Fournierbenton3017
Hydroxyl groups can dehydrogenate to form short and strong chelation bonds with the Fe2O3 countersurface. A friction-induced oriented molecular layer plays a key role in reducing friction, which is responsible for the excellent lubrication property. By varying temperatures in the range of 10-300 K, we found a nonmonotonic change in friction with a maxima at 100 K. At cryogenic temperatures, the molecular mobility was obviously suppressed, while the chain rigidity was enhanced, resulting in the less oriented interface and brittle-like shear interface, which is responsible for nonmonotonic friction. This work elucidates mechanisms of tribochemical reactions and transfer film formation between iron and PTFE at the atomistic level, facilitating design and development of self-lubricating materials, especially under harsh conditions.
To assess the ability of accountable care organizations (ACOs) to use electronic health record (EHR) data for quality.
Cross-sectional study of ACOs participating in the Medicare Shared Savings Program(MSSP).
A national survey of MSSP ACOs included questions on the number of EHR systems used across all providers in the ACO and barriers to reporting EHR-based quality measures.
Just 9% of ACOs use a single EHR system, whereas 77% use 6 or more EHR systems. The more EHR systems an ACO uses, the less likely it is to report having the infrastructure to aggregate EHR data and the more concerned it is about the short-term viability and accuracy of EHR-based quality measures.
ACOs have diverse structures that often result in the usage of multiple EHR systems. This has the potential to cause serious delays when CMS begins requiring ACOs to report their quality measures through their EHRs in2022.
ACOs have diverse structures that often result in the usage of multiple EHR systems. This has the potential to cause serious delays when CMS begins requiring ACOs to report their quality measures through their EHRs in 2022.
To develop a text analytics methodology to analyze in a refined manner the drivers of primary care physicians' (PCPs') electronic health record (EHR) inboxwork.
This study used 1 year (2018) of EHR inbox messages obtained from the Epic system for 184 PCPs from 18 practices.
An advanced text analytics latent Dirichlet allocation model was trained on physicians' inbox message texts to identify the different work themes managed by physicians and their relative share of workload across physicians and clinics.
The text analytics model identified 30 different work themes rolled up into 2 categories of medical and administrative tasks. We found that 50.8% (range across physicians, 34.5%-61.9%) of the messages were concerned with medical issues and 34.1% (range, 23.0%-48.9%) focused on administrative matters. More specifically, 13.6% (range, 7.1%-22.6%) of the messages involved ambiguous diagnosis issues, 13.2% (range, 6.9%-18.8%) involved condition management issues, 6.7% (range, 1.9%-13.4%) involved identifity of care, as well as staff work satisfaction.
Computable social risk factor phenotypes derived from routinely collected structured electronic health record (EHR) or health information exchange (HIE) data may represent a feasible and robust approach to measuring social factors. This study convened an expert panel to identify and assess the quality of individual EHR and HIE structured data elements that could be used as components in future computable social risk factor phenotypes.
Technical expert panel.
A 2-round Delphi technique included 17experts with an in-depth knowledge of available EHR and/or HIE data. The first-round identification sessions followed a nominal group approach to generate candidate data elements that may relate to socioeconomics, cultural context, social relationships, and community context. In the second-round survey, panelists rated each data element according to overall data quality and likelihood of systematic differences in quality across populations (ie, bias).
Panelists identified a total of 89 structured data elements. About half of the data elements (n = 45) were related to socioeconomic characteristics. The panelists identified a diverse set of data elements. HDAC activity assay Elements used in reimbursement-related processes were generally rated as higher quality. Panelists noted that several data elements may be subject to implicit bias or reflect biased systems of care, which may limit their utility in measuring social factors.
Routinely collected structured data within EHR and HIE systems may reflect patient social risk factors. Identifying and assessing available data elements serves as a foundational step toward developing future computable social factor phenotypes.
Routinely collected structured data within EHR and HIE systems may reflect patient social risk factors. Identifying and assessing available data elements serves as a foundational step toward developing future computable social factor phenotypes.
First, to assess whether hospitals expand the network breadth of their health information exchange (HIE) partners after joining an accountable care organization (ACO). Second, to analyze whether this HIE network expansion effect varies across markets with differing levels of ACO penetration.
Difference-in-differences analyses of US nonfederal acute care hospitals, 2014-2017.
