Prioritizing Patients from the Most Deprived Areas on Elective Waiting Lists in the NHS in England: Estimating the Health and Health Inequality Impact
Introduction. Reducing hospital waiting lists for elective procedures is a policy concern in the National Health Service (NHS) in England. Following growth in waiting lists after COVID-19, the NHS published an elective recovery plan that includes an aim to prioritize patients from deprived areas. We...
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SAGE Publishing
2025-01-01
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| Series: | MDM Policy & Practice |
| Online Access: | https://doi.org/10.1177/23814683241310146 |
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| author | Naomi Kate Gibbs Susan Griffin Nils Gutacker Adrián Villaseñor Simon Walker |
| author_facet | Naomi Kate Gibbs Susan Griffin Nils Gutacker Adrián Villaseñor Simon Walker |
| author_sort | Naomi Kate Gibbs |
| collection | DOAJ |
| description | Introduction. Reducing hospital waiting lists for elective procedures is a policy concern in the National Health Service (NHS) in England. Following growth in waiting lists after COVID-19, the NHS published an elective recovery plan that includes an aim to prioritize patients from deprived areas. We use a previously developed model to estimate the health and health inequality impact under hypothetical targeted versus universal policies to reduce waiting time. Methods. We use a Markov model to estimate the health impact of waiting, by index of multiple deprivation quintile group, for 8 elective procedures. We estimate patients’ remaining quality-adjusted life-years (QALYs) with baseline waiting times and under 2 hypothetical policy scenarios: 1) a universal policy in which all patients receive an equal reduction in wait and 2) a targeted policy in which patients living in the most deprived quintile are prioritized. We estimate individual and population level health under each of the 2 policies and compare it with baseline. We also estimate how health inequality changes from baseline using the slope index of inequality, reflecting the difference in health between the least and most deprived quintile based on QALYs. Results. A universal reduction in waiting time is estimated to improve overall population health but increase health inequality. A targeted reduction would achieve nearly the same overall health gain and would also increase population-level health inequalities but to a lesser extent than the universal policy would. Discussion. If the NHS is successful in prioritizing patients on waiting lists from the most deprived areas, this may result in smaller increases in health inequalities while maintaining a similar level of overall health gain compared with a universal policy. Highlights The NHS elective recovery plans include prioritizing patients who live in the most deprived areas of England. Evaluating a hypothetical targeted wait time reduction policy against a universal wait time reduction policy suggests almost the same level of population health gain could be achieved while lessening the negative impact on health inequality. Expected outcomes of government health policies should be quantified to explore the impact on both health maximization and health inequality minimization, as both represent legitimate policy concerns. |
| format | Article |
| id | doaj-art-d8d7fea65c2c442e85ca17764c427465 |
| institution | Kabale University |
| issn | 2381-4683 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | MDM Policy & Practice |
| spelling | doaj-art-d8d7fea65c2c442e85ca17764c4274652025-01-21T11:04:33ZengSAGE PublishingMDM Policy & Practice2381-46832025-01-011010.1177/23814683241310146Prioritizing Patients from the Most Deprived Areas on Elective Waiting Lists in the NHS in England: Estimating the Health and Health Inequality ImpactNaomi Kate GibbsSusan GriffinNils GutackerAdrián VillaseñorSimon WalkerIntroduction. Reducing hospital waiting lists for elective procedures is a policy concern in the National Health Service (NHS) in England. Following growth in waiting lists after COVID-19, the NHS published an elective recovery plan that includes an aim to prioritize patients from deprived areas. We use a previously developed model to estimate the health and health inequality impact under hypothetical targeted versus universal policies to reduce waiting time. Methods. We use a Markov model to estimate the health impact of waiting, by index of multiple deprivation quintile group, for 8 elective procedures. We estimate patients’ remaining quality-adjusted life-years (QALYs) with baseline waiting times and under 2 hypothetical policy scenarios: 1) a universal policy in which all patients receive an equal reduction in wait and 2) a targeted policy in which patients living in the most deprived quintile are prioritized. We estimate individual and population level health under each of the 2 policies and compare it with baseline. We also estimate how health inequality changes from baseline using the slope index of inequality, reflecting the difference in health between the least and most deprived quintile based on QALYs. Results. A universal reduction in waiting time is estimated to improve overall population health but increase health inequality. A targeted reduction would achieve nearly the same overall health gain and would also increase population-level health inequalities but to a lesser extent than the universal policy would. Discussion. If the NHS is successful in prioritizing patients on waiting lists from the most deprived areas, this may result in smaller increases in health inequalities while maintaining a similar level of overall health gain compared with a universal policy. Highlights The NHS elective recovery plans include prioritizing patients who live in the most deprived areas of England. Evaluating a hypothetical targeted wait time reduction policy against a universal wait time reduction policy suggests almost the same level of population health gain could be achieved while lessening the negative impact on health inequality. Expected outcomes of government health policies should be quantified to explore the impact on both health maximization and health inequality minimization, as both represent legitimate policy concerns.https://doi.org/10.1177/23814683241310146 |
| spellingShingle | Naomi Kate Gibbs Susan Griffin Nils Gutacker Adrián Villaseñor Simon Walker Prioritizing Patients from the Most Deprived Areas on Elective Waiting Lists in the NHS in England: Estimating the Health and Health Inequality Impact MDM Policy & Practice |
| title | Prioritizing Patients from the Most Deprived Areas on Elective Waiting Lists in the NHS in England: Estimating the Health and Health Inequality Impact |
| title_full | Prioritizing Patients from the Most Deprived Areas on Elective Waiting Lists in the NHS in England: Estimating the Health and Health Inequality Impact |
| title_fullStr | Prioritizing Patients from the Most Deprived Areas on Elective Waiting Lists in the NHS in England: Estimating the Health and Health Inequality Impact |
| title_full_unstemmed | Prioritizing Patients from the Most Deprived Areas on Elective Waiting Lists in the NHS in England: Estimating the Health and Health Inequality Impact |
| title_short | Prioritizing Patients from the Most Deprived Areas on Elective Waiting Lists in the NHS in England: Estimating the Health and Health Inequality Impact |
| title_sort | prioritizing patients from the most deprived areas on elective waiting lists in the nhs in england estimating the health and health inequality impact |
| url | https://doi.org/10.1177/23814683241310146 |
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