The impact of initiatives in education, self-management training, and computer-assisted self-care on outcomes in diabetes disease management

Assessing perceptions of nursing knowledge, attitudes, and practices in diabetes management within Chinese healthcare settings

Background

Effective management of diabetes mellitus (DM) involves comprehensive knowledge, attitudes, and practices (KAP) by nurses, which is essential for optimal patient care and aiding patients in their self-management of the condition.

Method

This survey evaluates nurses' self-assessed knowledge, attitudes, and practices (KAP) related to diabetes management, focusing on their perceptions of personnel expertise and care approaches. Using a stratified sampling method, the survey was disseminated across various online platforms from January 2023 to February 2024 within China, including WeChat and Sina Weibo. We employed binary logistic regression and Chi-square tests to explore the statistical correlates of KAP related to DM.

Results

A total of 4,011 nurses participated, revealing significant perceived knowledge deficiencies in specialized DM management areas, with only 34% (n = 1,360) proficient in current pharmacological treatments. Attitudinal assessments showed that 54% (n = 2,155) recognized the importance of cultural competence in dietary counseling. Practices were strong in routine glucose monitoring (96%, n = 3,851) but weaker in psychological support (68%, n = 2,736). Regression analysis indicated significant effects of experience on KAP, where nurses with 1-5 years of experience were more likely to show better knowledge (OR = 1.09; p = 0.08), and those with advanced degrees demonstrated higher competence (OR = 1.52; p = 0.028). Marital status influenced attitudes, with single nurses more likely to exhibit positive attitudes (OR = 0.49; p < 0.001), and work environment impacted knowledge, with hospital-based nurses more knowledgeable (OR = 1.15; p = 0.14). Additionally, gender differences emerged, with male nurses showing greater knowledge (OR = 1.65; p = 0.03) and better practices in diabetes care (OR = 1.47; p = 0.04).

Conclusion

The study underscores the critical need for targeted educational programs and policy interventions to enhance nursing competencies in DM management. While the study provides valuable insights into nurses' perceptions of their competencies, future research should incorporate objective knowledge assessments to ensure a comprehensive understanding of their actual capabilities. Interestingly, the data also suggests a substantial opportunity to leverage technology and inter-professional collaboration to further enhance DM management efficacy among nurses, fostering an integrated care approach.

Sleep Quality Among People with Type 2 Diabetes Mellitus During COVID-19 Pandemic: Evidence from Qatar's National Diabetes Center

Purpose

Sleep disturbance is suspected to increase during the COVID-19 pandemic, and people with type 2 DM are known to have a higher risk of sleep disturbance. We aimed to determine the prevalence and determinants of sleep disturbance through Pittsburgh Sleep Quality Index (PSQI) during the COVID-19 pandemic.

Patients and Methods

We randomly selected two hundred eighty-eight people with T2DM from the outpatient clinics of the National Diabetes Centre in Qatar. We used Chi-square, Mann-Whitney, Spearman, and Point Biserial correlation tests to examine the association between sleep quality and the independent variables. Finally, we conducted multiple logistics regression to identify the predictors of poor sleep quality and set the alpha level at 0.05.

Results

In our sample, the mean age (±SD) was 51.4 (± 9.5) years, and 64.3% of the study participants were males. The median (IQR) duration of diabetes was 10 (11) years. Additionally, 6.3% of the participants were on insulin. The median HbA1c was 7.6% (2.4). Three in ten patients reported poor sleep quality (PSQI>5); (n=103; 35.8%). Poor sleep quality was statistically associated with young age, previous history of sleep disturbance, prior diagnosis of sleep disorders, high depression score, and high perceived stress score. After adjusting for confounders, only high depressive symptoms score and previous history of sleep disorder were significant predictors of poor sleep quality (p < 0.001), with adjusted odd ratios of (aOR = 1.421; 95% CI: 1.242-1.625) and (aOR = 3.208; 95% CI: 1.574-6.537), respectively.

Conclusion

The prevalence of poor sleep quality among people with T2DM during the COVID-19 pandemic is high. Physicians must screen for depression, stress, and previous history of sleep disorder to tackle poor sleep among T2DM.

Nurse, midwife and patient perspectives and experiences of diabetes management in an acute inpatient setting: a mixed-methods study

BACKGROUND

In an acute hospital setting, diabetes can require intensive management with medication modification, monitoring and education. Yet little is known about the experiences and perspectives of nursing/midwifery staff and patients. The aim of this study was to investigate diabetes management and care for patients with diabetes in an acute care setting from the perspectives of nursing/midwifery staff and patients.

