016) HCUP State Inpatient Databases (SID) 2011-2012
  • 15
    • 84945453846 scopus 로고    scopus 로고
    • Accessed November 2, 2015
    • American Hospital Association (AHA). Fast facts on US hospitals. 2015. Available at: www.aha.org/research/rc/stat-studies/fast-facts.shtml. Accessed November 2, 2015.
    • (2015) Fast Facts on US Hospitals
  • 16
    • 85021351657 scopus 로고    scopus 로고
    • Rockville, MD. Accessed October 29, 2015
    • Agency for Healthcare Research and Quality. Inpatient quality indicators overview. Rockville, MD. 2015. Available at: www.qualityindicators.ahrq.gov/modules/iqi-resources.aspx. Accessed October 29, 2015.
    • (2015) Inpatient Quality Indicators Overview
  • 17
    • 85021330286 scopus 로고    scopus 로고
    • Rockville, MD: Agency for Healthcare Research and Quality; Accessed August 19, 2015
    • Healthcare Cost and Utilization Project (HCUP). Methods: Calculating Readmissions for HCUPnet. Rockville, MD: Agency for Healthcare Research and Quality; 2015. Available at: http://hcupnet.ahrq.gov/HCUPnet.app/Methods-HCUPnet%20readmissions.pdf?JS= Y. Accessed August 19, 2015.
    • (2015) Methods: Calculating Readmissions for HCUPnet
  • 18
    • 85021374879 scopus 로고    scopus 로고
    • Prepared for Centers for Medicare and Medicaid Services (CMS). Accessed March 17, 2016
    • Yale New Haven Health Services Corporation, Center for Outcomes Research and Evaluation. Measures updates and specifications report hospital-level 30-day risk-standardization readmission measures. Prepared for Centers for Medicare and Medicaid Services (CMS). 2014. Available at: http://altarum.org/sites/default/files/uploaded-publicationfiles/Rdmsn-Msr-Updts-HWR-0714-0.pdf. Accessed March 17, 2016.
    • (2014) Measures Updates and Specifications Report Hospital-level 30-day Risk-standardization Readmission Measures
  • 19
    • 33745282710 scopus 로고    scopus 로고
    • Rockville, MD: Agency for Healthcare Research and Quality; Accessed October 29, 2015
    • Healthcare Cost and Utilization Project (HCUP). Clinical Classifications Software (CCS) for ICD-9-CM. Rockville, MD: Agency for Healthcare Research and Quality; 2015. Available at: www.hcup-us. ahrq.gov/toolssoftware/ccs/ccs.jsp. Accessed October 29, 2015.
    • (2015) Clinical Classifications Software (CCS) for ICD-9-CM
  • 20
    • 85021310581 scopus 로고    scopus 로고
    • Rockville, MD: Agency for Healthcare Research and Quality; Accessed October 29, 2015
    • Healthcare Cost and Utilization Project (HCUP). Elixhauser Comorbidity Software, Version b 37. Rockville, MD: Agency for Healthcare Research and Quality; 2015. Available at: www.hcup-us.ahrq.gov/toolssoftware/comorbidity/comorbidity.jsp. Accessed October 29, 2015.
    • (2015) Elixhauser Comorbidity Software, Version B 37
  • 22
    • 2442682859 scopus 로고    scopus 로고
    • Presentation of multivariate data for clinical use: The Framingham Study risk score functions
    • Sullivan LM, Massaro JM, D'Agostino RB Sr. Presentation of multivariate data for clinical use: the Framingham Study risk score functions. Stat Med. 2004;23:1631-1660.
    • (2004) Stat Med. , vol.23 , pp. 1631-1660
    • Sullivan, L.M.1    Massaro, J.M.2    D'Agostino, R.B.3
  • 24
    • 84870061056 scopus 로고    scopus 로고
    • Systematic review of comorbidity indices for administrative data
    • Sharabiani MT, Aylin P, Bottle A. Systematic review of comorbidity indices for administrative data. Med Care. 2012;50:1109-1118.
    • (2012) Med Care , vol.50 , pp. 1109-1118
    • Sharabiani, M.T.1    Aylin, P.2    Bottle, A.3
  • 25
    • 0029944493 scopus 로고    scopus 로고
    • Searching for an improved clinical comorbidity index for use with ICD-9-CM administrative data
    • Ghali WA, Hall RE, Rosen AK, et al. Searching for an improved clinical comorbidity index for use with ICD-9-CM administrative data. J Clin Epidemiol. 1996;49:273-278.
    • (1996) J Clin Epidemiol. , vol.49 , pp. 273-278
    • Ghali, W.A.1    Hall, R.E.2    Rosen, A.K.3
  • 26
    • 0033762023 scopus 로고    scopus 로고
    • Use of comorbidity scores for control of confounding in studies using administrative databases
    • Schneeweiss S, Maclure M. Use of comorbidity scores for control of confounding in studies using administrative databases. Int J Epidemiol. 2000;29:891-898.
    • (2000) Int J Epidemiol. , vol.29 , pp. 891-898
    • Schneeweiss, S.1    Maclure, M.2
  • 27
    • 44849091245 scopus 로고    scopus 로고
    • The prognostic analogue of the propensity score
    • Hansen B. The prognostic analogue of the propensity score. Biometrika. 2008;95:481-488.
    • (2008) Biometrika , vol.95 , pp. 481-488
    • Hansen, B.1
  • 28
    • 85021330235 scopus 로고    scopus 로고
    • Rockville, MD: Agency for Healthcare Research and Quality; Accessed March 17, 2016
    • Healthcare Cost and Utilization Project (HCUP). Elixhauser Comorbidity Software for ICD-10-CM. Rockville, MD: Agency for Healthcare Research and Quality; 2015. Available at: www.hcup-us.ahrq.gov/toolssoftware/comorbidityicd10/comorbidity-icd10.jsp. Accessed March 17, 2016.
    • (2015) Elixhauser Comorbidity Software for ICD-10-CM
  • 29
    • 84896589414 scopus 로고    scopus 로고
    • Exploration of ICD-9-CM coding of chronic diseases within the Elixhauser comorbidity measure in patients with chronic heart failure
    • Garvin JH, Redd A, Bolton D, et al. Exploration of ICD-9-CM coding of chronic diseases within the Elixhauser comorbidity measure in patients with chronic heart failure. Perspect Health Inf Manag. 2013;10:1-30.
    • (2013) Perspect Health Inf Manag. , vol.10 , pp. 1-30
    • Garvin, J.H.1    Redd, A.2    Bolton, D.3
  • 30
    • 34548073902 scopus 로고    scopus 로고
    • Assessing and using comorbidity measures in elderly veterans with lower extremity amputations
    • Kurichi JE, Stineman MG, Kwong PL, et al. Assessing and using comorbidity measures in elderly veterans with lower extremity amputations. Gerontology. 2007;53:255-259.
    • (2007) Gerontology , vol.53 , pp. 255-259
    • Kurichi, J.E.1    Stineman, M.G.2    Kwong, P.L.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.