Development and evaluation of an intelligent handheld insulin dose advisor for patients with Type-1 diabetes

Diabetes mellitus is an increasingly common, chronic, incurable disease requiring careful monitoring and treatment so as to minimise the risk of serious long-term complications. It has been suggested that computers used by healthcare professionals and/or patients themselves may playa useful role in the diabetes care process. Seven key systems (AIDA, ADICOL, DIABETES, DIAS, IIumaLink, T-IDDM, POIRO) in the area of diabetes decision support, and their underlying techniques and approaches are summarised and compared. The development of the Patient-Oriented Insulin Regimen Optimiser (POIRO) for insulindependent (Type-I) diabetes, and its hybrid statistical and rule-based expert system is then taken forward. The re-implementation and updating of the system for the Palm OS family of modern Personal Digital Assistants (PDAs) is described. The evaluation of this new version in a seven week, randomised, open, cross-over clinical pilot study involving eight patients on short-acting plus long-acting insulin basalbolus regimens showed it to be easy-to-operate, reliable, not time consuming and well liked by patients. Following this, the characteristics and use of all currently available insulin formulations, and the corresponding insulin regimens are summarised. Algorithms to provide dose advice and decision support for patients taking the new rapid-acting, intermediate-acting and premixed insulin formulations are then developed. The user interface is improved and extended, amongst others through the development and use of a model describing individual user's meal time habits. Implementation-related issues encountered are discussed, and further work and future directions are identified and outlined. Motivated by the complex and safety-critical nature of systems such as POIRO, we also report on the use of the B abstract machine notation for the formal specification of the original POIRO system, and focusing on projects and published case studies. review the use of formal methods in the development of medical computer systems

The few touch digital diabetes diary : user-involved design of mobile self-help tools for peoplewith diabetes

Paper number 2, 4, 5 and 7 are not available in Munin, due to publishers' restrictions: 2. Årsand E, and Demiris G.: "User-Centered Methods for Designing Patient-Centric Self-Help Tools", Informatics for Health and Social Care, 2008 Vol. 33, No. 3, Pages 158-169 (Informa Healthcare). Available at http://dx.doi.org/10.1080/17538150802457562 4. Årsand E, Olsen OA, Varmedal R, Mortensen W, and Hartvigsen G.: "A System for Monitoring Physical Activity Data Among People with Type 2 Diabetes", pages 173-178 in S.K. Andersen, et.al. (eds.) "eHealth Beyond the Horizon - Get IT There", Proceedings of MIE2008, Studies in Health Technology and Informatics, Volume 136, May 2008, ISBN: 978-1-58603-864-9 5. Årsand E, Tufano JT, Ralston J, and Hjortdahl P.: "Designing Mobile Dietary Management Support Technologies for People with Diabetes", Journal of Telemedicine and Telecare, 2008 Volume 14, Number 7, Pp. 329-332 (Royal Society of Medicine Press). Available at http://dx.doi.org/10.1258/jtt.2008.007001 7. Årsand E, Walseth OA, Andersson N, Fernando R, Granberg O, Bellika JG, and Hartvigsen G.: "Using Blood Glucose Data as an Indicator for Epidemic Disease Outbreaks", pages 199-204 in R. Engelbrecht et.al. (eds.): "Connecting Medical Informatics and Bio-Informatics", Proceedings of MIE2005, Studies in Health Technology and Informatics, Volume 116, August 2005, ISBN: 978-1-58603-549-5. Check availabilityParadoxically, the technological revolution that has created a vast health problem due to a drastic change in lifestyle also holds great potential for individuals to take better care of their own health. The first consequence is not addressed in this dissertation, but the second represents the focus of the work presented, namely utilizing ICT to support self-management of individual health challenges. As long as only 35% of the patients in Norway achieve the International Diabetes Federation‟s goal for blood glucose (HbA1c), actions and activities to improve blood glucose control and related factors are needed. The presented work focuses on the development and integration of alternative sensor systems for blood glucose and physical activity, and a fast and effortless method for recording food habits. Various user-interface concepts running on a mobile terminal constitute a digital diabetes diary, and the total concept is referred to as the “Few Touch application”. The overall aim of this PhD project is to generate knowledge about how a mobile tool can be designed for supporting lifestyle changes among people with diabetes. Applying technologies and methods from the informatics field has contributed to improved insight into this issue. Conversely, addressing the concrete use cases for people with diabetes has resulted in the achievement of ICT designs that have been appreciated by the cohorts involved. Cooperation with three different groups of patients with diabetes over several years and various methods and theories founded in computer science, medical informatics, and telemedicine have been combined in design and research on patient-oriented aids. The blood glucose Bluetooth adapter, the step counter, and the nutrition habit registration system that have been developed were all novel and to my knowledge unique designs at the time they were first tested, and this still applies to the latter two. Whether it can be claimed that the total concept presented, the Few Touch application, will increase quality of life, is up to future research and large-scale tests of the system to answer. However, results from the Type 2 diabetes half-year study showed that several of the participants did adjust their medication, food habits and/or physical activity due to use of the application

