Enabling Data Interoperability for Decentralized, Smart, and Connected Health Applications

Enhancing real world data interoperability in healthcare: A methodological approach to laboratory unit harmonization

The implementation of data interoperability in healthcare relies heavily on policy frameworks. However, many hospitals across South Africa are struggling to integrate data interoperability between systems, due to insufficient policy frameworks. There is a notable awareness that existing policies do not provide clear actionable direction for interoperability implementation in hospitals. This study aims to develop a policy framework for integrating data interoperability in public hospitals in Gauteng Province, South Africa. The study employed a conceptual framework grounded in institutional theory, which provided a lens to understand policies for interoperability. This study employed a convergence mixed method research design. Data were collected through an online questionnaire and semi-structured interviews. The study comprised 144 clinical and administrative personnel and 16 managers. Data were analyzed through descriptive and thematic analysis. The results show evidence of coercive isomorphism that public hospitals lack cohesive policies that facilitate data interoperability. Key barriers to establishing policy framework include inadequate funding, ambiguous guidelines, weak governance, and conflicting interests among stakeholders. The study developed a policy to facilitate the integration of data interoperability in hospitals. This study underscores the critical need for the South African government, legislators, practitioners, and policymakers to consult and involve external stakeholders in the policy-making processes.

Introduction West Africa faces challenges in controlling Lassa Fever and other viral hemorrhagic fevers due to fragmented health information systems and limited cross-border data sharing. The absence of a unified digital health infrastructure in ECOWAS undermines disease surveillance and emergency response. This research aims to establish a distributed digital health system, leveraging data cooperatives to enable secure cross-border surveillance and epidemic preparedness. Methods This multi-country, mixed-methods study begins with stakeholder interviews, surveys, and analysis of digital health systems in clinics using electronic medical records. Insights from this phase will guide the design and prototyping of a distributed data management architecture based on cooperatives, modeled with BPMN and integrating privacy technologies, interoperability standards, and offline functionality. Results Preliminary findings identify ongoing barriers to data interoperability, privacy, and trust in cross-border health data sharing. The proposed system is designed to enable secure, ethical, and user-controlled exchange across ECOWAS, supporting real-time, anonymized data for surveillance and research, while supporting digital health and telemedicine initiatives. Conclusion A distributed digital health architecture built on data cooperatives has the potential to bridge gaps in data sharing and epidemics preparedness. This approach aims to enhance regional coordination, empower individuals and health systems, and support the future adoption of improved epidemic surveillance and control by ECOWAS and partner organizations.

20 years of history: Has that much changed?

Transparent sharing of digital health data: A call to action

Introduction: Digital health technologies, including telemedicine, mobile health (mHealth), artificial intelligence (AI), and health information exchange platforms, have the potential to revolutionize healthcare by improving access, efficiency, and patient outcomes. However, translating research evidence into practice and policy remains challenging due to barriers such as complex healthcare systems, data privacy concerns, regulatory hurdles, resource constraints, and organizational resistance.Methods: This article synthesizes insights from field experience and peer-reviewed literature to identify key barriers and propose strategies for effective translation of digital health evidence. References were selected based on their relevance to digital health implementation, focusing on high-impact studies and real-world examples published between 2013 and 2024, sourced from journals like Health Affairs, Healthcare, and Nature Medicine.Results: Key challenges include the complexity of healthcare systems, data privacy and security concerns, regulatory and policy barriers, resource limitations, and resistance to cultural change. Proposed strategies encompass strengthening data governance and interoperability, enhancing stakeholder collaboration, implementing robust policy frameworks, investing in education and training, and fostering cultural change. Case studies, such as telemedicine adoption during the COVID-19 pandemic and blockchain applications for data security, illustrate successful implementation when these barriers are addressed.Discussion: The integration of digital health into practice requires a multifaceted approach that addresses systemic, regulatory, and cultural challenges. Future directions include streamlining regulatory processes, enhancing interoperability, addressing health disparities, and scaling solutions without compromising quality. Collaborative, evidence-based strategies are essential to realize the full potential of digital health for equitable and efficient healthcare delivery.

