Accession Number : ADA434178


Title :   Evaluating and Predicting Patient Safety for Medical Devices With Integral Information Technology


Corporate Author : AGENCY FOR HEALTHCARE RESEARCH AND QUALITY ROCKVILLE MD


Personal Author(s) : Zhang, Jiajie ; Patel, Vimla L ; Johnson, Todd R ; Chung, Philip ; Turley, James P


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a434178.pdf


Report Date : Jan 2005


Pagination or Media Count : 15


Abstract : Human errors in medical device use account for a large portion of medical errors. Most of these errors are due to inappropriate designs for user interactions, rather than mechanical failures. Evaluating and predicting patient safety in medical device use is critical for developing interventions to reduce such errors either by redesigning the devices or, if redesign is not an option, by training the users on the identified trouble spots in the devices. We developed two methods for evaluating and predicting patient safety in medical devices with integral information technology, then applied and tested them on several infusion pumps. The first method is a modified discount-usability method called heuristic evaluation. The method was used to evaluate and compare the safety of two 1-channel volumetric infusion pumps. The results show that heuristic evaluation, when modifies for medical devices, is a useful, efficient, and low-cost method for evaluating patient safety features of medical devices through the identification of usability problems and their severities. The second method is an extended hierarchical task analysis (EHTA), devised to predict medical errors in medical device use. EHTA divides the task space between the external world of the device interface and the internal cognitive world of the user, allowing for descriptive predictions of potential user errors at the human device level. Its use is demonstrated in the analysis of two infusion pumps. The estimates of the likelihood of user errors with the two pumps are consistent with the corresponding reported use errors in the Federal Drug Administration (FDA)'s manufacturer and User Device Experience (MAUDE) database, thus demonstrating the usefulness of this tool for predicting medical device use errors.


Descriptors :   *SAFETY , *PATIENTS , *HEALTH CARE MANAGEMENT , DATA BASES , PERFORMANCE(HUMAN) , MEDICINE , ERRORS , HEURISTIC METHODS


Subject Categories : Medicine and Medical Research
      Medical Facilities, Equipment and Supplies


Distribution Statement : APPROVED FOR PUBLIC RELEASE