Noninsulin Diabetes Medications Research Articles

FRI268 Late Onset Polyglandular Autoimmune Syndrome Type 2

Abstract Disclosure: M.S. Nicholson: None. A. Barnett: None. A 66-year old white female was admitted for weakness, acute kidney injury, and hypotension. This is her 3rd hospital or ER visit in the last 12 months for similar complaints. She has a 25 year history of type 2 diabetes on insulin and oral therapy and 30 year history of hypothyroidism on levothyroxine 75 mcg daily. She was on oral estrogen replacement therapy for post-menopausal symptoms with a hysterectomy in her early 50s. She has a sister with type 2 diabetes on oral meds and hypothyroidism. She has a brother with type 1 diabetes. Her serum sodium was 135 mmol/L (135-145), potassium was 5.4 mEq/L (3.5 -5.1), and calcium was 9.2 (8.5-10.1). Her Creatinine was 1.2 with a GFR of 48. A random cortisol in the ED was 9.2 (no ref range). Blood pressure was low and she was tachycardic and her weight was 68 kg. She was a well developed female with a a tanned complexion. Areas of vitiligo were noted on her arms. A cosyntropin stimulation test was done midday with a baseline, 30, and 60 minute cortisol levels of 9.2, 8.8, and 9.3 respectively. Baseline ACTH was 877.6 pg/mL (7.2-63.6). Her TSH was 4.09 mIU/mL (0.358-3.74) and free T4 was 1.29 ng/dL (0.76-1.46). DHEA-S was 14 mcg/dL (13-130). She was started on stress dose steroids with rapid improvement in BP, hyponatremia, and symptoms. GAD-65 antibodies were above 250 IU/mL and 21-hydroxylase antibodies were positive. Her TPO antibodies were negative. Non-insulin diabetes medications were stopped and she was discharged home after stabilization on prednisone 5 mg daily and fludrocortisone 0.1 mg daily. This patient has an atypical presentation of polyglandular autoimmune syndrome type 2 (PAS2). She presented with an Addisons crisis at the age of 66. She was already diagnosed with hypothyroidism and insulin requiring diabetes and evidence of vitiligo. A majority of patients with PAS2 are female and present in their 20s to 40s with primary adrenal insufficiency and primary hypothyroidism. Her initial manifestation was hypothyroidism and then diabetes and vitiligo with adrenal insufficiency many years later. Her random cortisol was not suppressed and this lead to a delay in her diagnosis. This was likely due to oral estrogen therapy raising cortisol-binding globulin. Her elevated baseline ACTH and lack of response to ACTH stimulation confirmed her diagnosis of primary adrenal insufficiency. An ACTH stimulation test was repeated as an outpatient with similar response. This case highlights the importance of provocative testing for adrenal disorders and testing for autoimmune causes of endocrine disorders when patients are not responding as expected. Presentation: Friday, June 16, 2023

691-P: Closed-Loop Glycemic Control with the Insulin-Only Bionic Pancreas for the Management of Type 2 Diabetes

Closed-loop insulin delivery has been shown to improve glycemia in patients with type 1 diabetes (T1D) but fewer studies have applied these technologies to the management of type 2 diabetes (T2D). We conducted a random-order crossover feasibility study in 5 adults with T2D who used basal and prandial insulin, comparing automated glycemic control with the insulin-only bionic pancreas (BP) to usual care (UC) in the home-use setting. Each study period was one week long. Non-insulin diabetes medications besides metformin were held during the BP arm only. The BP utilized the same control algorithms previously tested in T1D. The system was initialized with participants’ body mass only; no information on insulin requirement or regimen was provided to the BP. Participants were encouraged to enter qualitative meal announcements (“typical”, “small”, or “ large” amounts of carbohydrate) for main meals but not for snacks. The BP used a target glucose of 100 mg/dl (110 mg/dl is the minimum target previously used by the insulin-only configuration in T1D studies). There was a nominal improvement in mean continuous glucose monitor (CGM) glucose in the BP compared to UC arms (137±8 vs. 153±21 mg/dl) with similar % time Disclosure J. Sherwood: None. C. A. Balliro: Consultant; Self; Beta Bionics, Inc., Novo Nordisk. M. Hillard: None. R. Selagamsetty: Employee; Self; Beta Bionics, Inc. F. El-khatib: Employee; Self; Beta Bionics, Inc., Stock/Shareholder; Self; Beta Bionics, Inc. E. Damiano: Other Relationship; Self; Beta Bionics, Inc., Stock/Shareholder; Spouse/Partner; Beta Bionics, Inc. S. J. Russell: Advisory Panel; Self; Companion Medical, ConvaTec Inc., Consultant; Self; Beta Bionics, Inc., Novo Nordisk, Other Relationship; Self; Beta Bionics, Inc., Research Support; Self; Beta Bionics, Inc., Novo Nordisk, Zealand Pharma A/S. Funding The Leona M. and Harry B. Helmsley Charitable Trust

Is it time to replace the star ratings adherence measures?

