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Results: 1 to 20 of 102

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 3;297(1):71-6.

PMID:
17200477
[PubMed - indexed for MEDLINE]
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 Jan-Feb;29(1):69-81. doi: 10.1177/0272989X08323297. Epub 2008 Sep 23.

PMID:
18812585
[PubMed - indexed for MEDLINE]
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.

PMID:
17968182
[PubMed - indexed for MEDLINE]
4.

Laboratory values improve predictions of hospital mortality.

Pine M, Jones B, Lou YB.

Int J Qual Health Care. 1998 Dec;10(6):491-501.

PMID:
9928588
[PubMed - indexed for MEDLINE]
Free Article
5.

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. doi: 10.1097/MLR.0b013e318158aed6.

PMID:
18219238
[PubMed - indexed for MEDLINE]
6.

Predictions of hospital mortality rates: a comparison of data sources.

Pine M, Norusis M, Jones B, Rosenthal GE.

Ann Intern Med. 1997 Mar 1;126(5):347-54.

PMID:
9054278
[PubMed - indexed for MEDLINE]
7.
8.

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. Erratum in: Am Surg. 2007 Feb;73(2):199.

PMID:
17120944
[PubMed - indexed for MEDLINE]
9.

[Volume and health outcomes: evidence from systematic reviews and from evaluation of Italian hospital data].

Amato L, Colais P, Davoli M, Ferroni E, Fusco D, Minozzi S, Moirano F, Sciattella P, Vecchi S, Ventura M, Perucci CA.

Epidemiol Prev. 2013 Mar-Jun;37(2-3 Suppl 2):1-100. Review. Italian.

PMID:
23851286
[PubMed - indexed for MEDLINE]
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.

PMID:
15051710
[PubMed - indexed for MEDLINE]
Free Article
11.

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 18;308(3):257-64. doi: 10.1001/jama.2012.7870.

PMID:
22797643
[PubMed - indexed for MEDLINE]
12.

Relationship between Medicare's hospital compare performance measures and mortality rates.

Werner RM, Bradlow ET.

JAMA. 2006 Dec 13;296(22):2694-702. Erratum in: JAMA. 2007 Feb 21;297(7):700.

PMID:
17164455
[PubMed - indexed for MEDLINE]
13.

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 Oct-Dec;20(4):253-62. doi: 10.1097/QMH.0b013e318231cf4f.

PMID:
21971023
[PubMed - indexed for MEDLINE]
14.

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.

PMID:
16899015
[PubMed - indexed for MEDLINE]
Free PMC Article
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. Epub 2007 May 30.

PMID:
17537190
[PubMed - indexed for MEDLINE]
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. doi: 10.1097/MLR.0b013e3181589bb6.

PMID:
18388836
[PubMed - indexed for MEDLINE]
17.

Comparison of clinical and administrative data sources for hospital coronary artery bypass graft surgery report cards.

Shahian DM, Silverstein T, Lovett AF, Wolf RE, Normand SL.

Circulation. 2007 Mar 27;115(12):1518-27. Epub 2007 Mar 12.

PMID:
17353447
[PubMed - indexed for MEDLINE]
Free Article
18.

Disability as a covariate in risk adjustment models for predicting hospital deaths.

Iezzoni LI.

Ann Epidemiol. 2014 Jan;24(1):17-22. doi: 10.1016/j.annepidem.2013.10.016. Epub 2013 Oct 29.

PMID:
24262999
[PubMed - indexed for MEDLINE]
19.

Refinement of the HCUP Quality Indicators.

Davies SM, Geppert J, McClellan M, McDonald KM, Romano PS, Shojania KG.

Rockville (MD): Agency for Healthcare Research and Quality (US); 2001 May.

PMID:
20734520
[PubMed]
Books & Documents
20.

Should we add clinical variables to administrative data?: The case of risk-adjusted case fatality rates after admission for acute myocardial infarction.

Johnston TC, Coory MD, Scott I, Duckett S.

Med Care. 2007 Dec;45(12):1180-5.

PMID:
18007168
[PubMed - indexed for MEDLINE]

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