209 research outputs found

    An Educational Module on the Benefits of Telehealth Assisted Preanesthetic Evaluations

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    Title An Educational Module on the Benefits of Telehealth Assisted Preanesthetic Evaluations Impact Statement Healthcare systems are always seeking new ways to increase efficiency, save on costs, and provide quality care for their patients. The use of telehealth in the preanesthesia setting is a tool that can help to further improve a healthcare system’s ability to achieve these goals. This project will be a step towards determining the support for and viability of telehealth utilization in the preanesthesia setting. Background/Purpose/Question Surgery cancellations are a significant problem with the potential for far-reaching consequences. Unexpected day-of-surgery cancellations can be costly to both the patient and the health care team. Telemedicine and telehealth are readily available tools for overcoming obstacles to accessing health care. Their use can improve patient outcomes, primarily by reducing the transportation time and costs and increasing the access to physicians. However, there is relatively little data on provider attitudes on the use of telemedicine to reduce cancellations and surgical delays. This project aims to answer: Among anesthesia providers (P), is an educational module designed to improve knowledge of the effectiveness of telehealth-assisted PAE (I), when compared to face-to-face preoperative assessment (C), effective in increasing provider knowledge (O) that leads to an improvement in the quality of patient care, the experience of the patient, its effect on staff, productivity, and cost-savings potential? Methods/Evidence Search Using the keywords listed under “Eligibility Criteria,” a search was conducted on CINAHL. Non-English, non-peer-reviewed articles were eliminated from the search, as well as articles older than 10 years. The same steps were taken with PubMed and Google Scholar. A total of 152 articles were found as potential evidence sources. Sources meeting criteria based on title were 44. Sources meeting criteria based on abstract were 13. Finally, sources meeting criteria based on full text were 8: a systematic literature review, a prospective randomized trial, a case-controlled study, a quasi-experimental study, a retrospective study, 2 descriptive studies, and a mixed methods approach. A total of 7 of the studies were performed in the United Sates while 1 was done in Australia. Synthesis of Literature/Results/Discussion A systematic literature review was conducted by Schoen and Prater. The results of their systematic review found that PAE can be successfully performed using telehealth and that patients also reported satisfaction with utilization of telehealth when performing PAE. For this project, the pre-test and post-test assessed if the educational module enhanced the participants attitude and perception of the use of telehealth during the PAE. The results show that after an educational module was shown, perception of the technology improved. Future research should focus on creating experiments with larger sample sizes and implementing the technology to see what real-world benefits the technology can offer. Conclusions/Recommendations for Practice 4 Telehealth is an increasingly relevant topic in the healthcare industry. It can provide many benefits to both the provider and the consumer. The project shows that presenting the topic and educating providers about the topic can make them more open to using the technology in their practice. Information gained from this project can be used to determine the feasibility of implementing this technology at health care facility where anesthesia providers practice

    From Data to Decision: An Implementation Model for the Use of Evidence-based Medicine, Data Analytics, and Education in Transfusion Medicine Practice

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    Healthcare in the United States is underperforming despite record increases in spending. The causes are as myriad and complex as the suggested solutions. It is increasingly important to carefully assess the appropriateness and cost-effectiveness of treatments especially the most resource-consuming clinical interventions. Healthcare reimbursement models are evolving from fee-for-service to outcome-based payment. The Patient Protection and Affordable Care Act has added new incentives to address some of the cost, quality, and access issues related to healthcare, making the use of healthcare data and evidence-based decision-making essential strategies. However, despite the great promise of these strategies, the transition to data-driven, evidence-based medical practice is complex and faces many challenges. This study aims to bridge the gaps that exist between data, knowledge, and practice in a healthcare setting through the use of a comprehensive framework to address the administrative, cultural, clinical, and technical issues that make the implementation and sustainability of an evidence-based program and utilization of healthcare data so challenging. The study focuses on promoting evidence-based medical practice by leveraging a performance management system, targeted education, and data analytics to improve outcomes and control costs. The framework was implemented and validated in transfusion medicine practice. Transfusion is one of the top ten coded hospital procedures in the United States. Unfortunately, the costs of transfusion are underestimated and the benefits to patients are overestimated. The particular aim of this study was to reduce practice inconsistencies in red blood cell transfusion among hospitalists in a large urban hospital using evidence-based guidelines, a performance management system, recurrent reporting of practice-specific information, focused education, and data analytics in a continuous feedback mechanism to drive appropriate decision-making prior to the decision to transfuse and prior to issuing the blood component. The research in this dissertation provides the foundation for implementation of an integrated framework that proved to be effective in encouraging evidence-based best practices among hospitalists to improve quality and lower costs of care. What follows is a discussion of the essential components of the framework, the results that were achieved and observations relative to next steps a learning healthcare organization would consider

