A telemonitoring intervention design for patients with poorly controlled type 2 diabetes: protocol for a feasibility study

BACKGROUND

Maintaining optimal glycemic control in type 2 diabetes (T2D) is difficult. Telemedicine has the potential to support people with poorly regulated T2D in the achievement of glycemic control, especially if the telemedicine solution includes a telemonitoring component. However, the ideal telemonitoring design for people with T2D remains unclear. Therefore, the aim of this feasibility study is to evaluate the feasibility of two telemonitoring designs for people with non-insulin-dependent T2D with a goal of identifying the optimal telemonitoring intervention for a planned future large-scale randomized controlled trial.

METHOD

This 3-month randomized feasibility study will be conducted in four municipalities in North Denmark starting in January 2024. There will be 15 participants from each municipality. Two different telemonitoring intervention designs will be tested. One intervention will include self-monitoring of blood glucose (SMBG) combined with sleep and mental health monitoring. The second intervention will include an identical setup but with the addition of blood pressure and activity monitoring. Two municipalities will be allocated to one intervention design, whereas the other two municipalities will be allocated to the second intervention design. Qualitative interviews with participants and clinicians will be conducted to gain insight into their experiences with and acceptance of the intervention designs and trial procedures (e.g., blood sampling and questionnaires). In addition, sources of differences in direct intervention costs between the two alternative interventions will be investigated.

DISCUSSION

Telemonitoring has the potential to support people with diabetes in achieving glycemic control, but the existing evidence is inconsistent, and thus, the optimal design of interventions remains unclear. The results of this feasibility study are expected to produce relevant information about telemonitoring designs for people with T2D and help guide the design of future studies. A well-tested telemonitoring design is essential to ensure the quality of telemedicine initiatives, with goals of user acceptance and improved patient outcomes.

TRIAL REGISTRATION

ClinicalTrials.gov, ID: NCT06134934 . Registered November 1, 2023. The feasibility trial has been approved (N-20230026) by the North Denmark Region Committee on Health Research Ethics (June 5, 2023).

Implementation of a coagulation component into a phosphate kinetics model in haemodialysis therapy: A tool for detection of clotting problems?

A coagulation component should be considered in phosphate kinetics modelling because intradialytic coagulation of the extracorporeal circuit and dialyser might reduce phosphate removal in haemodialysis. Thus, the objective of this study was to add and evaluate coagulation as an individual linear clearance reduction component to a promising three-compartment model assuming progressive intradialytic clotting. The model was modified and validated on intradialytic plasma and dialysate phosphate samples from 12 haemodialysis patients collected during two treatments (HD1 and HD2) at a Danish hospital ward. The most suitable clearance reduction in each treatment was identified by minimizing the root mean square error (RMSE). The model simulations with and without clearance reduction were compared based on RMSE and coefficient of determination (R2 ) values. Improvements were found for 17 of the 24 model simulations when clearance reduction was added to the model. The slopes of the clearance reduction were in the range of 0.011-0.632/h. Three improvements were found to be statistically significant (|observed z value| > 1.96). A very significant correlation (R2  = 0.708) between the slopes for HD1 and HD2 was found. Adding the clearance reduction component to the model seems promising in phosphate kinetics modelling and might be explained, at least in part, by intradialytic coagulation. In future studies, the model might be developed further to serve as a potentially useful tool for the quantitative detection of clotting problems in haemodialysis. NEW FINDINGS: What is the central question of this study? The aim was to add an intradialytic coagulation component to a modified version of a promising three-compartment phosphate kinetics model. The hypothesis was that circuit and dialyser clotting can be modelled by an individual linear phosphate clearance reduction component during haemodialysis treatment. What is the main finding and its importance? Improvements were found for 17 of 24 model simulations when clearance reduction was added to the model. Thus, the kinetics model seems promising and could be a useful tool for the quantitative detection of clotting problems in haemodialysis patients.

Effectiveness of Telemedicine in Managing Diabetes in Pregnancy: A Systematic Review and Meta-Analysis

BACKGROUND

Strict monitoring of blood glucose during pregnancy is essential for ensuring optimal maternal and neonatal outcomes. Telemedicine could be a promising solution for supporting diabetes management; however, an updated meta-analysis is warranted. This study assesses the effects of telemedicine solutions for managing gestational and pregestational diabetes.

METHODS

PubMed, EMBASE, Cochrane Library Central Register of Controlled Trials, and CINAHL were searched up to October 14, 2020. All randomized trials assessing the effects of telemedicine in managing diabetes in pregnancy relative to any comparator without the use of telemedicine were included. The primary outcome was infant birth weight. A meta-analysis comparing the mean difference (MD) in birth weight across studies was applied, and subgroup and sensitivity analyses were performed. The revised Cochrane tool was applied to assess the risk of bias, and the certainty of evidence was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach.

RESULTS

From a total of 18 studies, ten (totaling 899 participants) were used to calculate the effect on infant birth weight. The results nonsignificantly favored the control (MD of 19.34 g; [95% confidence interval, CI -47.8; 86.47]), with moderate effect certainty. Heterogeneity was moderate (I2 = 37.39%). Statistically significant secondary outcomes included differences in two-hour glucose tolerance postpartum (gestational diabetes; two studies: standardized mean difference 9.62 mg/dL [95% CI: 1.95; 17.28]) that favored the control (GRADE level, very low) and risk of shoulder dystocia (four studies: log odds -1.34 [95% CI: -2.61; -0.08]) that favored telemedicine (GRADE, low).

CONCLUSIONS

No evidence was found to support telemedicine as an alternative to usual care when considering maternal and fetal outcomes. However, further research is needed, including economic evaluations.

Patient-Reported Outcomes for Function and Pain in Total Knee Arthroplasty Patients

BACKGROUND

Some patients undergoing total knee arthroplasty successfully manage their condition postoperatively, while others encounter challenges in regaining function and controlling pain during recovery at home.

OBJECTIVE

To use traditional statistics and machine learning to develop prediction models that identify patients likely to have increased care needs related to managing function and pain following total knee arthroplasty.

METHODS

This study included 201 patients. Outcomes were changes between baseline and follow-up in the functional and pain subcomponents of the Oxford Knee Score. Both classification and regression modeling were applied. Twenty-one predictors were included. Tenfold cross-validation was used, and the regression models were evaluated based on root mean square error, mean absolute error, and coefficient of determination. Classification models were evaluated based on the area under the receiver operating curve, sensitivity, and specificity.

RESULTS

In classification modeling, random forest and stochastic gradient boosting provided the best overall metrics for model performance. A support vector machine and a stochastic gradient boosting machine in regression modeling provided the best predictive performance. The models performed better in predicting challenges related to function compared to challenges related to pain.

DISCUSSION

There is valuable predictive information in the data routinely collected for patients undergoing total knee arthroplasty. The developed models may predict patients who are likely to have enhanced care needs regarding function and pain management. Improvements are needed before the models can be implemented in routine clinical practice.

The potential of dividing the oxford knee score into subscales for predicting clinically meaningful improvements in pain and function of patients undergoing total knee arthroplasty

BACKGROUND

Subdividing the Oxford Knee Score (OKS) into a pain component scale (OKS-PCS) and a function component scale (OKS-FCS) for predicting clinically meaningful improvements may provide a basis for identifying patients in need of enhanced support from health care professionals to manage pain and functional challenges following total knee arthroplasty.

