Clinical Severity Score System in Dogs with Degenerative Mitral Valve Disease

BACKGROUND: Several risk factors already have been determined for dogs with degenerative mitral valve disease (DMVD). Risk factors often have been considered in isolation and have not always taken into account additional information provided by the history and physical examination (PE). HYPOTHESIS/OBJECTIVES: Data obtained from history and PE of dogs with DMVD provide prognostic information and can be used for risk stratification. ANIMALS: Client‐owned dogs (n = 244) with DMVD recruited from first opinion practice. METHODS: Prospective longitudinal follow‐up of dogs with DMVD. History and PE data were obtained at 6‐month intervals and analyzed with time‐dependent Cox models to derive relative risk of cardiac death. Independent hazard ratios were used to derive a clinical severity score (CSS), the prognostic value of which was evaluated by analyzing the median survival times for different risk groups and ROC analysis. Analysis of the progression of CSS over time also was undertaken. RESULTS: History of cough, exercise intolerance, decreased appetite, breathlessness (difficulty breathing) and syncope with PE findings of heart murmur intensity louder than III/VI and absence of respiratory sinus arrhythmia were independently associated with outcome and allowed development of the CSS. Clinical severity score distinguished groups of dogs with significantly different outcomes. CONCLUSIONS AND CLINICAL IMPORTANCE: Routinely obtained clinical findings allow risk stratification of dogs with DMVD. Results of ancillary diagnostic tests may be complementary to history and PE findings and always should be interpreted in conjunction with these findings

First passage percolation and a model for competing spatial growth

We generalize Richardson's model by starting with two sites of different colors and giving each new site the color of the site that spawned it. We show that co-existence is possible

Explicit isoperimetric constants and phase transitions in the random-cluster model

The random-cluster model is a dependent percolation model that has applications in the study of Ising and Potts models. In this paper, several new results are obtained for the random-cluster model on nonamenable graphs with cluster parameter $q\geq 1$. Among these, the main ones are the absence of percolation for the free random-cluster measure at the critical value, and examples of planar regular graphs with regular dual where \pc^\f (q) > \pu^\w (q) for $q$ large enough. The latter follows from considerations of isoperimetric constants, and we give the first nontrivial explicit calculations of such constants. Such considerations are also used to prove non-robust phase transition for the Potts model on nonamenable regular graphs

Coupling and Bernoullicity in random-cluster and Potts models

An explicit coupling construction of random-cluster measures is presented. As one of the applications of the construction, the Potts model on amenable Cayley graphs is shown to exhibit at every temperature the mixing property known as Bernoullicity

Usefulness and Usability of a Personal Health Record and Survivorship Care Plan for Colorectal Cancer Survivors: Survey Study

Background: As a result of improvements in cancer screening, treatment, and supportive care, nearly two-thirds of individuals diagnosed with colorectal cancer (CRC) live for 5 years after diagnosis. An ever-increasing population of CRC survivors creates a need for effective survivorship care to help manage and mitigate the impact of CRC and its treatment. Personal health records (PHRs) and survivorship care plans provide a means of supporting the long-term care of cancer survivors. Objective: The purpose of this study is to characterize the usefulness of a CRC PHR and survivorship care plan and to describe the usability of these technologies in a population of CRC survivors. To our knowledge, this is the first study to assess a PHR and survivorship care plan specifically targeting CRC survivors. Methods: Twenty-two patients with CRC were recruited from surgery clinics of an academic medical center and Veterans Affairs hospital in Indianapolis and provided access to an online Colorectal Cancer Survivor’s Personal Health Record (CRCS-PHR). Survey data were collected to characterize the usefulness of the CRCS-PHR and describe its usability in a population of CRC survivors. CRC survivors were surveyed 6 months after being provided online access. Means and proportions were used to describe the usefulness and ease of using the CRC website. Open-ended questions were qualitatively coded using the constant comparative method. Results: CRC survivors perceived features related to their health care (ie, summary of cancer treatment history, follow-up care schedule, description of side effects, and list of community resources) to be more useful than communication features (ie, creating online relationships with family members or caregivers, communicating with doctor, and secure messages). CRC survivors typically described utilizing traditional channels (eg, via telephone or in person) to communicate with their health care provider. Participants had overall positive perceptions with respect to ease of use and overall satisfaction. Major challenges experienced by participants included barriers to system log-in, lack of computer literacy or experience, and difficulty entering their patient information. Conclusions: For CRC, survivors may find the greater value in a PHR’s medical content than the communication functions, which they have available elsewhere. These findings regarding the usefulness and usability of a PHR for the management of CRC survivorship provide valuable insights into how best to tailor these technologies to patients’ needs. These findings can inform future design and development of PHRs for purposes of both cancer and chronic disease management

