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Scale and skill-mix efficiencies in nursing home staffing: inside the black box

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Health Systems

Abstract

Care workers account for a significant proportion of the total health expenditure in nursing homes and are by far the largest controllable resource. Therefore, determining the appropriate number and type of care workers required plays an important role in the search for more efficiency. This study provides insights into how and why ‘scale of scheduling’ and the enlargement of care workers’ jobs (blending tasks of different qualification levels (QLs)) affect the number and type of staff required to meet the preferences (in terms of day and time) of nursing home residents. The scheduling data for plannable care activities of three separate decision-making units within a single Dutch nursing home have been analyzed. The results show that in >85% of the examined cases, substantial scale and skill-mix economies can be achieved. We also found that the correlation between the demand patterns of different types of care tasks is of considerable importance when it comes to possible scale and skill-mix efficiencies.

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Acknowledgements

We thank the ‘anonymous nursing care organization’ for the data set and Verkooijen & Beima and CCmath for letting us use the OERplanner.

Author information

Authors and Affiliations

  1. School of Management and Governance, Avans University of Applied Sciences, The Netherlands

    Dennis Moeke

  2. Department of Mathematics, VU University Amsterdam, The Netherlands

    Ger Koole

  3. School of Healthcare, Windesheim University of Applied Sciences, The Netherlands

    Lineke Verkooijen

Authors
  1. Dennis Moeke
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  2. Ger Koole
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  3. Lineke Verkooijen
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Corresponding author

Correspondence to Dennis Moeke.

Appendix

Appendix

This appendix provides a more detailed description of the characteristics of the data used for this study. A summary of the statistical characteristics of the empirical data set that is used to determine the potential efficiency gains of job enlargement and the enlargement of the scale of scheduling can be found in Table A1. This table shows for each of the six examined days (and for each DMU) (1) the number of healthcare tasks, (2) the average tasksize in minutes, (3) the standard deviation (SD) of the tasksize, and also (4) the workload distribution between the three QLs. The workload is expressed as a percentage of the summation of the duration of all the healthcare tasks during that particular day.

Table A1 Statistical characteristics empirical data set
Full size table

The distribution of the number of tasks between the three QLs, when regarding the complete data set, are shown in Table A2. The statistical characteristics of the empirical data presented in Tables A1 and A2 were used as input for the simulation.

Table A2 Distribution of number of tasks based on empirical data set
Full size table

Table A3 shows the numerical results of the simulation. It shows, for each of the 40 days, the Weighted Average Correlation and the potential efficiency gain, in terms of number of care routes needed to meet the healthcare demand, when applying (1) job enlargement or (2) large-scale scheduling.

Table A3 Results simulation
Full size table

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Moeke, D., Koole, G. & Verkooijen, L. Scale and skill-mix efficiencies in nursing home staffing: inside the black box. Health Syst 3, 18–28 (2014). https://doi.org/10.1057/hs.2013.9

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  • DOI: https://doi.org/10.1057/hs.2013.9

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