Potential Cost Implications of Mandatory Non-Medical Switching Policies for Biologics for Rheumatic Conditions and Inflammatory Bowel Disease in Canada

In 2018, TNFα inhibitors were the highest cost drug class for Canadian public drug programs. In 2019, two Canadian provinces announced mandatory nonmedical switching policies in an attempt to reduce their costs by increasing biosimilar uptake. The national impact of similar policies across Canada is unknown. We conducted a cross-sectional analysis of monthly publicly funded prescription claims for infliximab, etanercept, and adalimumab between June 2015 and December 2019. We reported the market share of biosimilars for infliximab and etanercept in 2019 for each province and estimated the cost savings that public payers could have realized in 2019 if mandatory switching policies had been implemented across Canada, including a sensitivity analysis, which assumed that governments receive a 25% rebate on all biologics. Provincial drug programs spent CAD $991.84 million on infliximab, etanercept, and adalimumab in 2019, and, when biosimilars were available, they constituted only 15.5% of national utilization of these drugs. In British Columbia, the implementation of a mandatory switching policy for patients with rheumatic conditions increased the biosimilar market share of infliximab and etanercept by 299% (from 19.7% to 78.5%). If applied nationwide to all three biologics for all indications, we estimate such policies could lead to annual savings of between CAD $179.71 million and CAD $425.64 million nationally. The overall market share of biosimilars remains low in all provinces where mandatory switching policies have not been introduced. The cost implications of successfully increasing biosimilar uptake would be substantial, particularly as more biosimilars reach the Canadian market.

Hospital admissions after vertical integration of general practices with an acute hospital: a retrospective synthetic matched controlled database study

Background

New healthcare models are being explored to enhance care coordination, efficiency, and outcomes. Evidence is scarce regarding the impact of vertical integration of primary and secondary care on emergency department (ED) attendances, unplanned hospital admissions, and readmissions.

Aim

To examine the impact of vertical integration of an NHS provider hospital and 10 general practices on unplanned hospital care

Design and setting

A retrospective database study using synthetic controls of an NHS hospital in Wolverhampton integrated with 10 general practices, providing primary medical services for 67 402 registered patients.

Method

For each vertical integration GP practice, a synthetic counterpart was constructed. The difference in rate of ED attendances, unplanned hospital admissions, and unplanned hospital readmissions was compared, and pooled across vertical integration practices versus synthetic control practices pre-intervention versus post-intervention.

Results

Across the 10 practices, pooled rates of ED attendances did not change significantly after vertical integration. However, there were statistically significant reductions in the rates of unplanned hospital admissions (−0.11, 95% CI = −0.18 to −0.045, P = 0.0012) and unplanned hospital readmissions (−0.021, 95% CI = −0.037 to −0.0049, P = 0.012), per 100 patients per month. These effect sizes represent 888 avoided unplanned hospital admissions and 168 readmissions for a population of 67 402 patients per annum. Utilising NHS reference costs, the estimated savings from the reductions in unplanned care are ∼£1.7 million.

Conclusion

Vertical integration was associated with a reduction in the rate of unplanned hospital admissions and readmissions in this study. Further work is required to understand the mechanisms involved in this complex intervention, to assess the generalisability of these findings, and to determine the impact on patient satisfaction, health outcomes, and GP workload.

Quality of Care Standards in Inflammatory Bowel Diseases: a European Crohn's and Colitis Organisation [ECCO] Position Paper

The management of inflammatory bowel disease [IBD] is complex, and requires tight control of disease activity, close monitoring to avoid treatment side effects, health care professionals with expertise in IBD, and an interdisciplinary, holistic approach. Despite various efforts to standardise structures, processes, and outcomes,1-8 and due to the high variability at the local, national, and international levels, there are still no clear definitions or outcome measures available to establish quality of care standards for IBD patients which are applicable in all contexts and all countries. For this reason, the European Crohn's and Colitis Organisation [ECCO] supported the construction of a list of criteria summarising current standards of care in IBD. The list comprises 111 quality standard points grouped into three main domains [structure n = 31, process n = 42, outcomes n = 38] and is based on scientific evidence, interdisciplinary expert consensus, and patient-oriented perspectives. The list of proposed criteria is intended to represent the position of ECCO regarding the optimum quality of care that should be available to patients. Since health care systems and regulations vary considerably between countries, this list may require adaptation at local and national levels. It is recognised that not all these criteria that have been identified as optimal will be available in every unit. However, ECCO will continue its efforts to develop and coordinate projects and initiatives that will help to guarantee optimal quality of care for all IBD patients.

Role of immersive technologies in healthcare education during the COVID-19 epidemic

The unparalleled epidemic of the novel coronavirus (COVID-19), during early December 2019 in Wuhan, China, has rapidly evolved into a global pandemic, became a matter of grave concern. The pandemic presented a unique challenge to government agencies worldwide. The paucity of resources and lack of knowledges to manage the pandemic, coupled with the fear of future consequences has established the need for adoption of emerging and future technologies to address the upcoming challenges. With introduction of measures to control the pandemic, trainees will see a dramatic decline in their in-person exposure to all aspects of their education, with no clear endpoint. This presents an extreme challenge for educators and, given the rapidly evolving situation, there have not yet been training authorities recommendations. We propose several innovative solutions to deliver medical education while maintaining the safety of residents and educators.

