HbA1c testing in the community pharmacy: A new strategy to improve care for patients with diabetes
Bibliographic record
Abstract
Diabetes is one of the fastest growing diseases in Canada. It is estimated that 2 million Canadians have type 2 diabetes and that there are more than 60,000 new cases of this disease diagnosed each year. The cost of diabetes in Canada is projected to be up to $9 billion annually.1 One-third of those affected with type 2 diabetes are unaware that they have the disease.1 Managing diabetes is a challenging endeavour for those diagnosed and involves routine monitoring and regular testing in order for patients to maintain reasonable glycemic control. The DICE study in 2005 found that 1 in 2 Canadians with type 2 diabetes do not have their blood sugar under control and that control is worse the longer patients have had diabetes.2 As a measure of glycemic control, the Canadian Diabetes Association (CDA) recommends glycated hemoglobin (HbA1c [%]) levels ≤7.0.3 However, according to one study, only 29% of patients with diabetes actually had an HbA1c test in the previous year, and among those tested, only 43% had an HbA1c less than 7%.4 Additionally, 18% of those tested had an HbA1c of 9.5% or more, meaning that their blood glucose levels were uncontrolled.4 Given the complexity of diabetes control, evidence suggests that diabetes can be best managed through an interdisciplinary team that includes a pharmacist.5 The relative accessibility of the community pharmacist allows patients the opportunity to discuss their health care concerns, typically without the need for a referral or appointment (though making an appointment so that the pharmacist is able to set aside an appropriate amount of time is becoming more common). This unique position allows pharmacists to readily monitor patients and assist them in attaining adequate glucose control. HbA1c testing is an important outcome measure in patients with diabetes. Unlike a point-in-time blood glucose measure, the HbA1c provides an estimate of glycemic control over a 3-month period. It allows the health care provider to monitor patients with diabetes and estimate how well their disease is controlled and whether they require additional interventions to maintain target levels. The United Kingdom Prospective Diabetes Study (UKPDS) has shown that lower HbA1c levels have been correlated with fewer complications.6 For instance, in epidemiologic analyses, HbA1c levels >7.0% are associated with a significantly increased risk of both microvascular and macrovascular complications, regardless of underlying treatment.3 John Papastergiou Pharmacy Limited operates at 3 locations as Shoppers Drug Mart in Toronto, Ontario. All 3 pharmacies are located in an urban setting with a diverse, multi-ethnic patient population. The Pharmacy team, including pharmacists, pharmacy technicians, interns and pharmacy students from all 3 locations, is working to improve the management of patients with diabetes through the use of HbA1c testing. Historically, the testing of HbA1c required a visit to the physician and was limited to a laboratory blood test. With the introduction of the Bayer A1C Now meters, patients can be tested by their community pharmacist without a laboratory requisition and HbA1c results can be made available within 5 minutes. The HbA1c meter has demonstrated an accuracy of 99% in 3 independent evaluation studies.7 The Pharmacy team decided that the level of accuracy, in combination with the ease and speed of testing, made this new innovation the perfect tool for testing and monitoring their patients with diabetes. The meters provide an efficient and reliable method for HbA1c monitoring. The HbA1c result provides the pharmacist with more information regarding the patient's glycemic control and allows for additional consultation and recommendations in an attempt to improve outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.009 | 0.015 |
| Insufficient payload (model declined to judge) | 0.038 | 0.012 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".