What can we learn from general practitioners who left Spain? A mixed methods international study.

BACKGROUND: International mobility of health workforce affects the performance of health systems and has major relevance in human resources for health policy and planning. To date, there has been little research exploring the reasons why general practitioners (GPs) migrate. This mixed methods study aimed to investigate the reasons why Spain-trained GPs migrate and develop GP retention and recruitment health policy recommendations relevant to Spanish primary care. METHODS: The study followed an explanatory sequential mixed methods study design combining surveys with semi-structured interviews and focus groups with GPs who qualified in Spain and were living overseas at the time of the study. The survey data examined the reasons why GPs left Spain and their intention to return and were analysed using quantitative methods. The transcripts from interviews and focus groups centred on GPs' insights to enhance retention and recruitment in Spain and were analysed thematically. RESULTS: The survey had 158 respondents with an estimated 25.4% response rate. Insufficient salary (75.3%), job insecurity and temporality (67.7%), excessive workload (67.7%), poor primary care governance (55.7%), lack of flexibility in the workplace (43.7%) and personal circumstances (43.7%) were the main reasons for leaving Spain. Almost half of the respondents (48.7%) would consider returning to Spanish general practice if their working conditions improved. Interviews and focus groups with respondents (n = 24) pointed towards the need to improve the quality of employment contracts, working conditions, opportunities for professional development, and governance in primary care for effective retention and recruitment. CONCLUSION: Efforts to improve GP retention and recruitment in Spain should focus on salary, job security, flexibility, protected workload, professional development, and governance. We draw ten GP retention and recruitment recommendations expected to inform urgent policy action to tackle existing and predicted GP shortages in Spanish primary care.

An Early Warning Risk Prediction Tool (RECAP-V1) for Patients Diagnosed With COVID-19: Protocol for a Statistical Analysis Plan.

BACKGROUND: Since the start of the COVID-19 pandemic, efforts have been made to develop early warning risk scores to help clinicians decide which patient is likely to deteriorate and require hospitalization. The RECAP (Remote COVID-19 Assessment in Primary Care) study investigates the predictive risk of hospitalization, deterioration, and death of patients with confirmed COVID-19, based on a set of parameters chosen through a Delphi process performed by clinicians. We aim to use rich data collected remotely through the use of electronic data templates integrated in the electronic health systems of several general practices across the United Kingdom to construct accurate predictive models. The models will be based on preexisting conditions and monitoring data of a patient's clinical parameters (eg, blood oxygen saturation) to make reliable predictions as to the patient's risk of hospital admission, deterioration, and death. OBJECTIVE: This statistical analysis plan outlines the statistical methods to build the prediction model to be used in the prioritization of patients in the primary care setting. The statistical analysis plan for the RECAP study includes the development and validation of the RECAP-V1 prediction model as a primary outcome. This prediction model will be adapted as a three-category risk score split into red (high risk), amber (medium risk), and green (low risk) for any patient with suspected COVID-19. The model will predict the risk of deterioration and hospitalization. METHODS: After the data have been collected, we will assess the degree of missingness and use a combination of traditional data imputation using multiple imputation by chained equations, as well as more novel machine-learning approaches to impute the missing data for the final analysis. For predictive model development, we will use multiple logistic regression analyses to construct the model. We aim to recruit a minimum of 1317 patients for model development and validation. We will then externally validate the model on an independent dataset of 1400 patients. The model will also be applied for multiple different datasets to assess both its performance in different patient groups and its applicability for different methods of data collection. RESULTS: As of May 10, 2021, we have recruited 3732 patients. A further 2088 patients have been recruited through the National Health Service Clinical Assessment Service, and approximately 5000 patients have been recruited through the DoctalyHealth platform. CONCLUSIONS: The methodology for the development of the RECAP-V1 prediction model as well as the risk score will provide clinicians with a statistically robust tool to help prioritize COVID-19 patients. TRIAL REGISTRATION: ClinicalTrials.gov NCT04435041; https://clinicaltrials.gov/ct2/show/NCT04435041. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/30083.

Predicting Risk of Hospital Admission in Patients With Suspected COVID-19 in a Community Setting: Protocol for Development and Validation of a Multivariate Risk Prediction Tool.

