Point of no return: COVID-19 and the U.S. healthcare system: An emergency physician's perspective

When Agency Fails: An Analysis of the Association Between Hospital Agency Staffing and Quality Outcomes

Introduction

Staffing is critical to hospital quality, but recent years have seen hospitals grappling with severe shortages, forcing them to rely on contract or agency staff for urgent patient care needs. This shift in staffing mix has raised questions about its impact on quality. Consequently, this study investigated whether the increased use of agency staff has affected healthcare quality in hospitals. Given the limited recent research on this topic, practitioners remain uncertain about the effectiveness of their staffing strategies and their potential impact on quality.

Methods

Drawing from agency theory, data were obtained from Definitive Healthcare which consolidates information from numerous public access databases pertaining to hospitals such as the American Hospital Association Annual Survey (hospital profile) and the Hospital Value-Based Purchasing Program (quality data). We conducted a cross-sectional study using a multivariable linear regression model (2021-2022) with appropriate organizational and market- level control variables. Quality was measured across eight variables while the independent variable of interest was agency labor cost ratio operationalized as the percentage of net patient revenue consumed by agency labor expense.

Results

Our results suggested that the employment of agency staff was significantly and negatively associated with six of eight quality measures tested, including the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) star rating, Hospital Compare rating, the hospital Total Performance Score (TPS), and three of the four sub-domains that comprise the TPS: clinical domain score, person and community engagement domain score, and the efficiency and cost reduction score.

Discussion

Our results indicated that the increased use of agency labor may have a significant negative influence on quality outcomes at the hospital level. Our findings support the premise that interventions that promote full-time staffing may be more supportive of the quality of care delivered as well as patients' perceptions of care.

An epidemiological modeling framework to inform institutional-level response to infectious disease outbreaks: a Covid-19 case study

Institutions have an enhanced ability to implement tailored mitigation measures during infectious disease outbreaks. However, macro-level predictive models are inefficient for guiding institutional decision-making due to uncertainty in local-level model input parameters. We present an institutional-level modeling toolkit used to inform prediction, resource procurement and allocation, and policy implementation at Clemson University throughout the Covid-19 pandemic. Through incorporating real-time estimation of disease surveillance and epidemiological measures based on institutional data, we argue this approach helps minimize uncertainties in input parameters presented in the broader literature and increases prediction accuracy. We demonstrate this through case studies at Clemson and other university settings during the Omicron BA.1 and BA.4/BA.5 variant surges. The input parameters of our toolkit are easily adaptable to other institutional settings during future health emergencies. This methodological approach has potential to improve public health response through increasing the capability of institutions to make data-informed decisions that better prioritize the health and safety of their communities while minimizing operational disruptions.

An epidemiological modeling framework to inform institutional-level response to infectious disease outbreaks: A Covid-19 case study

Institutions have an enhanced ability to implement tailored mitigation measures during infectious disease outbreaks. However, macro-level predictive models are inefficient for guiding institutional decision-making due to uncertainty in local-level model input parameters. We present an institutional-level modeling toolkit used to inform prediction, resource procurement and allocation, and policy implementation at Clemson University throughout the Covid-19 pandemic. Through incorporating real-time estimation of disease surveillance and epidemiological measures based on institutional data, we argue this approach helps minimize uncertainties in input parameters presented in the broader literature and increases prediction accuracy. We demonstrate this through case studies at Clemson and other university settings during the Omicron BA.1 and BA.4/BA.5 variant surges. The input parameters of our toolkit are easily adaptable to other institutional settings during future health emergencies. This methodological approach has potential to improve public health response through increasing the capability of institutions to make data-informed decisions that better prioritize the health and safety of their communities while minimizing operational disruptions.

Current Healthcare Systems in Light of Hyperendemic NCDs and the COVID-19 Pandemic: Time to Change

Despite the significant achievements of current healthcare systems (CHCSs) in curing or treating several acute conditions, there has been far less success coping with noncommunicable diseases (NCDs), which have complex roots and nonconventional transmission vectors. Owing to the impact of the invisible hyperendemic NCDs and the COVID-19 pandemic, the limitations of CHCSs have been exposed. In contrast, the advent of omics-based technologies and big data science has raised global hope of curing or treating NCDs and improving overall healthcare outcomes. However, challenges related to their use and effectiveness must be addressed. Additionally, while such advancements intend to improve quality of life, they can also contribute the ever-increasing health disparity among vulnerable populations, such as low/middle-income populations, poorly educated people, gender-based violence victims, and minority and indigenous peoples, to name a few. Among five health determinants, the contribution of medical care to individual health does not exceed 11%. Therefore, it is time to implement a new well-being-oriented system complementary or parallel to CHCSs that incorporates all five health determinants to tackle NCDs and unforeseen diseases of the future, as well as to promote cost-effective, accessible, and sustainable healthy lifestyle choices that can reduce the current level of healthcare inequity.

