Managing Health Care Risk and Hospital Operations
Sloan School of Management, Massachusetts Institute of Technology, Center for Digital Business
To better understand the factors that support or inhibit process improvement in a hospital setting, we studied one hospital’s attempt to implement a health information system (HIS) to reduce errors in medical treatment and manage material flows. As part of this analysis, we explore opportunities to merge real-time operational data with feedback modeling to provide dynamic tools for hospital administration, risk management, and education and training. We believe that the major gains in HIS use will accompany new information gathering capabilities, as these capabilities result in collections of data that can be used to greatly improve patient safety, hospital operations, and medical decision support.
Our analysis suggests that critical determinants of success in efforts to improve hospital efficiency include connections among key hospital staff, including doctors, nurses, and pharmacists, as well as patients. Building on these observations, we propose a dynamic model capturing the evolution of the interactions among the “physics” underling hospital operations, information technology (IT), and staff behavior.
Our research will continue to utilize the valuable data produced by the POAS system by applying computational social science methodologies, primarily system dynamics modeling (SDM), to provide insights into the dynamics of improvement in POAS hospitals. In particular, we will explore opportunities to merge real time operational data with system dynamics methodologies; we anticipate this will be a powerful step forward in the utilization of hospital data, and will result in high-leverage management tools with continuously updating feedback.
