Patient perspectives on personalized glucose advisory systems for type 1 diabetes management

Patient experiences of continuous glucose monitoring and sensor-augmented insulin pump therapy for diabetes: A systematic review of qualitative studies

AIMS

Blood glucose control is central to the management of diabetes, and continuous glucose monitoring (CGM) improves glycemic control. We aimed to describe the perspectives of people with diabetes using CGM.

MATERIALS AND METHODS

We performed a systematic review of qualitative studies.

RESULTS

Fifty-four studies involving 1845 participants were included. Six themes were identified: gaining control and convenience (reducing pain and time, safeguarding against complications, achieving stricter glucose levels, and sharing responsibility with family); motivating self-management (fostering ownership, and increasing awareness of glycemic control); providing reassurance and freedom (attaining peace of mind, and restoring social participation); developing confidence (encouraged by the endorsement of others, gaining operational skills, customizing settings for ease of use, and trust in the device); burdened with device complexities (bewildered by unfamiliar technology, reluctant to rely on algorithms, overwhelmed by data, frustrated with malfunctioning and inaccuracy, distressed by alerts, and bulkiness of machines interfering with lifestyle); and excluded by barriers to access (constrained by cost, lack of suppliers).

CONCLUSIONS

CGM can improve self-management and confidence in patients managing diabetes. However, the technical issues, uncertainty in readings, and cost may limit the uptake. Education and training from the health professionals may help to reduce the practical and psychological burden for better patient outcomes.

Automated digital counselling with social network support as a novel intervention for patients with heart failure: protocol for randomised controlled trial

INTRODUCTION

Heart failure (HF) symptoms improve through self-care, for which adherence remains low among patients despite the provision of education for these behaviours by clinical teams. Open Access Digital Community Promoting Self-Care, Peer Support and Health Literacy (ODYSSEE-vCHAT) combines automated digital counselling with social network support to improve mortality and morbidity, engagement with self-care materials, and health-related quality of life.

METHODS AND ANALYSIS

Use of ODYSSEE-vCHAT via Internet-connected personal computer by 162 HF patients will be compared with a control condition over 22 months. The primary outcome is a composite index score of all-cause mortality, all-cause emergency department visits, and HF-related hospitalisation at trial completion. Secondary outcomes include individual components of the composite index, engagement with self-care materials, and patient-reported measures of physical and psychosocial well-being, disease management, health literacy, and substance use. Patients are recruited from tertiary care hospitals in Toronto, Canada and randomised on a 1:1 ratio to both arms of the trial. Online assessments occur at baseline (t=0), months 4, 8 and 12, and trial completion. Ordinal logistic regression analyses and generalised linear models will evaluate primary and secondary outcomes.

ETHICS AND DISSEMINATION

The trial has been approved by the research ethics boards at the University Health Network (20-5960), Sunnybrook Hospital (5117), and Mount Sinai Hospital (21-022-E). Informed consent of eligible patients occurs in person or online. Findings will be shared with key stakeholders and the public. Results will allow for the preparation of a Canada-wide phase III trial to evaluate the efficacy of ODYSSEE-vCHAT in improving clinical outcomes and raising the standard of outpatient care.

TRIAL REGISTRATION NUMBER

NCT04966104.

Parents' experiences of using a hybrid closed-loop system (CamAPS FX) to care for a very young child with type 1 diabetes: Qualitative study

AIMS

To explore parents' experiences of using a hybrid closed-loop system (CamAPS FX) when caring for a very young child (aged 1-7 years) with type 1 diabetes.

METHODS

Interviews with n = 33 parents of 30 children who used the system during a randomised controlled trial. Data analysis used a descriptive thematic approach.

RESULTS

While some parents were initially reticent about handing control to the system, all reported clinical benefits to using the technology, having to do less diabetes-related work and needing less clinical input over time. Parents welcomed opportunities to enhance the system's efficacy (using Ease-off and Boost functions) as required. Parents described how the system's automated glucose control facilitated more normality, including sleeping better, worrying less about their child, and feeling more confident and able to outsource care. Parents also described more normality for the child (alongside better sleep, mood and concentration, and lessened distress) and siblings. Parents liked being able to administer insulin using a smartphone, but suggested refinements to device size and functionality.