Measures of medication adherence to noninsulin diabetes medications (NIDM), statins, and renin angiotensin system antagonists (RASA) have been continuously used in the star ratings program since 2012. Adherence to these treatments is undoubtedly important. However, the consistent use of these measures in the star ratings program over time has limitations. The purpose of this Viewpoints article is to highlight concerns associated with the current star ratings adherence measures and to offer proposals for the improvement of the adherence measurement in the program. This scoping review outlines concerns with the validity of the 3 star ratings adherence measures. In addition, star ratings data are used to describe payment thresholds for the 3 adherence measures over time to describe concerns associated with their use. Since 2012, there has been significant growth in the proportion of patients considered adherent in the star ratings program. Rates of adherence in a 2-star plan for NIDM (79%), RASA agents (83%), and statins (79%) now exceed what is commonly reported in the clinical literature. For a plan to achieve a rating of 5 stars, more than 88% of patients must be adherent to each measure. These rates suggest a ceiling effect and a reduced ability to distinguish plan performance. In addition, concerns over the potential for plans to "game" these measures have been raised. The use of mail order services, 90-day prescription refill programs, and automatic refill reminders all improve the proportion of days covered measurement but may not reflect true adherence improvements. Given potential concerns associated with the use of the existing adherence measures, it may be time to consider their replacement. One option would be to adopt a broader inventory of chronic medications to measure adherence in the program and to rotate medication categories in the program each year. It might also be time to explore measuring patient adherence to all medications that a patient uses instead of the narrow focus on the 3 existing measures. DISCLOSURES: No funding supported the writing of this article. Farley has nothing to disclose. Urick reports consulting fees from Pharmacy Quality Solutions, unrelated to this work.

Evaluation of Clinical Outcomes With the V-Go Wearable Insulin Delivery Device in Patients With Type 2 Diabetes.

Uncontrolled type 2 diabetes can lead to a multitude of health complications. Insulin therapy is recommended when patients are unable to reach their A1C goal with oral or noninsulin injectable diabetes medications. This study evaluated the clinical benefits of switching from multiple daily insulin injections to a wearable insulin delivery device (V-Go). A retrospective chart review was conducted on 44 patients who received prescriptions for the V-Go at two family medicine offices. Investigators found a significant reduction in A1C and daily insulin requirements with no impact on weight or BMI.

Reasons for discontinuing insulin and factors associated with insulin discontinuation in patients with type 2 diabetes mellitus: a real-world evidence study

BackgroundEvidence suggests that insulin therapy of patients with type 2 diabetes mellitus (T2DM) is frequently discontinued. However, the reasons for discontinuing insulin and factors associated with insulin discontinuation in this patient population are not well understood.MethodsWe conducted a retrospective cohort study of adults with T2DM prescribed insulin between 2010 and 2017 at Partners HealthCare. Reasons for discontinuing insulin and factors associated with insulin discontinuation were studied using electronic medical records (EMR) data. Natural language processing (NLP) was applied to identify reasons from unstructured clinical notes. Factors associated with insulin discontinuation were extracted from structured EMR data and evaluated using multivariable logistic regression.ResultsAmong 7009 study patients, 2957 (42.2%) discontinued insulin within 12 months after study entry. Most patients who discontinued insulin (2121 / 71.7%) had reasons for discontinuation documented. The most common reasons were improving blood glucose control (33.2%), achieved weight loss (18.5%) and initiation of non-insulin diabetes medications (16.7%). In multivariable analysis adjusted for demographics and comorbidities, patients were more likely to discontinue either basal or bolus insulin if they were on a basal-bolus regimen (OR 1.6, 95% CI 1.3 to 1.8; p < 0.001) or were being seen by an endocrinologist (OR 2.6; 95% CI 2.2 to 3.0; p < 0.001).ConclusionsIn this large real-world evidence study conducted in an area with a high penetration of health insurance, insulin discontinuation countenanced by healthcare providers was common. In most cases it was linked to achievement of glycemic control, achieved weight loss and initiation of other diabetes medications. Factors associated with and stated reasons for insulin discontinuation were different from those previously described for non-adherence to insulin therapy, identifying it as a distinct clinical phenomenon.