AIM

To assess the potential of dividing the OKS into subscales for predicting clinically meaningful improvements in pre- and postoperative pain and function by comparing two different versions of extracting pain and function derived from the OKS.

METHODS

This retrospective observational cohort study included 201 patients undergoing total knee arthroplasty. Multiple logistic regression analysis was applied for binary classification of whether patients achieved clinically meaningful improvements in pain and function.

RESULTS

The best overall version for predicting clinically meaningful improvements had an area under the receiver operating characteristic curve of 0.79 for both pain and function, whereas Nagelkerke's R² was 0.322 and 0.334, respectively.

CONCLUSION

The findings indicate that it is reasonable to subdivide the OKS into subscales for predicting clinically meaningful improvements in pain and function. However, more studies are needed to compare various types of classification algorithms in larger patient populations.

Development of a multivariable prediction model for early revision of total knee arthroplasty - The effect of including patient-reported outcome measures

Background

Revision TKA is a serious adverse event with substantial consequences for the patient. As revision is becoming increasingly common in patients under 65 years, the need for improved preoperative patient selection is imminently needed. Therefore, this study aimed to identify the most important factors of early revision and to develop a prediction model of early revision including assessment of the effect of incorporating data on patient-reported outcome measures (PROMs).

Material and methods

A cohort of 538 patients undergoing primary TKA was included. Multiple logistic regression using forward selection of variables was applied to identify the best predictors of early revision and to develop a prediction model. The model was internally validated with stratified 5-fold cross-validation. This procedure was repeated without including data on PROMs to develop a model for comparison. The models were evaluated on their discriminative capacity using area under the receiver operating characteristic curve (AUC).

Results

The most important factors of early revision were age (OR 0.63 [0.42, 0.95]; P = 0.03), preoperative EQ-5D (OR 0.07 [0.01, 0.51]; P = 0.01), and number of comorbidities (OR 1.01 [0.97, 1.25]; P = 0.15). The AUCs of the models with and without PROMs were 0.65 and 0.61, respectively. The difference between the AUCs was not statistically significant (P = 0.32).

Conclusions

Although more work is needed in order to reach a clinically meaningful quality of the predictions, our results show that the inclusion of PROMs seems to improve the quality of the prediction model.

Characteristics of Subjects With Undiagnosed COPD Based on Post-Bronchodilator Spirometry Data

BACKGROUND

COPD is largely underdiagnosed. Patients with undiagnosed COPD need to be diagnosed to ensure early treatment institution. It is therefore relevant to obtain a more profound understanding of the characteristics of patients with undiagnosed COPD to improve COPD case finding. This study aimed to explore the characteristics of subjects with undiagnosed COPD from the United States National Health and Nutrition Examination Survey (NHANES) dataset (2007-2012) based on post-bronchodilator spirometry.

METHODS

A multitude of statistical tests were performed to explore the potential characteristics of subjects with undiagnosed COPD. A total of 1,098 subjects with a post-bronchodilator FEV₁/FVC < 0.7 or lower limit of normal (LLN) were included in the final sample.

RESULTS

Undiagnosed subjects experienced less phlegm (P < .001), wheezing (P < .001), and chest pain (P < .001) than subjects diagnosed with COPD. They were characterized by less shortness of breath (P < .001), fewer work/school days lost to wheezing (P < .001), less sleep disturbance (P < .001), and less difficulty socializing (P < .001). The undiagnosed subjects felt less depressed (P < .001). Additionally, they were less likely to have asthma (P < .001). The annual household income was higher among the undiagnosed subjects (P < .001), and they were also characterized by higher FEV₁ (P < .001), and FVC (P < .001).

CONCLUSIONS

Subjects with undiagnosed COPD were characterized by fewer symptoms and had better lung function than their diagnosed counterparts.

A Decision Support Tool for Healthcare Professionals in the Management of Hyperphosphatemia in Hemodialysis

Hyperphosphatemia is known as one of the more challenging conditions in end-stage renal disease patients. This study set out to present and evaluate a healthcare-oriented decision support tool in the management of hyperphosphatemia within hemodialysis therapy. A prototype module was designed to fit into the interface of a modern dialysis machine (Fresenius 5008). The prototype included three main functions: 1) immediate bedside blood sample access, 2) a model based prognosis tool with estimates of P-phosphate and 3) an overview of the user's phosphate related activities during dialysis treatments. The prototype was evaluated by a) heuristic evaluation with five human computer interaction experts and b) user testing with think-aloud by three users as (clinical) domain experts. The two evaluation procedures identified a total of 103 usability problems and led to some specific amendments to improve its practical potential. The overall results will guide further development of the decision support tool to ensure that the functions will support the user's needs. In conclusion, the prototype was evaluated to be relevant and potentially beneficial in the management of hyperphosphatemia in hemodialysis patients. Furthermore, it was found that some of the functions could be used for educational purposes or as decision support for some patient groups, e.g. for patient doing home-dialysis.

Phosphate Kinetic Models in Hemodialysis: A Systematic Review

BACKGROUND

Understanding phosphate kinetics in dialysis patients is important for the prevention of hyperphosphatemia and related complications. One approach to gain new insights into phosphate behavior is physiologic modeling. Various models that describe and quantify intra- and/or interdialytic phosphate kinetics have been proposed, but there is a dearth of comprehensive comparisons of the available models. The objective of this analysis was to provide a systematic review of existing published models of phosphate metabolism in the setting of maintenance hemodialysis therapy.

STUDY DESIGN

Systematic review.

SETTING & POPULATION

Hemodialysis patients.

SELECTION CRITERIA FOR STUDIES

Studies published in peer-reviewed journals in English about phosphate kinetic modeling in the setting of hemodialysis therapy.

PREDICTOR

Modeling equations from specific reviewed studies.

OUTCOMES

Changes in plasma phosphate or serum phosphate concentrations.

RESULTS

Of 1,964 nonduplicate studies evaluated, 11 were included, comprising 9 different phosphate models with 1-, 2-, 3-, or 4-compartment assumptions. Between 2 and 11 model parameters were included in the models studied. Quality scores of the studies using the Newcastle-Ottawa Scale ranged from 2 to 11 (scale, 0-14). 2 studies were considered low quality, 6 were considered medium quality, and 3 were considered high quality.

LIMITATIONS

Only English-language studies were included.

CONCLUSIONS

Many parameters known to influence phosphate balance are not included in existing phosphate models that do not fully reflect the physiology of phosphate metabolism in the setting of hemodialysis. Moreover, models have not been sufficiently validated for their use as a tool to simulate phosphate kinetics in hemodialysis therapy.

Subgroup analysis of telehealthcare for patients with chronic obstructive pulmonary disease: the cluster-randomized Danish Telecare North Trial

PURPOSE

Results from the Danish cluster-randomized trial of telehealthcare to 1,225 patients with chronic obstructive pulmonary disease (COPD), the Danish Telecare North Trial, concluded that the telehealthcare solution was unlikely to be cost-effective, by applying international willingness-to-pay threshold values. The purpose of this article was to assess potential sources of variation across subgroups, which could explain overall cost-effectiveness results or be utilized in future economic studies in telehealthcare research.

