-
1
-
-
0036829926
-
Defining and improving data quality in medical registries: A literature review, case study, and generic framework
-
Arts DG, De Keizer NF, Scheffer GJ. Defining and improving data quality in medical registries: a literature review, case study, and generic framework. J AmMed Inform Assoc. 2002;9(6):600-611.
-
(2002)
J AmMed Inform Assoc.
, vol.9
, Issue.6
, pp. 600-611
-
-
Arts, D.G.1
De Keizer, N.F.2
Scheffer, G.J.3
-
2
-
-
67649515088
-
Methods to analyze real-world databases and registries
-
Kremers HM. Methods to analyze real-world databases and registries. Bull NYU Hosp Jt Dis. 2009;67(2):193-197.
-
(2009)
Bull NYU Hosp Jt Dis.
, vol.67
, Issue.2
, pp. 193-197
-
-
Kremers, H.M.1
-
3
-
-
73249138897
-
Research using emergency department-related data sets: Current status and future directions
-
Hirshon JM, Warner M, Irvin CB, et al. Research using emergency department-related data sets: current status and future directions. Acad Emerg Med. 2009;16(11):1103-1109.
-
(2009)
Acad Emerg Med.
, vol.16
, Issue.11
, pp. 1103-1109
-
-
Hirshon, J.M.1
Warner, M.2
Irvin, C.B.3
-
4
-
-
58149105664
-
A primer in the evaluation of quality in acute care settings
-
Baldwin KB, Robertson JF. A primer in the evaluation of quality in acute care settings. Medsurg Nurs. 2008;17(4):241-246.
-
(2008)
Medsurg Nurs.
, vol.17
, Issue.4
, pp. 241-246
-
-
Baldwin, K.B.1
Robertson, J.F.2
-
5
-
-
44649119179
-
The value of trauma registries
-
Moore L, Clark DE. The value of trauma registries. Injury. 2008; 39(6):686-695.
-
(2008)
Injury.
, vol.39
, Issue.6
, pp. 686-695
-
-
Moore, L.1
Clark, D.E.2
-
6
-
-
77958514263
-
Administrative data have high variation in validity for recording heart failure
-
Quach S, Blais C, Quan H. Administrative data have high variation in validity for recording heart failure. Can J Cardiol. 2010;26(8): 306-312.
-
(2010)
Can J Cardiol.
, vol.26
, Issue.8
, pp. 306-312
-
-
Quach, S.1
Blais, C.2
Quan, H.3
-
7
-
-
80051565756
-
Accuracy of administrative claims data for polypectomy
-
Wyse JM, Joseph L, Barkun AN, Sewitch MJ. Accuracy of administrative claims data for polypectomy. CMAJ. 2011;183(11): E743-E747.
-
(2011)
CMAJ
, vol.183
, Issue.11
-
-
Wyse, J.M.1
Joseph, L.2
Barkun, A.N.3
Sewitch, M.J.4
-
8
-
-
80052027461
-
Administrative database research infrequently used validated diagnostic or procedural codes
-
van Walraven C, Bennett C, Forster AJ. Administrative database research infrequently used validated diagnostic or procedural codes. J Clin Epidemiol. 2011;64(10):1054-1059.
-
(2011)
J Clin Epidemiol.
, vol.64
, Issue.10
, pp. 1054-1059
-
-
Van Walraven, C.1
Bennett, C.2
Forster, A.J.3
-
9
-
-
33750218358
-
Assessing the validity of tuberculosis surveillance data in California
-
Sprinson JE, Lawton ES, Porco TC, Flood JM, Westenhouse JL. Assessing the validity of tuberculosis surveillance data in California. BMC Public Health. 2006;6:217.
-
(2006)
BMC Public Health.
, vol.6
, pp. 217
-
-
Sprinson, J.E.1
Lawton, E.S.2
Porco, T.C.3
Flood, J.M.4
Westenhouse, J.L.5
-
10
-
-
27644540561
-
Data cleaning: Detecting, diagnosing, and editing data abnormalities
-
Van den Broeck J, Cunningham SA, Eeckels R, Herbst K. Data cleaning: detecting, diagnosing, and editing data abnormalities. PLoS Med. 2005;2(10):e267.
