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Bulletin of the World Health Organization logoLink to Bulletin of the World Health Organization
. 2019 Jan 18;97(3):190–199. doi: 10.2471/BLT.18.215327

Changes in reporting for unintentional injury deaths, United States of America

Changements dans l'enregistrement des décès par traumatisme accidentel - États-Unis d'Amérique

Cambios en la manera de reportar muertes por lesiones no intencionales, los Estados Unidos de América

التغيرات في الإبلاغ عن الوفيات الناتجة عن الإصابات غير المتعمدة، الولايات المتحدة الأمريكية

美国意外伤害死亡率报告的变化

Изменения в отчетности о случаях гибели из-за непредумышленных травм, Соединенные Штаты Америки

Peishan Ning a, David C Schwebel b, Haitao Chu c, Motao Zhu d, Guoqing Hu e,
PMCID: PMC6453323  PMID: 30992632

Abstract

Objective

To quantify how changes in reporting of specific causes of death and of selecting underlying cause from among multiple causes of death contribute to trends in mortality from unintentional injury in Americans aged 65 years or older.

Methods

We extracted age-standardized unintentional injury mortality data in the United States Centers for Disease Control and Prevention online databases from 1999 to 2016. We used an attribution method to calculate two indicators: the proportion of mortality with specific codes out of all mortality; and the proportion of mortality with underlying cause of death selected from multiple causes of death. We conducted a linear regression to examine the changes over time in these proportions and in reported and age-adjusted mortality.

Findings

From 1999 through 2016, the proportion of cause-specific unintentional injury mortality in this age group increased from 74% in 1999 (136.9 out of 185.0 per 100 000 population) to 85% in 2016 (143.0 out of 169.1 per 100 000 population) based on multiple causes of death codes. The proportions of mortality with underlying cause of death selected out of multiple causes of death rose in all specific causes of unintentional injury except motor vehicle crash. Age-standardized mortality attributed to reporting changes increased steadily between 1999 and 2016. The increases for overall unintentional injury, fall, motor vehicle crash, suffocation, poisoning and fire or hot object were 24.2, 13.5, 2.1, 2.3, 1.6 and 0.4 deaths per 100 000 persons, respectively.

Conclusion

Changes in data reporting affect trends in overall and specific unintentional injury mortality over time for older Americans.

Introduction

Proper interpretation of reported injury mortality rates and their changes over time are important for assessing the effects of sociodemographic factors on injury risk, developing injury control and prevention efforts, and prioritizing policy interventions. The underlying cause of death is defined as the disease or injury that initiated the train of events leading directly to death, or the circumstances which produced a fatal injury.1 Underlying cause-of-death statistics, from which injury mortality rates are derived, are therefore often used to inform researchers, policy-makers and the public. Most users assume the statistics are valid.

The validity of underlying cause-of-death statistics, however, depends highly on the quality of multiple causes of death listings on death certificates. Two factors important for quality reporting are the correctness and specificity of the data on multiple causes of death and the correct selection of the underlying cause of death from the multiple causes of death.1,2 The correctness and specificity of multiple causes of death is primarily determined by clinical diagnosis and the skill of staff members who are responsible for completing death certificates. This includes both their skill in proper recording of each cause of death and in proper ranking of the sequence of multiple causes of death.1,2 Selection of the underlying cause of death from multiple causes of death is typically made according to the sequence of multiple causes of death on the death certificate, with the first cause in the sequence usually chosen.2

Over the last two decades, several efforts have been made to improve mortality reporting in the United States of America. In 1996, an international collaborative effort on automating mortality statistics was implemented in Washington, DC. The aim was to develop automated coding systems that assist in performing causal death coding, editing, selection of underlying cause of death and classification of multiple causes of death based on standardized decision tables.3 Since that time, automated computer systems such as the Automated Classification of Medical Entities system have been established, refined and expanded.4 The systems were demonstrated to be effective adjuncts to the traditional process of coding and classifying the underlying cause of death.2

Starting in 2001, the National Center for Health Statistics (NCHS) has conducted regular training on automated computer systems for staff members who conduct mortality coding and selection, plus substantial curriculum revision for that training.4 These efforts appear to have improved the accuracy of data reporting of specific causes of death and selecting underlying cause of death from multiple causes of death in the country.38

