Can computer simulation support strategic service planning? Modelling a large integrated mental health system on recovery from COVID-19
Abstract Background COVID-19 has had a significant impact on people’s mental health and mental health services. During the first year of the pandemic, existing demand was not fully met while new demand was generated, resulting in large numbers of people requiring support. To support mental health se...
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| Format: | Article |
| Language: | English |
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BMC
2024-03-01
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| Series: | International Journal of Mental Health Systems |
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| Online Access: | https://doi.org/10.1186/s13033-024-00623-z |
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| author | Livia Pierotti Jennifer Cooper Charlotte James Kenah Cassels Emma Gara Rachel Denholm Richard Wood |
| author_facet | Livia Pierotti Jennifer Cooper Charlotte James Kenah Cassels Emma Gara Rachel Denholm Richard Wood |
| author_sort | Livia Pierotti |
| collection | DOAJ |
| description | Abstract Background COVID-19 has had a significant impact on people’s mental health and mental health services. During the first year of the pandemic, existing demand was not fully met while new demand was generated, resulting in large numbers of people requiring support. To support mental health services to recover without being overwhelmed, it was important to know where services will experience increased pressure, and what strategies could be implemented to mitigate this. Methods We implemented a computer simulation model of patient flow through an integrated mental health service in Southwest England covering General Practice (GP), community-based ‘talking therapies’ (IAPT), acute hospital care, and specialist care settings. The model was calibrated on data from 1 April 2019 to 1 April 2021. Model parameters included patient demand, service-level length of stay, and probabilities of transitioning to other care settings. We used the model to compare ‘do nothing’ (baseline) scenarios to ‘what if’ (mitigation) scenarios, including increasing capacity and reducing length of stay, for two future demand trajectories from 1 April 2021 onwards. Results The results from the simulation model suggest that, without mitigation, the impact of COVID-19 will be an increase in pressure on GP and specialist community based services by 50% and 50–100% respectively. Simulating the impact of possible mitigation strategies, results show that increasing capacity in lower-acuity services, such as GP, causes a shift in demand to other parts of the mental health system while decreasing length of stay in higher acuity services is insufficient to mitigate the impact of increased demand. Conclusion In capturing the interrelation of patient flow related dynamics between various mental health care settings, we demonstrate the value of computer simulation for assessing the impact of interventions on system flow. |
| format | Article |
| id | doaj-art-76261129b52448cb9cee6b290ea14bd6 |
| institution | Kabale University |
| issn | 1752-4458 |
| language | English |
| publishDate | 2024-03-01 |
| publisher | BMC |
| record_format | Article |
| series | International Journal of Mental Health Systems |
| spelling | doaj-art-76261129b52448cb9cee6b290ea14bd62025-01-19T12:10:50ZengBMCInternational Journal of Mental Health Systems1752-44582024-03-0118111210.1186/s13033-024-00623-zCan computer simulation support strategic service planning? Modelling a large integrated mental health system on recovery from COVID-19Livia Pierotti0Jennifer Cooper1Charlotte James2Kenah Cassels3Emma Gara4Rachel Denholm5Richard Wood6NIHR Bristol Biomedical Research Centre, University of BristolNIHR Bristol Biomedical Research Centre, University of BristolNIHR Bristol Biomedical Research Centre, University of BristolBristol, North Somerset and South Gloucestershire Integrated Care Board, UK National Health ServiceBristol, North Somerset and South Gloucestershire Integrated Care Board, UK National Health ServiceNIHR Bristol Biomedical Research Centre, University of BristolBristol, North Somerset and South Gloucestershire Integrated Care Board, UK National Health ServiceAbstract Background COVID-19 has had a significant impact on people’s mental health and mental health services. During the first year of the pandemic, existing demand was not fully met while new demand was generated, resulting in large numbers of people requiring support. To support mental health services to recover without being overwhelmed, it was important to know where services will experience increased pressure, and what strategies could be implemented to mitigate this. Methods We implemented a computer simulation model of patient flow through an integrated mental health service in Southwest England covering General Practice (GP), community-based ‘talking therapies’ (IAPT), acute hospital care, and specialist care settings. The model was calibrated on data from 1 April 2019 to 1 April 2021. Model parameters included patient demand, service-level length of stay, and probabilities of transitioning to other care settings. We used the model to compare ‘do nothing’ (baseline) scenarios to ‘what if’ (mitigation) scenarios, including increasing capacity and reducing length of stay, for two future demand trajectories from 1 April 2021 onwards. Results The results from the simulation model suggest that, without mitigation, the impact of COVID-19 will be an increase in pressure on GP and specialist community based services by 50% and 50–100% respectively. Simulating the impact of possible mitigation strategies, results show that increasing capacity in lower-acuity services, such as GP, causes a shift in demand to other parts of the mental health system while decreasing length of stay in higher acuity services is insufficient to mitigate the impact of increased demand. Conclusion In capturing the interrelation of patient flow related dynamics between various mental health care settings, we demonstrate the value of computer simulation for assessing the impact of interventions on system flow.https://doi.org/10.1186/s13033-024-00623-zComputer modellingComputer simulationCOVID-19CoronavirusService designMental health services |
| spellingShingle | Livia Pierotti Jennifer Cooper Charlotte James Kenah Cassels Emma Gara Rachel Denholm Richard Wood Can computer simulation support strategic service planning? Modelling a large integrated mental health system on recovery from COVID-19 International Journal of Mental Health Systems Computer modelling Computer simulation COVID-19 Coronavirus Service design Mental health services |
| title | Can computer simulation support strategic service planning? Modelling a large integrated mental health system on recovery from COVID-19 |
| title_full | Can computer simulation support strategic service planning? Modelling a large integrated mental health system on recovery from COVID-19 |
| title_fullStr | Can computer simulation support strategic service planning? Modelling a large integrated mental health system on recovery from COVID-19 |
| title_full_unstemmed | Can computer simulation support strategic service planning? Modelling a large integrated mental health system on recovery from COVID-19 |
| title_short | Can computer simulation support strategic service planning? Modelling a large integrated mental health system on recovery from COVID-19 |
| title_sort | can computer simulation support strategic service planning modelling a large integrated mental health system on recovery from covid 19 |
| topic | Computer modelling Computer simulation COVID-19 Coronavirus Service design Mental health services |
| url | https://doi.org/10.1186/s13033-024-00623-z |
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