Improving care processes in healthcare institutions relies on effectively monitoring and making timely decisions for improving patient experience. Business Intelligence solutions have proven to be effective for monitoring processes in other industries. However, healthcare organizations face three challenges for implementing Business Intelligence solutions that effectively monitor care processes. First, the great variation of processes in healthcare domain makes it difficult to model them. Second, there is a gap between abstract administrative indicators and fine-grained operation-level measures of healthcare processes. Finally, it is difficult to reuse the underlying healthcare processes used for other successful solutions. In this paper, we present a Care Process Metamodel geared towards modeling healthcare processes. This metamodel (a) provides a platform for creating uniform care processes, (b) enables hierarchical care processes for modeling of composite processes as well as bridging the gap between abstract performance indicators and operation-level measures of healthcare processes, and (c) facilitates reusing the processes and the data structures required for monitoring them. This metamodel thus addresses some of the challenges for implementing successful Business Intelligence care process monitoring solutions for healthcare organizations. We also demonstrate how the Care Process Metamodel-based processes fit into an architecture, where data collected about encounters of patients can be used by stakeholders for improving the process and its execution. We use samples of cardiac-related processes to illustrate our approach.
Medical device requirements often depend on the healthcare processes in which the device is to be used. Since such processes may be complex, critical requirements may be specified inaccurately, or even missed altogether. We are investigating an automated requirement derivation approach that takes as input a model of the healthcare process along with a model of the device and tries to derive the requirements for that device. Our initial experience with this approach has shown that when the process and device involve complex behaviors, the derived requirements are also often complex and difficult to understand. In this paper, we describe an approach for creating a modal abstraction view of the derived requirements that decomposes each requirement based on its modes, and thus appears to improve understandability.
The dynamic nature of the medical domain is driving a need for continuous innovation and improvement in techniques for developing and assuring medical devices. Un-fortunately, research in academia and communication between academics, industrial engineers, and regulatory authorities is hampered by the lack of realistic non-proprietary development artifacts for medical devices. In this paper, we give an overview of a detailed requirements document for a Patient-Controlled Analgesic (PCA) pump developed under the US NSF's Food and Drug Administration (FDA) Scholar-in-Residence (SIR) program. This 60+ page document follows the methodology outlined in the US Federal Aviation Administrations (FAA) Requirements Engineering Management Handbook (REMH) and includes a domain overview, use cases, statements of safety & security requirements, and formal top-level system architectural description. Based on previous experience with release of a requirements document for a cardiac pacemaker that spawned a number of research and pedagogical activities, we believe that the described PCA requirements document can be an important research enabler within the formal methods and software engineering communities.
This paper proposes using resource-aware, discrete-event simulation to measure the effects of resource scheduling in hospital emergency departments. Determining staffing and resource allocation is a complex constraint-optimization problem that has significant impact on hospital costs and patient care quality. We developed detailed models of the emergency department process of caring for patients, the resources available to support that process, and the scheduling constraints on the deployment of those resources. We then ran a battery of discrete-event simulations of this process, varying details of process, resource mixes, and scheduling constraints, to analyze the effects of resource availability (e.g., staffing patterns) on patient length of stay. Our simulation approach proved to be particularly adept at supporting the systematic investigation of two issues of particular interest to domain experts: (1) an excessive focus on minimizing the average length of stay (the objective most typically used for optimizing emergency department staffing) can have undesirable, previously unappreciated effects, (2) too strong a focus on one particular kind of resource as the preferred vehicle for decreasing patient length of stay can tend to obscure the value of considering other kinds of resources. The unexpected nature of some of our results raises open questions about how to validate the results of complex simulations.
Information models used in the healthcare domain tend to be complex, in part because they were designed to be as flexible and generic as possible. This complexity presents a steep learning curve for implementers, which can lead to partial or poorly-implemented solutions. In this paper, we present a tool that facilitates the creation of sets of modular and composable clinical data abstractions. Using these, implementers can produce and consume standards-compliant clinical data correctly and efficiently without being experts in the underlying information models or the medical terminologies they reference.
