Predicting patient acuity according to their main problem

Developing a haemodialysis acuity tool (the HAT study): A qualitative study

BACKGROUND

Haemodialysis units are now managing an increasing number of patients with varying needs and levels of acuity. To maintain safety, haemodialysis patients must be placed in the most appropriate dialysis unit that has the required human and physical resources to care for them. The first step towards achieving these goals is to develop a tool specific to haemodialysis units to effectively measure patient acuity.

OBJECTIVE

To develop a haemodialysis acuity tool, utilising a focus group approach, in assessing patient's suitability for a specific dialysis location thus ensuring patient safety.

DESIGN

This is a cross-sectional qualitative study via a focus group approach.

PARTICIPANTS

Participants were nurse unit managers and team leaders of a District Renal Service.

APPROACH

Participants were interviewed to explore their views on the elements and measures identified in the research aims. Themes for interviews were informed by current literature on acuity tools for haemodialysis patients' admission to the dialysis units. Interviews were recorded and transcribed verbatim and progressively analysed using a thematic analysis approach.

RESULTS

Ten nurse unit managers/team leaders (100%) were interviewed and thematic analysis of the transcripts was conducted utilising the deductive approach. Five themes were identified which will form the main categories in the development of the tool, namely: Age/frailty; co-morbidity; physical; dialysis; and psychosocial.

CONCLUSION

This study is instrumental in the development of the haemodialysis acuity tool which can be used in allocating dialysis location specific to patient's needs and available resources. The tool can also be used in analysing patient care processes and resource requirements based on the patients' and unit's profile.

Peripheral intravenous catheter failure, nurse staffing levels and care complexity individual factors: A retrospective multicentre cohort study

INTRODUCTION

Short peripheral intravenous catheter (PIVC) failure is a common complication that is generally underdiagnosed. Some studies have evaluated the factors associated with these complications, but the impact of care complexity individual factors and nurse staffing levels on PIVC failure is still to be assessed. The aim of this study was to determine the incidence and risk factors of PIVC failure in the public hospital system of the Southern Barcelona Metropolitan Area.

METHODS

A retrospective multicentre observational cohort study of hospitalised adult patients was conducted in two public hospitals in Barcelona from 1st January 2016 to 31st December 2017. All adult patients admitted to the hospitalisation ward were included until the day of discharge. Patients were classified according to presence or absence of PIVC failure. The main outcomes were nurse staffing coverage (ATIC patient classification system) and 27-care complexity individual factors. Data were obtained from electronic health records in 2022.

RESULTS

Of the 44,661 patients with a PIVC, catheter failure was recorded in 2,624 (5.9%) patients (2,577 [5.8%] phlebitis and 55 [0.1%] extravasation). PIVC failure was more frequent in female patients (42%), admitted to medical wards, unscheduled admissions, longer catheter dwell time (median 7.3 vs 2.2 days) and those with lower levels of nurse staffing coverage (mean 60.2 vs 71.5). Multivariate logistic regression analysis revealed that the female gender, medical ward admission, catheter dwell time, haemodynamic instability, uncontrolled pain, communication disorders, a high risk of haemorrhage, mental impairments, and a lack of caregiver support were independent factors associated with PIVC failure. Moreover, higher nurse staffing were a protective factor against PIVC failure (AUC, 0.73; 95% confidence interval [CI]: 0.72-0.74).

CONCLUSION

About 6% of patients presented PIVC failure during hospitalisation. Several complexity factors were associated with PIVC failure and lower nurse staffing levels were identified in patients with PIVC failure. Institutions should consider that prior identification of care complexity individual factors and nurse staffing coverage could be associated with a reduced risk of PIVC failure.

Situation awareness in intensive care unit nurses: A qualitative directed content analysis

Background

Situation awareness (SA) is an essential cognitive construct to create positive patient safety outcomes. SA of the nurses in the intensive care unit (ICU), where conditions may change rapidly, is particularly important. The present study aimed to explain the perception and experience of SA in ICU nurses based on Endsley's SA model.