The ELIAS framework: A prescription for innovation and change

Healthcare is a complex adaptive system with multiple stakeholders and dynamic environments. Therefore, healthcare organizations must continuously learn, innovate, adapt, and co-evolve to be successful. This article describes a systematic, comprehensive, and holistic performance management framework that healthcare managers can use to achieve these goals. The framework involves the ongoing assessment, modification, or replacement of current programs or services aimed at adapting successfully to achieve the organization's strategic objectives. This is engendered by the presence of a culture that is premised on continuous learning and innovation. The foundation of the framework is based on accountability, the organization's strategy, and its culture. This then acts as the basis for an ongoing process of measurement, disconfirmation, contextualization, implementation, and routinization that enhances learning, innovation, adaptation, and sustainability within the healthcare organization.

Artificial intelligence (AI) and big data in cancer and precision oncology

Artificial intelligence (AI) and machine learning have significantly influenced many facets of the healthcare sector. Advancement in technology has paved the way for analysis of big datasets in a cost- and time-effective manner. Clinical oncology and research are reaping the benefits of AI. The burden of cancer is a global phenomenon. Efforts to reduce mortality rates requires early diagnosis for effective therapeutic interventions. However, metastatic and recurrent cancers evolve and acquire drug resistance. It is imperative to detect novel biomarkers that induce drug resistance and identify therapeutic targets to enhance treatment regimes. The introduction of the next generation sequencing (NGS) platforms address these demands, has revolutionised the future of precision oncology. NGS offers several clinical applications that are important for risk predictor, early detection of disease, diagnosis by sequencing and medical imaging, accurate prognosis, biomarker identification and identification of therapeutic targets for novel drug discovery. NGS generates large datasets that demand specialised bioinformatics resources to analyse the data that is relevant and clinically significant. Through these applications of AI, cancer diagnostics and prognostic prediction are enhanced with NGS and medical imaging that delivers high resolution images. Regardless of the improvements in technology, AI has some challenges and limitations, and the clinical application of NGS remains to be validated. By continuing to enhance the progression of innovation and technology, the future of AI and precision oncology show great promise.

‘Sorry doctor….I didn’t hear that….’: phenomenological analysis of medical students’ experiences of simulated hearing impairment through virtual reality

Introduction

Hearing impairment is a common condition that can have a significant impact on an individual. Ineffective communication between such individuals and doctors remains an important barrier. There is a need to provide medical students with a deeper understanding of such challenges. Increasingly, simulation is being used to develop empathy skills. In this study, we aimed to seek a deep understanding of medical students’ experiences of being placed in the role of a hearing-impaired patient by means of a virtual reality (VR) simulation.

Methods

A multidisciplinary group developed a 360° VR video-learning experience. This experience portrayed a consultation with a doctor from a hearing-impaired individual’s perspective. A qualitative study approach, using hermeneutic phenomenology, was conducted. Following the VR experience, students were interviewed, and transcripts of interviews were analysed using a Template Analysis approach.

Results

Analysis yielded four main themes: (1) ‘much more than just watching a video’: a VR experience of hearing impairment; (2) ‘hearing through their ears’: experiencing a person’s world with hearing impairment; (3) ‘not just what you can’t hear…but how it makes you feel’: reactions evoked by a VR hearing impairment experience and (4) redirecting my future professional self?

Discussion

This study provides an insight into medical students’ experiences of a novel VR hearing impairment simulation. VR simulation has the potential to provide a novel complementary training method for medical students. By providing an immersive learning experience, VR can offer an empathic stepping into the ears of those that live with hearing impairment.

Artificial intelligence for diabetic retinopathy screening, prediction and management

PURPOSE OF REVIEW

Diabetic retinopathy is the most common specific complication of diabetes mellitus. Traditional care for patients with diabetes and diabetic retinopathy is fragmented, uncoordinated and delivered in a piecemeal nature, often in the most expensive and high-resource tertiary settings. Transformative new models incorporating digital technology are needed to address these gaps in clinical care.

RECENT FINDINGS

Artificial intelligence and telehealth may improve access, financial sustainability and coverage of diabetic retinopathy screening programs. They enable risk stratifying patients based on individual risk of vision-threatening diabetic retinopathy including diabetic macular edema (DME), and predicting which patients with DME best respond to antivascular endothelial growth factor therapy.

SUMMARY

Progress in artificial intelligence and tele-ophthalmology for diabetic retinopathy screening, including artificial intelligence applications in 'real-world settings' and cost-effectiveness studies are summarized. Furthermore, the initial research on the use of artificial intelligence models for diabetic retinopathy risk stratification and management of DME are outlined along with potential future directions. Finally, the need for artificial intelligence adoption within ophthalmology in response to coronavirus disease 2019 is discussed. Digital health solutions such as artificial intelligence and telehealth can facilitate the integration of community, primary and specialist eye care services, optimize the flow of patients within healthcare networks, and improve the efficiency of diabetic retinopathy management.

