Communicating Treatment-Related Symptoms Using Passively Collected Data and Satisfaction/Loyalty Ratings: Exploratory Study

BackgroundElectronic patient-reported outcomes’ real time communication of treatment-related symptoms is increasingly associated with better outcomes including longer survival and less health care resource use, but the primary method of collecting this information, static questionnaires, has not evolved. ObjectiveThe aim of this paper is to describe the use of Noona’s three methods of communicating treatment-related symptoms, which are as follows: (1) Noona symptom questionnaires (NSQ), which incorporate branching logic; (2) a diary; and (3) secure messaging, the last two of which have NSQ reporting functionality. It also aims to explore, using multivariable analyses, whether patients find value using these features. MethodsNoona users (N=1081) who have an active account for more than 30 days, who responded to the satisfaction/loyalty item, and who were undergoing active cancer treatment (systemic or radiotherapy) in the United States were included in this study. All study data were collected via software embedded within Noona code. This includes metadata, patient activities (measured in clicks), and responses to a satisfaction/loyalty question (“How likely are you to recommend Noona to another patient”) displayed on the Noona home page. ResultsNoona users expressed a high degree of satisfaction/loyalty when asked to rate how likely they would recommend Noona to another patient. Multivariable analyses indicate small but significant effects for some of the analyses. Use of NSQs were significantly related to satisfaction/loyalty, users of NSQs had significantly higher satisfaction/loyalty than those who did not use any, and secure communication use was significantly higher for those who rated the app highly compared to those who did not. These relationships will likely be further explicated with the use of satisfaction/loyalty questions that focus specifically on feature use. ConclusionsNoona is well liked by respondents, and exploratory multivariable analyses demonstrate the potential for using passively and minimally invasive data to demonstrate value

The association between body mass index and health and economic outcomes in Brazil

Abstract Background Obesity is associated with significant physical, psychosocial and economic burden globally. In Brazil, almost 50% of the population is either overweight or obese. The prevalence of morbid obesity increased by 255% between 1975 and 2003. The current study sought to quantify the relationship between weight status and health outcomes. Methods Data from three waves (2011, 2012, and 2015) of the Brazil National Health and Wellness Survey, an Internet-based survey administered to a demographically diverse sample of Brazilian adults, were used. Body mass index category was calculated based on self-reported height and weight and respondents were categorized into five groups (normal, overweight, obese class I, obese class II, obese class III; n = 34,254). Multivariable analyses, controlling for sociodemographic variables and health history, tested the association with body mass index group and outcomes including health status (Medical Outcomes Study Short Form 12-Item Health Survey version 2/Medical Outcomes Study Short Form 36-Item Health Survey version 2), work productivity (Work Productivity and Activity Impairment-General Health Questionnaire), and costs associated with work impairment (indirect costs), self-reported healthcare resource use and associated direct costs. Results Overall, 53.6% of the surveyed Brazilian population reported being overweight or obese. In virtually all the analyses, increasing body mass index group was associated with significant and progressively worse outcomes. Most notable was the finding that hospitalization costs were over twice as high (R$3141.84 vs. R$1349.60) and indirect costs were nearly double (R$1656.80 vs. R$884.15) for obesity class III than for normal body mass index respondents. Conclusions Obesity rates in Brazil are considerable and, from a patient and societal perspective, increasingly burdensome, thereby highlighting the need for stakeholders to prioritize strategies for weight management interventions

Development of an Electronic Medical Record-Based Clinical Decision Support Tool to Improve HIV Symptom Management

Common symptoms associated with HIV disease and its management are often underrecognized and undertreated. A clinical decision support tool for symptom management was developed within the Veterans Health Administration electronic medical record (EMR), aiming at increasing provider awareness of and response to common HIV symptoms. Its feasibility was studied in March to May 2007 by implementing it within a weekly HIV clinic, comparing a 4-week intervention period with a 4-week control period. Fifty-six patients and their providers participated in the study. Patients' perceptions of providers' awareness of their symptoms, proportion of progress notes mentioning any symptom(s) and proportion of care plans mentioning any symptom(s) were measured. The clinical decision support tool used portable electronic “tablets” to elicit symptom information at the time of check-in, filtered, and organized that information into a concise and clinically relevant EMR note available at the point of care, and facilitated clinical responses to that information. It appeared to be well accepted by patients and providers and did not substantially impact workflow. Although this pilot study was not powered to detect effectiveness, 25 (93%) patients in the intervention group reported that their providers were very aware of their symptoms versuas 27 (75%) control patients (p = 0.07). The proportion of providers' notes listing symptoms was similar in both periods; however, there was a trend toward including a greater number of symptoms in intervention period progress notes. The symptom support tool seemed to be useful in clinical HIV care. The Veterans Health Administration EMR may be an effective “laboratory” for developing and testing decision supports