Telepharmacy and medication adherence in urban areas

BackgroundTelepharmacies, which dispense medications on-site under the supervision of an off-site pharmacist using telecommunication technologies, have been proposed as a means to ameliorate the impact of pharmacy closures and improve access to medications. ObjectivesTo examine whether adherence varies among individuals filling prescription medications through a telepharmacy versus a traditional pharmacy in an urban neighborhood. MethodsWe conducted a retrospective cohort study using dispensing records of a traditional pharmacy and a telepharmacy, located in the same low-income Chicago neighborhood, from January 2016 to December 2018. We focused on individuals using statins (n = 1044), angiotensin-converting enzyme inhibitors (ACEs)/angiotensin II receptor blockers (ARBs) (n = 1003), or noninsulin diabetes medications (NIDMs) (n = 692). We defined adherence as a proportion of days covered greater than 80% over 12-months. We examined the association between telepharmacy use and medication adherence using logistic regressions adjusted for demographics (age and sex) and index prescription characteristics (method of payment, e-prescription, 90-day supply). ResultsTelepharmacy users were less adherent to statins (37.6% vs. 54.3%, adjusted odds ratio 0.54 [95% CI 0.38–0.76], P < 0.01) and ACEs/ARBs (41.4% vs, 56.5%, 0.61 [0.44–0.84], P < 0.01) than users of the traditional pharmacy. However, adherence to NIDMs was similar among users of the tele- and traditional pharmacies (65.5% vs. 60.1%, 1.47 [0.92–2.35], P = 0.11). Our findings were similar when we conducted a series of sensitivity analyses, including restricting our cohorts to those who only used their index pharmacy and analyzing cohorts of new rather than continuing users of these medications. ConclusionIn this analysis, medication adherence was lower among users of telepharmacy than users of a traditional pharmacy in some but not all drug classes examined. Further research is needed to identify whether other interventions to improve adherence, such as longer hours of operation, at-home delivery, or 90-day supply, may be coupled with telepharmacies to increase their use in urban areas.

Impact of Adherence Education and Monitoring on Community Pharmacy Performance Scores and Patient Satisfaction.

Adherence, specifically to noninsulin diabetes medications, statins, and renin-angiotensin system antagonists (i.e. angiotensin-converting-enzyme inhibitors (ACEi), angiotensin II receptor blockers (ARBs), and aliskiren), is a measure tracked by the Centers for Medicare and Medicaid Services (CMS) to give Medicare Part D plans a star rating; pharmacies are impacted by these star ratings. The pharmacy is given a performance score based on the measure. Some pharmacies use a performance information management platform (PIMP) that allows pharmacies to better understand performance information to impact patient care. (1) To evaluate if a monthly adherence monitoring and education service impacts the percentage of patientsadherent determined by pharmacy performance scores; (2) To determine patient satisfaction with the service in a large community pharmacy chain. A six-month prospective interventional pilot study including patients with a proportion of days covered (PDC) of less than 80% for oral diabetes or renin-angiotensin system antagonists (RASA) medications was conducted in two pharmacies of a large community pharmacy chain in Southwest Virginia. Using pharmacy internal data analytics and PIMP data, the percentage of patients who are adherent to oral diabetes or RASA medications was determined including the baseline PDC for each patient. At the start of the study, the standard of care in this large community chain pharmacy was to address adherence, follow-up in one month and every three months thereafter. In this study, pharmacists provided monthly telephonic adherence monitoring and education for a six-month period. Each session was scripted for medication adherence history, education and data collection. The pharmacist provided guidance and counseling based on how the patient answered the questions. Pharmacists gathered information about adherence patterns and behaviors using a 14 item Likert-scale and multiple choice-based questionnaire during the first session. After completion of the final adherence monitoring and education session, pharmacists gathered patient satisfaction information using an eight item Likert-scale questionnaire. At the end of the six-month period, using PIMP data, the percentage of patients adherent to oral diabetes or RASA medications was determined based on pharmacy performance scores. The data was analyzed using uni-variate and bi-variate statistics to determine if there was a difference in pharmacy performance scores from the pre-study analysis. The adherence patterns and behaviors, as well as patient satisfaction with the program was evaluated to determine factors influencing nonadherence. A total of 55 patients were identified in two pharmacies, ten of which were excluded or declined involvement, leaving 45 enrolled in the adherence monitoring and education service. Of the 45 enrolled patients, ten completed the adherence patterns and behaviors questionnaire. About half of the patients were men (50.95%) with an average age of 71.17 years and taking an average of 6.55 prescription medications. All patients had Medicare Part D insurance and majority had a yearly income of less than $40,000. The average baseline PDC was 68.92. In pharmacy 1, the average performance score for oral diabetes medications trended down and the average performance score for hypertension medications trended up over the study period. In pharmacy 2, the average performance score for oral diabetes medications trended up and the average performance score in hypertension medications trended up over the study period. The adherence patterns and behaviors questionnaire revealed the majority of patients rarely forgot to take medications or run out of medications. Additionally, cost of medications did not seem to impact adherence and majority of patients knew the names and indications of their medications. Only one patient completed the patient satisfaction survey. An adherence monitoring and education service had mixed results in improving patient adherence and pharmacy performance scores. Only one patient completed the satisfaction survey, thus no conclusions can be made regarding patient satisfaction of the program. More research needs to be done regarding telephonic adherence programs.

Telepharmacy and Quality of Medication Use in Rural Areas, 2013-2019.

