iManageMyHealth and iSupportMyPatients: mobile decision support and health management apps for cancer patients and their doctors

Clinical decision support systems can play a crucial role in healthcare delivery as they promise to improve health outcomes and patient safety, reduce medical errors and costs and contribute to patient satisfaction. Used in an optimal way, they increase the quality of healthcare by proposing the right information and intervention to the right person at the right time in the healthcare delivery process. This paper reports on a specific approach to integrated clinical decision support and patient guidance in the cancer domain as proposed by the H2020 iManageCancer project. This project aims at facilitating efficient self-management and management of cancer according to the latest available clinical knowledge and the local healthcare delivery model, supporting patients and their healthcare providers in making informed decisions on treatment choices and in managing the side effects of their therapy. The iManageCancer platform is a comprehensive platform of interconnected mobile tools to empower cancer patients and to support them in the management of their disease in collaboration with their doctors. The backbone of the iManageCancer platform comprises a personal health record and the central decision support unit (CDSU). The latter offers dedicated services to the end users in combination with the apps iManageMyHealth and iSupportMyPatients. The CDSU itself is composed of the so-called Care Flow Engine (CFE) and the model repository framework (MRF). The CFE executes personalised and workflow oriented formal disease management diagrams (Care Flows). In decision points of such a Care Flow, rules that operate on actual health information of the patient decide on the treatment path that the system follows. Alternatively, the system can also invoke a predictive model of the MRF to proceed with the best treatment path in the diagram. Care Flow diagrams are designed by clinical experts with a specific graphical tool that also deploys these diagrams as executable workflows in the CFE following the Business Process Model and Notation (BPMN) standard. They are exposed as services that patients or their doctors can use in their apps in order to manage certain aspects of the cancer disease like pain, fatigue or the monitoring of chemotherapies at home. The mHealth platform for cancer patients is currently being assessed in clinical pilots in Italy and Germany and in several end-user workshops

Patient involvement in selection of immunosuppressive regimen following transplantation.

Transplantation has made a considerable difference to the lives of many patients. However, feedback from patients indicates that although having a transplant is a hugely positive experience, having to take medications indefinitely is one of the biggest challenges. An ideal scenario would be no medications following a transplant. A compromise would be a minimal number of medications, with minimal restrictions and as simple a regimen as possible. Although there is considerable research going into fine-tuning the management of the immune response to a transplant, to date there is no universal regimen that enables patients to remain free of immunosuppressant medications, making adherence paramount to maintain long-term allograft survival. This paper reviews the available immunosuppressant regimens and factors influencing choice from both the clinician's and the patient's perspective. Factors influencing the decision-making process, such as quality of life for patients, their satisfaction, acceptability, and adherence uptake are reviewed. We conclude with a further assessment of patient choice as a factor in regimen selection, its impact on adherence, and its implications

Development and Validation of a Rule-based Time Series Complexity Scoring Technique to Support Design of Adaptive Forecasting DSS

Evidence from forecasting research gives reason to believe that understanding time series complexity can enable design of adaptive forecasting decision support systems (FDSSs) to positively support forecasting behaviors and accuracy of outcomes. Yet, such FDSS design capabilities have not been formally explored because there exists no systematic approach to identifying series complexity. This study describes the development and validation of a rule-based complexity scoring technique (CST) that generates a complexity score for time series using 12 rules that rely on 14 features of series. The rule-based schema was developed on 74 series and validated on 52 holdback series using well-accepted forecasting methods as benchmarks. A supporting experimental validation was conducted with 14 participants who generated 336 structured judgmental forecasts for sets of series classified as simple or complex by the CST. Benchmark comparisons validated the CST by confirming, as hypothesized, that forecasting accuracy was lower for series scored by the technique as complex when compared to the accuracy of those scored as simple. The study concludes with a comprehensive framework for design of FDSS that can integrate the CST to adaptively support forecasters under varied conditions of series complexity. The framework is founded on the concepts of restrictiveness and guidance and offers specific recommendations on how these elements can be built in FDSS to support complexity

Departures from cost-effectiveness recommendations: The impact of health system constraints on priority setting

The methods and application of cost-effectiveness analysis have reached an advanced stage of development. Many decision makers consider cost-effectiveness analysis to be a valid and feasible approach towards setting health priorities, and it has been extensively applied in evaluating interventions and developing evidence based clinical guidelines. However, the recommendations arising from cost-effectiveness analysis are often not implemented as intended. A fundamental reason for the failure to implement is that CEA assumes a single constraint, in the form of the budget constraint, whilst in reality decision-makers may be faced with numerous other constraints. The objective of this paper is to develop a typology of constraints that may act as barriers to implementation of cost-effectiveness recommendations. Six categories of constraints are considered: the design of the health system; costs of implementing change; system interactions between interventions; uncertainty in estimates of costs and benefits; weak governance; and political constraints. Where possible -and if applicable- for each class of constraint, the paper discusses ways in which these constraints can be taken into account by a decision maker wishing to pursue the principles of cost-effectiveness

Modelling drivers' car parking behaviour using data from a travel choice simulator

This paper reports on models developed from data collected using the PARKIT parking choice simulator. PARKIT provided an experimental environment in which drivers’ choice of car parks, and of the routes chosen to reach them, could be observed and the influence of different levels of parking-stock knowledge (derived from experience or from information provided via roadside message signs) monitored. Separate models were estimated for the drivers’ initial choice of car park and for their revision of that choice as their journey progresses and they learn about actual conditions. The importance of price, walking time and driving distance is confirmed but the addition of variables describing the drivers’ choices on previous days, their expectations and their immediately preceding route-choice, greatly improved the models’ explanatory power. It is noted that variables such as these are not generally considered because they are rarely available to the modeller. Different discrete choice model structures were found to be appropriate for different decisions. Route choice was represented as an exit-choice model (whereby each journey is treated as a sequence of decisions – one at each intersection encountered). The paper discusses the incorporation of these choice models into a network assignment model and concludes that much of the power of the choice models is lost if the network model is not able to support use of information about travellers’ socio-economic characteristics and knowledge of the network and about the detailed network topology