METHODS

A convergent mixed-methods study design. Patients with diabetes (Type 1, Type 2 or gestational diabetes) recruited from a public health service in Melbourne, Australia completed a survey and nurses and midwives employed at the health service participated in focus groups. Descriptive statistics were used to summarise the survey data. Thematic analysis was used for the free-text survey comments and focus group data.

RESULTS

Surveys were completed by 151 patients. Although more than half of the patients were satisfied with the diabetes care they had received (n = 96, 67.6%), about a third felt the hospital nursing/midwifery staff had ignored their own knowledge of their diabetes care and management (n = 43, 30.8%). Few reported having discussed their diabetes management with the nursing/midwifery staff whilst in hospital (n = 47, 32.6%) or thought the nurses and midwives had a good understanding of different types of insulin (n = 43, 30.1%) and their administration (n = 47, 33.3%). Patients also reported food related barriers to their diabetes management including difficulties accessing appropriate snacks and drinks (n = 46, 30.5%), restricted food choices and timing of meals (n = 41, 27.2%). Fourteen nurses and midwives participated in two focus groups. Two main themes were identified across both groups: 1. challenges caring for patients with diabetes; and 2. lack of confidence and knowledge about diabetes management.

CONCLUSIONS

Patients and nursing/midwifery staff reported challenges managing patients' diabetes in the hospital setting, ensuring patients' optimal self-management, and provision of suitable food and timing of meals. It is essential to involve patients in their diabetes care and provide regular and up-to-date training and resources for nursing/midwifery staff to ensure safe and high-quality inpatient diabetes care and improve patient and staff satisfaction.

Management of patients with type 2 diabetes in cardiovascular rehabilitation

The clinical benefits of rehabilitation in cardiovascular disease are well established. Among cardiovascular disease patients, however, patients with type 2 diabetes mellitus require a distinct approach. Specific challenges to clinicians and healthcare professionals in patients with type 2 diabetes include the prevalence of peripheral and autonomic neuropathy, retinopathy, nephropathy, but also the intake of glucose-lowering medication. In addition, the psychosocial wellbeing, driving ability and/or occupational status can be affected by type 2 diabetes. As a result, the target parameters of cardiovascular rehabilitation and the characteristics of the cardiovascular rehabilitation programme in patients with type 2 diabetes often require significant reconsideration and a multidisciplinary approach. This review explains how to deal with diabetes-associated comorbidities in the intake screening of patients with type 2 diabetes entering a cardiovascular rehabilitation programme. Furthermore, we discuss diabetes-specific target parameters and characteristics of cardiovascular rehabilitation programmes for patients with type 2 diabetes in a multidisciplinary context, including the implementation of guideline-directed medical therapy.

Economic evaluation of chronic disease self-management for people with diabetes: a systematic review

AIMS

To systematically review the evidence on the costs and cost-effectiveness of self-management support interventions for people with diabetes.

BACKGROUND

Self-management support is the provision of education and supportive interventions to increase patients' skills and confidence in managing their health problems, potentially leading to improvements in HbA_1c levels in people with diabetes.

METHODS

Randomized controlled trials, observational studies or economic modelling studies were eligible for inclusion in the review. The target population was adults with diabetes. Interventions had to have a substantial component of self-management support and be compared with routine care. Study quality was evaluated using the Consensus on Health Economic Criteria and International Society of Pharmacoeconomic Outcomes Research questionnaires. A narrative review approach was used.

RESULTS

A total of 16 costing and 21 cost-effectiveness studies of a range of self-management support interventions were identified. There was reasonably consistent evidence across 22 studies evaluating education self-management support programmes suggesting these interventions are cost-effective or superior to usual care. Telemedicine-type interventions were more expensive than usual care and potentially not cost-effective. There was insufficient evidence regarding the other types of self-management interventions, including pharmacist-led and behavioural interventions. The identified studies were predominantly of poor quality, with outcomes based on short-term follow-up data and study designs at high risk of bias.

CONCLUSIONS

Self-management support education programmes may be cost-effective. There was limited evidence regarding other formats of self-management support interventions. The poor quality of many of the studies undermines the evidence base regarding the economic efficiency of self-management support interventions for people with diabetes.

