Publications by authors named "Marsha A Raebel"

Purpose: To estimate prevalence of prescription opioid use during pregnancy in eight US health plans during 2001-2014.

Methods: We conducted a cohort study of singleton live birth deliveries. Maternal characteristics were ascertained from health plan and/or birth certificate data and opioids dispensed during pregnancy from health plan pharmacy records.

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Context: Refill reminders can help patients improve adherence to inhaled corticosteroid (ICS) therapy. However, little is known about patient preferences for reminder type or whether patients who express a preference differ from patients who do not.

Objectives: To describe patient preferences for ICS prescription refill reminder type and to compare baseline ICS therapy adherence, measured as proportion of days covered (PDC) 1 year before initiating preference-based reminders, between patients who did and did not express a preference.

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Use of digital communication technologies (DCT) shows promise for enhancing outcomes and efficiencies in asthma care management. However, little is known about the impact of DCT interventions on healthcare personnel requirements and costs, thus making it difficult for providers and health systems to understand the value of these interventions. This study evaluated the differences in healthcare personnel requirements and costs between usual asthma care (UC) and a DCT intervention (Breathewell) aimed at maintaining guidelines-based asthma care while reducing health care staffing requirements.

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Purpose: The use of validated criteria to identify birth defects in electronic healthcare databases can avoid the cost and time-intensive efforts required to conduct chart reviews to confirm outcomes. This study evaluated the validity of various case-finding methodologies to identify neural tube defects (NTDs) in infants using an electronic healthcare database.

Methods: This analysis used data generated from a study whose primary aim was to evaluate the association between first-trimester maternal prescription opioid use and NTDs.

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Background: Challenges to health care efficiency are increasingly addressed with the help of digital communication technology tools (DCTs).

Objective: The objective of this study was to test whether DCT, compared with Usual Care, can reduce health care clinician burden without increasing asthma-related exacerbations among patients with asthma in a large integrated health care system.

Research Design: The (Breathewell) program was a pragmatic, randomized trial at (Kaiser Permanente Colorado), where asthma nurses screen patients for poor symptom control when beta2-agonist refill requests came within 60 days of previous fill or in the absence of a controller medication fill within 4 months (beta2-agonist overfill).

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RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) and CFIR (Consolidated Framework for Implementation Research) dissemination and implementation frameworks define theory-based domains associated with the adoption, implementation and maintenance of evidence-based interventions. Used together, the two frameworks identify metrics for evaluating implementation success, i.e.

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Clinical laboratory quality improvement (QI) efforts can include population test utilization. The authors used a health care organization's Medical Data Warehouse (MDW) to characterize a gap in guideline-concordant laboratory testing recommended for safe use of antirheumatic agents, then tested the effectiveness of laboratory-led, technology-enabled outreach to patients at reducing this gap. Data linkages available through the Kaiser Permanente Colorado MDW and electronic health record were used to identify ambulatory adults taking antirheumatic agents who were due/overdue for alanine aminotransferase (ALT), aspartate aminotransferase (AST), complete blood count (CBC), or serum creatinine (SCr) testing.

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Objectives: Previous analyses of data from 3 large health plans suggested that the substantial downward trend in antibiotic use among children appeared to have attenuated by 2010. Now, data through 2014 from these same plans allow us to assess whether antibiotic use has declined further or remained stable.

Methods: Population-based antibiotic-dispensing rates were calculated from the same health plans for each study year between 2000 and 2014.

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Distributed data networks enable large-scale epidemiologic studies, but protecting privacy while adequately adjusting for a large number of covariates continues to pose methodological challenges. Using 2 empirical examples within a 3-site distributed data network, we tested combinations of 3 aggregate-level data-sharing approaches (risk-set, summary-table, and effect-estimate), 4 confounding adjustment methods (matching, stratification, inverse probability weighting, and matching weighting), and 2 summary scores (propensity score and disease risk score) for binary and time-to-event outcomes. We assessed the performance of combinations of these data-sharing and adjustment methods by comparing their results with results from the corresponding pooled individual-level data analysis (reference analysis).

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Context.—: The laboratory total testing process includes preanalytic, analytic, and postanalytic phases, but most laboratory quality improvement efforts address the analytic phase. Expanding quality improvement to preanalytic and postanalytic phases via use of medical data warehouses, repositories that include clinical, utilization, and administrative data, can improve patient care by ensuring appropriate test utilization.

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Background: The incidence of pregnancy-associated cancer (PAC) is expected to increase as more women delay childbearing until later ages. However, information on frequency and incidence of PAC is scarce in the United States.

Methods: We identified pregnancies among women aged 10-54 years during 2001-2013 from five U.

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Background: The Medicare STAR program for Medicare Advantage Plans that include drug benefits provides monetary incentives for health plans to achieve good adherence to oral antihyperglycemic (OAH) agents but does not account for differential case mix that could affect the ability of health plans to achieve the required quality metrics.

Objective: To determine whether OAH adherence varies by age and comorbidities among patients aged 65 years or older and the extent to which adherence affects glycemic control across age and comorbidity strata.

