Clinical Decision Support: Effectiveness in Improving Quality Processes and Clinical Outcomes and Factors That May Influence Success

The use of electronic health records has skyrocketed following the 2009 HITECH Act, which provides financial incentives to health care providers for the “meaningful use” of electronic medical record systems. An important component of the “Meaningful Use” legislation is the integration of Clinical Decision Support Systems (CDSS) into the computerized record, providing up-to-date medical knowledge and evidence-based guidance to the physician at the point of care. As reimbursement is increasingly tied to process and clinical outcomes, CDSS will be integral to future medical practice. Studies of CDSS indicate improvement in preventive services, appropriate care, and clinical and cost outcomes with strong evidence for CDSS effectiveness in process measures. Increasing provider adherence to CDSS recommendations is essential in improving CDSS effectiveness, and factors that influence adherence are currently under study.     

Clinical Verification of A Clinical Decision Support System for Ventilator Weaning

Background

Weaning is typically regarded as a process of discontinuing mechanical ventilation in the daily practice of an intensive care unit (ICU). Among the ICU patients, 39%-40% need mechanical ventilator for sustaining their lives. The predictive rate of successful weaning achieved only 35-60% for decisions made by physicians. Clinical decision support systems (CDSSs) are promising in enhancing diagnostic performance and improve healthcare quality in clinical setting. To our knowledge, a prospective study has never been conducted to verify the effectiveness of the CDSS in ventilator weaning before. In this study, the CDSS capable of predicting weaning outcome and reducing duration of ventilator support for patients has been verified.

Methods

A total of 380 patients admitted to the respiratory care center of the hospital were randomly assigned to either control or study group. In the control group, patients were weaned with traditional weaning method, while in the study group, patients were weaned with CDSS monitored by physicians. After excluding the patients who transferred to other hospitals, refused further treatments, or expired the admission period, data of 168 and 144 patients in the study and control groups, respectively, were used for analysis.

Results

The results show that a sensitivity of 87.7% has been achieved, which is significantly higher (p<0.01) than the weaning determined by physicians (sensitivity: 61.4%). Furthermore, the days using mechanical ventilator for the study group (38.41 ± 3.35) is significantly (p<0.001) shorter than the control group (43.69 ± 14.89), with a decrease of 5.2 days in average, resulting in a saving of healthcare cost of NT$45,000 (US$1,500) per patient in the current Taiwanese National Health Insurance setting.

Conclusions

The CDSS is demonstrated to be effective in identifying the earliest time of ventilator weaning for patients to resume and sustain spontaneous breathing, thereby avoiding unnecessary prolonged ventilator use and decreasing healthcare cost.

     

Détection et prévention des effets indésirables liés aux médicaments par data-mining

Adverse drug events would be responsible from 10,000 death per year in France. Most often, detection relies on events declaration; alert and prevention rules are writen by experts thanks to cases reviews. Moreover, the medical departments’ specificities are not taken into account (patients, practices, knowledge). The objectives of the PSIP European project is to use data-mining to detect those events and automatically generate control rules, department by department. Using 10,500 French and Danish stays, we obtain till now 630 rules from which 75 have been validated. The article shows an example of a decision tree and its interpretation in the field of cautions taken during vitamin K antagonists’ use. Results’ exploitation cannot elude contextualization. A similar process may have many different uses.     

Computerised order entry systems and pathology services--a synthesis of the evidence

Computerised Physician Order Entry (CPOE) systems have been promoted in Australia and internationally for their potential to improve the quality of care. The existing research of the effect of CPOE on pathology laboratories has been variable, pointing to the potential to increase efficiency and effectiveness and contribute to enhancing the quality of patient care on the one hand, while leading to significant disruptions in work organisation with a negative impact on departmental relations on the other hand. In this paper we provide an overview of the research evidence about the impact of CPOE on four areas associated with pathology services; a) efficiency of the ordering process, e.g. test turnaround times, b) effectiveness as measured by test ordering volumes and test order appropriateness, c) quality of care, particularly its effects on patient care and d) work organisation patterns, which can be severely disrupted by CPOE. We discuss the possible ramifications of CPOE and offer three broad, but important recommendations for pathology laboratories, based on our own research experience investigating CPOE implementations over three years. Firstly, pathology laboratories need to be active participants in planning the implementation of CPOE. Secondly, the importance of building a firm organisational foundation for the introduction of the new system that includes openness and responsiveness to feedback. And thirdly, the implementation process needs to be underpinned by a strong commitment to a multi-method evaluation at every stage of the process to be able to measure the impact of the system on work practices and outcomes.     

