In 2025, coding inaccuracies in National Insurance Health (NIH) inpatient claims at Sulianti Saroso Infectious Disease Hospital (SSIDH) significantly contributed to pending claims, negatively impacting the hospital's financial performance. This study aimed to identify the factors influencing coding inaccuracies on NHI pending claims. Using a mixed-methods approach with an explanatory sequential design, researchers analyzed 425 randomly selected NHI inpatient claim files. Chi-Square tests revealed significant relationships between pending claims and five variables: incomplete supporting data, differences in perception between coders and NIH verifiers, incomplete medical administration, incomplete medical resumes, and coding non-compliance (all with p-values of 0.000). Logistic regression analysis showed that differences in perception between coders and the SSAA verifier had the greatest impact, increasing the likelihood of pending claims by a factor of 1,789.5. Incomplete supporting data increased the likelihood by 1.1 times, while coder competence and experience increased it by 6.1 times. The study concluded that coding inaccuracy is primarily influenced by differences in perception between hospital coders and SSAA verifiers, followed by coder competence and incomplete documentation. To reduce pending claims, the study recommends improving coder training, standardizing communication protocols between hospitals and SSAA, and strengthening administrative completeness. These measures are crucial for enhancing claim accuracy and improving hospital financial outcomes.