    A big data augmented analytics platform to operationalize efficiencies at community clinics

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    Indiana University-Purdue University Indianapolis (IUPUI)Community Health Centers (CHCs) play a pivotal role in delivery of primary healthcare to the underserved, yet have not benefited from a modern data analytics platform that can support clinical, operational and financial decision making across the continuum of care. This research is based on a systems redesign collaborative of seven CHC organizations spread across Indiana to improve efficiency and access to care. Three research questions (RQs) formed the basis of this research, each of which seeks to address known knowledge gaps in the literature and identify areas for future research in health informatics. The first RQ seeks to understand the information needs to support operations at CHCs and implement an information architecture to support those needs. The second RQ leverages the implemented data infrastructure to evaluate how advanced analytics can guide open access scheduling – a specific use case of this research. Finally, the third RQ seeks to understand how the data can be visualized to support decision making among varying roles in CHCs. Based on the unique work and information flow needs uncovered at these CHCs, an end to-end analytics solution was designed, developed and validated within the framework of a rapid learning health system. The solution comprised of a novel heterogeneous longitudinal clinic data warehouse augmented with big data technologies and dashboard visualizations to inform CHCs regarding operational priorities and to support engagement in the systems redesign initiative. Application of predictive analytics on the health center data guided the implementation of open access scheduling and up to a 15% reduction in the missed appointment rates. Performance measures of importance to specific job profiles within the CHCs were uncovered. This was followed by a user-centered design of an online interactive dashboard to support rapid assessments of care delivery. The impact of the dashboard was assessed over time and formally validated through a usability study involving cognitive task analysis and a system usability scale questionnaire. Wider scale implementation of the data aggregation and analytics platform through regional health information networks could better support a range of health system redesign initiatives in order to address the national ‘triple aim’ of healthcare

    Perioperative Care

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    Perioperative care practices worldwide are in the midst of a seeing change with the implementation of multidisciplinary processes that improve surgical outcomes through (1) better patient education, engagement, and participation; (2) enhanced pre-operative, intra-operative, and post-operative care bundles; and (3) interactive audit programs that provide feedback to the surgical team. These improved outcomes include reductions in the frequency and severity of complications and improved throughput, which ultimately reduce operative stress. Practices in theatre as well as ward are becoming more collaborative and evidence-driven.This book is best utilized by perioperative care team members engaged in quality improvement, collaborative practice, and application of innovations in surgical care

    Exploring occupational therapy’s role in headache & migraine management for women in military aviation fields through a biopsychosocial approach

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    This paper examines the role of occupational therapy in the management of headaches among women in military aviation. Headaches are a common complaint among aviation professions and can significantly impact their performance and their quality of life. Through a comprehensive literature review, this paper highlights the unique challenges faced by women in military aviation fields and the various factors that contribute to the headache experience. This paper explores the benefits of occupational therapy interventions utilizing the biopsychosocial model and the integrated headache model. The interventions are designed to address the musculoskeletal symptoms to include injury remediation and prevention, pain management techniques, manual therapy modalities and ergonomic assessments. Additionally, interventions address behavioral factors that support development of health promoting habits, roles and routines. Interventions may include but are not limited to the management of headache triggers such as sleep and rest, stress management and strategies which impact quality of life and the headache experience. The findings of this paper underscore the importance of occupational therapy in the holistic approach to managing headaches among women in military aviation and it highlights the need for further research in this area

    Applications of Artificial Intelligence in Healthcare

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    Now in these days, artificial intelligence (AI) is playing a major role in healthcare. It has many applications in diagnosis, robotic surgeries, and research, powered by the growing availability of healthcare facts and brisk improvement of analytical techniques. AI is launched in such a way that it has similar knowledge as a human but is more efficient. A robot has the same expertise as a surgeon; even if it takes a longer time for surgery, its sutures, precision, and uniformity are far better than the surgeon, leading to fewer chances of failure. To make all these things possible, AI needs some sets of algorithms. In Artificial Intelligence, there are two key categories: machine learning (ML) and natural language processing (NPL), both of which are necessary to achieve practically any aim in healthcare. The goal of this study is to keep track of current advancements in science, understand technological availability, recognize the enormous power of AI in healthcare, and encourage scientists to use AI in their related fields of research. Discoveries and advancements will continue to push the AI frontier and expand the scope of its applications, with rapid developments expected in the future

    Nurse Initiated Standing Orders: A Process Improvement at an Emergency Department in Interior Alaska

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    Emergency Departments (EDs) are a valuable and limited public health resource. In addition to treating acute medical emergencies, EDs bridge the gaps in urgent care and primary care accessibility, operating twenty-four hours a day, seven days a week, providing care regardless of an individual’s ability to pay. EDs across the country operate at or above capacity regularly, and overcrowding is projected to increase due to decreased facilities and available inpatient beds. Innovative measures are necessary to increase patient throughput and decrease length of stay while maintaining quality care. Nurse initiated standing orders, also known as nurse driven protocols, standing orders, order sets, standardized procedures, triage protocols, etc., initiated by registered nurses prior to a medical assessment by an Emergency Department Physician, Nurse Practitioner, or Physician’s Assistant, are an effective mechanism to reduce length of service

    Comprehensive, Evidence-Based, Consensus Guidelines for Prescription of Opioids for Chronic Non-Cancer Pain from the American Society of Interventional Pain Physicians (ASIPP).