A Taxonomic Review of the Use of IoT and Blockchain in Healthcare Applications

ObjectivesWith the rapid evolution and technology advancement, the healthcare sector is evolving day by day. It is taking advantage of different technologies such as Internet of things and Blockchain. Several applications related to daily healthcare activities are adopting the use of these technologies. In this paper, we present a review in which we group different healthcare applications that integrate the Internet of things and Blockchain in their systems.Material and methodsA review study about the integration of IoT and Blockchain in healthcare systems was conducted. We searched the databases ScienceDirect, IEEE Xplore, Google Scholar and ACM Digital Library.ResultsThis review focuses on categorizing the use cases of IoT and Blockchain in the healthcare sector. The study listed 6 applications in medical services, namely, remote patient monitoring, electronic medical records management, disease prediction, patient tracking, drug traceability and fighting infectious disease especially COVID-19. The paper also investigates the challenges associated with the adoption of the Blockchain technology in healthcare IoT-based systems and some of the existing solutions. It also introduces some future research directions.ConclusionThe survey of the use cases of IoT and Blockchain in the healthcare sector will serve as a state of the art for future researches. In addition, the paper gives some directions to new possible researches that could help to revolutionize the healthcare sector by using other technologies such as artificial intelligence, big data, fog and cloud computing.     

Enterprise imaging and big data: A review from a medical physics perspective

In recent years enterprise imaging (EI) solutions have become a core component of healthcare initiatives, while a simultaneous rise in big data has opened up a number of possibilities in how we can analyze and derive insights from large amounts of medical data. Together they afford us a range of opportunities that can transform healthcare in many fields. This paper provides a review of recent developments in EI and big data in the context of medical physics. It summarizes the key aspects of EI and big data in practice, with discussion and consideration of the steps necessary to implement an EI strategy. It examines the benefits that a healthcare service can achieve through the implementation of an EI solution by looking at it through the lenses of: compliance, improving patient care, maximizing revenue, optimizing workflows, and applications of artificial intelligence that support enterprise imaging. It also addresses some of the key challenges in enterprise imaging, with discussion and examples presented for those in systems integration, governance, and data security and privacy.     

Electronic Laboratory Medicine ordering with evidence-based Order sets in primary care (ELMO study): protocol for a cluster randomised trial

Background

Laboratory testing is an important clinical act with a valuable role in screening, diagnosis, management and monitoring of diseases or therapies. However, inappropriate laboratory test ordering is frequent, burdening health care spending and negatively influencing quality of care. Inappropriate tests may also result in false-positive results and potentially cause excessive downstream activities. Clinical decision support systems (CDSSs) have shown promising results to influence the test-ordering behaviour of physicians and to improve appropriateness. Order sets, a form of CDSS where a limited set of evidence-based tests are proposed for a series of indications, integrated in a computerised physician order entry (CPOE) have been shown to be effective in reducing the volume of ordered laboratory tests but convincing evidence that they influence appropriateness is lacking. The aim of this study is to evaluate the effect of order sets on the quality and quantity of laboratory test orders by physicians. We also aim to evaluate the effect of order sets on diagnostic error and explore the effect on downstream or cascade activities.

Methods

We will conduct a cluster randomised controlled trial in Belgian primary care practices. The study is powered to measure two outcomes. We will primarily measure the influence of our CDSS on the appropriateness of laboratory test ordering. Additionally, we will also measure the influence on diagnostic error. We will also explore the effects of our intervention on cascade activities due to altered results of inappropriate tests.

Discussion

We have designed a study that should be able to demonstrate whether the CDSS aimed at diagnostic testing is not only able to influence appropriateness but also safe with respect to diagnostic error. These findings will influence a lager, nationwide implementation of this CDSS.

Trial registration

ClinicalTrials.gov, NCT02950142.

