| Creators: |
Oberste, Luis and Finze, Nikola and Hoffmann, Philipp and Heinzl, Armin |
| Title: |
Supporting the Billing Process in Outpatient Medical Care: Automated Medical Coding Through Machine Learning |
| Item Type: |
Conference or Workshop Item |
| Event Title: |
(Proceedings of the) 30th European Conference on Information Systems (ECIS) |
| Event Location: |
Timișoara, Romania |
| Event Dates: |
June, 18-24, 2022 |
| Projects: |
IDI |
| Page Range: |
Paper 1765 |
| Additional Information: |
Zugl.: Research Paper 136 |
| Date: |
2022 |
| Divisions: |
Informationsmanagement |
| Abstract (ENG): |
Reimbursement in medical care implies significant administrative effort for medical staff. To bill the treatments or services provided, diagnosis and treatment codes must be assigned to patient records using standardized healthcare classification systems, which is a time-consuming and error-prone task. In contrast to ICD diagnosis codes used in most countries for inpatient care reimbursement, outpatient medical care often involves different reimbursement schemes. Following the Action Design Research methodology, we developed an NLP-based machine learning artifact in close collaboration with a general practitioner’s office in Germany, leveraging a dataset of over 5,600 patients with more than 63,000 billing codes. For the code prediction of most problematic treatments as well as a complete code prediction task, we achieved F1-scores of 93.60 % and 78.22 %, respectively. Throughout three iterations, we derived five meta requirements leading to three design principles for an automated coding system to support the reimbursement of outpatient medical care. |
| Forthcoming: |
No |
| Language: |
English |
| Citation: |
Oberste, Luis and Finze, Nikola and Hoffmann, Philipp and Heinzl, Armin
(2022)
Supporting the Billing Process in Outpatient Medical Care: Automated Medical Coding Through Machine Learning.
In: (Proceedings of the) 30th European Conference on Information Systems (ECIS), June, 18-24, 2022, Timișoara, Romania, Paper 1765.
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