IntroductionPharmacy closures in rural areas is an increasingly common problem. Closures disrupt medication access and decrease adherence to prescription medications. Telepharmacy is a potential solution to this problem; however, research on the relationship between telepharmacy and the quality of medication use is scarce. Our study sought to address this gap by comparing the quality of telepharmacies serving rural areas and traditional pharmacies that support them.MethodsWe obtained dispensing data for the first 18 months of operation from 3 telepharmacies and 3 traditional pharmacies located in the upper Midwest. We evaluated adherence for noninsulin diabetes medications, renin-angiotensin system antagonists, and statins, as well as inappropriate use of high-risk medications in older adults and statin use in persons with diabetes. All metrics were calculated using Medicare Part D specifications. We estimated the differences between telepharmacies serving rural areas and traditional pharmacies using generalized linear regression. We adjusted our models for potential sociodemographic and clinical confounders.ResultsA total of 2,832 patients contributed 4,402 observations to the quality measures. After covariate adjustment, we observed no significant differences between telepharmacies and traditional pharmacies for noninsulin diabetes medications, renin-angiotensin system antagonists, statins, and high-risk medications. However, statin use in persons with diabetes was higher in telepharmacies than traditional pharmacies.ConclusionWe found that the quality of medication use at telepharmacies that serve rural areas was no worse than at traditional pharmacies. For communities considering the adoption of telepharmacy, results indicate that telepharmacies provide a suitable solution for expanding medication access and that using telepharmacy would not negatively affect the quality of medication use.

Patient outcomes from implementing an enhanced services pharmacy network

ObjectiveTo evaluate the effect of implementing a network of community pharmacies on medication adherence, health service utilization, and health care spending. DesignQuasi-experimental difference-in-difference analysis with a nonequivalent control group. Setting and participantsEligible Medicaid-enrolled patients in North Carolina were attributed to intervention pharmacies between March 2015 and December 2016. A control group was propensity score-matched. Interventions consisted of enhanced services and a more intensive, comprehensive initial pharmacy assessment (CIPA). Outcome measuresOutcomes included hospitalizations; emergency department (ED) visits; health care spending for total medical, inpatient, outpatient, and ED services; and adherence to renin-angiotensin system antagonists (RASA), statins, noninsulin diabetes medications (NIDM), and multiple medications for chronic conditions (MMCC). ResultsThere were 31,509 patients who met eligibility criteria and were attributed to a participating pharmacy. Of these, 3897 received a CIPA. Before matching, patients attributed to participating pharmacies had greater Medicaid enrollment through aged, blind, or disabled status (49.2% vs. 31.5%, P < 0.001); greater case management (10.3% vs. 7%, P < 0.001); and worse rates of chronic disease (P < 0.001). Successful matching removed these differences. Adherence to RASA medications and MMCC increased by 9.5% and 10.3% (P < 0.05), respectively. Adherence did not change for statins and NIDM. The analysis also revealed a slower decline in average total medical spending of 5.7% (P < 0.01) relative to the control group over the same period, owed to a 9.6% (P < 0.001) slower decline in outpatient spending. ED utilization also decreased more slowly relative to controls by 4.8% (P < 0.05) following the intervention. ConclusionThe pharmacy intervention resulted in a statistically significant improvement in medication adherence to RASA and multiple chronic medications, but did not change or may have worsened utilization and spending outcomes. More research is needed to explore patient selection and variation in implementation and heterogeneity of treatment effects when evaluating pharmacy interventions.

1512-P: Severe Hypoglycemia and Hyperglycemia among U.S. Adults with Diabetes and ESRD on Dialysis, 2010-2015

Glycemic management in patients with diabetes and end-stage renal disease (ESRD) is challenging. There is limited evidence about the incidence of severe hypoglycemia and hyperglycemia in this population. Here, we examine rates of emergency department visits and hospitalizations for severe hypoglycemia and hyperglycemia (ascertained using validated ICD-9/10 codes) in a national cohort of adults with diabetes and incident ESRD, included in the United States Renal Data System, between 2010-2015. We then examine risk factors for these events using logistic regression. Among 678,376 patients with ESRD, 59.5% (n=403,490) had diabetes (63.6±13.0 years, 56.4% male, 26.8% Black, and 18.0% Hispanic). Rates of severe hypoglycemia and hyperglycemia were 126.2 and 35.5 per 1000 person-years, respectively. Strongest risk factors for hypoglycemia were insulin therapy (OR 4.5 [95% CI, 4.4-4.6] vs. no medications) and non-insulin diabetes medications (OR 3.7 [3.6-3.8]); Black race (OR 1.3 [1.3-1.4] vs. Caucasian); older age: 65-74 years (OR 1.2 [1.1-1.3] and ≥75 years OR 1.1 [1.1-1.1] vs. 18-44 years); and history of amputation (OR 1.4 [1.4-1.5]) or retinopathy (OR 1.2 [1.2-1.3]). Strongest risk factors for hyperglycemia were insulin (OR 7.7 [7.4-8.2]) and non-insulin diabetes medication use (OR 2.8 [2.6-3.1]) and retinopathy (OR 1.5 [1.4-1.5]). Older age was protective for hyperglycemia (OR 0.1 [0.1-0.1] for age ≥75 and 0.2 [0.2-0.2] for age 65-74 vs. 18-44 years). Patients on peritoneal dialysis had a lower risk (OR 0.8 [0.8-0.9]) of hypoglycemia, but no difference in odds of hyperglycemia, compared to patients on hemodialysis. Hypoglycemia requiring ED/hospital care was 3.6-fold more prevalent than severe hyperglycemia, greatly exceeding rates previously reported for older adults and those with non-end stage chronic kidney disease. There is a critical need for proactive interventions to reduce hypoglycemia and related ED/hospital use in this high-risk population. Disclosure R.J. Galindo: Advisory Panel; Self; Lilly Diabetes. Consultant; Self; Valeritas, Inc. Research Support; Self; Novo Nordisk Inc. Other Relationship; Self; UpToDate. M.K. Ali: Research Support; Self; Merck &amp; Co., Inc. N. Shah: None. S. Funni: None. G.E. Umpierrez: None. R.G. McCoy: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (P30DK111024)