     

Theme C: Medical information systems and databases – results and future work

This paper presents the activities of the theme C “medical information systems and databases” in the GDR Stic Santé. Six one-day workshops have been organized during the period 2011–2012. They were devoted to 1) sharing anatomical and physiological object models for simulation of clinical medical images, 2) advantages and limitations of datawarehouse for biological data, 3) medical information engineering, 4) systems for sharing medical images for research, 5) knowledge engineering for semantic interoperability in e-health applications, and 6) using context in health. In the future, our activities will continue with a specific interest on information systems for translational medicine and the role of electronic healthcare reports in decision-making. Workshops with other research groups will be organized in particular with the e-health research group.     

Expert systems and the pancreatic cancer problem: decision support in the pre-operative diagnosis

In this paper, after reviewing the main issue in artificial intelligence, decision support systems, medical decision-making, expert systems and some of their applications in medicine, we focus on the diagnostic aspect of pancreatic cancer. We briefly examine the most significant applications both from the oncological and from the diagnostic point of view. We discuss the medical problems mentioning incidence and mortality, aetiological factors and diagnosis, considering the roles of surgery and adjuvant therapies. Finally we justify the decision to develop an expert system in such a medical domain and discuss the SPES (Surgical Pancreatic Expert System) project, its parts dealing with the different medical phases of pancreatic cancer diagnosis and therapy: pre-operative, intra-operative and adjuvant therapies. In particular we discuss diagnostic aspects of pancreatic cancer disease, pointing out the aims of the project, methodologies, tools used and future developments.     

基于HIS模型建立肝病知识库对军队医院的作用及意义

目的:通过整合302医院丰富的肝病病例、肝病专家诊疗经验和临床科研数据,建立肝病知识库,提高基础资源辅助临床诊疗和科研的能力。方法:对肝病智能知识模型进行分析,获取知识库中结构化知识,并以知识库模型的形式建立知识库,形成一套独立、可重复的智能化的辅助诊疗和科研信息系统,实现知识库辅助临床诊疗、知识科学研究,最大程度发挥知识库的意义,真正为临床服务。结果:建立的基于HIS的肝病知识库主要编配于医疗单位,适用于临床医护人员、临床科研人员以及所有从事医疗行业的工作人员。医护工作者可通过程序访问知识库,对知识库中的肝病知识进行检索、分析、推理,辅助临床医护工作者提高临床诊疗能力,提升临床科研水平。结论:建立的肝病知识库系统为用户提供横向及纵向医疗基础信息的检索、分析及推理方法。推理出的合适的知识模型,为肝病的临床诊疗和临床科研提供前沿、实用、高效的智能辅助信息支持。     

Recent Advances in Nanogenerator‐Driven Self‐Powered Implantable Biomedical Devices

Implantable medical devices (IMDs) have experienced a rapid progress in recent years to the advancement of state‐of‐the‐art medical practices. However, the majority of this equipment requires external power sources like batteries to operate, which may restrict their application for in vivo situations. Furthermore, these external batteries of the IMDs need to be changed at times by surgical processes once expired, causing bodily and psychological annoyance to patients and rising healthcare financial burdens. Currently, harvesting biomechanical energy in vivo is considered as one of the most crucial energy‐based technologies to ensure sustainable operation of implanted medical devices. This review aims to highlight recent improvements in implantable triboelectric nanogenerators (iTENG) and implantable piezoelectric nanogenerators (iPENG) to drive self‐powered, wireless healthcare systems. Furthermore, their potential applications in cardiac monitoring, pacemaker energizing, nerve‐cell stimulating, orthodontic treatment and real‐time biomedical monitoring by scavenging the biomechanical power within the human body, such as heart beating, blood flowing, breathing, muscle stretching and continuous vibration of the lung are summarized and presented. Finally, a few crucial problems which significantly affect the output performance of iTENGs and iPENGs under in vivo environments are addressed.     