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    BACKGROUND: Opioid prescribing in the United States is decreasing, however, the opioid epidemic is continuing at an uncontrollable rate. Available data show a significant number of opioid deaths, primarily associated with illicit fentanyl use. It is interesting to also note that the data show no clear correlation between opioid prescribing (either number of prescriptions or morphine milligram equivalent [MME] per capita), opioid hospitalizations, and deaths. Furthermore, the data suggest that the 2016 guidelines from the Centers for Disease Control and Prevention (CDC) have resulted in notable problems including increased hospitalizations and mental health disorders due to the lack of appropriate opioid prescribing as well as inaptly rapid tapering or weaning processes. Consequently, when examined in light of other policies and complications caused by COVID-19, a fourth wave of the opioid epidemic has been emerging. OBJECTIVES: In light of this, we herein seek to provide guidance for the prescription of opioids for the management of chronic non-cancer pain. These clinical practice guidelines are based upon a systematic review of both clinical and epidemiological evidence and have been developed by a panel of multidisciplinary experts assessing the quality of the evidence and the strength of recommendations and offer a clear explanation of logical relationships between various care options and health outcomes. METHODS: The methods utilized included the development of objectives and key questions for the various facets of opioid prescribing practice. Also utilized were employment of trustworthy standards, and appropriate disclosures of conflicts of interest(s). The literature pertaining to opioid use, abuse, effectiveness, and adverse consequences was reviewed. The recommendations were developed after the appropriate review of text and questions by a panel of multidisciplinary subject matter experts, who tabulated comments, incorporated changes, and developed focal responses to questions posed. The multidisciplinary panel finalized 20 guideline recommendations for prescription of opioids for chronic non-cancer pain. Summary of the results showed over 90% agreement for the final 20 recommendations with strong consensus. The consensus guidelines included 4 sections specific to opioid therapy with 1) ten recommendations particular to initial steps of opioid therapy; 2) five recommendations for assessment of effectiveness of opioid therapy; 3) three recommendations regarding monitoring adherence and side effects; and 4) two general, final phase recommendations. LIMITATIONS: There is a continued paucity of literature of long-term opioid therapy addressing chronic non-cancer pain. Further, significant biases exist in the preparation of guidelines, which has led to highly variable rules and regulations across various states. CONCLUSION: These guidelines were developed based upon a comprehensive review of the literature, consensus among expert panelists, and in alignment with patient preferences, and shared decision-making so as to improve the long-term pain relief and function in patients with chronic non-cancer pain. Consequently, it was concluded - and herein recommended - that chronic opioid therapy should be provided in low doses with appropriate adherence monitoring and understanding of adverse events only to those patients with a proven medical necessity, and who exhibit stable improvement in both pain relief and activities of daily function, either independently or in conjunction with other modalities of treatments

    Utilizing artificial intelligence in perioperative patient flow:systematic literature review

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    Abstract. The purpose of this thesis was to map the existing landscape of artificial intelligence (AI) applications used in secondary healthcare, with a focus on perioperative care. The goal was to find out what systems have been developed, and how capable they are at controlling perioperative patient flow. The review was guided by the following research question: How is AI currently utilized in patient flow management in the context of perioperative care? This systematic literature review examined the current evidence regarding the use of AI in perioperative patient flow. A comprehensive search was conducted in four databases, resulting in 33 articles meeting the inclusion criteria. Findings demonstrated that AI technologies, such as machine learning (ML) algorithms and predictive analytics tools, have shown somewhat promising outcomes in optimizing perioperative patient flow. Specifically, AI systems have proven effective in predicting surgical case durations, assessing risks, planning treatments, supporting diagnosis, improving bed utilization, reducing cancellations and delays, and enhancing communication and collaboration among healthcare providers. However, several challenges were identified, including the need for accurate and reliable data sources, ethical considerations, and the potential for biased algorithms. Further research is needed to validate and optimize the application of AI in perioperative patient flow. The contribution of this thesis is summarizing the current state of the characteristics of AI application in perioperative patient flow. This systematic literature review provides information about the features of perioperative patient flow and the clinical tasks of AI applications previously identified
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