METHODS

First, the cost-structures and cost-effectiveness across COPD severities were analyzed. Second, five additional subgroup analyses were conducted, focusing on differences in cost-effectiveness across a set of comorbidities, age-groups, genders, resource patterns (resource use in the social care sector prior to randomization), and delivery sites. All subgroups were investigated post hoc. In analyzing cost-effectiveness, two separate linear mixed-effects models with treatment-by-covariate interactions were applied: one for quality-adjusted life-year (QALY) gain and one for total healthcare and social sector costs. Probabilistic sensitivity analysis was used for each subgroup result in order to quantify the uncertainty around the cost-effectiveness results.

RESULTS

The study concludes that, across the COPD severities, patients with severe COPD (GOLD 3 classification) are likely to be the most cost-effective group. This is primarily due to lower hospital-admission and primary-care costs. Telehealthcare for patients younger than 60 years is also more likely to be cost-effective than for older COPD patients. Overall, results indicate that existing resource patterns of patients and variations in delivery-site practices might have a strong influence on cost-effectiveness, possibly stronger than the included health or sociodemographic sources of heterogeneity.

CONCLUSION

Future research should focus more on sources of heterogeneity found in the implementation context and the way telehealthcare is adopted (eg, by integrating formative evaluation into cost-effectiveness analyses).

TRIAL REGISTRATION

Clinicaltrials.gov, NCT01984840.

The long-term effects of using telehomecare technology on functional health literacy: results from a randomized trial

OBJECTIVES

The association between the use of telehomecare technology and functional health literacy is rather unexplored in the current literature. This relationship could prove important in the future management of chronic diseases, as technology has become a more integrated part of modern healthcare systems. Therefore, the purpose of this study was to explore how the use of telehomecare technology affects the level of functional health literacy over a period of 10 months.

STUDY DESIGN

Randomized controlled trial.

METHODS

Our sample comprised 116 patients diagnosed with chronic obstructive pulmonary disease. A face-to-face interview and an objective test of functional health literacy were conducted with each patient at baseline and again at follow-up after 10 months. Twenty-six patients were lost to follow-up and thus, providing a total of 47 chronic obstructive pulmonary disease patients in the intervention group and 43 in the control group for this follow-up study. The level of functional health literacy was assessed with the Danish Test of Functional Health Literacy in Adults. The difference from baseline to follow-up, in both the functional health literacy score and the mean response time to the entire Danish Test of Functional Health Literacy in Adults (TOFHLA), was tested for statistical significance between the intervention group and the control group.

RESULTS

A significant increase in functional health literacy is observed in both the groups from baseline to follow-up, but there is no statistical difference between groups (P-value = 0.62).

CONCLUSIONS

A significant increase in the functional health literacy score was observed in both groups, but the findings of this present study provide no information on what causes the increase, so further research is needed to explore the increase in functional health literacy score more thoroughly and establish if the use of telehomecare technology is a part of the explanation.

Telehealthcare for patients suffering from chronic obstructive pulmonary disease: effects on health-related quality of life: results from the Danish 'TeleCare North' cluster-randomised trial

OBJECTIVE

To assess the effect of telehealthcare compared with usual practice in patients with chronic obstructive pulmonary disease (COPD).

DESIGN

A cluster-randomised trial with 26 municipal districts that were randomly assigned either to an intervention group whose members received telehealthcare in addition to usual practice or to a control group whose members received usual practice only (13 districts in each arm).

SETTING

Twenty-six municipal districts in the North Denmark Region of Denmark.

PARTICIPANTS

Patients who fulfilled the Global Initiative for COPD guidelines and one of the following criteria: COPD Assessment Test score ≥10; or Medical Research Dyspnoea Council Scale ≥3; or Modified Medical Research Dyspnoea Council Scale ≥2; or ≥2 exacerbations during the past 12 months.

MAIN OUTCOME MEASURES

Health-related quality of life (HRQoL) assessed by the physical component summary (PCS) and mental component summary (MCS) scores of the Short Form 36-Item Health Survey, Version 2. Data were collected at baseline and at 12 month follow-up and analysed according to the intention-to-treat principle with complete cases, n=574 (258 interventions; 316 controls) and imputed data, n=1225 (578 interventions, 647 controls) using multilevel modelling.

RESULTS

In the intention-to-treat analysis (n=1225), the raw mean difference in PCS from baseline to 12 month follow-up was -2.6 (SD 12.4) in the telehealthcare group and -2.8 (SD 11.9) in the usual practice group. The raw mean difference in MCS scores in the same period was -4.7 (SD 16.5) and -5.3 (SD 15.5) for telehealthcare and usual practice, respectively. The adjusted mean difference in PCS and MCS between groups at 12 months was 0.1 (95% CI -1.4 to 1.7) and 0.4 (95% CI -1.7 to 2.4), respectively.

CONCLUSIONS

The overall sample and all subgroups demonstrated no statistically significant differences in HRQoL between telehealthcare and usual practice.

TRIAL REGISTRATION NUMBER

NCT01984840; Results.

Prediction of excessive weight gain in insulin treated patients with type 2 diabetes

BACKGROUND

Weight gain is an ongoing challenge when initiating insulin therapy in patients with type 2 diabetes mellitus (T2DM). However, if prediction of insulin-associated weight gain was possible on an individual level, targeted initiatives could be implemented to reduce weight gain. The aim of the present study was to identify predictors of weight gain in insulin-treated patients with T2DM.

METHODS

In all, 412 individuals with T2DM were, in addition to metformin or placebo, randomized into 18-month treatment groups with three different insulin analog treatment regimens (biphasic, aspart, detemir). Participants with excessive weight gain were defined as the group with weight gain in the 4th quartile (>6.2 kg).We developed a pattern classification method to predict individuals prone to excessive weight gain.

RESULTS

Over the 18-month treatment period, median weight gain among all 412 patients was 2.4 kg (95% prediction interval [PI] -5.6, 12.4 kg), whereas median weight gain for those in the upper 4th quartile (n = 103) was 8.9 kg (95% PI 6.3, 15.2 kg). No clinical baseline data were strong predictors of excessive weight gain. However, the weight gain during the first 3 months of the trial and the subsequent dose of insulin yielded a useful predictor for weight gain at the 18-month follow-up. Combining these two predictors into a prediction model with other clinical available information produced a receiver operating characteristic area under the curve of 0.80.

CONCLUSIONS

We have developed a prediction model that could help identify a substantial proportion of individuals with T2DM prone to large weight gain during insulin therapy.

Stratification of telehealthcare for patients with chronic obstructive pulmonary disease using a predictive algorithm as decision support: A pilot study

Introduction

The number of patients needing care who suffer from chronic obstructive pulmonary disease (COPD) is expected to increase in the future. The consequences thereof will increase the socio-economic burden for both patients and society. Telehealthcare technologies have shown potential in reducing hospitalisation-related costs and in improving health-related quality of life (HRQOL) for some COPD patients, but not all. The aim of this study was to investigate the potential of predictive algorithms for helping the general practitioner to stratify telehealthcare for COPD patients in a way that maximises HRQOL and minimises COPD-related costs.

Methods

Data from 553 COPD patients based in the North Denmark Region were analysed and used as predictors for four multiple linear regression models. The models were trained and evaluated for their abilities to predict individual patient’s future health- and cost-related developments, with and without telehealthcare.

