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Background: Many hospitalised patients require rehabilitation during recovery from acute illness. We use routine data from Electronic Health Records (EHR) to report the quantity and intensity of rehabilitation required to achieve hospital discharge, comparing patients with and without COVID-19. Methods: We performed a retrospective cohort study of consecutive adults in whom COVID-19 testing was undertaken between March 2020 and August 2021 across three acute hospitals in Scotland. We defined rehabilitation contacts (physiotherapy, occupational therapy, dietetics and speech and language therapy) from timestamped EHR data and determined contact time from a linked workforce planning dataset. Our aim was to clarify rehabilitation required to achieve hospital discharge and so we excluded patients who died during their admission, and those who did not require rehabilitation (fewer than two specialist contacts). The primary outcome was total rehabilitation time. Secondary outcomes included the number of contacts, admission to first contact, and rehabilitation minutes per day. A multivariate regression analysis for identifying patient characteristics associated with rehabilitation time included age, sex, comorbidities, and socioeconomic status. Results: We included 11,591 consecutive unique patient admissions (76 [63,85] years old, 56% female), of which 651 (6%) were with COVID-19, and 10,940 (94%) were admissions with negative testing. There were 128,646 rehabilitation contacts. Patients with COVID-19 received more than double the rehabilitation time compared to those without (365 [165, 772] vs 170 [95, 350] mins, p<0.001), and this was delivered over more specialist contacts (12 [6, 25] vs 6 [3, 11], p<0.001). Admission to first rehabilitation contact was later in patients with COVID-19 (3 [1, 5] vs 2 [1, 4] days from admission). Overall, patients with COVID-19 received fewer minutes of rehabilitation per day of admission (14.1 [9.8, 18.7] vs 15.6 [10.6, 21.3], p<0.001). In our regression analyses, older age and COVID-19 were associated with increased rehabilitation time. Conclusions: Patients with COVID received more rehabilitation contact time than those without COVID, but this was delivered less intensively and was commenced later in an admission. Rehabilitation data derived from the EHR represents a novel measure of delivered hospital care. [ABSTRACT FROM AUTHOR]

Abstract Background The composition of care teams is crucial for delivering patient-centered healthcare, yet assembling a well-balanced team remains a challenge. This difficulty stems from the intricate dynamics of team capacity, culture, context, and the demands of the job. The current literature offers limited guidance for decision-makers on how to effectively navigate these dynamics to compose a balanced care team. Methods We conducted a systematic scoping review of literature spanning from 2009 to 2022. The aim was to identify factors that significantly influence the work environment, team performance, nursing outcomes, and patient outcomes within healthcare settings. Our review focused on extracting and synthesizing evidence to uncover these influencing factors. Results Our analysis identified 35 factors that play a significant role in shaping the work environment and influencing team performance, nursing outcomes, and patient outcomes. These factors were categorized into nine key domains: workload, leadership, team composition, stress and demands, professional relationships, safety, logistics and ergonomics, autonomy and responsibility, and transparency and task clearness. Conclusions To improve patient care and nursing job satisfaction, policymakers and decision-makers can consider these influencing factors in the design and management of care teams. The findings advocate for strategic adjustments in these domains to enhance a team’s balance. Furthermore, our review underscores the need for further research to fill the identified gaps in knowledge, offering a directive for future studies into optimal care team composition. This systematic approach to team composition can significantly impact patient outcomes and nurse satisfaction, providing a roadmap for creating more effective and harmonious teams.

Abstract Background The centrality of human resources in the provision of healthcare suggests that Human Resource (HR) management and the use of Human Resource analytics – use of digital data to better understand, assess, plan and organize the workforce - can play an important role in this. However, data driven decision making in the field of human resource management is lagging, and the appropriation of HR analytics in the healthcare sector is limited. Aim The current study explores the role of HR departments and the adoption of Human Resource analytics in four municipalities in Norway to obtain insights into what influences the use or lack of use of HR analytics. Methods Empirical data were generated through qualitative interviews with fourteen individuals working in HR departments, the municipal administration, and the healthcare services. Structurational theory guided the analysis. The findings show that none of the municipalities made extensive use of data to inform decision making related to human resource management or workforce planning. Results and conclusion Three conditions hampered or made irrelevant the use of HR analytics: a decoupling between the services and HR, a weak data-culture, and HR and decision-making processes involving a plurality of stakeholders. However, there were changes underway in all municipalities related to the role of HR and HR analytics.

