Moving towards Sustainable Electronic Health Applications

Electronic healthcare applications, both web-based and mobile health (mHealth) provide new modalities for chronic disease. These tools allow patients to track their symptoms and help them manage their condition. The sustainability of these tools is often not considered during their development. To ensure these applications can be adopted and sustainable, where policy differs amongst states and provinces, we must present the benefits of our findings to highlight the justification for its development. For technology to be sustainable it has to utilize infrastructure that is secure, stable and to be agile so that it can be deployed quickly with minimal interruption to patients, family members and healthcare professionals

A novel method to derive personalized minimum viable recommendations for type 2 diabetes prevention based on counterfactual explanations

Despite the growing availability of artificial intelligence models for predicting type 2 diabetes, there is still a lack of personalized approaches to quantify minimum viable changes in biomarkers that may help reduce the individual risk of developing disease. The aim of this article is to develop a new method, based on counterfactual explanations, to generate personalized recommendations to reduce the one-year risk of type 2 diabetes. Ten routinely collected biomarkers extracted from Electronic Medical Records of 2791 patients at low risk and 2791 patients at high risk of type 2 diabetes were analyzed. Two regions characterizing the two classes of patients were estimated using a Support Vector Data Description classifier. Counterfactual explanations (i.e., minimal changes in input features able to change the risk class) were generated for patients at high risk and evaluated using performance metrics (availability, validity, actionability, similarity, and discriminative power) and a qualitative survey administered to seven expert clinicians. Results showed that, on average, the requested minimum viable changes implied a significant reduction of fasting blood sugar, systolic blood pressure, and triglycerides and a significant increase of high-density lipoprotein in patients at risk of diabetes. A significant reduction in body mass index was also recommended in most of the patients at risk, except in females without hypertension. In general, greater changes were recommended in hypertensive patients compared to non-hypertensive ones. The experts were overall satisfied with the proposed approach although in some cases the proposed recommendations were deemed insufficient to reduce the risk in a clinically meaningful way. Future research will focus on a larger set of biomarkers and different comorbidities, also incorporating clinical guidelines whenever possible. Development of additional mathematical and clinical validation approaches will also be of paramount importance

Evaluation of mobile apps for treatment of patients at risk of developing gestational diabetes

This study evaluates mobile apps using a theory-based evaluation framework to discover their applicability for patients at risk of gestational diabetes. This study assessed how well the existing mobile apps on the market meet the information and tracking needs of patients with gestational diabetes and evaluated the feasibility of how to integrate these apps into patient care. A search was conducted in the Apple iTunes and Google Play store for mobile apps that contained keywords related to the following concepts of nutrition: diet, tracking, diabetes, and pregnancy. Evaluation criteria were developed to assess the mobile apps on five dimensions. Overall, the apps scored well on education and information functions and scored poorly on engagement functions. There are few apps that provide comprehensive evidence-based educational content, tracking tools, and integration with electronic health records. This study demonstrates the need to develop apps that have comprehensive content, tracking tools, and ability to bidirectionally share data

Feasibility Assessment for Implementation of Heart Failure Clinical Caremaps using Electronic Medical Records in Primary Practice

Objectives: The primary aim of this project is to evaluate the impact and level of use of Electronic Medical Records (EMRs) by family physicians (FPs) specifically with respect to HF management. This study provides pilot work towards successful implementation of HF clinical caremaps in EMRs to support decision making for FPs. Methods: A survey questionnaire was sent to 207 FPs from which 42 (20%) replies were received. The survey included questions on demographic information of the FP's practice, specifics about HF patients and their management, EMR use and whether they have improved management in HF patients.   Results: Among the 42 FPs who responded, 39 (93%) practice in the urban area of Hamilton and each have over 10 confirmed HF patients at their family practices, supporting the need for proper management of HF at the primary care level. FPs expressed concerns about difficulty in treating HF preserved vs. systolic HF, in managing HF patients with renal insufficiency and difficulty in the use of beta blockers. There was no consensus on whether EMRs have helped in improving the management of HF patients. Conclusions: There is a perceived need for management tools which can be integrated into EMRs to provide decision making support for FPs in managing HF.  Tools such as caremaps may help provide optimal care in managing HF patients as per the Canadian Cardiovascular Society guidelines

