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This paper presents a study of online patient portal utilization through the analysis of system logs. We analyze click data generated between August 2009 and July 2011 by 1886 users of an online patient portal. We investigate variations in utilization for Login and the top five system features (Appointment Review, Lab Tests, Medical Advice Request, Messaging and Result Component Graphing), and examine how age and gender influence these variations. Our findings indicate that the effects of age and gender on system use vary by feature, and that efficiency of use (how clicks are spread across sessions) varies across age, gender and feature. We provide a new approach for understanding system use through click data analysis utilizing system logs (an underutilized data source available to all health-care organizations), an example of how big data can help health-care organizations learn more about their patients’ utilization of patient portals.

Lower extremity chronic wounds affect 4.5 million Americans annually. Due to inadequate access to wound experts in underserved areas, many patients receive non-uniform, non-standard wound care, resulting in increased costs and lower quality of life. We explored machine learning classifiers to generate actionable wound care decisions about four chronic wound types (diabetic foot, pressure, venous, and arterial ulcers). These decisions (target classes) were: (1) Continue current treatment, (2) Request non-urgent change in treatment from a wound specialist, (3) Refer patient to a wound specialist. We compare classification methods (single classifiers, bagged & boosted ensembles, and a deep learning network) to investigate (1) whether visual wound features are sufficient for generating a decision and (2) whether adding unstructured text from wound experts increases classifier accuracy. Using 205 wound images, the Gradient Boosted Machine (XGBoost) outperformed other methods when using both visual and textual wound features, achieving 81% accuracy. Using only visual features decreased the accuracy to 76%, achieved by a Support Vector Machine classifier. We conclude that machine learning classifiers can generate accurate wound care decisions on lower extremity chronic wounds, an important step toward objective, standardized wound care. Higher decision-making accuracy was achieved by leveraging clinical comments from wound experts.

Diabetes mellitus is a serious chronic disease that affects millions of people worldwide. In patients with diabetes, ulcers occur frequently and heal slowly. Grading and staging of diabetic ulcers is the first step of effective treatment and wound depth and granulation tissue amount are two important indicators of wound healing progress. However, wound depths and granulation tissue amount of different severities can visually appear quite similar, making accurate machine learning classification challenging. In this paper, we innovatively adopted the fine-grained classification idea for diabetic wound grading by using a Bilinear CNN (Bi-CNN) architecture to deal with highly similar images of five grades. Wound area extraction, sharpening, resizing and augmentation were used to pre-process images before being input to the Bi-CNN. Innovative modifications of the generic Bi-CNN network architecture are explored to improve its performance. Our research generated a valuable wound dataset. In collaboration with wound experts from University of Massachusetts Medical School, we collected a diabetic wound dataset of 1639 images and annotated them with wound depth and granulation tissue grades as labels for classification. Deep learning experiments were conducted using holdout validation on this diabetic wound dataset. Comparisons with widely used CNN classification architectures demonstrated that our Bi-CNN fine-grained classification approach outperformed prior work for the task of grading diabetic wounds.

BACKGROUND Mobile health (mHealth) apps that support individuals pursuing health and wellness goals, such as weight management, stress management, smoking cessation, and self-management of chronic conditions have been on the rise. Despite their potential benefits, the use of these tools has been limited, as most users stop using them just after a few times of use. Under this circumstance, achieving the positive outcomes of mHealth apps is less likely. OBJECTIVE The objective of this study was to understand continued use of mHealth apps and individuals’ decisions related to this behavior. METHODS We conducted a qualitative longitudinal study on continued use of mHealth apps. We collected data through 34 pre- and postuse interviews and 193 diaries from 17 participants over two weeks. RESULTS We identified 2 dimensions that help explain continued use decisions of users of mHealth apps: users’ assessment of mHealth app and its capabilities (user experience) and their persistence at their health goals (intent). We present the key factors that influence users’ assessment of an mHealth app (interface design, navigation, notifications, data collection methods and tools, goal management, depth of knowledge, system rules, actionable recommendations, and user system fit) and relate these factors to previous literature on behavior change technology design. Using these 2 dimensions, we developed a framework that illustrated 4 decisions users might make after initial interaction with mHealth apps (to abandon use, limit use, switch app, and continue use). We put forth propositions to be explored in future research on mHealth app use. CONCLUSIONS This study provides insight into the factors that shape users’ decisions to continue using mHealth apps, as well as other likely decision scenarios after the initial use experience. The findings contribute to extant knowledge of mHealth use and provide important implications for design of mHealth apps to increase long-term engagement of the users.

