Medication nonadherence is widespread, but there are few efficient means of detecting medication nonadherence at the point of care. Visit-to-visit variability in clinical biomarkers has shown ...inconsistent efficiency to predict medication adherence.
To examine the performance of visit-to-visit variability (VVV) of hemoglobin A1c to predict nonadherence to antidiabetic medications.
In this cross-sectional study using a clinical and administrative database, adult members of a managed care plan at a safety-net medical center from 2008 to 2012 were included if they had ≥ 3 noninsulin antidiabetic prescription fills within the same class and ≥ 3 A1c measurements between the first and last prescription fills. The independent variable was VVV of A1c (within-subject standard deviation of A1c), and the dependent variable was medication adherence (defined by medication possession ratio) determined from pharmacy claims. Unadjusted and adjusted multivariate logistic regression models were created to examine the relationship between VVV of A1c and medication nonadherence. Receiver-operating characteristic (ROC) curves assessed the performance of the adjusted model at discriminating adherence from nonadherence.
Among 632 eligible subjects, mean A1c was 7.7% ± 1.3%, and 83% of the sample was nonadherent to antidiabetic medications. Increasing quintiles of VVV of A1c and medication nonadherence were both associated with increased within-subject mean A1c and younger subject age. The logistic regression model (adjusted for age, sex, race/ethnicity, within-subject mean A1c, number of A1c measurements, number of days between the first and last antidiabetic medication prescription fills, and rate of primary care visits during the study period) showed a nonsignificant association of VVV of A1c and medication nonadherence (OR = 1.19, 95% CI = 0.42-3.38 for the highest quintile of VVV). Adding VVV of A1c to a model including age, sex, and race only modestly improved the C-statistic of the ROC curve from 0.6786 to 0.7064.
VVV of A1c is not a robust predictor of antidiabetic medication nonadherence. Further innovation is needed to develop novel methods of detecting nonadherence.
The integration of behavioral economics (BE) principles and electronic health records (EHRs) using clinical decision support (CDS) tools is a novel approach to improving health outcomes. Meanwhile, ...the American Geriatrics Society has created the Choosing Wisely (CW) initiative to promote less aggressive glycemic targets and reduction in pharmacologic therapy in older adults with type 2 diabetes mellitus. To date, few studies have shown the effectiveness of combined BE and EHR approaches for managing chronic conditions, and none have addressed guideline-driven deprescribing specifically in type 2 diabetes. We previously conducted a pilot study aimed at promoting appropriate CW guideline adherence using BE nudges and EHRs embedded within CDS tools at 5 clinics within the New York University Langone Health (NYULH) system. The BE-EHR module intervention was tested for usability, adoption, and early effectiveness. Preliminary results suggested a modest improvement of 5.1% in CW compliance.
This paper presents the protocol for a study that will investigate the effectiveness of a BE-EHR module intervention that leverages BE nudges with EHR technology and CDS tools to reduce overtreatment of type 2 diabetes in adults aged 76 years and older, per the CW guideline.
A pragmatic, investigator-blind, cluster randomized controlled trial was designed to evaluate the BE-EHR module. A total of 66 NYULH clinics will be randomized 1:1 to receive for 18 months either (1) a 6-component BE-EHR module intervention + standard care within the NYULH EHR, or (2) standard care only. The intervention will be administered to clinicians during any patient encounter (eg, in person, telemedicine, medication refill, etc). The primary outcome will be patient-level CW compliance. Secondary outcomes will measure the frequency of intervention component firings within the NYULH EHR, and provider utilization and interaction with the BE-EHR module components.
Study recruitment commenced on December 7, 2020, with the activation of all 6 BE-EHR components in the NYULH EHR.
This study will test the effectiveness of a previously developed, iteratively refined, user-tested, and pilot-tested BE-EHR module aimed at providing appropriate diabetes care to elderly adults, compared to usual care via a cluster randomized controlled trial. This innovative research will be the first pragmatic randomized controlled trial to use BE principles embedded within the EHR and delivered using CDS tools to specifically promote CW guideline adherence in type 2 diabetes. The study will also collect valuable information on clinician workflow and interaction with the BE-EHR module, guiding future research in optimizing the timely delivery of BE nudges within CDS tools. This work will address the effectiveness of BE-inspired interventions in diabetes and chronic disease management.
ClinicalTrials.gov NCT04181307; https://clinicaltrials.gov/ct2/show/NCT04181307.
DERR1-10.2196/28723.