Materials and methods

This qualitative directed content analysis was conducted on nurses in six hospitals in Tehran, Iran, from December 2020 to July 2021. Twenty-seven ICU nurses were selected using purposive sampling. Data were collected by semi-structured interviews and field observations. The data were analyzed based on the Elo and Kyngas method modified by Assarroudi et al. COREQ checklist was used to report the research.

Results

The concept of SA in ICU nurses, based on Endsley's model, includes perception of patients' clinical cues, perception of the human environment, perception of the physical environment, and perception of the organizational environment as generic categories of the perception of the elements in the environment. SA in ICU nurses also includes the main categories of comprehension the current situation through a sense of salience and interpretation of cues and projection the future situation through the prediction of patient status into the near future and environmental foresight.

Conclusion

Findings have further developed the concept of SA in ICU nurses based on Endsley's SA model. The insights and knowledge gained from this study can be useful for future practice, education, and research on SA among ICU nurses.

Nurse staffing legislation: Empirical evidence and policy analysis

Unsafe nurse staffing conditions in hospitals have been shown to increase the risk of adverse patient events, including mortality. Consequently, United States and international professional nursing organizations often advocate for safer staffing conditions. There are a variety of factors to consider when staffing nurses for patient safety, such as the number of patients per nurse, nurse preparation, patient acuity, and nurse autonomy. The complex issue of staffing nurses often is compounded by cost issues and can become politicized. When nurse organizations' recommendations for safe staffing measures are disregarded by hospital administrations, nurse lobbyists and interest groups often pursue legislative action to protect patients and nurses from unsafe staffing conditions. This article presents a narrative review of safe nurse staffing factors and an analysis of nurse staffing legislation. Using a patient-centric lens, three state-level nurse staffing policies (mandated nurse-to-patient ratios, public reporting of staffing plans, and nurse staffing committees) were evaluated by empirical evidence, cost to hospitals and state governments, political feasibility, and potential to affect patient populations. Although nurse staffing policy analysis can be conducted in several ways, it is crucial that nurses consider empirical evidence related to staffing policies as well as evaluations of implemented policies and political influences.

An integrative review of comprehensive nursing assessment tools developed based on Gordon's Eleven Functional Health Patterns

PURPOSE

To evaluate the content and psychometric properties of comprehensive nursing assessment tools developed based on The Eleven Functional Health Patterns Assessment Framework.

METHODS

An integrative literature review following Whittemore and Knafl's method and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Searches on PubMed, Cinahl, and Virtual Health Library were conducted between September and December 2018.

FINDINGS

Six out of 146 records were included for review. Four articles were methodological studies and two were descriptive reports of the development of the tools. Tools were heterogenous in terms of their purpose, development, characteristics, and testing. Only one study provided data about construct validity. However, there were commonalities regarding the data that should be assessed in each tool.

CONCLUSIONS

Few comprehensive nursing assessment tools using The Eleven Functional Health Patterns Assessment Framework are available. Purpose, process of development, characteristics, and testing varied among the tools, and most lack robust psychometric testing.

IMPLICATIONS FOR NURSING PRACTICE

This review provided a synthesis of the literature regarding the use of a discipline-specific framework to guide comprehensive nursing assessment. The differences across the tools and the lack of psychometric testing compromise the visibility of nursing and make it difficult to emphasize the contribution of nursing knowledge to patient care.

Risk of acute deterioration and care complexity individual factors associated with health outcomes in hospitalised patients with COVID-19: a multicentre cohort study

BACKGROUND

Evidence about the impact of systematic nursing surveillance on risk of acute deterioration of patients with COVID-19 and the effects of care complexity factors on inpatient outcomes is scarce. The aim of this study was to determine the association between acute deterioration risk, care complexity factors and unfavourable outcomes in hospitalised patients with COVID-19.