Application of Predictive Modelling to Improve the Discharge Process in Hospitals

Objective

To find out the factors influencing discharge process turnaround time (TAT) and to accurately predict the discharge process TAT.

Methods

The discharge process of cardiology department inpatients in a tertiary care hospital was mapped over a month. The likely factors influencing discharge TAT were tested for significance by ANOVA. Multiple linear regression (MLR) was used to predict the TAT. The sample was divided into testing and training sets for regression. A model was generated using the training set and compared with the testing set for accuracy.

RESULTS

After a process map was plotted, the significant factors influencing the TAT were identified to be the treating doctor, and pending evaluations on the day of discharge. The MLR model was developed with Python libraries based on the two factors identified. The model predicted the discharge TAT with a 69% R2 value and 32.4 minutes (standard error) on the testing set and a 77.3% R2 value and 26.7 minutes (standard error) on the overall sample.

Conclusion

This study was an initiation to find out factors influencing discharge TAT and how those factors can be used to predict discharge in the hospital of interest. The study was validated and predicted the TAT with 77% accuracy after the significant factors that affect the discharge process were identified.

Distance Education in Anesthesia Using Screen-Based Simulation - A Brief Integrative Review

Screen-based simulation (SBS) using digital technology has been demonstrated to improve the cognitive and psychomotor skills of anesthesia trainees. As a method of education and evaluation, this form of simulation offers multiple advantages related to cost, availability, simplicity, repeatability, and scorability. Online use of SBS with software employing standard cloud-based peer-to-peer platforms allows for instruction at a distance of important anesthesia-related critical thinking skills including crisis management. Despite the fact that there are no studies concerning the application of SBS in anesthesia distance education, this form of instruction has increased as a result of quarantine measures associated with the coronavirus-2 pandemic that have disrupted traditional in-person mannequin-based simulation, and its usage likely will continue through the post-pandemic era for multiple reasons. Several options exist for asynchronous and synchronous teaching of anesthesia skills at a distance with SBS, and there are useful techniques that can assist in achieving these educational goals with this process.

Exploiting mutual information for the imputation of static and dynamic mixed-type clinical data with an adaptive k-nearest neighbours approach

BACKGROUND

Clinical registers constitute an invaluable resource in the medical data-driven decision making context. Accurate machine learning and data mining approaches on these data can lead to faster diagnosis, definition of tailored interventions, and improved outcome prediction. A typical issue when implementing such approaches is the almost unavoidable presence of missing values in the collected data. In this work, we propose an imputation algorithm based on a mutual information-weighted k-nearest neighbours approach, able to handle the simultaneous presence of missing information in different types of variables. We developed and validated the method on a clinical register, constituted by the information collected over subsequent screening visits of a cohort of patients affected by amyotrophic lateral sclerosis.

METHODS

For each subject with missing data to be imputed, we create a feature vector constituted by the information collected over his/her first three months of visits. This vector is used as sample in a k-nearest neighbours procedure, in order to select, among the other patients, the ones with the most similar temporal evolution of the disease over time. An ad hoc similarity metric was implemented for the sample comparison, capable of handling the different nature of the data, the presence of multiple missing values and include the cross-information among features captured by the mutual information statistic.

RESULTS

We validated the proposed imputation method on an independent test set, comparing its performance with those of three state-of-the-art competitors, resulting in better performance. We further assessed the validity of our algorithm by comparing the performance of a survival classifier built on the data imputed with our method versus the one built on the data imputed with the best-performing competitor.

CONCLUSIONS

Imputation of missing data is a crucial -and often mandatory- step when working with real-world datasets. The algorithm proposed in this work could effectively impute an amyotrophic lateral sclerosis clinical dataset, by handling the temporal and the mixed-type nature of the data and by exploiting the cross-information among features. We also showed how the imputation quality can affect a machine learning task.

The Promise of Clinical Decision Support Systems Targetting Low-Resource Settings

Low-resource clinical settings are plagued by low physician-to-patient ratios and a shortage of high-quality medical expertise and infrastructure. Together, these phenomena lead to over-burdened healthcare systems that under-serve the needs of the community. Alleviating this burden can be undertaken by the introduction of clinical decision support systems (CDSSs); systems that support stakeholders (ranging from physicians to patients) within the clinical setting in their day-to-day activities. Such systems, which have proven to be effective in the developed world, remain to be under-explored in low-resource settings. This review attempts to summarize the research focused on clinical decision support systems that either target stakeholders within low-resource clinical settings or diseases commonly found in such environments. When categorizing our findings according to disease applications, we find that CDSSs are predominantly focused on dealing with bacterial infections and maternal care, do not leverage deep learning, and have not been evaluated prospectively. Together, these highlight the need for increased research in this domain in order to impact a diverse set of medical conditions and ultimately improve patient outcomes.

Faculty Development: How Do We Encourage Faculty to Become Better Teachers and Mentors?

PURPOSE OF REVIEW

A healthy mentor relationship is a mutually beneficial experience and a necessary part of the natural progression of a career in academic medicine. We sought to explore the advantages of and challenges to becoming a mentor in current academic urology.

