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BMC Health Services Research
Published in: BMC Health Services Research 1/2014

Open Access 01-12-2014 | Research article

Validation of administrative health data for the pediatric population: a scoping review

Authors: Natalie J Shiff, Sadia Jama, Catherine Boden, Lisa M Lix

Published in: BMC Health Services Research | Issue 1/2014

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Abstract

Background

The purpose of this research was to perform a scoping review of published literature on the validity of administrative health data for ascertaining health conditions in the pediatric population (≤20 years).

Methods

A comprehensive search of OVID Medline (1946 - present), CINAHL (1937 - present) and EMBASE (1947 - present) was conducted. Characteristics of validation studies that were abstracted included the study population, health condition, topic of the validation (e.g., single diagnosis code versus case-finding algorithm), administrative and validation data sources. Inter-rater agreement was measured using Cohen’s κ. Extracted data were analyzed using descriptive statistics.

Results

A total of 37 articles met the study inclusion criteria. Cohen’s κ for study inclusion/exclusion and data abstraction was 0.88 and 0.97, respectively. Most studies validated administrative data from the USA (43.2%) and Canada (24.3%), and focused on inpatient records (67.6%). Case-finding algorithms (56.7%) were more frequently validated than diagnoses codes alone (37.8%). Five conditions were validated in more than one study: diabetes mellitus, inflammatory bowel disease, asthma, rotavirus infection, and tuberculosis.