BACKGROUND: During the pandemic, remote consultations have become the norm for assessing patients with signs and symptoms of COVID-19 to decrease the risk of transmission. This has intensified the clinical uncertainty already experienced by primary care clinicians when assessing patients with suspected COVID-19 and has prompted the use of risk prediction scores, such as the National Early Warning Score (NEWS2), to assess severity and guide treatment. However, the risk prediction tools available have not been validated in a community setting and are not designed to capture the idiosyncrasies of COVID-19 infection. OBJECTIVE: The objective of this study is to produce a multivariate risk prediction tool, RECAP-V1 (Remote COVID-19 Assessment in Primary Care), to support primary care clinicians in the identification of those patients with COVID-19 that are at higher risk of deterioration and facilitate the early escalation of their treatment with the aim of improving patient outcomes. METHODS: The study follows a prospective cohort observational design, whereby patients presenting in primary care with signs and symptoms suggestive of COVID-19 will be followed and their data linked to hospital outcomes (hospital admission and death). Data collection will be carried out by primary care clinicians in four arms: North West London Clinical Commissioning Groups (NWL CCGs), Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), Covid Clinical Assessment Service (CCAS), and South East London CCGs (Doctaly platform). The study involves the use of an electronic template that incorporates a list of items (known as RECAP-V0) thought to be associated with disease outcome according to previous qualitative work. Data collected will be linked to patient outcomes in highly secure environments. We will then use multivariate logistic regression analyses for model development and validation. RESULTS: Recruitment of participants started in October 2020. Initially, only the NWL CCGs and RCGP RSC arms were active. As of March 24, 2021, we have recruited a combined sample of 3827 participants in these two arms. CCAS and Doctaly joined the study in February 2021, with CCAS starting the recruitment process on March 15, 2021. The first part of the analysis (RECAP-V1 model development) is planned to start in April 2021 using the first half of the NWL CCGs and RCGP RSC combined data set. Posteriorly, the model will be validated with the rest of the NWL CCGs and RCGP RSC data as well as the CCAS and Doctaly data sets. The study was approved by the Research Ethics Committee on May 27, 2020 (Integrated Research Application System number: 283024, Research Ethics Committee reference number: 20/NW/0266) and badged as National Institute of Health Research Urgent Public Health Study on October 14, 2020. CONCLUSIONS: We believe the validated RECAP-V1 early warning score will be a valuable tool for the assessment of severity in patients with suspected COVID-19 in the community, either in face-to-face or remote consultations, and will facilitate the timely escalation of treatment with the potential to improve patient outcomes. TRIAL REGISTRATION: ISRCTN registry ISRCTN13953727; https://www.isrctn.com/ISRCTN13953727. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/29072.

Reorganisation of GP surgeries during the COVID-19 outbreak: analysis of guidelines from 15 countries.

BACKGROUND: General practitioners (GPs) play a key role in managing the COVID-19 outbreak. However, they may encounter difficulties adapting their practices to the pandemic. We provide here an analysis of guidelines for the reorganisation of GP surgeries during the beginning of the pandemic from 15 countries. METHODS: A network of GPs collaborated together in a three-step process: (i) identification of key recommendations of GP surgery reorganisation, according to WHO, CDC and health professional resources from health care facilities; (ii) collection of key recommendations included in the guidelines published in 15 countries; (iii) analysis, comparison and synthesis of the results. RESULTS: Recommendations for the reorganisation of GP surgeries of four types were identified: (i) reorganisation of GP consultations (cancelation of non-urgent consultations, follow-up via e-consultations), (ii) reorganisation of GP surgeries (area partitioning, visual alerts and signs, strict hygiene measures), (iii) reorganisation of medical examinations by GPs (equipment, hygiene, partial clinical examinations, patient education), (iv) reorganisation of GP staff (equipment, management, meetings, collaboration with the local community). CONCLUSIONS: We provide here an analysis of guidelines for the reorganisation of GP surgeries during the beginning of the COVID-19 outbreak from 15 countries. These guidelines focus principally on clinical care, with less attention paid to staff management, and the area of epidemiological surveillance and research is largely neglected. The differences of guidelines between countries and the difficulty to apply them in routine care, highlight the need of advanced research in primary care. Thereby, primary care would be able to provide recommendations adapted to the real-world settings and with stronger evidence, which is especially necessary during pandemics.

The role of the state in financing and regulating primary care in Europe: a taxonomy.