RECENT FINDINGS

Mentorship can promote self-confidence in the ability to choose a career, drive academic productivity, and even inspire a career in academic medicine. It is necessary to help promote advancement in diverse socioeconomic groups within medical trainees. Strong mentors can serve as role models to the next generation of doctors. However, the ability to be an effective mentor is being challenged in today's world of academic medicine. By staying current with the issues surrounding mentorship, an individual can be fulfilled and successful in training and guiding doctors into the new era of medicine.

Biomedical Waste Management by Using Nanophotocatalysts: The Need for New Options

Biomedical waste management is getting significant consideration among treatment technologies, since insufficient management can cause danger to medicinal service specialists, patients, and their environmental conditions. The improvement of waste administration protocols, plans, and policies are surveyed, despite setting up training programs on legitimate waste administration for all healthcare service staff. Most biomedical waste substances do not degrade in the environment, and may also not be thoroughly removed through treatment processes. Therefore, the long-lasting persistence of biomedical waste can effectively have adverse impact on wildlife and human beings, as well. Hence, photocatalysis is gaining increasing attention for eradication of pollutants and for improving the safety and clearness of the environment due to its great potential as a green and eco-friendly process. In this regard, nanostructured photocatalysts, in contrast to their regular counterparts, exhibit significant attributes such as non-toxicity, low cost and higher absorption efficiency in a wider range of the solar spectrum, making them the best candidate to employ for photodegradation. Due to these unique properties of nanophotocatalysts for biomedical waste management, we aim to critically evaluate various aspects of these materials in the present review and highlight their importance in healthcare service settings.

Real-World Budget Impact of the Adoption of Insulin Glargine Biosimilars in Primary Care in England (2015-2018)

BACKGROUND

Lantus, the reference insulin glargine used for the treatment of diabetes, lost its patent protection in 2014, opening the market to biosimilar competitors.

OBJECTIVE

First, to analyze the adoption rates of insulin glargine biosimilars in primary care in England and estimate the savings realized and missed, since an insulin glargine biosimilar was first used, and second, to assess potential variations in adoption rates across Clinical Commissioning Groups (CCGs).

RESEARCH DESIGN AND METHODS

Data sets capturing information on all insulin glargine items prescribed by all general practitioners up to December 2018 were used. Total costs of insulin glargine and uptake rates of biosimilars were calculated. The real-world budget impact was estimated assuming the cost of reference insulin glargine for all items and comparing the total costs in this scenario with the total costs in the real world. The missed savings were estimated assuming the cost of biosimilars for all insulin glargine items. Choropleth maps were generated to assess potential variations in uptake across CCGs.

RESULTS

Insulin glargine biosimilars generated savings of £900,000 between October 2015 (time of first prescription) and December 2018. The missed savings amounted to £25.6 million in this period, indicating that only 3.42% of the potential savings were achieved. The analyses demonstrated a large level of variation in the uptake of insulin glargine biosimilars across CCGs, with market shares ranging from 0 to 53.3% (December 2018).

CONCLUSIONS

These results may encourage decision makers in England to promote the use of best-value treatments in primary care and to reevaluate variation across CCGs.

Impact of Clinical Process Improvement Training in an Integrated Delivery System

Multiple integrated health systems use frontline staff training in quality and process improvement, although the optimal method to determine training success remains unknown. The authors assessed the Partners Clinical Process Improvement Leadership Program's short-term impact by evaluating data in project presentations during 14 courses between 2010 and 2016. Long-term impact was assessed via a graduate survey. Among 262 interprofessional teams, 180 (69%) achieved short-term improvement, including 78 (30%) achieving and 102 (39%) demonstrating improvement toward their project goal. Projects implementing ≥2 interventions were more likely to succeed. Of 231 graduates surveyed, 79% reported the ability to lead and 67% reported actual work on additional quality improvement projects. Ninety-seven percent of alumni reported a positive career impact. Hospital leadership support of clinical process improvement training meets short-term improvement needs and promotes long-term capacity for learning health systems.

Clinical Information Systems - Seen through the Ethics Lens

OBJECTIVE

The more people there are who use clinical information systems (CIS) beyond their traditional intramural confines, the more promising the benefits are, and the more daunting the risks will be. This review thus explores the areas of ethical debates prompted by CIS conceptualized as smart systems reaching out to patients and citizens. Furthermore, it investigates the ethical competencies and education needed to use these systems appropriately.

METHODS

A literature review covering ethics topics in combination with clinical and health information systems, clinical decision support, health information exchange, and various mobile devices and media was performed searching the MEDLINE database for articles from 2016 to 2019 with a focus on 2018 and 2019. A second search combined these keywords with education.

RESULTS

By far, most of the discourses were dominated by privacy, confidentiality, and informed consent issues. Intertwined with confidentiality and clear boundaries, the provider-patient relationship has gained much attention. The opacity of algorithms and the lack of explicability of the results pose a further challenge. The necessity of sociotechnical ethics education was underpinned in many studies including advocating education for providers and patients alike. However, only a few publications expanded on ethical competencies. In the publications found, empirical research designs were employed to capture the stakeholders' attitudes, but not to evaluate specific implementations.