Conclusions

This scoping review identified a number of gaps in the validation of administrative health data for pediatric populations, including limited investigation of outpatient populations and older pediatric age groups.
Appendix
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Literature
1.
Virnig BA, McBean M: Administrative data for public health surveillance and planning. Annu Rev Public Health. 2001, 22 (1): 213-230. 10.1146/annurev.publhealth.22.1.213.CrossRefPubMed
2.
van Walraven C, Austin P: Administrative database research has unique characteristics that can risk biased results. J Clin Epidemiol. 2012, 65 (2): 126-131. 10.1016/j.jclinepi.2011.08.002.CrossRefPubMed
3.
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. 10.1016/j.jclinepi.2011.01.001.CrossRefPubMed
4.
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. 10.1016/S0828-282X(10)70438-4.CrossRefPubMed
5.
Sharabiani MT, Aylin P, Bottle A: Systematic review of comorbidity indices for administrative data. Med Care. 2012, 50 (12): 1109-1118. 10.1097/MLR.0b013e31825f64d0.CrossRefPubMed
6.
Vlasschaert ME, Bejaimal SA, Hackam DG, Quinn R, Cuerden MS, Oliver MJ, Iansavichus A, Sultan N, Mills A, Garg AX: Validity of administrative database coding for kidney disease: a systematic review. Am J Kidney Dis. 2011, 57 (1): 29-43. 10.1053/j.ajkd.2010.08.031.CrossRefPubMed
7.
Benchimol EI, Manuel DG, To T, Griffiths AM, Rabeneck L, Guttmann A: Development and use of reporting guidelines for assessing the quality of validation studies of health administrative data. J Clin Epidemiol. 2011, 64 (8): 821-829. 10.1016/j.jclinepi.2010.10.006.CrossRefPubMed
8.
Cassidy JT: Textbook of Pediatric Rheumatology. 2011, Philadelphia, PA: Saunders, 6
9.
Arksey H, O’Malley L: Scoping studies: towards a methodological framework. Int J Soc Res Methodol. 2005, 8 (1): 19-32. 10.1080/1364557032000119616.CrossRef
10.
11.
Porta MS: International Epidemiological Association: A Dictionary of Epidemiology. 2008, Oxford; New York: Oxford University Press, 5
12.
Cohen J: A coefficient of agreement for nominal scales. Educ Psychol Meas. 1960, 20 (1): 37-46. 10.1177/001316446002000104.CrossRef
13.
Hodgson S, Beale L, Parslow RC, Feltbower RG, Jarup L: Creating a national register of childhood type 1 diabetes using routinely collected hospital data. Pediatr Diabetes. 2012, 13 (3): 235-243. 10.1111/j.1399-5448.2011.00815.x.CrossRefPubMed
14.
Amed S, Vanderloo SE, Metzger D, Collet JP, Reimer K, Mccrea P, Johnson JA: Validation of diabetes case definitions using administrative claims data. Diabetic Med. 2011, 28 (4): 424-427. 10.1111/j.1464-5491.2011.03238.x.CrossRefPubMed
15.
Dart AB, Martens PJ, Sellers EA, Brownell MD, Rigatto C, Dean HJ: Validation of a pediatric diabetes case definition using administrative health data in Manitoba. Canada Diabetes Care. 2011, 34 (4): 898-903. 10.2337/dc10-1572.CrossRefPubMed
16.
Guttmann A, Nakhla M, Henderson M, To T, Daneman D, Cauch-Dudek K, Wang X, Lam K, Hux J: Validation of a health administrative data algorithm for assessing the epidemiology of diabetes in Canadian children. Pediatr Diabetes. 2010, 11 (2): 122-128. 10.1111/j.1399-5448.2009.00539.x.CrossRefPubMed
17.
Liu L, Allison JE, Herrinton LJ: Validity of computerized diagnoses, procedures, and drugs for inflammatory bowel disease in a northern California managed care organization. Pharmacoepidemiol Drug Saf. 2009, 18 (11): 1086-1093. 10.1002/pds.1824.CrossRefPubMed
18.
Benchimol EI, Guttmann A, Griffiths AM, Rabeneck L, Mack DR, Brill H, Howard J, Guan J, To T: Increasing incidence of paediatric inflammatory bowel disease in Ontario, Canada: Evidence from health administrative data. Gut. 2009, 58 (11): 1490-1497. 10.1136/gut.2009.188383.CrossRefPubMed
19.
Moth G, Vedsted P, Schiotz PO: National registry diagnoses agree with medical records on hospitalized asthmatic children. Acta Paediatr. 2007, 96 (10): 1470-1473. 10.1111/j.1651-2227.2007.00460.x.CrossRefPubMed
20.
To T, Dell S, Dick PT, Cicutto L, Harris JK, MacLusky IB, Tassoudji M: Case verification of children with asthma in Ontario. Pediatr Allergy Immunol. 2006, 17 (1): 69-76. 10.1111/j.1399-3038.2005.00346.x.CrossRefPubMed
21.
Hsu VP, Staat MA, Roberts N, Thieman C, Bernstein DI, Bresee J, Glass RI, Parashar UD: Use of active surveillance to validate International Classification of Diseases code estimates of rotavirus hospitalizations in children. Pediatrics. 2005, 115 (1): 78-82.PubMed