Over the last several years, software engineering (SE) has given birth to several communities and venues related to research on SE in the context of health care systems. By and large, the interest in this topic has been spurred by alarming failures of software-intensive systems that have been deployed to address some of the challenges faced in current health care environments. Today, the software engineering in health care (SEHC) community faces several challenges. It needs to justify the significance of its existence towards the general SE community and towards the medical/health informatics community. The purpose of this paper is to explore some of the fundamental challenges pertaining to SEHC, to consider whether these challenges require a dedicated community-based effort and to generate recommendations on how to strengthen its impact. We argue that the community should adopt a conceptual model of knowledge translation (KT) analogous those used in the medical domain to position its research and maximize its impact.
Through the use of semi structured interviews with medical device software organizations it emerged that medical device software organizations are experiencing difficulties when following plan driven Software Development Life Cycles (SDLC), particularly in the area of requirements management. To attempt to resolve these issues an examination of the non-regulated industry was performed to determine if lessons learned there could be applied to the development of medical device software. This examination revealed that agile methods are being widely adopted in the non-regulated software industry. To learn if agile methods could be adopted when developing medical device software a mapping study was performed which looked for instances of where agile methods have been used in regulated industries and where they have been adopted, to what success. This mapping study revealed that incorporating agile practices with the existing plan driven SDLC is the most favourable choice for medical device software organizations. This research aims to develop a SDLC which has a foundation of a plan driven SDLC which incorporates agile practices which can be followed when developing regulatory compliant software.
Medical errors are a major cause of unnecessary suffering and even death. To address this problem, we are investigating an approach for automatically detecting when an executing process deviates from a set of recommended ways to perform that process. Such deviations could represent errors and, thus, detecting and reporting deviations as they occur could help catch errors before something bad happens. This paper presents the proposed deviation detection approach, identifies some of the major research issues that arise, and discusses strategies to address these issues. A preliminary evaluation is performed by applying the approach to a part of a detailed process model. This model has been developed in an in-depth case study on modeling and analyzing a blood transfusion process.
In this work, it is shown that by incorporating smartphone-based health/behavior interventions, people can be made in-charge of their own lifestyles and small but incremental changes can be achieved in their behavior which could lead to the prevention of obesity and other chronic diseases. However, it is also shown that the success of this idea depends on building context-aware personalized health intervention systems that take into consideration multiple factors that influence an individual's lifestyle to provide tailored intervention plans for different individuals based on their health behavior and surrounding context. Such context-aware tailored intervention plans are the only way these systems can achieve long-term behavior change required for effective prevention of obesity and its related diseases.
The need for high-quality models is increasingly recognized for driving and documenting complex medical processes such as cancer therapies. A medical environment for such processes has to deal with a great multiplicity of dimensions such as different pathologies, different hospital departments, different agents with different concerns and expertise, different resources with a wide spectrum of capabilities, and so forth. The variety of needs along those multiple dimensions calls for multiple, complementary and consistent facets of the composite process model, each addressing a specific dimension. Building multi-dimensional process models is in our experience hard and error-prone. The paper describes various operators for composing process model facets in a coherent way or, conversely, for decomposing process models into specific facets that abstract from details irrelevant to a specific dimension. These operators are grounded on the formal trace semantics provided by our process language and its supporting analysis toolset. The paper shows how these operators may help modeling, analyzing, documenting and enacting complex processes. Their use is illustrated on simplified examples taken from real cancer therapies.
Patient wait times and care service times are key performance measures for care processes in hospitals. Managing the quality of care delivered by these processes in real-time is challenging. A key challenge is to correlate source medical events to infer the care process states that define patient wait times and care service times. Commercially available complex event processing engines do not have built in support for the concept of care process state. This makes it unnecessarily complex to define and maintain rules for inferring states from source medical events in a care process. In this paper, we introduce a state monitoring engine for inferring and managing states based on an application model for care process monitoring. The research is validated with a case study developed in collaboration with a large community hospital.
Human beings make errors and that is nothing that we can avoid completely. We can however lower the risk of people doing wrong in situations where, for example, medical devices are used. The overall objective of the research presented in this paper is to investigate how usability testing can contribute to software risk management process in the medical device domain. Experience has been collected from both the risk management process and usability testing in a development project of a medical device. It can be concluded that usability tests can give valuable input to the risk management process. Usability tests can indicate risks that are not identified in the risk management process and render the possibility to verify if risks with high risk value actually cause the presumed problems.
