根本死因自动编码工具在死因监测工作中的编码实例分析

目的分析根本死因自动编码工具在对死亡个案进行根本死因编码时正确编码和错误编码的原因,以改进根本死因自动编码工具的性能,提高编码的准确性。方法在全国死因登记报告信息系统中抽取死亡个案,比较根本死因自动编码工具的编码结果与编码专家所编的正确编码的异同。结果根本死因自动编码工具的编码正确率达到84.76%,同时也存在不能正确反映出死因链上各疾病之间的逻辑关系从而不能得出正确根本死因编码的问题。结论居民死亡医学证明书的死因链上各疾病填写顺序是否规范及反映各种疾病之间映射关系的编码策略表完整与否是提高根本死因自动编码工具编码正确率的关键环节。     

死因监测中根本死因填报存在问题及解决途径

目的:分析死因监测中根本死因填报中存在的问题,以及相应的解决途径.方法:选择县疾控中心上报死亡个案600例,对其进行相应的建库、清洗、统计.记录所选案例中根本死因填报的正确率及错误率.针对存在的问题进行培训,培训后,选取另外600例死亡个案,记录其中根本死因填报的正确率及错误率,并与培训前进行对比.结果:在选取的600例死亡个案当中,根本死因填报的正确数为438例(73.00%),错误数为162例(27.00%).培训后,根本死因填报正确数为512例(85.33%),错误数为88(14.67%).结论:在过去的死因监测中,根本死因填报存在一定问题,正确率较低,针对存在的问题,采取有效的解决途径,能够有效提高根本死因填报的正确率.     

死因监测质量评价方法及应用

目的探讨质量评价方法，通过质量评价，提高死因监测质量。方法综合指数法，监测指标为：单位报告率、审核率、报告及时性、报告合格率、审核及时性、审核合格率、各区县站报告死亡病例数占总人群死亡病例数的比例、数据库质量、根本死因填报。结果全市单位报告率为83．62％，审核率为98．42％，全市平均报告合格率为60．78％，平均审核合格率为94．27％，全市报告病例数占总人群病例数为36．64％，缺漏项数占报告病例数1．62％，有死因链根本死因正确率为52．71％，无死因链根本死因正确率为82．22％。结论太原市死因监测工作情况表明，质量评价是行之有效的质量管理方法，它可以揭示各区县死因监测中存在的问题，确定下一步工作重点。目前太原市死因监测工作中，需要采取相应措施降低漏报，加强死亡病例报告、审核的及时性，提高根本死因判定的准确性。     

2010-2013年某医院死因报告质量分析

目的提高死因监测质量，确保死因填报的准确性。方法通过回顾性调查，对某医院2010—2013年死亡医学证明书和网络直报信息中存在的问题进行分析。结果4年间该医院死亡病人966人，总漏报率为2．0％，总迟报率4．9％，死因判断正确率为92．0％，死因编码正确率为88．5％，死因不明占死亡报告总人数的3．1％。2010年填报错误率最高。结论通过加强死亡医学证明书填写环节的质量控制、对相关人员培训、专人负责等一系列措施提高死亡医学证明书的填报质量。     

某市2015年-2017年死因监测数据质量分析

目的对毕节市死因监测数据进行质量分析，为进一步完善毕节市死因监测工作提供参考。方法使用死亡率、最高诊断单位构成、最高诊断依据构成、根本死因编码不准确比例等指标对毕节市2015年-2017年的死因监测情况进行评价。结果2015年-2017年毕节市死因监测点常住人口死亡病例41 594例，死亡率 567.83/10万；2015年-2017年毕节市死因监测点死者生前最高诊断单位为二级医院和三级医院的占比较高，生前最高诊断依据为可靠依据的占比60%左右，根本死因编码不准确比例2.76%。结论毕节市的死因监测数据质量有所提升，但总体上并不乐观，建议通过政府主导、部门合作、专业支撑等方式改善毕节市死因监测现状。     

2006年合肥市死亡病例网络报告信息质量评价

目的分析2006年合肥市医疗机构网络报告死亡信息及质量,为提高报告信息质量提供依据。方法收集2006年网络直报死亡信息,利用死因顺位、死因构成、死亡报告率、报告及时率、根本死因确定和编码错误率等指标进行分析评价。结果网络报告死亡病例占全市居民死亡总数的25.42%,网络死亡报告率93.04%,婴儿死亡报告率93.18%,报告及时率69.00%,网络报告死因根本死因确定或编码错误率12.72%。结论2006年网络报告的报告质量虽好于全国总体水平,但医疗机构根本死因确定和编码培训工作亟待加强。     