CONCLUSIONS

Using a hybrid closed-loop system in very young children can facilitate greater normality and may result in a lessened demand for health professionals' input. Systems may need to be customised for very young children.

Trust in hybrid closed loop among people with diabetes: Perspectives of experienced system users

Automated closed loop systems will greatly change type 1 diabetes management; user trust will be essential for acceptance of this new technology. This qualitative study explored trust in 32 individuals following a hybrid closed loop trial. Participants described how context-, system-, and person-level factors influenced their trust in the system. Participants attempted to override the system when they lacked trust, while trusting the system decreased self-management burdens and decreased stress. Findings highlight considerations for fostering trust in closed loop systems. Systems may be able to engage users by offering varying levels of controls to match trust preferences.

Cognitions Associated With Hypoglycemia Awareness Status and Severe Hypoglycemia Experience in Adults With Type 1 Diabetes

OBJECTIVE

Impaired awareness of hypoglycemia (IAH) and recurrent severe hypoglycemia (RSH) remain problematic for people with type 1 diabetes (T1D), despite major therapeutic advances. We explored beliefs around hypo- and hyperglycemia in adults with T1D with, and without, IAH and RSH.

RESEARCH DESIGN AND METHODS

A cross-sectional U.S. multicenter survey included Attitudes to Awareness of Hypoglycemia (A2A; a 19-item questionnaire concerning beliefs about hypoglycemia), the Gold score (single item: awareness of hypoglycemia), and a question about severe hypoglycemia over the preceding year. The survey was emailed to 6,200 adult participants of the annual T1D Exchange clinic registry data collection. A2A data were subjected to principal component analysis with varimax rotation.

RESULTS

Among 1,978 respondents (response rate 32%), 61.7% were women, mean ± SD age was 39.6 ± 16.3 years, and T1D duration was 23.1 ± 13.8 years. Thirty-seven percent reported IAH, 16% RSH, and 9% both. A2A items segregated into three factors, differently distributed by hypoglycemia experience. Respondents with IAH or RSH expressed appropriate concern about hypoglycemia, but those with IAH were more likely to prioritize hyperglycemia concerns than those with intact awareness (P = 0.002). Those with RSH showed greater normalization of asymptomatic hypoglycemia than those without (P = 0.019) and trended toward prioritizing hyperglycemia concerns (P = 0.097), driven by those with both IAH and RSH.

CONCLUSIONS

Adults with T1D with IAH and RSH report specific cognitions about hypoglycemia and hyperglycemia, which may act as barriers to hypoglycemia avoidance and recovery of awareness. These may be modifiable and present a target for enhancing engagement of vulnerable people with strategies to avoid future hypoglycemia.

Participants' Experiences of, and Views About, Daytime Use of a Day-and-Night Hybrid Closed-Loop System in Real Life Settings: Longitudinal Qualitative Study

OBJECTIVE

To explore individuals' experiences of daytime use of a day-and-night hybrid closed-loop system, their information and support needs, and their views about how future systems could be improved.

RESEARCH DESIGN AND METHODS

Twenty-four adults, adolescents, and parents were interviewed before using a hybrid day-and-night closed-loop system and 3 months later, data were analyzed thematically.

RESULTS

Participants praised the closed loop's ability to respond to high and low blood glucose in ways which extended beyond their own capabilities and to act as a safety net and mop up errors, such as when a mealtime bolus was forgotten or unplanned activity was undertaken. Participants also described feeling less burdened by diabetes as a consequence and more able to lead flexible, spontaneous lives. Contrary to their initial expectations, and after trust in the system had been established, most individuals wanted opportunities to collaborate with the closed loop to optimize its effectiveness. Such individuals expressed a need to communicate information, such as when routines changed or to indicate different intensities of physical activity. While individuals valued frequent contact with staff in the initial month of use, most felt that their long-term support needs would be no greater than when using an insulin pump.

CONCLUSIONS

While participants reported substantial benefits to using the closed loop during the day, they also identified ways in which the technology could be refined and education and training tailored to optimize effective use. Our findings suggest that mainstreaming this technology will not necessarily lead to increased demands on clinical staff.

