Automated glycemic pattern analysis: overcoming diabetes clinical inertia

Assessing quality of glycemic control: Hypo- and hyperglycemia, and glycemic variability using mobile self-monitoring of blood glucose system

Although mobile applications bring potential benefits of metabolic control for patients with diabetes, their effect on glycemic fluctuation has been less widely explored. The goal of this study was to utilize data from the Mobile Self-Monitoring of Blood Glucose System to obtain a picture of the metabolic progression. Twenty-seven adults with type 2 diabetes mellitus were recruited to receive a mobile diabetes self-care system for a six-week period. The approach to the interpretation of glycemic control patterns, utilizes the following methods: 1) Graphical displays of the percentage of hyper-and-hypoglycemia episodes; 2) Pattern recognition of glycemic variability based on a simple equation involving both the standard deviation and the mean. Analytical results reveal that short-term usage of the developed system stabilizes the week-by-week glycemic fluctuations. Four categories were established to distinguish different patterns of patients' glycemic variation. If patterns of glycemic control can be recognized or interpreted by newly designed mobile applications, then the collection and analysis of metabolic variation will greatly help both health care providers and patients in effective diabetes management.

Clinical inertia and its impact on treatment intensification in people with type 2 diabetes mellitus

Many people with type 2 diabetes mellitus (T2DM) fail to achieve glycaemic control promptly after diagnosis and do not receive timely treatment intensification. This may be in part due to 'clinical inertia', defined as the failure of healthcare providers to initiate or intensify therapy when indicated. Physician-, patient- and healthcare-system-related factors all contribute to clinical inertia. However, decisions that appear to be clinical inertia may, in fact, be only 'apparent' clinical inertia and may reflect good clinical practice on behalf of the physician for a specific patient. Delay in treatment intensification can happen at all stages of treatment for people with T2DM, including prescription of lifestyle changes after diagnosis, introduction of pharmacological therapy, use of combination therapy where needed and initiation of insulin. Clinical inertia may contribute to people with T2DM living with suboptimal glycaemic control for many years, with dramatic consequences for the patient in terms of quality of life, morbidity and mortality, and for public health because of the huge costs associated with uncontrolled T2DM. Because multiple factors can lead to clinical inertia, potential solutions most likely require a combination of approaches involving fundamental changes in medical care. These could include the adoption of a person-centred model of care to account for the complex considerations influencing treatment decisions by patients and physicians. Better patient education about the progressive nature of T2DM and the risks inherent in long-term poor glycaemic control may also reinforce the need for regular treatment reviews, with intensification when required.

Family physician clinical inertia in glycemic control among patients with type 2 diabetes

Background

Many patients with diabetes do not achieve target values. One of the reasons for this is clinical inertia. The correct explanation of clinical inertia requires a conjunction of patient with physician and health care system factors. Our aim was to determine the rate of clinical inertia in treating diabetes in primary care and association of patient, physician, and health care setting factors with clinical inertia.

Material/Methods

This was a national, multicenter, observational, cross-sectional study in primary care in Croatia. Each family physician (FP) provided professional data and collected clinical data on 15–25 type 2 diabetes (T2DM) patients. Clinical inertia was defined as a consultation in which treatment change based on glycated hemoglobin (HbA1c) levels was indicated but did not occur.

Results

A total of 449 FPs (response rate 89.8%) collected data on 10275 patients. Mean clinical inertia per FP was 55.6% (SD ±26.17) of consultations. All of the FPs were clinically inert with some patients, and 9% of the FPs were clinically inert with all patients. The main factors associated with clinical inertia were: higher percentage of HbA1c, oral anti-diabetic drug initiated by diabetologist, increased postprandial glycemia and total cholesterol, physical inactivity of patient, and administration of drugs other than oral antidiabetics.

Conclusions

Clinical inertia in treating patients with T2DM is a serious problem. Patients with worse glycemic control and those whose therapy was initiated by a diabetologist experience more clinical inertia. More research on causes of clinical inertia in treating patients with T2DM should be conducted to help achieve more effective diabetes control.