One specific challenge in coding of injury-related deaths is that data-reporting practices on death certificates vary across age cohorts.9 Elderly individuals have complex patterns of comorbidity, and their death may by delayed following a minor injury. For older people, therefore, coders less commonly attribute the underlying cause of death to the specific cause of the unintentional injury.10 As an example, three recent publications suggest that changes in data reporting in the United States appear to have had a potentially misleading impact on the increase in deaths from unintentional falls among older Americans.1113

Despite the evidence about falls, the impact of recent changes in mortality data reporting has not been systematically examined in the United States. We do not know the extent to which these changes might affect trends in mortality, especially for older Americans. We therefore conducted this study to assess the change in two common data reporting practices: (i) cause specificity, and (ii) selection of underlying cause of death from multiple causes of death. We also aimed to quantify the contributions of these practices to reported unintentional injury mortality for Americans older than 64 years from 1999 to 2016.

Methods

Data source

We used data from the Wide-ranging OnLine Data for Epidemiologic Research databases2 of the United States Centers for Disease Control and Prevention (CDC) web portal. These online databases provide public access to ad hoc queries, summary statistics, maps, charts and data extracts for many health-related data. The databases provide data on the number of deaths, crude death rates, age-standardized death rates and 95% confidence intervals (CI) for death rates based on death certificates for United States residents in the 50 States and the District of Columbia. Each entry for a death contains a single underlying cause of death; up to 20 additional multiple causes of death; and demographic data of the person, including place of residence, age, race, Hispanic or non-Hispanic ethnicity, gender, place of death, time of death and whether an autopsy was performed. Mortality data from the death certificates are either entered by the physician certifying a death, coded by the States and provided to NCHS through the Vital Statistics Cooperative Program; or they are coded by NCHS from copies of the original death certificate provided to NCHS by the State registration offices.2,14 Causes of death are coded according to the International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10).2 The age-standardized mortality rates in the databases are calculated by multiplying the age-specific death rate for each age group (classified by 10-year intervals, except for people aged under 1 year and 85 years and over) by the corresponding weight from the specified standard population (the year 2000 projected population). These are summed across all age groups and the results are multiplied by 100 000.2

We extracted age-standardized mortality rates, and their standard errors, for deaths coded as unintentional injury for Americans aged 65 years and older from 1999 (the earliest data) to 2016. We extracted data for both underlying cause of death and multiple causes of death. Data extraction was completed from January to April 2018. Based on the injury mortality matrix for ICD-10 recommended by the CDC,15 we classified the external causes of unintentional injury as: all unintentional injury; unspecified unintentional injury; and five major causes including fall, motor vehicle crash, suffocation, poisoning and fire or hot object (Box 1).

Box 1. ICD-10 codes used in the study of unintentional injury mortality attributed to changes in data reporting for Americans aged 65 years and older, 1999–2016.

1. All unintentional injury: codes V01–X59, Y85–Y86

2. Unspecified unintentional injury: code X59

3. Fall: codes W00–W19

4. Motor vehicle crash: codes V02–V04, V09.0, V09.2, V12–V14, V19.0–V19.2, V19.4–V19.6, V20–V79, V80.3–V80.5, V81.0–V81.1, V82.0–V82.1, V83–V86, V87.0–V87.8, V88.0–V88.8, V89.0, V89.2

5. Suffocation: codes W75–W84

6. Poisoning: codes X40–X49

7. Fire or hot object: codes X00–X19

ICD-10: International Statistical Classification of Diseases and Related Health Problems 10th revision.

Source: External cause of injury mortality matrix for ICD-10, 2002.15

Attribution model

During the reporting process of an injury-related death, the determination of the underlying cause of death from multiple causes of death can be divided into two consecutive and independent steps.

The first step is the reporting of multiple causes of death. To assess diagnoses, record, classify and sequence multiple causes of death, coders usually rely on external criteria, which are based on autopsy reports, physician review panels and querying of complete medical records (i.e. contacting certifiers for clarification).7,8 When detailed medical documents are lacking, deaths are typically recorded by certifiers as unspecified.2 Following previous studies,58 we obtained the unintentional injury mortality with specified causes recoded among multiple causes of death (MCD) codes and calculated this as the proportion of all-cause unintentional injury mortality (A):

graphic file with name BLT.18.215327-M1.jpg (1)

where y represents mortality, u represents unspecified-unintentional-injury and t all-unintentional-injury. This indictor approximately measures the specificity of injury causes; an increase or decrease in the proportion suggests improvement or deterioration in cause-specific reporting, respectively.5,7