CONCLUSION

Despite the broad discourses, ethical values have not yet found their firm place in empirically rigorous health technology evaluation studies. Similarly, sociotechnical ethics competencies obviously need detailed specifications. These two gaps set the stage for further research at the junction of clinical information systems and ethics.

Pre-analytical and analytical variables that influence urinary volatile organic compound measurements

There has been rapidly accelerating interest in the utilization of volatile organic compounds (VOCs) as non-invasive methods for rapid point-of-care medical diagnostics. There is widespread variation in analytical methods and protocols, with little understanding of the effects of sample storage on VOC profiles. This study aimed to determine the effects on VOC profiles of different storage times, at room temperature, prior to freezing, of sealed urine samples from healthy individuals. Analysis using Field Asymmetric Ion Motility Spectrometry (FAIMS) determined the alterations in VOC and total ion count profiles as a result of increasing room temperature storage times. Results indicated that increasing exposure time to room temperature prior to freezing had a threefold effect. Firstly, increased urinary VOC profile variability, with a plateau phase between 12 and 48 hours, before further degradation. Secondly, an increase in total ion count with time exposed to room temperature. Finally, a deterioration in VOCs with each sample run during the analysis process. This provides new insight into the effect of storage of urine samples for VOC analysis using FAIMS technology. Results of this study provide a recommendation for a 12-hour maximum duration at room temperature prior to storage.

Patients' attitudes towards cost feedback to doctors to prevent unnecessary testing: a qualitative focus group study

OBJECTIVES

There is a need to improve efficiency in healthcare delivery without compromising quality of care. One approach is the development and evaluation of behavioural strategies to reduce unnecessary use of common tests. However, there is an absence of evidence on patient attitudes to the use of such approaches in the delivery of care. Our objective was to explore patient acceptability of a nudge-type intervention that aimed to modify blood test requests by hospital doctors.

STUDY DESIGN

Single-centre qualitative study.

METHODS

The financial costs of common blood tests were presented to hospital doctors on results reports for 1 year at a hospital. Focus group discussions were conducted with recent inpatients at the hospital using a semi-structured question schedule. Discussions were transcribed and analysed using qualitative content analysis to identify and prioritise common themes explaining attitudes to the intervention approach.

RESULTS

Three focus groups involving 17 participants were conducted. Patients were generally apprehensive about the provision of blood test cost feedback to doctors. Attitudes were organised around themes representing beliefs about blood tests, the impact on doctors and their autonomy, and beliefs about unnecessary testing. Patients thought that blood tests were important, powerful and inexpensive, and cost information could place doctors under additional pressure.

CONCLUSION

The findings identify predominantly positive beliefs about testing and negative attitudes to the use of financial costs in the decision-making of hospital doctors. Public discussion and education about the possible overuse of common tests may allow more resources to be allocated to evidence-based healthcare, by reducing the perception that such strategies to improve healthcare efficiency negatively impact on quality of care.

Keep calm and carry on learning: using Microsoft Teams to deliver a medical education programme during the COVID-19 pandemic

The outbreak of COVID-19 in the UK in March 2020 required a radical remodelling of the medical workforce at Royal Free London NHS Foundation Trust to prepare for the anticipated surge of hospital admissions. The provision of relevant teaching and training was immediately identified as a priority, particularly for staff due to work outside their regular medical specialty. Rather than deliver face-to-face teaching, doctors at the Trust utilised Microsoft Teams, an online communications and collaboration platform, to deliver a multi-disciplinary Trust-wide education programme responsive to the needs of surveyed medical staff. To date members of 18 departments across the Trust have delivered 51 virtual teaching sessions which have been viewed 3,814 times. During this pandemic the virtual education programme has facilitated rapid dissemination of new information and provided a platform for discussion and unity amongst colleagues with overwhelmingly positive feedback from both learners and teachers.

The Frontline Nurse's Experience of Nursing Outlier Patients

The frontline nurses' experience of nursing with overstretched resources in acute care setting can affect their health and well-being. Little is known about the experience of registered nurses faced with the care of a patient outside their area of expertise. The aim of this paper is to explore the phenomenon of nursing the outlier patient, when patients are nursed in a ward that is not specifically developed to deal with the major clinical diagnosis involved (e.g., renal patient in gynecology ward). Using a hermeneutic phenomenological approach, eleven individual face-to-face in-depth interviews were conducted with registered nurses in New South Wales, Australia. The study identified that each nurse had a specialty construct developed from nursing in a specialized environment. Each nurse had normalized the experience of specialty nursing and had developed a way of thinking and practicing theorized as a "care ladder". By grouping and analyzing various "care ladders" together, the nursing capacities common to nurses formed the phenomenological orientation, namely "the composite care ladder". Compared to nursing specialty-appropriate patients, nursing the outlier patient caused disruption of the care ladder, with some nurses becoming less capable as they were nursing the outlier patient. Nursing the outlier patient disrupted the nurses' normalized constructs of nursing. This study suggests that nursing patients in specialty-appropriate wards will improve patient outcomes and reduce impacts on the nurses' morale.

Reliability of Supervised Machine Learning Using Synthetic Data in Health Care: Model to Preserve Privacy for Data Sharing

BACKGROUND

The exploitation of synthetic data in health care is at an early stage. Synthetic data could unlock the potential within health care datasets that are too sensitive for release. Several synthetic data generators have been developed to date; however, studies evaluating their efficacy and generalizability are scarce.

