![]() We used the electronic data elements to create case studies of older adults describing their health status including their socio-demographic, functional, cognitive, physical, mental, emotional, home environment and social support descriptors. Our study used de-identified data from variables gathered through approximately 1200 nursing admission assessments and ongoing documentation throughout the hospital stay. Most often, these CDS interventions arise from electronic health record (HER) data that is calculated, synthesized, or analyzed to provide meaningful information to the user at a critical decision point ( 6, 7). Examples of CDS interventions might include alerts/reminders, clinical guidelines, order sets, patient data reports and dashboards, documentation templates, diagnostic support, and other tools. A critical role of CDS is to provide healthcare providers, patients, and caregivers with general and person-specific information, intelligently filtered and organized, to enhance health and healthcare ( 6). home care, skilled nursing facility, etc.) (National Institute of Nursing Research 2RO1-007674). Based on seminal patient characteristics, the system will recommend the most appropriate site of care (i.e. Our research team is developing a clinical decision support (CDS) system for discharge planning that will assist clinicians to identify patients in need of post-acute referral. The implications and importance of this topic is critical to nurse managers and hospital administrators because they develop and approve documentation and data-use policies and provide strategic guidance to the informatics nurse leaders. ![]() The purpose of this article is to describe the challenges, solutions, and implications related to semantic harmonization while conducting research using EHR data from 4 hospitals. It can occur in one health system or across multiple systems. Semantic harmonization is the process of combining data from heterogeneous sources into a single clinical system ( 5). This requires the merging of data from multiple sources and semantic harmonization may be an issue. In addition, to increase the likelihood of generalizable results, researchers often seek samples from a variety of sites. Secondary use of data meant for clinical documentation, billing, or administrative purposes presents several challenges including issues around the collection from original sources, storage, aggregation, linkage and transmission of health data ( 4). However, we are in the beginning stages of seeing researchers actually use EHR data for studies. Further, the Institute of Medicine proposed a learning health system in which we use patient and health care information for research and continuous improvement in health and healthcare ( 3). Meaningful use of electronic health information, mandated by the Health Information Technology for Economic and Clinical Health (HITECH) Act, involves using EHR and related technology to improve quality, safety and efficiency of patient care engage patients and families improve care coordination and ensure adequate privacy and security for personal health information ( 2). The increasing number of EHR installations and several recent national policy initiatives have supported this trend. Using data elements from the electronic health record (EHR) for purposes beyond clinical documentation, billing, and administration is a rapidly growing practice ( 1).
0 Comments
Leave a Reply. |