The second step is selecting the underlying cause of death from multiple causes of death. How coders do this is determined by the sequence of conditions on the certificate, the provisions of the ICD-10 and the associated selection rules and modifications.2,16 According to the ICD rules, the sequencing of multiple causes of death determines the choice of the underlying cause of death in most cases.14 Therefore, the process reflects the quality of the sequencing of multiple causes, which depends on the knowledge, skill and diligence of the coders. We obtained the unintentional injury mortality recorded in underlying cause-of-death (UCD) codes and calculated this as a proportion of unintentional injury mortality recorded in multiple causes of death (MCD) codes (B):

graphic file with name BLT.18.215327-M2.jpg (2)

This indictor roughly reflects the quality of sequencing of multiple causes of death; a higher proportion indicates better quality coding.

We then performed two steps to estimate the contribution of changes in data reporting (of cause specificity and selection of underlying cause of death from multiple causes of death) to mortality data coded as unintentional injury. First, we adopted the widely used strategy of age-standardization to calculate adjusted unintentional injury mortality by assuming that data reporting remained unchanged from 1999 to 2016. The adjusted mortality (aM) from the underlying cause of death (UCD) for a specific cause i in a certain year m (mortality UCDi,m) can be calculated as:

graphic file with name BLT.18.215327-M3.jpg (3)

In this equation i means specific injury cause, with i = 1, …, 5, representing five major causes of unintentional injury (fall, motor vehicle crash, suffocation, poisoning and fire or hot object, respectively). m denotes the year, with m = 1999, …, 2016. A1999 denotes the proportion of unintentional injury mortality from multiple causes of death (mortality MCDt) with specific ICD-10 codes out of all-cause unintentional injury mortality from multiple causes of death in 1999. Ci,m represents the proportion of injury mortality recorded as the cause i in injury mortality with specific ICD-10 codes in the year m. This proportion reflects the combined impact of risk factors, injury control efforts and quality of data reporting (typically, misclassification across causes).17,18 Due to a lack of relevant data, we could not separate the effects of data reporting from that of risk factors and injury control efforts, and thus we used the proportion in year m here. Bi,1999 means the proportion of underlying cause of death selected from multiple causes of death for a given specific cause i in 1999.

Second, we calculated the difference between adjusted mortality UCDi,m and reported mortality UCDi,m. The difference reflects the contribution of changes in data reporting to unintentional injury mortality for a specific cause i in year m compared with year 1999.

Statistical analysis

We conducted the analyses in three steps. First, we plotted line graphs to demonstrate changes in the proportion of unintentional injury mortality with (i) specific external causes (i.e. cause specificity) and (ii) proportion of underlying cause of death selected out of multiple causes of death over years. The 95% CI of the two proportions were estimated using normal approximation due to large sample size. Second, we plotted stacked bar charts to show unintentional injury mortality attributed to data reporting changes from 1999 to 2016. Finally, we made a linear regression to examine changes in the proportion of unintentional injury mortality with specific external causes; selection proportion of underlying cause of death from multiple causes of death; reported and adjusted unintentional injury mortality; and unintentional injury mortality by data reporting changes from 1999 to 2016. We calculated the robust standard errors to provide valid inferences even under model misspecification.19 Because differences between robust and classical standard errors of regression coefficients were extremely small (from 0.00001 to 0.01944), we decided to use classical methods to estimate the standard errors of regression coefficients (β). We calculated percentage changes in injury mortality between 1999 and 2016 as:

graphic file with name BLT.18.215327-M4.jpg (4)

We performed all data analyses using Stata, version 12.1 software (Stata Corp., College Station, United States). We considered differences to be statistically significant in two-tailed tests if P-values were less than 0.05.

Ethical statement

This study used anonymous open-access data and did not involve personal information from individuals. Our use of data complied strictly with the terms of the data use restrictions of the CDC online databases. The research proposal was approved by the ethics committee of Xiangya School of Public Health, Changsha, China (no. XYGW-2016–28).