Development of AIDA v4.3b diabetes simulator: Technical upgrade to support incorporation of lispro, aspart, and glargine insulin analogues

Introduction. AIDA is an interactive educational diabetes simulator available on the Internet without charge since 1996 (accessible at: http://www.2aida.org/). Since the program’s original release, users have developed new requirements, with new operating systems coming into use and more complex insulin management regimens being adopted. The current work has aimed to design a comprehensive diabetes simulation system from both a clinical and information technology perspective. Methods. A collaborative development is taking place with a new generic model of subcutaneous insulin absorption, permitting the simulation of rapidly-acting and very long-acting insulin analogues, as well as insulin injections larger than 40 units. This novel, physiological insulin absorption model has been incorporated into AIDA v4. Technical work has also been undertaken to install and operate the AIDA software within a DOSBox emulator, to ensure compatibility with Windows XP, Vista and 7 operating systems as well as Apple Macintosh computers running Parallels PC emulation software. Results. Plasma insulin simulations are demonstrated following subcutaneous injections of a rapidly-acting insulin analogue, a short-acting insulin preparation, intermediate-acting insulin, and a very long-acting insulin analogue for injected insulin doses up to 60 units of insulin. Discussion. The current work extends the useful life of the existing AIDA v4 program.Lehmann, ED.; Tarín, C.; Bondía Company, J.; Teufel, E.; Deutsch, T. (2011). Development of AIDA v4.3b diabetes simulator: Technical upgrade to support incorporation of lispro, aspart, and glargine insulin analogues. Journal of Electrical and Computer Engineering. 2011:1-17. doi:10.1155/2011/427196S1172011Lehmann, E. D. (1996). 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Training in flexible, intensive insulin management to enable dietary freedom in people with type 1 diabetes: dose adjustment for normal eating (DAFNE) randomised controlled trial. BMJ, 325(7367), 746-746. doi:10.1136/bmj.325.7367.746Howorka, K., Pumprla, J., Wagner-Nosiska, D., Grillmayr, H., Schlusche, C., & Schabmann, A. (2000). Empowering diabetes out-patients with structured education: Journal of Psychosomatic Research, 48(1), 37-44. doi:10.1016/s0022-3999(99)00074-4Lehmann, E. . (1998). Preliminary experience with the Internet release of AIDA—an interactive educational diabetes simulator. Computer Methods and Programs in Biomedicine, 56(2), 109-132. doi:10.1016/s0169-2607(98)00019-4Lehmann, E. D. (1999). Experience with the Internet Release of AIDA v4.0 - http://www.diabetic.org.uk/aida.htm - An Interactive Educational Diabetes Simulator. Diabetes Technology & Therapeutics, 1(1), 41-54. doi:10.1089/152091599317567Lehmann, E. D. (1997). 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Medical Engineering & Physics, 16(4), 351-352. doi:10.1016/1350-4533(94)90064-7Lehmann, E. D., & Deutsch, T. (1996). Computer assisted diabetes care: a 6-year retrospective. Computer Methods and Programs in Biomedicine, 50(3), 209-230. doi:10.1016/0169-2607(96)01751-8Lehmann, E. D. (2001). Simulating Glycosylated Hemoglobin (HbA1c) Levels in Diabetes Using an Interactive Educational Virtual Diabetes Patient Simulator. Diabetes Technology & Therapeutics, 3(3), 517-524. doi:10.1089/15209150152607268Lehmann, E. D., & Deutsch, T. (1992). A physiological model of glucose-insulin interaction in type 1 diabetes mellitus. Journal of Biomedical Engineering, 14(3), 235-242. doi:10.1016/0141-5425(92)90058-sLehmann, E. D., Chatu, S. S., & Hashmy, S. S. H. (2006). Retrospective Pilot Feedback Survey of 200 Users of the AIDA Version 4 Educational Diabetes Program. 