The vision of PolicyForge.org is that it becomes an open repository for privacy policies at local, state and national level; provides collaboration services for discussing, interpreting, and tracking policies; and by embedding formal policy models with relevant ontologies, it provides a wide range of services for authoring, composing, analyzing policy models, and for exporting executable version of the models for Health Information Exchange platforms.
The philosophy and architecture of a novel mobile application to support maternal health are presented in this paper. A deployment study presents evidence on the benefits derived by the use of mobile devices for treatment adherence and compliance and care management. The application is intended for usage by rural caregivers for timely pregnancy related information management and to give relevant pregnancy and child care related advices. Automated advisory to help determine the risk condition of pregnancy and suggested treatment courses are handled by an expert system in the application. Much of the advisory rules run on the edge device right at the point of data collection and the dependency on network availability is negligible. The application also demands minimal medical expertise on the part of the caregivers, so early assistance can be provided even before a trained medical practitioner is made available to the patient.
In regulated domains such as finance and health care, failure to comply with regulation can lead to financial, civil and criminal penalties. While systems vary from organization to organization, regulations apply across organizations. We propose the use of Behavior-Driven-Development (BDD) scenarios as the basis of an automated compliance test suite for standards such as regulation and interoperability. Such test suites could become a shared asset for use by all systems subject to these regulations and standards. Each system, then, need only create their own system-specific test driver code to automate their compliance checks. The goal of this research is to enable organizations to compare their systems to regulation in a repeatable and traceable way through the use of BDD. To evaluate our proposal, we developed an abbreviated HIPAA test suite and applied it to three open-source electronic health record systems. The scenarios covered all security behavior defined by the selected regulation. The system-specific test driver code covered all security behavior defined in the scenarios, and identified where the tested system lacked such behavior.
The critical nature of safety in medical device software requires a repeatable and compliant software engineering process. This process should take into account the whole development life cycle, risk management, and software verification and validation activities that would commensurate with the device's complexity and risk. This paper discusses some of the key challenges medical device manufacturers are facing in the development and certification of medical device software. These challenges include: compliance with the EU and US regulatory requirements for medical device software, making software development and maintenance processes more agile in the medical device regulatory environment, integrating usability engineering process/human factors into software development, regulation of networked medical devices and mobile medical applications (apps). The MED-EL case study highlights some of the challenges described in this paper, and the approaches taken to overcome these challenges.
This paper reports on a study investigating the usability challenges faced by users of Magnetic Resonance Imaging (MRI) tools. In order to understand these problems, observation, shadowing and interviews were conducted with MRI scan users at two centers. After analyzing the collected data, low-fidelity prototypes were created and evaluated. We addressed the usability issues found by proposing a user-friendly and efficient high-fidelity prototype that replaces keyboard and mouse with two multi-touch screens.
This paper describes the ongoing development of ATTENTION, a new kind of clinical decision support system for synthesizing and managing longitudinal treatment plans, such as cancer treatment plans. ATTENTION combines stateof- the-art formal modeling and constraint solving with clinical information systems to synthesize complex cancer treatment plans that are also executable.
Introduction of IT in the health domain can potentially benefit the quality of the delivered healthcare, also contributing to increase safety. However health IT systems themselves can have safety implications and can result in accidents. Creating a safety case has been in practice in numerous domains and is starting to be adopted in the health IT domain with the most notable example, that of the UK National Health Service (NHS), Information Standards Board for Health and Social Care (ISB) standards (formerly DSCN 14/2009 & DSCN 18/2009). Safety cases can be thought of as a defensible, comprehensible and clear argument, supported by evidence that a system is acceptably safe in its operational context. This paper presents the main areas of safety case practice and its implication for the health IT development and stakeholders.
This paper argues that it is possible to develop useful generic representations of care pathways, drawing on evidence and argument about clinical teams, about the ability of teams to cope with radical uncertainty and about the influence of institutional arrangements on the journeys that patients take through health systems. The arguments are used to identify a mismatch between current practices in the design of large scale digital systems and the need for information about risks and outcomes.