Results

The average root-mean-square error (RMSE) of the health and cost models was 5.265 HRQOL scores and US dollars (US$)5430.49, respectively. The accuracy regarding the polarity of the predicted changes ranged from 61–65% for the health models and 74–75% for the cost models. While differences in the magnitude of predictions with and without telehealthcare were statistically significant ( p < 0.01), the polarity of predictions was similar across models in 82.05% of all cases.

Discussion

Our results indicate that it may be possible to predict the magnitude and polarity of a COPD patient’s future health- and cost-related developments with and without telehealthcare. Predictive algorithms may provide a useful decision support tool in stratifying telehealthcare for COPD patients.

Prediction of exacerbation onset in chronic obstructive pulmonary disease patients

The objective of this study was to develop an algorithm for prediction of exacerbation onset in Chronic Obstructive Pulmonary Disease (COPD) patients based on continuous self-monitoring of physiological parameters from telehome-care monitoring. 151 physiological parameters of COPD patients were monitored on a daily/weekly basis for up to 2 years. Data were segmented in 30-day periods leading up to an exacerbation (exacerbation episode) and starting from a 14-day recovery period post-exacerbation (control episode) and tested in 6 intervals to predict exacerbation onset using k-nearest neighbour (k = 1, 3, 5). A classifier with sensitivity of 73%, specificity of 74%, positive predictive value of 69%, negative predictive value of 78% and an accuracy of 74% was achieved using data intervals consisting of 5 days. Intelligent processing of physiological recordings have potential for predicting exacerbation onset.

Participatory Heuristic Evaluation of the Second Iteration of the eWALL Interface Application

The number of people having a chronic disease is increasing. Telehealth may provide an alternative to traditional medicine as telehealth solutions have shown to have a positive influence on quality of live and to decrease the number of hospital visits. A new telehealth solution is the eWALL system. Previously, the eWALL interface application has been evaluated using participatory heuristic evaluation (PHE). The previous round of PHE lead to drastic changes of the eWALL interface application. Consequently, a second round of PHE was performed. Five usability experts and two work-domain professionals inspected the eWALL interface application and identified usability problems (n = 384). The work domain professionals had a tendency to use other heuristics than the usability experts highlighting the relevance of using PHE in an interface development process.

Heuristic evaluation of a telehealth system from the Danish TeleCare North Trial

OBJECTIVE

The aim was to evaluate the usability of the design of the telehealth system, named Telekit, developed for the Danish TeleCare North Trial, early into the design process in order to assess potential problems and limitations which could hinder its successful implementation.

METHODS

Five experts, including one who pilot-tested the Telekit system, individually evaluated its usability and its compliance with Jakob Nielsen's ten usability heuristics for interaction design. Usability problems were categorised according to Rolf Molich's severity classification.

RESULTS

The five experts identified a total of 152 problems in the Telekit system, each identifying 22-40 problems. 86 (57%) out of the 152 problems were identified only once. All heuristics were used, but the three most frequently used were: "Match between system and the real world" (32%), "Consistency and standards" (13%) and "Aesthetic and minimalist design" (13%). The most widely used classifications were: "Improvement" (40%) and "Minor problem" (43%).

CONCLUSION

Heuristic evaluation was an effective method for uncovering and identifying problems with the system. The consistent finding of particular usability problems confirms that the development of a telehealth system should pay particular attention to user aspects. The most serious problem was the inability of the system to inform users of how to perform measurements correctly and to "speak the users' language". The problems found in the heuristic evaluation have led to several significant changes in the telehealth system. We suggest that heuristic evaluation always be followed by user tests to evaluate the design of telehealth systems.

Validation of the Test of Functional Health Literacy in Adults in a Danish population

OBJECTIVE

To describe how the original American full-length version of the Test of Functional Health Literacy in Adults (TOFHLA) was translated and adapted for use in the Danish setting and culture. A reliable Danish version of the TOFHLA was created and pretested using patients diagnosed with chronic obstructive pulmonary disease (COPD) as case group.

METHODS

Forty-two patients with COPD completed the Danish TOFHLA and participated in a face-to-face interview concerning their basic demographics. Statistical analyses were conducted to explore the demographic data provided by the participants and to determine the internal consistency and reliability of the Danish TOFHLA.

RESULTS

The mean age of sample was 68.7 years (range 34-86). The face validity, internal consistency and item to scale correlations of the Danish TOFHLA were determined and found to fulfil well-established criteria; on this basis, we found the reliability and consistency of the Danish TOFHLA to be satisfying.

CONCLUSION

The Danish TOFHLA is now ready for application in future research projects, which test levels of functional health literacy in an elderly Danish population at risk of chronic diseases. The evolvement in the measurement of health literacy is still ongoing, as there is a need to refine existing methods. Until recently, there has been a total lack of instruments for assessing health literacy in Scandinavia; it is hoped that this development of the Danish TOFHLA will promote further research within the field of health literacy in Scandinavia and other European countries.

A multi-method pilot evaluation of an online diabetes exercise system

The American Diabetes Association and The European Association of The Study of Diabetes recommend people with Type 2 diabetes to do moderate to vigorous aerobic exercise for 150 min per week to avoid late diabetic complications. However, most people with diabetes do not follow the recommendation. Consumer health information technology (CHIT) might play a role in supporting behavior changes that promote health and well-being. A CHIT prototype of an online diabetes exercise system, which contained the newest research of low volume high-intensity interval training (HIT), was developed. To test the system we used a multi-method pilot evaluation that includes; interviews, paper prototyping, heuristic evaluation, and test with patients. The patients expressed satisfaction with HIT and appreciated that the system was web-based. The findings from this pilot study inspire to further development and evaluation of online CHIT systems to diabetics.

Hypoglycaemia and QT interval prolongation in type 1 diabetes--bridging the gap between clamp studies and spontaneous episodes

AIMS

We propose a study design with controlled hypoglycaemia induced by subcutaneous injection of insulin and matched control episodes to bridge the gap between clamp studies and studies of spontaneous hypoglycaemia. The observed prolongation of the heart rate corrected QT interval (QTc) during hypoglycaemia varies greatly between studies.

METHODS

We studied ten adults with type 1 diabetes (age 41±15years) without cardiovascular disease or neuropathy. Single-blinded hypoglycaemia was induced by a subcutaneous insulin bolus followed by a control episode on two occasions separated by 4weeks. QT intervals were measured using the semi-automatic tangent approach, and QTc was derived by Bazett's (QTcB) and Fridericia's (QTcF) formulas.

RESULTS

QTcB increased from baseline to hypoglycaemia (403±20 vs. 433±39ms, p<0.001). On the euglycaemia day, QTcB also increased (398±20 vs. 410±27ms, p<0.01), but the increase was less than during hypoglycaemia (p<0.001). The same pattern was seen for QTcF. Plasma adrenaline levels increased significantly during hypoglycaemia compared to euglycaemia (p<0.01). Serum potassium levels decreased similarly after insulin injection during both hypoglycaemia and euglycaemia.

CONCLUSIONS

Hypoglycaemia as experienced after a subcutaneous injection of insulin may cause QTc prolongation in type 1 diabetes. However, the magnitude of prolongation is less than typically reported during glucose clamp studies, possible because of the study design with focus on minimizing unwanted study effects.