As traditional visual-examination-based methods provide neither reliable nor consistent wound assessment, several computer-based approaches for quantitative wound image analysis have been proposed in recent years. However, these methods require either some level of human interaction for proper image processing or that images be captured under controlled conditions. However, to become a practical tool of diabetic patients for wound management, the wound image algorithm needs to be able to correctly locate and detect the wound boundary of images acquired under less-constrained conditions, where the illumination and camera angle can vary within reasonable bounds. We present a wound boundary determination method that is robust to lighting and camera orientation perturbations by applying the associative hierarchical random field (AHRF) framework, which is an improved conditional random field (CRF) model originally applied to natural image multiscale analysis. To validate the robustness of the AHRF framework for wound boundary recognition tasks, we have tested the method on two image datasets: (1) foot and leg ulcer images (for the patients we have tracked for 2 years) that were captured under one of the two conditions, such that 70% of the entire dataset are captured with image capture box to ensure consistent lighting and range and the remaining 30% of the images are captured by a handheld camera under varied conditions of lighting, incident angle, and range and (2) moulage wound images that were captured under similarly varied conditions. Compared to other CRF-based machine learning strategies, our new method provides a determination accuracy with the best global performance rates (specificity: [Formula: see text] and sensitivity: [Formula: see text].

The potential of patient portals to improve patient engagement and health outcomes has been discussed for more than a decade. The slow growth in patient portal adoption rates among patients and providers in the United States, despite external incentives, indicates that this is a complex issue. We examined evidence of patient portal use and effects with a focus on the pulmonary domain. We found a paucity of studies of patient portal use in pulmonary practice, and highlight gaps for future research. We also report on the experience of a pulmonary department using a patient portal to highlight the potential of these systems.

Purpose – The needs of complex patients with chronic conditions can be unpredictable and can strain resources. Exploring how tasks vary for different patients, particularly those with complex needs, can yield insights about designing better processes in healthcare. The purpose of this paper is to explore the tasks required to manage complex patients in an anticoagulation therapy context. Design/methodology/approach – The authors analyzed interviews with 55 staff in six anticoagulation clinics using the Systems Engineering Initiative for Patient Safety (SEIPS) work system framework. The authors qualitatively described complex patients and their effects on care delivery. Findings – Data analysis highlighted how identifying complex patients and their effect on tasks and organization, and the interactions between them was important. Managing complex patients required similar tasks as non-complex patients, but with greater frequency or more intensity and several additional tasks. After complex patients and associated patient interaction and care tasks were identified, a work system perspective was applied to explore how such tasks are integrated within clinics and the resulting implications for resource allocation. Practical implications – The authors present a complex patient management framework to guide workflow design in specialty clinics, to better support high quality, effective, efficient and safe healthcare. Originality/value – The complex patient framework presented here, based on the SEIPS framework, suggests a more formal and integrated analysis be completed to provide better support for appropriate resource allocation and care coordination.

