Problems of using the International Statistical Classification of Diseases (ICD-10) in coding morbidity and mortality

Berseneva E.A.; Agamov Z.Kh.; Mikhailov D.Yu.

doi:https://doi.org/10.17116/profmed202124041132

Berseneva E.A.

Federal State Budgetary Institution «Natsional’nyj institut kachestva»;
Russian Presidential Academy of National Economy and Public Administration

ORCID: 0000-0003-3481-6190

Agamov Z.Kh.

N.A. Semashko National Research Institute of Public Health

ORCID: 0000-0002-3745-4888

Mikhailov D.Yu.

N.A. Semashko National Research Institute of Public Health

Problems of using the International Statistical Classification of Diseases (ICD-10) in coding morbidity and mortality

Authors:

Berseneva E.A., Agamov Z.Kh., Mikhailov D.Yu.

More about the authors

Journal: Russian Journal of Preventive Medicine. 2021;24(4): 132‑137

DOI: 10.17116/profmed202124041132

Read: 1887 times

Download PDF (RU)

Contact the author

Table of contents

To cite this article:

Berseneva EA, Agamov ZKh, Mikhailov DYu. Problems of using the International Statistical Classification of Diseases (ICD-10) in coding morbidity and mortality. Russian Journal of Preventive Medicine. 2021;24(4):132‑137. (In Russ.)
https://doi.org/10.17116/profmed202124041132

Подписка 2026 Профилактическая медицина (Russian Journal of Preventive Medicine)

Использование инфографики авторами научных работ

Close metadata

Recommended articles:

Morphofunctional and biochemical determinants of endothelial function in patients with a new coronavirus infection COVID-19. Russian Journal of Preventive Medicine. 2024;(10):90-96

Long-term outcomes in patients after hospital treatment for COVID-19 (three-year follow-up data). Russian Journal of Preventive Medicine. 2024;(12):114-121

Heart failure with preserved ejection fraction: morphofunctional state of the heart throughout 2 years after COVID-19 pneumonia. Russian Cardiology Bulletin. 2024;(3):53-61

ALDH1, CD133, CD34-positive cancer stem cells in lung adenocarcinoma in patients who had a new coronavirus infection and retained the persistence of viral proteins in the lung tissue. Russian Journal of Archive of Pathology. 2024;(5):5-14

Factors affecting the quality of life of patients with neurological manifestations of post-COVID syndrome. S.S. Korsakov Journal of Neurology and Psychiatry. 2024;(9):44-50

«Cytokine storm» as an immunopathologic reaction in pregnant women in the first trimester. Russian Bulletin of Obstetrician-Gynecologist. 2024;(5):19-24

Incidence of sudden cardiac death among diseases of the circulatory system during the COVID-19 pandemic in the Penza region. Forensic Medical Expertise. 2024;(5):10-14

Localization features of FAP-positive activated stromal cells in fibrosis in patients with new coronavirus infection COVID-19. Russian Journal of Archive of Pathology. 2024;(6):5-14

The role of drug Cytoflavin in the correction of dysautonomia in patients with post-COVID syndrome. S.S. Korsakov Journal of Neurology and Psychiatry. 2024;(11):140-146

Laparoscopic appendectomy for appendiceal mucocele in a patient with COVID-19. Endoscopic Surgery. 2024;(6):41-45

Abstract:

One of the important and actual problems of Russian health care is the low quality of statistical data obtained when using the International Statistical Classification of Diseases and Related Health Problems (ICD-10) when coding morbidity and mortality. A review of publications revealed that problems in the preparation of medical documentation associated with the registration of causes of death and diseases are caused by a large number of organizational, methodological, administrative, and economic factors. The main way to increase the reliability of statistical data along with increasing the level of competence of medical workers in the correct use of ICD-10 is the introduction of automated systems with a decision support function.

Keywords:

ICD-10

coding

morbidity statistics

mortality statistics

COVID-19

decision support system

Authors:

Berseneva E.A.

Federal State Budgetary Institution «Natsional’nyj institut kachestva»;
Russian Presidential Academy of National Economy and Public Administration

ORCID: 0000-0003-3481-6190

Agamov Z.Kh.

N.A. Semashko National Research Institute of Public Health

ORCID: 0000-0002-3745-4888

Mikhailov D.Yu.

N.A. Semashko National Research Institute of Public Health

Received:

22.11.2020

Accepted:

07.12.2020

Close metadata

References:

