Dataset Information

Patient risk profiles and practice variation in nonadherence to antidepressants, antihypertensives and oral hypoglycemics.

ABSTRACT: BACKGROUND: Many patients experience difficulties in following treatment recommendations. This study's objective is to identify nonadherence risk profiles regarding medication (antidepressants, antihypertensives, and oral hypoglycemics) from a combination of patients' socio-demographic characteristics, morbidity presented within general practice and medication characteristics. An additional objective is to explore differences in nonadherence among patients from different general practices. METHODS: Data were obtained by linkage of a Dutch general practice registration database to a dispensing registration database from the year 2001. Subjects included in the analyses were users of antidepressants (n = 4,877), antihypertensives (n = 14,219), or oral hypoglycemics (n = 2,428) and their GPs. Outcome variables were: 1) early dropout i.e., a maximum of two prescriptions and 2) refill nonadherence (in patients with 3+ prescriptions); refill adherence < 80% was considered as nonadherence. Multilevel modeling was used for analyses. RESULTS: Both early dropout and refill nonadherence were highest for antidepressants, followed by antihypertensives. Risk factors appeared medication specific and included: 1) non-western immigrants being more vulnerable for nonadherence to antihypertensives and antidepressants; 2) type of medication influencing nonadherence in both antihypertensives and antidepressants, 3) GP consultations contributing positively to adherence to antihypertensives and 4) somatic co-morbidity influencing adherence to antidepressants negatively. There was a considerable range between general practices in the proportion of patients who were nonadherent. CONCLUSION: No clear risk profiles for nonadherence could be constructed. Characteristics that are correlated with nonadherence vary across different types of medication. Moreover, both patient and prescriber influence adherence. Especially non-western immigrants need more attention with regard to nonadherence, for example by better monitoring or communication. Since it is not clear which prescriber characteristics influence adherence levels of their patients, there is need for further research into the role of the prescriber.

SUBMITTER: van Dijk L

PROVIDER: S-EPMC1855317 | biostudies-literature | 2007

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Patient risk profiles and practice variation in nonadherence to antidepressants, antihypertensives and oral hypoglycemics.

van Dijk Liset L Heerdink Eibert R ER Somai Dinesh D van Dulmen Sandra S Sluijs Emmy M EM de Ridder Denise T DT Griens Anna M G F AM Bensing Jozien M JM

BMC health services research 20070410

<h4>Background</h4>Many patients experience difficulties in following treatment recommendations. This study's objective is to identify nonadherence risk profiles regarding medication (antidepressants, antihypertensives, and oral hypoglycemics) from a combination of patients' socio-demographic characteristics, morbidity presented within general practice and medication characteristics. An additional objective is to explore differences in nonadherence among patients from different general practices ...[more]

PMID: 17425792

Similar Datasets

Project description:Background: Incident cancer diagnosis may increase the risk of coronary artery disease (CAD)-related hospitalizations, especially in older individuals. Adherence to statins and/or angiotensin-converting enzyme inhibitors (ACEIs)/angiotensin II receptor blockers (ARBs)/β-blockers reduces CAD-related hospitalizations. This study examined the relationship between medication adherence and CAD-related hospitalizations immediately following cancer diagnosis. Patients and Methods: A retrospective observational longitudinal study was conducted using SEER-Medicare data. Elderly Medicare fee-for-service beneficiaries with preexisting CAD and incident breast, colorectal, or prostate cancer (N=12,096) were observed for 12 months before and after cancer diagnosis. Hospitalizations measured every 120 days were categorized into CAD-related hospitalization, other hospitalization, and no hospitalization. Medication adherence was categorized into 5 mutually exclusive groups: adherent to both statins and ACEIs/ARBs/β-blockers (reference group), not adherent to both statins and ACEIs/ARBs/β-blockers, adherent to either statins or ACEIs/ARBs/β-blockers, use of one medication class and adherent to that class, and use of one medication class and not adherent to that class. The relationship between medication adherence and hospitalization was analyzed using repeated measures multinomial logistic regressions. Inverse probability treatment weights were used to control for observed group differences among medication adherence categories. Results: Adherence to both statins and ACEIs/ARBs/β-blockers was estimated at 31.2% during the 120-day period immediately following cancer diagnosis; 13.7% were not adherent to both medication classes during the same period, and 27.4% had CAD-related hospitalizations immediately after cancer diagnosis, which declined to 10.6% during the last 4 months of the postdiagnosis period. In the adjusted analyses, those not adherent to both statins and ACEIs/ARBs/β-blockers were more likely to have CAD-related hospitalization compared with those adherent to both medication classes (adjusted odds ratio, 1.82; 95% CI, 1.72-1.92; P<.0001). Conclusions: Given the complexity of interaction between CAD and cancer, it is important to routinely monitor medication adherence in general clinical practice and to provide linkages to support services that can increase medication adherence.

