Application of Population Catchment to Rural Health Services Planning & Monitoring
Population Catchment Applications In Practice
Rural Birth Index
The Rural Birth Index (RBI) was developed in 2008 and applied to rural communities based on population catchment analysis linked with perinatal services data.15,16 Each rural community in BC with an active maternity service or history of a maternity service within 10 years was included. An RBI score was calculated for each community as in the attached Figure 10.
The RBI score was parameterized against level of service and a framework of comparison was created with corresponding normative levels of maternity service. This work was then extended and applied across rural Australia.17,18 Most recently, a study was commissioned by the BC Ministry of Health to reevaluate the RBI using data from 2008 to 2019. This work led to the creation of a rolling measure of need for maternity services over time.16 The graph for Fort St James is reproduced below.
This provides a trend line over the past 14 years which strengthens the planning process for local maternity services. Data can also be tracked for the population including c-section rate, induction rate, and rates of forceps/vacuum assisted deliveries.
Rural Generalist Provider Services Index
Recent work has consisted of using the level of population need to calculate the demand for local primary care services and to parametrize this against the number of physician providers required by the community. This measure is represented by the Rural Generalist Provider Services Index (RGPSI).19 Each community can be assigned an RGPSI score, which can be included in their community catchment profile. The aim of the RGPSI is to better equip healthcare planners with data based on community-need versus an arbitrary assignment of healthcare personnel. Development of this index is ongoing and will be the subject of a dedicated publication.
Impacts of Population Catchment Approach
These applications can support rationale planning of health services for the catchment but also underpin quality improvement initiatives. For example, if there is concern about the high c-section rate for the catchment this could lead to an exploration of the reasons for the frequency of the surgical delivery, the design of an intervention, and the forward tracking of ongoing results. This situation could also inspire the flagging of maternity care as an area for potential improvement, a literature review, and study of comparable communities with lower rates of certain needs or conditions. Most importantly, the local maternity care providers and parturient women and families could work in partnership to understand the problem and change the patterns of care.
The transformation in the ability of the community to see data related to their own outcomes within a comparative framework empowers the local system to change as needed.
