Comparing human resource planning models in dentistry: A case study using Canadian Armed Forces dental clinics

Shaw, Jodi L; Farmer, Julie; Coyte, Peter C.; Lawrence, Herenia P.

doi:10.1111/cdoe.12277

Cited by 4 publications

(8 citation statements)

References 7 publications

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“…The main characteristics of the 23 selected studies are provided in Table 1. These publications were from 15 different countries across the world: Australia [23], Canada [24], Chile [25], China [26,27], Japan [28], Kuwait [29], India [30], Ireland [31], Malaysia [32,33], Oman [34], Sri Lanka [35], Taiwan [36], Trinidad & Tobago [37], the United Kingdom [38][39][40][41], and the United States of America [42][43][44][45]. Seven studies were based in the WHO American Region, followed by the European (n=5) and Western Pacific Regions (n=4).…”

Section: Main Study Characteristicsmentioning

confidence: 99%

“…Dentists were the dominant oral health workforce group modelled across 13 studies [24,25,36,43,44,[26][27][28][29][30][31]34,35]. Five studies considered both dental and allied dental workforce (including therapists, hygienists, clinical technicians, denturists) in the workforce models [32,33,[38][39][40].…”

Section: Main Study Characteristicsmentioning

confidence: 99%

“…The population being modelled in the studies ranged from the full population of the country/region (n=10) [23,25,[28][29][30][34][35][36]40,43] or limited to include a specific group such as children (n=4) [26,37,42,45], adults (n=3) [31][32][33], or older people (n=1) [38]. Four studies focused on population based at a specific catchment area such as province/state (Liaoning Province, China [27]; Kentucky, USA [44]; Georgia, USA [42]) or a service/administrative zone (South Central Strategic Health Authority, England/UK [39]; Canadian Armed Forces service areas, Canada [24])…”

Section: Main Study Characteristicsmentioning

confidence: 99%

“…One article compared both the workforce to population ratio and needs based demand weighted models in the same study. [24] Four studies used a needs based model [26,[31][32][33]; and three a demand or utilization based model alone [40,42,43].…”

Section: Main Study Characteristicsmentioning

confidence: 99%

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Planning the Future Oral Health Workforce: A Rapid Review of Supply, Demand and Need Models, Data Sources and Skill Mix Considerations

Balasubramanian

Hasan

Ganbavale

et al. 2021

Preprint

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Over the last decade, there has been a renewed interest in oral health workforce planning. The purpose of this review is to examine oral health workforce planning models on supply, demand and needs, mainly in respect to their data sources, modelling technique and use of skill mix. A search was carried out on PubMed, Web of Science, and Google Scholar databases for published scientific articles on oral health workforce planning models between 2010 to 2020. No restrictions were placed on the type of modelling philosophy, and all studies including supply, demand or needs based models were included. Rapid review methods guided the review process. Twenty-three studies from 15 different countries were included in the review. A majority were from high income countries (n=17). Dentists were the sole oral health workforce group modelled in 13 studies; only five studied included skill mix (allied dental personnel) considerations. The most common application of modelling was a workforce to population ratio or a needs-based demand weighted variant. Nearly all studies presented weaknesses in modelling process due to the limitations in data sources and/or non availability of necessary data to inform oral health workforce planning. Skill mix considerations in planning models were also limited to horizontal integration within oral health professionals. Planning for the future oral health workforce is heavily reliant on quality data being available for supply, demand and needs models. Integrated methodologies that expand skill mix considerations and account for uncertainty are essential for future planning exercises.

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Section: Main Study Characteristicsmentioning

confidence: 99%

Section: Main Study Characteristicsmentioning

confidence: 99%

Section: Main Study Characteristicsmentioning

confidence: 99%

Section: Main Study Characteristicsmentioning

confidence: 99%

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Planning the Future Oral Health Workforce: A Rapid Review of Supply, Demand and Need Models, Data Sources and Skill Mix Considerations

Balasubramanian

Hasan

Ganbavale

et al. 2021

Preprint

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show abstract

“…A number of models (n = 11) were most focused on projecting numbers based on supply of dentists (Ahmed et al 2000;Lexomboon and Punyasingh 2000;Tira et al 2003;Teusner and Chrisopoulos 2008;Guthrie et al 2009;Al-Jarallah et al 2010;Cartes-Velásquez 2013;Huang et al 2013;Gallagher et al 2015; US Department of Health and Human Services 2015; Shaw et al 2017). All these models centered on dentists rather than other oral health care workers, and generally staff numbers were the units of estimate rather than whole time equivalent, except for 2 (Huang et al 2013;Shaw et al 2017). The models tended to include an estimate of demand, but this was generally limited to population numbers so that projected supply could be compared with population size as a provider:population ratio.…”