Several models for estimating risk of incident diabetes in US adults are available. The authors aimed to determine the discriminative ability and calibration of published diabetes risk prediction ...models in a contemporary multiethnic cohort. Participants in the Multi-Ethnic Study of Atherosclerosis without diabetes at baseline (2000–2002; n = 5,329) were followed for a median of 4.75 years. The predicted risk of diabetes was calculated using published models from the Framingham Offspring Study, the Atherosclerosis Risk in Communities (ARIC) Study, and the San Antonio Heart Study. The mean age of participants was 61.6 years (standard deviation, 10.2); 29.3% were obese, 53.1% had hypertension, 34.9% had a family history of diabetes, 27.5% had high triglyceride levels, 33.8% had low high density lipoprotein cholesterol levels, and 15.3% had impaired fasting glucose. There were 446 incident cases of diabetes (fasting glucose level ≥126 mg/dL or initiation of antidiabetes medication use) diagnosed during follow-up. C statistics were 0.78, 0.84, and 0.83 for the Framingham, ARIC, and San Antonio risk prediction models, respectively. There were significant differences between observed and predicted diabetes risks (Hosmer-Lemeshow goodness-of-fit chi-squared test for each model: P < 0.001). The recalibrated and best-fit models achieved sufficient goodness of fit (each P > 0.10). The Framingham, ARIC, and San Antonio models maintained high discriminative ability but required recalibration in a modern, multiethnic US cohort.
A prediction model, developed in the Framingham Heart Study (FHS), has been proposed for use in estimating a given individual's risk of hypertension. We compared this model with systolic blood ...pressure (SBP) alone and age-specific diastolic blood pressure categories for the prediction of hypertension. Participants in the Multi-Ethnic Study of Atherosclerosis, without hypertension or diabetes mellitus (n=3013), were followed for the incidence of hypertension (SBP > or =140 mm Hg and/or diastolic blood pressure > or =90 mm Hg and/or the initiation of antihypertensive medication). The predicted probability of developing hypertension among 4 adjacent study examinations, with a median of 1.6 years between examinations, was determined. The mean (SD) age of participants was 58.5 (9.7) years, and 53% were women. During follow-up, 849 incident cases of hypertension occurred. The c statistic for the FHS model was 0.788 (95% CI: 0.773 to 0.804) compared with 0.768 (95% CI: 0.751 to 0.785; P=0.096 compared with the FHS model) for SBP alone and 0.699 (95% CI: 0.681 to 0.717; P<0.001 compared with the FHS model) for age-specific diastolic blood pressure categories. The relative integrated discrimination improvement index for the FHS model versus SBP alone was 10.0% (95% CI: -1.7% to 22.7%) and versus age-specific diastolic blood pressure categories was 146.0% (95% CI: 116.0% to 181.0%). Using the FHS model, there were significant differences between observed and predicted hypertension risks (Hosmer-Lemeshow goodness of fit: P<0.001); recalibrated and best-fit models produced a better model fit (P=0.064 and 0.245, respectively). In this multiethnic cohort of US adults, the FHS model was not substantially better than SBP alone for predicting hypertension.
Evidence-based solutions for changing health behaviors exist but problems with feasibility, sustainability, and dissemination limit their impact on population-based behavior change and maintenance.
...Our goal was to overcome the limitations of an established behavior change program by using the inherent capabilities of smartphones and wireless sensors to develop a next generation mobile health (mHealth) intervention that has the potential to be more feasible.
In response to the clinical need and the growing capabilities of smartphones, our study team decided to develop a behavioral hypertension reduction mHealth system inspired by Dietary Approaches to Stop Hypertension (DASH), a lifestyle modification program. We outline the key design and development decisions that molded the project including decisions about behavior change best practices, coaching features, platform, multimedia content, wireless devices, data security, integration of systems, rapid prototyping, usability, funding mechanisms, and how all of these issues intersect with clinical research and behavioral trials.
Over the 12 months, our study team faced many challenges to developing our prototype intervention. We describe 10 lessons learned that will ultimately stimulate more effective and sustainable approaches.
The experiences presented in this case study can be used as a reference for others developing mHealth behavioral intervention development projects by highlighting the benefits and challenges facing mHealth research.
Advances in genetics and sequencing technologies are enabling the identification of more individuals with inherited cancer susceptibility who could benefit from tailored screening and prevention ...recommendations. While cancer family history information is used in primary care settings to identify unaffected patients who could benefit from a cancer genetics evaluation, this information is underutilized. System-level population health management strategies are needed to assist health care systems in identifying patients who may benefit from genetic services. In addition, because of the limited number of trained genetics specialists and increasing patient volume, the development of innovative and sustainable approaches to delivering cancer genetic services is essential.