Project description:Background: Many patients face a financial burden due to their medications, which may lead to poor health outcomes. The behaviors of non-adherence due to financial difficulties, known as cost-related medication non-adherence (CRN), include taking smaller doses of drugs, skipping doses to make prescriptions last longer, or delaying prescriptions. To date, the prevalence of CRN remains unknown, and there are few studies about the association of CRN on self-reported healthcare utilization (Emergency room (ER) visits and outpatient visits) and self-reported health outcomes (health status and disability status) among older adults taking antidepressants. Objectives: The objectives were to 1) examine the CRN prevalence, and 2) determine the association of CRN on self-reported healthcare utilization and self-reported health outcomes. Methods: This study was a cross-sectional study of a sample of older adults from the Medicare Current Beneficiary Survey (MCBS) who reported having used antidepressants in 2017. Four logistic regressions were implemented to evaluate the association of CRN, and self-reported healthcare utilization and self-reported health outcomes. Results: The study identified 602 participants who were Medicare beneficiaries on antidepressants. The prevalence of CRN among antidepressant users was (16.61%). After controlling for covariates, CRN was associated with poorer self-reported outcomes but not statistically significant: general health status [odds ratio (OR): 0.67; 95% confidence interval (CI): 0.39-1.16] and disability status (OR: 1.34; 95% CI: 0.83-2.14). In addition, CRN was associated with increased outpatient visits (OR: 1.89; 95% CI: 1.19-3.02), but not associated with ER visits (OR: 1.10; 95% CI: 0.69-1.76). Conclusion: For Medicare beneficiaries on antidepressants, CRN prevalence was high and contributed to more outpatient visits. The healthcare provider needs to define the reasoning for CRN and provide solutions to reduce the financial burden on the affected patient. Also, health care providers need to consider the factors that may enhance patient health status and healthcare efficiency.

Project description:PurposePatient adherence to antidepressants is poor. However, this is rather unsurprising, given the equivocal efficacy, side effects, and practical problems of antidepressants. The aim of this study was to examine a wide array of patient experiences and perceptions regarding the efficacy, side effects, and practical problems of antidepressants, as well as their associations with nonadherence, and whether patients' perceived self-efficacy moderated these associations.Patients and methodsExperiences and perceptions of 225 patients, recruited through community pharmacies, were efficiently assessed with the Tailored Medicine Inventory. Nonadherence was assessed through self-report and pharmacy refill data.ResultsMany patients were not convinced of the efficacy, thought the efficacy to be limited or did not believe antidepressants to prevent relapse, were worried about or had experienced one or more side effects, and/or had experienced one or more practical problems regarding information, intake, and packaging. Being convinced of efficacy was associated with lower intentional nonadherence (odds ratio [OR] 0.9, 95% confidence interval [CI] 0.8-0.96). A higher number of practical problems experienced was associated with increased unintentional nonadherence (OR 1.3, 95% CI 1.1-1.7). Higher perceived self-efficacy regarding taking antidepressants was associated with lower unintentional nonadherence (OR 0.7, 95% CI 0.5-0.9). Perceived self-efficacy did not moderate associations of patient experiences and perceptions with nonadherence.ConclusionAssessing a wide array of patients' experiences and perceptions regarding the efficacy, side effects, and practical problems of antidepressants contributes to better understanding of nonadherence to antidepressants. Guiding physician-patient conversations by patients' experiences and perceptions may reduce both unintentional and intentional nonadherence. Also, it may give rise to considerations of prudent discontinuation, eg, when patients are not convinced of the efficacy.

Project description:Oral cancer is the most common malignant tumor in the oral and maxillofacial region, of which more than 90% is squamous cell carcinoma. The incidence of oral cancer is on the rise worldwide. An imbalance between the microorganism composition and its host may lead to the occurrence of oral malignant tumors. Accumulating evidence suggests that the oral microbiota plays an important role in oral cancer; however, the association between oral microbiota and oral cancer has not yet been comprehensively studied. In this study, metagenomic sequencing was used to compare the microbial composition of three groups of samples from Chinese patients with oral cancer, patients with precancerous lesion, and normal individuals. In terms of microbiota richness, the oral microbiota of patients with precancerous lesions was richer than that of oral cancer patients and healthy controls, whereas in terms of microbiota diversity, there was little difference between the three groups. The three groups of samples exhibited statistically significant differences in microbiota composition and metabolic function at the family, genus, and species levels (P < 0.05). The differentially enriched phylum in oral cancer samples was Bacteroidetes (P < 0.05). At the genus level, the main differentially enriched taxa were Prevotella, Peptostreptococcus, Carnobacterium, and Diastella (P < 0.05). The species level was differentially enriched in Prevotella intermedia and Peptostreptococcus stomatis (p < 0.05). The prediction of microbiota function shows that oral cancer is mainly associated with coenzyme A biosynthesis, phosphopantothenic acid biosynthesis, inosine 5'-phosphate degradation, and riboflavin biosynthesis. Furthermore, the increase in C-reactive protein level in oral cancer patients was found to be closely related to P. intermedia. Overall, oral bacterial profiles showed significant differences between the oral cancer group and normal group. Hence, microbes can be employed as diagnostic markers and treatment targets for oral cancer.