Designing Disease-Specific mHealth Apps for Clinical Value

mHealth apps for patient use are promising but continue to face a plateau in usage. Current apps work for a limited segment of the patient population, i.e., those who enjoy tracking for intrinsic rewards. There are many opportunities to support patient care in between health care provider visits that are not currently being met for many diseases and patient types (personas). This is an area of great potential growth for mHealth apps and could contribute greatly to patient health and wellness. In this chapter, we propose a framework for how to think about the between-visit needs of patients that would motivate continued use of mhealth apps. We view the app design process from the following perspectives: 1) disease-specific needs, 2) non-disease specific needs, 3) behavioral theoretical aspects of app usage and 4) app-intrinsic usage motivators. Myasthenia gravis serves as the use case for illustrating these perspectives and how to use them in designing a disease-specific mHealth app

Principles and operational model for governing Diabetes Action Canada’s data repository for patient-oriented research

Diabetes Action Canada is developing a data repository andregistry of potential research participants to support research,QI, and service to improve diabetes care. Central to the repositoryare pseudonymised linkable electronic medical records (EMRs) from family practices that are participating in theCanadian Primary Care Sentinel Surveillance Network (CPCSSN).Publisher PD

Participatory governance over research in an academic research network : the case of Diabetes Action Canada

This work was supported by Diabetes Action Canada, which is funded, in part, through a Canadian Institutes of Health Research chronic disease network grant under the Strategy for Patient-Oriented Research (Funding Reference number: SCA 145101).Digital data generated in the course of clinical care are increasingly being leveraged for a wide range of secondary purposes. Researchers need to develop governance policies that can assure the public that their information is being used responsibly. Our aim was to develop a generalisable model for governance of research emanating from health data repositories that will invoke the trust of the patients and the healthcare professionals whose data are being accessed for health research. We developed our governance principles and processes through literature review and iterative consultation with key actors in the research network including: a data governance working group, the lead investigators and patient advisors. We then recruited persons to participate in the governing and advisory bodies. Our governance process is informed by eight principles: (1) transparency; (2) accountability; (3) follow rule of law; (4) integrity; (5) participation and inclusiveness; (6) impartiality and independence; (7) effectiveness, efficiency and responsiveness and (8) reflexivity and continuous quality improvement. We describe the rationale for these principles, as well as their connections to the subsequent policies and procedures we developed. We then describe the function of the Research Governing Committee, the majority of whom are either persons living with diabetes or physicians whose data are being used, and the patient and data provider advisory groups with whom they consult and communicate. In conclusion, we have developed a values-based information governance framework and process for Diabetes Action Canada that adds value over-and-above existing scientific and ethics review processes by adding a strong patient perspective and contextual integrity. This model is adaptable to other secure data repositories.Publisher PDFPeer reviewe

Using a data entry clerk to improve data quality in primary care electronic medical records: a pilot study

Background The quality of electronic medical record (EMR) data is known to be problematic; research on improving these data is needed. Objective The primary objective was to explore the impact of using a data entry clerk to improve data quality in primary care EMRs. The secondary objective was to evaluate the feasibility of implementing this intervention. Methods We used a before and after design for this pilot study. The participants were 13 community based family physicians and four allied health professionals in Toronto, Canada. Using queries programmed by a data manager, a data clerk was tasked with re-entering EMR information as coded or structured data for chronic obstructive pulmonary disease (COPD), smoking, specialist designations and interprofessional encounter headers. We measured data quality before and three to six months after the intervention. We evaluated feasibility by measuring acceptability to clinicians and workload for the clerk. Results After the intervention, coded COPD entries increased by 38% (P = 0.0001, 95% CI 23 to 51%); identifiable data on smoking categories increased by 27% (P = 0.0001, 95% CI 26 to 29%); referrals with specialist designations increased by 20% (P = 0.0001, 95% CI 16 to 22%); and identifiable interprofessional headers increased by 10% (P = 0.45, 95 CI _3 to 23%). Overall, the interventionwas rated as being at least moderately useful and moderately usable. The data entry clerk spent 127 hours restructuring data for 11 729 patients. Conclusions Utilising a data manager for queries and a data clerk to re-enter data led to improvements in EMR data quality. Clinicians found this approach to be acceptable