Evaluating diabetes mobile applications for health literate designs and functionality, 2014

INTRODUCTION: The expansion of mobile health technologies, particularly for diabetes-related applications (apps), grew exponentially in the past decade. This study sought to examine the extent to which current mobile apps for diabetes have health literate features recommended by participants in an Institute of Medicine Roundtable and compare the health literate features by app cost (free or not). METHODS: We used diabetes-related keywords to identify diabetes-related apps for iOS devices. A random sample of 110 apps (24% of total number of apps identified) was selected for coding. The coding scheme was adapted from the discussion paper produced by participants in the Institute of Medicine Roundtable. RESULTS: Most diabetes apps in this sample addressed diabetes management and therapeutics, and paid apps were more likely than free apps to use plain language strategies, to label links clearly, and to have at least 1 feature (a “back” button) that helps with the organization. CONCLUSION: Paid apps were more likely than free apps to use strategies that should be more useful and engaging for people with low health literacy. Future work can investigate ways to make free diabetes mobile apps more user-friendly and accessible

The HealthPia GlucoPack™ Diabetes Phone: A Usability Study

This is a copy of an article published in Diabetes Technology & Therapeutics copyright Mary Ann Liebert, Inc.; Diabetes Technology & Therapeutics is available online at: http://online.liebertpub.com.Background: Type I diabetes is a common chronic disease of childhood. Both the growing influence of peers and the shifting away from parental influence have been implicated as prime elements contributing to poor glycemic outcomes in adolescents. Mobile technology that can be directed towards providing self-management support and modifying potentially negative child parent interaction holds promise to improve control in adolescents with diabetes. Methods: HealthPia, Inc. (Palisades Park, NJ) has developed a prototype system, the HealthPia GlucoPack™ Diabetes Monitoring System, which integrates a small blood glucose monitoring device into the battery pack of a cell phone. A pilot study used mixed quantitative and qualitative methods to evaluate user satisfaction with the integrated system, including the potential of the device to transmit self-monitoring data to a website for review and analysis by clinicians, parents, and patients. Results: Adolescents in our study liked the integration of the two technologies and agreed that the glucometer was easy to use and that the tool was useful in the management of their diabetes. Conclusions: Future work will focus on the utilization of the diabetes phone as a component of a care delivery system for adolescents with diabetes, including involvement of the health care team and enhancement of the web services that support the use of the phone

Prospect patents, data markets, and the commons in data-driven medicine : openness and the political economy of intellectual property rights

Scholars who point to political influences and the regulatory function of patent courts in the USA have long questioned the courts’ subjective interpretation of what ‘things’ can be claimed as inventions. The present article sheds light on a different but related facet: the role of the courts in regulating knowledge production. I argue that the recent cases decided by the US Supreme Court and the Federal Circuit, which made diagnostics and software very difficult to patent and which attracted criticism for a wealth of different reasons, are fine case studies of the current debate over the proper role of the state in regulating the marketplace and knowledge production in the emerging information economy. The article explains that these patents are prospect patents that may be used by a monopolist to collect data that everybody else needs in order to compete effectively. As such, they raise familiar concerns about failure of coordination emerging as a result of a monopolist controlling a resource such as datasets that others need and cannot replicate. In effect, the courts regulated the market, primarily focusing on ensuring the free flow of data in the emerging marketplace very much in the spirit of the ‘free the data’ language in various policy initiatives, yet at the same time with an eye to boost downstream innovation. In doing so, these decisions essentially endorse practices of personal information processing which constitute a new type of public domain: a source of raw materials which are there for the taking and which have become most important inputs to commercial activity. From this vantage point of view, the legal interpretation of the private and the shared legitimizes a model of data extraction from individuals, the raw material of information capitalism, that will fuel the next generation of data-intensive therapeutics in the field of data-driven medicine

Pediatric Obesity: Influence on Drug Dosing and Therapeutics

Obesity is an ongoing global health concern and has only recently been recognized as a chronic disease of energy homeostasis and fuel partitioning. Obesity afflicts 17% of US children and adolescents. Severe obesity (³120% of the 95th percentile of BMI-for-age, or a BMI of ³35 kg/m2) is the fastest growing subgroup and now approaches 6% of all US youth. Health consequences (e.g., type 2 diabetes, coronary heart disease) are related in a dose-dependent manner to severity of obesity. Since therapeutic interventions are less effective in severe obesity, prevention is a high priority. Treatment plans involving combinations of behavioral therapy, nutrition and exercise achieve limited success. Only one drug, orlistat, is FDA-approved for long-term obesity management in adolescents 12 years and older. As part of comprehensive medication management, clinicians should consider the propensity for a given drug to aggravate weight gain and to consider alternatives that minimize weight impact. Medication management must take into account developmental changes as well as pathophysiology of obesity and comorbidities. Despite expanding insight into obesity pathophysiology, there are gaps in its translation to therapeutic application. The historical construct of obesity as simply a fat storage disorder is fundamentally inaccurate. The approach to adjusting doses based solely on body size and extrapolating from therapeutic knowledge of adult obesity may be based on assumptions that are not fully substantiated. Classes of drugs commonly prescribed for comorbidities associated with obesity should be prioritized for clinical research evaluations aimed at optimizing dosing regimens in pediatric obesity

Oral Protein Therapy for the Future - Transport of Glycolipid-Modified Proteins: Vision or Fiction?

