Dataset Information

Association of Healthcare Plan with atrial fibrillation prescription patterns.

ABSTRACT:

Background

Atrial fibrillation (AF) is treated by many types of physician specialists, including primary care physicians (PCPs). Health plans have different policies for how patients encounter these providers, and these may affect selection of AF treatment strategy.

Hypothesis

We hypothesized that healthcare plans with PCP-gatekeeping to specialist access may be associated with different pharmacologic treatments for AF.

Methods

We performed a retrospective cohort study using a commercial pharmaceutical claims database. We utilized logistic regression models to compare odds of prescription of oral anticoagulant (OAC), non-vitamin K-dependent oral anticoagulant (NOAC), rate control, and rhythm control medications used to treat AF between patients with PCP-gated healthcare plans (eg, HMO, EPO, POS) and patients with non-PCP-gated healthcare plans (eg, PPO, CHDP, HDHP, comprehensive) between 2007 and 2012. We also calculated median time to receipt of therapy within 90 days of index AF diagnosis.

Results

We found similar odds of OAC prescription at 90 days following new AF diagnosis in patients with PCP-gated plans compared to those with non-PCP-gated plans (OR: OAC 1.01, P = 0.84; warfarin 1.05, P = 0.08). Relative odds were similar for rate control (1.17, P < 0.01) and rhythm control agents (0.93, P = 0.03). However, PCP-gated plan patients had slightly lower likelihood of being prescribed NOACs (0.82, P = 0.001) than non-gated plan patients. Elapsed time until receipt of medication was similar between PCP-gated and non-gated groups across drug classes.

Conclusions

Pharmaceutical claims data do not suggest that PCP-gatekeeping by healthcare plans is a structural barrier to AF therapy, although it was associated with lower use of NOACs.

SUBMITTER: Chang AY

PROVIDER: S-EPMC6489790 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Association of Healthcare Plan with atrial fibrillation prescription patterns.

Chang Andrew Young AY Askari Mariam M Fan Jun J Heidenreich Paul A PA Michael Ho P P Mahaffey Kenneth W KW Ullal Aditya Jathin AJ Perino Alexander Carroll AC Turakhia Mintu P MP

Clinical cardiology 20180922 9

<h4>Background</h4>Atrial fibrillation (AF) is treated by many types of physician specialists, including primary care physicians (PCPs). Health plans have different policies for how patients encounter these providers, and these may affect selection of AF treatment strategy.<h4>Hypothesis</h4>We hypothesized that healthcare plans with PCP-gatekeeping to specialist access may be associated with different pharmacologic treatments for AF.<h4>Methods</h4>We performed a retrospective cohort study usin ...[more]

PMID: 30098034

Similar Datasets

Project description:Early cardiology involvement after atrial fibrillation (AF) diagnosis is associated with increased oral anticoagulant prescription fills and reduced stroke risk. It is unknown if this association varies by race, sex, or education. We examined anticoagulant fills in 223,891 patients with incident nonvalvular AF (mean age = 71 years; 44% women; 84% white; 9% black; 5% Hispanic; 2% Asian) from the Optum Clinformatics database (2009 to 2014). Provider specialty and filled anticoagulant prescriptions 3 months before and 6 months after AF diagnosis were obtained. Poisson regression was used to compute the probability of oral anticoagulant prescription fill and Cox regression was used to estimate the risk of stroke and major bleeding. Cardiology involvement was less likely among nonwhites (white = Referent; black = relative risk = 0.96, 95% confidence interval (0.95 to 0.97); Hispanic = 0.99 (0.98 to 1.00); Asian = 0.95 (0.93 to 0.97)) and women (0.92 (0.91 to 0.93)), but more likely with higher education level (high school or less = Referent; some college = 1.03 (1.02 to 1.04); college or more = 1.08 (1.07 to 1.09)). Patients seen by cardiology providers were more likely to fill anticoagulant prescriptions (Any = 1.67 (1.64 to 1.69); direct oral anticoagulants = 2.59 (2.49 to 2.68); warfarin = 1.38 (1.35 to 1.41)) compared with patients not seen by a cardiology provider. Patients seen by a cardiologist had a reduced stroke risk (hazard ratio = 0.84 (0.79 to 0.88)) and similar bleeding risk (1.01 (0.96 to 1.06)). Outcomes did not vary by race, sex, or education level. In conclusion, although race, sex, and education differences exist in early cardiology involvement after AF diagnosis, the influence of cardiology involvement on anticoagulant prescription fills and AF-related outcomes does not vary by these factors. Initiatives to improve early cardiology referral in nonwhites, women, and those with lower educational attainment may improve AF outcomes.

