Digital algorithm-guided insulin therapy in home healthcare for elderly persons with type 2 diabetes: A proof-of-concept study

GlucoTab@MobileCare, a digital workflow and decision support system with integrated basal and basal-plus insulin algorithm was investigated for user acceptance, safety and efficacy in persons with type 2 diabetes receiving home health care by nurses. During a three months study nine participants (five female, age 77 ± 10 years, HbA1c 60 ± 13 mmol/mol (study start) vs. 57 ± 12 mmol/mol (study end) received basal or basal-plus insulin therapy as suggested by the digital system. In total 95% of all suggested tasks (blood glucose (BG) measurements, insulin dose calculations, insulin injections) were performed according to the digital system. Mean morning BG was 171 ± 68 mg/dL in the first study month vs. 145 ± 35 mg/dL in the last study month, indicating a reduced glycemic variability of 33 mg/dL (standard deviation). No hypoglycemic episode < 54 mg/dL occurred. User’s adherence was high and the digital system supported a safe and effective treatment. Larger scale studies are needed to confirm findings under routine care.

German Clinical Trials Register ID

DRKS00015059

Electronic Diabetes Management System Replaces Paper Insulin Chart: Improved Quality in Diabetes Inpatient Care Processes Due to Digitalization

BACKGROUND

GlucoTab, an electronic diabetes management system (eDMS), supports healthcare professionals (HCPs) in inpatient blood glucose (BG) management at point-of-care and was implemented for the first time under routine conditions in a regional hospital to replace the paper insulin chart.

METHOD

To investigate quality of the eDMS for inpatients with type 2 diabetes mellitus a monocentric retrospective before-after evaluation was conducted. We compared documentation possibilities by assessing a blank paper chart vs the eDMS user interface. Further quality aspects were compared by assessing filled-in paper charts (n = 106) vs filled-in eDMS documentation (n = 241). HCPs (n = 59) were interviewed regarding eDMS satisfaction.

RESULTS

The eDMS represented an improvement of documentation possibilities by offering a more structured and comprehensive user interface compared to the blank paper chart. The number of good diabetes days averaged to a median value of four days in both groups (paper chart: 4.38 [0-7] vs eDMS: 4.38 [0-7] days). Median daily BG was 170 (117-297) mg/dL vs 168 (86-286) mg/dL and median fasting BG was 152 (95-285) mg/dL vs 145 (69-333) mg/dL, and 0.1% vs 0.4% BG values <54 mg/dL were documented. Diabetes documentation quality improved when using eDMS, for example, documentation of ordered BG measurement frequency (1% vs 100%) and ordered BG targets (0% vs 100%). HCPs stated that by using eDMS errors could be prevented (74%), and digital support of work processes was completed (77%). Time saving was noted by 8 out of 11 HCPs and estimated at 10-15 minutes per patient day by two HCPs.

CONCLUSIONS

The eDMS completely replaced the paper chart, showed comparable glycemic control, was positively accepted by HCPs, and is suitable for inpatient diabetes management.

Study protocol for assessing the user acceptance, safety and efficacy of a tablet-based workflow and decision support system with incorporated basal insulin algorithm for glycaemic management in participants with type 2 diabetes receiving home health care: A single-centre, open-label, uncontrolled proof-of-concept study

Introduction

Diabetes management can be especially complex for older adults who receive health care at home. Thus, international guidelines recommend basal-insulin regimens due to simpler handling and low hypoglycaemia risk. A basal-insulin algorithm (including basal-plus) was developed to also include participant's health status and subsequently implemented into a tablet-based workflow and decision support system, GlucoTab@MobileCare. This study protocol describes a proof-of-concept study to investigate user acceptance, safety and efficacy of the GlucoTab@MobileCare system in participants receiving home health care.

Methods

The open-label, single-centre, uncontrolled study will recruit a maximum of ten participants with insulin treated type-2-diabetes (age ≥18 years) who receive home health care. During a three month study period participants will receive basal- or basal-plus-insulin therapy once daily as suggested by the GlucoTab@MobileCare system. Statistical analysis will be conducted on an intention-to-treat basis. The primary endpoint is the percentage of tasks (BG measurements, insulin dose calculations, insulin injections) that were performed according to GlucoTab@MobileCare suggestions relative to the total of suggested tasks. Secondary endpoints include user acceptance, safety and efficacy parameters. The study was approved by the ethics committee and regulatory authorities. Before obtaining written informed consent, all participants will receive oral and written information about all aspects of the study. Results will be published in a peer-reviewed journal and at diabetes and geriatric conferences.

