Feasibility of using payroll data to estimate hospital nurse staffing
The capacity for a hospital inpatient unit to provide high quality nursing care depends on a complex range of factors. Accurately identifying and measuring these factors is one of the challenges of nursing care quality research. Nursing hours per patient day and skill mix are two quantifiable indica...
| Main Authors: | , , , , |
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| Format: | Journal Article |
| Published: |
Elsevier BV
2015
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| Online Access: | http://hdl.handle.net/20.500.11937/28251 |
| _version_ | 1848752485566513152 |
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| author | Schreuders, L. Geelhoed, E. Bremner, A. Finn, Judith Twigg, D. |
| author_facet | Schreuders, L. Geelhoed, E. Bremner, A. Finn, Judith Twigg, D. |
| author_sort | Schreuders, L. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The capacity for a hospital inpatient unit to provide high quality nursing care depends on a complex range of factors. Accurately identifying and measuring these factors is one of the challenges of nursing care quality research. Nursing hours per patient day and skill mix are two quantifiable indicators of capacity to provide nursing care. Aims: The aims of the study are to measure fortnightly, unit-level nurse staffing and compare them to target nurse staffing levels. Method: Nurse staffing and inpatient unit movement data were sourced for the administrative records of three Western Australian tertiary metropolitan hospitals (2004-2008). The impact of data source on nurse staffing estimates was tested with linear mixed models, adjusting for financial year. Counts, proportions, means, and standard deviations were used to describe nurse staffing data. Bar graphs depict proportion of nursing hours provided by nurses of different skill levels. Results: Data source did not significantly affect estimate of nursing hours per patient day (p = 0.788). Fortnights during which nurse staffing targets were not reached were recorded for all units. Skill mix varied between units with different staffing targets. Conclusion: It is feasible to calculate fortnightly nursing hours and skill mix per hospital unit from raw nursing payroll and inpatient unit movement records. Fortnightly, unit-level measurement highlights nurse staffing fluctuations that are masked by annually aggregated data and are relevant for studies which investigate the association between nurse staffing levels and inpatient complication rates. Staffing shortfalls may affect nurses' experiences of working or patients' care experiences. |
| first_indexed | 2025-11-14T08:09:22Z |
| format | Journal Article |
| id | curtin-20.500.11937-28251 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:09:22Z |
| publishDate | 2015 |
| publisher | Elsevier BV |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-282512018-03-29T09:08:50Z Feasibility of using payroll data to estimate hospital nurse staffing Schreuders, L. Geelhoed, E. Bremner, A. Finn, Judith Twigg, D. The capacity for a hospital inpatient unit to provide high quality nursing care depends on a complex range of factors. Accurately identifying and measuring these factors is one of the challenges of nursing care quality research. Nursing hours per patient day and skill mix are two quantifiable indicators of capacity to provide nursing care. Aims: The aims of the study are to measure fortnightly, unit-level nurse staffing and compare them to target nurse staffing levels. Method: Nurse staffing and inpatient unit movement data were sourced for the administrative records of three Western Australian tertiary metropolitan hospitals (2004-2008). The impact of data source on nurse staffing estimates was tested with linear mixed models, adjusting for financial year. Counts, proportions, means, and standard deviations were used to describe nurse staffing data. Bar graphs depict proportion of nursing hours provided by nurses of different skill levels. Results: Data source did not significantly affect estimate of nursing hours per patient day (p = 0.788). Fortnights during which nurse staffing targets were not reached were recorded for all units. Skill mix varied between units with different staffing targets. Conclusion: It is feasible to calculate fortnightly nursing hours and skill mix per hospital unit from raw nursing payroll and inpatient unit movement records. Fortnightly, unit-level measurement highlights nurse staffing fluctuations that are masked by annually aggregated data and are relevant for studies which investigate the association between nurse staffing levels and inpatient complication rates. Staffing shortfalls may affect nurses' experiences of working or patients' care experiences. 2015 Journal Article http://hdl.handle.net/20.500.11937/28251 10.1016/j.colegn.2016.07.004 Elsevier BV restricted |
| spellingShingle | Schreuders, L. Geelhoed, E. Bremner, A. Finn, Judith Twigg, D. Feasibility of using payroll data to estimate hospital nurse staffing |
| title | Feasibility of using payroll data to estimate hospital nurse staffing |
| title_full | Feasibility of using payroll data to estimate hospital nurse staffing |
| title_fullStr | Feasibility of using payroll data to estimate hospital nurse staffing |
| title_full_unstemmed | Feasibility of using payroll data to estimate hospital nurse staffing |
| title_short | Feasibility of using payroll data to estimate hospital nurse staffing |
| title_sort | feasibility of using payroll data to estimate hospital nurse staffing |
| url | http://hdl.handle.net/20.500.11937/28251 |