A novel model enhances HbA1c-based diabetes screening using simple anthropometric, anamnestic, and demographic information

BACKGROUND

The sensitivity of HbA1c is not optimal for the screening of patients with latent diabetes. We hypothesize that simple healthcare information could improve accuracy.

METHODS

We retrospectively analyzed data, including HbA1c, from multiple years from the National Health and Nutrition Examination Survey (NHANES) database (2005-2010). The data were used to create a logistic regression classification model for screening purposes.

RESULTS

The study evaluated data for 5381 participants, including 404 with undiagnosed diabetes. The HbA1c screening data were supplemented with information about age, waist circumference, and physical activity in the HbA1c+ model. Alone, HbA1c alone had a receiver operating characteristics (ROC) curve for the area under the curve (AUC) of 0.808 (95% confidence interval [CI] 0.792-0.834). The HbA1c+ model had an ROC AUC of 0.851 (95% CI 0.843-0.872). There was a significant difference in the AUC between our model and using HbA1c without supplementary information (P < 0.05).

CONCLUSIONS

We have developed a novel screening model that could help improve screening for type 2 diabetes with HbA1c. It seems beneficial to systematically add additional patient healthcare information in the process of screening with HbA1c.

A novel algorithm for prediction and detection of hypoglycemia based on continuous glucose monitoring and heart rate variability in patients with type 1 diabetes

Hypoglycemia is a common and serious side effect of insulin therapy in patients with diabetes. Early detection and prediction of hypoglycemia may improve treatment and avoidance of serious complications. Continuous glucose monitoring (CGM) has previously been used for detection of hypoglycemia, but with a modest accuracy. Therefore, our aim was to investigate whether a novel algorithm that adds information of the complex dynamic/pattern of heart rate variability (HRV) could improve the accuracy of hypoglycemia as detected by a CGM device. Data from 10 patients with type 1 diabetes studied during insulin-induced hypoglycemia were obtained. Blood glucose samples were used as reference. HRV patterns and CGM data were combined in a mathematical prediction algorithm. Detection of hypoglycemic periods, performed by the algorithm, was treated as a pattern recognition problem and features/patterns derived from HRV and CGM prior to each blood glucose sample were used to decide if that particular point in time was below the hypoglycemic threshold of 3.9 mmol/L. A total of 903 samples were analyzed by the novel algorithm, which yielded a sensitivity of 79% and a specificity of 99%. The algorithm was able to detect 16/16 hypoglycemic events with no false positives and had a lead time of 22 minutes as compared to the CGM device. Detection accuracy and lead time were significantly improved by the novel algorithm compared to that of CGM alone.

Improved diabetes screening using an extended predictive feature search

BACKGROUND

Screening entire populations for diabetes is not cost-effective. Hence, an efficient screening process must select those people who are at high risk for diabetes. In this study, we investigated whether screening procedures could be improved using an extended predictive feature search.

MATERIALS AND METHODS

In order to develop our model and identify persons with diabetes (prevalence) we used data from years of the National Health and Nutrition Examination Survey (2005-2010), which has not been explored for this purpose before. We calculated all combinations of predictors in order to identify the optimal subset, and we used a linear logistic classification model to predict diabetes. V-fold cross-validation was used for the process of including variables and for validating the final models. This new model was compared with two established models.

RESULTS

In total, 5,398 participants were included in this study. Among these, 478 participants had unidentified diabetes. The established models had a receiver operating characteristics curve for the area under the curve (AUC) of 0.74 and 0.71 compared with an AUC of 0.78 for the new model, showing a significant difference (P<0.05). A proposed cutoff point for the established models yielded respective sensitivities/specificities of 63%/72% and 40%/72% compared with the new model, which had a sensitivity/specificity of 70%/72%.

CONCLUSIONS

Our data indicate that simple healthcare and economic information such as ratio of family income to poverty can add value in deciding who is at risk of unknown diabetes by using extended investigations of predictor combinations.

Participatory heuristic evaluation of a tablet computer system for clinical microbiology

MultiplexBCT is a molecular-based diagnostic test for rapid identification of microorganisms in positive blood cultures. A MultiplexBCT Android tablet computer application is being developed as an accessory to the diagnostic test. The aim of the application is to facility the end user's workflow by supporting data entry and communication of the MultiplexBCT test results in a hospital environment. This paper reports the results and benefit of a participatory heuristic evaluation conducted on the MultiplexBCT application. The design is an extension of heuristic evaluation that includes end users as work-domain experts to complement usability experts for inspection of a user interface. The user interface assessment identified 86 heuristic violations, which consisted of both product- and domain-related issues. These results will be used to guide further development of the MultiplexBCT application to ensure that the system will fully support the workflow of the end users when using the MultiplexBCT diagnostic test.

User satisfaction and experience with a telehealth system for the Danish TeleCare North Trial: a think-aloud study

The aim was to evaluate a redesigned version of Telekit--a telehealth system developed for the Danish TeleCare North Trial. Telekit is used in the management of care in patients diagnosed with chronic obstructive pulmonary disease (COPD). This paper summarises the experience and the feedback received from six COPD-participants in terms of usability and satisfaction. Participants were asked to think-aloud while performing some system specific tasks. After each session, participants completed a post-test questionnaire. The think-aloud test was recorded, and notes from the tests were categorised and analysed. All tasks were completed by participants. Difficulties were observed concerning monitoring of measurements and use of the touchscreen. User feedback was mainly positive, and nearly all participants perceived Telekit as very easy to use. The study provides important insight regarding use of Telekit by patients suffering from a chronic illness and increased understanding about, how similar systems can more effectively be used in such home health initiatives.

Heuristic evaluation and thinking aloud test of a digitized questionnaire for diabetes outpatient clinics

Diabetes is a chronic disease characterized by hyperglycaemia. The number of patients with diabetes is expected to exceed 592 million in 2035. The growing number of diabetics is a great burden for the Danish healthcare system. The Danish government desires a modern and efficient healthcare system with a high patient security and a coherent continuity of care. To achieve these outcomes medical record-keeping, paper questionnaires and notes must be digitized. The current system enforces that the diabetics fill out questionnaires in paper form after which the healthcare personnel enter the same information in the electronic health record. In this study, an online questionnaire was designed and the usability was evaluated using the following parameters: learnability, efficiency, memorability, errors, and satisfaction. The parameters were evaluated by using the discount usability engineering method. 5 double specialists and 6 patients diagnosed with diabetes provided the data of the study. The results indicated that simple and obvious figures were preferred in the online questionnaire, as well as error preventing in the form of validation fields. This study inspire to further development in the digitizing process.

Telehomecare technologies enhance self-management and empowerment among patients with chronic obstructive pulmonary disease (COPD) - where does health literacy fit into this equation?

Chronic obstructive pulmonary disease (COPD) is a chronic disease characterised by a graduate decline of pulmonary function and it constitutes a provable burden on society. Tele-homecare technology (THC) is a young field of research that has shown potential with regards to enhancing the level of self-management among COPD patients. Self-management is closely connected to health literacy. Health literacy and THC have shown great potential in terms of reducing healthcare costs and improving quality of life for COPD patients. The objective of this poster is to raise awareness regarding the potential of using THC to improve the level of health literacy.