2007-2014年湖南省人口死亡信息登记管理系统数据质量分析

目的评价2007-2014年湖南省人口死亡信息登记管理系统数据质量,为提高死因监测质量提供依据。方法利用湖南省人口死亡信息登记管理系统数据库,对死因链填报丰富程度和根本死因编码质量两方面指标进行分析评价。结果2007-2014年一级死因链所占比重最高,为87.05%;多死因链填写率为12.93%,且呈逐年上升趋势;伤害意图不明及伤害未特指的根本死因垃圾编码率均呈缓慢的下降趋势,症状、体征、未知或不可归类在他处者的根本死因垃圾编码率最高,在2007-2009年呈下降趋势;2007-2014年身份证号码填写率逐年上升,但平均填写率较低。结论2007-2014年湖南省死因监测数据质量逐年改善,但仍需进一步提高。     

安徽省国家疾病监测点2013～2017年死因网报数据质量评估

目的评估安徽省国家疾病监测点死因数据报告质量,分析存在的问题。方法采用分层整群随机抽样方法评估安徽省国家死因监测点(DSPs)2013-2017年死因填报质量。结果2013.2017年安徽省DSPs死因网报个案身份证号、死因链、根本死因及其编码填报年均准确率分别为85.83%.64.14%和82.19%,其中前两项指标准确率均见逐年增高趋势(P<0.05),第3项指标准确率比2013年提高2.77%。3项指标准确率在新老点和城乡之间的差异逐年缩小。除根本死因及其编码准确率外,新点填报准确率均优于老点;身份证号准确率城市点较优,死因链准确率农村点较优,而根本死因及其编码准确率无城乡差异。死因链上疾病编码缺失或错误、多死因链填报不准确是死因填报中主要的错误类型。结论2013-2017年安徽省国家疾病监测点死因网报质量不断提升,但仍有进步空间。在强化培训和督导的同时,各级疾控中心要严把审核工作的质量,并定期开展抽审评估工作,及时发现和解决问题。     

2008年～2010年昆明市死因监测网络直报情况分析

[目的]通过分析昆明市2008年～2010年死因监测网络．鲋良中网络报告质量、根本死因填报常见错误等,找出解决办法和途径,从而提高数据信息准确性,为卫生决策提供科学依据。[方法]数据来源于国家死因监测网络直报系统,用Microsoft AccesS整理和统计。[结果]昆明市2008年～2010年报告死亡率分别为502．33／10万、553．64／10万和595．99／10万,逐年接近国家死因监测居民粗死亡率兰600／10万的要求。县级以上医院报告及时性及死亡医学证明书的审核率逐年提高,提示死因网络直报质量逐年提高。死因编码评价指标（如死因诊断不明、伤害意图不明等所占比例）保持在较低比例,编码评价指标符合质量要求。根本死因填写常见错误为：无死因推断,只填写老死、猝死、来院已死或死因不明等;未按照根本死因选择原则来推断根本死因;意外伤害未填写外部原因或外部原因不明确;肿瘤未明确良性和恶性及原发部位;当原发癌和继发癌同时存在时,应选挥源发癌。[结论]重点加强对死因编码规则、死因链填写方法、根本死因填写要求和注意事项的培训和学习,降低死亡漏报率,提高死亡信息上报及时性和降低迟审率。     

大连市《死亡医学证明书》填报质量分析

为了解大连市《死亡医学证明书》（简称《死亡证》）的填报质量，为评估居民健康指标和制定卫生策略提供可靠数据。采用随机抽取不同医疗机构的《死亡证》，按照大连市死因登记管理规范要求，调查《死亡证》填报质量。计抽查2150例，总体质量比较好，错漏项比例〈5．0％，网报录入及时性99．81％，达到合格标准。死因链较合理，编码及根本死因确定准确性较高。     

Die Todesursachenstatistik in Deutschland

The causes of death statistics is widely used as a major source of data for monitoring particular health indicators and their change over time. Results of these comparisons are used for epidemiologic and medical research and as a starting point to give recommendations for prevention programs and for health policy. Nevertheless, the quality of the causes of death statistics is often criticized. Beside the quality of the medical information the critic aims in particular at the restricted comparability of the data and the limitation of the statistics on mono-causal causes of death. The latter aspects refer to steps which are performed within the scope of the data processing in the statistical offices. With the introduction of an automated coding system, which is able to code all causes of deaths on the death certificate and select the underlying cause of death automatically, it will be possible to solve these problems. Furthermore the automated coding system is the prerequisite for a routine multiple-cause coding which is demanded by several medical and statistical experts.     

