The informatics of diabetes management
Informatics is the science of information, the practice of information processing, and the engineering of information systems (1). An early informatics driver in diabetes was the St Vincent Declaration (2), which promoted continuous quality improvement, requiring high-quality information on diabetes, its treatment, and outcomes. This led to the establishment of diabetes registers, compensating for the underdevelopment of clinical information systems. Now, electronic health records are more advanced and the common mobile phone has more computing power than the desktop computer of 20 years ago. Perhaps more important for diabetes care, information and communications technologies are now interwoven with the fabric of society, informing not only our individual behaviours but affecting our interactions with one another.
From education to pervasive persuasion
Information for patients is the cornerstone of diabetes management. Face-to-face education about diabetes care from care professionals and peers remains important, but the internet has become the primary source of information (3). There numerous websites provided by reputable diabetes organizations (e.g. Diabetes UK, Fig. 126.96.36.199) which provide simple and convenient access to relevant and accurate information to empower people to care for their diabetes. These sites provide information relating to all aspects of living with diabetes and enable people to discover about aspects of diabetes which are relevant to them at a particular time.
The quality of diabetes information published at websites varies—the measurement of this quality is sometimes referred to as ‘infodemiology’ (4). The World Wide Web, however, evolves. ‘Web 2.0’ saw much more user-generated content and interaction between users online. People with chronic diseases such as diabetes form a large part of the more complex online blogging and forums (5). In some forums content is moderated by care professionals, which may provide more reliable information (6). The emerging ‘Semantic Web’ will see content finding users rather than users having to find content. So the increasingly pervasive information about diabetes will become more persuasive, especially as the Semantic Web follows people around in mobile phones.
There are also many online forums and blogs where people share their experiences and support their community. These can provide invaluable practical advice but care should be used when choosing such websites. Those associated with, and moderated by, professional bodies are more reliable.
The recent explosion in mobile phone applications includes software to help people manage their diabetes. A typical application might help the user to collect and summarize energy intake and carbohydrate content, providing estimates of carbohydrate exchanges. The same application may collect information automatically from blood glucose meters via wireless communication between the meter and the user’s phone, uploading the results into a personal diary which can be shared with a care professional through email when the user wants additional support (Fig. 188.8.131.52). One of the main requirements for such application is to support frequent decisions, for example, based on diet, to decide how much insulin is needed with each meal. As devices themselves start to connect directly to mobile phone networks it will become easier for online applications to gather a rich variety of signals to support health care. Some of these devices may be extremely small and require very little power to operate, and could form body sensor networks. The recent release of implantable glucose sensors is a development in this direction.
Intelligent health services for diabetes care
The global rise in diabetes prevalence poses major challenges for health care systems (7). It is not only the prevalence but also that complexity of diabetes care that is challenging. The care is provided by many different people, in different locations at different times. Consequently care can become fragmented resulting in duplication of care, neglect of care or the person with diabetes being confused as to how they access appropriate care. Accurate and timely information is essential for the effective delivery and planning of diabetes care. The increasing use of electronic health records and the integration of information across primary and secondary care, is starting to facilitate better coordinated care. In Scotland a national diabetes computer system (SCI-DC: Scottish Care Information Diabetes Collaboration) has been implemented which aims to capture all aspects of diabetes care in all settings, including general practices, hospitals and the community (8). SCI-DC links the diabetes information from the patient’s primary care records with their hospital record, including biochemical data from laboratories. Carers log into the system with a specific role, granting them access only to the information that is relevant to their role. This system ensures that their care teams can communicate effectively, efficiently, and with the relevant confidentiality safeguards in place.
In England the National Diabetes Information Service integrates information from primary care to provide a national diabetes information repository that can be used to prompt, plan, and coordinate diabetes care (9). Such information can be used to trigger workflows such as entry into the national retinopathy screening programme, ensuring annual recall and allowing key performance indicators to regularly monitor care delivery.
A number of primary care information systems providers have developed tools to facilitate diabetes identification and management. As symptoms of diabetes develop insidiously there are many people with undiagnosed type 2 diabetes who consequently do not receive appropriate structured preventative care. EMIS has developed a tool that identifies people without a coded diagnosis of diabetes in whom the glucose results suggest a diagnosis of type 2 diabetes mellitus, defined as a fasting glucose >7.0 mmol/l or random glucose >11.1 mmol/l. Examining 3.6 million records revealed 3758 previously unidentified people (0.1% population) with evidence of diabetes and 32 785 people newly recognized as needing additional follow-up as the random glucose was >7.0 mmol/l. For a typical primary care practice of 7000 people this equates to 8 people having biochemical evidence of diabetes with 68 people requiring further screening (10).