A rapid synthesis of the evidence on interventions supporting self-management for people with long-term conditions: PRISMS – Practical systematic RevIew of Self-Management Support for long-term conditions

Background

Despite robust evidence concerning self-management for some long-term conditions (LTCs), others lack research explicitly on self-management and, consequently, some patient groups may be overlooked.

Aim

To undertake a rapid, systematic overview of the evidence on self-management support for LTCs to inform health-care commissioners and providers about what works, for whom, and in what contexts.

Methods

Self-management is ‘the tasks . . . individuals must undertake to live with one or more chronic conditions . . . [including] . . . having the confidence to deal with medical management, role management and emotional management of their conditions’. We convened an expert workshop and identified characteristics of LTCs potentially of relevance to self-management and 14 diverse exemplar LTCs (stroke, asthma, type 2 diabetes mellitus, depression, chronic obstructive pulmonary disease, chronic kidney disease, dementia, epilepsy, hypertension, inflammatory arthropathies, irritable bowel syndrome, low back pain, progressive neurological disorders and type 1 diabetes mellitus). For each LTC we conducted systematic overviews of systematic reviews of randomised controlled trials (RCTs) of self-management support interventions (‘quantitative meta-reviews’); and systematic overviews of systematic reviews of qualitative studies of patients’ experiences relating to self-management (‘qualitative meta-reviews’). We also conducted an original systematic review of implementation studies of self-management support in the LTCs. We synthesised all our data considering the different characteristics of LTCs. In parallel, we developed a taxonomy of the potential components of self-management support.

Results

We included 30 qualitative systematic reviews (including 515 unique studies), 102 quantitative systematic reviews (including 969 RCTs), and 61 studies in the implementation systematic review. Effective self-management support interventions are multifaceted, should be tailored to the individual, their culture and beliefs, a specific LTC and position on the disease trajectory, and underpinned by a collaborative/communicative relationship between the patient and health-care professional (HCP) within the context of a health-care organisation that actively promotes self-management. Self-management support is a complex intervention and although many components were described and trialled in the studies no single component stood out as more important than any other. Core components include (1) provision of education about the LTC, recognising the importance of understanding patients’ pre-existing knowledge and beliefs about their LTC; (2) psychological strategies to support adjustment to life with a LTC; (3) strategies specifically to support adherence to treatments; (4) practical support tailored to the specific LTC, including support around activities of daily living for disabling conditions, action plans in conditions subject to marked exacerbations, intensive disease-specific training to enable self-management of specific clinical tasks; and (5) social support as appropriate. Implementation requires a whole-systems approach which intervenes at the level of the patient, the HCP and the organisation. The health-care organisation is responsible for providing the means (both training and time/material resources) to enable HCPs to implement, and patients to benefit from, self-management support, regularly evaluating self-management processes and clinical outcomes. More widely there is a societal need to address public understanding of LTCs. The lack of public story for many conditions impacted on patient help-seeking behaviour and public perceptions of need.

Conclusions

Supporting self-management is inseparable from the high-quality care for LTCs. Commissioners and health-care providers should promote a culture of actively supporting self-management as a normal, expected, monitored and rewarded aspect of care. Further research is needed to understand how health service managers and staff can achieve this culture change in their health-care organisations.

Study registration

This study is registered as PROSPERO CRD42012002898.

Funding

The National Institute for Health Research Health Services and Delivery Research programme.

Associations among health literacy, diabetes knowledge, and self-management behavior in adults with diabetes: results of a dutch cross-sectional study

Various studies have examined the association between health literacy and self-management behavior, but few have explored ways through which this occurs. The present study examines to what extent health literacy is associated with diabetes self-management behavior and to what extent diabetes knowledge is a mechanism in this association. The study was based on cross-sectional data retrieved from patient registrations and questionnaires completed in 2010. The sample included 1,714 predominantly type 2 diabetes patients, with a mean age of 67 years. Diabetes self-management was indicated by HbA1c level, glucose self-control and self-reported monitoring of glucose levels, physical activity, and smoking. Multilevel analyses were applied based on multiple imputed data. Lower health literacy was significantly associated with less diabetes knowledge, higher HbA1c level, less self-control of glucose level, and less physical activity. Participants with more diabetes knowledge were less likely to smoke and more likely to control glucose levels. Diabetes knowledge was a mediator in the association between health literacy and glucose self-control and between health literacy and smoking. This study indicates that higher health literacy may contribute to participation in certain self-management activities, in some cases through diabetes knowledge. Diabetes knowledge and health literacy skills may be important targets for interventions promoting diabetes self-management.

