scholarly journals Optimal cut-off points for adherence measure among patients with type 2 diabetes in primary care clinics: a retrospective analysis

2021 ◽  
Vol 12 ◽  
pp. 204062232199026
Author(s):  
Ming Tsuey Lim ◽  
Norazida Ab Rahman ◽  
Xin Rou Teh ◽  
Chee Lee Chan ◽  
Shantini Thevendran ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Primary Care ◽  
Medication Adherence ◽  
Poor Adherence ◽  
Adherence Measure ◽  
Primary Care Clinics ◽  
Assessment Period ◽  
Hba1c Target ◽  
Optimal Adherence

Background: Medication adherence measures are often dichotomized to classify patients into those with good or poor adherence using a cut-off value ⩾80%, but this cut-off may not be universal across diseases or medication classes. This study aimed to examine the cut-off value that optimally distinguish good and poor adherence by using the medication possession ratio (MPR) and proportion of days covered (PDC) as adherence measures and glycated hemoglobin (HbA1c) as outcome measure among type 2 diabetes mellitus (T2DM) patients. Method: We used pharmacy dispensing data of 1461 eligible T2DM patients from public primary care clinics in Malaysia treated with oral antidiabetic drugs between January 2018 and May 2019. Adherence rates were calculated during the period preceding the HbA1c measurement. Adherence cut-off values for the following conditions were compared: adherence measure (MPR versus PDC), assessment period (90-day versus 180-day), and HbA1c target (⩽7.0% versus ⩽8.0%). Results: The optimal adherence cut-offs for MPR and PDC in predicting HbA1c ⩽7.0% ranged between 86.1% and 98.3% across the two assessment periods. In predicting HbA1c ⩽8.0%, the optimal adherence cut-offs ranged from 86.1% to 92.8%. The cut-off value was notably higher with PDC as the adherence measure, shorter assessment period, and a stricter HbA1c target (⩽7.0%) as outcome. Conclusion: We found that optimal adherence cut-off appeared to be slightly higher than the conventional value of 80%. The adherence thresholds may vary depending on the length of assessment period and outcome definition but a reasonably wise cut-off to distinguish good versus poor medication adherence to be clinically meaningful should be at 90%.

scholarly journals Quality of Life and Associated Factors among Primary Care Asian Patients with Type 2 Diabetes Mellitus

2019 ◽  
Vol 16 (19) ◽  
pp. 3561 ◽  
Author(s):  
Hardesh Dhillon ◽  
Rusli Bin Nordin ◽  
Amutha Ramadas
Keyword(s):  
Quality Of Life ◽  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Primary Care ◽  
Type 2 Diabetes Mellitus ◽  
Medication Adherence ◽  
Well Being ◽  
Care Clinic

Diabetes complications, medication adherence, and psychosocial well-being have been associated with quality of life (QOL) among several Western and Asian populations with diabetes, however, there is little evidence substantiating these relationships among Malaysia’s unique and diverse population. Therefore, a cross-sectional study was conducted in a Malaysian public primary care clinic among 150 patients diagnosed with type 2 diabetes mellitus (T2DM). Structured and validated questionnaires were used to investigate the associations between demographic, clinical, and psychological factors with QOL of the study participants. Approximately three-quarters of patients had a good-excellent QOL. Diabetes-related variables that were significantly associated with poor QOL scores included insulin containing treatment regimens, poor glycemic control, inactive lifestyle, retinopathy, neuropathy, abnormal psychosocial well-being, higher diabetes complication severity, and nonadherence (p < 0.05). The main predictors of a good-excellent QOL were HbA1c ≤ 6.5% (aOR = 20.78, 95% CI = 2.5175.9, p = 0.005), normal anxiety levels (aOR = 5.73, 95% CI = 1.8–18.5, p = 0.004), medication adherence (aOR = 3.35, 95% CI = 1.3–8.7, p = 0.012), and an aDCSI score of one and two as compared to those greater than or equal to four (aOR = 7.78, 95% CI = 1.5–39.2, p = 0.013 and aOR = 8.23, 95% CI = 2.1–32.8, p = 0.003), respectively. Medication adherence has also been found to be an effect modifier of relationships between HbA1c, depression, anxiety, disease severity, and QOL. These predictors of QOL are important factors to consider when managing patients with T2DM.

