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Non-conventional in English | National Technical Information Service, Grey literature | ID: grc-753482

ABSTRACT

The Mobility Toolkit (MTK) is a single chest mounted device that utilizes inertial measurement units (IMUs) to assess gait quality. The purpose of this project is to test the implementation of the Mobility Toolkit in multiple trauma centers around the country and generate normative data on lower-extremity injuries common among military and civilian patients. The long-term goal is for this to be a clinical tool for evaluating recovery progress. This study is an important first step in establishing feasibility and in creating a normative set against which patient progress can be measured.

2.
Open Forum Infectious Diseases ; 8(SUPPL 1):S162-S163, 2021.
Article in English | EMBASE | ID: covidwho-1746742

ABSTRACT

Background. Ten percent of adult, outpatient visits result in an antibiotic prescription (Rx). At the start of our intervention, our VA healthcare system consisted of 13 community-based outpatient clinics (CBOCs), 9 of which did not have an onsite pharmacy but utilized automated dispensing cabinets (ADCs) for prepackaged outpatient Rxs. ADC antibiotic orders are generated from electronic medical record (EMR) order sets. The stewardship team shortened the durations of 5 antibiotics in the ADC order sets to make them consistent with current literature and guidelines. We assessed the impact of these changes on antibiotic prescribing habits. Methods. We compared outpatient antibiotic Rx data between 10/1/2018-9/30/2019 (pre-intervention) and 10/1/19-9/30/20 (post-intervention) from 8 CBOCs with ADCs (1 closed during the pandemic). Amoxicillin-clavulanate 875/125mg (AMC), cephalexin 500mg (CPH), levofloxacin 500mg and 750mg (LEV 500 and LEV 750), and sulfamethoxazole-trimethoprim 800/160mg (SXT) prescription durations were all reduced by 3 days. Process metrics included days supplied/1000 prescriptions (DS/1000 Rx), median DS, and ADC utilization rates. We used Mann-Whitney U and correlation statistical analyses to assess differences and associations. Results. The DS/1000 Rx of antibiotics with a default duration change decreased in the post-intervention phase for CBOCs with ADCs (AMC, -25.4%;CPH, -21.1%;LEV 500, -18.9%;LEV 750, -28.0%;SXT, -27.4%). The median DS for these antibiotics all reduced by 3 days in concordance with new ADC prescriptions defaults (AMC, 10 vs 7 days, P< 0.001;CPH, 10 vs 7 days, P< 0.001;LEV 500, 8 vs 5 days, P< 0.001;LEV 750, 8 vs 5 days, P< 0.001;SXT 10 vs 7 days, P< 0.001). Due to COVID-19, 7/8 ADC CBOCs closed for in-person visits from 3/20/20-5/4/20. ADC utilization was inversely proportional to DS/1000 Rx for most antibiotics (R: -0.51 to -0.77) except SXT. Conclusion. EMR-driven reductions in ADC default Rx durations led to a corresponding decrease in overall outpatient antibiotic prescribing. Higher DS/1000 Rx were often associated with lower ADC utilization. Informatics-driven antibiotic interventions may be potential outpatient stewardship tools to increase guideline-concordant prescribing across multisite healthcare systems.

3.
Diabetic Medicine ; 38(SUPPL 1):64, 2021.
Article in English | EMBASE | ID: covidwho-1238378

ABSTRACT

Aim: To adapt and deliver type 2 diabetes structured education online during the covid-19 pandemic. Methods: The covid-19 pandemic and resulting lockdown in March 2020 led to suspension of face-to- face diabetes education. In order to continue to deliver type 2 diabetes structured education we adapted our courses for both newly diagnosed and refresher education such that they could be delivered online. First, a series of videos covering key topics were recorded and posted online. These were advertised to patients and healthcare professionals. Online views showed strong initial interest, but we recognised that patients also needed interactive education. We piloted an approach combining 'flipped classroom' with blended learning. The videos became pre-session 'homework' for a 90-minute Zoom group session, where participants could apply their learning, ask questions, and gain peer support. Sessions were underpinned by behaviour change theory. DVDs were also produced for those without IT access. Results: Feedback was overwhelmingly positive. Participants cited being able to access education from home and not having to use public transport as particular advantages. The length of the session was also popular. Staff reported a positive experience and benefitted from less travel time. The Quality Institute for Self-Management Education & Training (QISMET) evaluation commended our strategy for meeting patient needs and enhancing patient empowerment. Conclusion: We have adapted and delivered QISMET-accredited online structured type 2 diabetes education during the covid-19 pandemic. Uptake has been high and feedback good. We will continue to offer online education as part of our suite of educational options.

4.
Annals of Emergency Medicine ; 76(4):S1-S2, 2020.
Article in English | EMBASE | ID: covidwho-898366

ABSTRACT

Study Objectives: As the number of COVID-19 patients increased across the US, health care systems required a variety of approaches to meet the demand for critical care resources. We sought to determine the ability of the existing health care system to meet these demands and explored the intersection of critical care bed (CCB) capacity and staffing availability in U.S. counties using two-week-ahead projections for April 13th, 2020. Methods: A linear optimization model was developed and solved using the revised simplex method. The model aimed to minimize unmet demand for COVID-19 critical care through an optimal combination of (i) redistribution of nurses and physicians within each state (within 250 miles) and (ii) provision of additional CCB capacity and staff. Staffing ratios of 2 CCBs/nurse and 10 CCBs/physician were applied. Advanced practice practitioners (APPs) were used to “extend” physician coverage with each APP equal to 0.5 physicians. Staffing counts were estimated using American Hospital Association and Health Resources and Services Administration Data. To account for critical care training, 15% of RNs, 12% of NPs, 1.4% of PAs, and 50% of CRNAs were considered as available critical care trained staff. Intensivists (100%) and Medical and Surgical specialists (30%) were included with 45% of these available for hospital staffing. Case count projections were taken from the Columbia University models (Shaman, 2020) and 70% of CCBs in each county were assumed to be occupied by non-COVID-19 patients. For each county, three potential constraints on increasing capacity were estimated: the number of nurses, the number of physicians (including APPs), and the number of CCBs. One or more constraints could be active at any time. Results: Prior to optimization, 91% of counties were able to meet the demand for projected case counts. In contrast, 8.4% were limited by nursing resources, 0.09% by physicians, and 0.8% by the number of CCBs. After optimization, 16.9% of counties sent nurses to a different county(s) (median 6 nurses sent, IQR 13.75) compared with 5.5% counties receiving them (median 23, IQR 43.5). Fewer physicians were relocated (0.09% sent, median 1, IQR 1;0.06% received, median 2.5, IQR 1.5) (Figure). Using baseline staffing ratios and availability, these redistributions led to a reduction in total unmet demand from 24,155 to 19,976. In order to fully meet demand across the US under these conditions, an additional 1,225 physicians, 41,939 nurses and 13,905 CCBs would have been needed. Conclusion: This work shows that with the redeployment of resources even within state boundaries may provide relief to areas of need without causing strain in other locations. While validation with actual redeployment during the pandemic can improve estimates, these models can provide decision support to stakeholders by suggesting optimal reallocation or the ability of existing resources to support additional capacity. [Formula presented]

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