Wouter T. Gude

Diabetes patients' experiences with the implementation of insulin therapy and their perceptions of computer-assisted self-management systems for insulin therapy.

Background Computer-assisted decision support is an emerging modality to assist patients with type 2 diabetes mellitus (T2DM) in insulin self-titration (ie, self-adjusting insulin dose according to daily blood glucose levels). Computer-assisted insulin self-titration systems mainly focus on helping patients overcome barriers related to the cognitive components of insulin titration. Yet other (eg, psychological or physical) barriers could still impede effective use of such systems. Objective Our primary aim was to identify experiences with and barriers to self-monitoring of blood glucose, insulin injection, and insulin titration among patients with T2DM. Our research team developed a computer-assisted insulin self-titration system, called PANDIT. The secondary aim of this study was to evaluate patients’ perceptions of computer-assisted insulin self-titration. We included patients who used PANDIT in a 4-week pilot study as well as patients who had never used such a system. Methods In-depth, semi-structured interviews were conducted individually with patients on insulin therapy who were randomly recruited from a university hospital and surrounding general practices in the Netherlands. The interviews were transcribed verbatim and analyzed qualitatively. To classify the textual remarks, we created a codebook during the analysis, in a bottom-up and iterative fashion. To support examination of the final coded data, we used three theories from the field of health psychology and the integrated model of user satisfaction and technology acceptance by Wixom and Todd. Results When starting insulin therapy, some patients feared a lifelong commitment to insulin therapy and disease progression. Also, many barriers arose when implementing insulin therapy (eg, some patients were embarrassed to inject insulin in public). Furthermore, patients had difficulties increasing the insulin dose because they fear hypoglycemia, they associate higher insulin doses with disease progression, and some were ignorant of treatment targets. Patients who never used a computer-assisted insulin self-titration system felt they had enough knowledge to know when their insulin should be adjusted, but still believed that the system advice would be useful to confirm their reasoning. Furthermore, the time and effort saved with automated insulin advice was considered an advantage. Patients who had used PANDIT found the system useful if their glycemic regulation improved. Nevertheless, for some patients, the absence of personal contact with their caregiver was a drawback. While guidelines state that adjustment of basal insulin dose based on fasting plasma glucose values is sufficient, both patients who had and those who had not used PANDIT felt that such a system should take more patient data into consideration, such as lifestyle and diet factors. Conclusions Patients encounter multiple obstacles when implementing insulin therapy. Computer-assisted insulin self-titration can increase patient awareness of treatment targets and increase their confidence in self-adjusting the insulin dose. Nevertheless, some barriers may still exist when using computer-assisted titration systems and these systems could also introduce new barriers.

Informatics for Health 2017: Advancing both science and practice

Introduction The Informatics for Health congress, 24-26 April 2017, in Manchester, UK, brought together the Medical Informatics Europe (MIE) conference and the Farr Institute International Conference. This special issue of the Journal of Innovation in Health Informatics contains 113 presentation abstracts and 149 poster abstracts from the congress. Discussion The twin programmes of “Big Data” and “Digital Health” are not always joined up by coherent policy and investment priorities. Substantial global investment in health IT and data science has led to sound progress but highly variable outcomes. Society needs an approach that brings together the science and the practice of health informatics. The goal is multi-level Learning Health Systems that consume and intelligently act upon both patient data and organizational intervention outcomes. Conclusions Informatics for Health 2017 demonstrated the art of the possible, seen in the breadth and depth of our contributions. We call upon policy makers, research funders and programme leaders to learn from this joined-up approach.

SMASH! The Salford medication safety dashboard

Background Patient safety is vital to well-functioning health systems. A key component is safe prescribing, particularly in primary care where most medications are prescribed. Previous research has demonstrated that the number of patients exposed to potentially hazardous prescribing can be reduced by interrogating the electronic health record (EHR) database of general practices and providing feedback to general practitioners (GPs) in a pharmacist-led intervention. We aimed to develop and roll out an online dashboard application that delivers this audit and feedback intervention in a continuous fashion. Method Based on initial system requirements, we designed the dashboard’s user interface over three iterations with six GPs, seven pharmacists and a member of the public. Prescribing safety indicators from previous work were implemented in the dashboard. Pharmacists were trained to use the intervention and deliver it to general practices. Results A web-based electronic dashboard was developed and linked to shared care records in Salford, UK. The completed dashboard was deployed in all but one (n = 43) general practices in the region. By November 2017, 36 pharmacists had been trained in delivering the intervention to practices. There were 135 registered users of the dashboard, with an average of 91 user sessions a week. Conclusion We have developed and successfully rolled out of a complex, pharmacist-led dashboard intervention in Salford, UK. System usage statistics indicate broad and sustained uptake of the intervention. The use of systems that provide regularly updated audit information may be an important contributor towards medication safety in primary care.

Development of a Web-Based Quality Dashboard Including a Toolbox to Improve Pain Management in Dutch Intensive Care

Audit and feedback (A&F) is a common strategy to improve quality of care. Meta-analyses have indicated that A&F may be more effective in realizing desired change when baseline performance is low, it is delivered by a supervisor or colleague, it is provided frequently and in a timely manner, it is delivered in both verbal and written formats, and it includes specific targets and an action plan. However, there is little information to guide operationalization of these factors. Researchers have consequently called for A&F interventions featuring well-described and carefully justified components, with their theoretical rationale made explicit. This paper describes the rationale and development of a quality dashboard including an improvement toolbox for four previous developed pain indicators, guided by Control Theory.