IADR Abstract Archives
Workforce Planning Models in Oral Healthcare: A Systematic Review
Objectives: In order for healthcare services to adequately serve populations, workforces must be planned appropriately. One way in which to do this is through quantitative models to estimate current and future health needs and/or workforce requirements. The aim of this review was to identify and describe the different workforce planning models being used to drive oral health workforce planning and to assess how these models address the health needs of populations.
Methods: A systematic review was conducted. The following databases were searched using a structured strategy: Medline via OVID, Embase via OVID, HMIC via OVID and EconHealth via OVID. In addition, a number of grey literature databases were searched and key bodies and policy makers were contacted. Workforce planning models were included if they projected workforce numbers and were specific to oral health. No limits were placed on language or country. Initial screening of abstracts was completed by a single reviewer; secondary screening and data extraction were completed duplicate by two independent reviewers. A narrative synthesis was conducted.
Results: Searches resulted in 4009 records for screening, 3751 records were excluded through initial screening and 258 full texts were reviewed. Of these, 191 were excluded with reasons, leaving 67 included papers. Models included varied significantly in terms of the data used to inform projections of workforce numbers, ranging from utilisation to demand, productivity and oral health needs.
Conclusions: Approaches to workforce planning are not always based on a reliable method to match workforce numbers to population needs. This review has identified quantitative workforce planning models that aim to address population needs; however the utility of these models relies on the existence and availability of the required data. It is critical that information systems are developed to effectively capture data necessary to plan future oral healthcare workforces.
Methods: A systematic review was conducted. The following databases were searched using a structured strategy: Medline via OVID, Embase via OVID, HMIC via OVID and EconHealth via OVID. In addition, a number of grey literature databases were searched and key bodies and policy makers were contacted. Workforce planning models were included if they projected workforce numbers and were specific to oral health. No limits were placed on language or country. Initial screening of abstracts was completed by a single reviewer; secondary screening and data extraction were completed duplicate by two independent reviewers. A narrative synthesis was conducted.
Results: Searches resulted in 4009 records for screening, 3751 records were excluded through initial screening and 258 full texts were reviewed. Of these, 191 were excluded with reasons, leaving 67 included papers. Models included varied significantly in terms of the data used to inform projections of workforce numbers, ranging from utilisation to demand, productivity and oral health needs.
Conclusions: Approaches to workforce planning are not always based on a reliable method to match workforce numbers to population needs. This review has identified quantitative workforce planning models that aim to address population needs; however the utility of these models relies on the existence and availability of the required data. It is critical that information systems are developed to effectively capture data necessary to plan future oral healthcare workforces.