Reliability and Validity of the Substance Abuse Outcomes Module

Videoconferencing at 384 kbit/s for the transmission of echocardiograms has proved useful for the assessment of children with suspected cardiac disease, in regional areas of Queensland. A retrospective review of patient and management outcomes was conducted on cardiac teleconsultations performed at two regional hospitals during the period November 2000 to February 2004, inclusive. There were 106 echo studies. A subset of 72 cardiac teleconsultations performed between May 2001 and February 2004 was reviewed in detail. The median age of patients at the time of consultation was 3 months (range 1 day-17 years). Sixteen per cent of teleconsultations were classified as urgent and were conducted on the same day as referral. Following the videoconference, 90% of patients could be managed locally and reviewed by the paediatrician or visiting paediatric cardiologist during an outreach clinic. Six children (8%) had significant cardiac lesions that were initially managed locally, with subsequent elective transfer at the appropriate time for treatment. Only one child (1%) required urgent transfer to the tertiary centre for specialist care and surgery. Telecardiology was effective in accurately identifying congenital heart disease. Paediatric telecardiology is an evolving modality of assessment and communication, and is likely to result in continued improvements in patient care, patient outcomes and parental satisfaction, in provincial centres removed from the tertiary cardiac centre.

This article is the third in a 6-part series to chronicle the processes, work, and outcomes of the ACGME Pursuing Excellence Pathway Innovators Project. These articles provide an overview of the project, detail the 4 drivers developed to define the project, and present the evaluation process developed. This article highlights initiatives that integrate health system learners into quality, safety, equity, and value processes of health care organizations.While the National Academy of Medicine's To Err Is Human1 and Crossing the Quality Chasm2 ushered in a new focus on quality and safety, and Unequal Treatment3 focused on health disparities, the ACGME Clinical Learning Environment Review (CLER) Program centered the importance of these principles in the clinical learning environment (CLE).The CLER Program, developed in 2012, increased the focus on Sponsoring Institutions' engagement of residents and fellows in quality improvement and patient safety within the CLE.4 The new focus was in part motivated by literature describing wide variations in care for standard practices, value-based care, and patient outcomes for similar conditions across geographic regions and health care systems. Layered on this is a growing body of literature demonstrating that residents and fellows who practice in health systems with greater attention to high-quality care delivery carry these behaviors forward into practice, and therefore their patients may experience better health outcomes.5The first CLER National Report of Findings published in 2016 highlighted significant variation between institutions in the degree to which learners meaningfully engaged in activities related to quality, safety, equity, and value.6 For example, although residents were often aware of institutional quality priorities, they often defaulted to existing solutions and/or guidelines, rather than using knowledge and skills to develop and apply new approaches. Residents' improvement work was often siloed by profession and department, with limited engagement in interprofessional teams. Specific improvement efforts identified by residents related to disparities focused on provision of services to low-income or marginalized populations, rather than linking quality to equity. Robust programs to engage residents and fellows in identifying and reducing local disparities were lacking. Lastly, a lack of experiential engagement in patient safety at all levels was observed, from frontline incident reports to high-level engagement with service- and institution-specific safety priorities.The Pursuing Excellence in Clinical Learning Environments initiative (Pursuing Excellence) was created to address the variation across Sponsoring Institutions identified in the CLER National Report of Findings 2016 by testing innovations as part of a longitudinal social learning model. A core activity of Pursuing Excellence was the establishment of the Pathway Innovators Collaborative with the aim of enhancing the integration of graduate medical education and the health care delivery system to enable measurable improvement in patient outcomes and learner experience.7 Through a competitive application process 8 diverse Sponsoring Institutions,8 varying in size and governance structures, were selected to participate in the Pathway Innovators Collaborative. Their charge was to work within their organizations and across Sponsoring Institutions to create sustainable and adaptable projects and processes that could improve the CLE and be shared with the entire GME learning community. This article provides a detailed perspective on the second of 4 major areas of work within the Pathway Innovators Collaborative.Four primary drivers for improvement of the CLE for residents and fellows were identified to guide the Collaborative. These primary drivers included focusing on alignment of the CLE and GME, engaging residents and staff in quality, safety, value, and equity, faculty development, and interprofessional learning. All of these primary drivers included multiple secondary drivers (see Figure). Half of the teams began by focusing their initial efforts on Driver 2, “Establish the processes and practices that fully integrate clinical learning environment staff and learners into the pursuit of quality, safety, equity, and value in the organization.” This approach reflects the growing recognition of health systems science that complements and synergizes with traditional basic and clinical sciences. All 8 sites met through sequential learning sessions, including in-person site visits, guided by a 4-year curriculum to refine their innovations.The Collaborative teams noted several factors to consider for implementation of Driver 2. A key factor was that patient safety and quality improvement work often relied on established nursing unit–based structures. The transient nature of residents was not conducive to a shared learning experience. While residents commonly rotate through units, they are not a permanent part of the unit-based team, and may work on multiple rotations across units, in some cases across multiple hospitals. Also, many units held quality or safety huddles at set times to review institutional and local metrics, and residents were often not aware of those huddles or able to attend due to other clinical or educational obligations. The lack of integrated resident and unit-based quality and safety work could result in projects at risk of not being sustained after a resident rotated off-service or graduated.An additional factor was lack of improvement expertise available at the point of care where residents work. Many institutions have improvement experts charged with overseeing institutional improvement initiatives (ie, Operational Excellence, Lean Transformation); however, that expertise was often not known or available to residents. Likewise, residents and fellows often did not know what quality data were routinely collected or how to access these data to drive improvement. Recognizing these challenges, the Collaborative undertook the work of implementing and sustaining an infrastructure that aligned and integrated learners with staff through a specified set of action steps articulated below.Each of the Collaborative teams utilized the secondary drivers of the Driver Diagram to begin the journey toward integrating residents and fellows in the quality, safety, value, and equity mission of the Sponsoring Institution. Notably, the Collaborative found it more practical and logical to approach the secondary drivers in the reverse order on the driver diagram. Articulated below is how the teams implemented each of the secondary drivers, presented in the sequence we