Design and evaluation of an electronic prospective medication order review system for medication orders in the inpatient setting.

Objectives: Since the 1970s, a plethora of tools have been introduced to support the medication use process. However, automation initiatives to assist pharmacists in prospectively reviewing medication orders are lacking. The review of many medications may be protocolized and implemented in an algorithmic fashion utilizing discrete data from the electronic health record (EHR). This research serves as a proof of concept to evaluate the capability and effectiveness of an electronic prospective medication order review (EPMOR) system compared to pharmacists' review. Materials and methods: A subset of the most frequently verified medication orders were identified for inclusion. A team of clinical pharmacist experts developed best-practice EPMOR criteria. The established criteria were incorporated into conditional logic built within the EHR. Verification outcomes from the pharmacist (human) and EPMOR (automation) were compared. Results: Overall, 13 404 medication orders were included. Of those orders, 13 133 passed pharmacist review, 7388 of which passed EPMOR. A total of 271 medication orders failed pharmacist review due to order modification or discontinuation, 105 of which passed EPMOR. Of the 105 orders, 19 were duplicate orders correctly caught by both EPMOR and pharmacists, but the opposite duplicate order was rejected, 51 orders failed due to scheduling changes. Discussion: This simulation was capable of effectively discriminating and triaging orders. Protocolization and automation of the prospective medication order review process in the EHR appear possible using clinically driven algorithms. Conclusion: Further research is necessary to refine such algorithms to maximize value, improve efficiency, and minimize safety risks in preparation for the implementation of fully automated systems.

Insights from the evaluations of the NIH Centers for Accelerated Innovation and Research Evaluation and Commercialization Hubs programs.

BACKGROUND: The National Institutes of Health launched the NIH Centers for Accelerated Innovation and the Research Evaluation and Commercialization Hubs programs to develop approaches and strategies to promote academic entrepreneurship and translate research discoveries into products and tools to help patients. The two programs collectively funded 11 sites at individual research institutions or consortia of institutions around the United States. Sites provided funding, project management, and coaching to funded investigators and commercialization education programs open to their research communities. METHODS: We implemented an evaluation program that included longitudinal tracking of funded technology development projects and commercialization outcomes; interviews with site teams, funded investigators, and relevant institutional and innovation ecosystem stakeholders and analysis and review of administrative data. RESULTS: As of May 2021, interim results for 366 funded projects show that technologies have received nearly $1.7 billion in follow-on funding to-date. There were 88 start-ups formed, a 40% Small Business Innovation Research/Small Business Technology Transfer application success rate, and 17 licenses with small and large businesses. Twelve technologies are currently in clinical testing and three are on the market. CONCLUSIONS: Best practices used by the sites included leadership teams using milestone-based project management, external advisory boards that evaluated funding applications for commercial merit as well as scientific, sustained engagement with the academic community about commercialization in an effort to shift attitudes about commercialization, application processes synced with education programs, and the provision of project managers with private-sector product development expertise to coach funded investigators.

Rheology and microstructure of polymer nanocomposite melts: variation of polymer segment-surface interaction.

We have studied the effects of particle packing fraction, polymer molecular weight (MW), and polymer-segment-particle-surface affinity on the phase behavior of 44 nm silica dispersions in unentangled, low MW polyethylene oxide (PEO), polyethylene oxide dimethyl ether (PEODME), and polytetrahydrofuran (PTHF) through rheological measurement and small-angle X-ray scattering. Particles are shown to be stable in PEO nanocomposites up to high volume fractions due to an adsorbed layer of polymer segments that stabilizes particles in the melt. Comparison of the PEO nanocomposite to PEODME and PTHF nanocomposites reveals little evidence of an adsorbed layer in the spirit of the PEO nanocomposite. Measurement of the PTHF nanocomposite viscosity reveals evidence of segment slip at the particle surface by the particle intrinsic viscosity being less than Einstein's value. At higher particle volume fractions, the viscosity diverges, yielding an elastic response. The elastic response of the PEO nanocomposite has the signatures of a colloidal glass, while the PEODME and PTHF nanocomposites resemble a gel. Measurement of the particle structure factor reveals a change from overall repulsive particles in PEO to attractive particles in PTHF as the segment-surface interaction is changed.

Colloidal glass transition in unentangled polymer nanocomposite melts.

The linear and non-linear rheology of a high volume fraction particle filled unentangled polymer melt is measured. The particles in the polymer melt behave like hard spheres as the particle volume fraction is raised. At high volume fractions, the suspension develops a plateau elastic modulus. Over the frequency range of the elastic modulus plateau, the viscous modulus develops a minimum and a maximum. The frequencies of the two local extrema initially have critical power law scaling, suggesting the approach of a singular glass transition. At higher volume fractions in excess of the glass transition, the viscous modulus continues to show a well defined minimum and a well defined maximum. The non-linear moduli show a single perturbative yield point beyond which the suspension softens. The yielding behavior of the nanocomposite is shown to be sensitive to the strain frequency and the proximity of the strain frequency to the maximum frequency for the linear viscous modulus from linear rheology which characterizes thermal relaxation of glassy particle clusters in the zero strain limit. The linear and non-linear measurements are compared against a recently developed mechanical theory for colloidal glasses.