Impact of New Technologies for Middle-Aged and Older Patients: In-Depth Interviews With Type 2 Diabetes Patients Using Continuous Glucose Monitoring

Background

Continuous glucose monitoring (CGM) uses subcutaneous sensors and records the average interstitial sensor current every 5 min in the recorder; data are subsequently exported to a computer 4 to 7 days later when calibration with self-measured blood glucose is made retrospectively. How middle-aged and older patients perceive the added technology intervention is not clear.

Objective

The study aimed to understand the factors associated with the adoption of new technology in diabetes care, to understand the feelings and behaviors while using it, and to determine the changes in attitudes and behavior after completing the use of the new technology at the 3-month follow-up.

Methods

Middle-aged and older type 2 diabetes patients who had received professional continuous glucose monitoring (iPro 2 [Medtronic]) were invited for semistructured in-depth interviews on the day of the CGM sensor removal and at 3 months after CGM-based counseling. A phenomenography approach was used to analyze the interview data.

Results

A total of 20 type 2 diabetes patients (aged 53 to 72 years, 13 males and 7 females, 4 to 40 years duration of diabetes, mean glycated hemoglobin 8.54% [SD 0.71%]) completed 2 sections of semistructured in-depth interviews. Physician guidance and participant motivation toward problem solving were found to be factors associated with adoption of the device. Participants indicated that technology can be a reminder, a supervisor, and a visualizer of blood glucose, all of which are helpful for disease management. However, CGM is somewhat inconvenient, and some participants also reported that the provision of this new technology might be a hint of disease progression. There was a higher percentage of women compared with men who reported that CGM can be a reminder or a supervisor to help them with diet control.

Conclusions

Physician guidance and participants’ degree of motivation are keys to adopting new technology in the case of middle-aged and older adults. Although the CGM sensor may cause inconvenience to patients on their limited body movement when wearing the device, it is helpful for diet control and is an effective behavioral modification tool that offers support, especially in the case of women.

Modeling of Diabetes and Its Clinical Impact

Understanding all aspects of diabetes treatment is hindered by the complexity of this chronic disease and its multifaceted complications and comorbidities, including social and financial impacts. In vivo studies as well as clinical trials provided invaluable information for unraveling not only metabolic processes but also risk estimations of, for example, complications. These approaches are often time- and cost-consuming and have frequently been supported by simulation models. Simulation models provide the opportunity to investigate diabetes treatment from additional viewpoints and with alternative objectives. This review presents selected models focusing either on metabolic processes or risk estimations and financial outcomes to provide a basic insight into this complex subject. It also discusses opportunities and challenges of modeling diabetes.

Hypoglycaemia in type 1 diabetes: technological treatments, their limitations and the place of psychology

Advances in technology allowing improved insulin delivery and glucose monitoring can significantly reduce the burden of hypoglycaemia when used appropriately. However, limitations of the current technology, and the skills, commitment and motivation required to use them, mean that it does not work for all people. Education and informed professional support are key to success. In the context of problematic hypoglycaemia, data suggest that newer technology has lower efficacy and uptake in those with most need. Identifying the causes of hypoglycaemia and understanding some of the underlying behavioural drivers may prove useful and psycho-educational strategies may be effective in selected individuals. Ultimately, as in many spheres of medicine, successful management of problematic hypoglycaemia depends upon matching the right treatment to the right individual.

Human Factors and Data Logging Processes With the Use of Advanced Technology for Adults With Type 1 Diabetes: Systematic Integrative Review

Background

People with type 1 diabetes (T1D) undertake self-management to prevent short and long-term complications. Advanced technology potentially supports such activities but requires consideration of psychological and behavioral constructs and usability issues. Economic factors and health care provider capacity influence access and uptake of advanced technology. Previous reviews have focused upon clinical outcomes or were descriptive or have synthesized studies on adults with those on children and young people where human factors are different.

Objective

This review described and examined the relationship between human factors and adherence with technology for data logging processes in adults with T1D.

Methods

A systematic literature search was undertaken by using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Quality appraisal was undertaken and data were abstracted and categorized into the themes that underpinned the human factor constructs that were examined.

