DOES INFORMATION TECHNOLOGY INCREASE OR DECREASE HOSPITALS’ RISK? AN EMPIRICAL EXAMINATION OF COMPUTERIZED PHYSICIAN ORDER ENTRY AND MALPRACTICE CLAIMS

Information technology (IT) has significant potential to improve the quality of patient care, to lower costs, and to improve efficiency. However, IT leaves an electronic paper trail that may demonstrate negligence and thereby create legal risk. Emerging research suggests that this fear of electronic discovery is delaying IT adoption, thereby perpetuating inefficiencies. Is this fear founded? If it is, then policy changes are needed to remove this obstacle to streamlining the healthcare system. If not, then healthcare providers should move ahead to realize IT benefits without being stymied by irrational fears. We examined the relationship between Computerized Physician Order Entry (CPOE) and malpractice claims against hospitals in Florida between 1999 and 2006. CPOE reduces the number, severity, and disposition time of claims, while having no effect on the amounts paid. This indicates that CPOE reduces hospital legal risk, suggesting that fears of increased legal risk due to IT are unfounded

A research agenda to support the development and implementation of genomics-based clinical informatics tools and resources.

OBJECTIVE: The Genomic Medicine Working Group of the National Advisory Council for Human Genome Research virtually hosted its 13th genomic medicine meeting titled Developing a Clinical Genomic Informatics Research Agenda . The meeting\u27s goal was to articulate a research strategy to develop Genomics-based Clinical Informatics Tools and Resources (GCIT) to improve the detection, treatment, and reporting of genetic disorders in clinical settings. MATERIALS AND METHODS: Experts from government agencies, the private sector, and academia in genomic medicine and clinical informatics were invited to address the meeting\u27s goals. Invitees were also asked to complete a survey to assess important considerations needed to develop a genomic-based clinical informatics research strategy. RESULTS: Outcomes from the meeting included identifying short-term research needs, such as designing and implementing standards-based interfaces between laboratory information systems and electronic health records, as well as long-term projects, such as identifying and addressing barriers related to the establishment and implementation of genomic data exchange systems that, in turn, the research community could help address. DISCUSSION: Discussions centered on identifying gaps and barriers that impede the use of GCIT in genomic medicine. Emergent themes from the meeting included developing an implementation science framework, defining a value proposition for all stakeholders, fostering engagement with patients and partners to develop applications under patient control, promoting the use of relevant clinical workflows in research, and lowering related barriers to regulatory processes. Another key theme was recognizing pervasive biases in data and information systems, algorithms, access, value, and knowledge repositories and identifying ways to resolve them

Inverting the model of genomics data sharing with the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space

The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL; https://anvilproject.org) was developed to address a widespread community need for a unified computing environment for genomics data storage, management, and analysis. In this perspective, we present AnVIL, describe its ecosystem and interoperability with other platforms, and highlight how this platform and associated initiatives contribute to improved genomic data sharing efforts. The AnVIL is a federated cloud platform designed to manage and store genomics and related data, enable population-scale analysis, and facilitate collaboration through the sharing of data, code, and analysis results. By inverting the traditional model of data sharing, the AnVIL eliminates the need for data movement while also adding security measures for active threat detection and monitoring and provides scalable, shared computing resources for any researcher. We describe the core data management and analysis components of the AnVIL, which currently consists of Terra, Gen3, Galaxy, RStudio/Bioconductor, Dockstore, and Jupyter, and describe several flagship genomics datasets available within the AnVIL. We continue to extend and innovate the AnVIL ecosystem by implementing new capabilities, including mechanisms for interoperability and responsible data sharing, while streamlining access management. The AnVIL opens many new opportunities for analysis, collaboration, and data sharing that are needed to drive research and to make discoveries through the joint analysis of hundreds of thousands to millions of genomes along with associated clinical and molecular data types

Can Improvements to Mobile Internet Service Help Address Digital Inequality and the Homework Gap? An Empirical Analysis

Good internet access is critical to participating in contemporary society. Unfortunately, many households - particularly those of low socioeconomic status and/or those in rural areas - do not have good internet access. Some have no access at all, while others are reliant on their mobile data plans for internet access, i.e., they are “smartphone dependent”. This generates inequality in internet access and creates the “homework gap,” which results from some children lacking the internet access necessary to complete schoolwork at home. Given the smartphone dependence of many disadvantaged households, we explore whether improvements to mobile internet service can help address digital inequality and the homework gap. We focus on a specific improvement: access to unlimited mobile data. For access to unlimited data to help close the gaps, it must generate larger gains for disadvantaged households than for advantaged ones. It is not obvious that this will be the case. Accordingly, we use detailed subscriber-level data from a major telecommunications firm to examine changes in the consumption of educational (and other) content after subscribers switch to unlimited mobile data plans. We find that although all subscribers increase their consumption, the increases are significantly larger for disadvantaged subscribers. This indicates that allowing access to unlimited mobile data is likely to be an effective way to address digital inequality and the homework gap

Can Improvements to Mobile Internet Service Help Address Digital Inequality and the Homework Gap? An Empirical Analysis

Good internet access is critical to participating in contemporary society. Unfortunately, many households - particularly those of low socioeconomic status and/or those in rural areas - do not have good internet access. Some have no access at all, while others are reliant on their mobile data plans for internet access, i.e., they are “smartphone dependent”. This generates inequality in internet access and creates the “homework gap,” which results from some children lacking the internet access necessary to complete schoolwork at home. Given the smartphone dependence of many disadvantaged households, we explore whether improvements to mobile internet service can help address digital inequality and the homework gap. We focus on a specific improvement: access to unlimited mobile data. For access to unlimited data to help close the gaps, it must generate larger gains for disadvantaged households than for advantaged ones. It is not obvious that this will be the case. Accordingly, we use detailed subscriber-level data from a major telecommunications firm to examine changes in the consumption of educational (and other) content after subscribers switch to unlimited mobile data plans. We find that although all subscribers increase their consumption, the increases are significantly larger for disadvantaged subscribers. This indicates that allowing access to unlimited mobile data is likely to be an effective way to address digital inequality and the homework gap

Significant Mortality Associated With COVID-19 and Comorbid Cerebrovascular Disease: A Quantitative Systematic Review

We report the first quantitative systematic review of cerebrovascular disease in coronavirus disease 2019 (COVID-19) to provide occurrence rates and associated mortality. Through a comprehensive search of PubMed we identified 8 cohort studies, 5 case series, and 2 case reports of acute cerebrovascular disease in patients with confirmed COVID-19 diagnosis. Our first meta-analysis utilizing the identified publications focused on comorbid cerebrovascular disease in recovered and deceased patients with COVID-19. We performed 3 additional meta-analyses of proportions to produce point estimates of the mortality and incidence of acute cerebrovascular disease in COVID-19 patients. Patient\u27s with COVID-19 who died were 12.6 times more likely to have a history of cerebrovascular disease. We estimated an occurrence rate of 2.6% (95% confidence interval, 1.2-5.4%) for acute cerebrovascular disease among consecutively admitted patients with COVID-19. While for those with severe COVID-19\u27 we estimated an occurrence rate of 6.5% (95% confidence interval, 4.4-9.6%). Our analysis estimated a rate of 35.5% for in-hospital mortality among COVID-19 patients with concomitant acute cerebrovascular disease. This was consistent with a mortality rate of 34.0% which we obtained through an individual patient analysis of 47 patients derived from all available case reports and case series. COVID-19 patients with either acute or chronic cerebrovascular disease have a high mortality rate with higher occurrence of cerebrovascular disease in patients with severe COVID-19