Background: The composition of care teams is crucial for delivering patient-centered healthcare, yet assembling a well-balanced team remains a challenge. This difficulty stems from the intricate dynamics of team capacity, culture, context, and the demands of the job. The current literature offers limited guidance for decision-makers on how to effectively navigate these dynamics to compose a balanced care team. Methods: We conducted a systematic scoping review of literature spanning from 2009 to 2022. The aim was to identify factors that significantly influence the work environment, team performance, nursing outcomes, and patient outcomes within healthcare settings. Our review focused on extracting and synthesizing evidence to uncover these influencing factors. Results: Our analysis identified 35 factors that play a significant role in shaping the work environment and influencing team performance, nursing outcomes, and patient outcomes. These factors were categorized into nine key domains: workload, leadership, team composition, stress and demands, professional relationships, safety, logistics and ergonomics, autonomy and responsibility, and transparency and task clearness. Conclusions: To improve patient care and nursing job satisfaction, policymakers and decision-makers can consider these influencing factors in the design and management of care teams. The findings advocate for strategic adjustments in these domains to enhance a team's balance. Furthermore, our review underscores the need for further research to fill the identified gaps in knowledge, offering a directive for future studies into optimal care team composition. This systematic approach to team composition can significantly impact patient outcomes and nurse satisfaction, providing a roadmap for creating more effective and harmonious teams. [ABSTRACT FROM AUTHOR]

Background: The centrality of human resources in the provision of healthcare suggests that Human Resource (HR) management and the use of Human Resource analytics – use of digital data to better understand, assess, plan and organize the workforce - can play an important role in this. However, data driven decision making in the field of human resource management is lagging, and the appropriation of HR analytics in the healthcare sector is limited. Aim: The current study explores the role of HR departments and the adoption of Human Resource analytics in four municipalities in Norway to obtain insights into what influences the use or lack of use of HR analytics. Methods: Empirical data were generated through qualitative interviews with fourteen individuals working in HR departments, the municipal administration, and the healthcare services. Structurational theory guided the analysis. The findings show that none of the municipalities made extensive use of data to inform decision making related to human resource management or workforce planning. Results and conclusion: Three conditions hampered or made irrelevant the use of HR analytics: a decoupling between the services and HR, a weak data-culture, and HR and decision-making processes involving a plurality of stakeholders. However, there were changes underway in all municipalities related to the role of HR and HR analytics. [ABSTRACT FROM AUTHOR]

Background: As the COVID-19 pandemic swept across the globe at the beginning of 2020, healthcare systems were forced to rapidly adapt and expand to meet the sudden surge in demand for intensive care services. This study is the first systematic analysis of the strategies employed by German hospitals to recruit personnel and expand bed capacities during the first wave of the pandemic, and to evaluate the effectiveness of those recruitment measures. Methods: 152 German hospitals with intensive care capacities were selected and invited to participate in an online-based retrospective survey. Factors like the geographic distribution, individual COVID burden and level of care were considered for inclusion in the sample. The data were analyzed descriptively. Results: A total of 41 hospitals participated in the survey. The additional demand for intensive care beds was met primarily by activating intensive care beds that were previously considered as non-operational in existing intensive care units (81% of respondents) and by upgrading recovery rooms (73%). The physician staffing requirements were met at approximately 75%, while the nursing staffing requirements were only met by about 45%. Staffing needs were met through reallocations/transfers (85%), staff recruitment from parental leave or retirement (49%), increased hours worked by internal staff (49%), new staff hiring (44%) and increased use of temporary staff (32%). Staff reallocations/transfers to critical care within a hospital were rated as the most effective measure. In this context, specialized personnel mostly from anesthesiology departments were appointed to intensive care medicine. Conclusions: Despite multiple recruitment efforts, the pandemic has exacerbated the nursing staff shortage. The reallocation of existing staff within hospitals was a key element in covering the staffing needs. However, additional measures and efforts are required in order to ensure that critically ill patients can be cared for without compromise. The results of this study may have important implications for healthcare providers and policymakers, offering an evidence-based foundation for responding to future public health emergencies with agility, efficiency, and success. [ABSTRACT FROM AUTHOR]