A diet management information and communication system to help chronic kidney patients cope with diet restrictions

Hyperphosphatemia, hyperkalemia, and fluid overload are frequently observed and pose major physiological concerns in chronic kidney patients. The problems are closely related to inadequate diet and phosphate binder intake, which are considerable challenges for many patients. The objective of this study was to develop and test an educational decision support system to help kidney patients cope with diet restrictions and phosphate binder dosage. A prototype was designed including three main functions: 1) information and education, 2) food analyser database and diet registration, and 3) model-based decision support to phosphate binder dosage. The functions and the usability of the prototype were evaluated through user testing and qualitative interviews including five kidney patients. The decision support function was modified and tested using experimental data. In conclusion, the system was evaluated to be a relevant, and potentially beneficial tool to cope with kidney diet restrictions. Further data are necessary to validate the correct phosphate binder dosage and assess the ability of the system to decrease the incidence of fluid and electrolyte disorders in kidney patients.

Exploring end users' system requirements for a handheld computer supporting both sepsis test workflow and current IT solutions

Sepsis is a systemic response associated with very high mortality. Early initiation of the correct antimicrobial therapy remains a cornerstone in the treatment of sepsis. Currently, a new microbiological test is under development, which aims to detect major, prevalent pathogens in positive blood cultures within an hour. Concurrently, a tablet-based data entry and reporting system will be developed to facilitate the workflow of the test. This study investigated the system requirements for the tablet-based data entry and reporting system in order to support the clinical workflow. By observing the workflow of the blood culture analysis and through interviews with medical laboratory technicians, four main system requirements were identified. The system requirements are; the ability to receive and send data to the laboratory information system, support for the use of barcodes, the ability to access a browser based instruction system, and communication of results between medical laboratory technicians and physicians. These system requirements will be used as a basis in the future development of the tablet-based data entry and reporting system.

Interindividual and intraindividual variations in postprandial glycemia peak time complicate precise recommendations for self-monitoring of glucose in persons with type 1 diabetes mellitus

BACKGROUND

In glycemic control, postprandial glycemia may be important to monitor and optimize as it reveals glycemic control quality, and postprandial hyperglycemia partly predicts late diabetic complications. Self-monitoring of blood glucose (SMBG) may be an appropriate technology to use, but recommendations on measurement time are crucial.

METHOD

We retrospectively analyzed interindividual and intraindividual variations in postprandial glycemic peak time. Continuous glucose monitoring (CGM) and carbohydrate intake were collected in 22 patients with type 1 diabetes mellitus. Meals were identified from carbohydrate intake data. For each meal, peak time was identified as time from meal to CGM zenith within 40-150 min after meal start. Interindividual (one-way Anova) and intraindividual (intraclass correlation coefficient) variation was calculated.

RESULTS

Nineteen patients were included with sufficient meal data quality. Mean peak time was 87 ± 29 min. Mean peak time differed significantly between patients (p = 0.02). Intraclass correlation coefficient was 0.29.

CONCLUSIONS

Significant interindividual and intraindividual variations exist in postprandial glycemia peak time, thus hindering simple and general advice regarding postprandial SMBG for detection of maximum values.

Moving prediction of exacerbation in chronic obstructive pulmonary disease for patients in telecare

We investigated whether physiological data can be used for predicting chronic obstructive pulmonary disease (COPD) exacerbations. Home measurements from 57 patients were analysed, during which 10 exacerbations occurred in nine patients. A total of 273 different features were evaluated for their discrimination abilities between periods with and without exacerbations. The analysis showed that if a sensitivity level of 70% is considered to be acceptable, then the specificity was 95% and the AUC was 0.73, i.e. it is possible to discriminate between periods of exacerbation and periods without. A system capable of predicting risk could provide support to COPD patients in their tele-rehabilitation.

Patient support ICT tool for hypertension monitoring

Detection of hypertension is traditionally a matter for the general practitioner, but an alternative detection scheme is home blood pressure measurement by patients, on patients' or doctors' decision. We designed and implemented a prototype software tool to provide information about hypertension, video instructions on correct home blood pressure measurement technique and a measurements diary. The system was developed using standard, software development methods and techniques. The program was developed for Danish-speaking patients. Usability (navigability, level and outcome of instructions, logical arrangement, level and focus of information, and program accessibility) was evaluated in a think-aloud test with test users performing specific, realistic tasks. The prototype provides written information about hypertension, written and video instructions on correct blood pressure measurement technique, and measurements diary functionality. All test users performed all tasks and rated navigability, level and outcome of instructions, logical arrangement, level and focus of information, and program accessibility high, and had positive attitudes towards the system. The components in the patient support tool can be used separately or in combination. The effects of video for home blood pressure measurement technique instruction remain unexplored.

Hypoglycemia impairs quality of blood glucose simulation in a clinical decision support system

BACKGROUND

Clinical decision support systems allow for decisions based on blood glucose simulations. The DiasNet simulation tool is based on accepted principles of physiology and simulates blood glucose concentrations accurately in type 1 diabetes mellitus (T1DM) patients during periods without hypoglycemia, but deviations appear after hypoglycemia, possibly because of the long-term glucose counter-regulation to hypoglycemia. The purpose of this study was to evaluate the impact of hypoglycemia on blood glucose simulations.

METHOD

Continuous glucose monitoring (CGM) data and diary data (meals, insulin, self-monitored blood glucose) were collected for 2 to 5 days from 17 T1DM patients with poor glycemic control. Hypoglycemic episodes [CGM glucose <63 mg/dl (3.5 mmol/liter) for ≥20 min] were identified in valid (well-calibrated) CGM data. For 24 hours after each hypoglycemic episode, a simulated (DiasNet) glucose profile was compared to the CGM glucose.

RESULTS

A total of 52 episodes of hypoglycemia were identified in valid data. All subjects had at least one hypoglycemic episode. Ten episodes of hypoglycemia from nine subjects were eligible for analysis. The CGM glucose was significantly (p < .05) higher than simulated blood glucose for a period of 13 h, beginning 8 h after hypoglycemia onset.

CONCLUSIONS

The present data show that hypoglycemia introduces substantial and systematic simulation errors for up to 24 h after hypoglycemia. This underlines the need for further evaluation of mechanisms behind this putative long-term glucose counter-regulation to hypoglycemia. When using blood glucose simulations in decision support systems, the results indicate that simulations for several hours following a hypoglycemic event may underestimate glucose levels by 100 mg/dl (5.6 mmol/liter) or more.

A pilot assessment of why patients choose not to participate in self-monitoring oral anticoagulant therapy

Patients suffering from heart diseases often face lifelong oral anticoagulant therapy. Traditionally, the patient's general practitioner takes care of the treatment. An alternative management scheme is a self-monitoring setup where the patient monitors and manages the oral treatment himself. Despite international evidence of reduced thrombosis risk and death rate among patients enrolled in self-monitoring, a majority of eligible patients deselect this opportunity. Little is about the causes if this. This study is a pilot assessment of why patients, located in the North Denmark Region, choose not to participate. The study is based on qualitative interviews with two nurses working in a medical practice and two patients participating in conventional anticoagulant therapy. The results of this study seem to suggest that at least some patients feel a lack of information to base their decision regarding self-monitoring or conventional management on and that the knowledge among the health personnel at the medical clinics should be increased.

