Hospital catchment populations: evaluation of a new method to understand service users and demands
PHE ePoster Library. Wright C. 09/12/19; 274456; 250
Dr. Caroline Wright
Dr. Caroline Wright
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Abstract
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Abstract Introduction
Hospitals need to understand catchment populations to evaluate admission thresholds, redesign services, measure inequalities, offer patient choice and plan finances. Traditionally, some hospitals have used administrative boundaries derived from the CCG they are located in to understand their populations (geographical-boundary method GBM). However, hospitals do not operate in fixed geographies or have patient lists. To capture cross-boundary flow, PHE devised a proportionate-flow method (PFM) to model catchments. PFM identifies hospital admissions from a Middle-Super-Output-Area and proportionally applies the area's total population to each hospital based on admission numbers.
Method
Variation in admissions, population size and demographic characteristics between GBM and PFM catchment models was analysed.
Results
PFM covered a significantly (p<.05) greater proportion of the England population (99.99%) compared with GBM (71.6%). PFM also accounted for a significantly (p<.05) greater proportion of all (98.3%), elective (99.1%) and emergency (98. 8%) admissions compared with GBM (76.3%; 74.6%; 78.8%). Differences in demographics also exist with PFM modelling a greater proportion of elderly patients (18.0%; 17.7%) and children (23.7%; 23.6%) in their catchment population. But a significantly lower proportion of men (49.4%; 50.6%), working-aged people (58.3%; 58.7%) and those from the lowest deprivation quintile (20.7%; 24.5%).
Conclusion
PHE's proportionate-flow method provides more representative patient numbers, activity and demographics compared with a traditional geographical-boundary method. Using this PMF method to understand hospital catchments could allow more accurate service decisions and planning. This is particularly important as hospitals become Integrated Care Systems, offering greater patient choice and greater involvement in prevention and public health. External funding details
Abstract Introduction
Hospitals need to understand catchment populations to evaluate admission thresholds, redesign services, measure inequalities, offer patient choice and plan finances. Traditionally, some hospitals have used administrative boundaries derived from the CCG they are located in to understand their populations (geographical-boundary method GBM). However, hospitals do not operate in fixed geographies or have patient lists. To capture cross-boundary flow, PHE devised a proportionate-flow method (PFM) to model catchments. PFM identifies hospital admissions from a Middle-Super-Output-Area and proportionally applies the area's total population to each hospital based on admission numbers.
Method
Variation in admissions, population size and demographic characteristics between GBM and PFM catchment models was analysed.
Results
PFM covered a significantly (p<.05) greater proportion of the England population (99.99%) compared with GBM (71.6%). PFM also accounted for a significantly (p<.05) greater proportion of all (98.3%), elective (99.1%) and emergency (98. 8%) admissions compared with GBM (76.3%; 74.6%; 78.8%). Differences in demographics also exist with PFM modelling a greater proportion of elderly patients (18.0%; 17.7%) and children (23.7%; 23.6%) in their catchment population. But a significantly lower proportion of men (49.4%; 50.6%), working-aged people (58.3%; 58.7%) and those from the lowest deprivation quintile (20.7%; 24.5%).
Conclusion
PHE's proportionate-flow method provides more representative patient numbers, activity and demographics compared with a traditional geographical-boundary method. Using this PMF method to understand hospital catchments could allow more accurate service decisions and planning. This is particularly important as hospitals become Integrated Care Systems, offering greater patient choice and greater involvement in prevention and public health. External funding details
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