A Generic Approach to Supporting the Management of Computerised Clinical Guidelines and Protocols

Clinical guidelines or protocols (CGPs) are statements that are systematically developed for the purpose of guiding the clinician and the patient in making decisions about appropriate healthcare for specific clinical problems. Using CGPs is one of the most effective and proven ways to attaining improved quality, optimised resource utilisation, cost containment and reduced variation in healthcare practice. CGPs exist mainly as paper-based natural language statements, but are increasingly being computerised. Supporting computerised CGPs in a healthcare environment so that they are incorporated into the routine used daily by clinicians is complex and presents major information management challenges. This thesis contends that the management of computerised CGPs should incorporate their manipulation (operations and queries), in addition to their specification and execution, as part of a single unified management framework. The thesis applies modern advanced database technology to the task of managing computerised CGPs. The event-condition-action (ECA) rule paradigm is recognised to have a huge potential in supporting computerised CGPs. In this thesis, a unified generic framework, called SpEM and an approach, called MonCooS, were developed for enabling computerised CGPs, to be specified by using a specification language, called PLAN, which follows the ECA rule paradigm; executed by using a software mechanism based on the ECA mechanism within a modern database system, and manipulated by using a manipulation language, called TOPSQL. The MonCooS approach focuses on providing clinicians with assistance in monitoring and coordinating clinical interventions while leaving the reasoning task to domain experts. A proof-of-concepts system, TOPS, was developed to show that CGP management can be easily attained, within the SpEM framework, by using the MonCooS approach. TOPS is used to evaluate the framework and approach in a case study to manage a microalbuminuria protocol for diabetic patients. SpEM and MonCooS were found to be promising in supporting the full-scale management of information and knowledge for the computerised clinical protocol. Active capability within modern DBMS is still experiencing significant limitations in supporting some requirements of this application domain. These limitations lead to pointers for further improvements in database management system (DBMS) functionality for ECA rule support. The main contributions of this thesis are: a generic and unified framework for the management of CGPs; a general platform and an advanced software mechanism for the manipulation of information and knowledge in computerised CGPs; a requirement for further development of the active functionality within modern DBMS; and a case study for the computer-based management of microalbuminuria in diabetes patients

Automated conflict resolution between multiple clinical pathways:A technology report

Background The number of people in the UK with three or more long-term conditions continues to grow and the management of patients with co-morbidities is complex. In treating patients with multimorbidities, a fundamental problem is understanding and detecting points of conflict between different guidelines which to date has relied on individual clinicians collating disparate information. Objective We will develop a framework for modelling a diverse set of care pathways, and investigate how conflicts can be detected and resolved automatically. We will use this knowledge to develop a software tool for use by clinicians that can map guidelines, highlight root causes of conflict between these guidelines and suggest ways they might be resolved. Method Our work consists of three phases. First, we will accurately model clinical pathways for six of the most common chronic diseases; second, we will automatically identify and detect sources of conflict across the pathways and how they might be resolved. Third, we will present a case study to prove the validity of our approach using a team of clinicians to detect and resolve the conflicts in the treatment of a fictional patient with multiple common morbidities and compare their findings and recommendations with those derived automatically using our novel software. Discussion This paper describes the development of an important software-based method for identifying a conflict between clinical guidelines. Our findings will support clinicians treating patients with multimorbidity in both primary and secondary care settings

Artificial intelligence applications in disease diagnosis and treatment: recent progress and outlook

The use of computers and other technologies to replicate human-like intelligent behaviour and critical thinking is known as artificial intelligence (AI).The development of AI-assisted applications and big data research has accelerated as a result of the rapid advancements in computing power, sensor technology, and platform accessibility that have accompanied advances in artificial intelligence. AI models and algorithms for planning and diagnosing endodontic procedures. The search engine evaluated information on artificial intelligence (AI) and its function in the field of endodontics, and it also incorporated databases like Google Scholar, PubMed, and Science Direct with the search criterion of original research articles published in English. Online appointment scheduling, online check-in at medical facilities, digitization of medical records, reminder calls for follow-up appointments and immunisation dates for children and pregnant women, as well as drug dosage algorithms and adverse effect warnings when prescribing multidrug combinations, are just a few of the tasks that already use artificial intelligence. Data from the review supported the conclusion that AI can play a significant role in endodontics, including the identification of apical lesions, classification and numbering of teeth, detection of dental caries, periodontitis, and periapical disease, diagnosis of various dental problems, aiding dentists in making referrals, and helping them develop more precise treatment plans for dental disorders. Although artificial intelligence (AI) has the potential to drastically alter how medicine is practised in ways that were previously unthinkable, many of its practical applications are still in their infancy and need additional research and development. Over the past ten years, artificial intelligence in ophthalmology has grown significantly and will continue to do so as imaging techniques and data processing algorithms improve

