Designing a Coding Data Warehouse to Support and Enhance Medical Act Coding.

Standards Data Warehouse has been implemented in many hospitals. It has enormous potential to improve performance measurement and health care quality. Accessing, organizing, and using these data to optimize clinical coding are evolving challenges for hospital systems.

Design and Implementation of Big Data-Based Documents to Optimize Medical Coding.

Clinical information systems (CISs) in some hospitals streamline the data management from data warehouses. These warehouses contain heterogeneous information from all medical specialties that offer patient care services. It is increasingly difficult to manage large volumes of data in a specific clinical context such as quality coding of medical services.

Constructing a Pre-Emptive System Based on a Multidimentional Matrix and Autocompletion to Improve Diagnostic Coding in Acute Care Hospitals.

Short-stay MSO (Medicine, Surgery, Obstetrics) hospitalization activities in public and private hospitals providing public services are funded through charges for the services provided (T2A in French). Coding must be well matched to the severity of the patient's condition, to ensure that appropriate funding is provided to the hospital. We propose the use of an autocompletion process and multidimensional matrix, to help physicians to improve the expression of information and to optimize clinical coding.

Using a snowflake data model and autocompletion to support diagnostic coding in acute care hospitals.

Purpose: Efficient and adequate coding is essential for all hospitals to optimize funding, follow activity, and perform epidemiological studies.

Objective: We propose an autocompletion method for optimizing diagnostic coding in acute care hospitals.

Methods: Using a terminology snowflake model integrating SNOMED 3.

Determinants of continuance intention in a post-adoption satisfaction evaluation of a clinical information system.

Purpose: The evaluation of end-user satisfaction is an essential part of any clinical information system (CIS) project. The purpose of this study is to evaluate the determinants of CIS continuance intention in a late post-adoption phase at the Georges Pompidou University Hospital (HEGP) in Paris.

Methods: We designed an electronic survey instrument based on an IT post-adoption model (ITPAM) developed from three previous models, i.