Predictors and consequences of declining insulin therapy by individuals with type 2 diabetes.

To determine the relationship between decline of insulin therapy by individuals with type 2 diabetes and subsequent blood glucose control. We retrospectively studied adults with type 2 diabetes and suboptimal (HbA1c ≥ 53 mmol/mol [7.0%]) glycaemic control followed at two academic hospitals between 2000 and 2014 who were recommended insulin therapy. Decline of insulin therapy recommendations was identified using natural language processing of provider notes. Time to HbA1c < 53 mmol/mol (7.0%) served as the primary outcome. Of 5307 study participants, 2267 (42.7%) declined insulin therapy. Median time to HbA1c control in individuals who declined vs. started insulin therapy was 50 vs. 38 months, respectively (P < 0.001). In multivariable analysis, decline of insulin therapy was associated with hazard ratio for HbA1c control of 0.89 (95% CI 0.82 to 0.97; P = 0.008). Participants were more likely to accept insulin therapy recommendations if they had diabetes complications (OR 1.32; 95% CI 1.13 to 1.53; P < 0.001) or a higher HbA1c (OR 1.10; 95% CI 1.07 to 1.13; P < 0.001), and less likely if they were older (OR 0.81; 95% CI 0.76 to 0.86; P < 0.001) or were taking more non-insulin diabetes medications (OR 0.78; 95% CI 0.74 to 0.83; P < 0.001). Individuals with uncontrolled type 2 diabetes who declined insulin therapy subsequently had worse glycaemic control. These findings highlight the need to improve our understanding of the relationship of this common but poorly explored clinical phenomenon to blood glucose control and ultimately diabetes complications.

Primary Care Provider Encounter Cadence and HbA1c Control in Older Patients With Diabetes

Primary care provider encounters are associated with health and well-being; however, limited evidence guides optimal primary care provider rate of visit, referred to as encounter cadence. This study measures associations between primary care provider encounter cadence and diabetes outcomes among individuals newly diagnosed with type 2 diabetes mellitus. In this retrospective cohort study, 7,106 people enrolled in Medicare Advantage and newly diagnosed with type 2 diabetes mellitus between July 1, 2012 and June 30, 2013 were identified and followed for 36 months. Two methods measured primary care provider encounter cadence: total primary care provider encounters (frequency) and quarters with primary care provider encounter (regularity). Logistic regression measured relationships between primary care provider encounter cadence and non-insulin diabetes medication adherence, HbA1c control, emergency department visits, and inpatient admissions. Non-insulin diabetes medication adherence was defined according to the National Committee for Quality Assurance, Healthcare Effectiveness Data and Information Set specifications and measured using healthcare claims data. Post-hoc models examined adherence and diabetes control among those nonadherent (n=5,212) and with noncontrolled HbA1c (n=326) during the encounter/cadence period. Data were extracted and analyzed in 2017. Adjusted models indicated that both frequency (AOR=1.08, 95% CI=1.06, 1.10) and regularity (AOR=1.18, 95% CI=1.13, 1.22) of primary care provider encounters were associated with increased odds of adherence. Post-hoc analyses indicated that more frequent (AOR=1.12, 95% CI=1.10, 1.15) and regular (AOR=1.27, 95% CI=1.22, 1.33) primary care provider encounters were associated significantly with adherence and were associated directionally with HbA1c control. More frequent and regular primary care provider encounters are associated with an increased likelihood of non-insulin diabetes medication adherence. These findings contribute to data needed to establish evidence-based guidelines for primary care provider encounter cadence for those newly diagnosed with type 2 diabetes mellitus.

