An electronic health record metadata-mining approach to identifying patient-level interprofessional clinician teams in the intensive care unit.

Objectives: Advances in health informatics rapidly expanded use of big-data analytics and electronic health records (EHR) by clinical researchers seeking to optimize interprofessional ICU team care. This study developed and validated a program for extracting interprofessional teams assigned to each patient each shift from EHR event logs.

Materials And Methods: A retrospective analysis of EHR event logs for mechanically-ventilated patients 18 and older from 5 ICUs in an academic medical center during 1/1/2018-12/31/2019.

How Artificial Intelligence is altering the nursing workforce.

This paper focuses on the implications of Artificial Intelligence (AI) for the nursing workforce, examining both the opportunities presented by AI in relieving nurses of routine tasks and enabling better patient care, and the potential challenges it poses. The discussion highlights the freeing of nurses' time from administrative duties, allowing for more patient interaction and professional development, while also acknowledging concerns about job displacement. Ethically integrating AI into patient care and the need for nurses' proactive engagement with AI-including involvement in its development and integration in nursing education-are emphasized.

The Nursing Human Capital Value Model.

Nursing's economic value is presently framed within the dominant "outcomes-over-cost" value framework. Within this context, organizations employing nurses often use nursing budget reductions as a cost-minimization strategy, with the intent of retaining high quality outcomes. However, persistent issues such as nurse understaffing, burnout, and turnover threaten healthcare systems' capacity to deliver the quality, equitable, affordable patient care that the public requires.

Patterns of interactions among ICU interprofessional teams: A prospective patient-shift-level survey approach.

Background: The Awakening, Breathing Coordination, Delirium monitoring and Early mobility bundle (ABCDE) is associated with lower mortality for intensive care unit (ICU) patients. However, efforts to improve ABCDE are variably successful, possibly due to lack of clarity about who are the team members interacting when caring for each patient, each shift. Lack of patient shift-level information regarding who is interacting with whom limits the ability to tailor interventions to the specific ICU team to improve ABCDE.

Shift-Level Team Familiarity Is Associated with Improved Outcomes in Mechanically Ventilated Adults.

Organizing ICU interprofessional teams is a high priority because of workforce needs, but the role of interprofessional familiarity remains unexplored. Determine if mechanically ventilated patients cared for by teams with greater familiarity have improved outcomes, such as lower mortality, shorter duration of mechanical ventilation (MV), and greater spontaneous breathing trial (SBT) implementation. We used electronic health records data of five ICUs in an academic medical center to map interprofessional teams and their ICU networks, measuring team familiarity as network coreness and mean team value.

It's Time! The Path for Nursing Reimbursement Reform.

Since the COVID-19 pandemic, nurses and nurse leaders are increasingly vocal about chronic understaffing and the impact the staffing crisis continues to have on nurses' well-being and patient outcomes. The American Nurses Association's Nurse Staffing Task Force addressed the importance of staffing standards as a critically needed step toward improving patient and population health outcomes. Against the backdrop of ongoing nursing shortages, hospital leaders have been hesitant to embrace staffing ratios, expressing concerns about their ability to hire and retain sufficient nursing staff, as operational revenue margins remain thin and nursing labor is costly.

Racial and Ethnic Disparities in Home Health Referral Among Adult Medicare Patients.

Background: Home health care (HHC) services following hospital discharge provide essential continuity of care to mitigate risks of posthospitalization adverse outcomes and readmissions, yet patients from racial and ethnic minority groups are less likely to receive HHC visits.

Objective: To examine how the association of nurse assessments of patients' readiness for discharge with referral to HHC services at the time of hospital discharge differs by race and ethnic minority group.

Research Design: Secondary data analysis from a multisite study of the implementation of discharge readiness assessments in 31 US hospitals (READI Randomized Clinical Trial: 09/15/2014-03/31/2017), using linear and logistic models adjusted for patient demographic/clinical characteristics and hospital fixed effects.

Using machine-learning methods to predict in-hospital mortality through the Elixhauser index: A Medicare data analysis.

Accurate in-hospital mortality prediction can reflect the prognosis of patients, help guide allocation of clinical resources, and help clinicians make the right care decisions. There are limitations to using traditional logistic regression models when assessing the model performance of comorbidity measures to predict in-hospital mortality. Meanwhile, the use of novel machine-learning methods is growing rapidly.

Part 6. Education for value-informed nursing practice.