Results

A total of 18 studies were included. A total of 6 constructs emerged from the data analysis: the relationship between adherence to data logging and measurable outcomes; satisfaction with the transition to advanced technology for self-management; use of advanced technology and time spent on diabetes-related activities; strategies to mediate the complexities of diabetes and the use of advanced technology; cognition in the wild; and meanings, views, and perspectives from the users of technology.

Conclusions

Increased treatment satisfaction was found on transition from traditional to advanced technology use—insulin pump and continuous glucose monitoring (CGM); the most significant factor was when blood glucose levels were consistently <7.00 mmol/L (P ≤.01). Participants spent considerable time on their diabetes self-care. Logging of data was positively correlated with increasing age when using an app that provided meaningful feedback (regression coefficient=55.8 recordings/year; P ≤.01). There were benefits of CGM for older people in mediating complexities and fears of hypoglycemia with significant differences in well-being (P ≤.001).

Qualitative studies explored the contextual use and uptake of technology. The results suggested frustrations with CGM, continuous subcutaneous insulin infusion, calibration of devices, and alarms. Furthermore implications for “body image” and the way in which “significant others” impacted on the behavior and attitude of the individual toward technology use. There were wide variations in the normal use of and interaction with technology across a continuum of sociocultural contexts, which has implications for the way in which future technologies should be designed.

Quantitative studies were limited by small sample sizes, making it difficult to generalize findings to other contexts. This was further limited by a sample that was predominantly white, well-controlled, and engaged with self-care. The use of critical appraisal frameworks demonstrated where research into human factors and data logging processes of individuals could be improved. This included engaging people in the design of the technology, especially hard-to-reach or marginalized groups.

Clinical Impact of Blood Glucose Monitoring Accuracy: An In-Silico Study

BACKGROUND

Patients with diabetes rely on blood glucose (BG) monitoring devices to manage their condition. As some self-monitoring devices are becoming more and more accurate, it becomes critical to understand the relationship between system accuracy and clinical outcomes, and the potential benefits of analytical accuracy.

METHODS

We conducted a 30-day in-silico study in type 1 diabetes mellitus (T1DM) patients using continuous subcutaneous insulin infusion (CSII) therapy and a variety of BG meters, using the FDA-approved University of Virginia (UVA)/Padova Type 1 Simulator. We used simulated meter models derived from the published characteristics of 43 commercial meters. By controlling random events in each parallel run, we isolated the differences in clinical performance that are directly associated with the meter characteristics.

RESULTS

A meter's systematic bias has a significant and inverse effect on HbA1c ( P < .01), while also affecting the number of severe hypoglycemia events. On the other hand, error, defined as the fraction of measurements beyond 5% of the true value, is a predictor of severe hypoglycemia events ( P < .01), but in the absence of bias has a nonsignificant effect on average glycemia (HbA1c). Both bias and error have significant effects on total daily insulin (TDI) and the number of necessary glucose measurements per day ( P < .01). Furthermore, these relationships can be accurately modeled using linear regression on meter bias and error.

CONCLUSIONS

Two components of meter accuracy, bias and error, clearly affect clinical outcomes. While error has little effect on HbA1c, it tends to increase episodes of severe hypoglycemia. Meter bias has significant effects on all considered metrics: a positive systemic bias will reduce HbA1c, but increase the number of severe hypoglycemia attacks, TDI use, and number of fingersticks per day.

Improving the Safety and Functionality of an Artificial Pancreas System for Use in Younger Children: Input from Parents and Physicians

BACKGROUND

Artificial pancreas (AP) systems have initially been designed for and tested in teens and adults, but there is evidence that an AP system with additional support and safety systems could greatly benefit younger children with type 1 diabetes (T1D).

SUBJECTS AND METHODS

Five pediatric endocrinologists and 15 parents of children aged 5-8 years with T1D participated in a total of four focus groups. Focus groups investigated current diabetes technology use and acceptance, as well as possible modifications to the current adult AP system, which would allow for safe and successful use in younger children. Modifications discussed include child-specific functionality for input tasks, safety features, and monitoring capabilities.

