Opportunities for the informatics community to advance learning health systems.

Objectives: There is rapidly growing interest in learning health systems (LHSs) nationally and globally. While the critical role of informatics is recognized, the informatics community has been relatively slow to formalize LHS as a priority area.

Materials And Methods: We compiled results from a short survey of LHS leaders and American Medical Informatics Association (AMIA) members, discussion from an LHS reception at the AMIA annual meeting, and a follow-up survey to inform priorities at the intersection of LHS and informatics.

Ten simple rules to make computable knowledge shareable and reusable.

Computable biomedical knowledge (CBK) is: "the result of an analytic and/or deliberative process about human health, or affecting human health, that is explicit, and therefore can be represented and reasned upon using logic, formal standards, and mathematical approaches." Representing biomedical knowledge in a machine-interpretable, computable form increases its ability to be discovered, accessed, understood, and deployed. Computable knowledge artifacts can greatly advance the potential for implementation, reproducibility, or extension of the knowledge by users, who may include practitioners, researchers, and learners.

Exploring Anesthesia Provider Preferences for Precision Feedback: Preference Elicitation Study.

Background: Health care professionals must learn continuously as a core part of their work. As the rate of knowledge production in biomedicine increases, better support for health care professionals' continuous learning is needed. In health systems, feedback is pervasive and is widely considered to be essential for learning that drives improvement.

Early intranasal medication administration in out-of-hospital cardiac arrest: Two randomized simulation trials.

Objective: Intranasal medications have been proposed as adjuncts to out-of-hospital cardiac arrest (OHCA) care. We sought to quantify the effects of intranasal medication administration (INMA) in OHCA workflows.

Methods: We conducted separate randomized OHCA simulation trials with lay rescuers (LRs) and first responders (FRs).

Factors Impacting Treatment of Out-of-Hospital Cardiac Arrest: A Qualitative Study of Emergency Responders.

Background Of the more than 250 000 emergency medical services-treated out-of-hospital cardiac arrests that occur each year in the United States, only about 8% survive to hospital discharge with good neurologic function. Treatment for out-of-hospital cardiac arrest involves a system of care that includes complex interactions among multiple stakeholders. Understanding the factors inhibiting optimal care is fundamental to improving outcomes.

CBK model composition using paired web services and executable functions: A demonstration for individualizing preventive services.

Introduction: Learning health systems are challenged to combine computable biomedical knowledge (CBK) models. Using common technical capabilities of the World Wide Web (WWW), digital objects called Knowledge Objects, and a new pattern of activating CBK models brought forth here, we aim to show that it is possible to compose CBK models in more highly standardized and potentially easier, more useful ways.

Methods: Using previously specified compound digital objects called Knowledge Objects, CBK models are packaged with metadata, API descriptions, and runtime requirements.

Barriers to the Initiation of Telecommunicator-CPR during 9-1-1 Out-of-Hospital Cardiac Arrest Calls: A Qualitative Study.

Introduction: Fewer than 10% of individuals who suffer out-of-hospital cardiac arrest (OHCA) survive with good neurologic function. Bystander CPR more than doubles the chance of survival, and telecommunicator-CPR (T-CPR) during a 9-1-1 call substantially improves the frequency of bystander CPR.

Objective: We examined the barriers to initiation of T-CPR.

Effectiveness of Lay Bystander Hands-Only Cardiopulmonary Resuscitation on a Mattress versus the Floor: A Randomized Cross-Over Trial.

Study Objective: Bystander cardiopulmonary resuscitation increases the likelihood of out-of-hospital cardiac arrest survival by more than two-fold. A common barrier to the prompt initiation of compressions is moving victims to the floor, but compression quality on a "floor" versus a "mattress" has not been tested among lay bystanders.

Methods: We conducted a prospective, randomized, cross-over trial comparing lay bystander compression quality using a manikin on a bed versus the floor.

Assessment of telecommunicator cardiopulmonary resuscitation performance during out-of-hospital cardiac arrest using a standardized tool for audio review.

Objective: Telecommunicator cardiopulmonary resuscitation (T-CPR) is a critical component of optimized out-of-hospital cardiac arrest (OHCA) care. We assessed a pilot tool to capture American Heart Association (AHA) T-CPR measures and T-CPR coaching by telecommunicators using audio review.