BACKGROUND Reviews of weight loss mobile apps have revealed they include very few evidence-based features, relying mostly on self-monitoring. Unfortunately, adherence to self-monitoring is often low, especially among patients with motivational challenges. One behavioral strategy that is leveraged in virtually every visit of behavioral weight loss interventions and is specifically used to deal with adherence and motivational issues is problem solving. Problem solving has been successfully implemented in depression mobile apps, but not yet in weight loss apps. OBJECTIVE This study describes the development and feasibility testing of the Habit app, which was designed to automate problem-solving therapy for weight loss. METHODS Two iterative single-arm pilot studies were conducted to evaluate the feasibility and acceptability of the Habit app. In each pilot study, adults who were overweight or obese were enrolled in an 8-week intervention that included the Habit app plus support via a private Facebook group. Feasibility outcomes included retention, app usage, usability, and acceptability. Changes in problem-solving skills and weight over 8 weeks are described, as well as app usage and weight change at 16 weeks. RESULTS Results from both pilots show acceptable use of the Habit app over 8 weeks with on average two to three uses per week, the recommended rate of use. Acceptability ratings were mixed such that 54% (13/24) and 73% (11/15) of participants found the diet solutions helpful and 71% (17/24) and 80% (12/15) found setting reminders for habits helpful in pilots 1 and 2, respectively. In both pilots, participants lost significant weight (P=.005 and P=.03, respectively). In neither pilot was an effect on problem-solving skills observed (P=.62 and P=.27, respectively). CONCLUSIONS Problem-solving therapy for weight loss is feasible to implement in a mobile app environment; however, automated delivery may not impact problem-solving skills as has been observed previously via human delivery. CLINICALTRIAL ClinicalTrials.gov NCT02192905; https://clinicaltrials.gov/ct2/show/NCT02192905 (Archived by WebCite at http://www.webcitation.org/6zPQmvOF2)

Osteoarthritis is a common chronic disease that can be better treated with the help of self-management interventions. Mobile health (mHealth) technologies are becoming a popular means to deliver such interventions. We reviewed the current state of research and development of mHealth technologies for osteoarthritis self-management to determine gaps future research could address. We conducted a systematic review of English articles and a survey of apps available in the marketplace as of 2016. Among 117 unique articles identified, 25 articles that met our inclusion criteria were reviewed in-depth. The app search identified 23 relevant apps for osteoarthritis self-management. Through the synthesis of three research themes (osteoarthritis assessment tools, osteoarthritis measurement tools, and osteoarthritis motion monitoring tools) that emerged from the current knowledge base, we provide a design framework to guide the development of more comprehensive osteoarthritis mHealth apps that facilitate self-management, decision support, and shared decision-making.

Introduction: Mobile health (mHealth) technology can be used to integrate into medical decision-making for patients with advanced knee arthritis. We explored patient preferences on content and design of a mobile health app to facilitate daily symptom capture and summary feedback reporting, in order to inform treatment decisions, including use of total knee replacement surgery (TKR).Methods: Patient focus groups were conducted to gather requirements for mHealth app development and to refine the design and content of the app. Clinician (physical therapist, surgeon) interviews were conducted to understand clinician expectations from the summary trend report generated by the app.Results: Sixteen patients attended focus groups with an average age of 67 and 63% female, and three clinicians participated in clinician interviews. The preliminary findings revealed that the patients preferred easy tap user interfaces to multitap or slider methods, and vertical question layout to horizontal orientation. Patients liked to be engaged by progress feedback reports and educational tips. Both patients and clinicians found a trended outcome summary report helpful which provides more precise details on whether and how the symptoms are changing over time.Discussion: User input can inform the design and implementation of mHealth technology to meet patient needs for their treatment decisions. Patient priorities must be considered through patient-centered app design.

The standard chronic wound assessment method based on visual examination is potentially inaccurate and also represents a significant clinical workload. Hence, computer-based systems providing quantitative wound assessment may be valuable for accurately monitoring wound healing status, with the wound area the best suited for automated analysis. Here, we present a novel approach, using support vector machines (SVM) to determine the wound boundaries on foot ulcer images captured with an image capture box, which provides controlled lighting and range. After superpixel segmentation, a cascaded two-stage classifier operates as follows: in the first stage, a set of k binary SVM classifiers are trained and applied to different subsets of the entire training images dataset, and incorrectly classified instances are collected. In the second stage, another binary SVM classifier is trained on the incorrectly classified set. We extracted various color and texture descriptors from superpixels that are used as input for each stage in the classifier training. Specifically, color and bag-of-word representations of local dense scale invariant feature transformation features are descriptors for ruling out irrelevant regions, and color and wavelet-based features are descriptors for distinguishing healthy tissue from wound regions. Finally, the detected wound boundary is refined by applying the conditional random field method. We have implemented the wound classification on a Nexus 5 smartphone platform, except for training which was done offline. Results are compared with other classifiers and show that our approach provides high global performance rates (average sensitivity = 73.3%, specificity = 94.6%) and is sufficiently efficient for a smartphone-based image analysis.