propose for future use. To make progress, some overlap will likely be required. Specific examples of team approaches are in the Table.Obtaining institutional resources and infrastructure to engage residents into quality, safety, equity, and value work is foundation to successful integration. This requires demonstrating a return on investment, allowing health system leaders to see this work as mission critical to health care delivery. Resources and infrastructure not only come in the form of leadership buy-in, but also in staff to support the work of engaging residents. The participants noted that this work can be both an educational and a clinical priority for the institution. One important way that alignment was achieved in the Collaborative was the explicit involvement of institutional leaders on each Pathway Innovators Steering Committee. This helped institutional leaders gain better understanding of the work of graduate medical education and promote and shape institutional strategies. Residents and fellows can identify challenges and become important allies to identify and solve systemic problems. In addition, each participating team created a business plan to gain buy-in from the C-suite by demonstrating the return on investment of meaningfully preparing faculty to effectively integrate residents, as well as other staff, into institutional improvement efforts. Interprofessional quality and safety initiatives were amplified and strengthened with broader participation. Bringing groups together helped standardized work and contributed to other efforts to improve patient outcomes, including length of stay, discharge planning, and interprofessional teamwork.A key element of success is ensuring that residents are not only aware of, but that they engage in health system–level approaches to improving quality, safety, value, and equity. The participants noted that it is especially important to ensure maximal impact and alignment of resident work with that of the health system. While many of the Collaborative organizations use Lean process improvement to drive transformation, residents were often an afterthought in the design of institutional improvement activities. The Collaborative helped institutional leaders reassess their Lean process improvement activities to include residents and fellows so they are able to enact changes that can improve patient care, interprofessional learning, and participation. These changes can be embedded into the system and thereby sustained after residents graduate. For example, several of the teams (Cleveland Clinic, Maine Medical Center, UCSF, University of Chicago, and University of Rochester) specifically integrated residents into existing systems-based improvement work using Lean transformation teams and Operational Excellence so that all residents learn and apply the institutional approach to quality improvement (Table).Local expertise, including coaches, can be an important and practical approach to successfully training residents to engage in institutional quality, safety, equity, and value work. Institutions developed models which fit with their existing institutional frameworks. Examples include bringing together groups of learners and frontline providers with institutional improvement experts (Rochester) and training a cadre of interprofessional faculty coaches to support ongoing trainee-led improvement work (Cleveland Clinic, UCSF). Some Collaborative teams used in-situ simulation to do this (Children's National), while others trained faculty to lead quality improvement discussions in the context of rounds (Our Lady of the Lake).Health care quality pioneer Ernest A. Codman, MD, stated, “To effect improvement, the first step is to admit and record the lack of perfection.”9 Residents are accustomed to receiving subjective feedback about their clinical performance. They may be less likely to receive or understand their patient outcomes for a variety of reasons, including lack of data and lack of appreciation of their own impact.10 Two key elements to consider when providing outcomes data are the extent to which the data are timely and actionable.11 In many large programs, residents rotate between services, units, and even health systems on a monthly basis. If residents are to change their own behavior based on data, they must receive data while they are still on the rotation. It's not necessary they receive their own individual data, as residents are members of teams affecting the care of a patient. However, at a minimum, they should have benchmarks to understand what they should aim to achieve.Residents should view the data as actionable (eg, residents' behavior changes may reasonably result in outcome changes). One can identify examples in which the link is linear (eg, timely removal of Foley catheters leads to fewer CAUTIs) or less linear (patients filling their post-discharge medications may depend on factors that are both within and beyond the trainees' control). Teams noted that faculty (physicians or non-physicians) need to be equipped to help residents understand how to interpret and contextualize data to drive behavior change which leads to better patient outcomes. In the collaborative, this often meant close alignment with the chief quality officer or quality staff to provide residents with access to existing quality dashboards or designing and deploying new ones.As checklists, backup processes, and other types of improvement work have become “standard work,” health care systems have come to depend on non-physician clinicians and staff to ensure that best practices are followed. Examples include having operating room nurses take responsibility for time outs or clinical pharmacists review medication orders for safety. Clinical educators can take advantage of teaching opportunities to focus on topics such as improvement science, rounding on visibility boards, or interprofessional collaboration. Faculty can role model how these systems-based topics are integrated into daily practice, rather than being viewed as an “add-ons.” For example, at Dell Medical School, faculty on one of their medicine teams, named the “Green Team,” test innovations in care while on service with their learners.The Pathway Innovators experience demonstrates that the secondary drivers can be used to guide integration of residents and fellows into the quality, safety, equity, and value mission of the Sponsoring Institution. Our experience was that the order of the steps mattered. In fact, for many participants, we found the ideal order was the reverse of how the secondary drivers were originally presented. It is important to note that to make progress, secondary drivers may need to be addressed concurrently, as appropriate to the institution or activity.While provision of resources and infrastructure are foundational, governance of most institutions was not designed to account for residents, making it harder to solicit support and create authentic roles for residents. Ironically, newer institutions may have an advantage because they can prospectively design systems to meaningfully integrate residents.Going forward, all institutions should be challenged to rethink CLEs to ensure that residents and fellows receive experiential learning not only in clinical care but also in the topics of quality, safety, equity, and value foundational to health systems science. For example, existing clinical rotations can be redesigned to incorporate a focus on systems-based practice, as a value add for the health system and for patient care. While documenting the impact of residents on quality, safety, equity, and value has been done and can be labor-intensive, measuring outcomes and return on investment is critical to sustainability and long-term commitment of resources.Perhaps most importantly, residents and fellows must also see the value in this integration. With increased workload and attention to well-being and burnout in training, faculty are obligated to demonstrate why quality, safety, equity, and value matter for patients, as well as for physician professional satisfaction and development. Leveraging external pressures can be a strategy for institutions to meaningfully engage residents and fellows.