17—Quantitative Survey Data. Diabetes Technology & Therapeutics, 8(3), 419-432. doi:10.1089/dia.2006.8.419Lehmann, E. D., Chatu, S. S., & Hashmy, S. H. (2006). Retrospective Pilot Feedback Survey of 200 Users of the AIDA Version 4 Educational Diabetes Program. 2—Qualitative Feedback Data. Diabetes Technology & Therapeutics, 8(5), 602-608. doi:10.1089/dia.2006.8.602Lehmann, E. D., Chatu, S. S., & Hashmy, S. S. H. (2007). Retrospective Pilot Feedback Survey of 200 Users of the AIDA Version 4 Educational Diabetes Program. 3—Discussion. Diabetes Technology & Therapeutics, 9(1), 122-132. doi:10.1089/dia.2006.0065Binder, C., Lauritzen, T., Faber, O., & Pramming, S. (1984). Insulin Pharmacokinetics. Diabetes Care, 7(2), 188-199. doi:10.2337/diacare.7.2.188Plougmann, S., Hejlesen, O. K., & Cavan, D. A. (2001). DiasNet—a diabetes advisory system for communication and education via the internet. International Journal of Medical Informatics, 64(2-3), 319-330. doi:10.1016/s1386-5056(01)00214-3Storm, M. C., & Dunn, M. F. (1985). The Glu(B13) carboxylates of the insulin hexamer form a cage for cadmium and calcium ions. Biochemistry, 24(7), 1749-1756. doi:10.1021/bi00328a027Kurtzhals, P., & Ribel, U. (1995). Action Profile of Cobalt(III)-Insulin: A Novel Principle of Protraction of Potential Use for Basal Insulin Delivery. Diabetes, 44(12), 1381-1385. doi:10.2337/diab.44.12.1381Kobayashi, T., Sawano, S., Itoh, T., Kosaka, K., Hirayama, H., & Kasuya, Y. (1983). The Pharmacokinetics of Insulin After Continuous Subcutaneous Infusion or Bolus Subcutaneous Injection in Diabetic Patients. Diabetes, 32(4), 331-336. doi:10.2337/diab.32.4.331Berger, M., & Rodbard, D. (1989). Computer Simulation of Plasma Insulin and Glucose Dynamics After Subcutaneous Insulin Injection. Diabetes Care, 12(10), 725-736. doi:10.2337/diacare.12.10.725Mosekilde, E., Jensen, K. S., Binder, C., Pramming, S., & Thorsteinsson, B. (1989). Modeling absorption kinetics of subcutaneous injected soluble insulin. Journal of Pharmacokinetics and Biopharmaceutics, 17(1), 67-87. doi:10.1007/bf01059088Trajanoski, Z., Wach, P., Kotanko, P., Ott, A., & Skraba, F. (1993). Pharmacokinetic Model for the Absorption of Subcutaneously Injected Soluble Insulin and Monomeric Insulin - Analogues - Pharmakokinetisches Modell für die Absorption von subkutan injiziertem löslichem Insulin und monomeren Insulinanaloga. Biomedizinische Technik/Biomedical Engineering, 38(9), 224-231. doi:10.1515/bmte.1993.38.9.224Wach, P., Trajanoski, Z., Kotanko, P., & Skrabal, F. (1995). Numerical approximation of mathematical model for absorption of subcutaneously injected insulin. Medical & Biological Engineering & Computing, 33(1), 18-23. doi:10.1007/bf02522939Tarin, C., Teufel, E., Pico, J., Bondia, J., & Pfleiderer, H.