Constructing a nursing budget using a patient classification system

Kolakowski, Deborah

doi:10.1097/01.numa.0000479449.43157.b5

Cited by 8 publications

(21 citation statements)

References 4 publications

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“…Six sources 19,20,39,[55][56][57] simply described the use of a staffing system or tool (classified as 'description'), although they also reported some data, generally exemplar graphs or charts of varying workload. In addition, three studies classified in this group sought to measure nursing workload or demand associated with different ward designs 58 or diagnostic groups 59 or to determine variability in patient need prior to developing a new workload management system.…”

Section: Descriptionmentioning

confidence: 99%

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The Safer Nursing Care Tool as a guide to nurse staffing requirements on hospital wards: observational and modelling study

Griffiths

Saville

Ball

et al. 2020

Health Serv Deliv Res

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Background The Safer Nursing Care Tool is a system designed to guide decisions about nurse staffing requirements on hospital wards, in particular the number of nurses to employ (establishment). The Safer Nursing Care Tool is widely used in English hospitals but there is a lack of evidence about how effective and cost-effective nurse staffing tools are at providing the staffing levels needed for safe and quality patient care. Objectives To determine whether or not the Safer Nursing Care Tool corresponds to professional judgement, to assess a range of options for using the Safer Nursing Care Tool and to model the costs and consequences of various ward staffing policies based on Safer Nursing Care Tool acuity/dependency measure. Design This was an observational study on medical/surgical wards in four NHS hospital trusts using regression, computer simulations and economic modelling. We compared the effects and costs of a ‘high’ establishment (set to meet demand on 90% of days), the ‘standard’ (mean-based) establishment and a ‘flexible (low)’ establishment (80% of the mean) providing a core staff group that would be sufficient on days of low demand, with flexible staff re-deployed/hired to meet fluctuations in demand. Setting Medical/surgical wards in four NHS hospital trusts. Main outcome measures The main outcome measures were professional judgement of staffing adequacy and reports of omissions in care, shifts staffed more than 15% below the measured requirement, cost per patient-day and cost per life saved. Data sources The data sources were hospital administrative systems, staff reports and national reference costs. Results In total, 81 wards participated (85% response rate), with data linking Safer Nursing Care Tool ratings and staffing levels for 26,362 wards × days (96% response rate). According to Safer Nursing Care Tool measures, 26% of all ward-days were understaffed by ≥ 15%. Nurses reported that they had enough staff to provide quality care on 78% of shifts. When using the Safer Nursing Care Tool to set establishments, on average 60 days of observation would be needed for a 95% confidence interval spanning 1 whole-time equivalent either side of the mean. Staffing levels below the daily requirement estimated using the Safer Nursing Care Tool were associated with lower odds of nurses reporting ‘enough staff for quality’ and more reports of missed nursing care. However, the relationship was effectively linear, with staffing above the recommended level associated with further improvements. In simulation experiments, ‘flexible (low)’ establishments led to high rates of understaffing and adverse outcomes, even when temporary staff were readily available. Cost savings were small when high temporary staff availability was assumed. ‘High’ establishments were associated with substantial reductions in understaffing and improved outcomes but higher costs, although, under most assumptions, the cost per life saved was considerably less than £30,000. Limitations This was an observational study. Outcomes of staffing establishments are simulated. Conclusions Understanding the effect on wards of variability of workload is important when planning staffing levels. The Safer Nursing Care Tool correlates with professional judgement but does not identify optimal staffing levels. Employing more permanent staff than recommended by the Safer Nursing Care Tool guidelines, meeting demand most days, could be cost-effective. Apparent cost savings from ‘flexible (low)’ establishments are achieved largely by below-adequate staffing. Cost savings are eroded under the conditions of high temporary staff availability that are required to make such policies function. Future work Research is needed to identify cut-off points for required staffing. Prospective studies measuring patient outcomes and comparing the results of different systems are feasible. Trial registration Current Controlled Trials ISRCTN12307968. Funding This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 8, No. 16. See the NIHR Journals Library website for further project information.