METHODS

A multicentre cohort study was conducted from 1 to 31 March 2020 at seven hospitals in Catalonia. All adult patients with COVID-19 admitted to hospitals and with a complete minimum data set were recruited retrospectively. Patients were classified based on the presence or absence of a composite unfavourable outcome (in-hospital mortality and adverse events). The main measures included risk of acute deterioration (as measured using the VIDA early warning system) and care complexity factors. All data were obtained blinded from electronic health records. Multivariate logistic analysis was performed to identify the VIDA score and complexity factors associated with unfavourable outcomes.

RESULTS

Out of a total of 1176 patients with COVID-19, 506 (43%) experienced an unfavourable outcome during hospitalisation. The frequency of unfavourable outcomes rose with increasing risk of acute deterioration as measured by the VIDA score. Risk factors independently associated with unfavourable outcomes were chronic underlying disease (OR: 1.90, 95% CI 1.32 to 2.72; p<0.001), mental status impairment (OR: 2.31, 95% CI 1.45 to 23.66; p<0.001), length of hospital stay (OR: 1.16, 95% CI 1.11 to 1.21; p<0.001) and high risk of acute deterioration (OR: 4.32, 95% CI 2.83 to 6.60; p<0.001). High-tech hospital admission was a protective factor against unfavourable outcomes (OR: 0.57, 95% CI 0.36 to 0.89; p=0.01).

CONCLUSION

The systematic nursing surveillance of the status and evolution of COVID-19 inpatients, including the careful monitoring of acute deterioration risk and care complexity factors, may help reduce deleterious health outcomes in COVID-19 inpatients.

Care complexity individual factors associated with adverse events and in-hospital mortality

Introduction

Measuring the impact of care complexity on health outcomes, based on psychosocial, biological and environmental circumstances, is important in order to detect predictors of early deterioration of inpatients. We aimed to identify care complexity individual factors associated with selected adverse events and in-hospital mortality.

Methods

A multicenter, case-control study was carried out at eight public hospitals in Catalonia, Spain, from January 1, 2016 to December 31, 2017. All adult patients admitted to a ward or a step-down unit were evaluated. Patients were divided into the following groups based on the presence or absence of three adverse events (pressure ulcers, falls or aspiration pneumonia) and in-hospital mortality. The 28 care complexity individual factors were classified in five domains (developmental, mental-cognitive, psycho-emotional, sociocultural and comorbidity/complications). Adverse events and complexity factors were retrospectively reviewed by consulting patients’ electronic health records. Multivariate logistic analysis was performed to identify factors associated with an adverse event and in-hospital mortality.

Results

A total of 183,677 adult admissions were studied. Of these, 3,973 (2.2%) patients experienced an adverse event during hospitalization (1,673 [0.9%] pressure ulcers; 1,217 [0.7%] falls and 1,236 [0.7%] aspiration pneumonia). In-hospital mortality was recorded in 3,996 patients (2.2%). After adjustment for potential confounders, the risk factors independently associated with both adverse events and in-hospital mortality were: mental status impairments, impaired adaptation, lack of caregiver support, old age, major chronic disease, hemodynamic instability, communication disorders, urinary or fecal incontinence, vascular fragility, extreme weight, uncontrolled pain, male sex, length of stay and admission to a medical ward. High-tech hospital admission was associated with an increased risk of adverse events and a reduced risk of in-hospital mortality. The area under the ROC curve for both outcomes was > 0.75 (95% IC: 0.78–0.83).

Conclusions

Several care complexity individual factors were associated with adverse events and in-hospital mortality. Prior identification of complexity factors may have an important effect on the early detection of acute deterioration and on the prevention of poor outcomes.

Relationships between the National Early Warning Score 2, clinical worry and patient outcome at discharge: Retrospective observational study

AIMS AND OBJECTIVES

To examine the performance of the National Early Warning Score 2 and composite score for clinical worry in identifying patients at risk of clinical deterioration, and to determine relationships between National Early Warning Score 2, clinical worry score and patient outcome at discharge.

BACKGROUND

The efficacy of early warning systems depends on patient population and care settings. Based on a theoretical framework on factors affecting clinical deterioration and patient outcomes, studies exploring the relationship between early warning systems and patient outcomes at discharge are sparse.

