Operational research applied to regional healthcare system

In this thesis we focus on optimization and simulation techniques applied to solve strategic, tactical and operational problems rising in the healthcare sector. At first we present three applications to Emilia-Romagna Public Health System (SSR) developed in collaboration with Agenzia Sanitaria e Sociale dell'Emilia-Romagna (ASSR), a regional center for innovation and improvement in health. Agenzia launched a strategic campaign aimed at introducing Operations Research techniques as decision making tools to support technological and organizational innovations. The three applications focus on forecast and fund allocation of medical specialty positions, breast screening program extension and operating theater planning. The case studies exploit the potential of combinatorial optimization, discrete event simulation and system dynamics techniques to solve resource constrained problem arising within Emilia-Romagna territory. We then present an application in collaboration with Dipartimento di Epidemiologia del Lazio that focuses on population demand of service allocation to regional emergency departments. Finally, a simulation-optimization approach, developed in collaboration with INESC TECH center of Porto, to evaluate matching policies for the kidney exchange problem is discussed.

Medical Malpractice in Public Healthcare Systems: An Empirical Investigation of Scheduled Damages

In the last decades, medical malpractice has been framed as one of the most critical issues for healthcare providers and health policy, holding a central role on both the policy agenda and public debate. The Law and Economics literature has devoted much attention to medical malpractice and to the investigation of the impact of malpractice reforms. Nonetheless, some reforms have been much less empirically studied as in the case of schedules, and their effects remain highly debated. The present work seeks to contribute to the study of medical malpractice and of schedules of noneconomic damages in a civil law country with a public national health system, using Italy as case study. Besides considering schedules and exploiting a quasi-experimental setting, the novelty of our contribution consists in the inclusion of the performance of the judiciary (measured as courts’ civil backlog) in the empirical analysis. The empirical analysis is twofold. First, it investigates how limiting compensations for pain and suffering through schedules impacts on the malpractice insurance market in terms of presence of private insurers and of premiums applied. Second, it examines whether, and to what extent, healthcare providers react to the implementation of this policy in terms of both levels and composition of the medical treatments offered. Our findings show that the introduction of schedules increases the presence of insurers only in inefficient courts, while it does not produce significant effects on paid premiums. Judicial inefficiency is attractive to insurers for average values of schedules penetration of the market, with an increasing positive impact of inefficiency as the territorial coverage of schedules increases. Moreover, the implementation of schedules tends to reduce the use of defensive practices on the part of clinicians, but the magnitude of this impact is ultimately determined by the actual degree of backlog of the court implementing schedules.

Methods and tools for analysis and management of risks and regulatory compliance in the healthcare sector: the hospital at home – HaH

Changing or creating an organisation means creating a new process. Each process involves many risks that need to be identified and managed. The main risks considered here are procedural and legal risks. The former are related to the risks of errors that may occur during processes, while the latter are related to the compliance of processes with regulations. Managing the risks implies proposing changes to the processes that allow the desired result: an optimised process. In order to manage a company and optimise it in the best possible way, not only should the organisational aspect, risk management and legal compliance be taken into account, but it is important that they are all analysed simultaneously with the aim of finding the right balance that satisfies them all. This is the aim of this thesis, to provide methods and tools to balance these three characteristics, and to enable this type of optimisation, ICT support is used. This work isn’t a thesis in computer science or law, but rather an interdisciplinary thesis. Most of the work done so far is vertical and in a specific domain. The particularity and aim of this thesis is not to carry out an in-depth analysis of a particular aspect, but rather to combine several important aspects, normally analysed separately, which however have an impact and influence each other. In order to carry out this kind of interdisciplinary analysis, the knowledge base of both areas was involved and the combination and collaboration of different experts in the various fields was necessary. Although the methodology described is generic and can be applied to all sectors, the case study considered is a new type of healthcare service that allows patients in acute disease to be hospitalised to their home. This provide the possibility to perform experiments using real hospital database.