Abstract Background The incidence of pancreatic cancer is rising. With improvements in knowledge for screening and early detection, earlier detection of pancreatic cancer will continue to be more common. To support workforce planning, our aim is to perform a model-based analysis that simulates the potential impact on the healthcare workforce, assuming an earlier diagnosis of pancreatic cancer. Methods We developed a simulation model to estimate the demand (i.e. new cases of pancreatic cancer) and supply (i.e. the healthcare workforce including general surgeons, medical oncologists, radiation oncologists, pain medicine physicians, and palliative care physicians) between 2023 and 2027 in Victoria, Australia. The model compares the current scenario to one in which pancreatic cancer is diagnosed at an earlier stage. The incidence of pancreatic cancer in Victoria, five-year survival rates, and Victoria’s population size were obtained from Victorian Cancer Registry, Cancer Council NSW, and Australian Bureau of Statistics respectively. The healthcare workforce data were sourced from the Australian Government Department of Health and Aged Care’s Health Workforce Data. The model was constructed at the remoteness level. We analysed the new cases and the number of healthcare workforce by profession together to assess the impact on the healthcare workforce. Results In the status quo, over the next five years, there will be 198 to 220 stages I-II, 297 to 330 stage III, and 495 to 550 stage IV pancreatic cancer cases diagnosed annually, respectively. Assuming 20–70% of the shift towards pancreatic cancer’s earlier diagnosis (shifting from stage IV to stages I-II pancreatic cancer within one year), the stages I-II cases could increase to 351 to 390 or 598 to 665 per year. The shift to early diagnosis led to substantial survival gains, translating into an additional 284 or 795 out of 5246 patients with pancreatic cancer remaining alive up to year 5 post-diagnosis. Workforce supply decreases significantly by the remoteness levels, and remote areas face a shortage of key medical professionals registered in delivering pancreatic cancer care, suggesting travel necessities by patients or clinicians. Conclusion Improving the early detection and diagnosis of pancreatic cancer is expected to bring significant survival benefits, although there are workforce distribution imbalances in Victoria that may affect the ability to achieve the anticipated survival gain.

Abstract Background Many health systems embrace the normative principle that the supply of health services ought to be based on the need for healthcare. However, a theoretically grounded framework to operationalize needs-based supply of healthcare remains elusive. The aim of this paper is to critically assess current methodologies that quantify needs-based supply of physicians and identify potential gaps in approaches for physician planning. To this end, we propose a set of criteria for consideration when estimating needs-based supply. Methods We conducted searches in three electronic bibliographic databases until March 2020 supplemented by targeted manual searches on national and international websites to identify studies in high-resource settings that quantify needs-based supply of physicians. Studies that exclusively focused on forecasting methods of physician supply, on inpatient care or on healthcare professionals other than physicians were excluded. Additionally, records that were not available in English or German were excluded to avoid translation errors. The results were synthesized using a framework of study characteristics in addition to the proposed criteria for estimating needs-based physician supply. Results 18 quantitative studies estimating population need for physicians were assessed against our criteria. No study met all criteria. Only six studies sought to examine the conceptual dependency between need, utilization and supply. Apart from extrapolations, simulation models were applied most frequently to estimate needs-based supply. 12 studies referred to the translation of need for services with respect to a physician’s productivity, while the rest adapted existing population-provider-ratios. Prospective models for estimating future care needs were largely based on demographic predictions rather than estimated trends in morbidity and new forms of care delivery. Conclusions The methodological review shows distinct heterogeneity in the conceptual frameworks, validity of data basis and modeling approaches of current studies in high-resource settings on needs-based supply of physicians. To support future estimates of needs-based supply, this review provides a workable framework for policymakers in charge of health workforce capacity planning.