Epidemiological potential of multiple-cause-of-death data listed on death certificates, Brazil, 2003]

OBJECTIVE: To evaluate the automated processing and the epidemiological potential of multiple-cause-of-death data listed on death certificates in Brazil in 2003. METHODS: Data were obtained from the Brazilian Mortality Information System. The distribution of the number of causes per death certificate was processed using the Multiple Cause of Death Tabulator software and expressed as a percentage of the total deaths in federation units, regions, and in the country as a whole. For the main causes of death identified in Brazil in 2003, we calculated the rate at which each cause was listed as the "underlying cause of death" in relation to the total times the cause was mentioned. RESULTS: The mean number of causes of death per certificate ranged from 2.07 in the state of Maranh?o to 3.15 in the state of S?o Paulo, and from 2.45 in the Northeast to 2.99 in the Mid-West. For the entire country, the mean number of causes of death per certificate was 2.81. External causes and neoplasms, unattended deaths, human immunodeficiency virus, and alcoholic liver disease were listed as the underlying cause more than 90% of the times they were mentioned; neoplasms, Chagas' disease, congenital malformations, ischemic heart diseases, and cerebrovascular diseases, between 70% to less than 90% of the times they were mentioned; and pneumonias, heart failure, alcohol dependence, malnutrition, hypertensive diseases, anemias, ill-defined causes, prematurity, septicemias, and respiratory failure, less than 40% of the times they were mentioned. CONCLUSIONS: Although underlying causes of death are still essential to analyze historical trends, compare countries, and to guide the prevention of death, multiple-cause-of-death-data offer a new insight into the study of mortality. The combination of the two methodologies is more useful than the isolated use of either approach.     

Death certificate coding practices related to diabetes in European countries--the 'EURODIAB Subarea C' Study.

The objective of this study was to compare and analyse coding practices for diabetes mortality data in nine European countries (Belgium, Republic of Ireland, France, Germany, Malta, The Netherlands, Northern Ireland, Scotland and Switzerland). In each country, a sample of 200 coded death certificates, which mentioned diabetes, was randomly sampled. All death certificates were recoded at the WHO Collaborating Centre for the Classification of Diseases in the French language. The results show wide differences between national coding and central coding. Discrepancies in the underlying cause of death existed at the 3-digit coding level for 26% of all death certificates and for 44% at the 4-digit level. Coding in Northern Ireland and Malta was characterized by a marked tendency to choose diabetes less frequently. In contrast, in The Netherlands and, to a lesser extent, in the Republic of Ireland and France, diabetes was more frequently selected as the underlying cause of death. Most of the differences concerned the coding of an association involving diabetes and circulatory system diseases. In some countries, these coding differences influence the reported level of diabetes mortality. For Northern Ireland and Malta, the number of certificates with diabetes as the underlying cause of death was more than doubled after central recoding and for The Netherlands, in contrast, it was almost halved. To explain the differences a number of factors are considered: a lack of information from the International Classification of Diseases (ICD), on the application of the coding rules, between-country differences in cause of death certification practices, a divergence of opinion about the causal role of diabetes when it is associated with other conditions, a lack of homogeneity between countries in data collection procedures.(ABSTRACT TRUNCATED AT 250 WORDS)     

Diabetes mellitus as cause of death

Certification and coding of diabetes mellitus as a cause of death were investigated by sending a random sample of 300 physicians a set of 6 case histories. Of these, 228 (76%) participated in the study by completing a death certificate for each of these cases. The certificates were subsequently coded by the Central Bureau of Statistics. The main finding was that doctors varied enormously in the way in which diabetes mellitus was mentioned on the death certificate: not at all, as a contributory cause of death, or as an underlying cause of death. Coding removes some of the inconsistencies, but induces additional variation: a higher age of the deceased is associated with a lower probability of having diabetes mellitus coded as the underlying cause of death, and a higher probability of not receiving a code of diabetes mellitus at all. It is concluded that the cause-of-death registration does not provide an accurate picture of the contribution of diabetes mellitus to the cause-of-death pattern of the Netherlands. This is due, amongst other things, to the conceptualization of causes of death on which the registration is based. On the other hand, changes in certification and coding practice within the current system may already lead to some improvement.     

