Decision Support for Diabetes in Scotland: Implementation and Evaluation of a Clinical Decision Support System.

BACKGROUND: Automated clinical decision support systems (CDSS) are associated with improvements in health care delivery to those with long-term conditions, including diabetes. A CDSS was introduced to two Scottish regions (combined diabetes population ~30 000) via a national diabetes electronic health record. This study aims to describe users' reactions to the CDSS and to quantify impact on clinical processes and outcomes over two improvement cycles: December 2013 to February 2014 and August 2014 to November 2014. METHODS: Feedback was sought via patient questionnaires, health care professional (HCP) focus groups, and questionnaires. Multivariable regression was used to analyze HCP SCI-Diabetes usage (with respect to CDSS message presence/absence) and case-control comparison of clinical processes/outcomes. Cases were patients whose HCP received a CDSS messages during the study period. Closely matched controls were selected from regions outside the study, following similar clinical practice (without CDSS). Clinical process measures were screening rates for diabetes-related complications. Clinical outcomes included HbA1c at 1 year. RESULTS: The CDSS had no adverse impact on consultations. HCPs were generally positive toward CDSS and used it within normal clinical workflow. CDSS messages were generated for 5692 cases, matched to 10 667 controls. Following clinic, the probability of patients being appropriately screened for complications more than doubled for most measures. Mean HbA1c improved in cases and controls but more so in cases (-2.3 mmol/mol [-0.2%] versus -1.1 [-0.1%], P = .003). DISCUSSION AND CONCLUSIONS: The CDSS was well received; associated with improved efficiencies in working practices; and large improvements in guideline adherence. These evidence-based, early interventions can significantly reduce costly and devastating complications.

Self-monitoring of blood glucose in type 2 diabetes: patients' perceptions of 'high' readings.

Among 207 non-insulin using patients with type 2 diabetes in Tayside, Scotland, who self-monitored blood glucose, we present evidence that many are tolerant of higher blood glucose levels than are clinically advisable; this may explain the lack of empirical evidence for the clinical benefits of self-monitoring in this group.

Self-monitoring among non-insulin treated patients with type 2 diabetes mellitus: Patients' behavioural responses to readings and associations with glycaemic control.

AIM: To investigate self-monitoring of blood glucose (SMBG) behaviour among non-insulin treated patients with type 2 diabetes mellitus, and to evaluate associations with glycaemic control. METHODS: Eligible patients in 23 GP practices in Tayside, Scotland, were identified (18-75 years, no insulin treatment, SMBG reagent strips dispensed in 2009). Consenting patients were administered questionnaires addressing SMBG behaviour: these primary data were record-linked to clinical data (including HbA1c) from a validated population-based diabetes clinical information system, then anonymised. RESULTS: Among 629 eligible patients, 207 were interviewed and analysed. Mean SMBG reagent strips dispensed in 12 months was 268. In response to a perceived high test result, 80 (38.8%) patients took no action or simply checked later with most of them (61.3%) indicating they did not know what action to take. Of the 126 (61.2%) patients who took some action, 101 made changes to diet, 12 increased physical activity, 10 made changes to medication and 12 mad a HCP appointment. A high score on a Diabetes Knowledge Test was a statistically significant predictor of taking action (odds ratio: 2.07). However, neither taking action nor increased SMBG frequency was associated with improved glycaemic control. CONCLUSIONS: Responding to SMBG test results and increased testing frequency were not associated with improved glycaemic control in the short-term. There is a lack of knowledge surrounding SMBG in non-insulin treated patients.

Using web technology to support population-based diabetes care.

BACKGROUND: Managed clinical networks have been used to coordinate chronic disease management across geographical regions in the United Kingdom. Our objective was to review how clinical networks and multidisciplinary team-working can be supported by Web-based information technology while clinical requirements continually change. METHODS: A Web-based population information system was developed and implemented in November 2000. The system incorporates local guidelines and shared clinical information based upon a national dataset for multispecialty use. Automated data linkages were developed to link to the master index database, biochemistry, eye screening, and general practice systems and hospital diabetes clinics. Web-based data collection forms were developed where computer systems did not exist. The experience over the first 10 years (to October 2010) was reviewed. RESULTS: The number of people with diabetes in Tayside increased from 9694 (2.5% prevalence) in 2001 to 18,355 (4.6%) in 2010. The user base remained stable (~400 users), showing a high level of clinical utility was maintained. Automated processes support a single point of data entry with 10,350 clinical messages containing 40,463 data items sent to external systems during year 10. The system supported quality improvement of diabetes care; for example, foot risk recording increased from 36% in 2007 to 73.3% in 2010. CONCLUSIONS: Shared-care datasets can improve communication between health care service providers. Web-based technology can support clinical networks in providing comprehensive, seamless care across a geographical region for people with diabetes. While health care requirements evolve, technology can adapt, remain usable, and contribute significantly to quality improvement and working practice.

Screening uptake in a well-established diabetic retinopathy screening program: the role of geographical access and deprivation.