The Diabetes Self-Management Questionnaire (DSMQ): development and evaluation of an instrument to assess diabetes self-care activities associated with glycaemic control

Background

Though several questionnaires on self-care and regimen adherence have been introduced, the evaluations do not always report consistent and substantial correlations with measures of glycaemic control. Small ability to explain variance in HbA_1c constitutes a significant limitation of an instrument’s use for scientific purposes as well as clinical practice. In order to assess self-care activities which can predict glycaemic control, the Diabetes Self-Management Questionnaire (DSMQ) was designed.

Methods

A 16 item questionnaire to assess self-care activities associated with glycaemic control was developed, based on theoretical considerations and a process of empirical improvements. Four subscales, ‘Glucose Management’ (GM), ‘Dietary Control’ (DC), ‘Physical Activity’ (PA), and ‘Health-Care Use’ (HU), as well as a ‘Sum Scale’ (SS) as a global measure of self-care were derived. To evaluate its psychometric quality, 261 patients with type 1 or 2 diabetes were assessed with the DSMQ and an established analogous scale, the Summary of Diabetes Self-Care Activities Measure (SDSCA). The DSMQ’s item and scale characteristics as well as factorial and convergent validity were analysed, and its convergence with HbA_1c was compared to the SDSCA.

Results

The items showed appropriate characteristics (mean item-total-correlation: 0.46 ± 0.12; mean correlation with HbA_1c: -0.23 ± 0.09). Overall internal consistency (Cronbach’s alpha) was good (0.84), consistencies of the subscales were acceptable (GM: 0.77; DC: 0.77; PA: 0.76; HU: 0.60). Principal component analysis indicated a four factor structure and confirmed the designed scale structure. Confirmatory factor analysis indicated appropriate fit of the four factor model. The DSMQ scales showed significant convergent correlations with their parallel SDSCA scales (GM: 0.57; DC: 0.52; PA: 0.58; HU: n/a; SS: 0.57) and HbA_1c (GM: -0.39; DC: -0.30; PA: -0.15; HU: -0.22; SS: -0.40). All correlations with HbA_1c were significantly stronger than those obtained with the SDSCA.

Conclusions

This study provides preliminary evidence that the DSMQ is a reliable and valid instrument and enables an efficient assessment of self-care behaviours associated with glycaemic control. The questionnaire should be valuable for scientific analyses as well as clinical use in both type 1 and type 2 diabetes patients.

Assessing diabetes practices in clinical settings: precursor to building community partnerships around disease management

Many recommended best practices exist for clinical and community diabetes management and prevention. However, in many cases, these recommendations are not being fully utilized. It is useful to gain a sense of currently utilized and needed practices when beginning a partnership building effort to ameliorate such practice problems. The purpose of this study was to assess current practices in clinical settings within the Brazos Valley in preparation for beginning a community-based participatory research project on improving diabetes prevention and management in this region. Fifty-seven physicians with admission privileges to a regional health system were faxed a survey related to current diabetes patient loads, knowledge and implementation of diabetes-related best practices, and related topics. Both qualitative and quantitative examination of the data was conducted. Fifteen percent of responding providers indicated they implemented diabetes prevention best practices, with significant differences between primary-care physicians and specialists. Respondents indicated a need for educational and counseling resources, as well as an increased health-care workforce in the region. The utilization of a faxed-based survey proved an effective means for assessing baseline data as well as serving as a catalyst for further discussion around coalition development. Results indicated a strong need for both clinical and community-based services regarding diabetes prevention and management, and provided information and insight to begin focused community dialogue around diabetes prevention and management needs across the region. Other sites seeking to begin similar projects may benefit from a similar process.

Prescription checking device promises to resolve intractable hypoglycemia

BACKGROUND

Satisfactory glycemic control, meeting American Diabetes Association recommendations, is often accompanied by unsatisfactory hypoglycemia. The converse is also true. We hypothesize that this diabetes treatment dilemma may be resolved by repeated, objective, prescription checks. To do this, a new, two-part device has been developed. It includes a personal diabetes database for the patient and a built-in diabetes prescription checker for the provider. Its goals are to enhance diabetes education and improve patient care.