Smart Textile Sensors for Healthcare Monitoring

Wearable electronic textiles are an emerging research field playing a pivotal role among several different technological areas such as sensing, communication, clothing, health monitoring, information technology, and microsystems. The possibility to realise a fully-textile platform, endowed with various sensors directly realised with textile fibres and fabric, represents a new challenge for the entire research community. Among several high-performing materials, the intrinsically conductive poly(3,4-ethylenedioxythiophene) (PEDOT), doped with poly(styrenesulfonic acid) (PSS), or PEDOT:PSS, is one of the most representative and utilised, having an excellent chemical and thermal stability, as well as reversible doping state and high conductivity. This work relies on PEDOT:PSS combined with sensible materials to design, realise, and develop textile chemical and physical sensors. In particular, chloride concentration and pH level sensors in human sweat for continuous monitoring of the wearer's hydration status and stress level are reported. Additionally, a prototype smart bandage detecting the moisture level and pH value of a bed wound to allow the remote monitoring of the healing process of severe and chronic wounds is described. Physical sensors used to monitor the pressure distribution for rehabilitation, workplace safety, or sport tracking are also presented together with a novel fully-textile device able to measure the incident X-ray dose for medical or security applications where thin, comfortable, and flexible features are essential. Finally, a proof-of-concept for an organic-inorganic textile thermoelectric generator that harvests energy directly from body heat has been proposed. Though further efforts must be dedicated to overcome issues such as durability, washability, power consumption, and large-scale production, the novel, versatile, and widely encompassing area of electronic textiles is a promising protagonist in the upcoming technological revolution.

Integration of heterogeneous data sources and automated reasoning in healthcare and domotic IoT systems

In recent years, IoT technology has radically transformed many crucial industrial and service sectors such as healthcare. The multi-facets heterogeneity of the devices and the collected information provides important opportunities to develop innovative systems and services. However, the ubiquitous presence of data silos and the poor semantic interoperability in the IoT landscape constitute a significant obstacle in the pursuit of this goal. Moreover, achieving actionable knowledge from the collected data requires IoT information sources to be analysed using appropriate artificial intelligence techniques such as automated reasoning. In this thesis work, Semantic Web technologies have been investigated as an approach to address both the data integration and reasoning aspect in modern IoT systems. In particular, the contributions presented in this thesis are the following: (1) the IoT Fitness Ontology, an OWL ontology that has been developed in order to overcome the issue of data silos and enable semantic interoperability in the IoT fitness domain; (2) a Linked Open Data web portal for collecting and sharing IoT health datasets with the research community; (3) a novel methodology for embedding knowledge in rule-defined IoT smart home scenarios; and (4) a knowledge-based IoT home automation system that supports a seamless integration of heterogeneous devices and data sources.

Analytics and optimization for emergency healthcare processes

This thesis deals with the analysis and management of emergency healthcare processes through the use of advanced analytics and optimization approaches. Emergency processes are among the most complex within healthcare. This is due to their non-elective nature and their high variability. This thesis is divided into two topics. The first one concerns the core of emergency healthcare processes, the emergency department (ED). In the second chapter, we describe the ED that is the case study. This is a real case study with data derived from a large ED located in northern Italy. In the next two chapters, we introduce two tools for supporting ED activities. The first one is a new type of analytics model. Its aim is to overcome the traditional methods of analyzing the activities provided in the ED by means of an algorithm that analyses the ED pathway (organized as event log) as a whole. The second tool is a decision-support system, which integrates a deep neural network for the prediction of patient pathways, and an online simulator to evaluate the evolution of the ED over time. Its purpose is to provide a set of solutions to prevent and solve the problem of the ED overcrowding. The second part of the thesis focuses on the COVID-19 pandemic emergency. In the fifth chapter, we describe a tool that was used by the Bologna local health authority in the first part of the pandemic. Its purpose is to analyze the clinical pathway of a patient and from this automatically assign them a state. Physicians used the state for routing the patients to the correct clinical pathways. The last chapter is dedicated to the description of a MIP model, which was used for the organization of the COVID-19 vaccination campaign in the city of Bologna, Italy.

Pedagogy of healthcare interactions. A study on pediatric well-child visits as culture-oriented and culture-making sites

This study investigates interactions between parents and pediatricians during pediatric well-child visits. Despite constituting a pivotal moment for monitoring and evaluating children’s development during the critical ‘first thousand days of life’ and for family support, no study has so far empirically investigated the in vivo realization of pediatrician-parent interactions in the Italian context, especially not from a pedagogical perspective. Filling this gap, the present study draws on a corpus of 23 videorecorded well-child visits involving two pediatricians and twenty-two families with children aged between 0 and 18 months. Combining an ethnographic perspective and conversation analysis theoretical-analytical constructs, the micro-analysis of interactions reveals how well-child visits unfold as culture-oriented and culture-making sites. By zooming into what actually happens during these visits, the analysis shows that there is much more than the “mere” accomplishment of institutionally relevant activities like assessing children’s health or giving parents advice on baby care. Rather, through the interactional ways these institutional tasks are carried out, parents and pediatricians presuppose, ratify, and transmit culturally-informed models of “normal” growth, “healthy” development, “good” caring practices, and “competent” parenting, thereby enacting a pervasive yet unnoticed educational and moral work. Inaugurating a new promising line of inquiry within Italian pedagogical research, this study illuminates how a) pediatricians work as a “social antenna”, bridging families’ private “small cultures” and broader socio-cultural models of children’s well-being and caregiving practices, and b) parents act as agentive, knowledgeable, (communicatively) competent, and caring parents, while also sensitive to the pediatrician’s ultimate epistemic and deontic authority. I argue that a video-based, micro-analysis of interactions represents a heuristically powerful instrument for raising pediatricians’ and parents’ awareness of the educational and moral density of well-child visits. Insights from this study can constitute a valuable empirical resource for underpinning medical and parental training programs aimed at fostering pediatricians’ and parents’ reflexivity.