OBJECTIVE: To identify criteria that affect uptake of diabetes retinal screening in a community screening program using mobile retinal digital photography units. RESEARCH DESIGN AND METHODS: Data from the regional diabetes population-based retinal screening program and regional ophthalmology laser database were linked to patient postal code (zip code) data. We used distance from retinal screening event, social deprivation scores, and demographic information to identify risk factors for nonattendance at a diabetes retinal screening event. Patients were subdivided into urban (>125,000 population), other urban (3,000-125,000 population), or rural (<3,000 population) depending on where they lived. Data were collected from 2004 to 2006 inclusive and included 15,150 patients and 32,621 eye screening records. RESULTS: The mean +/- SD age of patients was 63 +/- 15 years, and 54% were male. Mean travel time to retinal screening event varied from 7.1 to 17.0 min. For 12% of missed appointments, patients were more likely to be younger, to have longer diabetes duration, to have poor A1C and blood pressure control, to be smokers, and to live in deprived areas. Poor attendance was not associated with sex or distance to retinal screening event. CONCLUSIONS: Social deprivation is strongly associated with poor attendance at retinal screening events. Time traveled to screening event was not associated with attendance in this study of a mobile retinal screening service, which visited general practitioner surgeries. This data can help inform population-based diabetes retinal screening programs about improving patient uptake.

Quality measurement of care for people with type 2 diabetes in Tayside, Scotland: implications for the new UK general practice contract.

BACKGROUND: The new United Kingdom general practice contract proposes that up to a third of general practitioners' income will come from achieving quality targets. AIM: To examine selected quality markers in terms of their robustness to case-mix variation and chance effects, and in the attribution of quality to practices. STUDY DESIGN AND METHODS: Data were extracted from a population-based diabetes clinical information system in Tayside, Scotland, for patients with type 2 diabetes registered in 67 practices with complete ascertainment. RESULTS: Most practices would have received relatively high levels of payment for the process measures examined. Outcome measures appeared more challenging. Case-mix adjustment for age, sex, and postcode-assigned deprivation altered measured performance by up to 7%, but payment by up to 14%. Despite no strong evidence of any real difference in quality, chance effects meant that there was greater apparent variability for smaller practices from year to year. Hospital attendance was common, but highly variable between practices. CONCLUSION: Case-mix adjustment to allow fairer comparison is routine in national performance indicators, and ignoring it risks making the new contract quality framework inequitable. Because of chance effects, smaller practices may have greater year-to-year variability in income. Reflecting National Health Service structure, the new contract provides no incentives for integrated care and offers a perverse incentive to refer more patients to hospital. There are trade-offs between the validity of measures, and the cost and bureaucracy of collecting data. The planned evaluation of the new contrast should examine the effectiveness and equity of the quality framework, and rapidly act on deficiencies found.

A population study of first exposure to community antibacterials in children and the suitability of routine urine samples for study of the acquisition of drug resistance.

The study objectives were to measure time from birth to first exposure to antibacterials in children and compare the characteristics of children who submit urine samples with the general population. Antibacterials were dispensed to 63% of children within 1 year of birth, increasing to 75% within 2 years after birth. Boys had earlier exposure to antibacterials than girls. Children submitting urine samples were more likely to be socio-economically deprived, have prior exposure to antibacterials and have prior hospital admission. In conclusion, urine samples are unsuitable for a prospective cohort study of the relationship between antibacterial exposure and resistance in children.

Considerations on blood glucose management in Type 2 diabetes mellitus.

In recent years the benefits of more intensive management in preventing or delaying the development and progression of diabetic complications have been well documented. What is not as well documented is how to motivate the person with diabetes to manage the condition, how to set, assess and quantify glucose goals, and the glucose variables that should be routinely measured. This review discusses the importance of setting targets and communicating them in a way that the patient understands. When aiming for a glycaemia target, balance is required (1) between achieving reduction of complications and causing an increased degree of hypoglycaemia, and (2) between what is achievable and what degree of benefit is gained. Target values given in guidelines should be adapted by the clinician to take into account the patient's susceptibility to hypoglycaemia, stage and type of complications, age and life expectancy, co-morbidity, social environment, understanding of the steps required and level of commitment to the treatment. Several suggestions are given regarding possible improvements and amendments to existing guidelines for diabetes management in treating to glucose goal. For example, attention should be drawn to the need to individualize goals and to consider education, long-term support, patient needs and treatment outcome when formulating diabetes management plans. The relative properties of the different glucose variables-fasting plasma glucose (FPG), postprandial plasma glucose (PPG), glycated haemoglobin A(1c) (HbA(1c)), and glycated protein-in terms of their convenience of measurement, usefulness and relevance to the physician and patient are also evaluated. When prioritising the variables to be measured it is suggested that where feasible, HbA(1c) should be the standard measurement by which to gauge risk and treatment efficacy. Serial measurements should be made and, where possible, the use of blood glucose meters encouraged, in order to obtain a blood glucose profile for the patient.