-J. (2005). Comprehensive Pharmacokinetic Model of Insulin Glargine and Other Insulin Formulations. IEEE Transactions on Biomedical Engineering, 52(12), 1994-2005. doi:10.1109/tbme.2005.857681Lehmann, E. D., Tarín, C., Bondia, J., Teufel, E., & Deutsch, T. (2007). Incorporating a Generic Model of Subcutaneous Insulin Absorption into the AIDA v4 Diabetes Simulator. Journal of Diabetes Science and Technology, 1(3), 423-435. doi:10.1177/193229680700100317Lehmann, E. D., Tarín, C., Bondia, J., Teufel, E., & Deutsch, T. (2007). Incorporating a Generic Model of Subcutaneous Insulin Absorption into the AIDA v4 Diabetes Simulator 2. Preliminary Bench Testing. Journal of Diabetes Science and Technology, 1(5), 780-793. doi:10.1177/193229680700100525Lehmann, E. D., Tarín, C., Bondia, J., Teufel, E., & Deutsch, T. (2009). Incorporating a Generic Model of Subcutaneous Insulin Absorption into the AIDA v4 Diabetes Simulator 3. Early Plasma Insulin Determinations. Journal of Diabetes Science and Technology, 3(1), 190-201. doi:10.1177/193229680900300123Wong, J., Chase, J. G., Hann, C. E., Shaw, G. M., Lotz, T. F., Lin, J., & Le Compte, A. J. (2008). A Subcutaneous Insulin Pharmacokinetic Model for Computer Simulation in a Diabetes Decision Support Role: Model Structure and Parameter Identification. Journal of Diabetes Science and Technology, 2(4), 658-671. doi:10.1177/193229680800200417Wong, J., Chase, J. G., Hann, C. E., Shaw, G. M., Lotz, T. F., Lin, J., & Le Compte, A. J. (2008). A Subcutaneous Insulin Pharmacokinetic Model for Computer Simulation in a Diabetes Decision Support Role: Validation and Simulation. Journal of Diabetes Science and Technology, 2(4), 672-680. doi:10.1177/193229680800200418Kuang, Y., & Li, J. (2008). Systemically modeling the dynamics of plasma insulin in subcutaneous injection of insulin analogues for type 1 diabetes. Mathematical Biosciences and Engineering, 6(1), 41-58. doi:10.3934/mbe.2009.6.41Kang, S., Brange, J., Burch, A., Volund, A., & Owens, D. R. (1991). Subcutaneous Insulin Absorption Explained by Insulin’s Physicochemical Properties: Evidence From Absorption Studies of Soluble Human Insulin and Insulin Analogues in Humans. Diabetes Care, 14(11), 942-948. doi:10.2337/diacare.14.11.942Robertson, D. A., Singh, B. M., Hale, P. J., Jensen, I., & Nattrass, M. (1992). Metabolic Effects of Monomeric Insulin Analogues of Different Receptor Affinity. Diabetic Medicine, 9(3), 240-246. doi:10.1111/j.1464-5491.1992.tb01769.xKang, S., Owens, D. R., Vora, J. P., & Brange, J. (1990). Comparison of insulin analogue B9AspB27Glu and soluble human insulin in insulin-treated diabetes. The Lancet, 335(8685), 303-306. doi:10.1016/0140-6736(90)90602-2Bergman, R. N. (1989). Toward Physiological Understanding of Glucose Tolerance: Minimal-Model Approach. Diabetes, 38(12), 1512-1527. doi:10.2337/diab.38.12.1512Dalla Man, C., Rizza, R. A., & Cobelli, C. (2007). Meal Simulation Model of the Glucose-Insulin System. IEEE Transactions on Biomedical Engineering, 54(10), 1740-1749. doi:10.1109/tbme.2007.893506Sivitz, W. I., Davidson, P. C., Steed, D., Bode, B., & Richardson, P. (1989). Computer-Assisted Instruction in Intense Insulin Therapy Using a Mathematical Model for Clinical Simulation With a Clinical Algorithm and Flow Sheet. The Diabetes Educator, 15(1), 77-79. doi:10.1177/014572178901500120Hedbrant, J., Ludvigsson, J., & Nordenskjöld, K. (1991). Särimner: a computer model of diabetes physiology for education of physicians and patients. Diabetes Research and Clinical Practice, 14(2), 113-122. doi:10.1016/0168-8227(91)90117-vHedbrant, J., & Ludvigsson, J. (1995). Use of computer simulator training in the education of diabetic teenagers. Practical Diabetes International, 12(1), 18-21. doi:10.1002/pdi.1960120109Rutscher, A., Salzsieder, E., & Fischer, U. (1994). KADIS: model-aided education in type I diabetes. 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Dynamic Interactive Educational Diabetes Simulations Using the World Wide Web: An Experience of More Than 15 Years with AIDA Online