Background: Many health systems embrace the normative principle that the supply of health services ought to be based on the need for healthcare. However, a theoretically grounded framework to operationalize needs-based supply of healthcare remains elusive. The aim of this paper is to critically assess current methodologies that quantify needs-based supply of physicians and identify potential gaps in approaches for physician planning. To this end, we propose a set of criteria for consideration when estimating needs-based supply. Methods: We conducted searches in three electronic bibliographic databases until March 2020 supplemented by targeted manual searches on national and international websites to identify studies in high-resource settings that quantify needs-based supply of physicians. Studies that exclusively focused on forecasting methods of physician supply, on inpatient care or on healthcare professionals other than physicians were excluded. Additionally, records that were not available in English or German were excluded to avoid translation errors. The results were synthesized using a framework of study characteristics in addition to the proposed criteria for estimating needs-based physician supply. Results: 18 quantitative studies estimating population need for physicians were assessed against our criteria. No study met all criteria. Only six studies sought to examine the conceptual dependency between need, utilization and supply. Apart from extrapolations, simulation models were applied most frequently to estimate needs-based supply. 12 studies referred to the translation of need for services with respect to a physician's productivity, while the rest adapted existing population-provider-ratios. Prospective models for estimating future care needs were largely based on demographic predictions rather than estimated trends in morbidity and new forms of care delivery. Conclusions: The methodological review shows distinct heterogeneity in the conceptual frameworks, validity of data basis and modeling approaches of current studies in high-resource settings on needs-based supply of physicians. To support future estimates of needs-based supply, this review provides a workable framework for policymakers in charge of health workforce capacity planning. [ABSTRACT FROM AUTHOR]

Background: Understanding the influences on healthcare professionals' career choices and progression can inform interventions to improve workforce retention. Retention of health professionals is a high priority worldwide, in order to maintain expertise and meet the needs of national populations. In the UK, investment in clinical scientists' pre-registration education is high and the need to retain motivated scientists recognised. Methods: We conducted a mixed methods study to investigate the career choices and progression of early career clinical scientists. First job sector and salary of trainees who completed the UK pre-registration Scientist Training Programme (STP) between 2014 and 2019 were analysed using descriptive statistics and Chi-Squared tests. Semi-structured interviews conducted with volunteer practising clinical scientists who completed the programme in 2015 or 2016 were analysed thematically and reviewed for alignment with theories for understanding career choice and workforce retention. Results: Most scientists who completed the STP between 2014 and 2019 obtained a post in the UK National Health Service (NHS) and achieved the expected starting salary. Life scientists were more likely to work in non-NHS healthcare settings than other scientific divisions; and physiological scientists less likely to achieve the expected starting salary. Experiences during training influenced career choice and progression 0–3 years post qualification, as did level of integration of training places with workforce planning. Specialty norms, staff turnover, organisational uncertainty and geographical preferences influenced choices in both the short (0–3 years) and longer term (5 + years). Interviewees reported a strong commitment to public service; and some could foresee that these priorities would influence future decisions about applying for management positions. These factors aligned with the components of job embeddedness theory, particularly that of 'fit'. Conclusions: Training experiences, personal values, specialty norms and organisational factors all influence UK clinical scientists' early career choices and progression. Job embeddedness theory provides a useful lens through which to explore career choice and progression; and suggests types of intervention that can enhance the careers of this essential group. Interventions need to take account of variations between different scientific specialties. [ABSTRACT FROM AUTHOR]