DESIGN

Retrospective observational study.

METHODS

A random sample of 732 medical records were reviewed. The area under the receiver operating characteristic curve was calculated to evaluate predictive abilities regarding the events of unanticipated in-hospital mortality, unplanned intensive care unit/ higher dependency bed admission and cardiac arrest. Multiple logistic regression analyses were performed to determine relationships between National Early Warning Score 2, clinical worry score and patient outcome. Reporting followed the STROBE checklist.

RESULTS

National Early Warning Score 2 and clinical worry score significantly predicted the events within 24 hr of the assessment. After controlling for other patient, treatment and organisational characteristics, National Early Warning Score 2 was a significant factor associated with patient outcome, but clinical worry score was not. Specifically, patients at high risk based on National Early Warning Score 2 were less likely to have improved outcome.

CONCLUSIONS

National Early Warning Score 2 and clinical worry score performed well for predicting deteriorating condition of patients. National Early Warning Score 2 was significantly associated with patient outcome. It can be used for efficient patient management for safe, quality care.

RELEVANCE TO CLINICAL PRACTICE

National Early Warning Score 2 can be used for early assessment of not only clinical deterioration but also patient outcome and provide timely intervention, when coupled with clinical worry score.

Acuity, nurse staffing and workforce, missed care and patient outcomes: A cluster-unit-level descriptive comparison

AIM

To compare the patient acuity, nurse staffing and workforce, missed nursing care and patient outcomes among hospital unit-clusters.

BACKGROUND

Relationships among acuity, nurse staffing and workforce, missed nursing care and patient outcomes are not completely understood.

METHOD

Descriptive design with data from four unit-clusters: medical, surgical, combined and step-down units. Descriptive statistics were used to compare acuity, nurse staffing coverage, education and expertise, missed nursing care and selected nurse-sensitive outcomes.

RESULTS

Patient acuity in general (medical, surgical and combined) floors is similar to step-down units, with an average of 5.6 required RN hours per patient day. In general wards, available RN hours per patient day reach only 50% of required RN hours to meet patient needs. Workforce measures are comparable among unit-clusters, and average missed nursing care is 21%. Patient outcomes vary among unit-clusters.

CONCLUSION

Patient acuity is similar among unit-clusters, while nurse staffing coverage is halved in general wards. While RN education, expertise and missed care are comparable among unit-clusters, mortality, skin injuries and risk of family compassion fatigue rates are higher in general wards.

IMPLICATIONS FOR NURSING MANAGEMENT

Nurse managers play a pivotal role in hustling policymakers to address structural understaffing in general wards, to maximize patient safety outcomes.

Predicting patient acuity according to their main problem

AIM

To assess the ability of the patient main problem to predict acuity in adults admitted to hospital wards and step-down units.

BACKGROUND

Acuity refers to the categorization of patients based on their required nursing intensity. The relationship between acuity and nurses' clinical judgment on the patient problems, including their prioritization, is an underexplored issue.

METHOD

Cross-sectional, multi-centre study in a sample of 200,000 adults. Multivariate analysis of main problems potentially associated with acuity levels higher than acute was performed. Distribution of patients and outcome differences among acuity clusters were evaluated.

RESULTS

The main problems identified are strongly associated with patient acuity. The model exhibits remarkable ability to predict acuity (AUC, 0.814; 95% CI, 0.81-0.816). Most patients (64.8%) match higher than acute categories. Significant differences in terms of mortality, hospital readmission and other outcomes are observed (p < .005).

CONCLUSION

The patient main problem predicts acuity. Most inpatients require more intensive than acute nursing care and their outcomes are adversely affected.

IMPLICATIONS FOR NURSING MANAGEMENT

Prospective measurement of acuity, considering nurses' clinical judgments on the patient main problem, is feasible and may contribute to support nurse management workforce planning and staffing decision-making, and to optimize patients, nurses and organizational outcomes.