A prospective multiple case study of the impact of emerging scientific evidence on established colorectal cancer screening programs: a study protocol

In this editorial, we reflect on the arguments for starting a scientific society focused on research on how to improve healthcare. This society would take an inclusive approach to what constitutes healthcare. For instance, it should include mental health healthcare, treatment for substance abuse, the work of allied health professions, and preventive healthcare. The society would be open to researchers from all traditions. Thus, we take an inclusive approach to what constitutes scientific research, as long as it uses rigorous methods, is focused on improving healthcare, and aims at knowledge that can be transferred across settings. The society would primarily target scientific researchers but would invite others with an interest in this area of research, regardless of their discipline, position, field of application, or group affiliation (e.g., improvement science, behavioral medicine, knowledge translation). A society would need fruitful collaboration with related societies and organizations, which may include having combined meetings. Special links may be developed with one or more journals. A website to provide information on relevant resources, events, and training opportunities is another key activity. It would also provide a voice for the field at funding agencies, political arenas, and similar institutions. An organizational structure and financial resources are required to develop and run these activities. Our aim is to start an international debate, to discover if we can establish a shared vision across academics and stakeholders engaged with creating scientific knowledge on how to improve healthcare. We invite readers to express their views in the online questionnaire accessed by following the URL link provided at the end of the editorial.     

Virtual telepathology in Egypt,applications of WSI in Cairo University

Telepathology, the practice of pathology at a long distance, has advanced continuously since 1986. Today, fourth-generation telepathology systems, so-called virtual slide telepathology systems, are being used for education applications. Both conventional and innovative surgical pathology diagnostic services are being designed and implemented as well. We have a successful experience in Egypt in applying the static & dynamic techniques in a pilot project between the Italian Hospital in Cairo (NPO) and the Civico Hospital in Palermo This project began in 2003 and continued till now. In 2004, centers in Venice, London and Pittsburgh participated actively in our project. During the past seven years we consulted on many problematic pathological cases with these different specialized pathological centers in Italy, UK & USA. In addition to the highly specialized scientific value of consulting on the cases and exchanging knowledge, we saved a lot of time and money and succeeded in providing our patients with a better medical service. In view of this success we have already established a new Digital Telepathology unit (DTU) in the pathology department, Cairo University, using the latest technique of telepathology which is Whole Slide Imaging (WSI) since one year. This unit is considered the first Digital pathology unit in all the universities of the whole Middle East. During the passed year we created a digital pathology library for the under graduate students using the WSI technique and changed the teaching method of the histopathology slides to be completely digital. We are building another digital pathology library (for post graduate candidates) which will be available to all pathology candidates in Egyptian universities & universities in the surrounding Arabic countries. We are also creating a digital pathology network between pathology centers in the Middle East for exchanging knowledge & telepathology.     

AI applications to medical images: From machine learning to deep learning

PurposeArtificial intelligence (AI) models are playing an increasing role in biomedical research and healthcare services. This review focuses on challenges points to be clarified about how to develop AI applications as clinical decision support systems in the real-world context.MethodsA narrative review has been performed including a critical assessment of articles published between 1989 and 2021 that guided challenging sections.ResultsWe first illustrate the architectural characteristics of machine learning (ML)/radiomics and deep learning (DL) approaches. For ML/radiomics, the phases of feature selection and of training, validation, and testing are described. DL models are presented as multi-layered artificial/convolutional neural networks, allowing us to directly process images. The data curation section includes technical steps such as image labelling, image annotation (with segmentation as a crucial step in radiomics), data harmonization (enabling compensation for differences in imaging protocols that typically generate noise in non-AI imaging studies) and federated learning. Thereafter, we dedicate specific sections to: sample size calculation, considering multiple testing in AI approaches; procedures for data augmentation to work with limited and unbalanced datasets; and the interpretability of AI models (the so-called black box issue). Pros and cons for choosing ML versus DL to implement AI applications to medical imaging are finally presented in a synoptic way.ConclusionsBiomedicine and healthcare systems are one of the most important fields for AI applications and medical imaging is probably the most suitable and promising domain. Clarification of specific challenging points facilitates the development of such systems and their translation to clinical practice.     