Discussion

Potential implications may be improved quality and safety of basal-insulin therapy in older adults as well as support for health-care-providers in daily routine including evidence-based knowledge.

Trial registration

German Clinical Trials Register (DRKS00015059);

Development of a Protocol for Automated Glucose Measurement Transmission Used in Clinical Decision Support Systems Based on the Continua Design Guidelines

BACKGROUND

A fast and accurate data transmission from glucose meter to clinical decision support systems (CDSSs) is crucial for the management of type 2 diabetes mellitus since almost all therapeutic interventions are derived from glucose measurements.

OBJECTIVES

Aim was to develop a prototype of an automated glucose measurement transmission protocol based on the Continua Design Guidelines and to embed the protocol into a CDSS used by healthcare professionals.

METHODS

A literature and market research was performed to analyze the state-of-the-art and thereupon develop, integrate and validate an automated glucose measurement transmission protocol in an iterative process.

RESULTS

Findings from literature and market research guided towards the development of a standardized glucose measurement transmission protocol using a middleware. The interface description to communicate with the glucose meter was illustrated and embedded into a CDSS.

CONCLUSION

A prototype of an interoperable transmission of glucose measurements was developed and implemented in a CDSS presenting a promising way to reduce medication errors and improve user satisfaction.

A toolbox to improve algorithms for insulin-dosing decision support

BACKGROUND

Standardized insulin order sets for subcutaneous basal-bolus insulin therapy are recommended by clinical guidelines for the inpatient management of diabetes. The algorithm based GlucoTab system electronically assists health care personnel by supporting clinical workflow and providing insulin-dose suggestions.

OBJECTIVE

To develop a toolbox for improving clinical decision-support algorithms.

METHODS

The toolbox has three main components. 1) Data preparation: Data from several heterogeneous sources is extracted, cleaned and stored in a uniform data format. 2) Simulation: The effects of algorithm modifications are estimated by simulating treatment workflows based on real data from clinical trials. 3) ANALYSIS: Algorithm performance is measured, analyzed and simulated by using data from three clinical trials with a total of 166 patients.

RESULTS

Use of the toolbox led to algorithm improvements as well as the detection of potential individualized subgroup-specific algorithms.

CONCLUSION

These results are a first step towards individualized algorithm modifications for specific patient subgroups.

Information systems for administration, clinical documentation and quality assurance in an Austrian disease management programme

5.9% of the Austrian population is affected by diabetes mellitus. Disease Management is a structured treatment approach that is suitable for application to the diabetes mellitus area and often is supported by information technology. This article describes the information systems developed and implemented in the Austrian disease management programme for type 2 diabetes. Several workflows for administration as well as for clinical documentation have been implemented utilizing the Austrian e-Health infrastructure. De-identified clinical data is available for creating feedback reports for providers and programme evaluation.

On-the-fly form generation and on-line metadata configuration--a clinical data management Web infrastructure in Java

In this paper we describe the approach to build a web-based clinical data management infrastructure on top of an entity-attribute-value (EAV) database which provides for flexible definition and extension of clinical data sets as well as efficient data handling and high performance query execution. A "mixed" EAV implementation provides a flexible and configurable data repository and at the same time utilizes the performance advantages of conventional database tables for rarely changing data structures. A dynamically configurable data dictionary contains further information for data validation. The online user interface can also be assembled dynamically. A data transfer object which encapsulates data together with all required metadata is populated by the backend and directly used to dynamically render frontend forms and handle incoming data. The "mixed" EAV model enables flexible definition and modification of clinical data sets while reducing performance drawbacks of pure EAV implementations to a minimum. The system currently is in use in an electronic patient record with focus on flexibility and a quality management application (www.healthgate.at) with high performance requirements.

Client-server environment for high-performance gene expression data analysis

SUMMARY

We have developed a platform independent, flexible and scalable Java environment for high-performance large-scale gene expression data analysis, which integrates various computational intensive hierarchical and non-hierarchical clustering algorithms. The environment includes a powerful client for data preparation and results visualization, an application server for computation and an additional administration tool. The package is available free of charge for academic and non-profit institutions.