Human resources allocation in the hospital emergency department during COVID-19 pandemic

Gap analysis of strategies for promoting interprofessional teams in healthcare units

PURPOSE

A healthcare unit's effectiveness largely depends on how well its interprofessional teams work together. Unfortunately, the strategies used to improve these teams often lack substance. This study analyzed these strategies and found a performance gap.

DESIGN/METHODOLOGY/APPROACH

This study took a unique mixed-method approach, systematically reviewing both qualitative and quantitative studies that identified strategies to enhance interprofessional teams in healthcare units. To gauge the effectiveness of these strategies, the researcher utilized an Importance-Performance Analysis (IPA) in four specialized clinical training centers in Hamadan province, Iran. The analysis of the IPA involved 35 experts from these centers as the statistical population.

FINDINGS

Based on a systematic review, there are seven categories: contextual, strategic, communication, organizational, individual, Human Resources Management (HRM), and environmental for promoting interprofessional teams with a total of 36 sub-indicator. Based on the IPA, the HRM aspect shows the most extensive performance gap. The individual and organizational aspects fall under resource wastage, and the environmental aspect is within the indifferent zone. Also, some critical sub-indicators, such as incentives/rewards, roles and responsibilities, financial resources, team-initiated innovation, the culture of respect, partner resources, humility, data availability, set expectations, and team availability, are in the weak areas.

PRACTICAL IMPLICATIONS

This research has identified critical areas for improvement in promoting teamwork in clinical training centers through a comprehensive gap analysis. It also presents practical policy solutions to address these weak points, providing a clear roadmap for enhancing interprofessional teams in healthcare units.

ORIGINALITY/VALUE

Improving teamwork in healthcare can be challenging, but it is possible with proper strategies and tools. One of the highlights of the recent study was the combination of systematic review studies with IPA to identify areas for improving interprofessional teamwork in clinical training centers.

Time series analysis of COVID-19's impact on physician and dentist visits in Iran

This study aimed to assess the impact of the COVID-19 pandemic on general practitioner (GP), specialist, and dentist visits among 40 million Iranians covered by the Social Security Organization (SSO). A monthly interrupted time series analysis was conducted over a period of 72 months, including-47 months before the pandemic and 25 months after its onset. The outcomes variables were monthly number of GP, specialist, and dentist visits per 1000 SSO-insured individuals. The analysis was performed by total visits, visits to the SSO direct sector, and visits to the indirect sectors. The study found that in the first month of the pandemic, the number of visits per 1000 insured individuals significantly decreased for visits to GPs (by 51.12, 95% CI -64.42 to -37.88), visits to specialists (by 39.11, 95% CI -51.61 to -26.62), and visits to dentists (by 6.67, 95% CI -8.55 to -4.78). However, during the subsequent months of the pandemic, there was a significant increase in the number of monthly visits for all three categories, with GPs experiencing the highest increase (1.78 visits per 1000 insured), followed by specialists (1.32 visits per 1000 insured), and dentists (0.05 visits per 1000 insured). Furthermore, prior to the pandemic, the number of monthly GP visits per 1000 insured individuals was statistically significantly lower in the indirect sector compared to the direct sector (45.79, 95% CI -52.69 to -38.89). Conversely, the direct sector exhibited lower rates of specialist visits (25.84 visits per 1000 insured individuals, 95% CI 22.87 to 28.82) and dentist visits (0.75 visits per 1000 insured individuals, 95% CI 0.12 to 1.36) compared to the indirect sector. Additionally, the study found that in the first month of the pandemic, the monthly number of GP visits in the indirect sector significantly increased by 34.44 times (95% CI 24.81 to 44.08) compared to the direct sector. For specialist visits and dentist visits, the increase was 3.41 (95% CI -5.87 to 12.69) and 5.01 (95% CI 3.48 to 6.53) per 1000 insured individuals, respectively. Overall, the findings of this study demonstrate statistically significant disruptions in GP, specialist, and dentist visits during the COVID-19 pandemic, although some recovery was observed. Both the direct and indirect sectors experienced decreased visits.

Optimal resource allocation model for COVID-19: a systematic review and meta-analysis

BACKGROUND

A lack of health resources is a common problem after the outbreak of infectious diseases, and resource optimization is an important means to solve the lack of prevention and control capacity caused by resource constraints. This study systematically evaluated the similarities and differences in the application of coronavirus disease (COVID-19) resource allocation models and analyzed the effects of different optimal resource allocations on epidemic control.

METHODS

A systematic literature search was conducted of CNKI, WanFang, VIP, CBD, PubMed, Web of Science, Scopus and Embase for articles published from January 1, 2019, through November 23, 2023. Two reviewers independently evaluated the quality of the included studies, extracted and cross-checked the data. Moreover, publication bias and sensitivity analysis were evaluated.