OBJECTIVE

This work sets out to understand the difference in performance of supervised machine learning models trained on synthetic data compared with those trained on real data.

METHODS

A total of 19 open health datasets were selected for experimental work. Synthetic data were generated using three synthetic data generators that apply classification and regression trees, parametric, and Bayesian network approaches. Real and synthetic data were used (separately) to train five supervised machine learning models: stochastic gradient descent, decision tree, k-nearest neighbors, random forest, and support vector machine. Models were tested only on real data to determine whether a model developed by training on synthetic data can used to accurately classify new, real examples. The impact of statistical disclosure control on model performance was also assessed.

RESULTS

A total of 92% of models trained on synthetic data have lower accuracy than those trained on real data. Tree-based models trained on synthetic data have deviations in accuracy from models trained on real data of 0.177 (18%) to 0.193 (19%), while other models have lower deviations of 0.058 (6%) to 0.072 (7%). The winning classifier when trained and tested on real data versus models trained on synthetic data and tested on real data is the same in 26% (5/19) of cases for classification and regression tree and parametric synthetic data and in 21% (4/19) of cases for Bayesian network-generated synthetic data. Tree-based models perform best with real data and are the winning classifier in 95% (18/19) of cases. This is not the case for models trained on synthetic data. When tree-based models are not considered, the winning classifier for real and synthetic data is matched in 74% (14/19), 53% (10/19), and 68% (13/19) of cases for classification and regression tree, parametric, and Bayesian network synthetic data, respectively. Statistical disclosure control methods did not have a notable impact on data utility.

CONCLUSIONS

The results of this study are promising with small decreases in accuracy observed in models trained with synthetic data compared with models trained with real data, where both are tested on real data. Such deviations are expected and manageable. Tree-based classifiers have some sensitivity to synthetic data, and the underlying cause requires further investigation. This study highlights the potential of synthetic data and the need for further evaluation of their robustness. Synthetic data must ensure individual privacy and data utility are preserved in order to instill confidence in health care departments when using such data to inform policy decision-making.

Simulation of realistic nephrology case scenarios to facilitate intra-professional team learning

BACKGROUND

Learning in the workplace maximises relevance to clinical practice and facilitates the education of the whole multiprofessional team. Provision of structured teaching is becoming increasingly challenging with shift pattern working and staff shortages. This article describes a simulation course designed to facilitate team learning to improve the care of nephrology patients, and presents outcome data over 2 years.

METHODS

A full-day course, using high fidelity manikins, was designed for nephrology specialty trainees and nurse specialists. Nineteen learners (eleven specialty trainees and eight nurse specialists) and nine multidisciplinary team faculty members attended. Evaluation used pre- and post-course assessments, with a 1-year follow-up questionnaire.

RESULTS

Following the course, improved knowledge scores, 56% to 72% (P<0.05), and confidence scores, 57% to 71% (P<0.005), were demonstrated. Qualitative analysis found 'intra-disciplinary interaction', 'reflection' and 'practical skills' were the greatest enablers of learning. In the 1-year follow-up questionnaire, specialty trainees reported that the course improved clinical practice and helped preparation for consultant roles.

CONCLUSIONS

This course improved knowledge and confidence in managing nephrology scenarios across the multidisciplinary learning group, and the model could be used in other hospital specialties.

Speaking up in the perioperative setting

Patient safety is a key role for all staff who work in the perioperative environment. Being able to raise concerns and have these concerns listened to is a big part of maintaining patient safety. Freedom to Speak Up Guardians were introduced to assist health care workers in raising concerns; however, their access to perioperative areas may be restricted. This article therefore looks to explain the role of Freedom to Speak Up Guardians and how this new role impacts on how concerns should be raised.

Applying an immersive tutorial in virtual reality to learning a new technique

OBJECTIVE

The medical world is continuously evolving, with techniques being created or improved almost daily. Immersive virtual reality (VR) is a technology that could be harnessed to develop tools that meet the educational challenges of this changing environment. We previously described the immersive tutorial, a 3D video (filmed from the first-person point of view), displayed on a VR application. This tool offers access to supplementary educational data in addition to the video. Here we attempt to assess improvement in learning a technique using this new educational format.

MATERIAL AND METHODS

We selected a single neurosurgical technique for the study: external ventricular drainage. We wrote a technical note describing this procedure and produced the corresponding immersive tutorial. We conducted a prospective randomized comparative study with students. All participants read the technical note, and one group used the immersive tutorial as a teaching supplement. The students completed a multiple-choice questionnaire immediately after the training and again at six months.

RESULTS

One hundred seventy-six fourth-year medical students participated in the study; 173 were included in assessing the immediate learning outcomes and 72 were included at the six-month follow-up. The VR group demonstrated significantly better short-term results than the control group (P=0.01). The same trend was seen at six months.

CONCLUSION

To our knowledge, this study presents one of the largest cohorts for VR. The use of the immersive tutorial could enable a large number of healthcare professionals to be trained without the need for expensive equipment.