Project description:CONTEXT:Although the heritability of atrial fibrillation (AF) is established, the contribution of familial AF to predicting new-onset AF remains unknown. OBJECTIVE:To determine whether familial occurrence of AF is associated with new-onset AF beyond established risk factors. DESIGN, SETTING, AND PARTICIPANTS:The Framingham Heart Study, a prospective community-based cohort study started in 1948. Original and Offspring Cohort participants were aged at least 30 years, were free of AF at the baseline examination, and had at least 1 parent or sibling enrolled in the study. The 4421 participants in this analysis (mean age, 54 [SD, 13] years; 54% women) were followed up through December 31, 2007. MAIN OUTCOME MEASURES:Incremental predictive value of incorporating different features of familial AF (any familial AF, premature familial AF [onset ?65 years old], number of affected relatives, and youngest age of onset in a relative) into a risk model for new-onset AF. RESULTS:Across 11,971 examinations during the period 1968-2007, 440 participants developed AF. Familial AF occurred among 1185 participants (26.8%) and premature familial AF occurred among 351 participants (7.9%). Atrial fibrillation occurred more frequently among participants with familial AF than without familial AF (unadjusted absolute event rates of 5.8% and 3.1%, respectively). The association was not attenuated by adjustment for AF risk factors (multivariable-adjusted hazard ratio, 1.40; 95% confidence interval [CI], 1.13-1.74) or reported AF-related genetic variants. Among the different features of familial AF examined, premature familial AF was associated with improved discrimination beyond traditional risk factors to the greatest extent (traditional risk factors, C statistic, 0.842 [95% CI, 0.826-0.858]; premature familial AF, C statistic, 0.846 [95% CI, 0.831-0.862]; P = .004). Modest changes in integrated discrimination improvement were observed with premature familial AF (2.1%). Net reclassification improvement (assessed using 8-year risk thresholds of <5%, 5%-10%, and >10%) did not change significantly with premature familial AF (index statistic, 0.011; 95% CI, -0.021 to 0.042; P = .51), although categoryless net reclassification was improved (index statistic, 0.127; 95% CI, 0.064-0.189; P = .009). CONCLUSIONS:In this cohort, familial AF was associated with an increased risk of AF that was not attenuated by adjustment for AF risk factors including genetic variants. Assessment of premature familial AF was associated with a very slight increase in predictive accuracy compared with traditional risk factors.

Project description:BACKGROUND:Device-detected atrial fibrillation (AF) is associated with increased risk of stroke; however, there are no clearly defined thresholds of AF burden at which to initiate oral anticoagulation (OAC). We sought to describe OAC prescription practice variation in response to new device-detected AF and the association with outcomes. METHODS:We performed a retrospective cohort study using data from the Veterans Health Administration linked to remote monitoring data that included day-level AF burden. We included patients with cardiac implantable electronic devices and remote monitoring from 2011 to 2014, CHA2DS2-VASc score ≥2, and no prior stroke or OAC receipt in the preceding 2 years. We determined the proportion of patients prescribed OAC within 90 days after new device-detected AF across a range of AF thresholds (≥6 minutes to >24 hours) and examined site variation in OAC prescription. We used multivariable Cox proportional hazards regressions to determine the association of OAC prescription with stroke by device-detected AF burden. RESULTS:Among 10 212 patients with cardiac implantable electronic devices, 4570 (45%), 3969 (39%), 3263 (32%), and 2469 (24%) had device-detected AF >6 minutes, >1 hour, >6 hours, and >24 hours, respectively. For device-detected AF >1 hour, 1712 patients met inclusion criteria (72±10 years; 1.5% female; CHA2DS2-VASc score 4.0±1.4; HAS-BLED score 2.6±1.1). The proportion receiving OAC varied based on device-detected AF burden (≥6 minutes: 272/2101 [13%]; >1 hour: 273/1712 [16%]; >6 hours: 263/1279 [21%]; >24 hours: 224/818 [27%]). Across 52 sites (N=1329 patients), there was substantial site-level variation in OAC prescription after device-detected AF >1 hour (median, 16%; range, 3%-67%; median odds ratio, 1.56 [95% credible interval, 1.49-1.71]). In adjusted models, OAC prescription after device-detected AF >24 hours was associated with reduced stroke risk (hazard ratio, 0.28; 95% CI, 0.10-0.81; P=0.02), although the propensity-adjusted model was significant when AF lasted at least 6 minutes. CONCLUSIONS:Among veterans with cardiac implantable electronic devices, device-detected AF is common. There is large practice variation in 90-day OAC initiation after new device-detected AF, with low rates of treatment overall, even for episodes that last >24 hours. The strongest association of OAC with reduction in stroke was observed after device-detected AF >24 hours. Randomized trials are needed to confirm these observational findings.

Dataset Information

Association of Healthcare Plan with atrial fibrillation prescription patterns.

Background

Hypothesis

Methods

Results

Conclusions

Publications

Association of Healthcare Plan with atrial fibrillation prescription patterns.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets