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Printable Version
A1297
October 26, 2005
9:00:00 AM - 11:00:00 AM
Hall C4
Development of Automated Patient Disposition Tracking System Which Improves the Efficiency in Quality Assurance
Tomohiro Sawa, M.D., Ph.D., Masaharu Okahara, M.D., Takashi Funahara, M.D., Schmidt H. Ulrich, M.D., Ph.D., Yoshinori Nakata, M.D., M.B.A.
Department of Anesthesia, Teikyo University School of Medicine, Tokyo, Japan
Introduction: Hospital information system (HIS) and electronic health records (EHR) have been widely adopted and operating room (OR) workflow has become more efficient with OR management system. Attention has been paid to quality improvement in the post operative period. Although anesthesiologists usually visit patients for post-operative round within a couple of days after the operation, it is sometimes difficult to follow post-operative course until discharge. In this study, we developed automated disposition tracking system to follow post-operative course during the hospital stay. Using the system, it is easy to grasp patient disposition on the discharge and efficiently survey quality of post-operative care in the hospital.

Methods: The system analyzes Admission-Discharge-Transfer (ADT) data in HIS, problem-list data in EHR and anesthesia summary data in OR management system. The system is consisting of 3-tier architecture (web application layer, business logic layer and database layer). The database layer manages the three different databases, which are ADT in HIS, problems-list in EHR and anesthesia summary in OR management system. The layer uses OLE DB driver and was programmed using Microsoft .NET framework which integrates heterogeneous databases at the layer. The business logic layer issues SQL which generates inner join of ADT and problem-list using a patient ID in the anesthesia summary data as a primary key. The layer filters the rows of joined tables based on the different kind of disposition on discharge. Lastly, web application layer presents the results through web browser. The system interacts with the user who selects the term of the survey and indicates the kind of disposition. As a sample data, we used 2,183 anesthesia records in the year of 2004 and focused on the mortality on discharge.

Results: The system found 28 deaths on discharge in 2,183 operations in the year 2004. The time of the data generation from 300,000 master patient indexes was about five seconds. Out of the 28 cases, 6 cases (6 cases: ASAPS >= 3; 5 cases: emergency) died within 7 post-operative days, 11 cases (9 cases: ASAPS >= 3; 3 cases: emergency) died within 30 post-operative days and 11 cases (9 cases: ASAPS >= 3; 1 case: emergency) died more than 30 days after the operation. Eighty three percent of the cases who died within 7 post-operative days were resulted from acute disease such as trauma, cardiovascular disease. On the contrary, cancer or infectious diseases occupied 81 percent of the 11 cases who died more than 30 post-operative days.

Conclusion: We built an automated disposition tracking system which survey across the different databases in HIS, EHR and OR management system. For the quality assurance purposes, we have been surveyed paper based patient records and anesthesia records for all operations every year by manual. It took about several days to a week with a skilled clerk to complete the task. With the system we developed, we could save labor and time for the quality assurance survey.

Anesthesiology 2005; 103: A1297