Abstract Background Strong and effective workforce models are essential for improving comprehensive Indigenous primary healthcare service (PHC) provision to Indigenous peoples in Canada, Australia, New Zealand and the USA (CANZUS nations). This review systematically scoped the literature for studies that described or evaluated models and systems that support the sustainability, capacity or growth of the Indigenous PHC workforce to provide effective PHC provision. Methods Eleven databases, 10 websites and clearinghouses, and the reference lists of 5 review articles were searched for relevant studies from CANZUS nations published in English from 2000 to 2017. A process of thematic analysis was utilised to identify key conditions, strategies and outcomes of Indigenous PHC workforce development reported in the literature. Results Overall, 28 studies were found. Studies reported enabling conditions for workforce development as government funding and appropriate regulation, support and advocacy by professional organisations; community engagement; PHC leadership, supervision and support; and practitioner Indigeneity, motivation, power equality and wellbeing. Strategies focused on enhancing recruitment and retention; strengthening roles, capacity and teamwork; and improving supervision, mentoring and support. Only 12/28 studies were evaluations, and these studies were generally of weak quality. These studies reported impacts of improved workforce sustainability, workforce capacity, resourcing/growth and healthcare performance improvements. Conclusions PHCs can strengthen their workforce models by bringing together healthcare providers to consider how these strategies and enabling conditions can be improved to meet the healthcare and health needs of the local community. Improvement is also needed in the quality of evidence relating to particular strategies to guide practice.

Abstract Background Historically, governmental hospital organisation consisted in a heterogeneous distribution of staff and a fragmented logistical organisation without cross-functionality or sharing of resources between departments. This organisation could not last in a context of an evolving healthcare environment, changing patient profiles and hospital expenditure constraints. Cost-effective workforce regulation for optimal patient quality of care was urgently needed. The purpose of the study was to describe the reorganization that led to resource management no longer based on what has been achieved but based on a daily measured workload. Methods This prospective study used nursing intensity indicator, mirroring patient care needs, which was reported daily using VALPAReSO® software. Indirect care activities were recorded in departments of medicine, surgery and obstetrics. Based on data collected in 2012, a new organisation strategy was implemented and evaluated in 2015. Results Nursing intensity indicator analysis led to a reallocation of workforce per department, and the reinforcement unit (float pool) was managed based on this decision-aid tool for replacement and daily adequate staffing. The healthcare workflow audit resulted in the revision of five working tasks: time spent on handover, working time management, connections between services and the pharmacy, housekeeping, and food management. The reorganization took place at the same time as the transition to the development of very short-term care, resulting in a decrease in the number of full inpatient beds, which were therefore mainly occupied by heavier care profile patients. With the integrated strategy, this transition was achieved with constant staffing, and good overall patient satisfaction and working conditions were maintained. Conclusion The reorganisation strategy was managed in a context of institutional commitment, coaching leadership built on close manager-employee interaction, a defragmented management between healthcare and all service providers, and a seamlessly dissemination and sharing of indicator information between healthcare managers, nurses and healthcare assistants. The process optimization allowed a better allocation of tasks and enabled nurses to refocus on patient care. Nursing intensity and indirect care indicators, when widely accepted, can be used as decision support tools for daily adequate staffing.

Abstract Background Improving the health of rural populations requires developing a medical workforce with the right skills and a willingness to work in rural areas. A novel strategy for achieving this aim is to align medical training distribution with community need. This research describes an approach for planning and monitoring the distribution of general practice (GP) training posts to meet health needs across a dispersed geographic catchment. Methods An assessment of the location of GP registrars in a large catchment of rural North West Queensland (across 11 sub-regions) in 2017 was made using national workforce supply, rurality and other indicators. These included (1): Index of Access –spatial accessibility (2); 10-year District of Workforce Shortage (DWS) (3); MMM (Modified Monash Model) rurality (4); SEIFA (Socio-Economic Indicator For Areas) (5); Indigenous population and (6) Population size. Distribution was determined relative to GP workforce supply measures and population health needs in each health sub-region of the catchment. An expert panel verified the approach and reliability of findings and discussed the results to inform planning. Results 378 registrars and 582 supervisors were well-distributed in two sub-regions; in contrast the distribution was below expected levels in three others. Almost a quarter of registrars (24%) were located in the poorest access areas (Index of Access) compared with 15% of the population located in these areas. Relative to the population size, registrars were proportionally over-represented in the most rural towns, those consistently rated as DWS or those with the poorest SEIFA value and highest Indigenous proportion. Conclusions Current regional distribution was good, but individual town-level data further enabled the training provider to discuss the nuance of where and why more registrars (or supervisors) may be needed. The approach described enables distributed workforce planning and monitoring applicable in a range of contexts, with increased sensitivity for registrar distribution planning where most needed, supporting useful discussions about the potential causes and solutions. This evidence-based approach also enables training organisations to engage with local communities, health services and government to address the sustainable development of the long-term GP workforce in these towns.