Task Shifting and Health System Design: Report of the Expert Panel on effective ways of investing in Health (EXPH)

Imagine a health professional in any European country who fell asleep in 1960 and awoke in a health facility in 2019. Much of what the observer saw would be quite different. There would be many more patients who were surviving into old age thanks to advances in therapy. Many of the treatments that they were receiving would be much more complex, involving radically new techniques such as laparoscopic or even robotic surgery, and they would be amazed by the advances in diagnostic capacity. Yet, in many health systems, some things would have changed very little. Among them would be the traditional roles of different types of health worker, with responsibility for certain task being reserved for those with particular qualifications based on custom and practice rather than on evidence. This opinion argues that this situation must change. There is now an impressive body of evidence that things can often be done differently. This does not mean that they should be. Change is only appropriate where it helps to achieve the goals of the health system and allows it to provide better care in ways that are more responsive to the needs of users. Tasks can be shifted from health workers to patients and their carers, to machines, and to other health workers. Where these shifts have been evaluated, they often, but not always, are associated with outcomes that are as good or even better than with the status quo. However, the results are often context dependent, and it cannot be assumed that what works in one situation will apply equally to another. What matters is the evidence, rather than traditional, but often obsolete rules. If a health system can ensure that tasks are being undertaken by those most appropriate to do them, it will enhance patient care. However, change is often difficult. Those involved must be convinced of the rationale for change and must be supported in implementing it. This should recognise that any change in roles will have implication for their status and thus existing hierarchies. It may also be necessary to challenge outdated legislative or regulatory barriers. Finally, it is essential the changes are evaluated, results are documented, and lessons are learned, both in relation to what works and in what circumstances. Task shifting, where it is based on robust evidence and implemented effectively, can make a major contribution to health outcomes and to the sustainability of health systems. It is not, however, a panacea for all of the challenges health systems face.Představte si zdravotnického odborníka v kterékoli evropské zemi, který usnul v roce 1960 a probudil se ve zdravotnickém zařízení v roce 2019. Hodně z toho, co by pozorovatel viděl, by bylo úplně jiné. Bylo by mnohem více pacientů, kteří přežili do stáří díky pokrokům v terapii. Mnoho z ošetření, které dostávali, by bylo mnohem složitější, zahrnovalo radikálně nové techniky, jako je laparoskopická nebo dokonce robotická chirurgie, a byl by ohromen pokrokem v diagnostickém rozsahu. Přesto by se v mnoha zdravotnických systémech některé věci změnily jen velmi málo. Mezi nimi by byly tradiční role různých typů zdravotnických pracovníků, přičemž odpovědnost za určitý úkol by byla vyhrazena těm, kteří mají zvláštní kvalifikaci založenou spíše na zvyklostech a praxi než na důkazech. Toto stanovisko tvrdí, že se tato situace musí změnit. Nyní existuje impozantní soubor důkazů, že věci lze často dělat jinak. To neznamená, že by měli být jinak dělány. Změna je vhodná pouze tam, kde pomáhá dosahovat cílů zdravotnického systému a umožňuje jí poskytovat lepší péči způsoby, které lépe reagují na potřeby uživatelů. Úkoly lze převádět ze zdravotnických pracovníků na pacienty a jejich pečovatele, na stroje a další zdravotnické pracovníky. Tam, kde byly tyto posuny vyhodnoceny, jsou často, ale ne vždy, spojeny s výsledky, které jsou stejně dobré nebo dokonce lepší než za současného stavu. Výsledky jsou však často závislé na kontextu a nelze předpokládat, že to, co funguje v jedné situaci, se bude vztahovat stejně na jiné. Důležitý je důkaz spíše než tradiční, ale často zastaralá pravidla. Pokud zdravotní systém může zajistit, že osoby, které jsou pro ně nejvhodnější, plní správně alokované úkoly, zlepší se péče o pacienty. Změna je však často obtížná. Zúčastněné strany musí být přesvědčeny o důvodech změny a musí být podporovány při jejich provádění. Musí uznat, že každá změna rolí bude mít dopad na jejich stav, a tedy na existující hierarchie. Může být také třeba změnit zastaralé legislativní nebo regulační překážky. Nakonec je nezbytné, aby byly změny vyhodnoceny, výsledky zdokumentovány a vedly k ponaučení, co funguje a za jakých okolností. Posun úkolů, činností a kompetencí, pokud je založen na spolehlivých důkazech a je účinně prováděn, může významně přispět k lepším výsledkům v oblasti zdraví a k udržitelnosti zdravotních systémů. Nejedná se však o všelék na všechny výzvy, kterým zdravotnické systémy čelí.Imagine a health professional in any European country who fell asleep in 1960 and awoke in a health facility in 2019. Much of what the observer saw would be quite different. There would be many more patients who were surviving into old age thanks to advances in therapy. Many of the treatments that they were receiving would be much more complex, involving radically new techniques such as laparoscopic or even robotic surgery, and they would be amazed by the advances in diagnostic capacity. Yet, in many health systems, some things would have changed very little. Among them would be the traditional roles of different types of health worker, with responsibility for certain task being reserved for those with particular qualifications based on custom and practice rather than on evidence. This opinion argues that this situation must change. There is now an impressive body of evidence that things can often be done differently. This does not mean that they should be. Change is only appropriate where it helps to achieve the goals of the health system and allows it to provide better care in ways that are more responsive to the needs of users. Tasks can be shifted from health workers to patients and their carers, to machines, and to other health workers. Where these shifts have been evaluated, they often, but not always, are associated with outcomes that are as good or even better than with the status quo. However, the results are often context dependent, and it cannot be assumed that what works in one situation will apply equally to another. What matters is the evidence, rather than traditional, but often obsolete rules. If a health system can ensure that tasks are being undertaken by those most appropriate to do them, it will enhance patient care. However, change is often difficult. Those involved must be convinced of the rationale for change and must be supported in implementing it. This should recognise that any change in roles will have implication for their status and thus existing hierarchies. It may also be necessary to challenge outdated legislative or regulatory barriers. Finally, it is essential the changes are evaluated, results are documented, and lessons are learned, both in relation to what works and in what circumstances. Task shifting, where it is based on robust evidence and implemented effectively, can make a major contribution to health outcomes and to the sustainability of health systems. It is not, however, a panacea for all of the challenges health systems face