Artificial intelligence and the medical physics profession - A Swedish perspective

BackgroundThere is a continuous and dynamic discussion on artificial intelligence (AI) in present-day society. AI is expected to impact on healthcare processes and could contribute to a more sustainable use of resources allocated to healthcare in the future. The aim for this work was to establish a foundation for a Swedish perspective on the potential effect of AI on the medical physics profession.Materials and methodsWe designed a survey to gauge viewpoints regarding AI in the Swedish medical physics community. Based on the survey results and present-day situation in Sweden, a SWOT analysis was performed on the implications of AI for the medical physics profession.ResultsOut of 411 survey recipients, 163 responded (40%). The Swedish medical physicists with a professional license believed (90%) that AI would change the practice of medical physics but did not foresee (81%) that AI would pose a risk to their practice and career. The respondents were largely positive to the inclusion of AI in educational programmes. According to self-assessment, the respondents’ knowledge of and workplace preparedness for AI was generally low.ConclusionsFrom the survey and SWOT analysis we conclude that AI will change the medical physics profession and that there are opportunities for the profession associated with the adoption of AI in healthcare. To overcome the weakness of limited AI knowledge, potentially threatening the role of medical physicists, and build upon the strong position in Swedish healthcare, medical physics education and training should include learning objectives on AI.     

Linking engineering and medicine: fostering collaboration skills in interdisciplinary teams

Biomedical engineering embodies the spirit of combining disciplines. The engineer's pragmatic approach to--and appetite for--solving problems is matched by a bounty of technical challenges generated in medical domains. From nanoscale diagnostics to the redesign of systems of health-care delivery, engineers have been connecting advances in basic and applied science with applications that have helped to improve medical care and outcomes. Increasingly, however, integrating these areas of knowledge and application is less individualistic and more of a team sport. Success increasingly relies on a direct focus on practicing and developing collaboration skills in interdisciplinary teams. Such an approach does not fit easily into individual-focused, discipline-based programs. Biomedical engineering has done its fair share of silo busting, but new approaches are needed to inspire interdisciplinary teams to form around challenges in particular areas. Health care offers a wide variety of complex challenges across an array of delivery settings that can call for new interdisciplinary approaches. This was recognized by the deans of the University of Southern California's (USC's) Medical and Engineering Schools when they began the planning process, leading to the creation of the Health, Technology, and Engineering (HTE@USC or HTE for short) program. “Health care and technology are changing rapidly, and future physicians and engineers need intellectual tools to stay ahead of this change,” says Carmen A. Puliafito, dean of the Keck School of Medicine. His goal is to train national leaders in the quest for devices and processes to improve health care.     

Snakebites in “Invisible Populations”: A cross-sectional survey in riverine populations in the remote western Brazilian Amazon

In the Brazilian Amazon, long distances, low healthcare coverage, common use of ineffective or deleterious self-care practices, and resistance to seeking medical assistance have an impact on access to antivenom treatment. This study aimed to estimate snakebite underreporting, and analyze barriers that prevent victims from obtaining healthcare in communities located in 15 municipalities on the banks of the Solimões, Juruá and Purus Rivers, in the remote Western Brazilian Amazon. Information on the participants’ demographics, previous snakebites, access to healthcare, time taken to reach medical assistance, use of self-care practices, and the reason for not accessing healthcare were collected through semi-structured interviews. In the case of deaths, information was collected by interviewing parents, relatives or acquaintances. A total of 172 participants who reported having suffered snakebites during their lifetime were interviewed. A total of 73 different treatment procedures was reported by 65.1% of the participants. Participants living in different river basins share few self-care procedures that use traditional medicine, and 91 (52.9%) participants reported that they had access to healthcare. Living in communities along the Juruá River [OR = 12.6 (95% CI = 3.2–49.7; p<0.001)] and the use of traditional medicine [OR = 11.6 (95% CI = 3.4–39.8; p<0.001)] were variables that were independently associated to the lack of access to healthcare. The main reasons for not accessing healthcare were the pprioritization of traditional treatments (70.4%), and the failure to recognize the situation as being potentially severe (50.6%). Four deaths from complications arising from the snakebite were reported, and three of these were from communities on the banks of the Juruá River. Only one of these received medical assistance. We found an unexpectedly high underreporting of snakebite cases and associated deaths. Snakebite victims utilized three main different healing systems: 1) self-care using miscellaneous techniques; 2) official medical healthcare generally combined with traditional practices; and 3) self-care using traditional practices combined with Western medicines. To mitigate snakebite burden in the Brazilian Amazon, an innovative intervention that would optimize timely delivery of care, including antivenom distribution among existing community healthcare centers, is needed.