RESEARCH DESIGN AND METHODS

The device includes a database and supporting software, all contained in a standard USB flash drive. Using the medical prescription, body weight, and recent self-monitored blood glucose (SMBG) data, prescription checks can be done at any time. To demonstrate the device's capabilities, an observational study was performed using data from 11 patients with type 1 diabetes mellitus, on intensified therapy, with a mean glycated hemoglobin A1c <7%, and who all suffered intractable hypoglycemia. Patients had performed SMBG contours on successive days at monthly intervals. Each contour included pre- and postmeal as well as bedtime measurements. The replicated contours were used to predict the patient's glycemic profile each month. Applying a built-in simulator to each profile, changes in the prescription were explored that were consistent with reducing the recalcitrant hypoglycemia.

RESULTS

A total of 110 glycemic profiles containing 822 profile points were explored. Of these profile points, 351 (43%) showed risks of hypoglycemia, whereas 385 (47%) fell outside desired ranges. With the simulated changes in the prescription, the predicted risks of hypoglycemia were reduced 2.5-fold with insignificant increases predicted in hemoglobin A1c levels of +0.6 +/- 0.9%.

CONCLUSIONS

A novel support tool for diabetes promises to resolve the diabetes treatment dilemma. Supporting the patient, it improves self-management. Supporting the provider, it reviews the medical prescription in light of objective outcomes and formalizes interventions for maximum safety and efficacy.

Closing the circle of care with new firmware for diabetes: MyDiaBase+RxChecker

BACKGROUND

Satisfactory glycemic control, meeting American Diabetes Association recommendations, is difficult to achieve. Technologically, this is most likely because the circle of care is incomplete. Many have suggested that the introduction of information technology may remedy the situation. However, previous attempts have not succeeded. Recognizing this, we evolved firmware that supports and links both the patient at home and their care providers in the clinic.

FIRMWARE DESIGN AND METHODS

The device includes software and a database, all contained in a standard USB flash drive. At home, patients use the database portion of the device (MyDiaBase). It fully complements their diabetes education while capturing pertinent self-management information by tracking self-monitored blood glucose data, body weight, medication dosing, physical activity, diet, lifestyle, and stress. In the clinic, providers use the RxChecker program to perform prescription checks that are based on their patients' outcomes data, thereby effectively closing the circle of care.

Mobile diabetes intervention study: testing a personalized treatment/behavioral communication intervention for blood glucose control

BACKGROUND

National data find glycemic control is within target (A1c<7.0%) for 37% of patients with diabetes, and only 7% meet recommended glycemic, lipid, and blood pressure goals.

OBJECTIVES

To compare active interventions and usual care for glucose control in a randomized clinical trial (RCT) among persons with diabetes cared for by primary care physicians (PCPs) over the course of 1 year.

METHODS

Physician practices (n=36) in 4 geographic areas are randomly assigned to 1 of 4 study groups. The intervention is a diabetes communication system, using mobile phones and patient/physician portals to allow patient-specific treatment and communication. All physicians receive American Diabetes Association (ADA) Guidelines for diabetes care. Patients with poor diabetes control (A1c> or =7.5%) at baseline (n=260) are enrolled in study groups based on PCP randomization. All study patients receive blood glucose (BG) meters and a year's supply of testing materials. Patients in three treatment groups select one of two mobile phone models, receive one-year unlimited mobile phone data and service plan, register on the web-based individual patient portal and receive study treatment phone software based on study assignment. Control group patients receive usual care from their PCP. The primary outcome is mean change in A1c over a 12-month intervention period.

CONCLUSION

Traditional methods of disease management have not achieved adequate control for BG and other conditions important to persons with diabetes. Tools to improve communication between patients and PCPs may improve patient outcomes and be satisfactory to patients and physicians. This RCT is ongoing.

A novel method for assessing insulin dose adjustments by patients with diabetes

BACKGROUND

Insulin treated diabetic patients often do not adjust their insulin doses. We developed a method to provide a quantitative and qualitative assessment of this behavior.

METHODS

Fourteen patients provided logbook pages of their self-monitoring of blood glucose (SMBG) data and insulin doses. We compared the actual decisions of patients in real-life to what they would decide on the same SMBG, as an a posteriori exercise. We also compared these decisions and those proposed by 6 diabetologists on the same sets of data to the recommendations made by HumaLink, an automated insulin dosage system.