RESULTS

Participant suggestions included the following: passcodes for differential access to AP features by parents, ancillary caregivers, and the child; preset early, intermediate, and advanced child access categories; maximal customization for general and alarm settings; simplified meal screens utilizing the AP' corrective blood glucose (BG) ability; automated exercise mode; spoken and dictated messaging capabilities; emergency contacts; treatment instructions for the child and caregiver; remote monitoring website and application; animated continuous glucose monitor BG trace; gamification, such as rewarding diabetes-friendly behaviors; and comprehensive training of all individuals involved in the child's diabetes care.

CONCLUSION

Parents and physicians were eager for AP applications to be available for younger children, but stressed that a modified system could better serve this group's needs for safety and improved diabetes-related communication. The diverse and emerging needs of 5-8-year olds require flexible and customizable systems for T1D management.

Effect of BGM Accuracy on the Clinical Performance of CGM: An In-Silico Study

BACKGROUND

Standard management of type 1 diabetes (T1D) relies on blood glucose monitoring based on a range of technologies from self-monitoring of blood glucose (BGM) to continuous glucose monitoring (CGM). Even as CGM technology matures, patients utilize BGM for calibration and dosing. The question of how the accuracy of both technologies interact is still not well understood.

METHODS

We use a recently developed data-driven simulation approach to characterize the relationship between CGM and BGM accuracy especially how BGM accuracy impacts CGM performance in four different use cases with increasing levels of reliance on twice daily calibrated CGM. Simulations are used to estimate clinical outcomes and isolate CGM and BGM accuracy characteristics that drive performance.

RESULTS

Our results indicate that meter (BGM) accuracy, and more specifically systematic positive or negative bias, has a significant effect on clinical performance (HbA1c and severe hypoglycemia events) in all use-cases generated for twice daily calibrated CGMs. Moreover, CGM sensor accuracy can amplify or mitigate, but not eliminate these effects.

CONCLUSION

As a system, BGM and CGM and their mode of use (use-case) interact to determine clinical outcomes. Clinical outcomes (eg, HbA1c, severe hypoglycemia, time in range) can be closely approximated by linear relationships with two BGM accuracy characteristics, namely error and bias. In turn, the coefficients of this linear relationship are determined by the use-case and by CGM accuracy (MARD).

The First Use of Bolus Calculator With Speech Analyzer

BACKGROUND

The insulin therapy in type 1 diabetes involves a wide array of restrictions in patients and their families. One of those is a difficulty in estimation of the insulin dose programmed for each meal. The purpose of the study is an assessment of functionalities related to the expert system VoiceDiab-a calculator of meal boluses.

METHODS

The sample group composed of 54 patients, aged 3-52, all suffering from type 1 diabetes, treated with the insulin pump, taking part in the clinics RCT (for adults and a pediatrician), with a randomized allocation to a surveyed group and cross-over. The research methodology was based upon questionnaires and open-ended questions.

RESULTS

40% of respondents recognized the application's usefulness as high (18 of 47), giving it 10 points, and easy to use (70%). Disadvantages of this app comprised lack of some products in the application database (n = 23), troubles with the mobile range ( n = 4), and no option of a manual data input for processing purposes (n = 23). Advantages, that have been mentioned the most frequently included facilitation of measurements (n = 7), enhanced life quality of the patient (n = 8), and a guarantee of prompt and thorough calculations (n = 22). Of the surveyed individuals, 50% reached their diet, while 100% gave a top grade to the application, claiming it had contributed to a more efficient metabolic control.

CONCLUSION

The pilot scheme of the expert system VoiceDiab has potential to become an application, facilitating dosing of the meal insulin and improving the comfort and safety of insulin administering. However, it needs to be modified, as mentioned by the users who have tested the system.

Qualitative assessment of user experiences of a novel smart phone application designed to support flexible intensive insulin therapy in type 1 diabetes

Background

Modern flexible multiple daily injection (MDI) therapy requires people with diabetes to manage complex mathematical calculations to determine insulin doses on a day to day basis. Automated bolus calculators assist with these calculations, add additional functionality to protect against hypoglycaemia and enhance the record keeping process, however uptake and use depends on the devices meeting the needs of the user. We aimed to obtain user feedback on the usability of a mobile phone bolus calculator application in adults with T1DM to inform future development of mobile phone diabetes support applications.