Abstract Background Workforce planning in the British healthcare system (NHS) is associated with significant costs of agency staff employment. The introduction of a novel software (ABG) as a ‘people to people economy’ (P2PE) platform for temporary staff recruitment offers a potential solution to this problem. Consequently, the focus of this study was twofold – primarily to explore the locum doctor landscape, and secondarily to evaluate the implementation of P2PE in the healthcare industry. Methods Documentary analysis was conducted alongside thirteen semi structured interviews across five informant groups: two industry experts, two healthcare consultants, an executive director, two speciality managers and six doctors. Results We found that locum doctors are indispensable to covering workforce shortages, yet existing planning and recruitment practices were found to be inefficient, inconsistent and lacking transparency. Contrarily, mobile-first solutions such as ABG seem to secure higher convenience, better transparency, cost and time efficiency. We also identified factors facilitating the successful diffusion of ABG; these were in line with classically cited characteristics of innovation such as trialability, observability, and scope for local reinvention. Drawing upon the concept of value-based healthcare coupled with the analysis of our findings led to the development of Information Exchange System (IES) model, a comprehensive framework allowing a thorough comparison of recruitment practices in healthcare. Conclusion IES was used to evaluate ABG and its diffusion against other recruitment methods and ABG was found to outperform its alternatives, thus suggesting its potential to solve the staffing and cost crisis at the chosen hospital.

Background: A goal of health workforce planning is to have the most appropriate workforce available to meet prevailing needs. However, this is a difficult task when considering integrated care, as future workforces may require different numbers, roles and skill mixes than those at present. With this uncertainty and large variations in what constitutes integrated care, current health workforce policy and planning processes are poorly placed to respond. In order to address this issue, we present a scenario-based workforce planning approach.Methods: We propose a novel mixed methods design, incorporating content analysis, scenario methods and scenario analysis through the use of a policy Delphi. The design prescribes that data be gathered from workforce documents and studies that are used to develop scenarios, which are then assessed by a panel of suitably qualified people. Assessment consists of evaluating scenario desirability, feasibility and validity and includes a process for indicating policy development opportunities.Results: We confirmed our method using data from New Zealand's Older Persons Health sector and its workforce. Three scenarios resulted, one that reflects a normative direction and two alternatives that reflect key sector workforce drivers and trends. One of these, based on alternative assumptions, was found to be more desirable by the policy Delphi panel. The panel also found a number of favourable policy proposals.Conclusions: The method shows that through applying techniques that have been developed to accommodate uncertainty, health workforce planning can benefit when confronting issues associated with integrated care. The method contributes to overcoming significant weaknesses of present health workforce planning approaches by identifying a wider range of plausible futures and thematic kernels for policy development. The use of scenarios provides a means to contemplate future situations and provides opportunities for policy rehearsal and reflection. [ABSTRACT FROM AUTHOR]