We are conducting a randomized controlled trial, entitled Broadening the Reach, Impact, and Delivery of Genetic Services (BRIDGE), to address these needs. The trial is comparing uptake of genetic counseling, uptake of genetic testing, and patient adherence to management recommendations for automated, patient-directed versus enhanced standard of care cancer genetics services delivery models. An algorithm-based system that utilizes structured cancer family history data available in the electronic health record (EHR) is used to identify unaffected patients who receive primary care at the study sites and meet current guidelines for cancer genetic testing. We are enrolling eligible patients at two healthcare systems (University of Utah Health and New York University Langone Health) through outreach to a randomly selected sample of 2780 eligible patients in the two sites, with 1:1 randomization to the genetic services delivery arms within sites. Study outcomes are assessed through genetics clinic records, EHR, and two follow-up questionnaires at 4 weeks and 12 months after last genetic counseling contactpre-test genetic counseling.
BRIDGE is being conducted in two healthcare systems with different clinical structures and patient populations. Innovative aspects of the trial include a randomized comparison of a chatbot-based genetic services delivery model to standard of care, as well as identification of at-risk individuals through a sustainable EHR-based system. The findings from the BRIDGE trial will advance the state of the science in identification of unaffected patients with inherited cancer susceptibility and delivery of genetic services to those patients.
BRIDGE is registered as NCT03985852 . The trial was registered on June 6, 2019 at clinicaltrials.gov .
Few data are available on factors associated with low adherence or early clopidogrel discontinuation after percutaneous coronary intervention (PCI). Patients (n = 284) were evaluated before hospital ...discharge after PCI to identify factors associated with low adherence to clopidogrel 30 days later. Adherence to daily medications before PCI was assessed using the 8-item Morisky Medication Adherence Scale (MMAS-8) and categorized as low (score <6), medium (score 6 to <8), or high (score 8). Low adherence to clopidogrel was defined as MMAS-8 score <6 (n = 21) or having discontinued clopidogrel (n = 11), which was ascertained during a 30-day interview after PCI. At 30 days after PCI, 11% of patients had low adherence to clopidogrel. Odds ratios (95% confidence intervals CIs) for low adherence to clopidogrel were 3.78 (1.09 to 13.1), 3.06 (1.36 to 6.87), 2.46 (0.97 to 6.27), and 3.36 (0.99 to 11.4) for patients who before PCI reported taking smaller doses of medication because of cost, had difficulty filling prescriptions, had difficulty reaching their primary physician, and were not comfortable asking their doctor for instructions, respectively. Odds ratios (95% CIs) for low clopidogrel adherence after PCI in patients with medium and low versus high adherence to daily medications before PCI were 6.13 (1.34 to 28.2) and 10.9 (2.46 to 48.7), respectively. The c-statistic associated with MMAS-8 scores before PCI for discriminating low clopidogrel adherence at 30 days after PCI was 0.733 (95% CI 0.650 to 0.852). In conclusion, adherence to daily medications before PCI may be a useful indicator for identifying patients who will have low clopidogrel adherence after PCI.
While medicine has borrowed a great deal of corporate culture in its quality improvement efforts—few have adopted a similar emphasis on R&D investment in its core product—healthcare delivery. Despite ...a rich pool of experts to draw upon, academic medical centers typically lack the infrastructure; the financial incentives; and the teams with operations, research, and clinical representatives to support this T3 and T4 cross‐disciplinary, operationally sensitive research. In order to improve care and meet incentive payment targets, the operational team brings together clinicians, managers, and technical leads to create a program that follows evidence‐based guidelines to improve hypertension management in clinical practice.
Same-day discharge after percutaneous coronary intervention (PCI) may be safe for some patients. Few data are available on patient-reported outcomes and preferences for same-day discharge after PCI.
...Between March 2008 and March 2010, a total of 298 patients undergoing elective PCI via femoral access at 2 medical centers (Mount Sinai Hospital, New York, NY, and Baylor Medical Center, Dallas, TX) were randomized to same-day (n=150) or next-day (n=148) discharge. The primary outcome was high patient coping during the 7 days after discharge defined as scores <20 on the validated postdischarge coping difficulty scale. Safety outcomes, clopidogrel adherence, and patient preferences were secondary outcomes. Before discharge, patients randomized to same-day and next-day discharge were similar with respect to sociodemographic and clinical characteristics. High-coping ability, assessed 7 days after PCI, was present for 79% of patients randomized to same-day discharge and for 77% of patients randomized to next-day discharge. The difference in high coping ability, 2 (95% confidence interval, -7 to 11), did not cross the noninferiority threshold of -12% (P<0.001 that same-day discharge is not noninferior to next-day discharge). At 30 days after PCI, clopidogrel adherence, physician and emergency room visits, and hospitalization were similar in the 2 randomization groups. In addition, 80% and 68% of those randomized to same-day and next-day discharge, respectively, stated they would prefer same-day discharge if they were to have another PCI procedure.
Same-day discharge after PCI was associated with patient-reported and clinical outcomes similar to those of next-day discharge and was preferred by most patients.
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