Objective: Hospital at Home (HaH) programs currently lack decision support tools to help efficiently navigate the complex decision-making process surrounding HaH as a care option. We assessed user needs and perspectives to guide early prototyping and co-creation of 4PACS (Partnering Patients and Providers for Personalized Acute Care Selection), a decision support app to help patients make an informed decision when presented with discrete hospitalization options.
Methods: From December 2021 to January 2022, we conducted semi-structured interviews via telephone with patients and caregivers recruited from Atrium Health's HaH program and physicians and a nurse with experience referring patients to HaH. Interviews were evaluated using thematic analysis. The findings were synthesized to create illustrative user descriptions to aid 4PACS development.
Results: In total, 12 stakeholders participated (3 patients, 2 caregivers, 7 providers [physicians/nurse]). We identified 4 primary themes: attitudes about HaH; 4PACS app content and information needs; barriers to 4PACS implementation; and facilitators to 4PACS implementation. We characterized 3 user descriptions (one per stakeholder group) to support 4PACS design decisions. User needs included patient selection criteria, clear program details, and descriptions of HaH components to inform care expectations. Implementation barriers included conflict between app recommendations and clinical judgement, inability to adequately represent patient-risk profile, and provider burden. Implementation facilitators included ease of use, auto-populating features, and appropriate health literacy.
Conclusions: The findings indicate important information gaps and user needs to help inform 4PACS design and barriers and facilitators to implementing 4PACS in the decision-making process of choosing between hospital-level care options.
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http://dx.doi.org/10.1093/jamiaopen/ooae079 | DOI Listing |
Surg Endosc
December 2024
Cancer Center Amsterdam, Amsterdam, Netherlands.
Background: The surgical management of complicated diverticulitis varies across Europe. EAES members prioritized this topic to be addressed by a clinical practice guideline through an online questionnaire.
Objective: To develop evidence-informed clinical practice recommendations for key stakeholders involved in the treatment of complicated diverticulitis; to improve operative and perioperative outcomes, patient experience and quality of life through a systematic evidence-to-decision approach by a diverse, multidisciplinary panel.
Sci Rep
December 2024
School of Public Administration, Guangzhou University, Guangzhou, 510006, China.
With the accelerated urbanization and economic development in Northwest China, the efficiency of urban wastewater treatment and the importance of water quality management have become increasingly significant. This work aims to explore urban wastewater treatment and carbon reduction mechanisms in Northwest China to alleviate water resource pressure. By utilizing online monitoring data from pilot systems, it conducts an in-depth analysis of the impacts of different wastewater treatment processes on water quality parameters.
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December 2024
Advanced Research Institute for Digital-Twin Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.
Traditional hydraulic structures rely on manual visual inspection for apparent integrity, which is not only time-consuming and labour-intensive but also inefficient. The efficacy of deep learning models is frequently constrained by the size of available data, resulting in limited scalability and flexibility. Furthermore, the paucity of data diversity leads to a singular function of the model that cannot provide comprehensive decision support for improving maintenance measures.
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December 2024
Chongqing Jianzhu College, Chongqing, 400072, China.
Prefabricated construction involves manufacturing components in a factory and then transporting them to a construction site for assembly, yielding resource savings and improved efficiency. However, the large size and weight of prefabricated components, along with strict delivery requirements, introduce logistical challenges, such as increased carbon emissions during transport and site congestion. This study addresses the dual-objective vehicle scheduling problem for prefabricated components.
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December 2024
Department of Computer Sciences and Industries, Universidad Católica del Maule, Talca, Chile.
Antimicrobial resistance (AMR) poses a significant global health challenge, necessitating advanced predictive models to support clinical decision-making. In this study, we explore multi-label classification as a novel approach to predict antibiotic resistance across four clinically relevant bacteria: E. coli, S.
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