Methods: We studied 54,480 patients with diabetes aged > 65 years from the Colorado, Northwest, and Northern California regions of Kaiser Permanente who received OAH agents but not insulin in 2010.

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Purpose: In this report, we use data from FDA's Sentinel System to focus on how augmenting a diagnosis-based chronic kidney disease cohort with patients identified through laboratory results impacts cohort characteristics and outcomes.

Methods: We used data from 2 Data Partners. Patients were eligible if they were health plan members on January 1, 2012.

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Background: New health policies may have intended and unintended consequences. Active surveillance of population-level data may provide initial signals of policy effects for further rigorous evaluation soon after policy implementation.

Objective: This study evaluated the utility of sequential analysis for prospectively assessing signals of health policy impacts.

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Holidays from bisphosphonates (BPs) may help to prevent rare adverse events such as atypical femoral fractures, but may be appropriate only if risk of osteoporosis-related fractures does not increase. Our objective was to compare the incidence of osteoporosis-related fractures among women who had a BP holiday to those who continued to use BPs. This retrospective cohort study, conducted within four Kaiser Permanente integrated health system regions, included 39,502 women aged ≥45 years with ≥3 years exposure to BP.

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Purpose: Algorithms using information from electronic health records to identify adults with type 1 diabetes have not been well studied. Such algorithms would have applications in pharmacoepidemiology, drug safety research, clinical trials, surveillance, and quality improvement. Our main objectives were to determine the positive predictive value for identifying type 1 diabetes in adults using a published algorithm (developed by Klompas et al) and to compare it to a simple requirement that the majority of diabetes diagnosis codes be type 1.

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Background & Aims: Reported prevalence of primary biliary cholangitis (PBC) varies widely. Demographic features and treatment patterns are not well characterized in the United States (US). We analyzed data from the Fibrotic Liver Disease (FOLD) Consortium, drawn from 11 geographically diverse health systems, to investigate epidemiologic factors and treatment of PBC in the US.

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Aim: To understand stakeholders' views on data sharing in multicenter comparative effectiveness research studies and the value of privacy-protecting methods.

Materials & Methods: Semistructured interviews with five US stakeholder groups.

Results: We completed 11 interviews, involving patients (n = 15), researchers (n = 10), Institutional Review Board and regulatory staff (n = 3), multicenter research governance experts (n = 2) and healthcare system leaders (n = 4).

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Background: The Centers for Medicare and Medicaid Services (CMS) Medicare Star program provides incentives to health plans when their patients with diabetes meet adherence targets to angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers (ACEIs/ARBs) and statins. While a link between adherence and cardiovascular risk factor control is established, most studies included young patients with few comorbidities. Whether the Star adherence target is associated with reduced blood pressure or low-density lipoprotein cholesterol (LDL-C) in complex older patients is not well understood.

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Controversy exists about breast cancer risk associated with long-term use of calcium channel blockers (CCBs) or angiotensin-converting enzyme inhibitors (ACEis), respectively. Our objective in this study was to separately evaluate associations between duration of CCB or ACEi use and breast cancer in hypertensive women aged ≥55 years at 3 sites in the Kaiser Permanente health-care system (1997–2012). Exposures included CCB or ACEi use of 1–12 years’ duration, determined from pharmacy dispensings.

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Aim: Laboratory test (lab) results may be useful to detect incident diabetes in electronic health record and claims-based studies.

Research Design & Methods: Using the Mini-Sentinel distributed database, we assessed the value of lab results added to diagnosis codes and dispensing claims to identify incident diabetes.

Results: Inclusion of lab results increased the number of diabetes outcomes identified by 21%.

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Introduction: The identification of upper gastrointestinal (UGI) bleeding and perforated ulcers in claims data typically relies on inpatient diagnoses. The use of hemoglobin laboratory results might increase the detection of UGI events that do not lead to hospitalization.

Objectives: Our objective was to evaluate whether hemoglobin results increase UGI outcome identification in electronic databases, using non-steroidal anti-inflammatory drugs (NSAIDs) as a test case.

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Purpose: Our purpose was to quantify missing baseline laboratory results, assess predictors of missingness, and examine performance of missing data methods.

Methods: Using the Mini-Sentinel Distributed Database from three sites, we selected three exposure-outcome scenarios with laboratory results as baseline confounders. We compared hazard ratios (HRs) or risk differences (RDs) and 95% confidence intervals (CIs) from models that omitted laboratory results, included only available results (complete cases), and included results after applying missing data methods (multiple imputation [MI] regression, MI predictive mean matching [PMM] indicator).

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Purpose: The objective of this study was to evaluate regression, matching, and stratification on propensity score (PS) or disease risk score (DRS) in a setting of sequential analyses where statistical hypotheses are tested multiple times.

Methods: In a setting of sequential analyses, we simulated incident users and binary outcomes with different confounding strength, outcome incidence, and the adoption rate of treatment. We compared Type I error rate, empirical power, and time to signal using the following confounder adjustments: (i) regression; (ii) treatment matching (1:1 or 1:4) on PS or DRS; and (iii) stratification on PS or DRS.

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