Methods

Adults with T1DM who had previously received education in flexible MDI therapy were invited to participate. Eligible respondents attended app education and one month later participated in a focus group to provide feedback on the features of the app in relation to usability for patient-based flexible MDI and future app development.

Results

Seven adults participated in the app training and follow up interview. App features that support dose adjustment to reduce hypoglycaemia risk and features that enable greater efficiency in dose calculation, record keeping and report generation were highly valued.

Conclusions

Adults who are self managing flexible MDI found the Rapidcalc mobile phone app to be a useful self-management tool and additional features to further improve usability, such as connectivity with BG meter and food databases, shortcut options to economise data entry and web based storage of data, were identified. Further work is needed to ascertain specific features and benefit for those with lower health literacy.

Assessing Insulin Delivery Device Satisfaction in Patients with Type 1 and Type 2 Diabetes

Over the past several decades, insulin treatment has changed drastically, not only with the development of further insulin analogs but also with the introduction of novel insulin delivery devices such as pumps and pens. In addition, adjunct devices such as continuous glucose monitors and sensor-augmented pumps have become increasingly used in clinical care, increasing the volume of information available to patients and providers. However, with the development of new devices it has become clear that along with the many benefits of these advances, the use of these devices can also present a burden to people with diabetes. For example, some patients report being overwhelmed by too much data when using continuous glucose monitors. Furthermore, there are concerns regarding the accuracy of some of these new devices, particularly for glucose monitoring. As a result, some patients may choose not to use available devices, despite the recognized benefits. Therefore, it is critical to understand how the various insulin delivery devices available currently and in the future affect patients in terms of their diabetes management and perceived burdens and to understand which patient characteristics may predict a lack of satisfaction with these devices. This critical gap in our knowledge is addressed in an article in this issue of the journal through the development of a questionnaire that allows for a better understanding of the impact of insulin delivery devices on quality of life and diabetes management among both type 1 diabetes and insulin-dependent type 2 diabetes patients. The novelty, as well as limitations, of this new instrument for the assessment of insulin delivery device satisfaction are discussed.

Assessing sensor accuracy for non-adjunct use of continuous glucose monitoring

BACKGROUND

The level of continuous glucose monitoring (CGM) accuracy needed for insulin dosing using sensor values (i.e., the level of accuracy permitting non-adjunct CGM use) is a topic of ongoing debate. Assessment of this level in clinical experiments is virtually impossible because the magnitude of CGM errors cannot be manipulated and related prospectively to clinical outcomes.

MATERIALS AND METHODS

A combination of archival data (parallel CGM, insulin pump, self-monitoring of blood glucose [SMBG] records, and meals for 56 pump users with type 1 diabetes) and in silico experiments was used to "replay" real-life treatment scenarios and relate sensor error to glycemic outcomes. Nominal blood glucose (BG) traces were extracted using a mathematical model, yielding 2,082 BG segments each initiated by insulin bolus and confirmed by SMBG. These segments were replayed at seven sensor accuracy levels (mean absolute relative differences [MARDs] of 3-22%) testing six scenarios: insulin dosing using sensor values, threshold, and predictive alarms, each without or with considering CGM trend arrows.

RESULTS

In all six scenarios, the occurrence of hypoglycemia (frequency of BG levels ≤50 mg/dL and BG levels ≤39 mg/dL) increased with sensor error, displaying an abrupt slope change at MARD =10%. Similarly, hyperglycemia (frequency of BG levels ≥250 mg/dL and BG levels ≥400 mg/dL) increased and displayed an abrupt slope change at MARD=10%. When added to insulin dosing decisions, information from CGM trend arrows, threshold, and predictive alarms resulted in improvement in average glycemia by 1.86, 8.17, and 8.88 mg/dL, respectively.

CONCLUSIONS

Using CGM for insulin dosing decisions is feasible below a certain level of sensor error, estimated in silico at MARD=10%. In our experiments, further accuracy improvement did not contribute substantively to better glycemic outcomes.

Artificial pancreas (AP) clinical trial participants' acceptance of future AP technology

BACKGROUND

Artificial pancreas (AP) systems are currently an active field of diabetes research. This pilot study examined the attitudes of AP clinical trial participants toward future acceptance of the technology, having gained firsthand experience.

