Impact of Analytics Applying Artificial Intelligence and Machine Learning on Enhancing Intensive Care Unit: A Narrative Review

Introduction. The intensive care unit (ICU) plays a pivotal role in providing specialized care to patients with severe illnesses or injuries. As a critical aspect of healthcare, ICU admissions demand immediate attention and skilled care from healthcare professionals. However, the intricacies involved in this process necessitate analytical solutions to ensure effective management and optimal patient outcomes. Aim. The aim of this review was to highlight the enhancement of the ICUs through the application of analytics, artificial intelligence, and machine learning. Methods. The review approach was carried out through databases such as MEDLINE, Embase, Web of Science, Scopus, Taylor & Francis, Sage, ProQuest, Science Direct, CINAHL, and Google Scholar. These databases were chosen due to their potential to offer pertinent and comprehensive coverage of the topic while reducing the likelihood of overlooking certain publications. The studies for this review involved the period from 2016 to 2023. Results. Artificial intelligence and machine learning have been instrumental in benchmarking and identifying effective practices to enhance ICU care. These advanced technologies have demonstrated significant improvements in various aspects. Conclusions. Artificial intelligence, machine learning, and data analysis techniques significantly improved critical care, patient outcomes, and healthcare delivery

Emergency Department Management: Data Analytics for Improving Productivity and Patient Experience

The onset of big data, typically defined by its volume, velocity, and variety, is transforming the healthcare industry. This research utilizes data corresponding to over 23 million emergency department (ED) visits between January 2010 and December 2017 which were treated by physicians and advanced practice providers from a large national emergency physician group. This group has provided ED services to health systems for several years, and each essay aims to address operational challenges faced by this group’s management team. The first essay focuses on physician performance. We question how to evaluate performance across multiple sites and work to understand the relationships between patient flow, patient complexity, and patient experience. Specifically, an evaluation system to assess physician performance across multiple facilities is proposed, the relationship between productivity and patient experience scores is explored, and the drivers of patient flow and complexity are simultaneously identified. The second essay explores the relationship between physician performance and malpractice claims as we investigate whether physicians’ practice patterns change after they are named in a malpractice lawsuit. Overall, the results of this analysis indicate that the likelihood of being named in a malpractice claim is largely a function of how long a physician has practiced. Furthermore, physician practice patterns remain consistent after a physician is sued, but patient experience scores increase among sued physicians after the lawsuit is filed. Such insights are beneficial for management as they address the issue of medical malpractice claims. The final essay takes a closer look at the relationship between advanced practice providers (APPs) and physicians. Can EDs better utilize APPs to reduce waiting times and improve patient flow? A systematic data-driven approach which incorporates descriptive, predictive, and prescriptive analyses is employed to provide recommendations for ED provider staffing practices

Linking EMR to Virtual Care of Psychiatric Patients in the Acute Care Setting

The purpose of this study is to test if the implementation of the Tele-Psychiatric Consultation Process (built within the FirstNet (Cerner/EMR) application, which pulls the patient’s current EMR encounter from multiple facility locations to a different physical facility location for consultation) provided increased quality by decreasing in total length of stay. The coordination of virtual care consultations allows for inter-practice data exchange for multi-provider clinical decision support. Documentation of medications and treatment regimens, which may be unfamiliar to the acute care provider, are provided through virtual tele-psychiatric consultations. An eTracking queue within FirstNet was built in-house by Carolinas Healthcare System to bridge the gap by integrating separate dual processes from fourteen emergency departments and behavioral health centers to better coordinate the flow of patient care. This study will examine if the transaction of data and information by this FirstNet (EMR) enhancement of system processes results in a decrease in patient length of stay as an indicator of improvement in quality of care

Data Science Methods for Nursing-Relevant Patient Outcomes and Clinical Processes The 2019 Literature Year in Review

Data science continues to be recognized and used within healthcare due to the increased availability of large data sets and advanced analytics. It can be challenging for nurse leaders to remain apprised of this rapidly changing landscape. In this article, we describe our findings from a scoping literature review of papers published in 2019 that use data science to explore, explain, and/or predict 15 phenomena of interest to nurses. Fourteen of the 15 phenomena were associated with at least one paper published in 2019. We identified the use of many contemporary data science methods (eg, natural language processing, neural networks) for many of the outcomes. We found many studies exploring Readmissions and Pressure Injuries. The topics of Artificial Intelligence/Machine Learning Acceptance, Burnout, Patient Safety, and Unit Culture were poorly represented. We hope that the studies described in this article help readers: (1) understand the breadth and depth of data science\u27s ability to improve clinical processes and patient outcomes that are relevant to nurses and (2) identify gaps in the literature that are in need of exploratio

Improving Employee Engagement through the Development of an Enterprise Performance Management System

There is ample evidence of our health care delivery system relying heavily on value-based outcomes. The increased focus on outcomes has required health care organizations to adjust how they approach data and how they successfully implement performance management systems. These performance management systems help the organization identify, measure, and report the organization’s performance at an enterprise level using key performance indicators clearly linked to the organization’s overall strategy. As one organization began implementing an enterprise performance management system, the goal of this project was to show how participating in projects with that level of strategic impact can lead to improved engagement scores

Improving Employee Engagement through the Development of an Enterprise Performance Management System

There is ample evidence of our health care delivery system relying heavily on value-based outcomes. The increased focus on outcomes has required health care organizations to adjust how they approach data and how they successfully implement performance management systems. These performance management systems help the organization identify, measure, and report the organization’s performance at an enterprise level using key performance indicators clearly linked to the organization’s overall strategy. As one organization began implementing an enterprise performance management system, the goal of this project was to show how participating in projects with that level of strategic impact can lead to improved engagement scores

FIT FOR USE ASSESSMENT OF BIOZEN AS A BIOMETRIC SENSOR CONCENTRATOR FOR REMOTE PATIENT MONITORING

In recent years, COVID-19 highlighted the importance of virtual health solutions with regard to improving patient health and conserving valuable hospital resources. Currently, the Defense Health Agency (DHA) does not own a remote patient-monitoring solution and relies on external commercial entities to provide the application and services. This could potentially lead to the DHA not retaining complete data ownership when patient data would reside on or traverse through commercial remote patient-monitoring solutions. This thesis evaluates BioZen, a DHA-owned biomedical sensor concentrator designed to run on a mobile phone, as a remote patient-monitoring tool. From this analysis, several key measures of effectiveness and measures of performance for remote patient-monitoring tools are identified and operationalized to measure the overall value BioZen brings to the DHA. Based on this research, it was found that the current build of BioZen, 2.0.0, is unable to meet any of the measures outlined in the study as a remote patient-monitoring tool. A future build of BioZen, or any remote patient-monitoring tool, could then be assessed using the measures of effectiveness and measures of performance within this study to determine the overall value brought to the DHA.Defense Health Agency, 7700 Arlington Boulevard, Falls Church, VA 22042Captain, United States ArmyLieutenant, United States NavyApproved for public release. Distribution is unlimited