1997年我国部分地区多死因填写情况分析

目的 通过专题调查描述我国居民死亡医学证明书中对多死因填写的状况。方法 对我国四个死因点１９９７年１５３１７例死亡的死因实际填写情况进行审核后归纳、汇总并计算有关指标。结果 死亡原因的平均报告情况数为１．７２,有随死亡组年龄增加而上升的趋势。根本死因为循环系病、慢性下呼吸道疾病和糖尿病的平均编码数为１．７０以上,在前１０位死因中,不同程度地伴有其他影响居民健康的疾病。结论 对多数死亡不宜对一种死因     

Mortality from dementia in Norway, 1969-83.

From 1969 to the end of 1983 in Norway, dementia was coded as the underlying cause of death from 2058 death certificates, and as a contributory cause from 19,459. This is 3.56% of the total number of deaths. It seems that a considerable proportion of dementia cases are noted on death certificates in Norway. Death rates based on dementia as the underlying cause of death have increased with time, but when including contributory causes, rates have declined. The data may be useful in epidemiological studies, eg, to search for aetiological clues for Alzheimer's disease. Due to the inclusion of contributory causes of death in the registers and to the high number of dementia cases noted on death certificates, Norwegian mortality data on dementia are probably of better quality than in most other countries.     

Certification of cause of death in French diabetic patients.

STUDY OBJECTIVE--The aim was to assess the level of mortality related to diabetes in France. In other countries, an underrecording of diabetes on the death certificates of diabetic patients has been reported. DESIGN AND SETTING--Estimated death rate of diabetic patients was calculated using (a) the actual number of death certificates where diabetes was registered either as an underlying or as a contributory cause of death, and (b) estimates of the prevalence of diabetes in the population, by sex and age group, from which expected numbers of diabetic deaths were determined. Standardised mortality ratios were calculated using 1988 French mortality statistics as reference. MAIN RESULTS--The estimated standardised mortality ratio for diabetic subjects, with diabetes registered as the underlying cause, was 0.36. This standardised mortality ratio increased to 0.92 if both the underlying and contributory causes were considered. The estimated death rate, by sex and age group, implies that diabetes has a protective effect between the ages of 45 and 64 years, particularly in men. CONCLUSIONS--Evidence suggests that diabetes is completely omitted on the death certificates of many diabetic subjects, especially for those between the ages of 45 and 64 years. Using mortality statistics underestimates the prevalence of diabetes and its effects on public health. The difference in diabetes mortality between countries will not be reliable until there is a better registration of the causes of death in diabetic patients, and contributory as well as the underlying cause are coded and published.     

New dimensions in cause of death statistics.

This article discusses the limitations of traditional national cause of death statistics. These limitations derive from an attempt to conceptualize a multidimensional phenomenon and reduce down to a unidimensional framework. The article outlines the characteristics of a new multidimensional approach which involves the codification and tabulation of all causes (multiple causes) listed on death certificates. Preliminary data are presented which illustrate that multiple cause of death data do indeed represent a major new dimension to cause of death statistics. These data indicate that most major causes of death are contributory factors in many deaths in which they are not the underlying cause of death. For example, in 1976, diabetes mellitus was the underlying cause of approximately 35,000 deaths but was a contributing factor in another 100,000 deaths. This paper also demonstrates the contribution of multiple cause of death data to identifying patterns of association among diseases and the kinds of injuries resulting from various external causes. Finally, data are presented which depict the use of multiple cause data in evaluating the efficacy of the coding rules used to classify the underlying cause of death.     

Automation of mortality data coding and processing in the United States of America

The development in the United States of America of an automated system for coding mortality data (Automated Classification of Medical Entities--ACME) was undertaken with two major objectives in mind: (i) to introduce consistent and rapid assignment of underlying cause-of-death coding with reduced needs for manpower training; and (ii) to allow better utilization of medical information on death certificates for multiple cause-of-death analyses. The ACME system meets both of these objectives; the National Center for Health Statistics (NCHS) produces all of its underlying cause-of-death statistics for the United States on the basis of this system, and multiple cause-of-death data are routinely available for additional epidemiological study beyond the traditional methods of vital statistics analyses. Enhancements of the automated system, primarily through the software known as MICAR, reduce even further the levels of training necessary for persons doing the basic data entry. MICAR additionally will ease transitions between ICD revisions by reducing the need for coder reorientation and by permitting rapid calculation of comparability ratios when new revisions are introduced.