scholarly journals Analyzing the changes in certain infectious and parasitic diseases in urban population of India by using medical certification of cause of death data

2021 ◽  
Vol 46 (1) ◽  
pp. 20
Author(s):  
BalKishan Gulati ◽  
Saurabh Sharma ◽  
MV Vardhana Rao
Keyword(s):  
Cause Of Death ◽  
Urban Population ◽  
Parasitic Diseases ◽  
Medical Certification ◽  
Death Data

scholarly journals The impact of errors in medical certification on the accuracy of the underlying cause of death

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0259667
Author(s):  
U. S. H. Gamage ◽  
Tim Adair ◽  
Lene Mikkelsen ◽  
Pasyodun Koralage Buddhika Mahesh ◽  
John Hart ◽  
...  
Keyword(s):  
Cause Of Death ◽  
Death Certificate ◽  
International Classification Of Diseases ◽  
High Impact ◽  
Error Type ◽  
Medical Certification ◽  
Underlying Cause Of Death ◽  
The Impact ◽  
Very High ◽  
Death Data

Background Correct certification of cause of death by physicians (i.e. completing the medical certificate of cause of death or MCCOD) and correct coding according to International Classification of Diseases (ICD) rules are essential to produce quality mortality statistics to inform health policy. Despite clear guidelines, errors in medical certification are common. This study objectively measures the impact of different medical certification errors upon the selection of the underlying cause of death. Methods A sample of 1592 error-free MCCODs were selected from the 2017 United States multiple cause of death data. The ten most common types of errors in completing the MCCOD (according to published studies) were individually simulated on the error-free MCCODs. After each simulation, the MCCODs were coded using Iris automated mortality coding software. Chance-corrected concordance (CCC) was used to measure the impact of certification errors on the underlying cause of death. Weights for each error type and Socio-demographic Index (SDI) group (representing different mortality conditions) were calculated from the CCC and categorised (very high, high, medium and low) to describe their effect on cause of death accuracy. Findings The only very high impact error type was reporting an ill-defined condition as the underlying cause of death. High impact errors were found to be reporting competing causes in Part 1 [of the death certificate] and illegibility, with medium impact errors being reporting underlying cause in Part 2 [of the death certificate], incorrect or absent time intervals and reporting contributory causes in Part 1, and low impact errors comprising multiple causes per line and incorrect sequence. There was only small difference in error importance between SDI groups. Conclusions Reporting an ill-defined condition as the underlying cause of death can seriously affect the coding outcome, while other certification errors were mitigated through the correct application of mortality coding rules. Training of physicians in not reporting ill-defined conditions on the MCCOD and mortality coders in correct coding practices and using Iris should be important components of national strategies to improve cause of death data quality.

Mortality by cause of death in a rural area of Machakos District, Kenya in 1975–78

1990 ◽  
Vol 22 (1) ◽  
pp. 63-75 ◽  
Author(s):  
Omondi-Odhiambo ◽  
J. K. van Ginneken ◽  
A. M. Voorhoeve
Keyword(s):  
Young Adults ◽  
Rural Area ◽  
Cause Of Death ◽  
Respiratory System ◽  
Causes Of Death ◽  
Circulatory System ◽  
Respiratory Illness ◽  
Parasitic Diseases ◽  
Degenerative Diseases ◽  
Death Data

SummaryThis paper examines mortality by cause of death in a rural area of Machakos district in Kenya. The cause-of-death data collected between 1975 and 1978 were likely to be of fairly good quality. The number of deaths was higher among infants and children. Infectious diseases and diseases of the respiratory system were the leading causes of death among children below 5 years of age. Next in prominence were the causes ascribed to congenital anomalies and perinatal conditions.Among adolescents and young adults, injury and poisoning, together with tuberculosis and other infectious and parasitic diseases, were the leading causes of death. Degenerative diseases, especially diseases of the circulatory system and neoplasms and respiratory illness, were responsible for the majority of deaths among the older population.

scholarly journals Effectiveness of training interventions to improve quality of medical certification of cause of death: systematic review and meta-analysis

