Dataset Information

Financial Strain and Medication Adherence among Diabetes Patients in an Integrated Health Care Delivery System: The Diabetes Study of Northern California (DISTANCE).

ABSTRACT: To examine self-reported financial strain in relation to pharmacy utilization adherence data.Survey, administrative, and electronic medical data from Kaiser Permanente Northern California.Retrospective cohort design (2006, n = 7,773).We compared survey self-reports of general and medication-specific financial strain to three adherence outcomes from pharmacy records, specifying adjusted generalized linear regression models.Eight percent and 9 percent reported general and medication-specific financial strain. In adjusted models, general strain was significantly associated with primary nonadherence (RR = 1.37; 95 percent CI: 1.04-1.81) and refilling late (RR = 1.34; 95 percent CI: 1.07-1.66); and medication-specific strain was associated with primary nonadherence (RR = 1.42, 95 percent CI: 1.09-1.84).Simple, minimally intrusive questions could be used to identify patients at risk of poor adherence due to financial barriers.

SUBMITTER: Lyles CR

PROVIDER: S-EPMC4799896 | biostudies-other | 2016 Apr

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Financial Strain and Medication Adherence among Diabetes Patients in an Integrated Health Care Delivery System: The Diabetes Study of Northern California (DISTANCE).

Lyles Courtney R CR Seligman Hilary K HK Parker Melissa M MM Moffet Howard H HH Adler Nancy N Schillinger Dean D Piette John D JD Karter Andrew J AJ

Health services research 20150809 2

<h4>Objective</h4>To examine self-reported financial strain in relation to pharmacy utilization adherence data.<h4>Data sources/study setting</h4>Survey, administrative, and electronic medical data from Kaiser Permanente Northern California.<h4>Study design</h4>Retrospective cohort design (2006, n = 7,773).<h4>Data collection/extraction methods</h4>We compared survey self-reports of general and medication-specific financial strain to three adherence outcomes from pharmacy records, specifying adj ...[more]

PMID: 26256117

Similar Datasets

Project description:BackgroundPrevious studies have reported that health literacy limitations are associated with poorer disease control for chronic conditions, but have not evaluated potential associations with medication adherence.ObjectiveTo determine whether health literacy limitations are associated with poorer antidepressant medication adherence.DesignObservational new prescription cohort follow-up study.ParticipantsAdults with type 2 diabetes who completed a survey in 2006 and received a new antidepressant prescription during 2006-2010 (N?=?1,366) at Kaiser Permanente Northern California.Main measuresValidated three-item self-report scale measured health literacy. Discrete indices of adherence based on pharmacy dispensing data according to validated methods: primary non-adherence (medication never dispensed); early non-persistence (dispensed once, never refilled); non-persistence at 180 and 365 days; and new prescription medication gap (NPMG; proportion of time that the person is without medication during 12 months after the prescription date).Key resultsSeventy-two percent of patients were classified as having health literacy limitations. After adjusting for sociodemographic and clinical covariates, patients with health literacy limitations had significantly poorer adherence compared to patients with no limitations, whether measured as early non-persistence (46 % versus 38 %, p?<?0.05), non-persistence at 180 days (55 % versus 46 %, p?<?0.05), or NPMG (41 % versus 36%, p?<?0.01). There were no significant associations with primary adherence or non-persistence at 365 days.ConclusionsPoorer antidepressant adherence among adults with diabetes and health literacy limitations may jeopardize the continuation and maintenance phases of depression pharmacotherapy. Findings underscore the importance of national efforts to address health literacy, simplify health communications regarding treatment options, improve public understanding of depression treatment, and monitor antidepressant adherence.

Project description:BackgroundThe role that environmental factors, such as neighborhood socioeconomics, food, and physical environment, play in the risk of obesity and chronic diseases is not well quantified. Understanding how spatial distribution of disease risk factors overlap with that of environmental (contextual) characteristics may inform health interventions and policies aimed at reducing the environment risk factors. We evaluated the extent to which spatial clustering of extreme body mass index (BMI) values among a large sample of adults with diabetes was explained by individual characteristics and contextual factors.MethodsWe quantified spatial clustering of BMI among 15,854 adults with diabetes from the Diabetes Study of Northern California (DISTANCE) cohort using the Global and Local Moran's I spatial statistic. As a null model, we assessed the amount of clustering when BMI values were randomly assigned. To evaluate predictors of spatial clustering, we estimated two linear models to estimate BMI residuals. First we included individual factors (demographic and socioeconomic characteristics). Then we added contextual factors (neighborhood deprivation, food environment) that may be associated with BMI. We assessed the amount of clustering that remained using BMI residuals.ResultsGlobal Moran's I indicated significant clustering of extreme BMI values; however, after accounting for individual socioeconomic and demographic characteristics, there was no longer significant clustering. Twelve percent of the sample clustered in extreme high or low BMI clusters, whereas, only 2.67% of the sample was clustered when BMI values were randomly assigned. After accounting for individual characteristics, we found clustering of 3.8% while accounting for neighborhood characteristics resulted in 6.0% clustering of BMI. After additional adjustment of neighborhood characteristics, clustering was reduced to 3.4%, effectively accounting for spatial clustering of BMI.ConclusionsWe found substantial clustering of extreme high and low BMI values in Northern California among adults with diabetes. Individual characteristics explained somewhat more of clustering of the BMI values than did neighborhood characteristics. These findings, although cross-sectional, may suggest that selection into neighborhoods as the primary explanation of why individuals with extreme BMI values live close to one another. Further studies are needed to assess causes of extreme BMI clustering, and to identify any community level role to influence behavior change.

