Accuracy Analysis of Topographical and Morphological Code in the RSUP Dr. Sardjito Cancer Registry, Indonesia

In cancer cases, a cancer registry functions as a national cancer control program to analyze cancer severity and risk factors in specific areas, aiming to reduce morbidity and mortality. Accurate coding is essential for producing a high-quality cancer database. This study aims to analyze the accuracy of the cancer registry at RSUP Dr. Sardjito in assigning topography and morphology codes. A mixed-methods approach was employed to evaluate code accuracy and identify factors influencing accuracy and inaccuracy based on the 5M framework. Data were sourced from the Hospital-Based Cancer Registry at RSUP Dr. Sardjito, with a total population of 4500 patients in 2021. A sample of 1000 cancer patients was selected using a simple random sampling technique. Each sample was analyzed as true or false based on verifier notes, revealing that 904 topography codes were accurate (90.40%) and 96 were inaccurate (9.60%). For morphology codes, 913 were accurate (91.30%) and 87 were inaccurate (8.70%). Researchers conducted in-depth interviews with registrars and verifier doctors and observed all cancer registry activities, focusing on topography and morphology codification. Observations and interviews indicated no obstacles in codification activities, but inaccuracies occurred, possibly due to case complexity. In conclusion, the study demonstrates high accuracy in the coding of cancer cases at RSUP Dr. Sardjito. The complexity of cases may contribute to inaccuracies. The study suggests continuous evaluation to enhance coding accuracy, which is crucial for effective cancer control programs.

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Publication Details

Journal
JMMR (Jurnal Medicoeticolegal dan Manajemen Rumah Sakit)
Published
2024-08-15
DOI
https://doi.org/10.18196/jmmr.v13i2.406
Primary Topic
AI in cancer detection
Type
article
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article

Accuracy Analysis of Topographical and Morphological Code in the RSUP Dr. Sardjito Cancer Registry, Indonesia

Savitri Citra Budi, Yuliana Yuliana, Dhea Edvy Permata Putri, Novi Nurhidayah
JMMR (Jurnal Medicoeticolegal dan Manajemen Rumah Sakit)
AI in cancer detection
article

Accuracy Analysis of Topographical and Morphological Code in the RSUP Dr. Sardjito Cancer Registry, Indonesia

Savitri Citra Budi, Yuliana Yuliana, Dhea Edvy Permata Putri, Novi Nurhidayah
article en

Abstract

In cancer cases, a cancer registry functions as a national cancer control program to analyze cancer severity and risk factors in specific areas, aiming to reduce morbidity and mortality. Accurate coding is essential for producing a high-quality cancer database. This study aims to analyze the accuracy of the cancer registry at RSUP Dr. Sardjito in assigning topography and morphology codes. A mixed-methods approach was employed to evaluate code accuracy and identify factors influencing accuracy and inaccuracy based on the 5M framework. Data were sourced from the Hospital-Based Cancer Registry at RSUP Dr. Sardjito, with a total population of 4500 patients in 2021. A sample of 1000 cancer patients was selected using a simple random sampling technique. Each sample was analyzed as true or false based on verifier notes, revealing that 904 topography codes were accurate (90.40%) and 96 were inaccurate (9.60%). For morphology codes, 913 were accurate (91.30%) and 87 were inaccurate (8.70%). Researchers conducted in-depth interviews with registrars and verifier doctors and observed all cancer registry activities, focusing on topography and morphology codification. Observations and interviews indicated no obstacles in codification activities, but inaccuracies occurred, possibly due to case complexity. In conclusion, the study demonstrates high accuracy in the coding of cancer cases at RSUP Dr. Sardjito. The complexity of cases may contribute to inaccuracies. The study suggests continuous evaluation to enhance coding accuracy, which is crucial for effective cancer control programs.

JMMR (Jurnal Medicoeticolegal dan Manajemen Rumah Sakit)Vol. 13(2)
Universitas Gadjah Mada (ID), Rumah Sakit Umum Pusat Dr. Sardjito (ID)
Good health and well-being
Openalex Percentile: Top 88%
AI in cancer detection
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