-
(2005)
PLoS Med.
, vol.2
, Issue.10
-
-
Van Den Broeck, J.1
Cunningham, S.A.2
Eeckels, R.3
Herbst, K.4
-
11
-
-
76649124312
-
Data cleaning basics: Best practices in dealing with extreme scores
-
Osborne JW. Data cleaning basics: best practices in dealing with extreme scores. Newborn Infant Nurs Rev. 2010;10(1): 36-43.
-
(2010)
Newborn Infant Nurs Rev.
, vol.10
, Issue.1
, pp. 36-43
-
-
Osborne, J.W.1
-
12
-
-
34250689552
-
Advanced statistics: Missing data in clinical researchVpart 1: An introduction and conceptual framework
-
Haukoos JS, Newgard CD. Advanced statistics: missing data in clinical researchVpart 1: an introduction and conceptual framework. Acad Emerg Med. 2007;14(7):662-668.
-
(2007)
Acad Emerg Med.
, vol.14
, Issue.7
, pp. 662-668
-
-
Haukoos, J.S.1
Newgard, C.D.2
-
13
-
-
84866513330
-
Approaches for dealing with missing data in health care studies
-
Penny KI, Atkinson I. Approaches for dealing with missing data in health care studies. J Clin Nurs. 2012;21(19/20):2722-2729.
-
(2012)
J Clin Nurs.
, vol.21
, Issue.19-20
, pp. 2722-2729
-
-
Penny, K.I.1
Atkinson, I.2
-
14
-
-
67650519406
-
Females have fewer complications and lower mortality following trauma than similarly injured males: A risk adjusted analysis of adults in the National Trauma Data Bank
-
Haider AH, Crompton JG, Oyetunji T, et al. Females have fewer complications and lower mortality following trauma than similarly injured males: a risk adjusted analysis of adults in the National Trauma Data Bank. Surgery. 2009;146(2):308-315.
-
(2009)
Surgery.
, vol.146
, Issue.2
, pp. 308-315
-
-
Haider, A.H.1
Crompton, J.G.2
Oyetunji, T.3
-
15
-
-
80051800595
-
Validation of the IMPACT outcome prediction score using the Nottingham Head Injury Register dataset
-
Yeoman P, Pattani H, Silcocks P, Owen V, Fuller G. Validation of the IMPACT outcome prediction score using the Nottingham Head Injury Register dataset. J Trauma. 2011;71(2):387-392.
-
(2011)
J Trauma.
, vol.71
, Issue.2
, pp. 387-392
-
-
Yeoman, P.1
Pattani, H.2
Silcocks, P.3
Owen, V.4
Fuller, G.5
-
16
-
-
78649464693
-
Missing in action: A case study of the application ofmethods for dealing with missing data to trauma system benchmarking
-
O'ReillyGM, Jolley DJ, Cameron PA, Gabbe B.Missing in action: a case study of the application ofmethods for dealing with missing data to trauma system benchmarking. Acad Emerg Med. 2010; 17(10):1122-1129.
-
(2010)
Acad Emerg Med.
, vol.17
, Issue.10
, pp. 1122-1129
-
-
O'reilly, G.M.1
Jolley, D.J.2
Cameron, P.A.3
Gabbe, B.4
-
18
-
-
78649492264
-
Measuring quality with missing data: The invisible threat to national quality initiatives
-
Newgard CD, Haukoos JS. Measuring quality with missing data: the invisible threat to national quality initiatives. Acad Emerg Med. 2010;17(10):1130-1133.
-
(2010)
Acad Emerg Med.
, vol.17
, Issue.10
, pp. 1130-1133
-
-
Newgard, C.D.1
Haukoos, J.S.2
-
19
-
-
70350234768
-
A multiple imputation model for imputing missing physiologic data in the national trauma data bank
-
Moore L, Hanley JA, Turgeon AF, Lavoie A, Emond M. A multiple imputation model for imputing missing physiologic data in the national trauma data bank. J AmColl Surg. 2009;209(5):572-579.