BACKGROUND Integrating genomic data into electronic health records (EHRs) and clinical decision support (CDS) systems marks the beginning of a new era of precision medicine. Leveraging tailored insights from patient genomic data opens the door for patient care to have enhanced diagnosis, personalized treatment plans, and optimized medication management. OBJECTIVE This systematic review aims to examine the evolution of genetic data integration into Electronic Health Records by analyzing past developments, current implementation strategies, and future opportunities. It seeks to review historical milestones, identifying key advancements in genomic data collection, storage, and early integration efforts. It assesses current clinical practice and evaluates existing technologies and policies that shape the standards of genomic data interoperability. It also aims to highlight the technical, ethical, and regulatory challenges that hinder effective genomic integration and propose potential strategies and recommendations to address them. METHODS This systematic review follows PRISMA 2020 guidelines to ensure transparency and reproducibility. A comprehensive search was completed on the PubMed database with a predefined query and relevant inclusion and exclusion criteria. RESULTS A total of 48 articles were reviewed, with 27 included in the final review. Identified themes included technical integration, clinical utility, precision medicine, and human genome sequencing. These findings emphasize the role of AI, multi-omics data, APIs, and current work in maximizing the role of genetic data in clinical practice through integration in Electronic Health Records. CONCLUSIONS The integration journey is riddled with challenges such as data standardization, interoperability, data privacy, and resource constraints, which hinder the effective utilization of genomic information. This systematic review explores historical milestones, current practices, and future implementations in genomic data integration. It emphasizes the potential of emerging technologies like artificial intelligence, multi-omics data, next-generation sequencing, APIs, and automation to bridge existing gaps. Genomic integration can revolutionize healthcare delivery by harnessing these technologies, ensuring equitable and improved patient outcomes.