Predictors of glycemic control after decline of insulin therapy by patients with type 2 diabetes

AimDecline of insulin therapy by patients is common but poorly investigated. We conducted this study to determine patient and treatment characteristics predictive of glycemic control after declining clinician recommendation to initiate insulin therapy. MethodsWe retrospectively studied adults with type 2 diabetes mellitus treated at two academic medical centers between 1993 and 2014 who declined their healthcare provider recommendation to initiate insulin. ResultsIn a multivariable analysis of 300 study patients adjusted for demographics, comorbidities and clustering within providers, higher baseline HbA1c (OR 1.85; 95% CI 1.40 to 2.39; p < 0.001) and lifestyle changes (OR 8.39; 95% CI 3.26 to 21.55; p < 0.001) were associated with greater, while non-adherence to diabetes medications (OR 0.014; 95% CI 0.0025 to 0.085; p < 0.001) and discontinuation of a non-insulin diabetes medication (OR 0.30; 95% CI 0.11 to 0.80; p = 0.016) were associated with lower probability of HbA1c decrease after declining insulin therapy. ConclusionWe identified patient characteristics and treatment strategies associated with success and failure of glycemic control after insulin therapy decline by the patient. This information can assist in selection of optimal therapeutic approaches for these individuals.

Measuring Adherence: A Proof of Concept Study for Multiple Medications for Chronic Conditions in Alternative Payment Models.

Adherence to renin angiotensin system antagonists (RASA), non-insulin diabetes medications (NIDM) and statins has been included in the Medicare Star Ratings program since 2012. The long-term use of these measures emphasizes adherence to a limited number of chronic medications and may present opportunities for Part D plan sponsors to misuse the measures to influence their Medicare Part D Star Rating. It also does not capture the adherence needs of high-risk patients with multiple chronic conditions. The objective of this study was to describe the development of a new measure to capture adherence to multiple medications for chronic conditions (MMCC). The MMCC measure captures adherence to 71 different therapeutic categories of medication and was constructed using North Carolina Medicaid prescription claims data from 2015 to 2017. This measure was validated against the existing RASA, NIDM and statin adherence measures. This new measure was highly correlated with Star Rating measures, captured a greater number of eligible patients than these existing measures and had a lower proportion of patients meet the adherence threshold than the existing Star Ratings adherence measures. There is an opportunity to develop new measures, which include adherence to multiple medications in populations with multiple chronic conditions.

2376-PUB: Glycemic Control after Decline of Insulin Therapy by Patients

Recent evidence shows that many patients with type 2 diabetes (T2DM) initially decline insulin treatment. For some patients this could lead to poor glycemic control, whereas others may be able to lower blood glucose by alternative means. However, it is not currently known what factors affect achievement of glycemic control after decline of insulin therapy by patients. We conducted a retrospective cohort study to determine patient characteristics predictive of glycemic control after they decline insulin treatment. We studied adults with T2DM treated at two academic medical centers between 1993 and 2014 who rejected insulin therapy recommended by their providers. We compared 150 randomly selected patients whose A1c subsequently decreased to 150 patients whose A1c increased or stayed the same. Patients whose A1c decreased had a significantly higher baseline A1c (9.5% vs. 8.5%; p &amp;lt; .001), were more likely to implement lifestyle changes (27.3% vs. 7.3%; p &amp;lt; .001) and less likely to be non-adherent to diabetes medications (1.3% vs. 26.7%; p &amp;lt; .001) or to discontinue a non-insulin diabetes medication (8.0% vs. 16.0%; p = 0.03) after they declined insulin therapy. In a multivariable analysis adjusted for demographics, comorbidities and clustering within providers, higher baseline A1c (OR 1.85; 95% CI 1.41 to 2.42; p &amp;lt;.001) and lifestyle changes (OR 8.49; 95% CI 3.31 to 21.78; p &amp;lt;0.001) were associated with greater, while non-adherence to diabetes medications (OR 0.015; 95% CI 0.0025 to 0.088; p &amp;lt;.001) and discontinuation of a non-insulin diabetes medication (OR 0.30; 95% CI 0.12 to 0.78; p =0.013) were associated with lower probability of A1c decrease after initial decline of insulin therapy by the patient. We identified patient characteristics and treatment strategies associated with success and failure of glycemic control after insulin therapy decline by the patient. This information can help guide care and assist in design of rigorous interventional studies to evaluate optimal therapeutic approaches for these individuals. Disclosure L. Florez: None. A. Turchin: Advisory Panel; Self; Monarch Medical Technologies. Research Support; Self; Eli Lilly and Company. Stock/Shareholder; Self; Brio Systems.