Results

The total population aged 65 years and older was 34 797 841 in 1999 and 49 244 195 in 2016. The age-standardized mortality from all-cause unintentional injuries was 185.0 per 100 000 persons in 1999 and 163.9 per 100 000 in 2016, based on multiple causes of death codes. We found that the proportion of unintentional injury mortality with specific external causes recorded increased significantly from 74% in 1999 (136.9 per 100 000) to 85% in 2016 (143.0 per 100 000; b = 0.0067, P < 0.01; Table 1; Fig. 1). The proportion of underlying cause of death selected from multiple causes of death also rose significantly between 1999 and 2016 from 51% (93.6 per 100 000) to 65% (109.8 per 100 000). Increases in the selection proportion were found for specific causes (fall: 73% versus 81%; suffocation: 18% versus 23%; poisoning: 55% versus 73%; fire or hot object: 91% versus 94%), except for motor vehicle crash (95% versus 95%; Fig. 2).

Table 1. Specificity of injury cause and quality of sequencing of multiple causes of death from unintentional injury among Americans aged 65 years and older, 1999–2016.

Year Population Age-standardized mortality per 100 000 persons
All unintentional injury Unspecified unintentional injury Cause specificity indicator, % Unintentional injury selected as underlying cause Cause selection indicator, %
1999 34 797 841 185.0 48.1 74 93.6 51
2000 34 991 753 177.3 44.5 75 89.2 50
2001 35 290 291 178.6 45.4 75 92.6 52
2002 35 522 207 178.0 42.8 76 94.4 53
2003 35 863 529 177.2 41.3 77 95.0 54
2004 36 203 319 174.4 37.8 78 95.8 55
2005 36 649 798 178.7 36.7 79 98.7 55
2006 37 164 107 172.8 36.1 79 96.8 56
2007 37 825 711 170.8 34.0 80 98.9 58
2008 38 777 621 169.0 32.2 81 99.5 59
2009 39 623 175 161.1 28.0 83 96.9 60
2010 40 267 984 165.0 29.1 82 100.6 61
2011 41 394 141 165.3 28.3 83 102.2 62
2012 43 145 356 163.2 27.1 83 102.6 63
2013 44 704 074 162.2 26.0 84 102.6 63
2014 46 243 211 163.9 26.1 84 105.0 64
2015 47 760 852 169.3 27.2 84 108.9 64
2016 49 244 195 169.1 26.1 85 109.8 65

Notes: We extracted age-standardized mortality data from of the United States Centers for Disease Control and Prevention online databases;2 causes of death are recorded by International Statistical Classification of Diseases and Related Health Problems (10th revision) codes.16 All unintentional injury mortality is the total mortality from all causes recorded in multiple causes of death codes. The cause specificity indicator is the proportion of unintentional injury mortality with specific causes recorded out of all unintentional injury mortality recorded in multiple causes of death codes. The cause selection indicator is the proportion of unintentional injury mortality recorded in underlying cause of death codes selected from unintentional injury mortality recorded in multiple causes of death codes.

Fig. 1.

Proportion of mortality with specific causes recorded out of all unintentional injury in multiple causes of death codes for Americans aged 65 years and older, 1999–2016

Notes: We extracted age-standardized mortality data from of the United States Centers for Disease Control and Prevention online databases;2 causes of death are recorded by International Statistical Classification of Diseases and Related Health Problems (10th revision) codes.16

Fig. 1

Fig. 2.

Proportion of mortality from unintentional injury selected as underlying cause of death among multiple causes of death codes for Americans aged 65 years and older, 1999–2016

Notes: The error bars show 95% confidence interval of the proportion. We extracted age-standardized mortality data from of the United States Centers for Disease Control and Prevention online databases;2 causes of death are recorded by International Statistical Classification of Diseases and Related Health Problems (10th revision) codes.16

Fig. 2

Age-standardized mortality attributed to data reporting changes (namely, improvement in cause specificity and selection of underlying cause of death based on multiple causes of death) rose for overall and specific injury deaths from 1999 to 2016 (P < 0.05). Compared with 1999, data reporting changes contributed 24.2 per 100 000 persons to reported mortality rates based on underlying cause of death in 2016 for all unintentional injuries (Fig. 3). Corresponding figures for the five major causes of injury were 13.5 per 100 000 persons for fall, 2.1 for motor vehicle crash, 2.3 for suffocation, 1.6 for poisoning and 0.4, for fire or hot object due to data reporting changes.

Fig. 3.

