To complete this assignment, locate the locate the article (attached), and provided and 2 page explanation of possible information bias in the study, including the effect that the measurement error may have had on study results and interpretation. Then explain whether or not information bias was effectively minimized in the study. Finally, provide one alternative method for minimizing information bias and explain how the method might minimize error.
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J Epidemiol 2016
doi:10.2188/jea.JE20150010
Original Article
Accuracy of Death Certificates and Assessment of Factors
for Misclassification of Underlying Cause of Death
Makiko Naka Mieno1,*, Noriko Tanaka2,*, Tomio Arai3, Takuya Kawahara4,
Aya Kuchiba5, Shizukiyo Ishikawa6, and Motoji Sawabe7
1
Department of Medical Informatics, Center for Information, Jichi Medical University, Shimotsuke, Tochigi, Japan
Biostatistics Section, Department of Clinical Research and Informatics, Clinical Research Center,
National Center for Global Health and Medicine, Tokyo, Japan
3
Department of Pathology, Tokyo Metropolitan Geriatric Hospital, Tokyo, Japan
4
Department of Biostatistics, School of Public Health, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
5
Department of Biostatistics, National Cancer Center, Tokyo, Japan
6
Center for Community Medicine, Jichi Medical University, Shimotsuke, Tochigi, Japan
7
Section of Molecular Pathology, Graduate School of Health Care Sciences, Tokyo Medical and Dental University, Tokyo, Japan
2
Received January 25, 2015; accepted July 8, 2015; released online December 5, 2015
Copyright © 2015 Makiko Naka Mieno et al. This is an open access article distributed under the terms of Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
ABSTRACT
Background: Cause of death (COD) information taken from death certificates is often inaccurate and incomplete.
However, the accuracy of Underlying CODs (UCODs) recorded on death certificates has not been comprehensively
described when multiple diseases are present.
Methods: A total of 450 consecutive autopsies performed at a geriatric hospital in Japan between February 2000
and August 2002 were studied. We evaluated the concordance rate, sensitivity, and specificity of major UCODs
(cancer, heart disease, and pneumonia) reported on death certificates compared with a reference standard of
pathologist assessment based on autopsy data and clinical records. Logistic regression analysis was performed to
assess the effect of sex, age, comorbidity, and UCODs on misclassification.
Results: The concordance rate was relatively high for cancer (81%) but low for heart disease (55%) and pneumonia
(9%). The overall concordance rate was 48%. Sex and comorbidity did not affect UCOD misclassification rates,
which tended to increase with patient age, although the association with age was also not significant. The strongest
factor for misclassification was UCODs (P < 0.0001). Sensitivity and specificity for cancer were very high (80% and
96%, respectively), but sensitivity for heart disease and pneumonia was 60% and 46%, respectively. Specificity for
each UCOD was more than 85%.
Conclusions: Researchers should be aware of the accuracy of COD data from death certificates used as research
resources, especially for cases of elderly patients with pneumonia.
Key words: accuracy; autopsy; death certificates; outcome misclassification; underlying cause of death
INTRODUCTION
Cause of death (COD) data from death certificates are often
used in epidemiological studies to estimate mortality rates or
risk of death from certain diseases. However, the accuracy
and utility of COD data from death certificates are uncertain
and often questionable.1–5 For cancer mortality statistics in
particular, uncertainty regarding the information on death
certificates has been discussed for more than 100 years. For
example, in early 1900s, Riechelmann reported differences
in the number of cancer cases between autopsy and vital
statistics reports,6 and Wells discussed the degree of this
influence on vital statistics.7 In the late 20th century,
Hoel et al reviewed the effect of death certificate error on
cancer mortality statistics and found a consistent 18%
underestimation of total cancer mortality, with an especially
large influence on the elderly population (75 years or older).8
Since around 2000, site-specific analyses for misclassification
have been investigated. For example, Percy et al reported on
misclassification in colorectal cancer, finding that colon cancer
Address for correspondence. Noriko Tanaka, MHS, PhD, Biostatistics Section, Department of Clinical Research and Informatics, Clinical Science Center, National
Center for Global Health and Medicine, 1-21-1 Toyama, Shinjuku-ku, Tokyo 162-8655, Japan (e-mail: [email protected]).
*These authors contributed equally to this work.