Health Care Equity Through Intelligent Edge Computing and Augmented Reality/Virtual Reality: A Systematic Review

Intellectual capital is a scarce resource in the healthcare industry. Making the most of this resource is the first step toward achieving a completely intelligent healthcare system. However, most existing centralized and deep learning-based systems are unable to adapt to the growing volume of global health records and face application issues. To balance the scarcity of healthcare resources, the emerging trend of IoMT (Internet of Medical Things) and edge computing will be very practical and cost-effective. A full examination of the transformational role of intelligent edge computing in the IoMT era to attain health care equity is offered in this research. Intelligent edge computing-aided distribution and collaborative information management is a possible approach for a long-term digital healthcare system. Furthermore, IEC (Intelligent Edge Computing) encourages digital health data to be processed only at the edge, minimizing the amount of information exchanged with central servers/the internet. This significantly increases the privacy of digital health data. Another critical component of a sustainable healthcare system is affordability in digital healthcare. Affordability in digital healthcare is another key component of a sustainable healthcare system. Despite its importance, it has received little attention due to its complexity. In isolated and rural areas where expensive equipment is unavailable, IEC with AR / VR, also known as edge device shadow, can play a significant role in the inexpensive data collection process. Healthcare equity becomes a reality by combining intelligent edge device shadows and edge computing

2023 IMSAloquium

Welcome to IMSAloquium 2023. This is IMSA’s 36 th year of leading in educationalinnovation, and the 35th year of the IMSA Student Inquiry and Research (SIR) Program.https://digitalcommons.imsa.edu/archives_sir/1033/thumbnail.jp