Age-standardized mortality by adjusted underlying cause of death mortality and by data reporting change for Americans aged 65 years and older, 1999–2016: all unintentional injury

Notes: We defined adjusted underlying cause of death mortality as mortality from underlying cause of death calculated assuming that data reporting (cause specificity and selection of underlying cause of death from multiple causes of death) remained unchanged from 1999 to 2016. We defined data reporting change as the difference between adjusted underlying cause of death mortality and reported underlying cause of death mortality.

Fig. 3

Trend analysis showed data reporting changes significantly distorted and even reversed trends in overall and cause-specific mortality from underlying cause of death. The percentage change in mortality between 1999 and 2016 greatly differed between reported versus adjusted unintentional injury mortality: 18% versus −10% for overall unintentional injury (Table 2 and Fig. 3). Changes for the five major causes of injury were: 113% versus 63% for fall; −35% versus −44% for motor vehicle crash (Fig. 4); −18% versus −48% for suffocation; 134% versus 64% for poisoning; and −32% versus −42% for fire or hot object (Table 2 and Fig. 5).

Table 2. Percentage change in adjusted and reported mortality for underlying cause of death among Americans aged 65 years and older between 1999 and 2016: overall and cause-specific unintentional injuries.

Variable Age-standardized mortality per 100 000 persons
Reported
Adjusteda
1999 2016 % change (95% CI) 1999 2016 % change (95% CI)
All unintentional injury 93.6 109.8 18 (15 to 21) 93.6 85.6 −10 (−13 to −6)
Selected specific cause
Fall 29.4 61.6 113 (107 to 119) 29.4 48.1 63 (57 to 68)
Motor vehicle crash 22.4 16.3 −35 (−42 to −29) 22.4 14.2 −44 (−52 to −37)
Suffocation 9.9 7.6 −18 (−23 to −14) 9.9 5.3 −48 (−53 to −43)
Poisoning 2.0 4.8 134 (123 to 146) 2.0 3.2 64 (52 to 76)
Fire or hot object 3.6 2.4 −32 (−37 to −26) 3.6 2.0 −42 (−48 to −36)

CI: confidence interval.

a Adjusted mortality from the underlying cause of death was calculated by assuming that data reporting (cause specificity and selection of underlying cause of death from multiple causes of death) remained unchanged from 1999 to 2016.

Notes: We extracted age-standardized mortality data from of the United States Centers for Disease Control and Prevention online databases;2 causes of death are recorded by International Statistical Classification of Diseases and Related Health Problems (10th revision) codes.16 Percentage change in mortality between 1999 and 2016 was calculated as: [regression coefficient × 17 ÷ (mortality in 1999) × 100%]. The total population aged 65+ years in the 50 States and District of Columbia of the United States of America was 34 797 841 in 1999 and 49 244 195 in 2016.

Fig. 4.

Fig. 4

Age-standardized mortality by adjusted underlying cause of death mortality and by data reporting change for Americans aged 65 years and older, 1999–2016: unintentional injury from fall and motor vehicle crash

Fig. 5.

Fig. 5

Age-standardized mortality by adjusted underlying cause of death mortality and by data reporting change for Americans aged 65 years and older, 1999–2016: unintentional injury from suffocation, poisoning and fire or hot object

Discussion

Primary findings

Using the latest mortality data, we assessed two changes in data reporting – cause specificity and selection of underlying cause of death from multiple causes of death – and quantified their impact on unintentional injury mortality reports for Americans aged 65 years and older. The results reveal that a gradual increase in recording specificity of cause of death and an improvement in selecting the underlying cause of death from 1999 to 2016 caused a growing contribution to overall and specific unintentional injury mortality over time. These reporting changes altered published trends in unintentional injury mortality for older Americans, overestimating increases in mortality from overall unintentional injuries, fall and poisoning, and underestimating decreases in mortality from motor vehicle crash, suffocation and fire or hot object to some extent.

Validity of attribution method

The attribution method we propose is based on the built knowledge on roughly measuring cause specificity and selection of underlying cause of death from multiple causes of death through two surrogate indicators (cause specificity and selection of underlying cause of death from multiple causes of death). The two indicators are especially valuable when external and complete information for quality assessment is unavailable or inaccessible.