SUBJECTS AND METHODS

After possible influencers of AP technology adoption were considered, a 34-question questionnaire was developed. The survey assessed current treatment satisfaction, dimensions of clinical trial participant motivation, and variables of the technology acceptance model (TAM). Forty-seven subjects were contacted to complete the survey. The reliability of the survey scales was tested using Cronbach's α. The relationship of the factors to the likelihood of AP technology adoption was explored using regression analysis.

RESULTS

Thirty-six subjects (76.6%) completed the survey. Of the respondents, 86.1% were either highly likely or likely to adopt the technology once available. Reliability analysis of the survey dimensions revealed good internal consistency, with scores of >0.7 for current treatment satisfaction, convenience (motivation), personal health benefit (motivation), perceived ease of use (TAM), and perceived usefulness (TAM). Linear modeling showed that future acceptance of the AP was significantly associated with TAM and the motivation variables of convenience plus the individual item benefit to others (R(2)=0.26, P=0.05). When insulin pump and continuous glucose monitor use were added, the model significance improved (R(2)=0.37, P=0.02).

CONCLUSIONS

This pilot study demonstrated that individuals with direct AP technology experience expressed high likelihood of future acceptance. Results support the factors of personal benefit, convenience, perceived usefulness, and perceived ease of use as reliable scales that suggest system adoption in this highly motivated patient population.

Design of the Glucose Rate Increase Detector: A Meal Detection Module for the Health Monitoring System

The Glucose Rate Increase Detector (GRID), a module of the Health Monitoring System (HMS), has been designed to operate in parallel to the glucose controller to detect meal events and safely trigger a meal bolus. The GRID algorithm was tuned on clinical data with 40-70 g CHO meals and tested on simulation data with 50-100 g CHO meals. Active closed- and open-loop protocols were executed in silico with various treatments, including automatic boluses based on a 75 g CHO meal and boluses based on simulated user input of meal size. An optional function was used to reduce the recommended bolus using recent insulin and glucose history. For closed-loop control of a 3-meal scenario (50, 75, and 100 g CHO), the GRID improved median time in the 80-180 mg/dL range by 17% and in the >180 range by 14% over unannounced meals, using an automatic bolus for a 75 g CHO meal at detection. Under open-loop control of a 75 g CHO meal, the GRID shifted the median glucose peak down by 73 mg/dL and earlier by 120 min and reduced the time >180 mg/dL by 57% over a missed-meal bolus scenario, using a full meal bolus at detection. The GRID improved closed-loop control in the presence of large meals, without increasing late postprandial hypoglycemia. Users of basal-bolus therapy could also benefit from GRID as a safety alert for missed meal corrections.

Evaluation of a blood glucose monitoring system with automatic high- and low-pattern recognition software in insulin-using patients: pattern detection and patient-reported insights

BACKGROUND

This study aimed to evaluate the performance of a glucose pattern recognition tool incorporated in a blood glucose monitoring system (BGMS) and its association with clinical measures, and to assess user perception and understanding of the pattern messages they receive.

METHODS

Participants had type 1 or type 2 diabetes mellitus and were self-adjusting insulin doses for ≥1 year. During a 4-week home testing period, participants performed ≥6 daily self-tests, adjusted their insulin regimen based on BGMS results, and recorded pattern messages in the logbook. Participants reflected on usability of the pattern tool in a questionnaire.

RESULTS

Study participants (n = 101) received a mean ± standard deviation of 4.5 ± 1.9 pattern messages per week (3.6 ± 1.8 high glucose patterns and 0.9 ± 1.3 low glucose patterns). Most received ≥1 high (96.5%) and/or ≥1 low (46.0%) pattern message per week. The average number of high- and low-pattern messages per week was associated with higher and lower, respectively, baseline hemoglobin A1c (p &lt; .01) and fasting plasma glucose (p &lt; .05). Participants found high- and low-pattern messages clear and easy to understand (84.2% and 83.2%, respectively) and considered the frequency of low (82.0%) and high (63.4%) pattern messages about right. Overall, 71.3% of participants indicated they preferred to use a meter with pattern messages.

CONCLUSIONS

The on-device Pattern tool identified meaningful blood glucose patterns, highlighting potential opportunities for improving glycemic control in patients who self-adjust their insulin.