Background. AIDA is a widely available downloadable educational simulator of glucose-insulin interaction in diabetes. Methods. A web-based version of AIDA was developed that utilises a server-based architecture with HTML FORM commands to submit numerical data from a web-browser client to a remote web server. AIDA online, located on a remote server, passes the received data through Perl scripts which interactively produce 24 hr insulin and glucose simulations. Results. AIDA online allows users to modify the insulin regimen and diet of 40 different prestored “virtual diabetic patients” on the internet or create new “patients” with user-generated regimens. Multiple simulations can be run, with graphical results viewed via a standard web-browser window. To date, over 637,500 diabetes simulations have been run at AIDA online, from all over the world. Conclusions. AIDA online’s functionality is similar to the downloadable AIDA program, but the mode of implementation and usage is different. An advantage to utilising a server-based application is the flexibility that can be offered. New modules can be added quickly to the online simulator. This has facilitated the development of refinements to AIDA online, which have instantaneously become available around the world, with no further local downloads or installations being required

Crossing Boundaries: Patients’ Experiences of using a Diabetes eHealth System

This thesis is concerned with exploring patients’ experiences of using a diabetes eHealth system. The context of the study is the growth of interest in eHealth systems that focus on patient needs, alongside increasing home computer use and the rising incidence of chronic diseases, such as diabetes. I aim in this thesis to make a novel contribution to knowledge about how eHealth technology is experienced by patients with diabetes. The study takes the form of a qualitative enquiry into the use of a diabetes eHealth system by a group of patients and their healthcare practitioners at a primary care general practice in Northern England. Using symbolic interactionism as a methodological perspective and taking elements from grounded theory the study produces a theoretical framework based on a thematic analysis of participants’ descriptions of their experiences of using the eHealth system. A diabetes eHealth system was designed and built for the study, and 38 patients were recruited from a single GP practice using purposive sampling. Participants used the system for six months and were interviewed at the beginning, middle and end of the study period. Issues of surveillance, automation, endorsement and interaction influenced use and experiences of the system. Results from the study indicate that participants use and perceive the eHealth system as part of their diabetes management experience. My thesis is that the eHealth system is a boundary structure through which boundary objects, such as electronically formatted blood glucose readings, are created and shared across different social worlds. The eHealth system crosses the boundary between two spheres of an individual’s diabetes management experience, the personal sphere of self-management, and the external sphere of seeking and receiving support from medical experts and others with diabetes. The co-location of these two spheres exposes participants to scrutiny but also opens up new possibilities for collaboration and learning