Older patients undergoing emergency laparotomy: observations from the National Emergency Laparotomy Audit (NELA) years 1-4

BACKGROUND

older patients aged ≥65 years constitute the majority of the National Emergency Laparotomy Audit (NELA) population. To better understand this group and inform future service changes, this paper aims to describe patient characteristics, outcomes and process measures across age cohorts and temporally in the 4-year period (2014-2017) since NELA was established.

METHODS

patient-level data were populated from the NELA data set years 1-4 and linked with Office of National Statistics mortality data. Descriptive data were compared between groups delineated by age, NELA year and geriatrician review. Primary outcomes were 30- and 90-day mortality, length of stay (LOS) and discharge to care-home accommodation.

RESULTS

in total, 93,415 NELA patients were included in the analysis. The median age was 67 years. Patients aged ≥65 years had higher 30-day (15.3 versus 4.9%, P < 0.001) and 90-day mortality (20.4 versus 7.2%, P < 0.001) rates, longer LOS (median 15.2 versus 11.3 days, P < 0.001) and greater likelihood of discharge to care-home accommodation compared with younger patients (6.7 versus 1.9%, P < 0.001). Mortality rate reduction over time was greater in older compared with younger patients. The proportion of older NELA patients seen by a geriatrician post-operatively increased over years 1-4 (8.5 to 16.5%, P < 0.001). Post-operative geriatrician review was associated with reduced mortality (30-day odds ratio [OR] 0.38, confidence interval [CI] 0.35-0.42, P < 0.001; 90-day OR 0.6, CI 0.56-0.65, P < 0.001).

CONCLUSIONS

older NELA patients have poorer post-operative outcomes. The greatest reduction in mortality rates over time were observed in the oldest cohorts. This may be due to several interventions including increased perioperative geriatrician input.

COVID-19 impact and virtual medical education

The Corona-Virus Disease 2019 (COVID-19) Pandemic has had a tremendous effect on medical education. It is also challenging the medical educationists' ability to adapt to this whole unique situation. Considering the hospital-based education, clinical mentors, and students in all health professions are potential carriers. However, the current crisis is revitalizing the necessity for online learning opportunities and virtual education. Most medical schools are following reacting to lockdown with a shift to live online or video-based learning. Maintaining standard in medical education, keeping the clinical learning on stream, and minimizing the assessment disruption are unprecedented challenges under pandemic conditions. Adaptation to this new situation is necessary to prepare future clinicians for practice. This commentary discusses how this pandemic may affect medical education. In this commentary, the author highlights the importance of virtual education and the potential implications of integrating virtual simulation technologies into medical education for the future of clinical competency learning and assessment.

Use of a digital delirium pathway and quality improvement to improve delirium detection in the emergency department and outcomes in an acute hospital

BACKGROUND

delirium is a common condition associated with hospital admission. Detection and diagnosis is important to identify the underlying precipitating cause and implement effective management and treatment. Quality improvement (QI) methodology has been applied in limited publications. There are even fewer publications of the role of development of the electronic health record (EHR) to enhance implementation.

METHODS

we used QI methodology to improve delirium detection in the emergency department (ED). Plan Do Study Act (PDSA) cycles could be broadly categorised into technology, training and education and leadership. As part of the technology PDSA an electronic delirium pathway was developed as part of an NHS England digital systems improvement initiative (NHS England Global Digital Exemplar). The electronic pathway incorporated the 4AT screening tool, the Confusion Assessment Method, the TIME delirium management bundle, investigation order sets and automated coding of delirium as a health issue.

RESULTS

development of the EHR combined with education initiatives had benefit in terms of the number of people assessed for delirium on admission to the ED and the total number of people diagnosed with delirium across the organisation. The implementation of a delirium pathway as part of the EHR improved the use of 4AT in those 65 years and over from baseline of 3% completion in October 2017 to 43% in January 2018.

CONCLUSION

we showed that enhancement of the digital record can improve delirium assessment and diagnosis. Furthermore, the implementation of a delirium pathway is enhanced by staff education.

Value-based healthcare in mental health services

In value-based healthcare (VBHC) value is defined as outcomes that matter to patients divided by the cost of achieving these outcomes. Value is measured for discrete medical conditions across the whole cycle of care. Data on the value achieved by different providers is openly shared. Providers increase value using quality improvement (QI) techniques to improve outcomes, reduce costs or both. Patients or commissioners choose the provider achieving the greatest value. Units should compete regionally or nationally. There are challenges to implementing such ideas in the mental health services in the UK. However, measuring outcomes, understanding costs and using QI to drive up value may be possible without adopting the complete model that has developed in the context of a North American and acute hospital healthcare system.

Use of Semiprivate Smartphone Communication Applications in Nephrology Education

Advances in information technology have changed human interactions. These changes have had considerable implications for nonmedical and medical educational practices. The use of semi-private applications such as WhatsApp (Mountain View, CA), Slack (Canada), Viber (Israel), and Google Hangouts (Mountain View, CA) has not been well studied in nephrology education. In this narrative review, we review the literature on the use of these communication applications in medicine and nephrology education. Although many of these applications might be used currently in nephrology, there is little published data regarding the use of WhatsApp in nephrology fellowship. Given the easy accessibility of these communication applications by our learners in medical school, residency, and fellowship, the use of such applications can enhance nephrology education.