BackgroundReviews of weight loss mobile apps have revealed they include very few evidence-based features, relying mostly on self-monitoring. Unfortunately, adherence to self-monitoring is often low, especially among patients with motivational challenges. One behavioral strategy that is leveraged in virtually every visit of behavioral weight loss interventions and is specifically used to deal with adherence and motivational issues is problem solving. Problem solving has been successfully implemented in depression mobile apps, but not yet in weight loss apps. ObjectiveThis study describes the development and feasibility testing of the Habit app, which was designed to automate problem-solving therapy for weight loss. MethodsTwo iterative single-arm pilot studies were conducted to evaluate the feasibility and acceptability of the Habit app. In each pilot study, adults who were overweight or obese were enrolled in an 8-week intervention that included the Habit app plus support via a private Facebook group. Feasibility outcomes included retention, app usage, usability, and acceptability. Changes in problem-solving skills and weight over 8 weeks are described, as well as app usage and weight change at 16 weeks. ResultsResults from both pilots show acceptable use of the Habit app over 8 weeks with on average two to three uses per week, the recommended rate of use. Acceptability ratings were mixed such that 54% (13/24) and 73% (11/15) of participants found the diet solutions helpful and 71% (17/24) and 80% (12/15) found setting reminders for habits helpful in pilots 1 and 2, respectively. In both pilots, participants lost significant weight (P=.005 and P=.03, respectively). In neither pilot was an effect on problem-solving skills observed (P=.62 and P=.27, respectively). ConclusionsProblem-solving therapy for weight loss is feasible to implement in a mobile app environment; however, automated delivery may not impact problem-solving skills as has been observed previously via human delivery. Trial RegistrationClinicalTrials.gov NCT02192905; https://clinicaltrials.gov/ct2/show/NCT02192905 (Archived by WebCite at http://www.webcitation.org/6zPQmvOF2)

The active engagement of consumers is an important factor in achieving widespread success of health information systems. The disability community represents a major segment of the healthcare arena, with more than 50 million Americans experiencing some form of disability. In keeping with the “consumer-driven” approach to e-health systems, this paper considers the distinctive aspects of electronic and personal health record use by this segment of society. Drawing upon the information shared during two national policy forums on this topic, the authors present the concept of Electronic Disability Records (EDR). The authors outline the purpose and parameters of such records, with specific attention to its ability to organize health and financial data in a manner that can be used to expedite the disability determination process. In doing so, the authors discuss its interaction with Electronic Health Records (EHR) and Personal Health Records (PHR). The authors then draw upon these general parameters to outline a model use case for disability determination and discuss related implications for disability health management. The paper further reports on the subsequent considerations of these and related deliberations by the American Health Information Community (AHIC).

This study investigates project initiation for telemedicine, a technology innovation in healthcare organizations that manifests both intra- and inter-organizational collaboration. Moving from a telemedicine project to a sustainable telemedicine service line can be a challenge for many organizations (LeRouge, Tulu, & Forducey, 2010). Project definition (a.k.a., initiation) sets the strategic vision for a project and has been categorized as the most important stage in a project (C. Gray & Larson, 2008) and a key element for project success (Stah-Le Cardinal & Marle, 2006). Although project management best practices have been applied in many domains, there are few studies that link published best practices to the telemedicine domain. This study first presents a model, resulting from a review of project management literature that specifies the recommended components project definition. Using this model as a foundation, the authors explore how project definition is deployed in the telemedicine domain, using the instantiation of telestroke projects for this study. The authors base their findings on a multi-case qualitative data set, with each case representing a distinct telemedicine business model. Findings from this study explicate how the telestroke project initiation process is collaboratively managed and how this process impacts the overall success of the telemedicine programs through the lens of the five distinct telemedicine business models. Specifically, this study contributes insights on key elements of project initiation in the telemedicine context as well as the effects of the varying business models (focusing on commonalities and differences).

We developed a health and wellness smartphone app to support diabetes self-management. The target users are older, less healthy adults with advanced type 2 diabetes. We illustrate the design implications of a health and wellness smartphone app for such users by presenting the process and results of our usability and user experience lab test with our app.