599 Background: The White House Cancer Moonshot initiative aims to reduce cancer death rates by half before 2047 and emphasizes the importance of access to clinical data to improve patient outcomes through enhanced data standardization and interoperability. Effective data capture remains a critical challenge with manual abstraction consuming significant clinician administrative time. The US Oncology Network (The Network) partnered with Ontada to leverage artificial intelligence (AI) and Fast Healthcare Interoperability Resources (FHIR) standards to advance clinical data submission for the Center for Medicare and Medicaid Innovation (CMMI) Enhancing Oncology Model (EOM). Methods: A pilot study was conducted with The Network (Compass Oncology) to implement Ontada's AI-driven technology to submit 58 clinical data elements for 232 patients required for EOM Performance Period 1. Structured clinical data elements were sourced from iKnowMed Generation 2 EHR using FHIR mCODE (Minimal Common Oncology Data Elements) HL7 industry standards. Natural Language Processing (NLP) and AI models were developed to enhance data capture from unstructured clinical documentation for diagnosis date, primary tumor characteristics, regional lymph nodes, distant metastases, and histology. A time and motion study was conducted via manual chart abstraction to measure administrative time reduction and data quality improvements. Data was submitted to CMMI via FHIR. Results: Across five critical data elements representing 909 possible data points analyzed for this study, 53.5% were sourced from structured data vs. 40.6% from unstructured clinical documentation using AI. The time and motion study confirmed a 38% reduction in provider administrative time. The AI-driven submission successfully achieved 98% data completeness for EOM patients, exceeding the 90% threshold required by CMMI. Conclusions: Results from the pilot study underscore the transformative potential of AI and data interoperability in oncology care. By leveraging NLP technology and FHIR-compliant data standards, substantial improvements in data capture were achieved while significantly reducing administrative burden. This supports the Cancer Moonshot vision for standardized, interoperable oncology data and provides a scalable model for enhancing practice efficiency. The success of this pilot establishes a foundation for expanded implementation across additional practices to meet future EOM data submission requirements. Source of clinical data elements. Data Element Structured Unstructured-AI Manual Chart Abstraction Not Found Total Diagnosis Date 106 108 16 2 232 Primary Tumor (T) 99 47 3 0 149 Regional Nodes (N) 98 42 8 0 148 Distant Mets (M) 96 43 9 0 148 Histology 87 129 13 3 232 Total 486 (53.5%) 369 (40.6%) 49 (5.4%) 5 (0.5%) 909 (100%)