1243-P: Novel Use of Natural Language Processing to Identify Reasons for Insulin Discontinuation in Patients with T2DM: A Real-World Evidence Study

Insulin is an important part of treatment of type 2 diabetes mellitus (T2DM). Nevertheless, reasons for discontinuation of insulin therapy are poorly understood. We conducted a real-world-evidence analysis of EMR data at Partners HealthCare to study adults with T2DM who were prescribed insulin between 2010 and 2016. Reasons for insulin discontinuation were identified from a combination of structured EMR data and natural language processing analysis of EMR notes using a validated tool (sensitivity 76.9% and positive predictive value 89.7%). The mean age of study patients was 60.2 years; 52.7% were male. Among 7,009 study patients, 2,957 (42.2%) discontinued insulin within 12 months after study start. In multivariable logistic regression analysis adjusted for demographics and comorbidities, patients were more likely to discontinue either basal or bolus insulin if they were on a basal-bolus regimen compared to basal only (OR 1.56, 95% CI 1.33 to 1.83; p &amp;lt; 0.001) or if they were being seen by an endocrinologist (OR 2.58; 95% CI 2.22 to 2.99; p &amp;lt; 0.001). Most patients (2,121/71.7%) had one or more reasons for discontinuation documented. The most common reasons were improving blood glucose (BG) control (33.2%), weight loss (likely ultimately also leading to lower BG) (18.5%) and initiation of non-insulin diabetes medications (16.7%). In multivariable analysis, patients were more likely to stop insulin due to achievement of good BG control if they were treated by an endocrinologist (OR 2.52; 95% CI 2.11 to 3.00; p &amp;lt; 0.001) or by a female physician (OR 1.43; 95% CI 1.26 to 1.63; p &amp;lt; 0.001). This study represents a successful attempt to use natural language processing to understand reasons for insulin discontinuation. Insulin discontinuation is common, and particularly so for patients on a basal-bolus regimen. Achievement of glycemic control, weight loss and initiation of other diabetes medications were the most common reasons for insulin discontinuation. Disclosure J. Wu: None. F.J. Morrison: None. Z. Zhao: Employee; Self; Lilly Diabetes. X. He: Employee; Self; Eli Lilly and Company. M. Shubina: None. S. Malmasi: None. W. Ge: None. X. Peng: None. A. Turchin: Advisory Panel; Self; Monarch Medical Technologies. Research Support; Self; Eli Lilly and Company. Stock/Shareholder; Self; Brio Systems. Funding Eli Lilly and Company

Impact of medication synchronization programs on proportion of days covered (PDC) scores and Medicare Part D medication-related adherence metrics

ObjectivesThis study aimed to determine if patients enrolled in a medication synchronization program have improvements in proportion of days covered (PDC) score for 3 of the Centers for Medicare and Medicaid Services adherence metrics medication classes: statins, renin-angiotensin-aldosterone system antagonists, and noninsulin diabetes medications. MethodsThis retrospective cohort study used data from members of a Medicare Advantage Prescription Drug plan, who took at least 1 of the key metric medications and had sufficient data to calculate a PDC score. The exposed cohort (“sync”) consisted of patients who enrolled in the medication synchronization program within the plan’s preferred pharmacy network, and the control group consisted of those who did not enroll in the program but met all other criteria. The primary end point was the change in PDC score from 2015 (baseline) to 2017 for each medication class. Secondary end points included the proportion of members with PDC scores of at least 85% and the association of adherence with annual medical and pharmacy costs. ResultsThe largest PDC score increases for the entire study population were seen in all 3 sync groups (RASA, diabetes, and statin) with corresponding statistically significant PDC score increases of 1.6%, 4.8%, and 2.9%, compared with −0.4%, 0.5%, and 1.3% changes in the control groups. In the multiple linear regression analysis, there were significant PDC score differences in the changes from baseline between the sync and control RASA, diabetes, and statin groups (P = 0.005, P = 0.01, and P < 0.001, respectively). The proportion of members achieving the acceptable PDC score threshold increased by 1.1% in the control group and by 4.1% in the sync group. ConclusionIn a population of patients with high baseline adherence, this medication synchronization program was associated with a statistically significant increase in adherence scores for statin, RASA, and noninsulin diabetes medications. There was no significant change in medical or pharmacy costs from the health plan perspective.

Prescribing of diabetes medications to people with type 2 diabetes and chronic kidney disease: a national cross-sectional study