Project description:BackgroundLittle is known about the frequency of significant hypoglycemic events in actual practice. Limited health literacy (HL) is common among patients with type 2 diabetes, may impede diabetes self-management, and thus HL could increase the risk of hypoglycemia.ObjectiveTo determine the proportion of ambulatory, pharmacologically-treated patients with type 2 diabetes reporting > or =1 significant hypoglycemic events in the prior 12 months, and evaluate whether HL is associated with hypoglycemia.Research designCross-sectional analysis in an observational cohort, the Diabetes Study of Northern California (DISTANCE).SubjectsThe subjects comprised 14,357 adults with pharmacologically-treated, type 2 diabetes who are seen at Kaiser Permanente Northern California (KPNC), a non-profit, integrated health care delivery system.MeasuresPatient-reported frequency of significant hypoglycemia (losing consciousness or requiring outside assistance); patient-reported health literacy.ResultsAt least one significant hypoglycemic episode in the prior 12 months was reported by 11% of patients, with the highest risk for those on insulin (59%). Patients commonly reported limited health literacy: 53% reported problems learning about health, 40% needed help reading health materials, and 32% were not confident filling out medical forms by themselves. After adjustment, problems learning (OR 1.4, CI 1.1-1.7), needing help reading (OR 1.3, CI 1.1-1.6), and lack of confidence with forms (OR 1.3, CI 1.1-1.6) were independently associated with significant hypoglycemia.ConclusionsSignificant hypoglycemia was a frequent complication in this cohort of type 2 diabetes patients using anti-hyperglycemic therapies; those reporting limited HL were especially vulnerable. Efforts to reduce hypoglycemia and promote patient safety may require self-management support that is appropriate for those with limited HL, and consider more vigilant surveillance, conservative glycemic targets or avoidance of the most hypoglycemia-inducing medications.

Project description:BackgroundDiabetes is one of the leading noncommunicable chronic diseases globally. In people with diabetes, blood glucose levels need to be monitored regularly and managed adequately through healthy lifestyles and medications. However, various factors contribute to poor medication adherence. Smartphone apps can improve medication adherence in people with diabetes, but it is not clear which app features are most beneficial.ObjectiveThis study aims to systematically review and evaluate high-quality apps for diabetes medication adherence, which are freely available to the public in Android and Apple app stores and present the technical features of the apps.MethodsWe systematically searched Apple App Store and Google Play for apps that assist in diabetes medication adherence, using predefined selection criteria. We assessed apps using the Mobile App Rating Scale (MARS) and calculated the mean app-specific score (MASS) by taking the average of app-specific scores on 6 dimensions, namely, awareness, knowledge, attitudes, intention to change, help-seeking, and behavior change rated on a 5-point scale (1=strongly disagree and 5=strongly agree). We used the mean of the app's performance on these 6 dimensions to calculate the MASS. Apps that achieved a total MASS mean quality score greater than 4 out of 5 were considered to be of high quality in our study. We formulated a task-technology fit matrix to evaluate the apps for diabetes medication adherence.ResultsWe identified 8 high-quality apps (MASS score≥4) and presented the findings under 3 main categories: characteristics of the included apps, app features, and diabetes medication adherence. Our framework to evaluate smartphone apps in promoting diabetes medication adherence considered physiological factors influencing diabetes and app features. On evaluation, we observed that 25% of the apps promoted high adherence and another 25% of the apps promoted moderate adherence. Finally, we found that 50% of the apps provided low adherence to diabetes medication.ConclusionsOur findings show that almost half of the high-quality apps publicly available for free did not achieve high to moderate medication adherence. Our framework could have positive implications for the future design and development of apps for patients with diabetes. Additionally, apps need to be evaluated using a standardized framework, and only those promoting higher medication adherence should be prescribed for better health outcomes.

Dataset Information

Financial Strain and Medication Adherence among Diabetes Patients in an Integrated Health Care Delivery System: The Diabetes Study of Northern California (DISTANCE).

Publications

Financial Strain and Medication Adherence among Diabetes Patients in an Integrated Health Care Delivery System: The Diabetes Study of Northern California (DISTANCE).

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets