Application of the "immunization islands" model to improve quality, efficiency and safety of a COVID-19 mass vaccination site

Abstract

After SARS-CoV-2 vaccines development came at an unprecedented speed, ensuring safe and efficient mass immunization, vaccine delivery be-came the major public health mandate. Although mass-vaccination sites have been identified as essential to curb COVID-19, their organization and functioning is challenging. In this paper we present the planning, implementation and evalua-tion of a massive vaccination center in Lombardy - the largest Region in Italy and the most heavily hit by the pandemic. The massive hub of Novegro (Milan), managed by the Gruppo Ospedaliero San Donato, opened in April 2021. The Novegro mass-immunization model was developed building a la-yout based on the available scientific evidence, on comparative analysis with other existing models and on the experience of COVID-19 immunization delivery of Gruppo Ospedaliero San Donato. We propose a "vaccine islands" mass-immunization model, where 4 physicians and 2 nurses operate in each island, with up to 10 islands functioning at the same time, with the capacity of providing up to 6,000 vaccinations per day. During the first week of activity a total of 37,900 doses were administered (2,700/day), most of them with Pfizer vaccine (85.8%) and first doses (70.9%). The productivity was 10.5 vaccines/hour/vaccine station. Quality, efficiency and safety were boosted by ad-hoc personnel training, quality technical infrastructure and the presence of a shock room. Constant process monitoring allowed to identify and promptly tackle process pitfalls, including vaccine refusals (0.36%, below expectations) and post-vaccinations adverse reactions (0.4%). Our innovative "vaccine islands" mass-immunization model might be scaled-up or adapted to other settings. The Authors consider that sharing best practices in immunization delivery is fundamen-tal to achieve population health during health emergencies.

Managing transition to ValueēBased hospital care pathways

Issue

San Raffaele Hospital (OSR) is part of a European alliance of 9 University Hospitals (EUHA) which promotes comparison and excellence in the clinical, research and training strategies.

Description of the Problem

The development of Value-Based (VB) strategies has been active in OSR since March 2019, with multidisciplinary healthcare pathways and with the promotion of patient engagement.

Results

The prostate cancer pathway was identified as a pilot and replicable model to promote the VB culture in different areas, in particular in the field of digitalization, human resources, research, redesigning of paths and outcomes collection. The other clinical pathways progressively launched during 2019 were: breast cancer, stroke, heart failure and pancreatic cancer.

The project was realized by: • setting up a Multidisciplinary disease teams; developing a training course on VB, involving all the healthcare professionals (clinicians and managers);involving patient associations in the development of the pathway;adopting sets of clinical outcomes, Patient-Related Outcome Measures (PROMs) and Patient-Related Experience Measures (PREMs) with a specific collection platform, currently under implementation;identifying new IT support tools, activated from March to December 2019 in 11 Disease Units: HealthMeeting, a platform supporting document and data sharing, connecting different Specialists and performing advanced digital multidisciplinary meetings; DNM-Digital Narrative Medicine, a platform connecting patients with their clinical team, supporting web-based storytelling and personalized therapeutic approach.

Lessons

The introduction of a new shared and patient-centred work model, with the reorganization of spaces, resources and dedicated IT tools, has improved the diagnostic-therapeutic process.

Key messages

The main challenge of hospital transition to VB pathways is organizational and cultural. For VB implementation is needed sustainable use of available resources and IT, to achieve better outcomes.

Telemedicine and mental health: coming of age?

Telemedicine is the practice of medicine from distance using information technology and include mainly teleconsultation via video and/or chat, teleexpertise to request the opinion of a specialist, and remote patient monitoring to improve the follow-up of patients. The use of telemedicine in mental health and most specially psychiatry has been one of the first use case described in the scientific literature, via video teleconsultation, due to the absence of physical patient examination. One of the oldest telepsychiatry case from the literature was published in 1973 for patients assessed from 1968 with the Massachusetts General Hospital in Boston, USA.

Despite its medical and technical ease, telepsychiatry is still not widely spread and integrated into healthcare systems due to organisational and implementation challenges. More recently, telepsychology and other telemedicine interventions in mental health have been growing across the globe, including for mental wellbeing promotion and prevention of mental health conditions in specific environments. The rise of consumer digital healthcare directly through mobile app and dedicated websites is also to be considered in the wide opportunities of telemedicine opportunities to address mental health issues at a global scale. Various models needs thus to be considered between digital only care and blended approach mixing face-to-face and digital ways, as well as telemental health delivered only via the existing healthcare system or via new private digital players. The objective of the presentation is to describe the spectrum of existing telemedicine interventions in mental health, the digital features enabling its adoption and the assessment of its impact on clinical and public health outcomes.

Narrative medicine in the cancer care: implementation and impact

Issue

National and international health authorities have described Narrative-based medicine (NBM) in clinical practice as a fundamental tool for acquiring, understanding and integrating the different points of view of those involved in the disease and its treatment, promoting more effective and appropriate care.

Description of the problem

The use of NBM is part of the strategic project to improve patient-engagement in San Raffaele Hospital in Milan. Its implementation started, using the 'DNM-Digital Narrative Medicine' web-based platform, with the pilot prostate cancer path in March 2019.

Results

A 10-item questionnaire was sent to all 47 patients and 45 doctors involved, to evaluate: benefits perceived by the care team in terms of communication support, personalization of therapy, observation of cognitive elements not otherwise evident; benefits perceived by the patient (support, communication, self-management, identification of emotional, relational, social elements of daily life); patient and medical staff opinions in terms of compliance, accessibility, ease of use. The overall rating was 4.3/5 for doctors and 4.2/5 for patients. Patients valued the most the platform supporting them in the decision on what treatment to undergo (4.8/5), for the doctor the platform has been important in considering unknown aspects of the patient and understanding the patient's point of view (4.4/5). Patients, more than doctors, perceived platform usability positively. 43% of the patients who decided not to participate reported to prefer a direct approach with the doctor.

Lessons

The oncologic field represents an optimal setting for the implementation of methods aimed at strengthening communication and relationship of care. NBM offers the possibility of exploring elements as adherence to treatment, perception of illness, socio-psychological impact, sometimes missed during the visit, enhancing the conversation between patient and care team and stimulating the co-construction of care.

Key messages

NBM has proven to be a useful tool and a good communication channel in the oncologic setting. The NBM platform demonstrated good acceptability and ease of use by doctors and patients.

Audit methodology for the quality assessment of medical records in the emergency department

Issue

Filling out medical records properly in Emergency Departments (ED) can be challenging, due to the high number of daily admissions and the variety of involved health care professionals (HCP).

Description of the Problem

The ED of IRCCS San Raffaele Hospital (OSR), with a mean of 198 admissions per day in 2019, suffers of frequent overcrowding; patients are managed by multiple HCPs, based on specific care needs; coordination and handover between them are crucial to guarantee quality care. The OSR Healthcare Directorate, the ED's Staff and the School of Public Health of Vita-Salute San Raffaele University developed and validated a model of internal audit to identify ED medical records' quality issues and to implement corrective actions. The workflow included: developing a structured checklist, mapping critical processes and highlighting each figure's tasks. A group of auditors, made up by medical residents in Public Health, tested n = 300 medical charts, filled out during the first semester of 2019, picked up in order to provide a representative sample of the triage priority codes assigned to patients in this period.

Results

To assess completeness and quality of ED's medical records, a new checklist was developed, comprising 4 major sections, furtherly divided in 14 items, scored from 1 (poor adherence/completeness) to 5 (excellent), providing a total score for each record, ranging from 14 to 70. Specific comments to items could be added and an ultimate judgement was written by each auditor. This approach made medical records measurable and comparable.

Lessons

The new checklist and the audit process are useful instruments for the evaluation of medical records and the identification of corrective measures in the ED of our hospital. Next steps will be the extension of the sample, the implementation of corrective actions, and the institution of a stable working group for a regular evaluation.

Key messages

ED's medical records must be clear, understandable and complete. The developed checklist is a tool for preventing and correcting wrong behaviours in a continuous improvement perspective.

Use and impact of smartphone apps in mental health

As smartphone usage is more and more ubiquitous, the app market is flourishing in all fields, including health. Indeed, the availability and use of smartphone apps (SAs) in health has exponentially grown in recent years. It has been estimated that in 2018 there were over 97,000 health apps available and that, 15% and 8% of US phone users aged 18-29 and 30-49 years respectively had health apps installed on their mobile devices. Health apps might potentially support people health paths in multiple ways: channeling health education, enabling personal health data tracking, self-monitoring and goals setting, facilitating access to health records or compliance to treatment, fostering effective communication with healthcare providers and health services, as well as supporting clinical decision-making.

Despite such large potential, still scant evidence is available on the impact of SAs on clinical outcomes in different fields of medicine, including mental health. With an estimated prevalence of around 450 million people currently suffering from mental disorders and 1 in 4 people in the world affected at some point in own life, mental disorders are a leading cause of ill-health and disability worldwide whose prevention and care might be enhanced by mHealth technology.

The general aim of the presentation is to provide an overview on the use and impact of SAs in the field of mental health. Specific objectives are: i) to present a conceptual framework on how SAs might support mental disorders prevention, diagnosis and treatment, ii) to report on SAs use in mental health in different settings, iii) to collect and pool available evidence from observational and experimental studies on the impact of SAs use on different mental health outcomes, iv) to explore the quality, effectiveness and attributes of top-rated smartphone mental health apps and lastly, v) to suggest gaps in knowledge to be filled by future research.

Artificial Intelligence-based tools to control healthcare associated infections: where do we stand

Background

Control of Healthcare associated infections (HAI) is a key public health concern in Europe. Current HAI surveillance systems are based on manual medical records review, vulnerable to misclassification & expensive. Artificial intelligence (AI), as a digital tool, offers great potential to HAI control. Still, scant evidence is available on both its practice and impact.

Methods

As part of a broader multidisciplinary project, we conducted a systematic review to retrieve, pool and critically apprize all the available evidence on practice, performance and impact of AI-based HAI control programmes. We followed PRISMA and searched the Medline and Embase databases for relevant studies. Included studies were stratified by HAI type and outcomes of interest, including all possible performance measures, clinical, organizational and economic outcomes.

Results

We screened 2873 records, resulting in 27 papers included in the review. Studies were carried out in 9 countries, the majority in the US (56%), 18.5% in EU countries, 25.9% published in 2018. Two thirds of studies focused on selected types of infections. Study designs were very diverse and performance observed for HAI detection were very heterogeneous, precluding pooled calculation of summary diagnostic accuracy estimates in most instances, but generally higher than non AI-based models. Overall performance measures of AI algorithms were: sensitivity range 19%-92%, accuracy 70.2%-96.1%.

Conclusions

Use of AI for HAI surveillance of HAI has increased reliability compared to traditional surveillance or to automated surveillance models. With ongoing improvements in information technology, implementation of AI models will improve the quality and capacity of surveillance will support hospital HAI surveillance.

Main messages

AI offer great potential to healthcare associated infections control. Preliminary evidence show AI-based models have perform better than manual or automated models for HAIs detection.

Artificial Intelligence-based tools to control healthcare associated infections: where do we stand

Background

Control of Healthcare associated infections (HAI) is a key public health concern in Europe. Current HAI surveillance systems are based on manual medical records review, vulnerable to misclassification and expensive. Artificial intelligence (AI) offers great potential to public health action and, specifically, to HAI control. Still, scant evidence is available on both its practice and impact.

Methods

As part of a broader multidisciplinary project, we conducted a systematic review to retrieve, pool and critically apprize all the available evidence on practice, performance and impact of AI-based HAI control programmes. We followed PRISMA guidelines and searched the Medline and Embase databases for relevant studies. Included studies were stratified by HAI type and outcomes of interest, including all possible performance measures, clinical, organizational and economic outcomes.

Results

We screened 2873 records, resulting in 27 papers included in the review. Studies were carried out in 9 countries, the majority in the US (56%), 18.5% in EU countries, 25.9% published in 2018. Two thirds of studies focused on selected types of infections. Study designs were very diverse and performance observed for HAI detection were very heterogeneous, precluding pooled calculation of summary diagnostic accuracy estimates in most instances, but generally higher than non AI-based models. The highest performance outcomes were Specificity and Negative Predictive Value. Overall performance measures of AI algorithms were: sensitivity range 19%-92%, specificity range 64%-96%, accuracy 70.2%-96.1%.

Conclusions

Use of AI algorithms for HAI surveillance of HAI has increased reliability compared to traditional surveillance or to automated surveillance models. With ongoing improvements in information technology, implementation of AI models will improve the quality and capacity of surveillance will support hospital HAI surveillance.

Key messages

Artificial Intelligence (AI) offer great potential to healthcare associated infections (HAI) control. Preliminary evidence show AI-based models have perform better than manual or automated models for HAIs detection.

Information and communication technology-based interventions to support healthcare in migrants

Background

Advances in the field of Information and Communication Technology (ICT) are revolutionizing healthcare, while massive migration flows and cross-border populations’ transit impose the planning, implementation, and evaluation of new integrated healthcare services and programmes. Nevertheless, no conclusive evidence exists on the vast potential offered by ICT to promote healthcare in migrant populations.

Methods

We carried out a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines to retrieve, pool and critically appraise all the available evidence on the effectiveness of ICT-based interventions to support the healthcare provision to migrant and in-transit populations in Europe. We searched the electronic databases Medline and Embase, relevant grey literature and consulted with experts in the field. We restricted the area of interest to EU/EEA countries and included studies providing original quantitative data.

Results

Out of 127 retrieved records, 53 (42%) met the inclusion criteria. Included studies were classified in the following four interventions: implementation of healthcare services (47%), patients’ education (26%), healthcare services’ monitoring (17%), and interventions on providers (10%). The most relevant data refer to telemedicine, prevention interventions, and healthcare data sharing and the most represented specific health-topic is that of mental health (26%). We present available data qualitatively and quantitatively pooled by country, type of ICT, target population and health topic.

Conclusions

Selected ICT-based interventions have been implemented in Europe to promote healthcare in migrant populations; however, in most cases, no monitoring and evaluation exist on their impact, effectiveness, and cost-effectiveness. Strengthened efforts are needed to identify, plan, implement and evaluate effective interventions and share best practices to protect in-transit populations’ health.

Key messages

Information and Communication Technology (ICT) offer great potential to promote health-care in migrant populations. Effective ICT interventions and best practices should be shared across Europe.