RESULTS

1) Patients in real-life modified their insulin doses least often. However, given a chance to make these decisions a posteriori, they modified their insulin doses more often. HumaLink proposed changes even more often, and diabetologists were the most aggressive in changing insulin doses. 2) The decisions proposed by the patients in real-life or a posteriori and by the diabetologists were compared to the recommendations made by HumaLink, using a decisions analysis grid (DAG). For these three groups, full disagreement with HumaLink (patient or physician increases while HumaLink decreases and the opposite) was observed for less than 5% of the cases. 3) By comparison to HumaLink, patient decisions seemed guided by the desire to avoid hypoglycemia. By contrast, decisions by diabetologists seemed often to be guided by the desire to avoid hyperglycemia.

CONCLUSION

These methods provide an objective evaluation of insulin dose adjustments by patients with diabetes and may be useful to assess the effectiveness of educational programs.

A systematic review of interactive computer-assisted technology in diabetes care. Interactive information technology in diabetes care

BACKGROUND

Excellent diabetes care and self-management depends heavily on the flow of timely, accurate information to patients and providers. Recent developments in information technology (IT) may, therefore, hold great promise.

OBJECTIVE

To determine, in a systematic review, how emerging interactive IT has been used to enhance care for adults with type 2 diabetes.

METHOD

Eligible studies were randomized controlled trials (RCTs) and observational studies (both before-after designs and post-intervention assessments) focused on computer-assisted interactive IT that included > or =10 adults with diabetes (> or =50% type 2) and reported in English. We searched 4 electronic databases (up to 2003) using terms for diabetes and technology, reviewed bibliographies, and handsearched Diabetes Care (January 1990 to February 2004). Two reviewers independently selected articles and worked serially on data extraction with adjudication of discrepancies by consensus.

RESULTS

There were 26 studies (27 reports): internet (n=6; 3 RCTs), telephone (n=7; 4 RCTs), and computer-assisted integration of clinical information (n=13, 7 RCTs). The median (range) sample size was 165 (28 to 6,469 participants) for patients and 37 (15 to 67) for providers; the median duration was 6 (1 to 29) months. Ethnic minorities or underserved populations were described in only 8 studies. Six of 14 interventions demonstrated moderate to large significant declines in hemoglobin A1c levels compared with controls. Most studies reported overall positive results and found that IT-based interventions improved health care utilization, behaviors, attitudes, knowledge, and skills.

CONCLUSIONS

There is growing evidence that emerging IT may improve diabetes care. Future research should characterize benefits in the long term (>1 year), establish methods to evaluate clinical outcomes, and determine the cost-effectiveness of using IT.

How good is your glucose control?

BACKGROUND

Glycemic control is fundamental to the management of diabetes and maintenance of health. Popular measures of performance in glycemic control include A1c and self-monitoring of blood glucose (SMBG). As measures of performance, A1c has perspective, but it fails to recognize hypoglycemia, while SMBG lacking overall perspective finds use mainly by patients to simply evaluate their glycemic status and current response to therapy. An additional, preferably visual, measure of performance in diabetes management in general and glycemic control in particular is needed.

METHODS

To form a visual measure of performance, a graphical method of analysis from the statistician's toolbox (known as the lag plot) was adapted. It can utilize SMBG data sets from any source, including memory meters and registry databases in call centers. Data are retrieved, processed, formatted, and then plotted on a PC screen or printer. The resulting lag plots visually characterize the performance of glucose control achieved over periods (selectable by the user) from days to months. Supporting numerical statistics provide rigorous outcome measures that correlate with glycated hemoglobin.

RESULTS

Clinical use of the lag plot is illustrated in seven case studies spanning the range from no diabetes, through glucose intolerance, early-onset type 2 diabetes mellitus, type 1 diabetes, intensified therapy, pump therapy, and finally islet cell transplantation. Visual comparisons before and after action/referral show impacts of interventions, incidences of hypoglycemia, and changes in the polyglycemia of unstable diabetes. Statistical significance of observed changes are quantified.

CONCLUSIONS

The simple lag plot can empower patients and their providers to identify problems in glycemic control, seek proactive action, adopt beneficial strategies, evaluate outcomes, and, most importantly, rule out interventions with no benefit.

Home blood glucose prediction: clinical feasibility and validation in islet cell transplantation candidates

AIMS/HYPOTHESIS

Diabetic subjects do home monitoring to substantiate their success (or failure) in meeting blood glucose targets set by their providers. To succeed, patients require decision support, which, until now, has not included knowledge of future blood glucose levels or of hypoglycaemia. To remedy this, we devised a glucose prediction engine. This study validates its predictions.