JE20150010-1
2
Accuracy of Death Certificates and Underlying Cause of Death
was over-reported while rectal cancer was underreported on
death certificates.9 Similarly, Yin et al indicated that 82% of
misclassified rectal cancer deaths were coded as colon cancer
deaths.10
For diseases other than cancer, Cheng et al reported death
certificate sensitivity and specificity for diabetes of 34.7%
and 98.1%, respectively. In their 30-year study, they also
reported cardiovascular disease-related diabetes sensitivity
stratified by decade of death and showed a time trend of
improved sensitivity that reflected increased recognition of
cardiovascular disease risk factors.11 In Japan, Saito et al
reported the validity of death certificates for ischemic heart
diseases after the ICD-10 code revision. They compared
death certificates and the diagnosis examined by a review of
the medical records and/or interviews with physicians and
reported that the sensitivity and specificity for ischemic heart
disease certified as the cause of death was 86.5% and 64.7%,
respectively.12 Ravakhah compared death certificate diagnoses
with autopsy report diagnoses in 223 cases and reported
that myocardial infarction was more likely to be unsuspected
in women and those with advanced age.13 Kohn reviewed
autopsy findings in 200 persons older than 85 years, indicating
that the autopsy data were in strong disagreement with the
causes of death listed in the vital statistics and proposing that
‘senescence’ be accepted as a cause of death.14
These studies underscore the difficulty in specifying
underlying COD (UCOD), especially among elderly people,
who tend to have multiple diseases before death. However,
the accuracy of UCODs recorded on the death certificates of
elderly people has not yet been comprehensively examined for
multiple diseases using consecutive autopsy studies. Here, we
evaluated the accuracy of UCODs of elderly people recorded
on death certificates compared to a reference standard of
autopsy findings.
METHODS
Study subjects
Of 532 consecutive autopsies performed at the Tokyo
Metropolitan Geriatric Hospital (Tokyo, Japan) between
February 2000 and August 2002, 450 (84.6%) were included
in the present study. No medico-legal cases were included.
The average autopsy rate during this period was 32%. All
subjects were registered in the geriatric autopsy database
(GEAD) at the Tokyo Metropolitan Geriatric Hospital, which
contains clinical information (presence or absence of 26
geriatric diseases, as follows: ischemic heart disease, atrial
fibrillation, degenerative valvular diseases, hypertension,
aneurysm, arteriosclerosis obliterans, dementia, cerebrovascular disorder, Parkinson’s disease, diabetes mellitus,
hyperlipidemia, malnutrition, osteoporosis, degenerative
osteoarthritis, aspiration, chronic obstructive pulmonary
disease, idiopathic interstitial pneumonia, urinary tract
infection, prostatic hypertrophy, decubital ulcer, lung cancer,
J Epidemiol 2016
gastric cancer, colon cancer, hematopoietic malignancy,
cataract, and glaucoma, as well as clinical dementia ratings
and histories of smoking and alcohol consumption) and
pathological findings (720 items frequently encountered in
autopsy examinations of elderly subjects). Details on the
GEAD have been reported elsewhere.15
COD data
All CODs recorded on death certificates based on clinical and
autopsy records were first evaluated by M.S., a pathologist
and co-author of this study, for reporting consistency and
adherence to instructions for proper completion of the death
certificate. The CODs were subsequently evaluated by T.A.,
also a pathologist and co-author of this study, to confirm
the accuracy of the findings and were entered into the
database using the International Classification of Diseases,
Tenth Revision (ICD-10) codes. UCODs based on death
certificates were defined as the diagnoses listed last in Part I
of death certificates according to guidelines published by the
Ministry of Health, Labour and Welfare in Japan.16 UCODs
based on postmortem examination in conjunction with clinical
information were diagnosed by the same two pathologists,
M.S. and T.A., as the reference standard. UCODs specified for
each subject were coded using Simcode as well as ICD-10.