Project description:BackgroundNonadherence to aromatase inhibitors (AIs) is common and increases risk of breast cancer (BC) recurrence. We analyzed factors associated with nonadherence among patients enrolled in S1105, a randomized trial of text messaging.MethodsAt enrollment, patients were required to have been on an adjuvant AI for at least 30 days and were asked about financial, medication, and demographic factors. They completed patient-reported outcomes (PROs) representing pain (Brief Pain Inventory), endocrine symptoms (Functional Assessment of Cancer Therapy-Endocrine Symptoms), and beliefs about medications (Treatment Satisfaction Questionnaire for Medicine; Brief Medication Questionnaire). Our primary endpoint was AI nonadherence at 36 months, defined as urine AI metabolite assay of less than 10 ng/mL or no submitted specimen. We evaluated the association between individual baseline characteristics and nonadherence with logistic regression. A composite risk score reflecting the number of statistically significant baseline characteristics was examined.ResultsWe analyzed data from 702 patients; median age was 60.9 years. Overall, 35.9% patients were nonadherent at 36 months. Younger patients (younger than age 65 years) were more nonadherent (38.8% vs 28.6%, odds ratio [OR] = 1.51, 95% confidence interval [CI] = 1.05 to 2.16; P = .02). Fourteen baseline PRO scales were each statistically significantly associated with nonadherence. In a composite risk model categorized into quartile levels, each increase in risk level was associated with a 46.5% increase in the odds of nonadherence (OR = 1.47, 95% CI =1.26 to 1.70; P < .001). The highest-risk patients were more than 3 times more likely to be nonadherent than the lowest-risk patients (OR = 3.14, 95% CI = 1.97 to 5.02; P < .001).ConclusionsThe presence of multiple baseline PRO-specified risk factors was statistically significantly associated with AI nonadherence. The use of these assessments can help identify patients for targeted interventions to improve adherence.

Project description:BackgroundWe aimed to address which antihypertensives are superior to placebo/no therapy or another antihypertensive for controlling nonsevere pregnancy hypertension and provide future sample size estimates for definitive evidence.MethodsRandomized trials of antihypertensives for nonsevere pregnancy hypertension were identified from online electronic databases, to February 28, 2021 (registration URL: https://www.crd.york.ac.uk/PROSPERO/; unique identifier: CRD42020188725). Our outcomes were severe hypertension, proteinuria/preeclampsia, fetal/newborn death, small-for-gestational age infants, preterm birth, and admission to neonatal care. A Bayesian random-effects model generated estimates of direct and indirect treatment comparisons. Trial sequential analysis informed future trials needed.ResultsOf 1246 publications identified, 72 trials were included; 61 (6923 women) were informative. All commonly prescribed antihypertensives (labetalol, other β-blockers, methyldopa, calcium channel blockers, and mixed/multi-drug therapy) versus placebo/no therapy reduced the risk of severe hypertension by 30% to 70%. Labetalol decreased proteinuria/preeclampsia (odds ratio, 0.73 [95% credible interval, 0.54-0.99]) and fetal/newborn death (odds ratio, 0.54 [0.30-0.98]) compared with placebo/no therapy, and proteinuria/preeclampsia compared with methyldopa (odds ratio, 0.66 [0.44-0.99]) and calcium channel blockers (odds ratio, 0.63 [0.41-0.96]). No other differences were identified, but credible intervals were wide. Trial sequential analysis indicated that 2500 to 10 000 women/arm (severe hypertension or safety outcomes) to >15 000/arm (fetal/newborn death) would be required to provide definitive evidence.ConclusionsIn summary, all commonly prescribed antihypertensives in pregnancy reduce the risk of severe hypertension, but labetalol may also decrease proteinuria/preeclampsia and fetal/newborn death. Evidence is lacking for many other safety outcomes. Prohibitive sample sizes are required for definitive evidence. Real-world data are needed to individualize care.

Dataset Information

Patient risk profiles and practice variation in nonadherence to antidepressants, antihypertensives and oral hypoglycemics.

Publications

Patient risk profiles and practice variation in nonadherence to antidepressants, antihypertensives and oral hypoglycemics.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets