Patient dependency in the emergency department (ED): Reliability and validity of the Jones Dependency Tool (JDT)

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Summary

Background

Rising patient demand in emergency departments is an international problem. Patient dependency (the degree of nursing care required) has major implications for nursing. Nurse skill mix and staffing levels can be addressed more effectively when dependency can be measured. A valid and reliable method of determining patient dependency in the emergency department in the United Kingdom is required.

Aim

To test the validity, reliability and generalisability of the Jones Dependency Tool.

Methods

Six emergency departments across England were included. The sample was 140 adult patients from each site (n = 840). Information was collected by nurses on: demographics, triage, chief complaint, vital clinical signs, nurse’s own subjective rating of patient dependency, Jones Dependency Tool ratings and a comparative tool ratings. For a sub-sample of 40 patients, observation data were collected.

Results

There was a highly significant correlation between the Jones Dependency Tool scores and the nurses’ subjective ratings of patient dependency (R = 0.786, P < 0.001). There was a significant correlation between triage rating and Jones Dependency Tool scores (R = 0.58, P < 0.001). The higher the dependency, the higher the proportion of patients with abnormal pulse rates (χ2 = 7.45, df = 1, P = 0.006), abnormal respiratory rates (χ2 = 15.683, df = 1, P < 0.001) and abnormal oxygen saturation (χ2 = 15.583, df = 1, P < 0.001). The higher the amount of time spent by nurses in direct care of patients the higher the patient’s level of dependency (R = 0,72, P < 0.001). Length of time spent by nurses with patients was also significantly and positively correlated with the nurses’ subjective ratings of patient dependency (R = 0.49, P = 0.001). There was a positive and significant correlation between Jones Dependency Tool scores and comparator scores (R = 0.726, P < 0.001). There was a good correlation between JDT scores measured over time (κ = 0.68) and good inter-rater reliability (κ = 0.75).

Conclusions

The Jones Dependency Tool can be recommended as a valid and reliable tool for the measurement of patient dependency in the emergency department.

Introduction

Rising demand in emergency departments (EDs) is an international problem. For example overcrowding, as a result of rising demand in EDs, has been reported as an issue of concern in the United States of America (USA) (Trezeciak and Rivers, 2003), Canada (Schull et al., 2003), China (Shih et al., 1999), Greece (Agouridakis et al., 2004) and Spain (Miro et al., 2003). The demand for emergency department services in the United Kingdom (UK) is increasing annually, in 2003–2004 15 million people sought emergency care through either an emergency department or a walk-in centre (National Audit Office, 2004).

Nursing staff shortages is also a problem faced by many industrialized nations. Difficulties with nursing shortages have been reported in the USA (Bower and McCullough, 2004, Janiszewski Goodwin, 2003), Australia (Hawthorne, 2001) Europe (De Raeve, 2003) and the UK (Gerrish and Griffith, 2004). The recent British National Audit Office report has identified a shortage of nursing staff within the Emergency Department (National Audit Office, 2004).

Patient Classification Systems (PCS) to guide staff planning date back to 1947 and have been widely used in nursing (Vail, 1989) especially in the USA and Australia. Economic pressures and nursing shortages have increased the urgency to develop and implement effective PCSs.

PCSs have been defined as ‘the methods and processes of determining, validating and monitoring individual patient care requirements over time in order to assist in such determinations as: unit staffing, patient assignments, case mix analysis, budget planning and defense, per patient cost of nursing services, variable patient billing and the maintenance of quality assurance standards’ (DeGroot, 1989a, p. 30).

The purpose of a PCS is ‘to determine the intensity of nursing care for a patient, or group of patients, including both direct and indirect nursing requirements’ (Vail, 1989, p. 120). According to Vail (1989) the elements of a PCS should include:

Direct Nursing Care Time: time required for those activities that take place in the presence of the patient and/or family. These activities are behavioural and observable.

