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      Evaluating the effect of an in-service training workshop on ICD-10 coding instructions of pregnancy, childbirth and the puerperium for clinical coders

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          Abstract

          The quality of the data coded based on the 10 th revision of the International Classification of Diseases (ICD-10) can be improved by providing continuous education and promoting the clinical coders’ knowledge and skills. Due to the significance of maternal health in promoting the health of society, the present study evaluated the effects of an in-service training workshop on ICD-10 coding instructions of pregnancy, childbirth, and the puerperium for clinical coders. This applied evaluation study was conducted to evaluate the effects of a coding instructions training course focusing on the 15 th chapter of the ICD-10. The statistical population comprised 45 clinical coders working in the hospitals. The data were collected by a researcher-made questionnaire scored on a five-point Likert scale at the reaction level and by pretest and posttest questionnaires at the learning level. The data were then analyzed by descriptive statistics at the reaction level and by a paired-samples t-test at the learning level. The participants’ satisfaction with the training course was 94.7% on average at the reaction level. At the learning level, the results of the paired-samples t-test showed a significant difference between the means of scores before and after the training course (p=0.000). The training course led to satisfaction and enhanced the capabilities of the clinical coders with regard to coding the 15 th chapter of ICD-10. Clinical Coders must receive training on the new changes and guidelines in the other chapters of ICD-10 based on its most recent revision and employ them in the workplace.

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          Reliability of diagnoses coding with ICD-10.

          Reliability of diagnoses coding is essential for the use of routine data in a national health care system. The present investigation compares reliability of diagnoses coding with ICD-10 between three groups of coding subjects. One hundred and eighteen students coded 15 diagnoses lists, 27 medical managers from hospitals 34 discharge letters, and 13 coding specialists 12 discharge letters. Agreement in principal diagnosis was assessed using Cohen's Kappa and the fraction of coincidences over the number of pairs, agreement for the full set of diagnoses with a previously developed measure p(om). Kappa values were fair (managers) or moderate (coders) for terminal codes with 0.27 and 0.42 (agreement 29.2% versus 46.8%), substantial for the chapter level with 0.71 and 0.72 (agreement 78.3% versus 80.8%). p(om) was lower for the full set of diagnoses than for principal diagnoses, for example in case of managers with 0.21 versus 0.29 for terminal codes. Best results were achieved by students coding diagnoses lists. In summary, the results are remarkably lower than in earlier publications. The refinement of the ICD-10 accompanied by innumerous coding rules has established a complex environment that leads to significant uncertainties even for experts. Use of coded data for quality management, health care financing, and health care policy requires a remarkable simplification of ICD-10 to receive a valid image of health care reality.
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            Coder perspectives on physician-related barriers to producing high-quality administrative data: a qualitative study.

            Professional coding specialists ("coders") are experts at translating patient chart information into alphanumerical codes, which are then widely used in research and health policy decision-making. Coders rely solely on documentation by health care providers to complete this task. We aimed to explore physician-related barriers to coding that results in high-quality administrative data.
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              Do coder characteristics influence validity of ICD-10 hospital discharge data?

              Background Administrative data are widely used to study health systems and make important health policy decisions. Yet little is known about the influence of coder characteristics on administrative data validity in these studies. Our goal was to describe the relationship between several measures of validity in coded hospital discharge data and 1) coders' volume of coding (≥13,000 vs. <13,000 records), 2) coders' employment status (full- vs. part-time), and 3) hospital type. Methods This descriptive study examined 6 indicators of face validity in ICD-10 coded discharge records from 4 hospitals in Calgary, Canada between April 2002 and March 2007. Specifically, mean number of coded diagnoses, procedures, complications, Z-codes, and codes ending in 8 or 9 were compared by coding volume and employment status, as well as hospital type. The mean number of diagnoses was also compared across coder characteristics for 6 major conditions of varying complexity. Next, kappa statistics were computed to assess agreement between discharge data and linked chart data reabstracted by nursing chart reviewers. Kappas were compared across coder characteristics. Results 422,618 discharge records were coded by 59 coders during the study period. The mean number of diagnoses per record decreased from 5.2 in 2002/2003 to 3.9 in 2006/2007, while the number of records coded annually increased from 69,613 to 102,842. Coders at the tertiary hospital coded the most diagnoses (5.0 compared with 3.9 and 3.8 at other sites). There was no variation by coder or site characteristics for any other face validity indicator. The mean number of diagnoses increased from 1.5 to 7.9 with increasing complexity of the major diagnosis, but did not vary with coder characteristics. Agreement (kappa) between coded data and chart review did not show any consistent pattern with respect to coder characteristics. Conclusions This large study suggests that coder characteristics do not influence the validity of hospital discharge data. Other jurisdictions might benefit from implementing similar employment programs to ours, e.g.: a requirement for a 2-year college training program, a single management structure across sites, and rotation of coders between sites. Limitations include few coder characteristics available for study due to privacy concerns.
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                Author and article information

                Journal
                J Med Life
                J Med Life
                JMedLife
                Journal of Medicine and Life
                Carol Davila University Press (Romania )
                1844-122X
                1844-3117
                Jul-Aug 2021
                : 14
                : 4
                : 565-569
                Affiliations
                [1. ]Department of Health Information Technology, School of Paramedical Sciences, Kermanshah University of Medical Sciences, Kermanshah, Iran
                [2. ]Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
                Author notes
                * Corresponding Author: Farkhondeh Asadi, Associate Professor of Health Information Management, Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Darband St, Qods Square, Shariati St, Tehran, Iran E-mail: asadifar@ 123456sbmu.ac.ir
                Author information
                https://orcid.org/
                Article
                JMedLife-14-565
                10.25122/jml-2021-0062
                8485367
                34621383
                e882ffa2-cc16-482d-8f5f-e265aab9917f
                ©2021 JOURNAL of MEDICINE and LIFE

                This article is distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 4 April 2021
                : 15 July 2021
                Categories
                Original Article

                Medicine
                clinical coders,evaluation,icd-10,in-service training,kirkpatrick model
                Medicine
                clinical coders, evaluation, icd-10, in-service training, kirkpatrick model

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