Measuring and controlling medical record abstraction (MRA) error rates in an observational study.

BACKGROUND: Studies have shown that data collection by medical record abstraction (MRA) is a significant source of error in clinical research studies relying on secondary use data. Yet, the quality of data collected using MRA is seldom assessed. We employed a novel, theory-based framework for data quality assurance and quality control of MRA. The objective of this work is to determine the potential impact of formalized MRA training and continuous quality control (QC) processes on data quality over time. METHODS: We conducted a retrospective analysis of QC data collected during a cross-sectional medical record review of mother-infant dyads with Neonatal Opioid Withdrawal Syndrome. A confidence interval approach was used to calculate crude (Wald\u27s method) and adjusted (generalized estimating equation) error rates over time. We calculated error rates using the number of errors divided by total fields ( all-field error rate) and populated fields ( populated-field error rate) as the denominators, to provide both an optimistic and a conservative measurement, respectively. RESULTS: On average, the ACT NOW CE Study maintained an error rate between 1% (optimistic) and 3% (conservative). Additionally, we observed a decrease of 0.51 percentage points with each additional QC Event conducted. CONCLUSIONS: Formalized MRA training and continuous QC resulted in lower error rates than have been found in previous literature and a decrease in error rates over time. This study newly demonstrates the importance of continuous process controls for MRA within the context of a multi-site clinical research study

Addressing COVID-19 vaccine hesitancy in rural community pharmacies: a protocol for a stepped wedge randomized clinical trial

Background: Uptake of COVID-19 vaccines remains problematically low in the USA, especially in rural areas. COVID-19 vaccine hesitancy is associated with lower uptake, which translates to higher susceptibility to SARS-CoV-2 variants in communities where vaccination coverage is low. Because community pharmacists are among the most accessible and trusted health professionals in rural areas, this randomized clinical trial will examine implementation strategies to support rural pharmacists in delivering an adapted evidence-based intervention to reduce COVID-19 vaccine hesitancy. Methods: We will use an incomplete stepped wedge trial design in which we will randomize 30 rural pharmacies (unit of analysis) to determine the effectiveness and incremental cost-effectiveness of a standard implementation approach (consisting of online training that describes the vaccine hesitancy intervention, live webinar, and resource website) compared to adding on a virtual facilitation approach (provided by a trained facilitator in support of the delivery of the vaccine hesitancy counseling intervention by pharmacists). The intervention (ASORT) has been adapted from an evidence-based vaccine communication intervention for HPV vaccines through a partnership with rural pharmacies in a practice-based research network in seven southern US states. ASORT teaches pharmacists how to identify persons eligible for COVID-19 vaccination (including a booster), solicit and address vaccine concerns in a non-confrontational way, recommend the vaccine, and repeat the steps later if needed. The primary trial outcome is fidelity to the ASORT intervention, which will be determined through ratings of recordings of pharmacists delivering the intervention. The secondary outcome is the effectiveness of the intervention, determined by rates of patients who agree to be vaccinated after receiving the intervention. Other secondary outcomes include feasibility, acceptability, adoption, reach, and cost. Cost-effectiveness and budget impact analyses will be conducted to maximize the potential for future dissemination and sustainability. Mixed methods will provide triangulation, expansion, and explanation of quantitative findings. Discussion: This trial contributes to a growing evidence base on vaccine hesitancy interventions and virtual-only facilitation of evidenced-based practices in community health settings. The trial will provide the first estimate of the relative value of different implementation strategies in pharmacy settings. Trial registration: NCT05926544 (clinicaltrials.gov); 07/03/2023

Analysis of TaqMan Array Cards Data by an Assumption-Free Improvement of the maxRatio Algorithm Is More Accurate than the Cycle-Threshold Method

<div><p>Quantitative PCR diagnostic platforms are moving towards increased sample throughput, with instruments capable of carrying out thousands of reactions at once already in use. The need for a computational tool to reliably assist in the validation of the results is therefore compelling. In the present study, 328 residual clinical samples provided by the Public Health England at Addenbrooke's Hospital (Cambridge, UK) were processed by TaqMan Array Card assay, generating 15 744 reactions from 54 targets. The amplification data were analysed by the conventional cycle-threshold (CT) method and an improvement of the <i>maxRatio</i> (MR) algorithm developed to filter out the reactions with irregular amplification profiles. The reactions were also independently validated by three raters and a consensus was generated from their classification. The inter-rater agreement by Fleiss' kappa was 0.885; the agreement between either CT or MR with the raters gave Fleiss' kappa 0.884 and 0.902, respectively. Based on the consensus classification, the CT and MR methods achieved an assay accuracy of 0.979 and 0.987, respectively. These results suggested that the assumption-free MR algorithm was more reliable than the CT method, with clear advantages for the diagnostic settings.</p></div

The Associations of Diagnoses of Fatigue and Depression with Use of Medical Services in Patients with Heart Failure

© Wolters Kluwer Health, Inc. All rights reserved. Background: Fatigue and depression based on self-report and diagnosis are prevalent in patients with heart failure and adversely affect high rates of hospitalization and emergency department visits, which can impact use of medical services. The relationships of fatigue and depression to use of medical services in patients with preserved and reduced left ventricular ejection fraction (LVEF) may differ. Purpose: We examined the associations of diagnoses of fatigue and depression with use of medical services in patients with preserved and reduced LVEF, controlling for covariates. Methods: Data were collected on fatigue, depression, covariates, and use of medical services. Patients (N = 582) were divided into 2 groups based on LVEF (<40%, reduced LVEF; ≥40%, preserved LVEF). Multiple linear regression analyses were used to analyze the data. Results: A diagnosis of fatigue was a significant factor associated with more use of medical services in the total sample (β =.18, P <.001, R2 = 54%) and patients with reduced LVEF (β =.13, P =.008, R2 = 54%) and also preserved LVEF (β =.21, P <.001, R2 = 54%), controlling for all covariates, but a diagnosis of depression was not. Conclusions: This study demonstrates the important roles of a diagnosis of fatigue in use of medical services. Thus, fatigue needs to be assessed, diagnosed, and managed effectively

Prediction of Heart Failure Symptoms and Health-Related Quality of Life at 12 Months From Baseline Modifiable Factors in Patients With Heart Failure.

BackgroundIn patients with heart failure (HF), good health-related quality of life (HRQOL) is as valuable as, or more valuable than, longer survival. However, HRQOL is remarkably poor, and HF symptoms are strongly associated with poor HRQOL. Yet, the multidimensional, modifiable predictors have been rarely examined.ObjectiveThe aim of this study was to examine the baseline psychosocial, behavioral, and physical predictors of HF symptoms and HRQOL at 12 months and the mediator effect of HF symptoms in the relationship between depressive symptoms and HRQOL.MethodsWe collected data from 94 patients with HF (mean ± SD age, 58 ± 14 years). Data included sample characteristics, depressive symptoms, perceived control, social support, New York Heart Association (NYHA) functional class, medication adherence, sodium intake, self-care management, and HF symptoms at baseline, as well as HF symptoms and HRQOL at 12 months. Multiple regression analyses were performed to address the purpose.ResultsBaseline depressive symptoms (P ConclusionSymptoms of HF and HRQOL could be improved by targeting multidimensional, modifiable predictors, such as self-care, depressive symptoms, and NYHA functional class