For individuals with type 2 diabetes, foot ulcers represent a significant health issue. The aim of this study is to design and evaluate a wound assessment system to help wound clinics assess patients with foot ulcers in a way that complements their current visual examination and manual measurements of their foot ulcers.The physical components of the system consist of an image capture box, a smartphone for wound image capture and a laptop for analyzing the wound image. The wound image assessment algorithms calculate the overall wound area, color segmented wound areas, and a healing score, to provide a quantitative assessment of the wound healing status both for a single wound image and comparisons of subsequent images to an initial wound image.The system was evaluated by assessing foot ulcers for 12 patients in the Wound Clinic at University of Massachusetts Medical School. As performance measures, the Matthews correlation coefficient (MCC) value for the wound area determination algorithm tested on 32 foot ulcer images was .68. The clinical validity of our healing score algorithm relative to the experienced clinicians was measured by Krippendorff's alpha coefficient (KAC) and ranged from .42 to .81.Our system provides a promising real-time method for wound assessment based on image analysis. Clinical comparisons indicate that the optimized mean-shift-based algorithm is well suited for wound area determination. Clinical evaluation of our healing score algorithm shows its potential to provide clinicians with a quantitative method for evaluating wound healing status.

The potential of patient portals to improve patient engagement and health outcomes has been discussed for more than a decade. The slow growth in patient portal adoption rates among patients and providers in the United States, despite external incentives, indicates that this is a complex issue. We examined evidence of patient portal use and effects with a focus on the pulmonary domain. We found a paucity of studies of patient portal use in pulmonary practice, and highlight gaps for future research. We also report on the experience of a pulmonary department using a patient portal to highlight the potential of these systems.

Diabetic foot ulcers represent a significant health issue. Currently, clinicians and nurses mainly base their wound assessment on visual examination of wound size and healing status, while the patients themselves seldom have an opportunity to play an active role. Hence, a more quantitative and cost-effective examination method that enables the patients and their caregivers to take a more active role in daily wound care potentially can accelerate wound healing, save travel cost and reduce healthcare expenses. Considering the prevalence of smartphones with a high-resolution digital camera, assessing wounds by analyzing images of chronic foot ulcers is an attractive option. In this paper, we propose a novel wound image analysis system implemented solely on the Android smartphone. The wound image is captured by the camera on the smartphone with the assistance of an image capture box. After that, the smartphone performs wound segmentation by applying the accelerated mean-shift algorithm. Specifically, the outline of the foot is determined based on skin color, and the wound boundary is found using a simple connected region detection method. Within the wound boundary, the healing status is next assessed based on red–yellow–black color evaluation model. Moreover, the healing status is quantitatively assessed, based on trend analysis of time records for a given patient. Experimental results on wound images collected in UMASS—Memorial Health Center Wound Clinic (Worcester, MA) following an Institutional Review Board approved protocol show that our system can be efficiently used to analyze the wound healing status with promising accuracy.

Running is a popular physical activity that improves physical and mental wellbeing. Unfortunately, up-to- date information about runners’ performance and psychological wellbeing is limited. Many questions remain unanswered, such as how far and how fast runners typically run, their preferred running times and frequencies, how long new runners persist before dropping out, and what factors cause runners to quit. Without hard data, establishing patterns of runner behavior and mitigating the challenges they face are difficult. Collecting data manually from large numbers of runners for research studies is costly and time consuming. Emerging Social Networking Services (SNS) and fitness tracking devices make tracking and sharing personal physical activity information easier than before. By monitoring the tweets of a runner group on Twitter (SNS) over a 3-month period, we collected 929,825 messages (tweets), in which runners used Nike+ fitness trackers while running. We found that (1) fitness trackers were most popular in North America (2) one third of runners dropped out after one run (3) Over 95% of runners ran for at least 10 minutes per session (4) less than 2% of runners consistently ran for at least 150 minutes a week, which is the level of physical activity recommended by the CDC (5) 5K was the most popular distance.

Over one billion smartphones have now been shipped worldwide. These mobile devices feature multi-core CPUs and GPUs, megapixel cameras and an array of sensors. Smartphone sensors can now be processed to diagnose a wide variety of medical conditions including cough detection, irregular heartbeat detection, and lung function analysis. The ability to diagnose ailments in the convenience of patients' homes on smartphones that they already possess could lead to early detection, which could ultimately reduce healthcare costs. This paper reviews state-of-the-art examples, examines the technical issues involved in the use of the smartphone as a medical device, and outlines potential benefits and challenges. A case study of an Android smartphone app for wound detection and healing progress analysis by diabetes patients is also presented.