Internet of healthcare (law): privacy and data protection aspects in an internet of everything

The purpose of this research study is to discuss privacy and data protection-related regulatory and compliance challenges posed by digital transformation in healthcare in the wake of the COVID-19 pandemic. The public health crisis accelerated the development of patient-centred remote/hybrid healthcare delivery models that make increased use of telehealth services and related digital solutions. The large-scale uptake of IoT-enabled medical devices and wellness applications, and the offering of healthcare services via healthcare platforms (online doctor marketplaces) have catalysed these developments. However, the use of new enabling technologies (IoT, AI) and the platformisation of healthcare pose complex challenges to the protection of patient’s privacy and personal data. This happens at a time when the EU is drawing up a new regulatory landscape for the use of data and digital technologies. Against this background, the study presents an interdisciplinary (normative and technology-oriented) critical assessment on how the new regulatory framework may affect privacy and data protection requirements regarding the deployment and use of Internet of Health Things (hardware) devices and interconnected software (AI systems). The study also assesses key privacy and data protection challenges that affect healthcare platforms (online doctor marketplaces) in their offering of video API-enabled teleconsultation services and their (anticipated) integration into the European Health Data Space. The overall conclusion of the study is that regulatory deficiencies may create integrity risks for the protection of privacy and personal data in telehealth due to uncertainties about the proper interplay, legal effects and effectiveness of (existing and proposed) EU legislation. The proliferation of normative measures may increase compliance costs, hinder innovation and ultimately, deprive European patients from state-of-the-art digital health technologies, which is paradoxically, the opposite of what the EU plans to achieve.

Patient data sharing for the improvement of healthcare and medical research: towards a moral duty of patients to share health-related data?

The project answers to the following central research question: ‘How would a moral duty of patients to transfer (health) data for the benefit of health care improvement, research, and public health in the eHealth sector sit within the existing confidentiality, privacy, and data protection legislations?’. The improvement of healthcare services, research, and public health relies on patient data, which is why one might raise the question concerning a potential moral responsibility of patients to transfer data concerning health. Such a responsibility logically would have subsequent consequences for care providers concerning the further transferring of health data with other healthcare providers or researchers and other organisations (who also possibly transfer the data further with others and other organisations). Otherwise, the purpose of the patients’ moral duty, i.e. to improve the care system and research, would be undermined. Albeit the arguments that may exist in favour of a moral responsibility of patients to share health-related data, there are also some moral hurdles that come with such a moral responsibility. Furthermore, the existing European and national confidentiality, privacy and data protection legislations appear to hamper such a possible moral duty, and they may need to be reconsidered to unlock the full use of data for healthcare and research.

Advancing digital healthcare research and machine learning-aided knowledge extraction amidst the COVID-19 pandemic

The rapid progression of biomedical research coupled with the explosion of scientific literature has generated an exigent need for efficient and reliable systems of knowledge extraction. This dissertation contends with this challenge through a concentrated investigation of digital health, Artificial Intelligence, and specifically Machine Learning and Natural Language Processing's (NLP) potential to expedite systematic literature reviews and refine the knowledge extraction process. The surge of COVID-19 complicated the efforts of scientists, policymakers, and medical professionals in identifying pertinent articles and assessing their scientific validity. This thesis presents a substantial solution in the form of the COKE Project, an initiative that interlaces machine reading with the rigorous protocols of Evidence-Based Medicine to streamline knowledge extraction. In the framework of the COKE (“COVID-19 Knowledge Extraction framework for next-generation discovery science”) Project, this thesis aims to underscore the capacity of machine reading to create knowledge graphs from scientific texts. The project is remarkable for its innovative use of NLP techniques such as a BERT + bi-LSTM language model. This combination is employed to detect and categorize elements within medical abstracts, thereby enhancing the systematic literature review process. The COKE project's outcomes show that NLP, when used in a judiciously structured manner, can significantly reduce the time and effort required to produce medical guidelines. These findings are particularly salient during times of medical emergency, like the COVID-19 pandemic, when quick and accurate research results are critical.