Weissman DS. System of analysis of mortality statistics according to «Medical certificates of death» and reliability of registration of causes of death. Social aspects of public health. 2013;2:1-15. (In Russ.).
Chen D, Zhang R, Zhao H, Feng J. Bibliometric Analysis of the Development of ICD-11 in Medical Informatics. J Healthc Eng. 2019;2019:1649363. https://doi.org/10.1155/2019/1649363
Shi X, Liu H, Zhan S, Wang Z, Wang L, Dong C, Wang Y, Yao C, Ding J, Li Y. Rare diseases in China: analysis of 2014-2015 hospitalization summary reports for 281 rare diseases from 96 tertiary hospitals. Orphanet J Rare Dis. 2019;14(1):160. https://doi.org/10.1186/s13023-019-1137-y
Kakorina EP, Maksimova MV, Mishnev OD, Ovcharov VK, Pogorelova EI. Sekrieru EM. Use of the International statistical classification of diseases and health-related problems, tenth revision (ICD-10) in the practice of domestic medicine. Moscow: NII im. N.A. Semashko RAMN; 2002. Accessed February 12, 2021. (In Russ.). https://webmed.irkutsk.ru/doc/pdf/mkb1.pdf
Jones LK, Pulk R, Gionfriddo MR, Evans MA, Parry D. Utilizing big data to provide better health at lower cost. Am J Health Syst Pharm. 2018;75(7):427-435. https://doi.org/10.2146/ajhp170350
Bouzillé G, Poirier C, Campillo-Gimenez B, Aubert ML, Chabot M, Chazard E, Lavenu A, Cuggia M. Leveraging hospital big data to monitor flu epidemics. Comput Methods Programs Biomed. 2018;154:153-160. https://doi.org/10.1016/j.cmpb.2017.11.012
Cheng SW, Wang CY, Chen JH, Ko Y. Healthcare costs and utilization of diabetes-related complications in Taiwan: A claims database analysis. Medicine (Baltimore). 2018;97(31):e11602. https://doi.org/10.1097/MD.0000000000011602
Chiu ATG, Chung CCY, Wong WHS, Lee SL, Chung BHY. Healthcare burden of rare diseases in Hong Kong — adopting ORPHAcodes in ICD-10 based healthcare administrative datasets. Orphanet J Rare Dis. 2018;13(1):147. https://doi.org/10.1186/s13023-018-0892-5
Yumaguzin VV, Vinnik MV. Problems of statistical accounting of mortality from external causes in Russia. Problems of social hygiene, health care and the history of medicine. 2017;25(5):265-268. Accessed February 12, 2021. (In Russ.). https://cyberleninka.ru/article/n/problemy-statisticheskogo-uchyota-smertnosti-ot-vneshnih-prichin-v-rossii
Barbarash OL, Bojcov SA, Vajsman DSh, Galyavich AS, Drapkina OM, Zabozlaev FG, Zajrat’yanc OV, Kakorina EP, Kakturskij LV, Klevno VA, Nikulina NN, Samorodskaya IV, Cherkasov SN, Ehfros LA, Yakushin SS. Position Statement on Challenges in Assessing Cause-Specific Mortality. Complex Issues of Cardiovascular Diseases. 2018;7(2):6-9. (In Russ.). https://doi.org/10.17802/2306-1278-2018-7-2-6-9
Papanova EK, Shkolnikov VM, Andreev EM, Timonin SA. High life expectancy of muscovites at old ages: reality or statistical artifact? Uspekhi gerontologii. 2017;30(6):826-835. Accessed February 12, 2021. (In Russ.). https://www.gersociety.ru/netcat_files/userfiles/10/AG_2017-30-06.pdf
Lopakov KV. Evaluation of confidence for coded causes of death: a pilot study. Social aspects of public health. 2011;2:1-12. Accessed February 12, 2021. (In Russ.). https://vestnik.mednet.ru/content/view/292/30/lang,ru/
Samorodskaya II, Vatolina MA, Belov VB, Boitsov SA. Estimation of the death rate from mental diseases and diseases of the circulatory system: problems of coding and statistical accounting of deaths. Problems of social hygiene, health care and the history of medicine. 2014;5:8-12. Accessed February 12, 2021. (In Russ.). https://cyberleninka.ru/article/n/otsenka-urovnya-smertnosti-ot-psihicheskih-zabolevaniy-i-bolezney-sistemy-krovoobrascheniya-problemy-kodirovaniya-i-statisticheskogo
Sabgayda TP, Semyonova VG, Ivanova AE, Evdokushkina GN, Sekrieru EM, Nikitina SYu. Completeness of accounting in medical certificates of death of conditions that led to death. Healthcare of the Russian Federation. 2014;5:4-7. Accessed February 12, 2021. (In Russ.). https://elibrary.ru/item.asp?id=21943807
Ivanov VK, Kochergina EV, Zelenskaya NS, Maksyutov MA, Tumanov KA, Shchukina NV, Chekin SYu. Methods for analyzing the quality of primary medical information on cerebrovascular diseases for a cohort of Russian liquidators. Radiatsiya i risk (Byulleten’ NRER). 2015;2:77-84. Accessed February 12, 2021. (In Russ.). https://cyberleninka.ru/article/n/metody-analiza-kachestva-pervichnoy-meditsinskoy-informatsii-po-tserebrovaskulyarnym-boleznyam-dlya-kogorty-rossiyskih-likvidatorov