Advancing patient-centered care: moving from outcome-based to risk factor-based models using the big four risk factors

This article reimagines the health care system to focus on risk factors rather than outcomes in order to improve patient-centered care and reduce health care expenditure. Patient-centered care has been a global priority since 2001 when the Institute of Medicine declared it an essential aim for health care systems. As part of this discussion and to help facilitate this change, the concept of the big four risk factors – diet and nutrition; physical activity; smoking and tobacco use; and excessive alcohol consumption – is introduced in the context of the Americas from which it originates. Using peer-reviewed literature, health policy guidelines, theories, frameworks, and transdisciplinary implementation science strategies, this article explains how public health research and medical centers are set up in terms of disease, or outcome, rather than risk factor, or exposure. It suggests how moving from outcome-based health care models to focus on prevention using the big four risk factors will lead to better patient-centered care and health outcomes. Transdisciplinary research and complexity science, a framework largely developed and tested in Latin America, are recommended to facilitate this change and develop multicomponent, multistakeholder action and cooperation. Future research should pilot the proposed changes at various health-system levels and in different settings and report on the outcomes of implementation to assess effectiveness and improve translation of research, perhaps using the standardized RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) evaluation framework.

Health workforce retention in low-income settings: an application of the Root Stem Model

The World Health Organization (WHO) recognizes a critical shortage of health workers as a growing global crisis. The shortage persists despite local and global efforts to recruit health workers ethically. Unequal migration of healthcare professionals, most often from low to high-resource countries, overwhelmingly defeats the objective of achieving Universal Health Coverage (UHC). If not addressed, especially given emerging global pandemics like COVID-19, the critical shortage of health workers could decimate vulnerable public health systems. This Viewpoint describes the Root-Stem Model, a six-stage process of strategic factors affecting work life that could help policymakers address the challenge of brain-drain among healthcare workers in low-income countries.

Effect of Coronavirus Disease 2019 (Covid-19), a Nationwide Mass Casualty Disaster on Intensive Care Units: Clinical Outcomes and Associated Cost-of-Care

OBJECTIVE

The COVID-19 pandemic resulted in millions of deaths worldwide and is considered a significant mass-casualty disaster (MCD). The surge of patients and scarcity of resources negatively impacted hospitals, patients and medical practice. We hypothesized ICUs during this MCD had a higher acuity of illness, and subsequently had increased lengths of stay (LOS), complication rates, death rates and costs of care. The purpose of this study was to investigate those outcomes.

METHODS

This was a multicenter, retrospective study that compared intensive care admissions in 2020 to those in 2019 to evaluate patient outcomes and cost of care. Data were obtained from the Vizient Clinical Data Base/Resource Manager (Vizient Inc., Irvine, Texas, USA).

RESULTS

Data included the number of ICU admissions, patient outcomes, case mix index and summary of cost reports. Quality outcomes were also collected, and a total of 1304981 patients from 333 hospitals were included. For all medical centers, there was a significant increase in LOS index, ICU LOS, complication rate, case mix index, total cost, and direct cost index.

CONCLUSION

The MCD caused by COVID-19 was associated with increased adverse outcomes and cost-of-care for ICU patients.

A Tale of Three Pandemics – SARS-CoV-2, HCV, and HIV in an Urban Emergency Department in Baltimore, Maryland

Background

We sought to determine the prevalence and sociodemographic and clinical correlates of acute and convalescent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), hepatitis C virus (HCV), and human immunodeficiency virus (HIV) infections among emergency department (ED) patients in Baltimore.

Methods

Remnant blood samples from 7450 unique patients were collected over 4 months in 2020 for SARS-CoV-2 antibody (Ab), HCV Ab, and HIV-1/2 antigen and Ab. Among them, 5012 patients were tested by polymerase chain reaction for SARS-CoV-2 based on clinical suspicion. Sociodemographics, ED clinical presentations, and outcomes associated with coinfections were assessed.

Results

Overall, 729 (9.8%) patients had SARS-CoV-2 (acute or convalescent), 934 (12.5%) HCV, 372 (5.0%) HIV infection, and 211 patients (2.8%) had evidence of any coinfection (HCV/HIV, 1.5%; SARS-CoV-2/HCV, 0.7%; SARS-CoV-2/HIV, 0.3%; SARS-CoV-2/HCV/HIV, 0.3%). The prevalence of SARS-CoV-2 (acute or convalescent) was significantly higher in those with HCV or HIV vs those without (13.6% vs 9.1%, P < .001). Key sociodemographic disparities (race, ethnicity, and poverty) and specific ED clinical characteristics were significantly correlated with having any coinfections vs no infection or individual monoinfection. Among those with HCV or HIV, aged 18–34 years, Black race, Hispanic ethnicity, and a cardiovascular-related chief complaint had a significantly higher odds of having SARS-CoV-2 (prevalence ratios: 2.02, 2.37, 5.81, and 2.07, respectively).

Conclusions

The burden of SARS-CoV-2, HCV, and HIV co-pandemics and their associations with specific sociodemographic disparities, clinical presentations, and outcomes suggest that urban EDs should consider implementing integrated screening and linkage-to-care programs for these 3 infections.