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Section: Descriptionmentioning

confidence: 99%

“…68,79 Finally, tools can be used retrospectively to review the success of staffing planshow well the plan met needsor as a measure of resource use for pricing, budgeting or billing purposes. 57…”

Section: Staffing Decisions and The Use Of Toolsmentioning

confidence: 99%

The Safer Nursing Care Tool as a guide to nurse staffing requirements on hospital wards: observational and modelling study

Griffiths

Saville

Ball

et al. 2020

Health Serv Deliv Res

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“…Physical, material, technological and financial resources, although essential for the achievement of quality care, are subordinated to the real needs of users, as well as the knowledge of professionals about the quantity and optimization of the use of these resources ( 2 - 3 ) .…”

Section: Introductionmentioning

confidence: 99%

“…Nursing management is challenged daily by demands that, for sustainability and safe care, require a great deal of involvement from nurses in administrative, financial and economic issues, in addition to mastering modern tools for the development of managerial competences, such as leadership, flexibility, proactivity, among others (1)(2)(3) .…”

Section: Introductionmentioning

confidence: 99%

Adaptation and validation of an adult patient classification instrument with emphasis on the family dimension

et al. 2023

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Objectives: to adapt and validate an instrument for classifying adult patients that emphasizes the family support network in the demand for nursing care. Methods: methodological study, carried out in three phases: adaptation of an instrument considering the reality of adult patients; content validation with seven experts and assessment of measurement properties (construct validity and internal consistency) with 781 hospitalized patients. Results: in content validation, the indicators reached the values established for the Content Validity Index (0.85-1.00). In the confirmatory factor analysis, the 11 indicators were distributed in three domains and presented average variance extracted and factor loading greater than 0.5. Composite reliability was greater than 0.7. Conclusions: the present study adapted and made available, with evidence of validity and reliability, an instrument for classifying adult patients that considers the family support network in the demand for nursing care.

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“…This is essential for budget planning and nursing staffing, as nursing personnel accounts for the largest percentage of hospital expenses. Careful cost management is essential in order to maintain a balance between patient care and cost‐effective budgeting (Kolakowski, 2016). However, the degree of reliability and accuracy of cost prediction largely depends on costing methodology, which can impact resource allocation (Kludacz‐Alessandri, 2020; Tan et al., 2012).…”

Section: Introductionmentioning

confidence: 99%

Critical care nursing service costs: Comparison of the top‐down versus bottom‐up micro‐costing approach in Brazil

et al. 2021

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Aim To estimate the nursing service costs using a top‐down micro‐costing approach and to compare it with a bottom‐up micro‐costing approach. Background Accurate data of nursing cost can contribute to reliable resource management. Method We employed a retrospective cohort design in an adult intensive care unit in São Paulo. A total of 286 patient records were included. Micro‐costing analysis was conducted in two stages: a top‐down approach, whereby nursing costs were allocated to patients through apportionment, and a bottom‐up approach, considering actual nursing care hours estimated by the Nursing Activities Score (NAS). Results The total mean cost by the top‐down approach was US$1,640.4 ± 1,484.2/patient. The bottom‐up approach based on a total mean NAS of 833 ± 776 points (equivalent to 200 ± 86 hr of nursing care) yielded a mean cost of US$1,487.2 ± 1,385.7/patient. In the 268 patients for whom the top‐down approach estimated higher costs than the bottom‐up approach, the total cost discrepancy was US$4,427.3, while for those costed higher based on NAS, the total discrepancy was US$436.9. The top‐down methodology overestimated costs for patients requiring lower intensity of care, while it underestimated costs for patients requiring higher intensity of care (NAS >100). Conclusions The top‐down approach may yield higher estimated ICU costs compared with a NAS‐based bottom‐up approach. Implications for nursing management These findings can contribute to an evidence‐based approach to budgeting through reliable costing methods based on actual nursing workload, and to efficient resource allocation and cost management.

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Constructing a nursing budget using a patient classification system

Cited by 8 publications

References 4 publications

The Safer Nursing Care Tool as a guide to nurse staffing requirements on hospital wards: observational and modelling study

The Safer Nursing Care Tool as a guide to nurse staffing requirements on hospital wards: observational and modelling study

Adaptation and validation of an adult patient classification instrument with emphasis on the family dimension

Critical care nursing service costs: Comparison of the top‐down versus bottom‐up micro‐costing approach in Brazil

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