Health IT Regulation: Report of an Implementation Challenge.
Author(s): Strasberg, Howard R, Weinstein, David, Borbolla, Damian, McClure, Robert C
DOI: 10.1055/s-0044-1779022
Author(s): Strasberg, Howard R, Weinstein, David, Borbolla, Damian, McClure, Robert C
DOI: 10.1055/s-0044-1779022
Observational research has shown its potential to complement experimental research and clinical trials by secondary use of treatment data from hospital care processes. It can also be applied to better understand pediatric drug utilization for establishing safer drug therapy. Clinical documentation processes often limit data quality in pediatric medical records requiring data curation steps, which are mostly underestimated.
Author(s): Rödle, Wolfgang, Prokosch, Hans-Ulrich, Neumann, Eva, Toni, Irmgard, Haering-Zahn, Julia, Neubert, Antje, Eberl, Sonja
DOI: 10.1055/s-0043-1777741
Despite mortality benefits, only 19.9% of U.S. adults are fully vaccinated against the coronavirus disease 2019 (COVID-19). The inpatient setting is an opportune environment to update vaccinations, and inpatient electronic health record (EHR) alerts have been shown to increase vaccination rates.
Author(s): Black, Kameron Collin, Snyder, Nicole Ashley, Zhou, Mengyu, Zhu, Zhen, Uptegraft, Colby, Chintalapani, Ani, Orwoll, Benjamin
DOI: 10.1055/a-2250-6305
Patient-reported outcome (PRO) measures have become an essential component of quality measurement, quality improvement, and capturing the voice of the patient in clinical care. In 2004, the National Institutes of Health endorsed the importance of PROs by initiating the Patient-Reported Outcomes Measurement Information System (PROMIS), which leverages computer-adaptive tests (CATs) to reduce patient burden while maintaining measurement precision. Historically, PROMIS CATs have been used in a large number of research [...]
Author(s): Nolla, Kyle, Rasmussen, Luke V, Rothrock, Nan E, Butt, Zeeshan, Bass, Michael, Davis, Kristina, Cella, David, Gershon, Richard, Barnard, Cynthia, Chmiel, Ryan, Almaraz, Federico, Schachter, Michael, Nelson, Therese, Langer, Michelle, Starren, Justin
DOI: 10.1055/a-2235-9557
Existing monitoring of machine-learning-based clinical decision support (ML-CDS) is focused predominantly on the ML outputs and accuracy thereof. Improving patient care requires not only accurate algorithms but also systems of care that enable the output of these algorithms to drive specific actions by care teams, necessitating expanding their monitoring.
Author(s): Hekman, Daniel J, Barton, Hanna J, Maru, Apoorva P, Wills, Graham, Cochran, Amy L, Fritsch, Corey, Wiegmann, Douglas A, Liao, Frank, Patterson, Brian W
DOI: 10.1055/a-2219-5175
This study aimed to utilize metrics from physician action logs to analyze surgeon clinical, volume, electronic health record (EHR) efficiency, EHR proficiency, and workload outside scheduled time as impacted by physician characteristics such as years of experience, gender, subspecialty, academic title, and administrative title.
Author(s): Tang, Kevin, Labagnara, Kevin, Babar, Mustufa, Loloi, Justin, Watts, Kara L, Jariwala, Sunit, Abraham, Nitya
DOI: 10.1055/a-2194-1061
Improving child health using health information technology (IT) requires a unique set of functionalities that are built into the electronic health record (EHR) and are used to support patient care. In this article, we review and discuss the milestones preceding the development of a new child health EHR standard and describe the salient features of this contemporary standard.
Author(s): Shafi, Obeid, Liu, Daniel, Thompson, Cori, Margo, Todd, Bennett, Timothy, Suresh, Srinivasan, Yu, Feliciano
DOI: 10.1055/a-2188-0736
Children with medical complexity (CMC) are uniquely vulnerable to medication errors and preventable adverse drug events because of their extreme polypharmacy, medical fragility, and reliance on complicated medication schedules and routes managed by undersupported family caregivers. There is an opportunity to improve CMC outcomes by designing health information technologies that support medication administration accuracy, timeliness, and communication within CMC caregiving networks.
Author(s): Jolliff, Anna, Coller, Ryan J, Kearney, Hannah, Warner, Gemma, Feinstein, James A, Chui, Michelle A, O'Brien, Steve, Willey, Misty, Katz, Barbara, Bach, Theodore D, Werner, Nicole E
DOI: 10.1055/a-2214-8000
Standardized taxonomies (STs) facilitate knowledge representation and semantic interoperability within health care provision and research. However, a gap exists in capturing knowledge representation to classify, quantify, qualify, and codify the intersection of evidence and quality improvement (QI) implementation. This interprofessional case report leverages a novel semantic and ontological approach to bridge this gap.
Author(s): Gao, Grace, Vaclavik, Lindsay, Jeffery, Alvin D, Koch, Erica C, Schafer, Katherine, Cimiotti, Jeannie P, Pathak, Neha, Duva, Ingrid, Martin, Christie L, Simpson, Roy L
DOI: 10.1055/a-2207-7396
Standardized taxonomies (STs) facilitate knowledge representation and semantic interoperability within health care provision and research. However, a gap exists in capturing knowledge representation to classify, quantify, qualify, and codify the intersection of evidence and quality improvement (QI) implementation. This interprofessional case report leverages a novel semantic and ontological approach to bridge this gap.
Author(s): Gao, Grace, Vaclavik, Lindsay, Jeffery, Alvin D, Koch, Erica C, Schafer, Katherine, Cimiotti, Jeannie P, Pathak, Neha, Duva, Ingrid, Martin, Christie L, Simpson, Roy L
DOI: 10.1055/s-0043-1777455