Thaison Tong1, Praveen Thokala1, Brian McMillan2, Rob Ghosh3, John Brazier1. 1. School of Health and Related Research, University of Sheffield, Sheffield, UK. 2. Centre for Primary Care, University of Manchester, Manchester, UK. 3. Geriatric and Stroke Medicine, Sheffield Teaching Hospitals, Sheffield, UK.
Abstract
INTRODUCTION: We estimated the cost effectiveness of different cognitive screening tests for use by General Practitioners (GPs) to detect cognitive impairment in England. METHODS: A patient-level cost-effectiveness model was developed using a simulated cohort that represents the elderly population in England (65 years and older). Each patient was followed over a lifetime period. Data from published sources were used to populate the model. The costs include government funded health and social care, private social care and informal care. Patient health benefit was measured and valued in Quality Adjusted Life Years (QALYs). RESULTS: Base-case analyses found that adopting any of the three cognitive tests (Mini-Mental State Examination, 6-Item Cognitive Impairment Test or GPCOG (General Practitioner Assessment of Cognition)) delivered more QALYs for patients over their lifetime and made savings across sectors including healthcare, social care and informal care compared with GP unassisted judgement. The benefits were due to early access to medications. Among the three cognitive tests, adopting the GPCOG was considered the most cost-effective option with the highest Incremental Net Benefit (INB) at the threshold of £30 000 per QALY from both the National Health Service and Personal Social Service (NHS PSS) perspective (£195 034 per 1000 patients) and the broader perspective that includes private social care and informal care (£196 251 per 1000 patients). Uncertainty was assessed in both deterministic and probabilistic sensitivity analyses. CONCLUSIONS: Our analyses indicate that the use of any of the three cognitive tests could be considered a cost-effective strategy compared with GP unassisted judgement. The most cost-effective option in the base-case was the GPCOG.
INTRODUCTION: We estimated the cost effectiveness of different cognitive screening tests for use by General Practitioners (GPs) to detect cognitive impairment in England. METHODS: A patient-level cost-effectiveness model was developed using a simulated cohort that represents the elderly population in England (65 years and older). Each patient was followed over a lifetime period. Data from published sources were used to populate the model. The costs include government funded health and social care, private social care and informal care. Patient health benefit was measured and valued in Quality Adjusted Life Years (QALYs). RESULTS: Base-case analyses found that adopting any of the three cognitive tests (Mini-Mental State Examination, 6-Item Cognitive Impairment Test or GPCOG (General Practitioner Assessment of Cognition)) delivered more QALYs for patients over their lifetime and made savings across sectors including healthcare, social care and informal care compared with GP unassisted judgement. The benefits were due to early access to medications. Among the three cognitive tests, adopting the GPCOG was considered the most cost-effective option with the highest Incremental Net Benefit (INB) at the threshold of £30 000 per QALY from both the National Health Service and Personal Social Service (NHS PSS) perspective (£195 034 per 1000 patients) and the broader perspective that includes private social care and informal care (£196 251 per 1000 patients). Uncertainty was assessed in both deterministic and probabilistic sensitivity analyses. CONCLUSIONS: Our analyses indicate that the use of any of the three cognitive tests could be considered a cost-effective strategy compared with GP unassisted judgement. The most cost-effective option in the base-case was the GPCOG.
Authors: KongFatt Wong-Lin; Paula L McClean; Niamh McCombe; Daman Kaur; Jose M Sanchez-Bornot; Paddy Gillespie; Stephen Todd; David P Finn; Alok Joshi; Joseph Kane; Bernadette McGuinness Journal: BMC Med Date: 2020-12-16 Impact factor: 8.775
Authors: Michael F Bergeron; Sara Landset; Xianbo Zhou; Tao Ding; Taghi M Khoshgoftaar; Feng Zhao; Bo Du; Xinjie Chen; Xuan Wang; Lianmei Zhong; Xiaolei Liu; J Wesson Ashford Journal: J Alzheimers Dis Date: 2020 Impact factor: 4.472