The Accuracy of Reporting of the Hypertensive Disorders of Pregnancy in Population Health Data

REFERENCES

• Zhang J, Meikle S, Trumble A. Severe maternal morbidity associated with hypertensive disorders in pregnancy in the United States. Hypertens Pregnancy. 2003; 22: 203–212
   Google Scholar
• Juurlink DN, Mamdani MM, Lee DS, et al. Rates of hyperkalemia after publication of the Randomized Aldactone Evaluation Study. N Engl J Med. 2004; 351: 543–551
   Google Scholar
• Moodley J. Maternal deaths associated with hypertensive disorders of pregnancy: a population-based study. Hypertens Pregnancy 2004; 23: 247–256
   PubMed Web of Science ®Google Scholar
• Ellekjaer H, Holmen J, Kruger O, et al. Identification of incident stroke in Norway. Stroke. 1999; 30: 56–60
   Google Scholar
• Marelli AJ, Mackie AS, Ionescu-Ittu R, et al. Congenital heart disease in the general population: changing prevalence and age distribution. Circulation. 2007; 115: 163–172
   Google Scholar
• Nassar N, Bower C, Barker A. Increasing prevalence of hypospadias in Western Australia, 1980–2000. Arch Dis Child. 2007; 92: 580–584
   Google Scholar
• Lawler J, Osman M, Shelton JA, et al. Population-based analysis of hypertensive disorders in pregnancy. Hypertens Pregnancy. 2007; 26: 67–76
   Google Scholar
• Roberts CL, Algert CS, Morris JM, et al. Hypertensive disorders in pregnancy: a population-based study. Med J Aust 2005; 182: 332–335
   PubMed Web of Science ®Google Scholar
• Dawson LM, Parfrey PS, Hefferton D, et al. Familial risk of preeclampsia in Newfoundland: a population-based study. J Am Soc Nephrol 2002; 13: 1901–1906
   PubMed Web of Science ®Google Scholar
• Lee W, O'Connell CM, Baskett TF. Maternal and perinatal outcomes of eclampsia: Nova Scotia, 1981–2000. J Obstet Gynaecol Canada 2004; 26: 119–123
   PubMedGoogle Scholar
• Jacobs DJ, Vreeburg SA, Dekker GA, et al. Aust N Z J Obstet Gynaecol. Risk factors for hypertension during pregnancy in South Australia. 2003; 43: 421–428
   Google Scholar
• Moller B, Lindmark G. Eclampsia in Sweden, 1976–1980. Acta Obstet Gynecol Scand. 1986; 65: 307–314
   Google Scholar
• Stanley FJ, Croft ML, Gibbins J, et al. A population database for maternal and child health research in Western Australia using record linkage. Paediatr Perinat Epidemiol. 1994; 8: 433–447
   Google Scholar
• Bright RA, Avorn J, Everitt DE. Medicaid data as a resource for epidemiologic studies: strengths and limitations. J Clin Epidemiol 1989; 42: 937–945
   PubMed Web of Science ®Google Scholar
• Lydon-Rochelle MT, Holt VL, Cardenas V, et al. The reporting of pre-existing maternal medical conditions and complications of pregnancy on birth certificates and in hospital discharge data. Am J Obstet Gynecol 2005; 193: 125–134
   PubMed Web of Science ®Google Scholar
• Malenka DJ, McLerran D, Roos N, et al. Using administrative data to describe casemix: a comparison with the medical record. J. Clin. Epidemiol. 1994; 47: 1027–1032
   PubMed Web of Science ®Google Scholar
• Roberts CL, Algert CS, Ford JB. Methods for dealing with discrepant records in linked population health datasets: a cross-sectional study. BMC Health Serv Res. 2007; 7: 12
   Google Scholar
• Schoendorf KC, Branum AM. The use of United States vital statistics in perinatal and obstetric research. Am J Obstet Gynecol 2006; 194: 911–915
   PubMed Web of Science ®Google Scholar
• Henderson T, Shepheard J, Sundararajan V. Quality of diagnosis and procedure coding in ICD-10 administrative data. Med Care. 2006; 44: 1011–1019
   Google Scholar
• Romano PS, Mark DH. Bias in the coding of hospital discharge data and its implications for quality assessment. Med Care. 1994; 32: 81–90
   Google Scholar
• Fisher ES, Whaley FS, Krushat WM, et al. The accuracy of Medicare's hospital claims data: progress has been made, but problems remain. Am J Public Health 1992; 82: 243–248