-
(2009)
J AmColl Surg.
, vol.209
, Issue.5
, pp. 572-579
-
-
Moore, L.1
Hanley, J.A.2
Turgeon, A.F.3
Lavoie, A.4
Emond, M.5
-
20
-
-
34250614356
-
Advanced statistics: Missing data in clinical researchVpart 2: Multiple imputation
-
Newgard CD, Haukoos JS. Advanced statistics: missing data in clinical researchVpart 2: multiple imputation. Acad EmergMed. 2007;14(7):669-678.
-
(2007)
Acad EmergMed.
, vol.14
, Issue.7
, pp. 669-678
-
-
Newgard, C.D.1
Haukoos, J.S.2
-
21
-
-
0036479629
-
Focus on research methods: Multiple imutation for missing data
-
Patrician PA. Focus on research methods: multiple imutation for missing data. Res Nurs Health. 2002;25:76-84.
-
(2002)
Res Nurs Health.
, vol.25
, pp. 76-84
-
-
Patrician, P.A.1
-
22
-
-
84855177476
-
MissForestVnonparametric missing value imputation for mixed-type data
-
Stekhoven DJ, Buhlmann P. MissForestVnonparametric missing value imputation for mixed-type data. Bioinformatics. 2012;28(1):112-118.
-
(2012)
Bioinformatics.
, vol.28
, Issue.1
, pp. 112-118
-
-
Stekhoven, D.J.1
Buhlmann, P.2
-
23
-
-
8144225500
-
Using Medicare data to estimate the number of cases missed by a cancer registry: A 3-source capturerecapture model
-
McClish D, Penberthy L. Using Medicare data to estimate the number of cases missed by a cancer registry: a 3-source capturerecapture model. Med Care. 2004;42(11):1111-1116.
-
(2004)
Med Care.
, vol.42
, Issue.11
, pp. 1111-1116
-
-
McClish, D.1
Penberthy, L.2
-
24
-
-
84873898732
-
-
ACS. NTDB Reports and Publications. 2011.. Accessed November 27, 2011.
-
ACS. NTDB Reports and Publications. 2011. http://www.facs.org/trauma/ ntdb/docpub.html. Accessed November 27, 2011.
-
-
-
-
25
-
-
79952536428
-
Setting sample size to ensure narrow confidence intervals for precise estimation of population values
-
Corty EW, Corty RW. Setting sample size to ensure narrow confidence intervals for precise estimation of population values.Nurs Res. 2011;60(2):148-153.
-
(2011)
Nurs Res.
, vol.60
, Issue.2
, pp. 148-153
-
-
Corty, E.W.1
Corty, R.W.2
-
26
-
-
0004198559
-
-
The Bare Essentials. 3rd ed. Shelton, CT: B. C. Decker
-
Norman G, Streiner D. Biostatistics. The Bare Essentials. 3rd ed. Shelton, CT: B. C. Decker; 2008.
-
(2008)
Biostatistics
-
-
Norman, G.1
Streiner, D.2
-
27
-
-
42449114434
-
Statistical significance versus clinical significance
-
Houle TT, Stump DA. Statistical significance versus clinical significance. Semin Cardiothorac Vasc Anesth. 2008;12(1):5-6.
-
(2008)
Semin Cardiothorac Vasc Anesth.
, vol.12
, Issue.1
, pp. 5-6
-
-
Houle, T.T.1
Stump, D.A.2
-
28
-
-
56149115933
-
Statistical and clinical significance: Are they one and the same?
-
Pittman J, Rawl SM. Statistical and clinical significance: are they one and the same? J Wound Ostomy Contin Nurs. 2008;35(4): 374-376.
-
(2008)
J Wound Ostomy Contin Nurs.
, vol.35
, Issue.4
, pp. 374-376
-
-
Pittman, J.1
Rawl, S.M.2
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