This study investigates telemedicine as a collaborative technology innovation in healthcare organizations. We use the collaborative ontology [17] inspiring this mini-track to describe our instantiation of telemedicine, namely telestroke services. We discuss how the telestroke project initiation process is managed and how this process impacts the overall success of the telemedicine programs through the lens of three distinct telemedicine business models. We provide insights on the effects of the varying business models focusing on commonalities and differences in project initiation phase. We base our findings on a multi-case qualitative data set.

This paper evaluates existing taxonomies aimed at characterizing the interaction between robots and their users and modifies them for health care applications. The modifications are based on existing robot technologies and user acceptance of robotics. Characterization of the user, or in this case the patient, is a primary focus of the paper, as they present a unique new role as robot users. While therapeutic and monitoring-related applications for robots are still relatively uncommon, we believe they will begin to grow and thus it is important that the spurring relationship between robot and patient is well understood.

Personal Health Records (PHRs) and patient portals are becoming more popular as health systems continue to emphasize patient centered health care delivery. Our study investigates the factors that influence adoption and utilization of PHR systems using a mixed method approach. Our data include PHR system utilization data collected about registered users of seven primary care physicians during the period between September 2009 and February 2011, as well as interviews of a subset of these users. Analyses of these data provide insights into how and why users interact with the system. They also assist in identifying ways to enhance the overall PHR portal experience for physicians and patients. In this paper, we present our preliminary findings and discuss potential future research directions.

Many employers now provide electronic personal health records (PHR) to employees as part of a free or low cost health benefit program. This paper reports findings from a survey distributed to employees of a large U.S. corporation. The survey focused on identifying employee concerns and expectations from an employer sponsored PHR system and to help understand the utilization and adoption of PHR systems sponsored by the employer. Despite some past research showing significant demand for PHR products across the general public, especially those that are offered for free, responses indicated many barriers. Participants responded with their concerns and expectations prior to using the system as well as their difficulty or ease of use. Key issues are discussed, including current and future role of employers in the PHR marketplace, including the need to “tether” these offerings to larger health care provider networks in order for employees to realize the value added.

This chapter provides a conceptual foundation by exploring the existing literature on traditional healthcare, patient-centered healthcare, and the progression of e-health in enabling the movement towards patient-centered care. This chapter also discusses enhancing the relationship between the patient and the healthcare provider through e-health. We conclude with a discussion of the future of patient-centered e-health and future research opportunities in this area.

Transferring concepts of value for many health information technologies (HIT) into strategic, sustainable programs for health care organizations can be a challenge. The objective of this study is to explore organizational strategy for deploying HIT programs to provide a foundation for strategic guidelines and archetype models in the health care domain. Telemedicine (medical video conferencing) serves as our instantiation of an HIT. We use a multi-case study approach that employs quantitative and qualitative methods.

This exploratory study investigated the impact of incomplete medical evidence on the SSA disability determination process and the role of HIT as a solution. We collected qualitative data from nineteen expert-interviews. Findings indicate that HIT can lead to innovative solutions that can significantly improve the determination process.

Telemedicine allows medical doctors and specialized skilled experts to provide services to patients who are in remote locations using advanced telecommunications. This paper presents a taxonomy that systematically classifies various telemedicine efforts worldwide using five major dimensions: application purpose, application area, environmental setting, communication infrastructure, and delivery options. To identify relationships and patterns between these different dimensions telemedicine programs survey data from the Telemedicine Information Exchange (TIE) was analyzed using multiple regression and path analysis. Major findings indicate that interactive video is the most preferred modality. Store-and-forward technology is preferred for ophthalmology, radiology, and pathology. However, a negative correlation exists between store-and-forward and interactive video with mental health application. The study also indicates that the Internet is still not the dominant communications infrastructure when it comes to telemedicine. We showed that these dimensions can capture almost all efforts in telemedicine and also help program planners to understand the issues in telemedicine deployment. Our findings indicate that the taxonomy is useful for categorizing and comparing existing programs, and can be used for planning future programs.