   PubMed Web of Science ®Google Scholar
• Humphries KH, Rankin JM, Carere RG, et al. Co-morbidity data in outcomes research: are clinical data derived from administrative databases a reliable alternative to chart review?. J Clin Epidemiol 2000; 53: 343–349
   PubMed Web of Science ®Google Scholar
• Taylor L, Travis S, Pym M, et al. How useful are hospital morbidity data for monitoring conditions occurring in the perinatal period? Aust N Z J Obstet Gynaecol. 2005; 45: 36–41
   Google Scholar
• Dobie SA, Baldwin LM, Rosenblatt RA, et al. How well do birth certificates describe the pregnancies they report? The Washington State experience with low-risk pregnancies. Matern Child Health J. 1998; 2: 145–154
   Google Scholar
• DiGiuseppe DL, Aron DC, Ranbom L, et al. Reliability of birth certificate data: a multi-hospital comparison to medical records information. Matern Child Health J 2002; 6: 169–179
   PubMedGoogle Scholar
• Yasmeen S, Romano PS, Schembri ME, et al. Accuracy of obstetric diagnoses and procedures in hospital discharge data. Am J Obstet Gynecol 2006; 194: 992–1001
   PubMed Web of Science ®Google Scholar
• Geller SE, Ahmed S, Brown HL, et al. International Classification of Disease 9th Revision for Coding preeclampsia: How accurate is it?. Aim J Obstet Gynecol 2004; 190: 1629–1634
   PubMed Web of Science ®Google Scholar
• Roos LL, Roos NP, Jr., Cageorge SM, et al. How good are the data? Reliability of one health care data bank. Med Care. 1982; 20: 266–276
   Google Scholar
• National Centre for Classification in Health. The international statistical classification of diseases and related health problems, 10th revision, Australian modification (ICD-10-AM). National Centre for Classification in Health, University of Sydney, Sydney 2004
   Google Scholar
• Roberts CL, Cameron CA, Bell JC, et al. Measuring maternal morbidity in routinely collected data: Development and validation of a maternal morbidity outcome indication. Med Care. 2008; 46, (in press).
   Google Scholar
• National High Blood Pressure Education Program Working Group on High Blood Pressure in Pregnancy. Report of the National High Blood Pressure Education Program Working Group on High Blood Pressure in Pregnancy. Am J Obstet Gynecol 2000; 183: S1–S22
   PubMed Web of Science ®Google Scholar
• Brown MA, Hague WM, Higgins J, et al. The detection, investigation and management of hypertension in pregnancy: full consensus statement. Aust N Z J Obstet Gynaecol 2000; 40: 139–155
   PubMed Web of Science ®Google Scholar
• Waterstone M, Bewley S, Wolfe C. Incidence and predictors of severe obstetric morbidity: case-control study. BMJ 2001; 322: 1089–1093
   PubMed Web of Science ®Google Scholar
• http://cancercenter.mayo.edu/mayo/research/biostat/upload/senspe.sas, (SAS Macro); 2005. Cha S. Calculate sensitivity and specificity: Mayo Clinic College of Medicine. Online at
   Google Scholar
• Ding EL, Song Y, Cook NR, et al. Methods in validating and determining misclassifications in disease self-reports and estimating bias on relative risks in prospective cohorts. Am J Epidemiol 2007; 165–S148
   Web of Science ®Google Scholar
• Woodward M. Epidemiology: Study Design and Data Analysis. Chapman and Hall /Boca Raton: CRC. 1999
   Google Scholar
• Cameron CA, Roberts CL, Olive EC, et al. Trends in postpartum haemorrhage. Aust N Z J Public Health. 2006; 30: 151–156
   Google Scholar
• Roberts CL, Lain SJ, Hadfield RM. Quality of population health data reporting by mode of delivery. Birth. 2007; 34: 274–275
   Google Scholar
• Riley M, Halliday J. The accuracy of eclampsia cases reported to the Victorian Inpatient Minimum Database and the Perinatal Data Collection Unit. Health Inf Manag. 1998; 28: 13–15
   Google Scholar