Objective:This manuscript aims to provide a review and synthesis of contemporary advancements in footwear, sensor technology for remote monitoring, and digital health, with a focus on improving offloading and measuring and enhancing adherence to offloading in diabetic foot care.Methods:A narrative literature review was conducted by sourcing peer-reviewed articles, clinical studies, and technological innovations. This paper includes a review of various strategies, from specifically designed footwear, smart insoles and boots to using digital health interventions, which aim to offload plantar pressure and help prevent and manage wounds more effectively by improving the adherence to such offloading.Results:In-house specially made footwear, sensor technologies remotely measuring pressure and weight-bearing activity, exemplified for example, through applications like smart insoles and SmartBoot, and other digital health technologies, show promise in improving offloading and changing patient behaviour towards improving adherence to offloading and facilitating personalised care. This paper introduces the concept of gamification and emotive visual indicators as novel methods to enhance patient engagement. It further discusses the transformative role of digital health technologies in the modern era.Conclusions:The integration of technology with footwear and offloading devices offers unparallelled opportunities for improving diabetic foot disease management not only through better offloading but also through improved adherence to offloading. These advancements allow healthcare providers to personalise treatment plans more effectively, thereby promising a major improvement in patient outcomes in diabetic foot ulcer healing and prevention.

The Global Evidence Summit (GES2024), held in Prague from September 9 to 13, 2024, united scholars, healthcare professionals, and policymakers to tackle global health challenges. Among the diverse topics presented, implementation science stood out, emphasising collaboration to bridge evidence and practice gaps while fostering discussions on improving health systems and outcomes. Notably, many talks and posters focused on implementing clinical guideline recommendations—a critical and growing area of interest. However, a paradox remains: whilst the development of implementation tools is on the rise, their actual influence on clinical outcomes remains largely unquantified. The GES2024 presented numerous presentations on digital technologies, decision-support systems, and other advanced tools for disseminating and implementing clinical guidelines. For example, one exhibit showcased a mobile app designed to integrate palliative care guidelines into daily practice through a web-based platform for healthcare professionals. Despite their popularity and high levels of user engagement, evidence of these innovations' effectiveness in improving patient outcomes was limited. Many implementation tools gauge success through superficial metrics like downloads or user engagement, which primarily reflect conceptual use,1 while these metrics indicate awareness or understanding, they rarely lead to the behavioural or process changes characteristic of instrumental use. For meaningful and sustained impact, such efforts must progress beyond these surrogate outcomes to measurable clinical outcomes that directly improve patient care or system efficiency, aligning with the goals of knowledge translation and implementation science. For example, the palliative care platform received over 100,000 visits in its first 6 months, but data on patient impact were lacking. Measuring app downloads is different from evaluating their effect on patient outcomes. While high engagement numbers suggest interest, they do not indicate whether the guidelines improved patient care or symptom management. This raises a critical question: Are implementers failing to recognise the importance of measuring the true impact of these tools, or are clinical guidelines recommendations inherently difficult to assess in real-world practice? The literature emphasises that focusing only on engagement without assessing clinical outcomes undermines the main goal of guidelines—improving patient care. There is still a significant lack of information about the effective implementation of these recommendations. Despite existing frameworks, there is a shortage of evidence about real-world application and effectiveness. Research shows a persistent gap between creating guidelines and putting them into practice, often worsened by inconsistent adaptation across different contexts. This underscores the need for strong research methods to determine whether guidelines genuinely improve clinical practice and patient outcomes rather than relying solely on their potential impact.2-4 Successful implementation of clinical tools requires more than availability; it demands integration into routine practice, alongside continuous evaluation. The lack of data on how well these tools are embedded in healthcare demonstrates the need for comprehensive assessments of implementation outcomes. Guideline recommendations are complex to implement, and the strategies should integrate several approaches. Technological tools can be useful, and their effectiveness has been proven in the past,5 but it's important to consider that they are only a small piece of the puzzle. The hindrances behind a good implementation process are varied and depend on the specific context targeted for implementation.6, 7 The discussions at the GES offered a platform to rethink how the implementation of recommendations should be evaluated. This editorial seeks to raise awareness that implementing recommendations extends beyond technical assistance systems. It emphasises the importance of considering the broader context, including local adaptation, sustainability, and real-world outcomes, to ensure that guidelines effectively improve practice and patient care. The implementation process must be viewed as a dynamic, multifaceted endeavour rather than a purely technical task. I, Laura Alejandra Mora Moreo, confirm that I am the sole author of this manuscript. I made substantial contributions to the conception and interpretation of the work, drafted the manuscript, and revised it for important intellectual content. Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.