Section: Supply and Demand Populationmentioning

confidence: 99%

Workforce Planning Models for Oral Health Care: A Scoping Review

O’Malley

Macey

Allen

et al. 2020

JDR Clinical & Translational Research

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Background: For health care services to address the health care needs of populations and respond to changes in needs over time, workforces must be planned. This requires quantitative models to estimate future workforce requirements that take account of population size, oral health needs, evidence-based approaches to addressing needs, and methods of service provision that maximize productivity. The aim of this scoping review was to assess whether and how these 4 elements contribute to existing models of oral health workforce planning. Methods: A scoping review was conducted. MEDLINE, Embase, HMIC, and EconLit were searched, all via OVID. Additionally, gray literature databases were searched and key bodies and policy makers contacted. Workforce planning models were included if they projected workforce numbers and were specific to oral health. No limits were placed on country. A single reviewer completed initial screening of abstracts; 2 independent reviewers completed secondary screening and data extraction. A narrative synthesis was conducted. Results: A total of 4,009 records were screened, resulting in 42 included articles detailing 47 models. The workforce planning models varied significantly in their use of data on oral health needs, evidence-based services, and provider productivity, with most models relying on observed levels of service utilization and demand. Conclusions: This review has identified quantitative workforce planning models that aim to estimate future workforce requirements. Approaches to planning the oral health workforce are not always based on deriving workforce requirements from population oral health needs. In many cases, requirements are not linked to population needs, while in models where needs are included, they are constrained by the existence and availability of the required data. It is critical that information systems be developed to effectively capture data necessary to plan future oral health care workforces in ways that relate directly to the needs of the populations being served. Knowledge Transfer Statement: Policy makers can use the results of this study when making decisions about the planning of oral health care workforces and about the data to routinely collect within health services. Collection of suitable data will allow for the continual improvement of workforce planning, leading to a responsive health service and likely future cost savings.

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Metodologie per la determinazione del fabbisogno di personale nel management della sanità: una revisione della letteratura internazionale

Pirrotta,

Da Ros,

Cantarelli

et al. 2024

Mecosan

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I sistemi sanitari di tutto il mondo non sono nuovi agli sforzi volti a definire algoritmi efficienti per stimare il fabbisogno di personale tra professioni e setting assistenziali perché ciò è consequenziale per la quantità e la qualità dei servizi forniti. Per migliorare le iniziative a livello nazionale in Italia, particolarmente rilevanti nell'attuale contesto, è essenziale avere una comprensione completa delle metodologie internazionali utilizzate per stimare i fabbisogni di personale nella gestione sanitaria. Questo studio esamina gli strumenti più riconosciuti e ampiamente utilizzati a livello globale per la stima del fabbisogno nelle professioni sanitarie, per individuare l'eventuale esistenza di uno standard di riferimento oppure identificare le variabili chiave ricorrenti nei vari strumenti analizzati. La combinazione di una revisione esplorativa e di una sintesi sistematica di 69 articoli rivela che non esiste un solo algoritmo. La maggior parte degli algoritmi tiene conto di variabili quali la produzione attuale di servizi e l'andamento storico dell'evoluzione della quantità della forza lavoro, mentre solo una minoranza considera i modelli organizzativi. L'articolo discute le implicazioni gestionali per il miglioramento della definizione delle metodologie di stima dei fabbisogni di personale nel settore sanitario italiano.

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Comparing human resource planning models in dentistry: A case study using Canadian Armed Forces dental clinics

Cited by 4 publications

References 7 publications

Planning the Future Oral Health Workforce: A Rapid Review of Supply, Demand and Need Models, Data Sources and Skill Mix Considerations

Planning the Future Oral Health Workforce: A Rapid Review of Supply, Demand and Need Models, Data Sources and Skill Mix Considerations

Workforce Planning Models for Oral Health Care: A Scoping Review

Metodologie per la determinazione del fabbisogno di personale nel management della sanità: una revisione della letteratura internazionale

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