The proportion of mortality with specific ICD-10 codes out of all mortality approximately reflects the specificity of multiple causes of death, so it measures the quality of codes and sufficiency of information on the death certificates.58 The proportion of underlying cause of death selected from multiple causes of death depends on the sequencing of multiple causes of death in most cases and follows the selection rules of underlying cause of death from the ICD.14 The sequencing of multiple causes of death further relies on the knowledge, skill and diligence of coders. Thus, the selection proportion of underlying cause of death from multiple causes of death approximately reflects data reporting quality;20,21 this strategy has been used previously.22

Interpretation of findings

This study replicates previous findings suggesting that reporting of specific causes of death for unintentional injury among older adults has improved. This change in reporting has had an impact on reported cause-specific unintentional injury mortality in the United States.68 Our study extends those findings in several ways, by visualizing the improvements in selection of underlying cause of death from multiple causes of death. We also describe a strategy to quantify the combined contribution of changes in cause specificity and selection of underlying cause of death from multiple causes of death to the reported mortality from multiple causes of death from 1999 to 2016.

The data reporting improvements we observed are likely to be a result of continuous and enhanced efforts by federal, state and local governments in the United States over the past three decades. These efforts include improved quality of training and practice for coding and selection2326 and the development of automated coding and classification systems using computer procedures that implement standardized selection rules consistent with ICD-10 modifications.3,4,14,16,27 For example, New York city created an eLearning instructional course on cause-of-death reporting in 2008 and mandated this course for users of the electronic death registration system in 2010.3,4 Empirical research demonstrated these changes were successful in teaching medical professionals to report cause of death accurately.23,24

Implications

Our findings have several implications. First, we documented that reporting of unintentional injury mortality among older Americans has gradually improved, yielding significant effects on reported mortality from the underlying cause of death. For this reason, data reporting changes must be considered when using mortality from underlying cause of death to examine the extent of injury mortality and the effectiveness of interventions over time, as well as to develop and evaluate national and local health initiatives such as Healthy People 2020 and 2030.28 In practice, two strategies can be used to address data reporting changes. The first strategy is to completely and routinely assess data reporting quality (including cause specificity, selection of the underlying cause of death from multiple causes of death, and completeness and misclassification). Its impact on reported injury mortality from the underlying cause of death can then be adjusted at federal, state and local levels before releasing data. An alternative strategy is to provide users with warnings that the mortality rates of specific subgroups or certain causes might be heavily affected by changes in data reporting. The first option requires considerable resources, but may be more effective; the second option may be more feasible in many lower-resource environments.

Second, our findings reinforce the vital role that data quality plays in evidence-based research and decision-making. Although our findings were based on American data, the results are relevant globally, as many other countries undergo regular data reporting changes. For example, Australia, France, Italy, the Netherlands and Sweden, and have successively introduced and converted to automated computer systems over the past two decades.4 These transitions have been shown to yield data changes (e.g. in pneumonia deaths in Australia after the introduction of automated computer systems).29 Similarly, a recent analysis of 195 countries reported that 26 countries had improved data consistency between health and non-health data for road traffic mortality from 1985 to 2013, and nine countries had decreased data consistency.30

Last, although the changes in data reporting we report here yield a growing impact on overall and specific unintentional injury mortality, the actual mortality caused by unintentional injury remains high among older Americans. Continued efforts to develop and disseminate effective prevention strategies are needed in addition to efforts to improve data quality.

Study limitations

These findings should be viewed in the light of some limitations of the research. First, although we quantitatively attributed changes in specificity and selection of reporting the underlying cause of unintentional injury deaths from multiple causes of death, such attribution assumes all other factors remain unchanged over the study period. In reality, data reporting changes are likely interacting with other factors that we did not consider. Second, due to lack of detailed data, we could not quantify the contribution of other attributes of data reporting (e.g. completeness of reporting and misclassification across diseases and injuries).31 Further studies are needed to systematically assess recent changes in data reporting and their impact on injury mortality statistics.

Conclusions

Injury mortality data reporting in the United States has changed significantly over 1999–2016 in both the reporting of the specific causes of death and in the selection of underlying cause of death from multiple causes of death. These changes created an apparent contribution to increasing unintentional injury mortality for Americans aged 65 years and older and significantly altered trends in overall and specific unintentional injury mortality. The potential impact of changes in data reporting should be considered by researchers, policy-makers and other stakeholders who interpret and use the data.

Funding:

This study was supported by the Natural Science Foundation of China (No. 81573260).

Competing interests:

None declared.