BackgroundPrevious studies in general practice and hospital settings have identified that prescribing of non-insulin diabetes medications may be sub-optimal in people with type 2 diabetes (T2D) and renal impairment. Since these publications, a number of new medications have become available for the management of T2D. Study aims were to, in a cohort of Australians with T2D and renal impairment attending general practice, (1) investigate whether the prescribing of non-insulin diabetes medications is consistent with dosing adjustments recommended within current Australian Diabetes Society (ADS) guidelines; and (2) identify patient socio-demographic and clinical factors associated with at least one prescription of a non-insulin diabetes medication inconsistent with current ADS guidelines for medication doses.MethodsCross-sectional study using data from the MedicineInsight general practice database managed by NPS MedicineWise. Patients with T2D who were aged 18 years and over, with an average eGFR< 60 ml/min/1.73m2 and at least one prescription of a non-insulin diabetes medication between 1st January 2015 and 30th June 2017 were included. Descriptive statistics were used to summarise patient characteristics and medication use. Marginal logistic regression models were used to estimate associations between sociodemographic and clinical factors and prescribing of ≥1non-insulin diabetes medicine not consistent with ADS guidelines.ResultsThe majority of the 3505 patients included (90.4%) had an average eGFR of 30-59 ml/min/1.73m2. In terms of absolute numbers, metformin was the medication most frequently prescribed at a dose not consistent with current ADS guidelines for dosing in renal impairment (n = 1601 patients), followed by DPP4 inhibitors (n = 611) and sulphonylureas (n = 278). The drug classes with the highest proportion of prescriptions with dosage not consistent with ADS guidelines were SGLT2 inhibitors (83%), followed by biguanides (58%) and DPP4 inhibitors (46%). Higher HbA1c, longer known diabetes duration and diagnosis of retinopathy were associated with receiving ≥1prescription with a dosage not consistent with guidelines.ConclusionsPrescribing of non-insulin diabetes medications at doses inconsistent with current ADS guideline recommendations for dosing adjustments for people with renal impairment was common. Further research is needed to understand how general practitioners access, interpret and apply the ADS guidelines and the impact this may have on patient outcomes.

Use of non-insulin diabetes medicines after insulin initiation: A retrospective cohort study.

BackgroundClinical guidelines recommend that metformin be continued after insulin is initiated among patients with type 2 diabetes, yet little is known regarding how often metformin or other non-insulin diabetes medications are continued in this setting.MethodsWe conducted a retrospective cohort study to characterize rates and use patterns of six classes of non-insulin diabetes medications: biguanides (metformin), sulfonylureas, thiazolidinediones (TZDs), glucagon-like peptide 1 receptor agonists (GLP1 receptor agonists), dipeptidyl peptidase 4 inhibitors (DPP4 inhibitors), and sodium-glucose co-transporter inhibitors (SGLT2 inhibitors), among patients with type 2 diabetes initiating insulin. We used the 2010–2015 MarketScan Commercial Claims and Encounters data examining 72,971 patients with type 2 diabetes aged 18–65 years old who initiated insulin and had filled a prescription for a non-insulin diabetes medication in the 90 days prior to insulin initiation. Our primary outcome was the proportion of patients refilling the various non-insulin diabetes medications during the first 90 days after insulin initiation. We also used time-to-event analysis to characterize the time to discontinuation of specific medication classes.ResultsMetformin was the most common non-insulin medication used prior to insulin initiation (N = 53,017, 72.7%), followed by sulfonylureas (N = 25,439, 34.9%) and DPP4 inhibitors (N = 8,540, 11.7%). More than four out of five patients (N = 65,902, 84.7%) refilled prescriptions for any non-insulin diabetes medications within 90 days after insulin initiation. Within that period, metformin remained the most common medication with the highest continuation rate of 84.6%, followed by SGLT2 inhibitors (81.9%) and TZDs (79.3%). Sulfonylureas were the least likely medications to be continued (73.6% continuation) though they remained the second most common medication class used after insulin initiation. The median time to discontinuation varied by therapeutic class from the longest time to discontinuation of 26.4 months among metformin users to the shortest (3.0 months) among SGLT2 inhibitor users.ConclusionWhile metformin was commonly continued among commercially insured adults starting insulin, rates of continuation of other non-insulin diabetes medications were also high. Further studies are needed to determine the comparative effectiveness and safety of continuing insulin secretagogues and newer diabetes medications after insulin initiation.

Management of type 2 diabetes mellitus in the elderly population with cardiovascular diseases

Addressing the glycemic control of the elderly patients with type 2 diabetes mellitus (T2DM) requires creating an individualized plan for each patient due to the heterogeneity among this population. The personalized plan should address topics such as comorbidities, polypharmacy, and cost of medications. One of the major comorbidities that necessitate consideration is cardiovascular disease (CVD), which makes it essential for clinicians to stay updated with literature on cardiovascular safety of diabetes medications. Metformin, along with dietary changes and adequate exercise, should be the first line treatment for patients with T2DM. Glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter-2 inhibitors should be considered for add-on therapy for elderly patients with CVD whom do not reach their hemoglobin A1c goal on metformin alone. All drugs in these two categories have been shown to be safe in patients with CVD and most of them have shown to reduce adverse cardiovascular events. Sulfonylureas should be used cautiously in elderly due to their high risk of hypoglycemia. Thiazolidinediones, saxagliptin and alogliptin should be avoided in patients with heart failure. With the high rate of major adverse cardiovascular events in elderly population, it is imperative to consider cardiovascular safety and efficacy of non-insulin diabetes medications in formulating management plan for elderly patients with concurrent T2DM and CVD.