22.
Matson DO, Estes MK: Impact of rotavirus infection at a large pediatric hospital. J Infect Dis. 1990, 162 (3): 598-604. 10.1093/infdis/162.3.598.CrossRefPubMed
23.
Siegel D, Song X, Klontz K, Pastor W, Singh N: Epidemiology of childhood tuberculosis: use and evaluation of the pediatric health information system to assess local and national incidence. Pediatr Infect Dis J. 2011, 30 (5): 428-430. 10.1097/INF.0b013e318211581e.CrossRefPubMed
24.
Trepka MJ, Beyer TO, Proctor ME, Davis JP: An evaluation of the completeness of tuberculosis case reporting using hospital billing and laboratory data; Wisconsin, 1995. Ann Epidemiol. 1999, 9 (7): 419-423. 10.1016/S1047-2797(99)00011-3.CrossRefPubMed
25.
Kuhle S, Kirk SF, Ohinmaa A, Veugelers PJ: Comparison of ICD code-based diagnosis of obesity with measured obesity in children and the implications for health care cost estimates. BMC Med Res Methodol. 2011, 11: 173-10.1186/1471-2288-11-173.CrossRefPubMedPubMedCentral
26.
Nash JQ, Chandrakumar M, Farrington CP, Williamson S, Miller E: Feasibility study for identifying adverse events attributable to vaccination by record linkage. Epidemiol Infect. 1995, 114 (3): 475-480. 10.1017/S0950268800052183.CrossRefPubMedPubMedCentral
27.
Kostylova A, Swaine B, Feldman D: Concordance between childhood injury diagnoses from two sources: An injury surveillance system and a physician billing claims database. Inj Prev. 2005, 11 (3): 186-190. 10.1136/ip.2004.006585.CrossRefPubMedPubMedCentral
28.
Dodds L, Spencer A, Shea S, Fell D, Armson BA, Allen AC, Bryson S: Validity of autism diagnoses using administrative health data. Chronic Dis Can. 2009, 29 (3): 102-107.PubMedPubMedCentral
29.
Breitfeld PP, Dale T, Kohne J, Hui S, Tierney WM: Accurate case finding using linked electronic clinical and administrative data at a children’s hospital. J Clin Epidemiol. 2001, 54 (10): 1037-1045. 10.1016/S0895-4356(01)00376-6.CrossRefPubMed
30.
Daley TC, Simeonsson RJ, Carlson E: Constructing and testing a disability index in a US sample of preschoolers with disabilities. Disabil Rehabil. 2009, 31 (7): 538-552. 10.1080/09638280802214352.CrossRefPubMed
31.
Das DK, Baker MG, Venugopal K: Increasing incidence of necrotizing fasciitis in New Zealand: A nationwide study over the period 1990 to 2006. J Infect. 2011, 63 (6): 429-433. 10.1016/j.jinf.2011.07.019.CrossRefPubMed
32.
Wu JJ, Black MH, Smith N, Porter AH, Jacobsen SJ, Koebnick C: Low prevalence of psoriasis among children and adolescents in a large multiethnic cohort in southern California. J Am Acad Dermatol. 2011, 65 (5): 957-964. 10.1016/j.jaad.2010.09.005.CrossRefPubMed
33.
O’Sullivan CE, Baker MG: Proposed epidemiological case definition for serious skin infection in children. J Paediatr Child Health. 2010, 46 (4): 176-183. 10.1111/j.1440-1754.2009.01658.x.CrossRefPubMed
34.
Larsen H, Nielsen GL, Bendsen J, Flint C, Olsen J, Sørensen H: Predictive value and completeness of the registration of congenital abnormalities in three Danish population-based registries. Scand J Public Health. 2003, 31 (1): 12-16. 10.1080/14034940210134194.CrossRefPubMed
35.
Frohnert BK, Lussky RC, Alms MA, Mendelsohn NJ, Symonik DM, Falken MC: Validity of hospital discharge data for identifying infants with cardiac defects. J Perinatol. 2005, 25 (11): 737-742. 10.1038/sj.jp.7211382.CrossRefPubMed
36.
Beitel AJ, Olson KL, Reis BY, Mandl KD: Use of emergency department chief complaint and diagnostic codes for identifying respiratory illness in a pediatric population. Pediatr Emerg Care. 2004, 20 (6): 355-360. 10.1097/01.pec.0000133608.96957.b9.CrossRefPubMed
37.
Nelson EA, Tam JS, Yu LM, Li AM, Chan PK, Sung RY: Assessing disease burden of respiratory disorders in Hong Kong children with hospital discharge data and linked laboratory data. Hong Kong Med J. 2007, 13 (2): 114-121.PubMed
38.
Hamvas A, Kwong P, DeBaun M, Schramm W, Cole FS: Hyaline membrane disease is underreported in a linked birth-infant death certificate database. Am J Public Health. 1998, 88 (9): 1387-1389. 10.2105/AJPH.88.9.1387.CrossRefPubMedPubMedCentral
39.
Vestergaard M, Obel C, Henriksen TB, Christensen J, Madsen KM, Ostergaard JR, Olsen J: The Danish National Hospital Register is a valuable study base for epidemiologic research in febrile seizures. J Clin Epidemiol. 2006, 59 (1): 61-66. 10.1016/j.jclinepi.2005.05.008.CrossRefPubMed
