A Primer on Quality Assurance and Performance Improvement for Interprofessional Chronic Kidney Disease Care: A Path to Joint Commission Certification.

Interprofessional care for chronic kidney disease facilitates the delivery of high quality, comprehensive care to a complex, at-risk population. Interprofessional care is resource intensive and requires a value proposition. Joint Commission certification is a voluntary process that improves patient outcomes, provides external validity to hospital administration and enhances visibility to patients and referring providers. This is a single-center, retrospective study describing quality assurance and performance improvement in chronic kidney disease, Joint Commission certification and quality outcomes. A total of 440 patients were included in the analysis. Thirteen quality indicators consisting of clinical and process of care indicators were developed and measured for a period of two years from 2009-2017. Significant improvements or at least persistently high performance were noted for key quality indicators such as blood pressure control (85%), estimation of cardiovascular risk (100%), measurement of hemoglobin A1c (98%), vaccination (93%), referrals for vascular access and transplantation (100%), placement of permanent dialysis access (61%), discussion of advanced directives (94%), online patient education (71%) and completion of office visit documentation (100%). High patient satisfaction scores (94-96%) are consistent with excellent quality of care provided

A network analysis to compare biomarker profiles in patients with and without diabetes mellitus in acute heart failure

Aims: It is unclear whether distinct pathophysiological processes are present among patients with acute heart failure (AHF), with and without diabetes. Network analysis of biomarkers may identify correlative associations that reflect different pathophysiological pathways. Methods and results: We analysed a panel of 48 circulating biomarkers measured within 24 h of admission for AHF in a subset of patients enrolled in the PROTECT trial. In patients with and without diabetes, we performed a network analysis to identify correlations between measured biomarkers. Compared with patients without diabetes (n = 1111), those with diabetes (n = 922) had a higher prevalence of ischaemic heart disease and traditional coronary risk factors. After multivariable adjustment, patients with and without diabetes had significantly different levels of biomarkers across a spectrum of pathophysiological domains, including inflammation (TNFR-1a, periostin), cardiomyocyte stretch (BNP), angiogenesis (VEGFR, angiogenin), and renal function (NGAL, KIM-1) (adjusted P-value <0.05). Among patients with diabetes, network analysis revealed that periostin strongly clustered with C-reactive protein and interleukin-6. Furthermore, renal markers (creatinine and NGAL) closely associated with potassium and glucose. These findings were not seen among patients without diabetes. Conclusion: Patients with AHF and diabetes, compared with those without diabetes, have distinct biomarker profiles. Network analysis suggests that cardiac remodelling, inflammation, and fibrosis are closely associated with each other in patients with diabetes. Furthermore, potassium levels may be sensitive to changes in renal function as reflected by the strong renal–potassium–glucose correlation. These findings were not seen among patients without diabetes and may suggest distinct pathophysiological processes among AHF patients with diabetes

Receding Horizon Control of Type 1 Diabetes Mellitus by Using Nonlinear Programming

Receding Horizon Controllers are one of the mostly used advanced control solutions in the industry. By utilizing their possibilities we are able to predict the possible future behavior of our system; moreover, we are able to intervene in its operation as well. In this paper we have investigated the possibilities of the design of a Receding Horizon Controller by using Nonlinear Programming. We have applied the developed solution in order to control Type 1 Diabetes Mellitus. The nonlinear optimization task was solved by the Generalized Reduced Gradient method. In order to investigate the performance of our solution two scenarios were examined. In the first scenario, we applied “soft” disturbance—namely, smaller amount of external carbohydrate—in order to be sure that the proposed method operates well and the solution that appeared through optimization is acceptable. In the second scenario, we have used “unfavorable” disturbance signal—a highly oscillating external excitation with cyclic peaks. We have found that the performance of the realized controller was satisfactory and it was able to keep the blood glucose level in the desired healthy range—by considering the restrictions for the usable control action

An integrated circuit for chip-based analysis of enzyme kinetics and metabolite quantification