This paper describes the design, architecture, and implementation of a software application, FreezeFramer, developed to help individuals manage stress. The application measures heart rate variability through a finger or earlobe clip-on sensor that reads pulse information. While a detailed subjective evaluation is on going, system performance analyses are reported here.

This study investigates the adoption of Electronic Medical Records (EMRs) in a developing country, Mexico. The motivating factors for and barriers to adoption of EMR is discussed based on the data collected through focus groups and surveys.

Our study focuses on the video component of multimedia applications with the goal of understanding the relationship between objective and subjective video quality measures and clinical decision making capability of the medical professionals on the receiving end, with Internet as the transmission channel. An actual telemedicine video sequence is used in this study. The quality of this sequence was degraded using network impairments and 14 degraded sequences plus the original sequence were presented to 15 subjects. Participants were asked to evaluate the quality of the sequences and their decision making capability based on the sequence under consideration. The results indicate that the quality score does not always correlate to the clinical decision making capability score. Same thing is also true for objective quality measures. Further research is needed to better understand the effects of video quality degradation on medical decision making in telemedicine environments. quality of the actual video being received by the users of the digital video system rather than the measured quality of traditional video test signals (e.g., color bar)". Especially in telemedicine, perceived video quality plays a critical role in the medical professional's confidence level in decision making. We utilized the outcome of our previous work where a test video was transmitted over an emulated Internet and a large number of degraded video clips were obtained (2). In the previous study, objective metrics such as Peak Signal to Noise Ratio (PSNR) were calculated for various degradations. In this study, these video clips were later evaluated by human subjects in terms of their perceived quality score and their perceived decision making capability score.

The Internet is designed to provide best effort service, which is not suitable for real-time applications. Therefore, carrying real-time applications over the Internet presents a number of challenges. While quality of service technologies can overcome some of these challenges, most medical facilities and patient homes do not utilize them since there is a high cost associated. Telemedicine and related technologies provide a promising opportunity to improve our healthcare reach to wider populations. The low cost and ubiquity of the Internet can help deliver healthcare to a wider population. However, the unreliable connection properties of packet-based systems hamper the quality of Internet-based telemedicine applications. This research is aimed to explore the delay, jitter, and drop cutoff points for Internet-based videoconferencing applications where video quality stays above the acceptable peak-signal-to-noise-ratio value (25dB). An experimental study is conducted on our testbed where behavior of the Internet is emulated on a Linux PC using NIST Net, a network emulation tool. Video file utilized during these experiments is an ophthalmology telemedicine session and it was obtained from the Regenstrief Institute for Health Care. Video quality measurements are computed using Video Quality Metric (VQM) software, which was developed by the Institute for Telecommunication Sciences (ITS). Our analysis and results indicate that jitter has a severe effect on the video quality whereas the effect of delay is almost invisible. Drop effects are similar to jitter with less impact on video quality. Results presented in this paper include the cutoff points for these variables as well.

This chapter develops a conceptual model for physician acceptance and tests this socio-work structure model using a nationwide survey of physicians (n = 141). The domain focus of this study is physician acceptance of online disability evaluation systems for generating and managing medical examination reports. The survey measured whether behavioral intention to use the new system varied as a function of IT infrastructure, organizational readiness relating to IT, physician experience with computer use in clinical settings, and both specific and general attitudes toward online system use in clinical settings. Survey findings suggest that each of these factors affects behavioral intent to use online disability evaluation systems and that these factors are more important than generalized attitudes toward online systems or socio-demographic predictors. Findings suggest that work-practice variables are important when considering physicians use of online systems. The chapter concludes with a discussion of implications for devising advanced testing systems that can be used to ensure active physician participation in medical informatics systems

Geographic information systems (GIS) have numerous applications in human health. This chapter opens with a brief discussion of the three dimensions of decision-making in organizations — operational control, management control, and strategic planning. These dimensions are then discussed in terms of three case studies: a practice-improvement case study under operational control, a service-planning case study under management control, and a research case study under strategic planning. The discussion proceeds with an analysis of GIS contributions to three health care applications: medical/disability services (operational control/practice), emergency response (management control/planning), and infectious disease/SARS (strategic planning/research). The chapter concludes with a cross-case synthesis and discussion of how GIS could be integrated into health care management through Spatial Decision Support Systems and presents three keys issues to consider regarding the management of organizations: Data Integration for Operational Control, Planning Interorganizational Systems for Management Control, and Design Research for Strategic Planning.