BMC Medicine ◽  
2020 ◽  
Vol 18 (1) ◽  
Author(s):  
U. S. H. Gamage ◽  
Pasyodun Koralage Buddhika Mahesh ◽  
Jesse Schnall ◽  
Lene Mikkelsen ◽  
John D. Hart ◽  
...  
Keyword(s):  
Cause Of Death ◽  
Meta Analysis ◽  
Sensitivity Analyses ◽  
Narrative Synthesis ◽  
Training Interventions ◽  
Medical Certification ◽  
Effectiveness Of Training ◽  
Meta Analyses ◽  
Death Data

Abstract Background Valid cause of death data are essential for health policy formation. The quality of medical certification of cause of death (MCCOD) by physicians directly affects the utility of cause of death data for public policy and hospital management. Whilst training in correct certification has been provided for physicians and medical students, the impact of training is often unknown. This study was conducted to systematically review and meta-analyse the effectiveness of training interventions to improve the quality of MCCOD. Methods This review was registered in the International Prospective Register of Systematic Reviews (PROSPERO; Registration ID: CRD42020172547) and followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. CENTRAL, Ovid MEDLINE and Ovid EMBASE databases were searched using pre-defined search strategies covering the eligibility criteria. Studies were selected using four screening questions using the Distiller-SR software. Risk of bias assessments were conducted with GRADE recommendations and ROBINS-I criteria for randomised and non-randomised interventions, respectively. Study selection, data extraction and bias assessments were performed independently by two reviewers with a third reviewer to resolve conflicts. Clinical, methodological and statistical heterogeneity assessments were conducted. Meta-analyses were performed with Review Manager 5.4 software using the ‘generic inverse variance method’ with risk difference as the pooled estimate. A ‘summary of findings’ table was prepared using the ‘GRADEproGDT’ online tool. Sensitivity analyses and narrative synthesis of the findings were also performed. Results After de-duplication, 616 articles were identified and 21 subsequently selected for synthesis of findings; four underwent meta-analysis. The meta-analyses indicated that selected training interventions significantly reduced error rates among participants, with pooled risk differences of 15–33%. Robustness was identified with the sensitivity analyses. The findings of the narrative synthesis were similarly suggestive of favourable outcomes for both physicians and medical trainees. Conclusions Training physicians in correct certification improves the accuracy and policy utility of cause of death data. Investment in MCCOD training activities should be considered as a key component of strategies to improve vital registration systems given the potential of such training to substantially improve the quality of cause of death data.

scholarly journals Multiple cause-of-death data among people with AIDS in Italy: a nationwide cross-sectional study

2017 ◽  
Vol 15 (1) ◽  
Author(s):  
Enrico Grande ◽  
Antonella Zucchetto ◽  
Barbara Suligoi ◽  
Francesco Grippo ◽  
Marilena Pappagallo ◽  
...  
Keyword(s):  
Cause Of Death ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Death Data

A haláloki diagnózisok megbízhatóságának javítása a népegészségügyi hatóság és a Központi Statisztikai Hivatal együttműködésével

2016 ◽  
Vol 157 (13) ◽  
pp. 504-511
Author(s):  
Mária Szücs ◽  
Dojna Pintérné Grósz ◽  
János Sándor
Keyword(s):  
Public Health ◽  
Cause Of Death ◽  
Health Authority ◽  
Control Method ◽  
International Classification Of Diseases ◽  
Public Health Authority ◽  
Central Statistical ◽  
Central Statistical Office ◽  
Death Data

Introduction: The diagnosis of cause of death is based on the sequence of diagnoses declared by the physician who completes the death certificate that is processed by Central Statistical Office in Hungary. The validity control of the data requires the active involvement of the public health authority. Aim: The authors analyzed the death certificates from Tolna county in order to elaborate and evaluate methods for cause of death data validity control. Method: Diagnoses of cause of death declared by the physician, corrected by the social statistical review in the Central Statistical Office, and revised by public health authority were compared to evaluate the quality of cause of death data. Results: It was found that 5–10% of the cause of death diagnoses declared by physicians required some modification, resulting more than 1% change in county specific mortality statistics of the main International Classification of Diseases groups. Physicians who reported inaccurate cause of death data were identified. 10 indicators were defined to monitor the process elaborated in the project. Conclusions: Co-operation between the Central Statistical Office and public health authorities to improve the quality of cause of death data should be continued because evaluation of public health interventions needs more and more reliable and detailed cause of death statistics. Orv. Hetil., 2016, 157(13), 504–511.

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