Management of Patients with Type 2 Diabetes by Pharmacists in Primary Care Clinics

1998 ◽  
Vol 32 (6) ◽  
pp. 636-641 ◽  
Author(s):  
Elizabeth A Coast-Senior ◽  
Beverly A Kroner ◽  
Catherine L Kelley ◽  
Lauren E Trilli
Keyword(s):  
Type 2 Diabetes ◽  
Primary Care ◽  
Blood Glucose ◽  
Glycemic Control ◽  
Glycosylated Hemoglobin ◽  
Fasting Blood Glucose ◽  
Face To Face ◽  
Primary Care Clinics ◽  
Blood Glucose Concentrations

OBJECTIVE: To determine the impact of clinical pharmacists involved in direct patient care on the glycemic control of patients with type 2 diabetes mellitus. DESIGN: Eligible patients included those with type 2 diabetes who received insulin or were initiated on insulin therapy by the pharmacists and were willing to perform self-monitoring of blood glucose. The pharmacists provided diabetes education, medication counseling, monitoring, and insulin initiation and/or adjustments. All initial patient interactions with the pharmacists were face-to-face. Thereafter, patient–pharmacist interactions were either face-to-face or telephone contacts. SETTING: Two primary care clinics in a university-affiliated Veterans Affairs Medical Center. PARTICIPANTS: Study subjects were patients with type 2 diabetes who were referred to the pharmacists by their primary care providers for better glycemic control. OUTCOME MEASURES: Primary outcome variables were changes from baseline in glycosylated hemoglobin, fasting blood glucose, and random blood glucose measurements. Secondary outcomes were the number and severity of symptomatic episodes of hypoglycemia, and the number of emergency room visits or hospitalizations related to diabetes. Twenty-three veterans aged 65 ± 9.4 years completed the study. Fifteen (65%) patients were initiated on insulin by the pharmacists; 8 (35%) were already using insulin. Patients were followed for a mean ± SD of 27 ± 10 weeks. Glycosylated hemoglobin, fasting blood glucose concentrations, and random blood glucose concentrations significantly decreased from baseline by 2.2% (p = 0.00004), 65 mg/dL (p < 0.01), and 82 mg/dL (p = 0.00001), respectively. Symptomatic hypoglycemic episodes occurred in 35% of patients. None of these episodes required physician intervention. CONCLUSIONS: This study demonstrates that pharmacists working as members of interdisciplinary primary care teams can positively impact glycemic control in patients with type 2 diabetes requiring insulin.

scholarly journals A Highly Tailored Text and Voice Messaging Intervention to Improve Medication Adherence in Patients With Either or Both Hypertension and Type 2 Diabetes in a UK Primary Care Setting: Feasibility Randomized Controlled Trial of Clinical Effectiveness

10.2196/16629 ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. e16629 ◽  
Author(s):  
Aikaterini Kassavou ◽  
Venus Mirzaei ◽  
James Brimicombe ◽  
Simon Edwards ◽  
Efthalia Massou ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Primary Care ◽  
Randomized Controlled Trial ◽  
Medication Adherence ◽  
Controlled Trial ◽  
Intervention Group ◽  
Clinical Effectiveness ◽  
Control Group ◽  
Randomized Controlled