Indirect Nursing Care Time: time required for those activities and tasks performed away from the patient and/or family, and include such tasks as: communication, planning care, assessing needs, preparation and checking of equipment, team conferences and meetings.

Unavailable for Patient Care Time (non-productive time): includes those activities of personnel not directed toward patient care that detract from time available for patient care and includes unit management.

In defining patient classification systems (PCSs) Conners (1994) stated that there are two types of classification systems:

Prototype – a system that uses only a few tasks (e.g. bathing, ambulation) that have been shown to be predictors of the amount of care provided. Patients are then categorised into groups based on whether they demonstrate one or more of these critical indicators. This type of classification is described as subjective.

Factor type – identifies a comprehensive list of tasks or procedures performed, with a numerical value given to each task based on the time taken to perform them. These values are summed and the category is determined by the number of points.

DeGroot, 1989a, DeGroot, 1989b, DeGroot, 1994 set out critical factors for patient classification tool selection criteria. These are

  • (1)

    validity,

  • (2)

    reliability,

  • (3)

    simplicity/efficiency,

  • (4)

    utility,

  • (5)

    objectivity,

  • (6)

    acceptability,

  • (7)

    prospective measure for the ED setting,

  • (8)

    need to measure both direct, indirect nursing time and unavailable for nursing time,

  • (9)

    need to describe how scores translate into staffing requirements.

DeGroot (1994) also stated that there should not be an in-house development of PCSs but rather instruments developed by knowledgeable nurse researchers.

In a recent systematic review, 11 PCSs were identified for specific use within the ED setting. These were developed in the US, Hawaii, Sweden, Australia and the UK (Williams and Crouch, 2006). Of these only two, one developed in the US The ED Patient Classification Matrix (Butler, 1986) and one developed in Australia (a modification of the ED Patient Classification Matrix) (Conners, 1994) demonstrated good validity and reliability.

However, both these PCSs have limitations. Butler (1986) reported that implementation was only for a one week period and not all staff participated. The author recommended that implementation of the PCS should cover a longer period to be more representative of staffing needs by allowing for differences in patient numbers, illness acuity levels and staffing patterns. The tool was also developed for use within one particular department and therefore has no demonstrable generalisability. For the Conners Tool (Conners, 1994) the trial commenced at a convenient time for the department, which could have resulted in case mix selection bias and reduced generalisability.

Patients, who present to the ED have undifferentiated and undiagnosed problems. Presentations can range from simple self-limiting conditions to life-threatening illnesses or injuries with varying degrees of dependency. Patient dependency has been defined as the degree of nursing care required by the patient, nursing workload has been defined as the tasks that the patient dependency creates (Jones, 1990). Existing British guidance on nurse staffing levels in EDs is helpful but could be strengthened with a formula to facilitate individual department calculation of nurse staffing levels (Royal College of Nursing, RCN, 1993, British Association for Accident and Emergency Medicine BAEM, 2004). Determining staffing levels on volume of patients alone takes no account of the severity of illness/injury, case mix, patient dependency or workload. Both patient dependency and the length of time the patient remains in the emergency department are key factors in determining the numbers and skill mix of nurses required to provide quality care. Insufficient numbers of nursing staff may lead to high staff sickness, stress and turnover rates resulting in higher costs, dissatisfaction among nursing staff and poorer quality care for patients (McVicar, 2003, Carr, 1994).

The British government accepted the House of Commons Health Select Committee recommendation for a major review of workforce planning for all professional groups in the NHS (Department of Health, DoH, 2000). Workforce planning is defined as “trying to predict the future demand for different types of staff and seeking to match this with supply” to ensure that “there are sufficient staff available with the right skills to deliver quality care to patients” (Department of Health, DoH, 2000). In the report, it is stated that “if workforce planning and development is to be effective, there will be a need for high quality relevant and timely information on the workforce in particular to provide routine information on staff involved in different care groups” (Department of Health, DoH, 2000). To date there has been insufficient information available on two interrelated key factors in establishing staffing for EDs: skill mix and patient dependency.

