Department of Dentistry, Radboud University Medical Center, Nijmegen, The Netherlands.
Estonian Dental Association, Tallinn, Estonia.
Hum Resour Health. 2024 Nov 8;22(1):73. doi: 10.1186/s12960-024-00957-2.
Current methods for oral health workforce planning lack responsiveness to dynamic needs, hampering efficiency, equity and sustainability. Effective workforce planning is vital for resilient health care systems and achieving universal health coverage. Given this context, we developed and operationalised a needs-adaptive oral health workforce planning model and explored the potential of various future scenarios.
Using publicly available data, including the Special Eurobarometer 330 Oral Health Survey, we applied the model in a hypothetical context focusing on the Dutch population's dental needs from 2022 to 2050. We compared current and future provider supply and requirement and examined, in addition to a base case scenario, several alternative scenarios. These included epidemiological transition scenarios with different oral health morbidity trajectories, skill-mix scenarios with independent oral hygienists conducting check-ups and multiple dental student intake and training duration (5 instead of 6 years) scenarios.
Based on the aforementioned historical data, our model projects that provider requirement will exceed supply for the planning period. If the percentage of people having all natural teeth increases by 10% or 20% in 2032, 34 or 68 additional full-time equivalent (FTE) dentists will be required, respectively, compared to the base case scenario. In the skill-mix scenario, the model indicates that prioritising oral hygienists for check-ups and shifting dentists' focus to primarily complex care could address population needs more efficiently. Among the student intake and training duration scenarios, increasing intake to 375 and, to a lesser extent, reducing training to 5 years is projected to most effectively close the provider gap.
The study underscores the importance of understanding oral health morbidity trajectories for effective capacity planning. Due to limited dental epidemiological data, projections carry substantial uncertainty. Currently, demand for FTE dentists seems to exceed supply, though this may vary with epidemiological changes. Skill-mix strategies could offer efficiency gains by redistributing tasks, while adjustments in dental intake and training duration could also help address the requirement-supply gap. Resolving dentistry workforce challenges requires a multifaceted approach, including strengthening oral epidemiology projections, addressing the root causes of dental health issues and prioritising harmonious dental public health and general practice prevention measures.
目前的口腔卫生人力规划方法缺乏对动态需求的响应能力,从而降低了效率、公平性和可持续性。有效的劳动力规划对于有弹性的医疗保健系统和实现全民健康覆盖至关重要。鉴于此,我们开发并实施了一种需求自适应口腔卫生劳动力规划模型,并探讨了各种未来情景的潜力。
使用公开可用的数据,包括特别 Eurobarometer 330 口腔健康调查,我们在一个假设的背景下应用了该模型,重点是荷兰人口 2022 年至 2050 年的牙科需求。我们比较了当前和未来的提供者供应和需求,并在基础案例情景之外,还研究了几种替代情景。这些情景包括具有不同口腔健康发病率轨迹的流行病学过渡情景、独立口腔卫生员进行检查的技能组合情景以及多个牙科学生入学和培训时间(5 年而不是 6 年)情景。
根据上述历史数据,我们的模型预测在规划期内,提供者的需求将超过供应。如果 2032 年有 10%或 20%的人拥有所有天然牙齿,与基础案例情景相比,分别需要增加 34 或 68 个全职当量(FTE)牙医。在技能组合情景中,该模型表明,优先考虑口腔卫生员进行检查并将牙医的重点转移到主要的复杂护理上,可以更有效地满足人口需求。在学生入学和培训时间情景中,增加入学人数至 375 人,在较小程度上减少培训至 5 年,预计将最有效地缩小提供者差距。
该研究强调了了解口腔健康发病率轨迹对于有效能力规划的重要性。由于牙科流行病学数据有限,预测存在很大的不确定性。目前,对 FTE 牙医的需求似乎超过了供应,但这可能因流行病学变化而有所不同。技能组合策略可以通过重新分配任务来提高效率,而调整牙科入学和培训时间也可以帮助解决供需差距。解决牙科劳动力挑战需要采取多方面的方法,包括加强口腔流行病学预测、解决牙科健康问题的根本原因以及优先考虑和谐的牙科公共卫生和一般实践预防措施。