References

  • 1.Kircher T, Anderson RE. Cause of death. Proper completion of the death certificate. JAMA. 1987. July 17;258(3):349–52. 10.1001/jama.1987.03400030065033 [DOI] [PubMed] [Google Scholar]
  • 2.CDC WONDER online databases [internet]. Atlanta: Centers for Disease Control and Prevention, US Department of Health & Human Services; 2018. Available from: http://wonder.cdc.gov/ [cited 2018 Mar 23].
  • 3.Peters K, editor. Proceedings of the International Collaborative Effort on Automating Mortality Statistics, Volume 1. DHHS Publication No. (PHS) 99-1252. Hyattsville: National Center for Health Statistics, Centers for Disease Control and Prevention, US Department of Health & Human Services; 1999. Available from: https://www.cdc.gov/nchs/data/misc/ice99_1.pdf [cited 2018 Mar 25].
  • 4.Minino AM, Rosenberg Harry M, editors. Proceedings of the International Collaborative Effort on Automating Mortality Statistics, Volume 2. Hyattsville: National Center for Health Statistics, Centers for Disease Control and Prevention, US Department of Health & Human Services; 2001. Available from: https://www.cdc.gov/nchs/data/misc/ice01_acc.pdf [cited 2018 Mar 25].
  • 5.Lu TH, Walker S, Anderson RN, McKenzie K, Bjorkenstam C, Hou WH. Proportion of injury deaths with unspecified external cause codes: a comparison of Australia, Sweden, Taiwan and the US. Inj Prev. 2007. August;13(4):276–81. 10.1136/ip.2006.012930 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Kharrazi RJ, Nash D, Mielenz TJ. Increasing trend of fatal falls in older adults in the United States, 1992 to 2005: coding practice or reporting quality? J Am Geriatr Soc. 2015. September;63(9):1913–7. 10.1111/jgs.13591 [DOI] [PubMed] [Google Scholar]
  • 7.Hu G, Mamady K. Impact of changes in specificity of data recording on cause-specific injury mortality in the United States, 1999–2010. BMC Public Health. 2014. September 27;14(1):1010. 10.1186/1471-2458-14-1010 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Cheng X, Wu Y, Yao J, Schwebel DC, Hu G. Mortality from unspecified unintentional injury among individuals aged 65 years and older by U.S. state, 1999–2013. Int J Environ Res Public Health. 2016. July 27;13(8):763. 10.3390/ijerph13080763 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Dijkhuis H, Zwerling C, Parrish G, Bennett T, Kemper HC. Medical examiner data in injury surveillance: a comparison with death certificates. Am J Epidemiol. 1994. March 15;139(6):637–43. 10.1093/oxfordjournals.aje.a117053 [DOI] [PubMed] [Google Scholar]
  • 10.Baker SP, O’Neill B, Haddon W Jr, Long WB. The injury severity score: a method for describing patients with multiple injuries and evaluating emergency care. J Trauma. 1974. March;14(3):187–96. 10.1097/00005373-197403000-00001 [DOI] [PubMed] [Google Scholar]
  • 11.Hu G, Baker SP. Recent increases in fatal and non-fatal injury among people aged 65 years and over in the USA. Inj Prev. 2010. February;16(1):26–30. 10.1136/ip.2009.023481 [DOI] [PubMed] [Google Scholar]
  • 12.Hu G, Baker SP. An explanation for the recent increase in the fall death rate among older Americans: a subgroup analysis. Public Health Rep. 2012. May-Jun;127(3):275–81. 10.1177/003335491212700307 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Alamgir H, Muazzam S, Nasrullah M. Unintentional falls mortality among elderly in the United States: time for action. Injury. 2012. December;43(12):2065–71. 10.1016/j.injury.2011.12.001 [DOI] [PubMed] [Google Scholar]
  • 14.National Center for Health Statistics instruction manual. Part 2a: instructions for classifying the underlying cause of death. Hyattsville: National Center for Health Statistics, Centers for Disease Control and Prevention, US Department of Health & Human Services; 2008. Available from: http://www.cdc.gov/nchs/data/dvs/2a2008Final.pdf [cited 2018 Apr 5].
  • 15.External cause of injury mortality matrix for ICD-10. Atlanta: Centers for Disease Control and Prevention, US Department of Health & Human Services; 2002. Available from: https://www.cdc.gov/nchs/data/ice/icd10_transcode.pdf [cited 2018 Mar 21].