Simcode is the classification code developed by the Japanese
Ministry of Health, Labour and Welfare to define vital
statistics.17 The overall agreement between UCOD identified
on death certificates and the reference standard was classified
into the following categories: 1. Perfect ICD-10 code
agreement; 2. Disagreement involving the same organ
system; 3. Disagreement, but listed as a COD on death
certificate; and 4. Complete disagreement. We defined these
agreement proportions as the concordance rates, sensitivity
as the proportion of the cases positively identified using
both methods (UCOD identified on death certificate [+]
and UCOD identified using the reference standard [+]) to
the cases positively identified using the reference standard,
and specificity as the proportion of the cases negatively
identified using both methods (UCOD identified on death
certificate [−] and UCOD identified using the reference
standard [−]) to the cases negatively identified using the
reference standard.
Statistical analysis
McNemar’s test was used to evaluate differences between
UCOD proportions estimated based on data solely from the
death certificates and those estimated based on reference
standard data. We also calculated the 95% Wald confidence
intervals (CIs) with Bonett-Price Laplace adjustment for
differences between proportions.18 Multivariate unconditional
logistic regression analyses assessed the effect of age at
death (<80 vs 80–89 and ≥90 years), sex, comorbidity, and
major UCODs identified on death certificates (cancer, heart
disease, pneumonia, and others) on UCOD misclassification.
Mieno MN, et al.
Comorbidity was defined as the number of clinical findings
present among the 26 findings registered in the GEAD. In the
logistic regression model, we had classified the number of
comorbidity into three groups: no or low comorbidity (0–1
finding), moderate comorbidity (2–4 findings), and high
comorbidity (≥5 findings).
Sensitivity and specificity with 95% Clopper-Pearson exact
CIs were calculated for UCODs estimated to be present in at
least 5% of the study population. We used SAS and JMP
software for Windows (versions 9.3 and 10, respectively; SAS
Institute, Cary, NC, USA) for all statistical analyses. Statistical
significance was set at P < 0.05.
Ethical considerations
The Japanese Postmortem Examination and Corpse
Preservation Act generally permits use of autopsy materials
for medical education and research. This study was approved
by the ethics committee of Tokyo Metropolitan Geriatric
Hospital (#240423).
RESULTS
Table 1 shows subject characteristics. The average age at
death was 79.8 years (range, 46–100 years; median, 80 years).
Median number of major clinical findings was 3 (range, 0–8).
UCOD distributions by sex are shown in Table 2. Simcodes
generally conformed to ICD-10 codes, which are also shown
in Table 2. The results indicate that cancer mortality would
be underestimated (the absolute difference between death
certificate information and the reference standard was 5.3% in
women [95% CI, 0.49–10.0%; P = 0.025] and 6.1% in men
[95% CI, 2.2–9.9%; P = 0.0017]), whereas the mortality for
respiratory system diseases, especially pneumonia, would
be overestimated (the absolute difference between death
certificate information and the reference standard was 6.4%
[95% CI, 1.6–11.1%; P = 0.0073] in women and 8.7% [95%
CI, 4.1–13.3%; P = 0.0002] in men).
Of 450 UCODs identified on death certificates, 214 (47.6%)
agreed completely with UCODs identified based on clinical
and post-autopsy reports at ICD-10 three-digit code levels.
When we applied Simcode (broader categories than the
Table 1. Patient characteristics
Sex
Mean (SD) age at death, years
frequency (%)
<70 years
70–79 years
80–89 years
≥90 years
Mean (SD) number of major
clinical findings
frequency (%)
0–1
2–4
≥5
Female (n = 187)
81.9 (8.7)
9
61
75
42
(5%)
(33%)
(40%)
(23%)
Male (n = 263)
78.2 (8.6)
33
118
83
29
(13%)
(45%)
(32%)
(11%)
Total (n = 450)
79.8 (8.8)
42
179
158
71
(9%)
(40%)
(35%)
(16%)
3.1 (1.7)
3.1 (1.6)
3.1 (1.7)
34 (18%)
117 (63%)
36 (19%)
50 (19%)
164 (62%)
49 (19%)
84 (19%)
281 (62%)
85 (19%)
3
ICD-10 code categories shown in Table 2) to UCODs, the
concordance rate increased to 59.3% and was further
improved to 69.6% when major Simcodes (largest CODs
category, indicated by boldface in Table 2, used for rough
national mortality statistics) were used (Figure). Of 236
instances of UCOD disagreement, 83 (35.2%) cases were
assigned to the same organ system, 38 (16.1%) were assigned
as CODs but not UCODs on the death certificates, and 115
(48.7%) disagreed completely.