Artificial Intelligence and Human Trust in Healthcare: Focus on Clinicians

Artificial intelligence (AI) can transform health care practices with its increasing ability to translate the uncertainty and complexity in data into actionable-though imperfect-clinical decisions or suggestions. In the evolving relationship between humans and AI, trust is the one mechanism that shapes clinicians' use and adoption of AI. Trust is a psychological mechanism to deal with the uncertainty between what is known and unknown. Several research studies have highlighted the need for improving AI-based systems and enhancing their capabilities to help clinicians. However, assessing the magnitude and impact of human trust on AI technology demands substantial attention. Will a clinician trust an AI-based system? What are the factors that influence human trust in AI? Can trust in AI be optimized to improve decision-making processes? In this paper, we focus on clinicians as the primary users of AI systems in health care and present factors shaping trust between clinicians and AI. We highlight critical challenges related to trust that should be considered during the development of any AI system for clinical use.

Integrating sustainability into postgraduate medical education

The delivery of healthcare is a major contributor to the climate crisis, with the NHS being the largest public sector contributor of carbon emissions in the UK. Physicians have an important role to play in the fight against climate change through the practice of sustainable healthcare. This involves maintaining the current and future quality of healthcare through balancing environmental, social and financial constraints. To this end, integrating these skills into medical education is crucial. A large number of medical schools have already embedded planetary health and sustainability theory into their curriculum, however, there is no formal sustainability curriculum in postgraduate education and training. This is vital for enabling clinicians to translate sustainability theory taught at undergraduate level into clinical practice. This article proposes which topics should be included in a postgraduate sustainability curriculum and explores various methods that could be used to incorporate these into the current educational framework.

The contributions of NHS healthcare workers who are shielding or working from home during COVID-19

During the COVID-19 pandemic, many healthcare staff and others who work for the NHS have been working from home (WFH) or shielding due to various health conditions, including pregnancy. While emphasis has been given to the support and wellbeing of those working at the frontline, little is known about the contribution of those who are working remotely. This online survey attempts to throw some light on how these healthcare workers have been contributing to the NHS while WFH, the resources they may or may not have to undertake their remote duties, their perception of whether their contribution is valued at the workplace, and their views on whether the new ways of working would influence the manner in which they would work in the future.

Evaluation of training programmes mapped to the new internal medicine curriculum

In preparation for the internal medicine training (IMT) programme introduced in 2019, the core medical training (CMT) programme in London was made 'IMT-ready' in 2018 by creating new rotations that reflected the compulsory requirements of the first 2 years of the IMT curriculum, including provision of the requisite number of critical care placements. Core medical trainees completed posts within the 'IMT-ready' programme between August 2018 and August 2019, during which time the trainee experience was evaluated. A total of 497 responses were received. Of these, 96% of trainees were on an 'acute unselected take' on-call rota, 79% were able to attend outpatient clinics, 80% had the opportunity to practise procedural skills and 88% had the opportunity to apply palliative care skills. Clear areas for improvement were identified that predominantly focused on the need to optimise trainee attendance of outpatient clinics and the number of patients seen during an acute take. With respect to future career intentions, only 63% of trainees planned on applying to a group 1 (with general medicine) higher medical specialty. Thematic analysis of trainees in critical care placements highlighted an appreciation of the level of senior support, feeling well integrated into the team, a positive experience of induction and excellent opportunities for performing procedures.

The effectiveness of behavioral economics-informed interventions on physician behavioral change: A systematic literature review

OBJECTIVE

Interventions informed by behavioral economics have the potential to change behaviors governed by underlying cognitive biases. This has been explored extensively for various use in healthcare including changing patient behavior and, more recently, physician behavior. We aimed to systematically review the literature on the use and effectiveness of behavioral economics-informed interventions in changing physician behavior.

METHOD

We searched Medline, Cochrane Library, EBM Reviews, PsychINFO, EconLit, Business Source Complete and Web of Science for peer-reviewed studies published in English that examined the effectiveness of behavioral economics-informed interventions on physician behavioral change. We included studies of physicians in all care settings and specialties and all types of objectively measured behavioral outcomes. The reporting quality of included studies was appraised using the Effective Public Health Practice Project tool.

RESULTS

We screened 6,439 studies and included 17 studies that met our criteria, involving at least 9,834 physicians. The majority of studies were conducted in the United States, published between 2014 and 2018, and were in the patient safety and quality domain. Reporting quality of included studies included strong (n = 7), moderate (n = 6) and weak (n = 4). Changing default settings and providing social reference points were the most widely studied interventions, with these studies consistently demonstrating their effectiveness in changing physician behavior despite differences in implementation methods among studies. Prescribing behavior was most frequently targeted in included studies, with consistent effectiveness of studied interventions.

CONCLUSION

Changing default settings and providing social reference points were the most frequently studied and consistently effective interventions in changing physician behavior towards guideline-concordant practices. Additional theory-informed research is needed to better understand the mechanisms underlying the effectiveness of these interventions to guide implementation.