Smallpox and Bioterrorism: Why the Plan to Protect the Nation Is Stalled and What to Do

The Iraq war is over, no weapons of mass destruction (WMD) have yet been found, and the president's smallpox plan, though sound, is running out of steam. Instead of being well on the way to protecting the nation's civilian population by vaccinating up to 10 million health, emergency, and public safety workers, we are stalled at 37,971 vaccinated civilians while the military has successfully and safely vaccinated more than 450,000 people. Moreover, whether or not WMD are found in Iraq, it is only one of a number of nations on the list of suspects. Of all biological weapons, smallpox has the greatest potential for doing widespread harm. Given that the risk of death or serious harm to anyone from any form of terrorism is very low, we should live our daily lives normally, not in fear. However, to do that we need to be sure that our government is taking effective steps to reduce the chances of terrorism and, when it occurs, to minimize its consequences. Even though there is enough vaccine for everyone, we are ill prepared to rapidly contain smallpox after a bioterrorist release. Although Centers for Disease Control and Prevention (CDC) guidelines have recently improved, they continue to overstate the risk of side effects of the vaccine and erroneously suggest that, after an attack, the techniques used decades ago to eradicate smallpox will work well today. Medicine and public health are very risk-averse professions in our risk-averse culture. We have not yet realized the complexity and difficulty of vaccinating millions of Americans rapidly after an attack. Nor have we come to grips with the need to make rapid, possibly draconian, post-attack decisions based on limited data of uncertain quality. That type of decisionmaking runs counter to the culture of public health. The Bush administration needs to revitalize our preparations for a smallpox bioterrorist event

Scoping study of the feasibility of developing a software tool to assist designers of pedestrian crossing places

This report is the outcome of a scoping study of how guidance can be provided for practising highway engineers in designing informal pedestrian crossing facilities. The main component of this report is an analysis by an IT consultant of a range of mechanisms for delivery of this. The study was informed by the opinions of a group of practitioners who have a direct interest in the provision of pedestrian facilities. These results are placed in context and their consequences are explored in the first part of the report

Pharmacogenomic testing and its future in community pharmacy

Although it is common to see pharmacogenomic testing used North America and Australia, it is not yet part of practice in the UK. With the promise of genomic screening becoming part of the NHS, pharmacists must equip themselves with a knowledge of how the process works. Source: Shutterstock.com In January 2019, the UK government unveiled its ten-year plan for NHS England and emphasised the role pharmacists can play in promoting patient self-care[1]. There was also a focus on delivering value from medicines and reducing avoidable medicines related-harm, which costs the NHS a minimum of £98.5m per year[2]. This coincides with the NHS Genomic Medicine Service, which will be rolled out across England from April 2020, meaning that the routine use of genomic screening and personalised treatments will be the new normal in the NHS[3],[4]. Pharmacists’ advice currently relies on knowledge of observable patient characteristics, such as age, weight, comorbidities and concurrent medicines, while largely disregarding genetics. However, it is estimated that genetic factors could contribute to between 25–50% of inappropriate drug responses[5]. Knowing exactly which medicine to use for a patient and which to avoid can be a challenging task in clinical practice. However, pharmacogenomics can provide the prescriber with additional information on some of the unobserved patient characteristics that affect drug response — this can assist with both drug selection and safety. Therefore, the combination of this pharmacogenomic information along with other factors influencing pharmaceutical care may provide an opportunity to deliver more ‘personalised’ medicine, facilitating better selection and reducing the need for ‘trial and error’ prescribing

Model Predictive Control Based Trajectory Generation for Autonomous Vehicles - An Architectural Approach

Research in the field of automated driving has created promising results in the last years. Some research groups have shown perception systems which are able to capture even complicated urban scenarios in great detail. Yet, what is often missing are general-purpose path- or trajectory planners which are not designed for a specific purpose. In this paper we look at path- and trajectory planning from an architectural point of view and show how model predictive frameworks can contribute to generalized path- and trajectory generation approaches for generating safe trajectories even in cases of system failures.Comment: Presented at IEEE Intelligent Vehicles Symposium 2017, Los Angeles, CA, US

The Internationalization of Agency Actions

U.S. agencies routinely base their domestic regulations on international considerations, such as the benefits of coordinating American and foreign standards or the foreign policy advantages of a particular policy. I refer to this phenomenon as the internationalization of agency actions. This Article examines what the internationalization of agency actions means for agency decision-making processes, institutional design, and legal doctrine. It creates a stylized model of how agencies determine whether to coordinate their standards with foreign regulations. Among other institutional design findings, it shows that court opinions that reduce the stringency of judicial review when agencies implement internationally coordinated standards make such coordination more likely to occur, but they simultaneously deprive the executive of bargaining power because U.S. agencies cannot credibly threaten that any coordinated agreement must align more closely with U.S. values or risk being overturned in U.S. courts. This Article also develops a taxonomy of international factors relied on by agencies and applies that taxonomy to help clarify the doctrinal issue of whether and when agencies can use international factors to justify their actions in court. This taxonomical approach shows how the Supreme Court’s opinion in Massachusetts v. EPA can reasonably be read to allow agencies to invoke a far broader range of foreign policy rationales than some prevailing views suggest