Jones (1990) has proposed a prospective dependency tool that has been used in a number of EDs in the UK. The Jones Dependency Tool (JDT) was developed through extensive observational work of factors associated with patient dependency. The JDT has face validity. An expert panel of 12 ED nurses and 12 ED consultants received questionnaires during three rounds to refine and develop the tool. After the completion of three rounds there was high consensus agreement 94% (16 /17) that the tool adequately reflected key factors determining patient dependency (Crouch et al., 2001). There is a need to further assess the validity and reliability of the JDT.

Section snippets

Aims

The aims of this study were to determine the validity, reliability and generalisability of the JDT as a concurrent method of determining patient dependency in the ED setting. The study questions were

  • Does the JDT show good construct validity?

  • Does the JDT show criterion-related validity?

  • Does the JDT show good inter-rater reliability?

  • Does the JDT show good reliability over time?

Sample

To ensure generalisability of the tool, six hospital ED sites were recruited into the study; a mix of urban and inner city hospitals.

Procedure

Ethical approval was gained from the Multi-Centre Regional Ethics Committee. Approval by Local Research Ethical Committees for all 6 sites was then sought and granted. NHS Trust approval was also sought and granted from each of the six sites. The main data collection was conducted between January 15th, 2001 and 7th June 2001. Seven shifts (a mix of late, early,

Criterion validity

The criterion-related validity requires the comparison between the findings of the tool with data collected on the same patient using other methods. The data to be compared were vital signs, triage category, and nurse subjective opinion of the dependency of the patient (collected via a Likert scale) and patient demographic data. For a sub-sample of patients (n = 40) the observed length of contact time with the patient was collected for comparison with the other measures. The timings of activity

Results

Data were collected on a total of 976 patient cases from the six ED sites. Of these 136 cases were excluded. Of the cases excluded, there were 96 child cases, 19 cases with date of birth missing and 21 cases with missing ratings on at least one of the components of the Jones Dependency Tool. The final data set was 840 adult cases from the six sites, the desired sample size required for the study.

Triage across sites

The triage categories reflect the urgency of need for clinical care (Red = Immediate; Orange = Very urgent, should be seen in 10 min; Yellow = Urgent should be seen within 1 hour; Green = Standard, should be seen in 2–4 hours; Blue = non-urgent). The breakdown of triage classification per site is presented in Fig. 1.

Discussion

The data from this study provides evidence of the validity and reliability of the JDT in six EDs in the UK. It has been validated for use with adult patients. Although absolute generalisability is not confirmed by this study, the sites selected were of differing characteristics. It is therefore likely that the JDT will be applicable in all adult ED settings in the UK.

Rising demand in EDs and nursing staff shortages are international problems (Trezeciak and Rivers, 2003, Schull et al., 2003,

Study limitations

The comparator measure the ED Patient Classification Matrix (Butler, 1986) is a tool using patient acuity as an indicator of dependency. The JDT only includes this as one of its components (i.e. triage). It was therefore recognised that this could increase the difficulty in achieving good correlation between JDT scores and the ED Patient Classification Matrix as the ‘Gold Standard’. However, despite this, ED Patient Classification Matrix scores were found to be significantly correlated with the

Conclusions

Overall, there have been no valid and reliable tools developed to facilitate accurate forecasting of the numbers of nursing staff required to effectively manage ED workload in the UK. The JDT is a valid and reliable tool that can be used to measure patient dependency. Introducing the JDT in the ED setting may help in the development of staffing patterns linked to patient dependency.

The JDT could also be applicable for use in other countries with similar healthcare systems. Further assessment of

Acknowledgements

We are very grateful to all the nurses who participated in the study and in particular the senior nurses who managed the data collection at each site. We thank the patients who took part in the observations. We also thank Susan Rogers for her administrative support and Dr Richard Hooper for his statistical advice. The grant from the NHS Executive is gratefully acknowledged.

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