Evaluation of using web 2.0 technologies in diabetes education for adolescent and young patients

Diabetes Mellitius is a major chronic disease with multi-organ involvement and high-cost implications. Although it has been demonstrated that structured education can control the risk of developing these complications, there is a substantial room for improvement in the educational services for these patients. E-learning can be a good solution to fill this gap. A system dynamics model was developed in this study to highlight the potential return on investment in these systems

An evidence-based approach to the use of telehealth in long-term health conditions: development of an intervention and evaluation through pragmatic randomised controlled trials in patients with depression or raised cardiovascular risk

Background: Health services internationally are exploring the potential of telehealth to support the management of the growing number of people with long-term conditions (LTCs). Aim: To develop, implement and evaluate new care programmes for patients with LTCs, focusing on two common LTCs as exemplars: depression or high cardiovascular disease (CVD) risk. Methods Development: We synthesised quantitative and qualitative evidence on the effectiveness of telehealth for LTCs, conducted a qualitative study based on interviews with patients and staff and undertook a postal survey to explore which patients are interested in different forms of telehealth. Based on these studies we developed a conceptual model [TElehealth in CHronic disease (TECH) model] as a framework for the development and evaluation of the Healthlines Service for patients with LTCs. Implementation: The Healthlines Service consisted of regular telephone calls to participants from health information advisors, supporting them to make behaviour change and to use tailored online resources. Advisors sought to optimise participants’ medication and to improve adherence. Evaluation: The Healthlines Service was evaluated with linked pragmatic randomised controlled trials comparing the Healthlines Service plus usual care with usual care alone, with nested process and economic evaluations. Participants were adults with depression or raised CVD risk recruited from 43 general practices in three areas of England. The primary outcome was response to treatment and the secondary outcomes included anxiety (depression trial), individual risk factors (CVD risk trial), self-management skills, medication adherence, perceptions of support, access to health care and satisfaction with treatment. Trial results Depression trial: In total, 609 participants were randomised and the retention rate was 86%. Response to treatment [Patient Health Questionnaire 9-items (PHQ-9) reduction of ≥ 5 points and score of < 10 after 4 months] was higher in the intervention group (27%, 68/255) than in the control group (19%, 50/270) [odds ratio 1.7, 95% confidence interval (CI) 1.1 to 2.5; p = 0.02]. Anxiety also improved. Intervention participants reported better access to health support, greater satisfaction with treatment and small improvements in self-management, but not improved medication adherence. CVD risk trial: In total, 641 participants were randomised and the retention rate was 91%. Response to treatment (maintenance of/reduction in QRISK®2 score after 12 months) was higher in the intervention group (50%, 148/295) than in the control group (43%, 124/291), which does not exclude a null effect (odds ratio 1.3, 95% CI 1.0 to 1.9; p = 0.08). The intervention was associated with small improvements in blood pressure and weight, but not smoking or cholesterol. Intervention participants were more likely to adhere to medication, reported better access to health support and greater satisfaction with treatment, but few improvements in self-management. The Healthlines Service was likely to be cost-effective for CVD risk, particularly if the benefits are sustained, but not for depression. The intervention was implemented largely as planned, although initial delays and later disruption to delivery because of the closure of NHS Direct may have adversely affected participant engagement. Conclusion: The Healthlines Service, designed using an evidence-based conceptual model, provided modest health benefits and participants valued the better access to care and extra support provided. This service was cost-effective for CVD risk but not depression. These findings of small benefits at extra cost are consistent with previous pragmatic research on the implementation of comprehensive telehealth programmes for LTCs