As a result of growing interest in telemedicine during the last decade, we have seen the development and deployment of several video conferencing telemedicine applications during recent years. Deployment of these applications was on ISDN lines or dedicated circuits since the bandwidth, security, and privacy have been the biggest concern in telemedicine. Session Initiation Protocol (SIP) is a signaling standard that attracts telemedicine application developers since SIP was designed for multimedia communications over IP-based networks and has inherent native mode security mechanisms built in. We have developed a SIP-based video conferencing application that runs over the Internet and can provide authentication using MD5 Digest hashing mechanism. This client is designed to provide voice and video services using SIP, currently being standardized by IETF. The client is also integrated with directory service designed on commObject architecture. The video conferencing client performance and interoperability has been successfully tested. We are now working on deploying it in a telemedicine environment. In a telemedicine setting we will gather data from users in order to evaluate user satisfaction for both physicians and patients. There are additional features we have identified that can enhance the patient physician communication and they will be obtained easily from our client in the future.

In today's world of ever increasing amounts of information, hospitals and medical groups must continually find ways to manage the myriad information that is gathered on patients. This reality makes the field of medicine well suited to benefit from integrative and online information systems. However, research reveals that at times physicians resist the use of information technology (IT) in the clinical setting. This paper seeks to develop a conceptual model for physician acceptance and test this socio-work structure model using a nationwide survey of physicians (n=141) conducted by the authors. The domain focus of this study is physician acceptance of an online disability evaluation system for generating and managing medical examination reports. The survey measured whether behavioral intention to use the new system varied as a function of IT infrastructure, organizational processes relating to IT, physician experience with computer use in clinical settings, and both specific and general attitudes toward IT use in clinical settings. Survey findings suggest that each of these factors affects behavioral intention to use online disability evaluation systems, and that these factors are more important than generalized attitudes toward online systems or socio-demographic predictors. These findings suggest that work-system variables are important when considering physicians use of online systems. This extends traditional use of TAM to consider organizational factors when analyzing the acceptance decision.

This paper examines the relationship between the healthcare industry and disability evaluation, with a special focus on how information technology (IT) can assist in fostering the disability evaluation process. In the USA, various disability compensation programmes exist, and each uses a specialised terminology to define disability based on the compensation payer's definition. However, ambiguity arises as a result of the use of these multiple definitions and interpretation of terms, which contributes to delays in the disability evaluation process. This paper develops two conceptual models for disability evaluation and explores the underlying business models and the role of IT in achieving productivity gains. Throughout this discussion the focus is on process inefficiencies in determining disabilities and the potential role of innovative business models and technology practices. Finally, future research opportunities and their implications are also enumerated.

This paper presents a conceptual security framework and a case study of a digital signature solution implementation for a healthcare organisation that provides disability evaluation services for various government agencies and private companies. One service the company provides for its clients is online disability report generation and electronic report submission. When generating these disability reports, the signature of the examining physician is required for submission. The current process used by the company involves the manual collection of signatures. To streamline this process, and to meet legal and client requirements, the company investigated a digital signature solution. A security framework previously proposed was utilised to guide the implementation of the digital signature solution. This security framework consists of eight sequential stages. An in-depth analysis of the first seven stages for this case is provided, including guidelines for choosing digital signature solutions, vendor analyses and implementation issues.

There is some tacit understanding that telemedicine can provide cost efficiency along with increased access and equality of care for the geographically disadvantaged. However, concrete strategic guidance for healthcare organizations to attain these benefits is fragmented and limited in existing literature. Telemedicine programs need to move from a grant-funded to a profit-centered status to sustain their existence. This article extends work presented at a recent American Telemedicine Association Business and Finance Special Interest Group course to provide a conceptual framework for strategic planning and for effectively implementing telemedicine programs. An expert panel of telemedicine coordinators provides insight and recommendations.