Managing healthcare services: Are professionals ready to play the role of manager?

Managers' perceptions of organizational readiness for change within disability healthcare: a Swedish national study with an embedded mixed-methods approach

BACKGROUND

People with disabilities experience significant health inequities compared with the general population. Addressing these inequities requires the development and implementation of tailored interventions, but a gap often exists between recommended best practices and the actual care provided. Successful implementation is complex, involving multiple organizational factors. Assessing organizational readiness for change is crucial to overcome barriers and improve health outcomes for people with disabilities. This study aims to examine managers' perceptions of their organization's readiness for change regarding the implementation of interventions within disability healthcare in Sweden.

METHODS

This descriptive cross-sectional study employs an embedded mixed-methods approach. The primary approach for the overall study is based on quantitative data, while qualitative data is analyzed to provide supplementary deepened information. Both types of data were collected simultaneously through a web-based survey. The data analysis involves various statistical techniques for the quantitative data and inductive content analysis for the qualitative data.

RESULTS

Several key factors influence managers' perceptions of their organization's readiness for change, including gender, age, tenure, organizational type, managerial level, and experience. Enabling factors for implementation include trust-based leadership, staff involvement, motivation, and engagement. Barriers include complex processes, lack of support, resistance and fear, and insufficient time and resources.

CONCLUSIONS

This study highlights the complexity of organizational readiness for disability healthcare interventions, shaped by both individual and organizational factors. In particular, managerial characteristics, organizational dynamics, and resource availability play key roles. These findings suggest that a comprehensive strategy can strengthen healthcare organizations' ability to navigate implementation challenges effectively.

A deep learning-based approach for predicting COVID-19 diagnosis

This paper focuses on forecasting the total count of confirmed COVID-19 cases in Saudi Arabia through a range of methodologies, including ARIMA, mathematical modeling, and deep learning network (DQN) techniques. Its primary aim is to anticipate the verified COVID-19 cases in Saudi Arabia, aiding in decision-making for life-saving interventions by enhancing awareness of COVID-19 infection. Mathematical modeling and ARIMA are employed for their efficacy in forecasting, while DQN approaches, particularly through comparative analysis, are utilized for prediction. This comparative analysis evaluates the predictive capacities of ARIMA, mathematical modeling, and DQN techniques, aiming to pinpoint the most reliable method for forecasting positive COVID-19 cases. The modeling encompasses COVID-19 cases in Saudi Arabia, the United Kingdom (UK), and Tunisia (TU) spanning from 2020 to 2021. Predicting the number of individuals likely to test positive for COVID-19 poses a challenge, requiring adherence to fundamental assumptions in mathematical and ARIMA projections. The proposed methodology was implemented on a local server. The DQN algorithm formulates a reward function to uphold target functional performance while balancing training and testing periods. The findings indicate that DQN technology surpasses conventional approaches in efficiency and accuracy for predictions.

Framing doctor-managers' resilience during Covid-19 pandemic: A descriptive analysis from the Italian NHS

With the aim of providing evidence about doctor-managers' resilience during the Covid-19 pandemic, this study analyzes the characteristics of 114 doctor-managers operating within the Italian National Health Service (NHS). During the emergency, doctor-managers had to show adaptive capacities to deal with unexpected situations and develop new paradigms, procedures, and quick responses to patients' needs. This is in line with resilience, and in this perspective, it is crucial to investigate resilience determinants. The paper, therefore, provides an identikit of the resilient doctor-manager. The research was conducted between November and December 2020. Primary data were collected through an online questionnaire consisting of six sections. Participation was voluntary and anonymous. Data were analyzed using quantitative techniques and employing Stata 16. Confirmatory Factor Analysis was employed to test construct validity and scale reliability. Results show that increasing levels of individual resilience are related to increasing levels of managerial identity. Moreover, physicians' individual resilience has a positive association with commitment, knowledge diffusion, and Evidence-Based Medicine adoption. Finally, physicians' individual resilience has a negative association with their role in the university, their specialty, and their gender. The study suggests some practical implications for healtcare organizations. In general, career paths are decided primarily on competency assessment, while an important role should be devoted to behavioral characteristics. Furthermore, organizations should take care of the levels of individual commitment and encourage professional networking because both help doctor-managers cope with uncertainty. The originality of the study relies on a fresh look at all previous work. There are currently few contributions in the literature to explore and investigate resilience elements in doctor-managers during the pandemic era.

Artificial intelligence in healthcare: combining deep learning and Bayesian optimization to forecast COVID-19 confirmed cases

Healthcare is a topic of significant concern within the academic and business sectors. The COVID-19 pandemic has had a considerable effect on the health of people worldwide. The rapid increase in cases adversely affects a nation's economy, public health, and residents' social and personal well-being. Improving the precision of COVID-19 infection forecasts can aid in making informed decisions regarding interventions, given the pandemic's harmful impact on numerous aspects of human life, such as health and the economy. This study aims to predict the number of confirmed COVID-19 cases in Saudi Arabia using Bayesian optimization (BOA) and deep learning (DL) methods. Two methods were assessed for their efficacy in predicting the occurrence of positive cases of COVID-19. The research employed data from confirmed COVID-19 cases in Saudi Arabia (SA), the United Kingdom (UK), and Tunisia (TU) from 2020 to 2021. The findings from the BOA model indicate that accurately predicting the number of COVID-19 positive cases is difficult due to the BOA projections needing to align with the assumptions. Thus, a DL approach was utilized to enhance the precision of COVID-19 positive case prediction in South Africa. The DQN model performed better than the BOA model when assessing RMSE and MAPE values. The model operates on a local server infrastructure, where the trained policy is transmitted solely to DQN. DQN formulated a reward function to amplify the efficiency of the DQN algorithm. By examining the rate of change and duration of sleep in the test data, this function can enhance the DQN model's training. Based on simulation findings, it can decrease the DQN work cycle by roughly 28% and diminish data overhead by more than 50% on average.