Methods: Using a pilot tool, we conducted a retrospective review of 911 call audio from 65 emergency medical services-treated out-of-hospital cardiac arrest (OHCA) patients.

Development of a standards-based phenotype model for gross motor function to support learning health systems in pediatric rehabilitation.

Introduction: Research and continuous quality improvement in pediatric rehabilitation settings require standardized data and a systematic approach to use these data.

Methods: We systematically examined pediatric data concepts from a pediatric learning network to determine capacity for capturing gross motor function (GMF) for children with Cerebral Palsy (CP) as a demonstration for enabling infrastructure for research and quality improvement activities of an LHS. We used an iterative approach to construct phenotype models of GMF from standardized data element concepts based on case definitions from the Gross Motor Function Classification System (GMFCS).

Partnership development of the COVID-19 Front Door: a best evidence resource.

This project describes the creation of a single searchable resource during the pandemic, called the COVID-19 Best Evidence Front Door, with a primary goal of providing direct access to high-quality meta-analyses, literature syntheses, and clinical guidelines from a variety of trusted sources. The Front Door makes relevant evidence findable and accessible with a single search to aggregated evidence-based resources, optimizing time, discovery, and improved access to quality scientific evidence while reducing the burden of frontline health care providers and other knowledge-seekers in needing to separately identify, locate, and explore multiple websites.

Evaluating Completeness of Discrete Data on Physical Functioning for Children With Cerebral Palsy in a Pediatric Rehabilitation Learning Health System.

Objective: The purpose of this study was to determine the extent that physical function discrete data elements (DDE) documented in electronic health records (EHR) are complete within pediatric rehabilitation settings.

Methods: A descriptive analysis on completeness of EHR-based DDEs detailing physical functioning for children with cerebral palsy was conducted. Data from an existing pediatric rehabilitation research learning health system data network, consisting of EHR data from 20 care sites in a pediatric specialty health care system, were leveraged.

Should electronic differential diagnosis support be used early or late in the diagnostic process? A multicentre experimental study of Isabel.

Background: Diagnostic errors unfortunately remain common. Electronic differential diagnostic support (EDS) systems may help, but it is unclear when and how they ought to be integrated into the diagnostic process.

Objective: To explore how much EDS improves diagnostic accuracy, and whether EDS should be used early or late in the diagnostic process.

Improving diagnostic performance through feedback: the Diagnosis Learning Cycle.

Background: Errors in reasoning are a common cause of diagnostic error. However, it is difficult to improve performance partly because providers receive little feedback on diagnostic performance. Examining means of providing consistent feedback and enabling continuous improvement may provide novel insights for diagnostic performance.

Addressing the Covid-19 pandemic and future public health challenges through global collaboration and a data-driven systems approach.

Covid-19 has already taught us that the greatest public health challenges of our generation will show no respect for national boundaries, will impact lives and health of people of all nations, and will affect economies and quality of life in unprecedented ways. The types of rapid learning envisioned to address Covid-19 and future public health crises require a systems approach that enables sharing of data and lessons learned at scale. Agreement on a systems approach augmented by technology and standards will be foundational to making such learning meaningful and to ensuring its scientific integrity.

Use of electronic health records to support a public health response to the COVID-19 pandemic in the United States: a perspective from 15 academic medical centers.

Our goal is to summarize the collective experience of 15 organizations in dealing with uncoordinated efforts that result in unnecessary delays in understanding, predicting, preparing for, containing, and mitigating the COVID-19 pandemic in the US. Response efforts involve the collection and analysis of data corresponding to healthcare organizations, public health departments, socioeconomic indicators, as well as additional signals collected directly from individuals and communities. We focused on electronic health record (EHR) data, since EHRs can be leveraged and scaled to improve clinical care, research, and to inform public health decision-making.

Reconsidering hospital EHR adoption at the dawn of HITECH: implications of the reported 9% adoption of a "basic" EHR.

Objective: In 2009, a prominent national report stated that 9% of US hospitals had adopted a "basic" electronic health record (EHR) system. This statistic was widely cited and became a memetic anchor point for EHR adoption at the dawn of HITECH. However, its calculation relies on specific treatment of the data; alternative approaches may have led to a different sense of US hospitals' EHR adoption and different subsequent public policy.