Traditional health systems typologies were based on health system financing type, such as the well-known OECD typology. However, the number of dimensions captured in classifications increased to reflect health systems complexity. This study aims to develop a taxonomy of primary care (PC) systems based on the actors involved (state, societal and private) and mechanisms used in governance, financing and regulation, which conceptually represents the degree of decentralisation of functions. We use nonlinear canonical correlations analysis and agglomerative hierarchical clustering on data obtained from the European Observatory on Health Systems and Policy and informants from 24 WHO European Region countries. We obtain four clusters: 1) Bosnia Herzegovina, Czech Republic, Germany, Slovakia and Switzerland: corporatist and/or fragmented PC system, with state involvement in PC supply regulation, without gatekeeping; 2) Greece, Ireland, Israel, Malta, Sweden, and Ukraine: public and (re)centralised PC financing and regulation with private involvement, without gatekeeping; 3) Finland, Norway, Spain and United Kingdom: public financing and devolved regulation and organisation of PC, with gatekeeping; and 4) Bulgaria, Croatia, France, North Macedonia, Poland, Romania, Serbia, Slovenia and Turkey: public and deconcentrated with professional involvement in supply regulation, and gatekeeping. This taxonomy can serve as a framework for performance comparisons and a means to analyse the effect that different actors and levels of devolution or fragmentation of PC delivery may have in health outcomes.

Challenges in the implementation of primary health care reforms: a qualitative analysis of stakeholders' views in Turkey.

OBJECTIVES: This study aims to assess the implementation of the Family Medicine Programme (FMP), which has taken place in Turkey from 2005 to 2010 as a set of comprehensive primary health care (PHC) reforms and involved changes in professional organisation (eg, family medicine specialisation) and service provision (eg, patients' registration list). Our particular interest is to identify the challenges and limitations that PHC physicians and academicians have encountered in the implementation of the FMP which could have influenced the delivery of care and utilisation of services. DESIGN: We applied the framework method to analyse data obtained through semi-structured interviews conducted in the field. This qualitative approach involved the categorisation of raw data into a predefined framework, which comprised challenges and limitations identified in the literature, and the emergence of a new framework, whose categories corresponded to challenges and limitations identified through thematic analysis of our data. SETTING: PHC centres and academic departments from five Turkish provinces. PARTICIPANTS: PHC physicians and academicians involved in training and/or research were invited to participate. 20 participants agreed to take part and, due to schedule limitations, 15 participants (seven PHC physicians and eight academicians) completed the interviews. RESULTS: Shortcomings in the planning of the reforms, inadequate commitment to integration of PHC in the system and collateral effects of a market model in healthcare emerged as limitations to successful FMP implementation. Uncertainty about care quality and physicians' ethical values as well as perceptions of organisational injustice among healthcare workers were contributing challenges. CONCLUSIONS: A systems thinking approach in the FMP design and implementation could help foresee and address these limitations. In decentralisation processes, such as FMP, shared governance by including PHC stakeholders in policy-making and planning could alleviate misalignment of interests and positively affect PHC performance, for example, by removing barriers to gatekeeping implementation.

The impact of governance in primary health care delivery: a systems thinking approach with a European panel.

BACKGROUND: Enhancing primary health care (PHC) is considered a policy priority for health systems strengthening due to PHC's ability to provide accessible and continuous care and manage multimorbidity. Research in PHC often focuses on the effects of specific interventions (e.g. physicians' contracts) in health care outcomes. This informs narrowly designed policies that disregard the interactions between the health functions (e.g. financing and regulation) and actors involved (i.e. public, professional, private), and their impact in care delivery and outcomes. The purpose of this study is to analyse the interactions between PHC functions and their impact in PHC delivery, particularly in providers' behaviour and practice organisation. METHODS: Following a systems thinking approach with data obtained through a three-round European Delphi process, we developed a framework that captures (1) the interactions between PHC functions by analysing correlations between PHC characteristics of participating countries, (2) how actors involved shaped these interactions by identifying the actor and level of devolution (or fragmentation) in the analysis, and (3) their potential effect on care delivery by exploring panellists' opinions. RESULTS: A total of 59 panellists from 24 countries participated in the first round and 76% of the initial panellists (22 countries) completed the last round. Findings show correlations between governance, financing and regulation based on their degree of decentralisation. This is supported by panellists, who agreed that the actors involved in health system governance determine the type of PHC financing (e.g. ownership or payment mechanisms) and regulation (e.g. competences or gatekeeping), and this may impact care delivery and outcomes. Governance in our framework is an overarching function whose impact in PHC delivery is mediated through the degree of decentralisation (both delegation and devolution) of PHC financing and regulation. CONCLUSIONS: The application of this approach in policy implementation assessment intends to uncover limitations due to poor accountability and commitment to shared objectives. Its application in the design of health strategies helps foresee (and prevent) undesired or unexpected effects of narrow interventions. This approach will assist in the development of the realistic and long-term policies required for health systems strengthening.