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RESEARCH AND PRACTICE |
Karin Galil, Jane Seward, Pamela A. Meyer, Andrew L. Baughman, and Melinda Wharton are with the Centers for Disease Control and Prevention, Atlanta, Ga. At the time of this study, Mark J. Pletcher was with the Association of Schools of Public Health, Atlanta, Ga. Barbara J. Wallace is with the New York State Department of Health, Albany.
Correspondence: Requests for reprints should be sent to Karin Galil, MD, MPH, CDC Mail Stop E-61, 1600 Clifton Rd, Atlanta, GA 30333 (e-mail: kgalil{at}cdc.gov).
| INTRODUCTION |
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| METHODS |
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The positive predictive value (PPV) of a varicella code in a data source was defined as the proportion of deaths identified by the data source that were classified as varicella after medical record review. The PPV in each database search was calculated 3 ways: (1) by excluding unclassifiable VZV deaths; (2) by assuming that unclassifiable VZV deaths were from herpes zoster; and (3) by assuming that unclassifiable VZV deaths were from varicella. The PPV was calculated separately for persons aged younger than 50 years and those aged 50 years and older, because varicella is rare in older adults. Exact binomial confidence limits were calculated for each PPV.9 Capturerecapture analysis10 was used to estimate the total number of varicella deaths during the study period. Confidence intervals were calculated by the goodness-of-fit method.11 The completeness of each data source was calculated as the number of verified deaths identified by each database as a proportion of the estimated total number of varicella deaths by capturerecapture analysis. We used the Fisher exact test12 to compare PPV estimates and the McNemar test12 to compare the completeness estimates.
| RESULTS |
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PPV of a Varicella Code
The PPV of a varicella code was greater on a death certificate than in SPARCS and was higher in persons aged younger than 50 years than in those aged 50 years and older (Table 2
). The PPVs were not substantially altered under our three assumptions, namely that they could not be classified and were excluded, that they were all assumed to be due to varicella, and that they were all assumed to be due to herpes zoster.
CaptureRecapture Analysis
Of the 30 varicella deaths, 9 (30%) were identified exclusively from a search of death certificates, 4 (13%) exclusively from SPARCS, and 17 (57%) from both sources. Excluding deaths without medical records, the capturerecapture analysis yielded an estimate of 32 (95% confidence interval [CI] = 30, 38) varicella deaths. The search was 81% complete (26 of 32) for the death certificates and 66% complete (21 of 32) for the SPARCS hospital discharge data (P = .27).
| DISCUSSION |
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Study limitations include the difficulty in distinguishing varicella and disseminated herpes zoster, the small number of persons in the study (particularly persons aged 50 years and older), and a possible underestimation of total varicella deaths through capturerecapture analysis. Because the same physician may have coded the discharge diagnoses and completed the death certificate, the assumption of 2 independent data sources for capturerecapture analysis may have been violated.10 Medical records were unavailable for 10 deaths (16%). Assuming that these deaths were similar to those we reviewed, the total number of varicella deaths estimated by capturerecapture analysis might have been as high as 42, with correspondingly lower estimates of completeness.
This study suggests that death certificates are useful for monitoring varicella deaths for persons aged younger than 50 years. Hospital discharge records were neither more accurate nor more complete than death certificates and may be more difficult to search. In states with automated hospital discharge databases, it may be preferable to search both sources of information to derive a better estimate of the number of varicella deaths.
| Footnotes |
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Human Participant Protection
No human subjects participated in this study.
Accepted for publication July 5, 2001.
| References |
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2. Meyer PA, Seward JF, Jumaan AO, Wharton M. Varicella mortality: trends before vaccine licensure in the United States, 19701994. J Infect Dis. 2000;182:383390.[Medline]
3. Seward JF, Watson BM, Peterson CL, et al. Varicella disease after introduction of varicella vaccine in the United States, 19952000. JAMA. 2002;287:606611.
4. Halloran ME. Epidemiologic effects of varicella vaccination. Infect Dis Clin North Am. 1996;10:631655.[Medline]
5. Amler RW. The health impact of varicella. In: 17th Immunization Conference Proceedings (Atlanta). Atlanta, Ga: Centers for Disease Control; 1982:137138.
6. Preblud SR. Age-specific risks of varicella complications. Pediatrics. 1981;68:1417.
7. Centers for Disease Control and Prevention. Evaluation of varicella reporting to the National Notifiable Disease Surveillance SystemUnited States, 19721997. MMWR Morb Mortal Wkly Rep. 1999;48:5558.[Medline]
8. Council of State and Territorial Epidemiologists. Inclusion of Varicella-Related Deaths in the National Public Health Surveillance System. Atlanta, Ga: Council of State and Territorial Epidemiologists; 1998. Position statement ID-10.
9. Rosner B. Fundamentals of Biostatistics. 3rd ed. Boston, Mass: PWS-KENT Publishing Co; 1990:170173.
10. Hook EB, Regal RR. Capturerecapture methods in epidemiology: methods and limitations. Epidemiol Rev. 1995;17:243264.
11. Regal RR, Hook EB. Goodness-of-fit based confidence intervals for estimates of the size of a closed population. Stat Med. 1984;3:287291.[Medline]
12. Fleiss JL. Statistical Methods for Rates and Proportions. 2nd ed. New York, NY: John Wiley & Sons; 1981.
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