The role and resources required for the introduction of generic ward assistants using GRASP systems workload methodology: a quantitative study

Machine learning-based patient classification system for adult patients in intensive care units: A cross-sectional study

AIM

This study aimed to develop a patient classification system that stratifies patients admitted to the intensive care unit based on their disease severity and care needs.

BACKGROUND

Classifying patients into homogenous groups based on clinical characteristics can optimize nursing care. However, an objective method for determining such groups remains unclear.

METHODS

Predictors representing disease severity and nursing workload were considered. Patients were clustered into subgroups with different characteristics based on the results of a clustering algorithm. A patient classification system was developed using a partial least squares regression model.

RESULTS

Data of 300 patients were analysed. Cluster analysis identified three subgroups of critically patients with different levels of clinical trajectories. Except for blood potassium levels (p = .29), the subgroups were significantly different according to disease severity and nursing workload. The predicted value ranges of the regression model for Classes A, B and C were <1.44, 1.44-2.03 and >2.03. The model was shown to have good fit and satisfactory prediction efficiency using 200 permutation tests.

CONCLUSIONS

Classifying patients based on disease severity and care needs enables the development of tailored nursing management for each subgroup.

IMPLICATIONS FOR NURSING MANAGEMENT

The patient classification system can help nurse managers identify homogeneous patient groups and further improve the management of critically ill patients.

Health and social care workforce planning and development--an overview

PURPOSE

The purpose of this paper is to discuss the issues relating to getting the right health and social care staff with the right skills in the right place at the right time and at the right price.

DESIGN/METHODOLOGY/APPROACH

Key points arising from several master-classes with health and social care managers, supported by a literature review, generated remarkable insights into health and social care workforce planning and development (WP&D).

FINDINGS

Flawed methods and overwhelming data are major barriers to health and social care WP&D. Inefficient and ineffective WP&D policy and practice, therefore, may lead to inappropriate care teams, which in turn lead to sub-optimal and costly health and social care. Increasing health and social care demand and service re-design, as the population grows and ages, and services move from hospital to community, means that workforce planners face several challenges. Issues that drive and restrain their health and social care WP&D efforts are lucid and compelling, which leave planners in no doubt what is expected if they are to succeed and health and social care is to develop. One main barrier they face is that although WP&D definitions and models in the literature are logical, clear and effective, they are imperfect, so planners do not always have comprehensive tools or data to help them determine the ideal workforce. They face other barriers. First, WP&D can be fragmented and uni-disciplinary when modern health and social care is integrating. Second, recruitment and retention problems can easily stymie planners' best endeavours because the people that services need (i.e. staff with the right skills), even if they exist, are not evenly distributed throughout the country.

PRACTICAL IMPLICATIONS

This paper underlines triangulated workforce demand and supply methods (described in the paper), which help planners to equalise workloads among disparate groups and isolated practitioners--an important job satisfaction and staff retention issue. Regular and systematic workforce reviews help planners to justify their staffing establishments; it seems vital, therefore, that they have robust methods and supporting data at their fingertips.

ORIGINALITY/VALUE

This paper stock-takes the latest health and social care workforce planning and development issues.

Health care assistants: the views of managers of health care agencies on training and employment

AIM

The aim of this study was to obtain the views of managers of health care agencies to assess whether they would employ trained health care assistants (HCAs).

BACKGROUND

In 2000/2001, a training programme for HCAs was piloted in the Republic of Ireland. It was important to ascertain if the training programme was capable of producing HCAs that health care agencies would employ.

METHODS

A self-administrated postal survey was distributed to health care agencies.

RESULTS

Findings included suggestions on how the content of the programme could be made more relevant; most of the managers surveyed would employ a HCA trained on the programme; respondents did not believe that the HCA role encroached on that of the nurse and/or midwife and; most already employed HCAs with some offering informal, in-house training.

CONCLUSION

Overall, respondents' views of the training programme were extremely positive with many recommending that it be continued and expanded.

Fast-tracking (bypassing the PACU) does not reduce nursing workload after ambulatory surgery †

BACKGROUND

Postoperative day-case patients are usually allowed to recover from anaesthesia in a postanaesthesia care unit (PACU) before transfer back to the day surgical unit (DSU). Bypassing the PACU can decrease recovery time after day surgery. Cost savings may result from a reduced nursing workload associated with the decreased recovery time. This study was designed to evaluate the effects of bypassing the PACU on patient recovery time and nursing workload and costs.

METHODS

Two hundred and seven consenting outpatients undergoing day surgery procedures were enrolled. Anaesthesia was induced and maintained with a standardized technique and the electroencephalographic bispectral index was monitored and maintained at 40-60 during anaesthetic maintenance. At the end of surgery, patients were randomly assigned to either a routine or fast-tracking (FT) group. Patients in the FT group were transferred from the operating room to the DSU (i.e. bypassing the PACU) if they achieved the FT criteria. All other patients were transferred to the PACU and then to the DSU. Nursing workload was evaluated using a patient care hour chart based on the type and frequency of nursing interventions in the PACU and DSU. A cost associated with the nursing workload was calculated.

RESULTS

The overall time from end of anaesthesia to discharge home was significantly decreased in the fast-tracking group. However, overall patient care hours and costs were similar in the two recovery groups.

CONCLUSION

Bypassing the PACU after these short outpatient procedures significantly decreases recovery time without compromising patient satisfaction. However, the overall nursing workload and the associated cost were not significantly affected.

The utilization of the healthcare assistant role in intensive care

The increasing role of healthcare assistants (HCAs) in intensive care in relation to patient monitoring has raised concerns among some clinical managers, particularly where such roles are not underpinned by a sound knowledge base and critical reasoning ability. This article describes a study which was undertaken in an attempt to identify how HCAs are currently utilized within the general intensive care environment. The results show a wide variation between units in relation to the activities undertaken by HCAs, their training and the levels of remuneration. This article seeks to open up the debate as to whether or not nurses should be challenging the nursing care that is now delivered by non-nurses and makes recommendations for the way forward in this area.