Background: Mental illness is prevalent across the globe and affects multiple aspects of life. Despite advances in treatment, there is little evidence that prevalence rates of mental illness are falling. While the prevention of cardiovascular disease and cancers are common in the policy dialogue and in service delivery, the prevention of mental illness remains a neglected area. There is accumulating evidence that mental illness is at least partially preventable, with increasing recognition that its antecedents are often found in infancy, childhood, adolescence and youth, creating multiple opportunities into young adulthood for prevention. Developing valid and reproducible methods for translating the evidence base in mental illness prevention into actionable policy recommendations is a crucial step in taking the prevention agenda forward. Method: Building on an aetiological model of adult mental illness that emphasizes the importance of intervening during infancy, childhood, adolescence and youth, we adapted a workforce and service planning framework, originally applied to diabetes care, to the analysis of the workforce and service structures required for best-practice prevention of mental illness. Results: The resulting framework consists of 6 steps that include identifying priority risk factors, profiling the population in terms of these risk factors to identify at-risk groups, matching these at-risk groups to best-practice interventions, translation of these interventions to competencies, translation of competencies to workforce and service estimates, and finally, exploring the policy implications of these workforce and services estimates. The framework outlines the specific tasks involved in translating the evidence-base in prevention, to clearly actionable workforce, service delivery and funding recommendations. Conclusions: The framework describes the means to deliver mental illness prevention that the literature indicates is achievable, and is the basis of an ongoing project to model the workforce and service structures required for mental illness prevention. [ABSTRACT FROM AUTHOR]

Background: Improving the health of rural populations requires developing a medical workforce with the right skills and a willingness to work in rural areas. A novel strategy for achieving this aim is to align medical training distribution with community need. This research describes an approach for planning and monitoring the distribution of general practice (GP) training posts to meet health needs across a dispersed geographic catchment.Methods: An assessment of the location of GP registrars in a large catchment of rural North West Queensland (across 11 sub-regions) in 2017 was made using national workforce supply, rurality and other indicators. These included (1): Index of Access -spatial accessibility (2); 10-year District of Workforce Shortage (DWS) (3); MMM (Modified Monash Model) rurality (4); SEIFA (Socio-Economic Indicator For Areas) (5); Indigenous population and (6) Population size. Distribution was determined relative to GP workforce supply measures and population health needs in each health sub-region of the catchment. An expert panel verified the approach and reliability of findings and discussed the results to inform planning.Results: 378 registrars and 582 supervisors were well-distributed in two sub-regions; in contrast the distribution was below expected levels in three others. Almost a quarter of registrars (24%) were located in the poorest access areas (Index of Access) compared with 15% of the population located in these areas. Relative to the population size, registrars were proportionally over-represented in the most rural towns, those consistently rated as DWS or those with the poorest SEIFA value and highest Indigenous proportion.Conclusions: Current regional distribution was good, but individual town-level data further enabled the training provider to discuss the nuance of where and why more registrars (or supervisors) may be needed. The approach described enables distributed workforce planning and monitoring applicable in a range of contexts, with increased sensitivity for registrar distribution planning where most needed, supporting useful discussions about the potential causes and solutions. This evidence-based approach also enables training organisations to engage with local communities, health services and government to address the sustainable development of the long-term GP workforce in these towns. [ABSTRACT FROM AUTHOR]

Background: Workforce planning in the British healthcare system (NHS) is associated with significant costs of agency staff employment. The introduction of a novel software (ABG) as a 'people to people economy' (P2PE) platform for temporary staff recruitment offers a potential solution to this problem. Consequently, the focus of this study was twofold - primarily to explore the locum doctor landscape, and secondarily to evaluate the implementation of P2PE in the healthcare industry.Methods: Documentary analysis was conducted alongside thirteen semi structured interviews across five informant groups: two industry experts, two healthcare consultants, an executive director, two speciality managers and six doctors.Results: We found that locum doctors are indispensable to covering workforce shortages, yet existing planning and recruitment practices were found to be inefficient, inconsistent and lacking transparency. Contrarily, mobile-first solutions such as ABG seem to secure higher convenience, better transparency, cost and time efficiency. We also identified factors facilitating the successful diffusion of ABG; these were in line with classically cited characteristics of innovation such as trialability, observability, and scope for local reinvention. Drawing upon the concept of value-based healthcare coupled with the analysis of our findings led to the development of Information Exchange System (IES) model, a comprehensive framework allowing a thorough comparison of recruitment practices in healthcare.Conclusion: IES was used to evaluate ABG and its diffusion against other recruitment methods and ABG was found to outperform its alternatives, thus suggesting its potential to solve the staffing and cost crisis at the chosen hospital. [ABSTRACT FROM AUTHOR]