EHR-mediated Workflow Analysis and Optimization Framework in PreOp Settings

Perioperative care has a direct and crucial impact on patient safety and patient outcomes, as well as the financial viability of the healthcare facility. The time pressure and workload of caring patients facing surgery are heavier than caring inpatients of other departments. This workload raises requirements for PreOp nurses, the primary PreOp caregiver, to complete information gathering, screening, and verification tasks accurately and efficiently. EHRs (Electronic Health Record System) have evolved continuously with increasing features to meet newly raised needs and expectations. Many healthcare institutions have undergone EHR conversion since the introduction of first-generation EHRs. Thus, the need for a systematic evaluation of changed information system workflow following conversion is becoming more and more manifest. There are a growing number of methods for analyzing health information technology use. However, few studies provide and apply a standard method to understand the impact of EHR transition and inspire opportunities for improvement. This dissertation focuses on PreOp nurse’s EHR use in PreOp settings. The goals of this dissertation are to: (a) introduce a systematic framework to evaluate EHR-mediated workflow and the impact of the EHR transition; (b) understand the impact of different EHR systems on PreOp nurse’s workflow and preoperative care efficiency; (c) transform the evaluation results into practical user-centered EHR designs. This research draws on computational ethnography, cognitive engineering process and user-centered design concepts to build a practical approach for EHR transition-related workflow evaluation and optimization. Observational data were collected before and after a large-scale EHR conversion throughout Mayo Clinic’s different regional health systems. For a structured computational evaluation framework, the time-efficiency of PreOp nurses’ work were compared quantitatively by means of coding and segmenting nurses’ tasks. Interview data provided contextual information, reflecting practical challenges and opportunities before and after the EHR transition. The total case time, the time spent on EHR, and the task fragmentation were improved after converting to the new EHR system. A trend of standardization of information-related workflow and EHR transition was observed. Notably, the approach helped to identify current new system challenges and pointed out potential optimization solutions.