Improving Health Care Outcomes through Personalized Comparisons of Treatment Effectiveness Based on Electronic Health Records

Abstract

Comparative effectiveness research (CER) is one of the Patient Protection and Affordable Care Act's significant initiatives that aims to improve treatment outcomes and lower health care costs. This article takes CER a step further and suggests a novel clinical application for it. The article proposes the development of a national framework to enable physicians to rapidly perform, through a computerized service, medically sound personalized comparisons of the effectiveness of possible treatments for patients' conditions. A treatment comparison for a given patient would be based on data from electronic health records of a cohort of clinically similar patients who received the treatments previously and whose outcomes were recorded. This framework has unique potential to simultaneously improve the quality of health care, reduce its cost, and alleviate public concerns about rationing and “one size fits all” medicine.

Health Information Technology and Nursing

“…Anecdotal reports show conflicting evidence regarding efficiencies and improved quality relating to EHRs, [16][17][18][19][20] and although EHRs are expected to streamline certain processes for nurses, there is the possibility that switching to this new technology could compromise patient safety if users aren't properly educated on its use. Anecdotal reports show conflicting evidence regarding efficiencies and improved quality relating to EHRs, [16][17][18][19][20] and although EHRs are expected to streamline certain processes for nurses, there is the possibility that switching to this new technology could compromise patient safety if users aren't properly educated on its use.…”

Metaheuristic Algorithms for Healthcare: Open Issues and Challenges

“…• National and regional level: At this level, how to represent and keep the data of patients typically is a critical research issue [31] . Finding useful information from the data of a national or regional medical center [26,44,55,56] has been a promising research trend in recent years because a data analytics system can verify the assumption and find out interesting patterns from a sufficient amount of data. Moreover, metaheuristic-based data mining algorithms can be used to find out the relationships between symptoms and particular disease, or even the relationships between cause and effect of human behaviors and disease.…”

Technology and the Bedside Nurse

“…Recent actual and proposed developments in big data analytics within the EMR are increasingly making this possible. 39,40 The future of evidence-based careHealthcare accelerator Rock Health is predicting big advances for startups and healthcare providers using personalized, predictive analytic tools. The use of predictive analytics, essentially looking at historic data to predict future developments to directly intervene in patient care, will only increase as data multiplies, the report argues.…”