RESULTS

A total of 22 articles were included for systematic review; in the application of optimal allocation models, 59.09% of the studies used propagation dynamics models to simulate the allocation of various resources, and some scholars also used mathematical optimization functions (36.36%) and machine learning algorithms (31.82%) to solve the problem of resource allocation; the results of the systematic review show that differential equation modeling was more considered when testing resources optimization, the optimization function or machine learning algorithm were mostly used to optimize the bed resources; the meta-analysis results showed that the epidemic trend was obviously effectively controlled through the optimal allocation of resources, and the average control efficiency was 0.38(95%CI 0.25-0.51); Subgroup analysis revealed that the average control efficiency from high to low was health specialists 0.48(95%CI 0.37-0.59), vaccines 0.47(95%CI 0.11-0.82), testing 0.38(95%CI 0.19-0.57), personal protective equipment (PPE) 0.38(95%CI 0.06-0.70), beds 0.34(95%CI 0.14-0.53), medicines and equipment for treatment 0.32(95%CI 0.12-0.51); Funnel plots and Egger's test showed no publication bias, and sensitivity analysis suggested robust results.

CONCLUSION

When the data are insufficient and the simulation time is short, the researchers mostly use the constructor for research; When the data are relatively sufficient and the simulation time is long, researchers choose differential equations or machine learning algorithms for research. In addition, our study showed that control efficiency is an important indicator to evaluate the effectiveness of epidemic prevention and control. Through the optimization of medical staff and vaccine allocation, greater prevention and control effects can be achieved.

Impact of COVID-19 Pandemic on Healthcare Utilization among Patients with Type 2 Diabetes Mellitus: A Systematic Review

As the COVID-19 pandemic continues, healthcare services have been grossly overwhelmed by the pandemic. Due to this circumstance, routine care for individuals with type 2 diabetes mellitus (T2DM) has been temporarily disrupted. The purpose of this systematic review was to summarize the evidence regarding the impact of the COVID-19 pandemic on healthcare utilization among patients with T2DM. A systematic search was conducted in the Web of Science, Scopus, and PubMed databases. The process of identifying the final articles followed the PRISMA guidelines. The inclusion criteria were articles published between 2020 and 2022, written in English, and studies focusing on the research question. Any proceedings and books were excluded. A total of fourteen articles relevant to the research question were extracted. Following that, the included articles were critically appraised using the Mixed Method Appraisal Tool (MMAT) and the Joanna Briggs Institute Critical Appraisal Tool to assess the quality of the studies. The findings were further classified into three themes: reduced healthcare utilization among T2DM patients in routine healthcare services, a surge of telemedicine usage, and delay in the delivery of healthcare services. The key messages include demands for monitoring the long-term effects of the missed care and that better preparedness is crucial for any pandemic in the future. A tight diagnostic workup at the community level and regular follow-ups are crucial in managing the impact of the pandemic among T2DM patients. Telemedicine should be on the agenda of the health system to maintain and complement healthcare services. Future research is warranted to determine effective strategies to deal with the impact of the pandemic on healthcare utilization and delivery among T2DM patients. A clear policy is essential and should be established.

Population Access to Hospital Emergency Departments: The Spatial Analysis in Public Health Research

The emergency medical services support the primary health care system. Hospital emergency departments (HEDs), which provide medical assistance to all patients in a state of emergency are of considerable importance to the system. When studying access to HEDs, attention should be focused on spatial relations resulting from the location of HEDs and the places of residence of the potential patients. The aim of the paper is to explain the level of spatial accessibility of HEDs and its changes as a result of organizational and spatial transformations of HEDs' networks in Poland. The research was conducted within two time series, comparing the changes in the distribution of HEDs in 2011 and 2021. GIS techniques were used to measure the distances between emergency departments and places of residence. It was observed that the transformation of the spatial organization of the hospital emergency department network in 2011-2021 resulted in the overall improvement of the spatial accessibility of these facilities, reducing the distance between them and places of residence.

Process Improvement Approaches for Increasing the Response of Emergency Departments against the COVID-19 Pandemic: A Systematic Review

The COVID-19 pandemic has strongly affected the dynamics of Emergency Departments (EDs) worldwide and has accentuated the need for tackling different operational inefficiencies that decrease the quality of care provided to infected patients. The EDs continue to struggle against this outbreak by implementing strategies maximizing their performance within an uncertain healthcare environment. The efforts, however, have remained insufficient in view of the growing number of admissions and increased severity of the coronavirus disease. Therefore, the primary aim of this paper is to review the literature on process improvement interventions focused on increasing the ED response to the current COVID-19 outbreak to delineate future research lines based on the gaps detected in the practical scenario. Therefore, we applied the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to perform a review containing the research papers published between December 2019 and April 2021 using ISI Web of Science, Scopus, PubMed, IEEE, Google Scholar, and Science Direct databases. The articles were further classified taking into account the research domain, primary aim, journal, and publication year. A total of 65 papers disseminated in 51 journals were concluded to satisfy the inclusion criteria. Our review found that most applications have been directed towards predicting the health outcomes in COVID-19 patients through machine learning and data analytics techniques. In the overarching pandemic, healthcare decision makers are strongly recommended to integrate artificial intelligence techniques with approaches from the operations research (OR) and quality management domains to upgrade the ED performance under social-economic restrictions.