Information technologies that facilitate care coordination: provider and patient perspectives

Health information technology is a core infrastructure for the chronic care model, integrated care, and other organized care delivery models. From the provider perspective, health information exchange (HIE) helps aggregate and share information about a patient or population from several sources. HIE technologies include direct messages, transfer of care, and event notification services. From the patient perspective, personal health records, secure messaging, text messages, and other mHealth applications may coordinate patients and providers. Patient-reported outcomes and social media technologies enable patients to share health information with many stakeholders, including providers, caregivers, and other patients. An information architecture that integrates personal health record and mHealth applications, with HIEs that combine the electronic health records of multiple healthcare systems will create a rich, dynamic ecosystem for patient collaboration

Some Conditional Correlation Inequalities for Percolation and Related Processes

Consider ordinary bond percolation on a finite or countably infinite graph. Let s, t, a and b be vertices. An earlier paper proved the (nonintuitive) result that, conditioned on the event that there is no open path from s to t, the two events "there is an open path from s to a" and "there is an open path from s to b" are positively correlated. In the present paper we further investigate and generalize the theorem of which this result was a consequence. This leads to results saying, informally, that, with the above conditioning, the open cluster of s is conditionally positively (self-)associated and that it is conditionally negatively correlated with the open cluster of t. We also present analogues of some of our results for (a) random-cluster measures, and (b) directed percolation and contact processes, and observe that the latter lead to improvements of some of the results in a paper of Belitsky, Ferrari, Konno and Liggett (1997)

IUPUI Center for Cancer Population Analytics and Patient-Centered Informatics

poster abstractAbstract: More than 30,000 Indiana residents are diagnosed with cancer each year. Cancer is the second leading cause of death in the state, claiming more than 12,000 lives annually. More than $1 billion was spent in Indiana on direct costs of treating the cancer population in 2003. Indirect costs to cancer patients and their families are also of great importance. Cancer care coordination has the potential to reduce costs and improve quality in cancer care delivery. Coordination may occur both among (1) multiple cancer care providers caring for populations of cancer patients, and (2) between providers and individual patients with cancer The IUPUI Center for Cancer Population Analytics and Patient-Centered Informatics was established in 2013. The center’s mission is to develop team science that combines innovative health information technologies with rigorous health services research methods in order to create knowledge that will have an impact upon the health and health care of patients and populations with cancer in the state of Indiana and the U.S. The center’s goals are (1) to build collaborative, multidisciplinary scientific teams to create national leaders in the state of Indiana in the fields of cancer health services research and informatics, and (2) to perform top-tier national cancer health services research and “big data” analytics to improve the quality, efficiency, coordination, and outcomes of cancer care The Center Cores: To build our research portfolio, we have the following 2 main cores of activity: I. Cancer Population Analytics Core: Data sources from multiple health care organizations throughout central Indiana are being joined together to answer important clinical/epidemiologic questions regarding the quality of cancer care, and design population-based, system interventions to improve the lives of Indiana cancer patients. Further support has been leveraged for this work, namely, the IU Cancer Center has provided a pilot grant to link the Indiana state cancer registry with data from the Regenstrief Institute’s Indiana Network for Patient Care in order to study the utilization of high-cost imaging among cancer survivors. Furthermore, support from a Regenstrief/Merck collaboration will facilitate assessment of the quality of the data linkage at the level of both the patient and cancer case. II. Cancer Patient-Centered Informatics Core: Multiple platforms are being leveraged to develop and test patient-centered technologies to enable individuals to track health care received and communicate with providers. Utilizing OpenMRS, a personal health record (PHR) module was created for colorectal cancer patients including treatment summary information, evidence-based decision support regarding surveillance, and online communication tools. Additional development is being focused upon updating the user interface, creating patient social networks, and providing tools to support patient well-being. Support has also been obtained from the Walther Cancer Foundation to collect information about patient symptoms and from the Regenstrief/Merck collaboration to collect patient-reported outcome measures. Finally, an NIH proposal has been developed for the SUrvivorship Care Plan-PERsonal Health Record Intervention Trial (SUPER-IT), a randomized controlled trial designed to test the effect of this new technology upon both the quality of care received and patient-centered outcomes