QT interval prolongation during spontaneous episodes of hypoglycaemia in type 1 diabetes: the impact of heart rate correction

AIMS/HYPOTHESIS

Prolongation of the heart rate corrected QT interval (QTc) is seen during episodes of hypoglycaemia in type 1 diabetes. We studied the relationship between spontaneous hypoglycaemia and the QT interval and hypothesised that the choice of heart rate correction affects the observed change in QTc.

METHODS

Twenty-one participants with type 1 diabetes (aged 58 +/- 10 years with duration of diabetes 34 +/- 12 years) had continuous glucose and ECG monitoring for 72 h. QT and RR intervals were measured during hypoglycaemia (blood glucose or continuous glucose measurements <or=3.5 mmol/l) and compared with euglycaemia (5-12 mmol/l). QT intervals were measured using the semi-automated tangent method from signal-averaged ECG and corrected using Bazett's formula, Fridericia's formula, the nomogram method and a linear subject-specific method.

RESULTS

Hypoglycaemia was present in 14 participants. With Bazett's formula, QTc changed significantly from euglycaemia to hypoglycaemia (422 +/- 30 vs 432 +/- 33 ms; p = 0.02). Heart rate, QT intervals and QTc corrected with formulas other than Bazett's were not associated with a significant change (p = 0.07-0.29). During hypoglycaemia, significantly lower values of QTc compared with the subject-specific method were seen for Fridericia's formula (p = 0.02) and the nomogram method (p = 0.04).

CONCLUSIONS/INTERPRETATION

Spontaneous hypoglycaemia was associated with a modest increase in QTc. Bazett's formula resulted in overcorrection of QTc while both Fridericia's formula and the nomogram method undercorrected the QTc compared with the subject-specific method during hypoglycaemia. The results may indicate that the use of a fixed heart rate correction formula can lead to misleading results in investigations of spontaneous hypoglycaemia.

Data mining to assess variations in oral anticoagulant treatment

Variations in International Normalized Ratio's (INR) are closely related to bleeding and thrombosis incidents in patients on oral anticoagulation treatment. This study investigates predictive factors that affect INR values. Data sampled with relatively high frequency allows for detection of local INR variations, and hence also allows detection and evaluation of predictive factors where time is taken into consideration. Univariate linear regression was applied and different models were reduced into a final predictive model. F-tests were utilized to test whether or not a model reduction would benefit INR predictions, in terms of decreasing observed variance. In addition to an INR submodel, the final model includes individual interaction from the last three days change in mean warfarin intake and three days change in mean vitamin K intake. Prediction residual error was mainly reduced by the INR submodel, while the warfarin model and the vitamin K submodel did not benefit predictions to same extend compared to the INR submodel. However, more studies on the temporal aspects of the effect of warfarin seem to be relevant.

Assessing importance of dietary data in anticoagulation treatment

This paper describes the outcome of including information on dietary intake in the attempt to predict International Normalized Ratio (INR) values. An already published model has been extended and is now tested with the additional dietary data and without it. When predicting INR values seven days into the future, the new proposed model outperforms the existing one. It is concluded that adding information on dietary intake improves the accuracy of INR predictions.

Clinical implications of a quality assessment of transcutaneous CO2 monitoring in preterm infants in neonatal intensive care

More than 1% of infants are born premature. Many of these children require special treatment because of immature organs and body functions. CO2 is an important parameter to monitor in order to avoid serious brain damage. Blood sampling of CO2 has several shortcomings and non-invasive transcutaneous CO2 is being investigated in order to assess its potential to contribute with the same type of information as blood CO2 measurements. The present study assesses the quality of transcutaneous CO2 data by comparing it to the "golden standard" blood CO2 data, in order to provide clinicians with a better understanding of the usefulness and limitations of transcutaneous CO2 data in neonatal care. The study shows that for low transcutaneous CO2 the error is relatively high and in most cases the true CO2, represented by the blood CO2, which can be regarded as the "gold standard", is higher than the measured transcutaneous CO2. The opposite is the case for high transcutaneous CO2. It is discussed how this is not due to any systematic error in the equipment, but due to the natural behaviour of noisy data.

Modeling the effect of blood glucose and physical exercise on plasma adrenaline in people with type 1 diabetes

BACKGROUND

Adrenaline is often studied in people with type 1 diabetes during hypoglycemic episodes. Adrenaline is difficult and costly to measure, and therefore a pharmacokinetic model of adrenaline can be a supportive tool that adds information and saves measurements resources.

METHODS

We have developed a compartment model of adrenaline secretion and elimination. It is based on input on physical exercise, blood glucose level, and optional infused adrenaline. The model parameters are identified using least square regression on published data of adrenaline kinetics measured in a number of different clinical studies.

RESULTS

Simulation of published adrenaline measurements shows agreement with data of adrenaline infusion (R(2) = 0.9), exercise (R(2) = 0.97), and hypoglycemic episodes (R(2) = 0.93-0.97). The identified function describing adrenaline secretion during hypoglycemia shows an exponential increase for a blood glucose decreasing below 3.5 mmol/L and an approaching maximum around 1 mmol/L. Exercise intensity increasing above 50% of maximal oxygen uptake maximum causes approximately exponential increase in adrenaline secretion.

CONCLUSION

The model is a simple tool that can be used to simulate and predict adrenaline concentrations in situations of hypoglycemia, physical exercise, and adrenaline infusion. In conclusion, the developed model, although simple, seems to be useful for simulating adrenaline dynamics in situations with hypoglycemic episodes, physical exercise, or infusion.

The impact of non-model-related variability on blood glucose prediction

BACKGROUND

Physiological models are frequently used to predict blood glucose values from insulin and meal data of people with diabetes. Obviously, errors in the input data used result in prediction errors. A more complex problem is that no model may include all factors influencing the blood glucose level in any given situation. We have analyzed the influence of five parameters on prediction accuracy with respect to the time horizon.

METHODS

A physiological model, consisting of an insulin model, a meal model, and a glucose metabolism model in combination with a Monte Carlo simulation, was used for this investigation. It was used to examine the change in blood glucose following the intake of carbohydrate and insulin. The intra-individual variability, which was studied, included pharmacokinetic variability of insulin aspart and estimation error of carbohydrate intake, as well as the accuracy of blood glucose meters and insulin pens.

RESULTS

Simulations showed how the coefficient of variance for the different model compartments changes over time. For average people with diabetes the inaccuracies of blood glucose meters and carbohydrate estimates contribute to more than half of the variance.

CONCLUSION

We showed how blood glucose prediction is severely affected by the inaccuracy in the input variables. Metabolic fluctuations, causing variability in insulin dynamics, also display important effects, but these are difficult to change. The inaccuracy of carbohydrate counting and the use of blood glucose meters appear to be the two main sources of error, which can be reduced through better patient education.