Weissman DSh. On the influence of coding some diseases from the class «Diseases of the circulatory system» on the statistics of morbidity and mortality. Vrach i informatsionnye tekhnologii. 2013;4:50-55. Accessed February 12, 2021. (In Russ.). https://www.elibrary.ru/download/elibrary_20276403_18332803.pdf
Krivonos OV. Parkinson’s Disease: reliability of statistical indicators of morbidity and mortality in the Russian Federation. Saratovskii nauchno-meditsinskii zhurnal. 2013;4:863-866. Accessed February 12, 2021. (In Russ.). https://www.elibrary.ru/download/elibrary_21527878_54768960.pdf
Berseneva EA, Sedov AA. Lexical analysis automated system: main methods and approaches. The Bulletin of Contemporary Clinical Medicine. 2017; 10(2):7-12. (In Russ.). https://doi.org/10.20969/vskm.2017.10(2).7-12
Guidelines for coding and selecting the underlying condition in morbidity statistics and the initial cause in mortality statistics related to COVID-19. Approved by the Ministry of health of the Russian Federation on May 27, 2020. Accessed February 12, 2021. (In Russ.). https://www.garant.ru/products/ipo/prime/doc/74083741/
Neznanov AA, Starichkova YuV. Development of classification of clinical diagnoses in medical information systems. Biznes-informatika. 2015;2(32):39-46. Accessed February 12, 2021. (In Russ.). https://www.hse.ru/data/2015/06/16/1084146088/4.pdf
Weissman DS. Improving the system of information support for assessing and analyzing population mortality at the level of the subject of the Russian Federation. Abstract of the doctoral dissertation. M. 2015. Accessed February 12, 2021. (In Russ.). mednet.ru/images/stories/files/abstracts/Autoreferat_Vajsman.pdf
Schiff AA, Lushnov MS, Soldatenkova ZhM, Berezin AI. Scientific substantiation of automation of data collection and processing on death rates in Saint Petersburg. Vestnik NovGU. 2010;59:24-28. Accessed February 12, 2021. (In Russ.). https://www.elibrary.ru/download/elibrary_15220519_53831002.pdf
Yumaguzin VV, Vinnik MV. Problems of quality of mortality statistics in Russia. EKO. 2019;10:54-77. (In Russ.).
Weissman DSh. Analysis of the impact of training doctors and the implementation of an automated system on the reliability of mortality statistics. Byulleten’ Nacional’nogo nauchno-issledovatel’skogo instituta obshhestvennogo zdorov’ya im. N.A. Semashko. 2015;6:22-31. Accessed February 12, 2021. (In Russ.). https://cyberleninka.ru/article/n/analiz-vliyaniya-obucheniya-vrachey-i-vnedreniya-avtomatizirovannoy-sistemy-na-dostovernost-statistiki-smertnosti
Automated AI approaches to clinical coding «A Case Study». Growing Data; 2020. Accessed February 12, 2021. https://growingdata.com.au/automated-ai-approaches-to-clinical-coding-a-case-study/
Sychugov GV, Divisenko AS, Shiman IN. Analysis of the incorrect formulation of the final clinical diagnosis. Vestnik Severo-Zapadnogo gosudarstvennogo medicinskogo universiteta im. I.I. Mechnikova. 2016;8(1):117-122. Accessed February 12, 2021. (In Russ.). https://cyberleninka.ru/article/n/analiz-nepravilnoy-formulirovki-zaklyuchitelnogo-klinicheskogo-diagnoza/viewer
Popova NM, Kir’janov NA, Semenovyh EA, Andreeva AM, Pljuhin SV. Uluchshenie kachestva okazanija medicinskoj pomoshhi: rol’ patologoanatomicheskoj sluzhby. Nauchnyj medicinskij zhurnal «Avicenna». 2017;14:38-40. Accessed February 12, 2021. (In Russ.). https://www.elibrary.ru/item.asp?id=32378857
Chechenin GI, Reich AV, Dubrovin AA, Zhilina NM. Information support for decision-making by a doctor to improve the quality of medical care. ORGZDRAV: Novosti. Mneniya. Obuchenie. Vestnik VShOUZ. 2015;2(2):151. Accessed February 12, 2021. (In Russ.). https://cyberleninka.ru/article/n/informatsionnaya-podderzhka-prinyatiya-resheniy-vrachom-dlya-povysheniya-kachestva-meditsinskoy-pomoshi
Sannikov AG. Systems of support of decision-making in forensic psychiatry. Vrach i informatsionnye tekhnologii. 2008;4:64-65. Accessed February 12, 2021. (In Russ.). https://www.elibrary.ru/download/elibrary_11968988_36158120.pdf
Khromushin VA, Khadartsev AA, Dailnev VI, lastovetsky AG. Principles of implementing mortality monitoring at the regional level. Vestnik novykh meditsinskikh tekhnologii. Elektronnoe izdanie. 2014;1. (In Russ.). https://doi.org/10.12737/5610
Berseneva EA, Mikhaylov DYu. Comparative analysis of coding indicators in the departments of the Clinical Hospital of Ministry of Internal Affairs of the Russian Federation for Moscow. Ural’skij medicinskij zhurnal. 2020(4):61-66. (In Russ.). https://doi.org/10.25694/URMJ.2020.04.09