Quality of medical information determine the quality of diagnosis code

Maryati, Warsi; Rahayuningrum, Indriyati Oktaviano; Ismayani, Ani

doi:10.11591/ijphs.v8i3.20236

Cited by 6 publications

(5 citation statements)

References 10 publications

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“…The results of this study are in line with the research of Warsi Waryani et al (2019) at Dr. Moewardi who stated that, complete medical information has a better quality of diagnosis code (73.80%) compared to incomplete medical information (36.00%) with 1.54 times better probability of diagnosis code quality than poor quality (12).…”

Section: Discussionsupporting

confidence: 91%

Correlation Between Medical Information Completeness and Accuracy of The Diagnosis Code for Upper Respiratory Tract Infection and Hypertension Based on ICD-10 in Medical Record at Cibening Health Center

Muchlis

Ramadhanty

2021

MMJ

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Background: Completeness of patient medical information in medical records is one indicator in assessing the quality of health services. Complete and accurate medical records contribute to the accuracy of medical staff in making a diagnosis so that they can determine the correct diagnosis code according to the ICD-10 guidelines. A good medical record shows that a doctor or other medical staff has carried out their duties by the demands of their profession as stated in the Medical Practice Law No.29 of 2004. Purposes: To find out there is or not a correlation between the medical information completeness and the accuracy of the diagnosis code for upper respiratory tract infection and hypertension based on the ICD-10 in the medical record documents of outpatients at the Cibening Health Center in 2019. Method: The method used in this study is observational analytic with a cross-sectional study design. The population of this study was outpatient medical records with a diagnosis of upper respiratory tract infection and hypertension at the Cibening Health Center in 2019. The sampling technique used a simple random sampling technique with a sample size of 100. Results: Out of obtained 71 complete medical record (71%) filling in medical records, 64 medical records (64%) were accurate in giving ICD-10 codes, 63 medical records (88.7%) with complete medical information had accurate diagnosis codes in comparison with 8 medical records (11.3%) which were complete but inaccurate diagnosis code. Conclusion: With a p-value of 0.000, there is a significant correlation between the completeness of medical information and the accuracy of the diagnosis code for Upper Respiratory Tract Infection and Hypertension based on ICD-10.

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Section: Discussionsupporting

confidence: 91%

Correlation Between Medical Information Completeness and Accuracy of The Diagnosis Code for Upper Respiratory Tract Infection and Hypertension Based on ICD-10 in Medical Record at Cibening Health Center

Muchlis

Ramadhanty

2021

MMJ

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“…Regarding the role of poor or inaccurate documentation, Maryati et al emphasized that high-quality medical information leads to a better diagnostic code (about 73.80%), while low-quality medical information leads to a poor diagnostic code (about 36%). When the quality of medical information is high, the quality of the diagnostic code is 1.54 times higher than when the quality of medical information is low (19).…”

Section: Discussionmentioning

confidence: 92%

Factors Affecting Clinical Coding Errors

et al. 2022

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Background: Coding errors lead to incorrect classification of diseases and thus severely affect health care planning and epidemiological research. Objectives: This study aimed to investigate the factors affecting clinical coding errors. Methods: This descriptive study was conducted in 2020 in 2 stages. In the first stage, a questionnaire was developed by examining relevant resources, documents, and articles. The questionnaire’s validity was examined by 5 health information management experts. Its reliability was determined using Cronbach α and correlation coefficient (r = 0.84%). In the second stage, the data were collected by visiting teaching hospitals affiliated with Shahid Beheshti University of Medical Sciences, examining the medical records, and interviewing the coders. Data were analyzed using descriptive statistics. Results: Non-observance of diagnostic principles by physicians, illegibility of medical records, use of ambiguous and nonstandard abbreviations, and incomplete medical documentation were the most important causes of coding errors. Conclusions: Considering the importance of coding in presenting correct data as a powerful lever in health care, knowledge of the factors affecting the occurrence of coding errors will greatly contribute to the selection of effective strategies to reduce and eliminate errors.

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“…In their study entitled "Quality of Medical Information Determines Quality of Diagnostic Code", Maryati et al stated that high quality of medical information leads to better diagnostic coding (about 73.8%), and poor quality of medical information results in poor diagnostic coding (about 36%) (32). Therefore, it is essential that researchers assess this potential error when evaluating other diseases.…”

Section: Discussionmentioning

confidence: 99%

Auditing the Accuracy of Medical Diagnostic Coding based on International Classification of Diseases, Tenth Revision

Mirhashemi

Ramezanghorbani

Asadi

et al. 2020

ircmj

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Background: Medical diagnostic coding is used for the ease of retrieval and accuracy of medical information classification in health information systems. This information is the main source of decision making for health managers and policymakers in planning, epidemiological, and medical research at different levels. Objectives: The present study aimed to audit the accuracy of the ICD-10 (International Classification of Diseases, Tenth Revision) medical diagnosis code. Materials and Methods: The present cross-sectional study was performed on a sample of 692 hospitalized cases in 9 educational centers affiliated to Shahid Beheshti University of Medical Sciences in the first half of 2020. The content validity of the checklist was determined in this study, and the obtained data were analyzed in SPSS software using descriptive statistics. Results: The average accuracy of coding for the main medical diagnoses across all subjects was 70%, signifying that 30% of medical records contain coding errors. The highest and least accuracy values of diagnostic coding were 80% and 47%, respectively. The application of standard abbreviations and file legibility were recognized as variables affecting code accuracy. The highest precision percentage of codes attributed to other medical diagnoses, including ICD-10-based comorbidity and complication, was in 84%-85% of the participants. Conclusion: Given the importance of all-encompassing coding in retrieving medical information, research, and macro-health policymaking, the coding accuracy audit must be conducted on a regular basis. The interaction between coders and healthcare providers, coders' training, and improving the documentation process exerts a significant impact on the enhancement of coding accuracy.

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Quality of medical information determine the quality of diagnosis code

Cited by 6 publications

References 10 publications

Correlation Between Medical Information Completeness and Accuracy of The Diagnosis Code for Upper Respiratory Tract Infection and Hypertension Based on ICD-10 in Medical Record at Cibening Health Center

Correlation Between Medical Information Completeness and Accuracy of The Diagnosis Code for Upper Respiratory Tract Infection and Hypertension Based on ICD-10 in Medical Record at Cibening Health Center

Factors Affecting Clinical Coding Errors

Auditing the Accuracy of Medical Diagnostic Coding based on International Classification of Diseases, Tenth Revision

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