title: Evaluation of an automated inferencing engine generating ICD-9CM codes for physician and hospital billing.
abstract: Recent Medicare changes to Severity Diagnosis Related Groups (MS-DRGs) for inpatients have made the appropriate and timely coding of services provided by hospitals and physicians a challenge, and require education for clinicians and coders. Clinical departments have limited funds to hire dedicated personnel to code and prepare payor submissions. Automating the process can assist in accurate data collection and reimbursement.
authors.affiliation: NewYork-Presbyterian Hospital, New York, NY, USA.
authors.forename: Maryam
authors.initials: M
authors.lastname: Behta
authors.forename: Glenna
authors.initials: G
authors.lastname: Friedman
authors.forename: Maxine
authors.initials: M
authors.lastname: Manber
authors.forename: Desmond
authors.initials: D
authors.lastname: Jordan
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D016247:Information Storage and Retrieval / Q000379:methods; D007344:Insurance Claim Reporting; D038801:International Classification of Diseases / Q000458:organization & administration*; D016347:Medical Records Systems, Computerized / Q000145:classification*; D009323:Natural Language Processing; D009519:New York City; D010363:Pattern Recognition, Automated / Q000379:methods*; D012984:Software; D012986:Software Validation; D009626:Terminology as Topic