Introduction: Minimally Invasive Surgical (MIS) techniques have revolutionized the field of surgery, offering significant benefits over traditional open surgery. This narrative review examines the historical evolution, current advancements, and prospects of MIS, with a focus on its impact on patient outcomes, surgical training, and healthcare systems. Objective: To provide a comprehensive overview of the advancements in MIS, highlighting technological innovations, changes in clinical practice, and the evolution of surgical education. The review also aims to discuss the challenges and future directions of MIS. Methods: The review included 24 articles published from 2004 to 2023. Criteria for inclusion were relevance to MIS development and impact, with exclusion for non-English and unrelated articles. Data were synthesized to outline the progression, current state, and future trends in MIS. Results: Key findings include significant advancements in surgical technologies such as robotics and enhanced imaging, the expansion of MIS across various specialties, and improved patient outcomes like reduced recovery times and lower complication rates. Challenges identified include the steep learning curve for surgeons and disparities in global access to MIS. Future trends indicate a move towards AI integration, personalized surgical approaches, and further refinement of robotic systems. Conclusions: MIS represents a paradigm shift in surgical practice, characterized by technological innovation and improved patient care. Despite challenges, its future is promising, with continuous advancements expected to further reshape surgical procedures. Keywords: Minimally Invasive Surgical Procedures; Robotic Surgical Procedures; Surgical Education; Patient Outcome Assessment.

L’imagerie cerebrale a permis des progres considerables dans le domaine de la maladie d’Alzheimer (MA). Des criteres ont recemment ete proposes pour diagnostiquer la maladie a un stade plus precoce en s’appuyant sur des biomarqueurs d’imagerie. D’autre part la confrontation de multiples methodes d’imagerie permet d’evaluer les liens entre les differentes alterations qu’elles revelent afin de mieux comprendre les mecanismes de la maladie. Les objectifs principaux de cette these etaient d’une part de contribuer au developpement de biomarqueurs plus sensibles aux stades precoces de la MA, et d’autre part d’evaluer les liens entre depots amyloides, deficits metaboliques et atrophie cerebrale, en s’appuyant sur des techniques innovantes. Dans un premier temps, nous avons developpe une sequence IRM de haute resolution ciblee sur l’hippocampe ainsi qu’un protocole de delimitation des sous-champs hippocampiques que nous avons valides. Nous avons ainsi pu montrer que l’atrophie du sous-champ CA1 predominait et etait plus sensible que la mesure du volume de l’hippocampe entier pour distinguer des patients a un stade pre-dementiel de la MA. Au contraire, le vieillissement normal affectait preferentiellement un autre sous-champ : le subiculum. Dans un second temps, grâce a une approche multimodale, nous avons souligne les discordances dans la topographie des lesions caracteristiques de la MA, suggerant l’implication de differents mecanismes sous-jacents. De plus, les resultats indiquaient qu’atrophie et hypometabolisme ne sont pas correles aux depots amyloides chez les patients MA, indiquant l’absence de lien direct entre ces processus a ce stade avance de la maladie