The electronic health record: does it enhance or distract from patient safety?

The electronic health record (EHR) is an invaluable tool that may be used to improve patient safety. With a variety of different features, such as clinical decision support and computerized physician order entry, it has enabled improvement of patient care throughout medicine. EHR allows for built-in reminders for such items as antibiotic dosing and venous thromboembolism prophylaxis. In anesthesiology, EHR often improves patient safety by eliminating the need for reliance on manual documentation, by facilitating information transfer and incorporating predictive models for such items as postoperative nausea and vomiting. The use of EHR has been shown to improve patient safety in specific metrics such as using checklists or information transfer amongst clinicians; however, limited data supports that it reduces morbidity and mortality. There are numerous potential pitfalls associated with EHR use to improve patient safety, as well as great potential for future improvement.

Tewfik G ，Rivoli S ，Methangkool E 《-》

Future of electronic health records: implications for decision support.

The potential benefits of the electronic health record over traditional paper are many, including cost containment, reductions in errors, and improved compliance by utilizing real-time data. The highest functional level of the electronic health record (EHR) is clinical decision support (CDS) and process automation, which are expected to enhance patient health and healthcare. The authors provide an overview of the progress in using patient data more efficiently and effectively through clinical decision support to improve health care delivery, how decision support impacts anesthesia practice, and how some are leading the way using these systems to solve need-specific issues. Clinical decision support uses passive or active decision support to modify clinician behavior through recommendations of specific actions. Recommendations may reduce medication errors, which would result in considerable savings by avoiding adverse drug events. In selected studies, clinical decision support has been shown to decrease the time to follow-up actions, and prediction has proved useful in forecasting patient outcomes, avoiding costs, and correctly prompting treatment plan modifications by clinicians before engaging in decision-making. Clinical documentation accuracy and completeness is improved by an electronic health record and greater relevance of care data is delivered. Clinical decision support may increase clinician adherence to clinical guidelines, but educational workshops may be equally effective. Unintentional consequences of clinical decision support, such as alert desensitization, can decrease the effectiveness of a system. Current anesthesia clinical decision support use includes antibiotic administration timing, improved documentation, more timely billing, and postoperative nausea and vomiting prophylaxis. Electronic health record implementation offers data-mining opportunities to improve operational, financial, and clinical processes. Using electronic health record data in real-time for decision support and process automation has the potential to both reduce costs and improve the quality of patient care.

Rothman B ，Leonard JC ，Vigoda MM 《-》

National Trends in the Safety Performance of Electronic Health Record Systems From 2009 to 2018.

Classen DC ，Holmgren AJ ，Co Z ，Newmark LP ，Seger D ，Danforth M ，Bates DW ... -  《JAMA Network Open》

Electronic Health Records and Use of Clinical Decision Support.

In 2009, the Health Information Technology for Economic and Clinical Health (HITECH) Act was signed into law. Along with this initiative came the push for meaningful use of the electronic health record. Clinicians, information technology professionals, and informaticists must partner to create evidence-based clinical decision support models to guide patient care using tools such as structured computerized physician order entry, order sets, templates, alerts, and reminders. Clinical decision support should be used to improve the quality of patient care and compliance with regulatory standards, while inherently following a provider's workflow.

Mills S 《-》

Clinical Decision Support using a Terminology Server to improve Patient Safety.

Garcia-Jimenez A ，Moreno-Conde A ，Martínez-García A ，Marín-León I ，Medrano-Ortega FJ ，Parra-Calderón CL ... -  《-》