METHODS

The prediction engine is a computer program that accesses a central database in which daily records of self-monitored blood glucose data and life-style parameters are stored. New data are captured by an interactive voice response server on-line 24 h a day, 7 days a week. Study subjects included 24 patients with debilitating hypoglycaemia (unawareness), which qualified them for islet cell transplantation. Comparison of each prediction with the actually observed data was done using a Clarke Error Grid (CEG). Patients and providers were blinded as to the predictions.

RESULTS

Prior to transplantation, a total of 31,878 blood glucose levels were reported by the study subjects. Some 31,353 blood glucose predictions were made by the engine on a total of 8,733 days-used. Of these, 79.4% were in the clinically acceptable Zones of the CEG. Of 728 observed episodes of hypoglycaemia, 384 were predicted. After transplantation, a total of 45,529 glucose measurements were reported on a total of 12,906 days-used. Some 42,316 glucose predictions were made, of which 97.5% were in the acceptable CEG Zones A and B. Successful transplantation eliminated hypoglycaemia, improved glycaemic control, lowered HbA(1)c and freed 10 of 24 patients from daily insulin therapy.

CONCLUSIONS/INTERPRETATION

It is clinically feasible to generate valid predictions of future blood glucose levels. Prediction accuracy is related to glycaemic stability. Risk of hypoglycaemia can be predicted. Such knowledge may be useful in self-management.

A graphical user interface for diabetes management that integrates glucose prediction and decision support

BACKGROUND

The promise of the Diabetes Control and Complications Trial (DCCT) has yet to be realized in clinical practice. Notwithstanding intensive education and intensified therapy, there is a distinct lack of a suitable alternative to the intensive decision support that was also provided in the DCCT. Recently, a novel glucose predicting engine has been developed and validated. Use of its predictions in decision support in respect to medication dosing, diet, exercise, and stress promises to empower patients to achieve better diabetes control while reducing hypoglycemia and preventing body weight gain. A graphical user interface (GUI) suitable for these purposes is here described.

METHODS

The kernel of the GUI is a registry database located on a server accessible to both patients and their providers. The patient-GUI includes the resources of the glucose predicting engine and user-friendly, intuitive means to enter body weight and all home-monitored blood glucose levels. In response, means to modify medication dosages (dosing decision support) and modify planned diet and physical activity (lifestyle decision support) are afforded the user. Each action is animated so that the patient can visually see the impact of his or her changes on predicted glucose outcomes and the pending risks of hypoglycemia.

RESULTS

A staged sequence of screens supports the self-management tasks, including selection of the current meal period, the entry of data, and documentation. The GUI returns current medications and presents up-down buttons for adjusting dosages, for changing carbohydrates, for changing exercise, and for predicting the effects of stress. For each adjustment, the impact on medications or predicted glycemia outcomes is animated.

CONCLUSIONS

A new GUI that incorporates a novel glucose predicting engine is intended for all insulin-treated patients with diabetes. It may help patients and their providers to realize better glycemic control and thereby achieve the promise of the DCCT.

Patient confidentiality, data security, and provider liabilities in diabetes management

From inception, the electronic patient record has raised issues of data protection and patient confidentiality. These privacy issues have become more complicated with the introduction of electronic links to patient information held in databases sited on local and wide area networks. The first purpose of this paper is to review, from the provider's perspective, the issues surrounding patient confidentiality, data security, and consequential provider liabilities. The second is to propose possible immediate strategies and long-term solutions. Clinical procedures in diabetes practice create patient data from confidential information. This information is owned by the patient, received by the provider, enriched by a professional interpretation, and merged with other data into health records. Ownership, privacy, accountability, and responsibility issues are raised. Consequential data security and patient privacy are easily met by storage in a locked box or file cabinet. Conversion of such records into digital data in databases on local and wide area networks markedly increases the provider's exposure to liabilities. Current methods for securing remote data exist. These involve user authentication and secure transmission, but remote data storage is far less secure than a locked box. New tools for the secure storage of patient data are outlined. These involve encryption and decryption by the provider alone. A suite of computer protocols is presented that can restore security equivalent to a "locked box" and thus reduce liabilities for the provider. Providers should protect the privacy of their patients by encrypting all data that are stored in remote repositories. The tools to do this are urgently needed. A standardized digital protocol for verifying user identities, preserving patient confidentiality, and controlling data security by encryption will fully mitigate provider liabilities. Standardization and economies of scale promise future cost containment.