With the ongoing transition to value-based health care, a strong command of foundational economic concepts, like cost and value, and the ability to thoughtfully engage in value-informed nursing practice have become essential for the future of the nursing profession. Earlier in this six-part series, we explained value-informed nursing practice, its historical, economic, and ethical foundation, its promise for an environmentally responsible, innovation-driven future health care, and why its adoption requires a reframing of some of the nursing's professional norms and behaviors. This paper concludes the series with one of the most important issues-education for value-informed nursing practice.

Part 4: Value-informed nursing practice depends on nursing innovation.

With the adoption of value-based payments which tie reimbursement to patient outcomes and costs, days when nursing is viewed primarily as a cost to hospitals will soon be over. Already the backbone of high-quality care delivery and patient outcomes, nurses are becoming key drivers of health care organizations' financial outcomes, too. The first three articles published in this 6-part series on value-informed nursing practice-practice that considers both the outcomes and the cost of producing the outcomes-described what value-informed nursing practice means, its economic, policy, and ethical impetuses, and how value-informed nursing practice helps improve environmental sustainability of health systems.

Healthy Lifetime : An Internet-Based Behavioral Health Coaching Protocol for Older Adults.

By 2060, the number of Americans 65 years and older will more than double, comprising nearly one-quarter of the population in the United States. While there are many advantages to living longer, a byproduct of aging is also a growing incidence of chronic illness and functional health limitations associated with a concurrent rise in chronic disease and disability that impair independent living in the community. We describe a personalized, behavioral health coaching protocol for early intervention that is delivered online to enhance a participant's independent functioning and to increase their self-care capacity with a goal to maintain independent living throughout aging.

Value-informed nursing practice is needed to make our healthcare systems more environmentally sustainable.

In this 3rd part of our 6-part series on value-informed nursing practice-practice that focuses on both achieving desired patient outcomes and minimizing the use of costly resources to achieve these outcomes-we focus on the importance of nurses in improving environmental outcomes and reducing costly environmental waste. We also propose how nursing education needs to change to prepare the next generation of nurses to effectively address environmental problems through providing value-informed nursing practice.

Value-informed nursing practice: What is it and how to make it a reality.

Nurses make decisions about the use of costly resources in countless care delivery settings 24 hours a day. Consequently, nurses are inseparably connected to not only the quality and safety of care, but to the cost-of-care as well. This article is Part 1 of a 6-part series on value-informed nursing practice.

Lives saved and lost in the first six month of the US COVID-19 pandemic: A retrospective cost-benefit analysis.

In the beginning of the COVID-19 US epidemic in March 2020, sweeping lockdowns and other aggressive measures were put in place and retained in many states until end of August of 2020; the ensuing economic downturn has led many to question the wisdom of the early COVID-19 policy measures in the US. This study's objective was to evaluate the cost and benefit of the US COVID-19-mitigating policy intervention during the first six month of the pandemic in terms of COVID-19 mortality potentially averted, versus mortality potentially attributable to the economic downturn. We conducted a synthesis-based retrospective cost-benefit analysis of the full complex of US federal, state, and local COVID-19-mitigating measures, including lockdowns and all other COVID-19-mitigating measures, against the counterfactual scenario involving no public health intervention.

The Effect of Reduced Access to Chiropractic Care on Medical Service Use for Spine Conditions Among Older Adults.

Objective: The purpose of this study was to examine the extent to which access to chiropractic care affects medical service use among older adults with spine conditions.

Methods: We used Medicare claims data to identify a cohort of 39,278 older adult chiropractic care users who relocated during 2010-2014 and thus experienced a change in geographic access to chiropractic care. National Plan and Provider Enumeration System data were used to determine chiropractor per population ratios across the United States.

Nonlinear association of nurse staffing and readmissions uncovered in machine learning analysis.

Objective: Several studies of nurse staffing and patient outcomes found a curvilinear or U-shaped relationship, with benefits from additional nurse staffing diminishing or reversing at high staffing levels. This study examined potential diminishing returns to nurse staffing and the existence of a "tipping point" or the level of staffing after which higher nurse staffing no longer improves and may worsen readmissions.

Data Sources/study Setting: The Readiness Evaluation And Discharge Interventions (READI) study database of over 130,000 adult (18+) inpatient discharges from 62 medical, surgical, and medical-surgical (noncritical care) units from 31 United States (US) hospitals during October 2014-March 2017.