We also explored how concordance rates varied depending
on UCODs. The concordance rate for cancer was 80.8% at
the ICD-10 code level and increased to 93.6% at the major
Simcode level. The concordance rate at the ICD-10 code level
for heart disease was not high (54.7%); however, it improved
to 83.0% at the major Simcode level. Among major UCODs,
pneumonia, which is the third leading COD in Japan in
2012,19 had the lowest concordance rate (8.8% at the ICD-10
code level) (Figure).
We next examined the effects of sex, age, comorbidity,
and UCODs on misclassification of UCODs identified on
death certificates (Table 3). We found that sex, comorbidity,
and age did not affect the UCOD misclassification rate
(P = 0.53, P = 0.75, and P = 0.13, respectively), although the
misclassification rate showed an increasing trend, especially
for cases >90 years old (adjusted odds ratio [vs <80 years
old] 1.44; 95% CI, 0.72–2.88). The strongest factor for
misclassification was UCODs (P < 0.0001); the results also
show that cancer and heart disease were less often
misclassified than other minor UCODs (adjusted odds ratio
0.10; 95% CI, 0.06–0.16 and adjusted odds ratio 0.34;
95% CI, 0.18–0.65, respectively), whereas pneumonia was
significantly misclassified compared to other minor UCODs
(adjusted odds ratio 4.44; 95% CI, 1.66–11.8) (Table 3).
On exploring the factors influencing accuracy of sensitivity
and specificity for each disease, we found that age (>90 years)
had a profound influence on specificity for pneumonia (odds
ratio 3.23; 95% CI, 1.50–6.69; P = 0.0016), although the
sample size was relatively small for such disease-specific
analyses.
Finally, we evaluated the sensitivity and specificity of
UCODs estimated to be present in at least 5% of the
population (Table 4). Statistics were calculated for each
UCOD identified on death certificates compared with the
reference standard of assessment by two pathologists based on
autopsy data and past clinical records. Overall, specificity for
each UCOD was at least 85%. Sensitivity for any cancer was
high (80%), although values varied according to organ.
Sensitivity for heart disease was 60%, and sensitivity for
pneumonia was very low (46%). Results also suggested that
diseases of the digestive system were difficult to specify as
UCOD (sensitivity, 51.9%). Among 13 deaths attributable to
digestive diseases, 5 (38%) were reported as deaths due to
unknown causes, 3 (23%) as deaths due to infectious diseases,
and 3 (23%) as deaths due to heart disease.
J Epidemiol 2016
4
Accuracy of Death Certificates and Underlying Cause of Death
Table 2. Patients proportion of UCOD measured by death certificates only or by clinical and autopsy reports
Females (n = 187)
Disease category
ICD-10 codes
UCOD on
the death
certificates
Certain infectious and parasitic diseases
Malignant neoplasms
Malignant neoplasms of lip, oral cavity, and pharynx
Malignant neoplasm of esophagus
Malignant neoplasm of stomach
Malignant neoplasm of colon
Malignant neoplasm of rectum and rectosigmoid junction
Malignant neoplasm of liver and intrahepatic bile ducts