We have created a novel chip-based diagnostic tools based upon quantification of metabolites using enzymes specific for their chemical conversion. Using this device we show for the first time that a solid-state circuit can be used to measure enzyme kinetics and calculate the Michaelis-Menten constant. Substrate concentration dependency of enzyme reaction rates is central to this aim. Ion-sensitive field effect transistors (ISFET) are excellent transducers for biosensing applications that are reliant upon enzyme assays, especially since they can be fabricated using mainstream microelectronics technology to ensure low unit cost, mass-manufacture, scaling to make many sensors and straightforward miniaturisation for use in point-of-care devices. Here, we describe an integrated ISFET array comprising 216 sensors. The device was fabricated with a complementary metal oxide semiconductor (CMOS) process. Unlike traditional CMOS ISFET sensors that use the Si3N4 passivation of the foundry for ion detection, the device reported here was processed with a layer of Ta2O5 that increased the detection sensitivity to 45 mV/pH unit at the sensor readout. The drift was reduced to 0.8 mV/hour with a linear pH response between pH 2 – 12. A high-speed instrumentation system capable of acquiring nearly 500 fps was developed to stream out the data. The device was then used to measure glucose concentration through the activity of hexokinase in the range of 0.05 mM – 231 mM, encompassing glucose’s physiological range in blood. Localised and temporal enzyme kinetics of hexokinase was studied in detail. These results present a roadmap towards a viable personal metabolome machine

A case study in open source innovation: developing the Tidepool Platform for interoperability in type 1 diabetes management.

OBJECTIVE:Develop a device-agnostic cloud platform to host diabetes device data and catalyze an ecosystem of software innovation for type 1 diabetes (T1D) management. MATERIALS AND METHODS:An interdisciplinary team decided to establish a nonprofit company, Tidepool, and build open-source software. RESULTS:Through a user-centered design process, the authors created a software platform, the Tidepool Platform, to upload and host T1D device data in an integrated, device-agnostic fashion, as well as an application ("app"), Blip, to visualize the data. Tidepool's software utilizes the principles of modular components, modern web design including REST APIs and JavaScript, cloud computing, agile development methodology, and robust privacy and security. DISCUSSION:By consolidating the currently scattered and siloed T1D device data ecosystem into one open platform, Tidepool can improve access to the data and enable new possibilities and efficiencies in T1D clinical care and research. The Tidepool Platform decouples diabetes apps from diabetes devices, allowing software developers to build innovative apps without requiring them to design a unique back-end (e.g., database and security) or unique ways of ingesting device data. It allows people with T1D to choose to use any preferred app regardless of which device(s) they use. CONCLUSION:The authors believe that the Tidepool Platform can solve two current problems in the T1D device landscape: 1) limited access to T1D device data and 2) poor interoperability of data from different devices. If proven effective, Tidepool's open source, cloud model for health data interoperability is applicable to other healthcare use cases

Innovative Device for Indocianyne Green Navigational Surgery

Dynamic reality has been integrated into developing surgical techniques, with the goals of providing increased intraoperative accuracy, easier detection of critical anatomical landmarks, and better general results for the patient. Enhancement of the reality in surgical theaters using single or multi sensorial augmenters (haptic, thermic and visual) has been reported with various degrees of success. This paper presents a novel device for navigational surgery and ancillary clinical applications based on the fluorescent properties of Indocyanine Green (ICG), a safe, FDA-approved dye that emits fluorescence at higher wavelengths than endogenous proteins. The latest technological developments and the aforementioned convenient quantum behavior of ICG allow for its effective identification in tissues by means of a complementary metal-oxide semiconductor (CMOS) infrared camera. Following fundamental research on the fluorophor in different biological suspensions and at various concentrations, our team has built a device that casts a beam of excitation light at 780nm and collects emission light at 810-830nm, filtering ambient light and endogenous autofluorescence. The emission light is fluorescent and infrared, unlike visible light. It can penetrate tissues up to 1.6cm in depth, providing after digitization into conventional imaging anatomical and functional data of immense intra-operative value