Some informatics initiatives target specific end-organ damage: for example the New Opportunities for Early Renal Intervention by Computerised Assessment (NEOERICA) system (11). In NEOERICA information is extracted from primary and secondary care systems to compare each patient’s care against the chronic kidney disease (CKD) guidelines (12). This system searches for patients needing additional investigations, additional treatments or referral into renal services as their renal function, as defined by estimated glomerular filtration rate (eGFR), is declining by more than 5% per year. Such decision support tools demonstrate how informatics can support the implementation of guidelines—prompting appropriate care and, by analysing trends in results, identifying patients whose renal function is deteriorating faster than expected, thereby targeting more intensive management where it is needed most.
The coordination of contact between patients and care professionals is a major target for informatics in diabetes care: The increasing numbers of people with type 2 diabetes mellitus necessitates more efficient delivery of care. For example, using specially trained telephonists, supported by software and a diabetes nurse specialist, the Pro-Active Call Centre Treatment Support (PACCTS) for diabetes care initiative demonstrated improvements in glucose control at lower cost than increasing access to clinics (13). PACCTS used information from the local diabetes register to prompts calls to patients with type 2 diabetes at intervals based upon their HbA1c concentrations: Where HbA1c was >9.0% (75 mmol/mol) people were contacted every 4 weeks whereas where HbA1c was <7.0% (53 mmol/mol) they were contacted every 3 months. The software generated advice scripts for telecarers to use in the consultations—the scripts were adjusted according to glycaemic control and the interactions in previous calls. This enabled the telecarers to remind people of best care pathways and where relevant to suggest modifications to treatment regimens. Non-standard problems were escalated to the diabetes nurse specialist during the call. In addition to improving glucose control, PACCTS was popular with patients—the majority wanting to continue the telephone contacts routinely. The important factors were: the convenience of being able to arrange calls at a time to suit the patient; continuity of care with a telecarer; and the reduction in clinic visits (Box 184.108.40.206).
Diabetes care information systems have developed faster than overall electronic health records. It is now important to integrate diabetes informatics with other parts of clinical information systems and the emerging personal health record systems. National initiatives, such as England’s NHS National Programme for IT seek to improve the quality and safety of patient care by giving health care staff faster, easier access to reliable information so they can provide more effective treatment to patients. At first a ‘Summary Care Record’ is intended to deliver key information such as allergies and current prescriptions, later incorporating details of current health problems, summaries of the care and details of the health care staff treating the patient. This is intended to evolve into a comprehensive medical record as the constituent information systems merge over time. Patient access to their own records is key. The NHS is attempting this through HealthSpace (14), whereas corporations such as Microsoft and Google are offering patients personal health records directly. The future of health information will undoubtedly be more citizen-driven, but there are many issues of ethics, privacy, and governance to work through. For example, with the NHS Summary Care Record, a patient may refuse to allow the record, delete it or limit the type of data contained. In the NHS context, privacy and security are addressed by: managing the care record within Europe’s largest virtual private network, N3, across the NHS; using smartcards to define role-based access control and automated audits looking for unusual activity. Given an increasing acceptance of security safeguards, patients may come to expect comprehensive summaries of their care in the ‘always on’ mode of the Web. So the clinical informatics drive to provide integrated care information (e.g. Fig. 220.127.116.11) will need to interface with patient/citizen-driven health information systems effectively.
Devices for managing diabetes
Numerous studies have demonstrated that near-normal glucose control in people with type 1 diabetes mellitus reduces the development of complications but is associated with an increased risk of hypoglycaemia (15). All intensive insulin regimens, either using multiple insulin injections or insulin pumps, require frequent monitoring of home glucose concentrations.
The Ames Reflectance meter was patented in 1971 and, because of its size (18 × 9 cm) was not really suitable for home glucose monitoring. This meter required a ‘large’ drop of blood to be applied and for the result to be read at exactly 60 s for which a stopwatch was recommended. Over the past 20 years there have been huge improvements in the blood glucose meters. They have become far smaller in size therefore easier to carry; require smaller volumes of blood (0.3 μl); are very quick, typically displaying the result within 5 s and are far easier to use. These devices can typically store the results, along with the time that the test was performed, and these data can be linked into a computer to display trends and averages throughout the day enabling people to make better adjustments to their insulin therapy.
More recently has been the introduction of continuous glucose monitoring whereby the glucose is measured every few minutes. Continuous glucose sensors offer the potential to significantly increase the amount of glucose data and to provide real time glucose values enabling alarms to be set to warn of impending hypoglycaemia or hyperglycaemia. Again these data can be uploaded onto a computer to provide a graphical representation of blood glucose levels during the 24 h. This information can improve the user’s clinical decisions resulting in improved glucose control with fewer hypoglycaemic episodes.
There have also been developments in the delivery of insulin delivery with the introduction of insulin pumps, which enable the insulin rate to be programmed throughout the day providing yet another tool for improving glucose control (16). The potential for combining glucose sensors with continuous insulin infusion pumps, thereby creating an artificial pancreas where the insulin administration is controlled by the real-time glucose measurements is another example of the benefits that informatics can offer in the management of diabetes.
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