Introduction

In this report, we present results from the application of a needs-based funding methodology to a series of six population simulations. The purpose of presenting these examples is to provide a clear illustration of the impact on Regional Health Authority (RHA) funding allocations arising from two central features of populations: their age structure and their relative need for health care services.

To illustrate the impact of these two population features, we have presented a series of simulations based on populations of 100,000 persons. There are three different age structures modeled in the simulations: a population distribution that is younger than the provincial population distribution, a population distribution similar to the provincial population distribution and a population that is older than the provincial population distribution. The younger distribution is typical of northern RHA populations, the provincial distribution is typical of Winnipeg and the older distribution is typical of many southern rural RHA populations.

The health care resource allocations for each of these three populations is then simulated under two assumptions of need for medical care: high and low need. In the Regional Health Authority funding methodology, need for medical care is measured by an indicator which combines information on premature mortality and the social and economic characteristics of regional populations. Detailed explanations on the approach to developing this blended need indicator are contained in a report titled 'A Methodology for Need-Adjusted Population-Based Resource Allocation in Health Care Services'.

The use of health services is strongly related to age, and this profile of utilization differs across health care service pools. In this simulation, we have represented three service pools: institutional acute care (hospitals), institutional long term care (nursing homes and extended care facilities) and health promotion 1 disease prevention services (community and public health services).

With the exception of the first year of life, when use of hospital care is valued at approximately $3,131 per infant, the age specific use of hospital resources rises over the age course, reaching amounts in the range of $3,000 per person by age 80.

The use of long term care resources, estimated on a per capita basis, is concentrated among the elderly. The estimated per capita utilization of public health services is more evenly distributed over the age course, with the exception of a much higher allocation of resources to children in the first year of life.

Funding Methodology

Under an assumption that there is no difference in health status across populations, Regional Health Authority allocations can be calculated by multiplying each age-specific per capita allocation by the number of persons in that age group in each region and summing the product of this age-specific calculation over all age groups. It can be appreciated that the age distribution of a population has very large consequences for the allocation of health care resources. A young population of 100,000 people would receive approximately 30% fewer resources for institutional acute care than a population of 100,000 with an age distribution similar to the provincial profile ($53.1 million vs. $77.2 million). Conversely, an old population of 100,000 people would receive approximately 17% more resources than the provincial age profile population ($90.4 million vs. $77.2 million). These differences attributable to population age structure are even more dramatic in the institutional long term care pool. Regional Health Authority allocations in the health promotion and disease prevention pool is less strongly influenced by age structure differences, because the per capita provision of services across age groups is more similar.

The final step in the Regional Health Authority funding methodology involves the application of an adjustment for differences in health status across populations. In making this adjustment, the methodology explicitly implements an assumption that the need for health care, after accounting for age and sex differences in the composition of regional populations, may differ across regions. To state this issue another way, the funding methodology acknowledges that on average, women aged 50-54 in one region may not be as healthy as women of the same age in another region. To ensure an equitable allocation of resources in relation to need for health care, regions with less healthy populations should be assigned more resources than regions with more healthy populations, after accounting for differences in population age structure.

The approach to need adjustment in the funding methodology is based on the following sequence of steps. For each region, a measure of need for health care is computed, based on integrating information on premature mortality and a set of social and economic characteristics of the population. This measure of need is used, in turn, to adjust the age and sex-specific per capita allocations within a service pool either upwards (if the region has higher need than the provincial average) or downward (if the region has lower need than the provincial average).

The need adjustment of the per capita age and sex allocation is based on multiplying the region's need score by a coefficient, or multiplier, obtained from analyses of Winnipeg population's use of health care services. In these analyses, the population of Winnipeg has been divided into 15 geographic areas, and need scores for each area are regressed on observed per capita utilization of hospital services and long term care. The coefficient from these regressions indicates the additional dollars of resources used by a population with a 1.0 unit increase in need score. So, for example, at ages 0-14, the average per capita utilization of hospital resources in Winnipeg is estimated to be $312, and children in areas of the city with a need score 1.0 units above the city average would use $372 ($312 + $60). The multiplier term is simply the ratio of the coefficient to the intercept value.

These regression results indicate that hospital use is most strongly influenced by need at younger ages, and that this relationship declines with rising age, so that by ages 75 +, there is no detectable difference in the use of hospital services across city populations with different measures of need.

Per Capita Need Adjustment, Poor Health Status


= (age-specific per capita allocation) x (Regional Health Authority need score) x (age-specific multiplier)

= $3,131.28 x 1.6 x 0.19

= $965.98

Per Capita Need Adjustment, Poor Health Status


= (age-specific per capita allocation) x (Regional Health Authority need score) x (age-specific multiplier)

= $3,131.28 x -0.50 x 0. 19

= -$297.93

The final step in the need adjustment procedure is to increase or decrease the age/sex per capita allocation by the per capita need adjustment value. In this example, in a region with poor health status, the Regional Health Authority would be allocated $4,097.27 ($3,131.28 + $965.98) for each child under the age of 1. In a region with good health status, the Regional Health Authority would be allocated $2,833.36 ($3,131.28 - $297.93) for each infant.

Multipliers derived from the institutional acute care pool regression analyses have also been applied to the Health Promotion and Disease Prevention pool.

In the institutional acute care pool, for example, a high need assumption in a young population would increase the regional allocation by 21.2%, from $53.2 million to $64.4 million. Conversely, a low need assumption would reduce the allocation by 6.5 %, to $49.7 million. The impact of these two contrasting need assumptions can be observed in this table across three different age structures and three service pools.

It is clear from these data that differences in age composition and in need for medical care can have very large implications for resource allocation to regions with identical population sizes. For example, the extreme contrast in the institutional acute care pool, between a young population of 100,000 people with low need and an old population of 100,000 with high need: $49.7 million vs. $100.9 million. In the institutional long term care pool the differences are even more substantial: a young population of 100,000 people with low need would be allocated $3.9 million and an old population of 100,000 with high need would be allocated $45.7 million.