Decision support for diagnosis of lyme disease

This paper describes the development of a Bayesian model for diagnosis of patients suspected of Lyme disease, and the integration of such a model into a medical information system. A Bayesian network incorporating the clinical history and laboratory results has been constructed. Because many of the symptoms are not exclusive to Lyme disease and they develop over time, the clinical history is important for making the correct diagnosis. The model is based on time slices, where each time slice contains the observed pathological picture from one consultation with for example, the general practitioner. Since the time intervals between consultations typically are not equivalent, we have developed a novel method that can handle non-equivalent time intervals between the time slices in the network. The method is based on a description of the general development pattern of Lyme disease, which is implemented in a model that states the conditional probabilities of experiencing a certain pathological picture given time since infection. The model has been integrated into a web-based medical information system, called Borrelia Systems, which has enabled us to evaluate the model during a progressive diagnostic process. The integration has been accomplished through the development of a Bayesian Application Framework. This framework specifies a communication data structure in XML providing a graphical user interface and database components, which can be used when developing systems that are based on Bayesian networks. The framework generalizes the integration of Bayesian networks so that it is possible to switch network without manually having to update or change the system.

Use of the Internet to optimize self-management of type 1 diabetes: preliminary experience with DiasNet

Six patients with type 1 diabetes participated in a pilot trial. Their median age was 36 years (range 29-61) and the median duration of diabetes was 10 years (range 3-29). They were asked to enter, from their home or work PC, blood glucose values, insulin doses and a food diary. From the data entered, a computer model generated a simulation of the blood glucose concentration for the data collection period. It could then suggest alternative insulin doses (or regimes), or meal sizes, to reduce the risk of hypo- and hyperglycaemia. During a six-month study, patients entered a median of five sets of data (range two to eight). Feedback from participants revealed that while the system was helpful, difficulties with data entry hindered its use. Information gained from this exercise is shaping further development of the system.

Copability, coping, and learning as focal concepts in the evaluation of computerised diabetes disease management

INTRODUCTION

Within diabetes care, the majority of health decisions are in the hands of the patient. Therefore, the concepts of disease management and self-care represent inescapable challenges for both patient and healthcare professionals, entailing a considerable amount of learning. Thus, a computerised diabetes disease management systems (CDDM) is to be seen not merely as tools for the medical treatment, but also as pedagogical tools to enhance patient competence.

HYPOTHESIS

The unfortunate lack of success for most knowledge-based systems might be related to the problem of finding an adequate way of evaluating the systems from their development through the implementation phase to the daily clinical practice. The following presents the initial methodological considerations for evaluating the usefulness of a CDDM system called DiasNet, which is being implemented as a learning tool for patients. The evaluation of usefulness of a CDDM, we claim, entails clinical assessment taking into account the challenges and pitfalls in diabetes disease management.

RESULTS

Drawing on activity theory, we suggest the concept of copability as a supplement to 'usability' and 'utility' when determining 'usefulness'. We maintain that it is necessary to ask how well the user copes with the new situation using the system. As ways to measure copability of DiasNet the concepts of coping and learning are discussed, as well as ways this methodology might inform systems development, implementation, and daily clinical practice.

The relationship between age and colour content in fundus images

INTRODUCTION

The morphological appearance of the ocular fundus is one of the key parameters used in the diagnosis and management of retinal disease. However, optical imperfections in the refractive media result in blurring, low luminance and contrast, and changes in the colour composition of the image which can be seen as an increasing yellowish appearance with age. The introduction of a method for quantifying this age-related change in colour content may help in diagnosing and grading pathological changes in the eye lens which are secondary to ocular and systemic diseases.

METHODS

A total of 102 digitized fundus images from 102 healthy subjects (mean age = 50.4 years, range 7.0-94.3 years) were used to build a model for estimating the age of the subject from the colour content of the images.

RESULTS

Estimation of age from the fundus images could be done within approximately 16 years. This variation could be reduced considerably by analysis of repeated photographs from the same examination.

CONCLUSION

The colour content of fundus images can be used to estimate the ages of healthy subjects. Furthermore, when the colour content of fundus images deviates from that expected according to subject age, this may indicate causes other than age of increased light absorption in the lens, such as cumulative exposure to hyperglycaemia in diabetic patients. This could potentially be used to identify patients with undiagnosed type 2 diabetes in the general population and help to establish their risk of developing late diabetic complications as the cumulative exposure to hyperglycaemia is unknown at the time of diagnosis of the disease.

Using the internet in patient-centred diabetes care for communication, education, and decision support

The New England Journal of Medicine 329 (1993) 977- The present paper describes two systems for communication, education, and decision support in patient-centred diabetes care. Both systems are developed under the assumption that while the clinical resources in the health care sector are limited, patients' resources and new information technology may be able to play a much more central role. With DiasNet patients can experiment with their own data. They can, retrospectively, adjust insulin doses or meals sizes, and thereby learn how to cope with various situations. DiabVision, brings together algorithms for detection of retinal lesions in digital images and for aligning time series of retinal images. While the former algorithms are aimed at automated procedures for screening for diabetic retinopathy, the latter can be used to enable motivated patients to see the actual retinal lesions in their own eyes, illustrating how the changes appear, and perhaps disappear, as a consequence of changes in lifestyle and glycaemic control. One of the long-term goals of our work is to assess the potential of integrating all health related information for patients with diabetes and other major chronic diseases. One solution to these problems would be to organise data and information as one virtual database, which then could be accessed by both health professionals and by patients. This structure would facilitate easy access, a clear overview, and quality control. A web site taking the first step in this process has been launched.

Activity theory and medical informatics: usability, utility, and copability

Working with health care today also means working with IT-systems. 'Human Factors' or 'user-friendly design' has been renowned as key factors for the development of safe and successful systems in many industries, not least in the IT-business. Likewise in the computerization of health care, the concepts of 'usefulness' and 'usability' will become key issues in the daily life (and death) in health care context at hospitals, at the GP's office, and in the home of the patient. Though it is a pressing problem, the literature is still very scarce on how to meet this challenge. Inspired by activity theory, this paper sets out to coin a term for an important way to ask questions when determining the usefulness of a medical IT-system. We normally ask two types of questions: 'How usable is the system?' (usability), and 'How functional is the system?' (utility). But most important, we will also have to ask: 'How well does the user cope with the new situation?' As a concept for the latter way of asking questions, we will suggest the term 'copability'.

Diabetes patients' ability to estimate dietary carbohydrate content for use in a decision support system

The aim of the study was to assess Type 1 (insulin-dependent) diabetic patients' ability to give valid information of the dietary carbohydrate (CHO) intake and to use the log function of a blood glucose meter for easy transfer of data to a decision support system. 18 Type 1 diabetic patients were enrolled from the Diabetes Outpatient Clinic at the Department of Endocrinology, Aalborg Hospital, Denmark. The patients were divided in subgroups of 4 or 5 patients and was instructed by the dietitian how to estimate the CHO intake and by the doctor in the use of the Accutrend DM blood glucose meter. During a 3 days data collecting period the patients were asked to keep a written diary containing a description of the meals, the estimated CHO intake, the insulin-dosage and the time of the meals and insulin injections, and to make 8-point blood glucose profiles daily. They were furthermore asked to use the log function of the Accutrend DM blood glucose meter. At the second visit the data were discussed individually with the patients and if there where more than three data points missing using the log function the patients were asked to repeat the data collection. A deviation of 10 grams or more, between the patient's and the dietician's estimate, was seen in 7.3% of the meals following the first instruction, in 1.0% of the meals following the second instruction, and in 2.4% of the meals following the third and last instruction. In conclusion, this study showed that Danish Type 1 diabetic patients were able to estimate the dietary carbohydrate content with a high degree of correctness, and to use the log function of the blood glucose meter, after a maximum of 3 hours of training.