Malignant neoplasm of gallbladder and unspecified parts
of biliary tract
Malignant neoplasm of pancreas
Malignant neoplasm of trachea, bronchus, and lung
Malignant neoplasm of cervix uteri, corpus uteri, and uterus
Malignant neoplasm of prostate
Malignant neoplasm of bladder
Malignant lymphoma
Leukemia
Other malignant neoplasms
Non-malignant neoplasms
Diseases of the blood and blood-forming organs and
certain disorders involving the immune mechanism
Endocrine, nutritional, and metabolic diseases
Diabetes mellitus
Other endocrine, nutritional, and metabolic diseases
Mental and behavioral disorders
Diseases of the nervous system
Diseases of the circulatory system
Hypertensive diseases
Heart disease
A00–B99
C00–C97
C00–C14
C15
C16
C18
C19–C20
C22
C23–C24
6
62
0
0
1
4
1
2
5
C25
C33–C34
C53–C55
C61
C67
C81–C85
C91–C95
Others in C00–C97
D00–D48
D50–D89
4 (2.1%)
14 (7.5%)
1 (0.5%)
—
3 (1.6%)
11 (5.9%)
10 (5.3%)
6 (3.2%)
6 (3.2%)
1 (0.5%)
E00–E90
E10–E14
Others in E00–E90
F00–F99
G00–G99
I00–I99
I10–I15
I01–I02, I05–I09,
I20–I25, I27, I30–I52
I60–I69
I71
Others in I00–I99
1
1
0
0
5
46
1
26
J00–J99
J12–J18
J41–J44
Others in J00–J99
K00–K93
L00–L99
M00–M99
29
20
2
7
16
0
1
Cerebrovascular diseases
Aortic aneurysm and dissection
Diseases of the circulatory system other than aortic
aneurysm and dissection
Diseases of the respiratory system
Pneumonia
Chronic obstructive pulmonary disease
Other diseases of the respiratory system
Diseases of the digestive system
Diseases of the skin and subcutaneous tissue
Diseases of the musculoskeletal system and connective
tissue
Diseases of the genitourinary system
Other cause of death
N00–N99
Others
(3.2%)
(33.2%)
(0.0%)
(0.0%)
(0.5%)
(2.1%)
(0.5%)
(1.1%)
(2.7%)
(0.5%)
(0.5%)
(0.0%)
(0.0%)
(2.7%)
(24.6%)
(0.5%)
(13.9%)
9 (4.8%)
5 (2.7%)
5 (2.7%)
(16.5%)
(10.7%)
(1.1%)
(3.7%)
(8.6%)
(0.0%)
(0.5%)
7 (3.7%)
7 (3.7%)
UCOD based on
clinical and
autopsy-derived
information
Males (n = 263)
absolute
differencea
UCOD on
the death
certificates
UCOD based on
clinical and
autopsy-derived
information
absolute
differencea
−1.1%
5.3%
0.0%
0.0%
0.6%
0.0%
0.0%
1.6%
1.6%
10
94
0
1
14
2
2
4
3
3 (1.6%)
13 (7.0%)
1 (0.5%)
—
1 (0.5%)
13 (7.0%)
16 (8.6%)
5 (2.7%)
1 (0.5%)
2 (1.1%)
−0.5%
−0.5%
0.0%
—
−1.1%
1.1%
3.3%
−0.5%
−2.7%
0.6%
4 (1.5%)
26 (9.9%)
—
1 (0.4%)
1 (0.4%)
8 (3.0%)
23 (8.7%)
5 (1.9%)
3 (1.1%)
3 (1.1%)
5 (1.9%)
31 (11.8%)
—
0 (0.0%)
1 (0.4%)
11 (4.2%)
24 (9.1%)
5 (1.9%)
5 (1.9%)
3 (1.1%)
0.4%
1.9%
—
−0.4%
0.0%
1.2%
0.40%
0.0%
0.8%
0.0%
6
2
4
1
6
52
0
34
2.7%
0.6%
2.1%
0.5%
0.5%
3.2%
−0.5%
4.3%
5
2
3
0
4
41
2
27
5
3
2
0
7
45
0
33
0.0%
0.3%
−0.3%
0.0%
1.2%
1.5%
−0.8%
2.2%
4
72
0
0
2
4
1
5
8
(2.1%)
(38.5%)
(0.0%)
(0.0%)
(1.1%)
(2.1%)
(0.5%)
(2.7%)
(4.3%)
(3.2%)
(1.1%)
(2.1%)
(0.5%)
(3.2%)
(27.8%)
(0.0%)
(18.2%)
6 (3.2%)
6 (3.2%)
6 (3.2%)
−1.6%
0.5%
0.5%
(3.8%)
(35.7%)
(0.0%)
(0.4%)
(5.3%)
(0.8%)
(0.8%)
(1.5%)
(1.1%)
(1.9%)
(0.8%)
(1.1%)
(0.0%)
(1.5%)
(15.6%)
(0.8%)
(10.3%)
4 (1.5%)
4 (1.5%)
4 (1.5%)
(9.1%)
(4.3%)
(0.0%)
(4.8%)
(7.5%)
(0.5%)
(2.7%)
−7.4%
−6.4%
−1.1%
1.1%
−1.1%
0.5%
2.2%
70
37
11
22
15
1
1
5 (2.7%)
1 (0.5%)
−1.0%
−3.2 …
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