  • 16.International statistical classification of diseases and related health problems, 10th revision. Volume 2: instruction manual. 5th ed. Geneva: World Health Organization; 2016. Available from: http://apps.who.int/classifications/icd10/browse/Content/statichtml/ICD10Volume2_en_2016.pdf [cited Feb 23 2018].
  • 17.Improving the quality and use of birth, death and cause-of-death information: guidance for a standards-based review of country practices. Geneva: World Health Organization; 2010. Available from: http://apps.who.int/iris/bitstream/handle/10665/44274/9789241547970_eng.pdf;jsessionid=CE20FB8F3E9705CF1F17849A0926D22F?sequence=1 [cited 2018 Mar 24].
  • 18.Lahti RA, Penttilä A. Cause-of-death query in validation of death certification by expert panel; effects on mortality statistics in Finland, 1995. Forensic Sci Int. 2003. January 28;131(2-3):113–24. 10.1016/S0379-0738(02)00418-8 [DOI] [PubMed] [Google Scholar]
  • 19.Huber PJ. Robust statistics. International encyclopedia of statistical science. Berlin: Springer; 2011. [Google Scholar]
  • 20.Lu TH, Hsiao A, Chang PC, Chao YC, Hsu CC, Peng HC, et al. Counting injury deaths: a comparison of two definitions and two countries. Inj Prev. 2015. April;21 e1:e127–32. 10.1136/injuryprev-2013-040974 [DOI] [PubMed] [Google Scholar]
  • 21.Lu TH, Lin JJ. Using multiple-cause-of-death data as a complement of underlying-cause-of-death data in examining mortality differences in psychiatric disorders between countries. Soc Psychiatry Psychiatr Epidemiol. 2010. August;45(8):837–42. 10.1007/s00127-009-0127-0 [DOI] [PubMed] [Google Scholar]
  • 22.Goldberger N, Applbaum Y, Meron J, Haklai Z. High Israeli mortality rates from diabetes and renal failure: can international comparison of multiple causes of death reflect differences in choice of underlying cause? Isr J Health Policy Res. 2015. October 1;4(1):31. 10.1186/s13584-015-0027-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Hemans-Henry C, Greene CM, Koppaka R. Integrating public health–oriented e-learning into graduate medical education. Am J Public Health. 2012. June;102(S3) Suppl 3:S353–6. 10.2105/AJPH.2012.300669 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Madsen A, Begier E. Improving quality of cause-of-death reporting in New York City. Prev Chronic Dis. 2013. July 18;10:130227. 10.5888/pcd10.130227 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Madsen A, Thihalolipavan S, Maduro G, Zimmerman R, Koppaka R, Li W, et al. An intervention to improve cause-of-death reporting in New York City hospitals, 2009-2010. Prev Chronic Dis. 2012;9:120071. 10.5888/pcd9.120071 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Al-Samarrai T, Madsen A, Zimmerman R, Maduro G, Li W, Greene C, et al. Impact of a hospital-level intervention to reduce heart disease overreporting on leading causes of death. Prev Chronic Dis. 2013. May 16;10:120210. 10.5888/pcd10.120210 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Stanfill MH, Williams M, Fenton SH, Jenders RA, Hersh WR. A systematic literature review of automated clinical coding and classification systems. J Am Med Inform Assoc. 2010. Nov-Dec;17(6):646–51. 10.1136/jamia.2009.001024 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Healthy People 2020 [internet]. Washington: Office of Disease Prevention and Health Promotion; 2018. Available from: https://www.healthypeople.gov/ [cited 2018 Apr 7].
  • 29.McKenzie K, Walker S, Tong S. Assessment of the impact of the change from manual to automated coding on mortality statistics in Australia. Health Inf Manag. 2002;30(3):1–11. [PubMed] [Google Scholar]
  • 30.Huang H, Yin Q, Schwebel DC, Ning P, Hu G. Availability and consistency of health and non-health data for road traffic fatality: Analysis of data from 195 countries, 1985–2013. Accid Anal Prev. 2017. November;108:220–6. 10.1016/j.aap.2017.08.033 [DOI] [PubMed] [Google Scholar]
  • 31.Birkhead GS, Klompas M, Shah NR. Uses of electronic health records for public health surveillance to advance public health. Annu Rev Public Health. 2015. March 18;36(1):345–59. 10.1146/annurev-publhealth-031914-122747 [DOI] [PubMed] [Google Scholar]

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