Screening for Chronic Conditions Using a Patient Internet Portal: Recruitment for an Internet-based Primary Care Intervention

Background: Patient Internet portals have created new opportunities for assessment and management of chronic conditions. Objective: To conduct an online screening survey for a study recruitment using a secure patient Internet portal to identify primary care patients with untreated depression, chronic pain, or mobility difficulty before nonurgent office visits. Design: Internet-based screening survey for a randomized trial. Participants: Patients who were registered portal users who had scheduled primary care appointments. Approach: Electronic study invitations via the portal were sent to 4,047 patients with scheduled visits to 34 primary care physicians participating in the study. After clicking on a link in the study invitation, patients were consecutively shown the study description, consent form, and lastly, the screening survey to determine final eligibility for study participation. Results: Of the 2,113 (52%) patients who opened the study invitation, 1,001 consented online to join the study and 981 (98%) of these completed the screening survey. Of the respondents, 319 (33%) screened positive for 1 or more of the 3 conditions. Conclusions: The online screening survey conducted through the patient portal was effective in identifying patients with chronic conditions in advance of scheduled primary care visits for participation in an intervention study

Targeting medication non-adherence behavior in selected autoimmune diseases: a systematic approach to digital health program development

Background 29 autoimmune diseases, including Rheumatoid Arthritis, gout, Crohn’s Disease, and Systematic Lupus Erythematosus affect 7.6-9.4% of the population. While effective therapy is available, many patients do not follow treatment or use medications as directed. Digital health and Web 2.0 interventions have demonstrated much promise in increasing medication and treatment adherence, but to date many Internet tools have proven disappointing. In fact, most digital interventions continue to suffer from high attrition in patient populations, are burdensome for healthcare professionals, and have relatively short life spans. Objective Digital health tools have traditionally centered on the transformation of existing interventions (such as diaries, trackers, stage-based or cognitive behavioral therapy programs, coupons, or symptom checklists) to electronic format. Advanced digital interventions have also incorporated attributes of Web 2.0 such as social networking, text messaging, and the use of video. Despite these efforts, there has not been little measurable impact in non-adherence for illnesses that require medical interventions, and research must look to other strategies or development methodologies. As a first step in investigating the feasibility of developing such a tool, the objective of the current study is to systematically rate factors of non-adherence that have been reported in past research studies. Methods Grounded Theory, recognized as a rigorous method that facilitates the emergence of new themes through systematic analysis, data collection and coding, was used to analyze quantitative, qualitative and mixed method studies addressing the following autoimmune diseases: Rheumatoid Arthritis, gout, Crohn’s Disease, Systematic Lupus Erythematosus, and inflammatory bowel disease. Studies were only included if they contained primary data addressing the relationship with non-adherence. Results Out of the 27 studies, four non-modifiable and 11 modifiable risk factors were discovered. Over one third of articles identified the following risk factors as common contributors to medication non-adherence (percent of studies reporting): patients not understanding treatment (44%), side effects (41%), age (37%), dose regimen (33%), and perceived medication ineffectiveness (33%). An unanticipated finding that emerged was the need for risk stratification tools (81%) with patient-centric approaches (67%). Conclusions This study systematically identifies and categorizes medication non-adherence risk factors in select autoimmune diseases. Findings indicate that patients understanding of their disease and the role of medication are paramount. An unexpected finding was that the majority of research articles called for the creation of tailored, patient-centric interventions that dispel personal misconceptions about disease, pharmacotherapy, and how the body responds to treatment. To our knowledge, these interventions do not yet exist in digital format. Rather than adopting a systems level approach, digital health programs should focus on cohorts with heterogeneous needs, and develop tailored interventions based on individual non-adherence patterns

Multicommodity Capacitated Network Design

This paper presents a comprehensive survey of models and algorithms for multicommodity capacitated network design problems, which are mostly encountered in telecommunications and transportation network planning. These problems are important not only due to the major relevance of their applications, but also because they pose considerable modeling and algorithmic challenges. We present a general arc-based model, describe useful alternative formulations and survey the literature on simplex-based cutting plane and Lagrangian relaxation approaches. We then focus on our own contributions that develop and compare several relaxation methods for a particular case of this model, the fixed-charge problem. These methods are based on Lagrangian relaxation and nondifferentiable optimization techniques, namely, the subgradient and bundle approaches. Our experimental results, while very encouraging, indicate that solving effciently these diffcult problems requires a judicious combination of cutting planes, Lagrangian relaxation methods and sophisticated heuristics. In addition, due to their inherent decomposition properties, these techniques can be adapted to parallel computing environments, which is highly desirable in order to solve realistically sized instances