We used data from the American Hospital Association Annual Survey and Information Technology Supplement to measure hospital ACO participation, HIE network breadth (defined as number of different partner types), and ACO market penetration at the hospital referral region level. We implemented a difference-in-differences model to estimate changes in hospitals' HIE network breadth with ACO participation in different years. We estimate these effects combined across all markets and stratified by markets with high and low ACO market penetration.
In combined analyses, HIE breadth increased by 0.35 partner types with ACO participation, a 3h-ACO penetration markets and smaller, delayed effects in low-ACO penetration markets.
To determine the degree of telemedicine expansion overall and across patient subpopulations and diagnoses. We hypothesized that telemedicine visits would increase substantially due to the need for continuity of care despite the disruptive effects of COVID-19.
A retrospective study of health insurance claims for telemedicine visits from January 1, 2018, through March 10, 2020 (prepandemic period), and March 11, 2020, through October 31, 2020 (pandemic period).
We analyzed claims from 1,589,777 telemedicine visits that were submitted to Independence Blue Cross (Independence) from telemedicine-only providers and providers who traditionally deliver care in person. The primary exposure was the combination of individual behavior changes, state stay-at-home orders, and the Independence expansion of billing policies for telemedicine. The comparison population consisted of telemedicine visits in the prepandemic period.
Telemedicine increased rapidly from a mean (SD) of 773 (155) weekly visits in prepandemic 20uggest that telemedicine will likely play a key role in postpandemic care delivery.During a surge of COVID-19 cases, the majority of care delivery at a large academic medical center moved to virtual care. Due to COVID-19-associated regulatory changes, virtual care is now delivered through telephone and videoconferencing platforms. Although virtual platforms allow patients to access care while socially distancing, patients with limited English proficiency (LEP) face structural barriers to these platforms, including lack of access to technology, need for medical interpreters, unfriendly patient portals, and increased privacy concerns. Strategies for increasing access to virtual platforms and technology for patients with LEP included offering patient education in multiple languages, reducing barriers to patient portal enrollment, and addressing the technology literacy gap through the use of tablets and bilingual interns. Strategies for addressing privacy concerns for patients with LEP included developing a low-literacy script and other actions that address patient concerns about Immigration and Customs Enforcement and mitigate perceived risk, as well as identifying a virtual platform that meets privacy regulations and does not require a patient to download an application to their phone or computer to join. Strategies for integrating medical interpreters into virtual visits included assessing existing virtual platforms for the ability to host a third party, changing the electronic health record software (Epic) interface, and convening directors of interpreter departments at each site to ensure comprehensive system rollout. Health care organizations that rely heavily on virtual visits to provide patient care will need to take all these challenges into consideration for patients with LEP.
Patient portals are health information technology tools that offer patients access to their personal health information and a means to communicate with health care providers, but little is known about their impact on patient satisfaction. Identifying factors that increase patient satisfaction may improve patient care and can protect health care providers from financial penalties. Our study sought to investigate how patient portals are associated with patient satisfaction in both inpatient and outpatient settings.
Retrospective, pooled cross-sectional study.
Data from the Clinician and Group Consumer Assessment of Healthcare Providers and Systems (CG-CAHPS) and Hospital CAHPS (HCAHPS) patient satisfaction surveys were linked to inpatient and outpatient portal account status at a large academic medical center. Using fractional logistic regression, we investigated the relationship between patient satisfaction survey scores and patient portal activation.
Patients with an activated outpatient portal account-centeredness of care. Our findings indicate important considerations for both health care organizations and their patients to promote patient portal use as a means of improving patient satisfaction, especially in the context of potential impacts on reimbursement and reputation.
As predictive analytics are increasingly used and developed by health care systems, recognition of the threat posed by bias has grown along with concerns about how providers can make informed decisions related to predictive models. To facilitate informed decision-making around the use of these models and limit the reification of bias, this study aimed to (1) identify user requirements for informed decision-making and utilization of predictive models and (2) anticipate and reflect equity concerns in the information provided about models.
Qualitative analysis of user-centered design (n = 46) and expert interviews (n = 10).
We conducted a user-centered design study at an academic medical center with clinicians and stakeholders to identify informational elements required for decision-making related to predictive models with a product information label prototype. We also conducted equity-focused interviews with experts to extend the user design study and anticipate the ways in which models could interact witfrom inception through the model development process.