Background The efficacy of a highly tailored digital intervention to support medication adherence and feasibility to support clinical effectiveness as an adjunct to the primary care setting has not been evaluated. Objective This trial aimed to assess the behavioral efficacy of a highly tailored digital intervention to support medication adherence and to evaluate the feasibility of its clinical effectiveness, in patients with either or both hypertension and type 2 diabetes. We also examined quality of life and mechanisms of behavior change. Intervention fidelity, engagement, and satisfaction were also explored. Methods This was a multicenter, individually randomized controlled trial of 2 parallel groups: an intervention group that received a highly tailored text message and interactive voice response intervention for 12 weeks, and a control group that received usual care. Medication adherence was measured using self-reports and assessor-blinded practice records of a repeat prescription. Systolic blood pressure and glucose levels were assessed by nurses blinded to group allocation during practice visits at 3 months follow-up. Questionnaires obtained data to assess intervention mechanisms of action and satisfaction and digital log files captured data to evaluate fidelity and engagement. Results A total of 135 nonadherent patients (62/135, 46% female; 122/135, 90.3%; aged above 50 years) were randomly allocated in the intervention (n=79) or in the control group (n=56); of whom 13% (18/135) were lost at follow-up. Medication adherence was significantly improved in the intervention group compared with the control group (t116=2.27; P=.02, 2-tailed). Systolic blood pressure was 0.6 mmHg (95% CI −7.423 to 6.301), and hemoglobin A1c was 4.5 mmol/mol (95% CI −13.099 to 4.710) lower in the intervention group compared with the control group. Changes in intentional nonadherence and nonintentional nonadherence explained the improvements in medication adherence in the intervention group (beta=.074, SE=0.464; P=.04), but not in the control group (beta=.00, SE 1.35; P=.37). The intervention had 100% fidelity, a median of 12 days of engagement, and 76% overall satisfaction. Conclusions Our trial is the first that has been conducted in the United Kingdom and showed that among nonadherent patients with either or both hypertension and type 2 diabetes, a highly tailored digital intervention was effective at improving treatment adherence and feasible to obtain clinically meaningful outcomes. Changes in intentional and nonintentional nonadherence predicted the improvements in medication adherence. The intervention had high fidelity, engagement, and satisfaction. Future research using a rigorous design is needed to evaluate the clinical effectiveness and cost-effectiveness of the intervention in primary care. Trial Registration International Standard Randomized Controlled Trial Number (ISRCTN) 10668149; http://www.controlled-trials.com/ISRCTN10668149.

scholarly journals Current Management of Type 2 Diabetes Mellitus in Primary Care Clinics in Korea

2019 ◽  
Vol 34 (3) ◽  
pp. 282 ◽  
Author(s):  
Da Hea Seo ◽  
Shinae Kang ◽  
Yong-ho Lee ◽  
Jung Yoon Ha ◽  
Jong Suk Park ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Primary Care ◽  
Type 2 Diabetes Mellitus ◽  
Current Management ◽  
Primary Care Clinics

scholarly journals Making sense of diabetes medication decisions: a mixed methods cluster randomized trial using a conversation aid intervention

Endocrine ◽  
2021 ◽  
Author(s):  
Marleen Kunneman ◽  
Megan E. Branda ◽  
Jennifer L. Ridgeway ◽  
Kristina Tiedje ◽  
Carl R. May ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Primary Care ◽  
Decision Making ◽  
Mixed Methods ◽  
Medication Adherence ◽  
Usual Care ◽  
Cluster Randomized Trial ◽  
Patient Knowledge ◽  
Cluster Randomized

Abstract Purpose To determine the effectiveness of a shared decision-making (SDM) tool versus guideline-informed usual care in translating evidence into primary care, and to explore how use of the tool changed patient perspectives about diabetes medication decision making. Methods In this mixed methods multicenter cluster randomized trial, we included patients with type 2 diabetes mellitus and their primary care clinicians. We compared usual care with or without a within-encounter SDM conversation aid. We assessed participant-reported decisions made and quality of SDM (knowledge, satisfaction, and decisional conflict), clinical outcomes, adherence, and observer-based patient involvement in decision-making (OPTION12-scale). We used semi-structured interviews with patients to understand their perspectives. Results We enrolled 350 patients and 99 clinicians from 20 practices and interviewed 26 patients. Use of the conversation aid increased post-encounter patient knowledge (correct answers, 52% vs. 45%, p = 0.02) and clinician involvement of patients (Mean between-arm difference in OPTION12, 7.3 (95% CI 3, 12); p = 0.003). There were no between-arm differences in treatment choice, patient or clinician satisfaction, encounter length, medication adherence, or glycemic control. Qualitative analyses highlighted differences in how clinicians involved patients in decision making, with intervention patients noting how clinicians guided them through conversations using factors important to them. Conclusions Using an SDM conversation aid improved patient knowledge and involvement in SDM without impacting treatment choice, encounter length, medication adherence or improved diabetes control in patients with type 2 diabetes. Future interventions may need to focus specifically on patients with signs of poor treatment fit. Clinical trial registration ClinicalTrial.gov: NCT01502891.

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