40.
Nelson EAS, Chiu SS, Ip KS, Lau D, Lau YL, Ng CH, Ng DK, Poon KH, Yiu WL, Kwok WK, Tam P, Yeung CK, Tam JS, Bock H, Boudville I, Tang HH: Intussusception trends in Hong Kong children. Hong Kong Med J. 2007, 13 (4): 279-283.
41.
Chang S, Begier EM, Schech SD, Venus P, Shatin D, Braun MM, Ball R: Perinatal hepatitis B transmission and vaccination timing in a managed care cohort: assessment of the temporary delay in newborn hepatitis B vaccination due to thimerosal content. Pediatr Infect Dis J. 2007, 26 (4): 329-333. 10.1097/01.inf.0000258616.12752.51.CrossRefPubMed
42.
Shaklee J, Zerr DM, Elward A, Newland J, Leckerman K, Asti L, Guth R, Bass J, Selvarangan R, Coffin S, Zaoutis T: Improving surveillance for pediatric Clostridium difficile infection: Derivation and validation of an accurate case-finding tool. Pediatr Infect Dis J. 2011, 30 (3): e38-e40. 10.1097/INF.0b013e3182027c22.CrossRefPubMed
43.
Dydensborg S, Toftedal P, Biaggi M, Lillevang ST, Hansen DG, Husby S: Increasing prevalence of coeliac disease in Denmark: a linkage study combining national registries. Acta Paediatr. 2012, 101 (2): 179-184. 10.1111/j.1651-2227.2011.02392.x.CrossRefPubMed
44.
Tieder JS, Hall M, Auger KA, Hain PD, Jerardi KE, Myers AL, Rahman SS, Williams DJ, Shah SS: Accuracy of Administrative Billing Codes to Detect Urinary Tract Infection Hospitalizations. Pediatrics. 2011, 128 (2): 323-330. 10.1542/peds.2010-2064.CrossRefPubMedPubMedCentral
45.
Ong KL, Apostal M, Comstock N, Hurd S, Webb TH, Mickelson S, Scheftel J, Smith G, Shiferaw B, Boothe E, Gould LH: Strategies for surveillance of pediatric hemolytic uremic syndrome: Foodborne Diseases Active Surveillance Network (FoodNet), 2000–2007. Clin Infect Dis. 2012, 54 (Suppl 5): S424-S431. 10.1093/cid/cis208.CrossRefPubMedPubMedCentral
46.
Heckbert SR, Stryker WS, Coltin KL, Manson JE, Platt R: Serum sickness in children after antibiotic exposure: estimates of occurrence and morbidity in a health maintenance organization population. Am J Epidemiol. 1990, 132 (2): 336-342.PubMed
47.
Tuckuviene R, Kristensen SR, Helgestad J, Christensen AL, Johnsen SP: Predictive value of pediatric thrombosis diagnoses in the Danish National Patient Registry. Clin Epidemiol. 2010, 2 (1): 107-122.CrossRefPubMedPubMedCentral
48.
Taylor LK, Travis S, Pym M, Olive E, Henderson-Smart DJ: How useful are hospital morbidity data for monitoring conditions occurring in the perinatal period?. Aust N Z J Obstet Gynaecol. 2005, 45 (1): 36-41. 10.1111/j.1479-828X.2005.00339.x.CrossRefPubMed
49.
West SL, D’Aloisio AA, Ringel-Kulka T, Waller AE, Clayton Bordley W: Population-based drug-related anaphylaxis in children and adolescents captured by South Carolina Emergency Room Hospital Discharge Database (SCERHDD) (2000–2002). Pharmacoepidemiol Drug Saf. 2007, 16 (12): 1255-1267. 10.1002/pds.1502.CrossRefPubMed
50.
Van Cleave J, Gortmaker SL, Perrin JM: Dynamics of obesity and chronic health conditions among children and youth. JAMA. 2010, 303 (7): 623-630. 10.1001/jama.2010.104.CrossRefPubMed
51.
Halfon N, Newacheck PW: Evolving notions of childhood chronic illness. JAMA. 2010, 303 (7): 665-666. 10.1001/jama.2010.130.CrossRefPubMed
52.
Wise PH: The future pediatrician: the challenge of chronic illness. J Pediatr. 2007, 151 (5): S6-S10. 10.1016/j.jpeds.2007.08.013.CrossRefPubMed
53.
Kim SY, Servi A, Polinski JM, Mogun H, Weinblatt ME, Katz JN: Validation of rheumatoid arthritis diagnoses in health care utilization data. Arthritis Res Ther. 2011, 13: R32-10.1186/ar3260.CrossRefPubMedPubMedCentral
54.
Ng B, Aslam F, Petersen NJ, Yu H, Suarez-almazor ME: Identification of rheumatoid arthritis patients using an administrative database: a Veterans Affairs study. Arthritis Res Ther. 2012, 64 (10): 1490-1496.CrossRef
55.
Singh JA, Holmgren AR, Noorbaloochi S: Accuracy of Veterans Administration databases for a diagnosis of rheumatoid arthritis. Arthritis Rheum. 2004, 51 (6): 952-957. 10.1002/art.20827.CrossRefPubMed
Metadata
Title
Validation of administrative health data for the pediatric population: a scoping review
Authors
Natalie J Shiff
Sadia Jama
Catherine Boden
Lisa M Lix
Publication date
01-12-2014
Publisher
BioMed Central
Published in
BMC Health Services Research / Issue 1/2014
Electronic ISSN: 1472-6963
DOI
https://doi.org/10.1186/1472-6963-14-236

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