Better with GPs as managers? - Variation in perceptions of feedback messages, goal-clarity and performance across manager´s in Swedish primary care

BACKGROUND

Primary care in several countries is developing towards team-based and multi-professional care, requiring leadership and management capabilities at the primary care practice level. This article reports findings from a study of primary care managers in Sweden, focusing variation in performance and perceptions of feedback messages and goal-clarity, depending on managers' professional background.

METHODS

The study was designed as a cross-sectional analysis of primary care practice managers' perceptions combined with registered data on patient-reported performance. Managers perceptions was collected through a survey to all 1 327 primary care practice managers in Sweden. Data about patient-reported performance was collected from the 2021 National Patient Survey in primary care. We used bivariate (Pearson correlation) and multivariate (ordinary least square regression analysis) statistical methods to describe and analyse the possible association between managers' background, responses to survey statements and patient-reported performance.

RESULTS

Both GP and non-GP managers had positive perceptions of the quality and support of feedback messages from professional committees focusing medical quality indicators, although managers perceived that the feedback facilitated improvement work to a lower degree. Feedback from the regions as payers scored consistently lower in all dimensions, especially among GP-managers. Results from regression analysis indicate that GP-managers correlate with better patient-reported performance when controlling for selected primary care practice and managerial characteristics. A significant positive relationship with patient-reported performance was also found for female managers, a smaller size of the primary care practice and a good staffing situation of GPs.

CONCLUSIONS

Both GP and non-GP managers rated the quality and support of feedback messages from professional committees higher than feedback from regions as payers. Differences in perceptions were especially striking among GP-managers. Patient-reported performance was significantly better in primary care practices managed by GPs and female managers. Variables reflecting structural and organizational, rather than managerial, characteristics contributed with additional explanations behind the variation in patient-reported performance across primary care practices. As we cannot exclude reversed causality, the findings may reflect that GPs are more likely to accept being a manager of a primary care practice with favourable characteristics.

The managerial role of healthcare professionals in public hospitals: a time-driven analysis of their activities

BACKGROUND

New Public Management theory affected reforms of public sectors worldwide. In Italy, an important reform of the healthcare sector changed the profile of public hospitals, creating new management related positions in 1992. The reform defined the role of the clinician-manager: a hybrid figure, in charge of managing an entire unit. This paper aims to investigate how much clinician-managers feel like managers and how much they still feel like professionals, using time as a driver to conduct the analysis.

METHODS

A survey-questionnaire was administered to a set of 2,011 clinician-managers employed in public hospitals, with a response rate of 60.42%. The managerial role of healthcare professionals in public hospitals: A time-driven analysis of their activities. The questionnaire aimed to identify the difference between how much time clinician-managers actually spend on daily activities and how much time they would think be appropriate. To better cluster different type of management styles, subgroups were identified based on the type of organisations respondents work for, geographical location, and professional specialty.

RESULTS

Findings suggest that clinician-managers spend more time on clinical activities than management. Clear differences are found according to professional specialty, and there are fewer differences in geographical location and the type of organisation.

CONCLUSIONS

The absence of clear differences in the responses between different geographical areas implies that a shared organisational culture characterizes the whole sector. However, differences in how the clinician-manager role is perceived based on the professional specialty suggest that closer integration may be needed.

Competencies of hospital managers - A systematic scoping review

Hospital managers around the world work under constant pressure to adapt their organizations to new challenges and health policy goals. This requires a comprehensive set of competencies. The objective of this scoping review was to identify, map, and systematize the literature on hospital manager competencies. The review involved six steps: (1) defining research questions; (2) identifying relevant literature; (3) selecting publications; (4) data extraction; (5) data analysis and result reporting; and (6) consultations. A total of 57 full-text publications were included (46 empirical studies, six literature reviews, four expert opinions/guidelines, and one dissertation). Interest in this topic has grown in recent years, with most of the identified studies published since 2015. The empirical studies fall into three major groups: 34.8% (16/46) examined hospital managers' competencies in terms of their types or classifications; 30.4% (14/46) focused on their measurement; and 30.4% (14/46) examined both aspects. In majority of studies, both 'hard competencies,' such as specific technical knowledge or skills acquired through practical training, and 'soft competencies,' e.g., adaptability, leadership, communication, teamwork, are echoed for effective hospital management. These point out the importance of both 'external' formal education trainings as well as 'internal' peer-support and/or coaching as complementary competency improvement approaches. This scoping review helps build a knowledge base around the topic and provides implications for future research. The latter can involve: a targeted systematic review addressing the methods for measuring the level of competence of hospital managers or studies focused on identifying the need for new types of competencies.