The reliable and early diagnosis of common complex multifactorial diseases depends on the individual determination of all (or as many as possible) polymorphisms of each susceptibility gene together with amount and type of the corresponding gene products and their downstream effects, including the synthesis and flux of metabolites and regulation of signalling processes. In addition, this system's biology-driven personalized diagnosis must be accompanied by options for personalized reliable and early therapy. In the midterm, the direct substitution or inhibition of the proteins encoded by the corresponding defective gene products of the susceptibility genes exerting lower or higher activity by administration of the `normal' proteins or inhibitory antibodies, respectively, seems to be most promising. The critical hurdle of oral bioavailability as well as transport into the cytoplasm of the target cells, if required, could be overcome by therapeutic proteins with carboxy-terminal modification by glycosylphosphatidylinositol (GPI). This may be deduced from recent experiments with rat adipocytes. Here this membrane-anchoring glycolipid structure induces the sequential transport of proteins from special regions of the plasma membrane via the surface of intracellular lipid droplets to special membrane vesicles, which are finally released from the adipocytes together with the associated GPI proteins. It remains to be studied whether similar molecular mechanisms operate in intestinal epithelial cells and may enable the transport of GPI proteins from the intestinal lumen into the blood stream. If so, modification of proteins encoded by (combinations of) susceptibility genes with GPI could significantly facilitate the personalized therapy of common diseases on the basis of `inborn' safety, efficacy, rapid realization and oral application. Copyright (C) 2010 S. Karger AG, Base

Artificial neural network algorithm for online glucose prediction from continuous glucose monitoring.

Background and Aims: Continuous glucose monitoring (CGM) devices could be useful for real-time management of diabetes therapy. In particular, CGM information could be used in real time to predict future glucose levels in order to prevent hypo-/hyperglycemic events. This article proposes a new online method for predicting future glucose concentration levels from CGM data. Methods: The predictor is implemented with an artificial neural network model (NNM). The inputs of the NNM are the values provided by the CGM sensor during the preceding 20 min, while the output is the prediction of glucose concentration at the chosen prediction horizon (PH) time. The method performance is assessed using datasets from two different CGM systems (nine subjects using the Medtronic [Northridge, CA] Guardian® and six subjects using the Abbott [Abbott Park, IL] Navigator®). Three different PHs are used: 15, 30, and 45 min. The NNM accuracy has been estimated by using the root mean square error (RMSE) and prediction delay. Results: The RMSE is around 10, 18, and 27 mg/dL for 15, 30, and 45 min of PH, respectively. The prediction delay is around 4, 9, and 14 min for upward trends and 5, 15, and 26 min for downward trends, respectively. A comparison with a previously published technique, based on an autoregressive model (ARM), has been performed. The comparison shows that the proposed NNM is more accurate than the ARM, with no significant deterioration in the prediction delay

A Minority of Patients with Type 1 Diabetes Routinely Downloads and Retrospectively Reviews Device Data.

BackgroundIn type 1 diabetes (T1D), periodic review of blood glucose and insulin dosing should be performed, but it is not known how often patients review these data on their own. We describe the proportion of patients with T1D who routinely downloaded and reviewed their data at home.Materials and methodsA cross-sectional survey of 155 adults and 185 caregivers of children with T1D at a single academic institution was performed. "Routine Downloaders" (downloaded four or more times in the past year) were also considered "Routine Reviewers" if they reviewed their data most of the time they downloaded from devices. Logistic regression was used to identify factors associated with being a Routine Reviewer.ResultsOnly 31% of adults and 56% of caregivers reported ever downloading data from one or more devices, whereas 20% and 40%, respectively, were considered Routine Downloaders. Only 12% of adults and 27% of caregivers were Routine Reviewers. Mean hemoglobin A1c was lower in Routine Reviewers compared with non-Routine Reviewers (7.2±1.0% vs. 8.1±1.6% [P=0.03] in adults and 7.8±1.4% vs. 8.6±1.7% [P=0.001] in children). In adjusted analysis of adults, the odds ratio of being a Routine Reviewer of one or more devices for every 10-year increase in age was 1.5 (95% confidence interval, 1.1, 2.1 [P=0.02]). For every 10 years since diabetes diagnosis, the odds ratio of being a Routine Reviewer was 1.7 (95% confidence interval, 1.2, 2.4 [P=0.01]). For caregivers, there were no statistically significant factors associated with being a Routine Reviewer.ConclusionsA minority of T1D patients routinely downloads and reviews data from their devices on their own. Further research is needed to understand obstacles, provide better education and tools for self-review, and determine if patient self-review is associated with improved glycemic control

Molecular Biology at the bedside: the impact of Genomics on the practice of medicine

Imagine being a newborn baby, discharged home after delivery, with a most unusual gift, a compact disc (CD) carrying all data on "My Genome". The parents would be most anxious to play it on their home PC. Soon, they could discover whether their child has been spared those major single gene disorders which uncle John had before he died young. The doctors had told them they could be selected out when they had opted for pre-gestational diagnosis and selective fertilisation.peer-reviewe