Perioperative and ICU Healthcare Analytics within a Veterans Integrated System Network: a Qualitative Gap Analysis |
| |
Authors: | Seshadri Mudumbai Ferenc Ayer Jerry Stefanko |
| |
Affiliation: | 1.VA Palo Alto Health Care System,Anesthesiology and Perioperative Care Service,Palo Alto,USA;2.Department of Anesthesiology, Perioperative, and Pain Medicine,Stanford University School of Medicine,Stanford,USA;3.VA Office of Quality, Safety and Value,Product Effectiveness Program,Washington,USA;4.Whitney, Bradley and Brown (WBB),Reston,USA |
| |
Abstract: | Health care facilities are implementing analytics platforms as a way to document quality of care. However, few gap analyses exist on platforms specifically designed for patients treated in the Operating Room, Post-Anesthesia Care Unit, and Intensive Care Unit (ICU). As part of a quality improvement effort, we undertook a gap analysis of an existing analytics platform within the Veterans Healthcare Administration. The objectives were to identify themes associated with 1) current clinical use cases and stakeholder needs; 2) information flow and pain points; and 3) recommendations for future analytics development. Methods consisted of semi-structured interviews in 2 phases with a diverse set (n = 9) of support personnel and end users from five facilities across a Veterans Integrated Service Network. Phase 1 identified underlying needs and previous experiences with the analytics platform across various roles and operational responsibilities. Phase 2 validated preliminary feedback, lessons learned, and recommendations for improvement. Emerging themes suggested that the existing system met a small pool of national reporting requirements. However, pain points were identified with accessing data in several information system silos and performing multiple manual validation steps of data content. Notable recommendations included enhancing systems integration to create “one-stop shopping” for data, and developing a capability to perform trends analysis. Our gap analysis suggests that analytics platforms designed for surgical and ICU patients should employ approaches similar to those being used for primary care patients. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|