[Analysis of the national DST/Aids policy from the perspective of advocacy coalition framework (ACF)]

The success of the National STD/AIDS Program in Brazil is, to a great extent, associated with the multiplicity of social actors involved in the fight against AIDS. The scope of this article is to analyze the dynamics of changes occurring within the subsystem of national STD/AIDS policy in the light of the advocacy coalition framework (ACF) model. The study is based on documentary analysis of regulatory frameworks and interviews with key informants. The results point to the formation of three coalitions: Coalition A (social engagement); Coalition B (the force of governmental policies/actors); and Coalition C (international partnerships) which, mediated by the House of representatives and scientific institutions, wage disputes to translate their viewpoints into government actions. The data show that, despite being successful, the National STD/AIDS Policy faced great difficulties in establishing standards that addressed the needs of the population. However, although coalitions have different strategies, they are convergent, as they are directed towards the same objectives. It is worth mentioning that nowadays, the conservative wave in Brazil tends to preclude renewed policies in the field of AIDS and may threaten well-established human and social rights. Such impacts need to be analyzed in future studies.

Enlightenment from the COVID-19 Pandemic: The Roles of Environmental Factors in Future Public Health Emergency Response

The coronavirus disease 2019 (COVID-19) pandemic is challenging the current public health emergency response systems (PHERSs) of many countries. Although environmental factors, such as those influencing the survival of viruses and their transmission between species including humans, play important roles in PHERSs, little attention has been given to these factors. This study describes and elucidates the roles of environmental factors in future PHERSs. To improve countries' capability to respond to public health emergencies associated with viral infections such as the COVID-19 pandemic, a number of environmental factors should be considered before, during, and after the responses to such emergencies. More specifically, to prevent pandemic outbreaks, we should strengthen environmental and wildlife protection, conduct detailed viral surveillance in animals and hotspots, and improve early-warning systems. During the pandemic, we must study the impacts of environmental factors on viral behaviors, develop control measures to minimize secondary environmental risks, and conduct timely assessments of viral risks and secondary environmental effects with a view to reducing the impacts of the pandemic on human health and on ecosystems. After the pandemic, we should further strengthen surveillance for viruses and the prevention of viral spread, maintain control measures for minimizing secondary environmental risks, develop our capability to scientifically predict pandemics and resurgences, and prepare for the next unexpected resurgence. Meanwhile, we should restore the normal life and production of the public based on the "One Health" concept, that views global human and environmental health as inextricably linked. Our recommendations are essential for improving nations' capability to respond to global public health emergencies.

COVID-19 Outbreak Management and Vaccination Strategy in The United States of America

Four months after the first case of COVID-19 was reported in the United States, the SARS-CoV-2 virus had spread to more than 90% of all counties. Although the transmission of the virus can be grossly mitigated through non-pharmaceutical interventions and public health measures, risks of future outbreaks, emergence of more infectious variants, and disruptions to socio-economic life will probably remain until effective vaccines are administered to large portions of the global population. An exceptional collaboration between governments and the scientific community has led to the authorization of eight vaccines globally for full use, four of which were funded and developed in the United States. In this paper, we contextualize epidemiological, political, and economic impacts of the COVID-19 vaccination strategy in the United States of America between 20 January 2020, to 5 May 2021, with a key focus on vaccine hesitancy and public-private partnerships.

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department

During the coronavirus disease 2019 (COVID-19) pandemic, rapid and accurate triage of patients at the emergency department is critical to inform decision-making. We propose a data-driven approach for automatic prediction of deterioration risk using a deep neural network that learns from chest X-ray images and a gradient boosting model that learns from routine clinical variables. Our AI prognosis system, trained using data from 3661 patients, achieves an area under the receiver operating characteristic curve (AUC) of 0.786 (95% CI: 0.745-0.830) when predicting deterioration within 96 hours. The deep neural network extracts informative areas of chest X-ray images to assist clinicians in interpreting the predictions and performs comparably to two radiologists in a reader study. In order to verify performance in a real clinical setting, we silently deployed a preliminary version of the deep neural network at New York University Langone Health during the first wave of the pandemic, which produced accurate predictions in real-time. In summary, our findings demonstrate the potential of the proposed system for assisting front-line physicians in the triage of COVID-19 patients.

Top priorities for the next decade of nursing health services research

BACKGROUND

The U.S. health care system faces increasing pressures for reform. The importance of nurses in addressing health care delivery challenges cannot be overstated.

PURPOSE

To present a Nursing Health Services Research (NHSR) agenda for the 2020s.

METHOD

A meeting of an interdisciplinary group of 38 health services researchers to discuss five key challenges facing health care delivery (behavioral health, primary care, maternal/neonatal outcomes, the aging population, health care spending) and identify the most pressing and feasible research questions for NHSR in the coming decade.

FINDINGS

Guided by a list of inputs affecting health care delivery (health information technology, workforce, delivery systems, payment, social determinants of health), meeting participants identified 5 to 6 research questions for each challenge. Also, eight cross-cutting themes illuminating the opportunities and barriers facing NHSR emerged.

DISCUSSION

The Agenda can act as a foundation for new NHSR - which is more important than ever - in the 2020s.