From screening to ascertainment of the primary outcome using electronic health records: Challenges in the STRIDE trial.
Ontology highlight
ABSTRACT:
SUBMITTER: Esserman D
PROVIDER: S-EPMC7415626 | biostudies-literature | 2020 Aug
REPOSITORIES: biostudies-literature
Publications
From screening to ascertainment of the primary outcome using electronic health records: Challenges in the STRIDE trial.
Clinical trials (London, England) 20200514 4
Electronic health record data are a rich resource and can be utilized to answer a wealth of research questions. It is important when using electronic health record data in clinical trials that systems be put in place and vetted prior to enrollment to ensure data elements can be collected consistently across all health care systems. It is often overlooked how something conceptualized on paper (e.g. use of the electronic health record in a study) can be difficult to implement in practice. This art ...[more]
Similar Datasets
Project description:Background/aimIn clinical trials, there is potential for bias from unblinded observers that may influence ascertainment of outcomes. This issue arose in the Strategies to Reduce Injuries and Develop Confidence in Elders trial, a cluster randomized trial to test a multicomponent intervention versus enhanced usual care (control) to prevent serious fall injuries, originally defined as a fall injury leading to medical attention. An unblinded nurse falls care manager administered the intervention, while the usual care arm did not involve contact with a falls care manager. Thus, there was an opportunity for falls care managers to refer participants reporting falls to seek medical attention. Since this type of observer bias could not occur in the usual care arm, there was potential for additional falls to be reported in the intervention arm, leading to dilution of the intervention effect and a reduction in study power. We describe the clinical basis for ascertainment bias, the statistical approach used to assess it, and its effect on study power.MethodsThe prespecified interim monitoring plan included a decision algorithm for assessing ascertainment bias and adapting (revising) the primary outcome definition, if necessary. The original definition categorized serious fall injuries requiring medical attention into Type 1 (fracture other than thoracic/lumbar vertebral, joint dislocation, cut requiring closure) and Type 2 (head injury, sprain or strain, bruising or swelling, other). The revised definition, proposed by the monitoring plan, excluded Type 2 injuries that did not necessarily require an overnight hospitalization since these would be most subject to bias. These injuries were categorized into those with (Type 2b) and without (Type 2c) medical attention. The remaining Type 2a injuries required medical attention and an overnight hospitalization. We used the ratio of 2b/(2b + 2c) in intervention versus control as a measure of ascertainment bias; ratios > 1 indicated the likelihood of falls care manager bias. We determined the effect of ascertainment bias on study power for the revised (Types 1 and 2a) versus original definition (Types 1, 2a, and 2b).ResultsThe estimate of ascertainment bias was 1.14 (95% confidence interval: 0.98, 1.30), providing evidence of the likelihood of falls care manager bias. We estimated that this bias diluted the hazard ratio from the hypothesized 0.80 to 0.86 and reduced power to under 80% for the original primary outcome definition. In contrast, adapting the revised definition maintained study power at nearly 90%.ConclusionThere was evidence of ascertainment bias in the Strategies to Reduce Injuries and Develop Confidence in Elders trial. The decision to adapt the primary outcome definition reduced the likelihood of this bias while preserving the intervention effect and study power.
| S-EPMC8009806 | biostudies-literature
Project description:Access and utilization of electronic health records with extensive medication lists and genetic profiles is rapidly advancing discoveries in pharmacogenomics. In this study, we analyzed ~116,000 variants on the Illumina Metabochip for response to antihypertensive and lipid lowering medications in African American adults from BioVU, the Vanderbilt University Medical Center's biorepository linked to de-identified electronic health records. Our study population included individuals who were prescribed an antihypertensive or lipid lowering medication, and who had both pre- and post-medication blood pressure or low-density lipoprotein cholesterol (LDL-C) measurements, respectively. Among those with pre- and post-medication systolic and diastolic blood pressure measurements (n=2,268), the average change in systolic and diastolic blood pressure was -0.6 mg Hg and -0.8 mm Hg, respectively. Among those with pre- and post-medication LDL-C measurements (n=1,244), the average change in LDL-C was -26.3 mg/dL. SNPs were tested for an association with change and percent change in blood pressure or blood levels of LDL-C. After adjustment for multiple testing, we did not observe any significant associations, and we were not able to replicate previously reported associations, such as in APOE and LPA, from the literature. The present study illustrates the benefits and challenges with using electronic health records linked to biorepositories for pharmacogenomic studies.
| S-EPMC4720980 | biostudies-literature
Project description:ObjectivesBetter indicators from affordable, sustainable data sources are needed to monitor population burden of musculoskeletal conditions. We propose five indicators of musculoskeletal health and assessed if routinely available primary care electronic health records (EHR) can estimate population levels in musculoskeletal consulters.MethodsWe collected validated patient-reported measures of pain experience, function and health status through a local survey of adults (≥35 years) presenting to English general practices over 12 months for low back pain, shoulder pain, osteoarthritis and other regional musculoskeletal disorders. Using EHR data we derived and validated models for estimating population levels of five self-reported indicators: prevalence of high impact chronic pain, overall musculoskeletal health (based on Musculoskeletal Health Questionnaire), quality of life (based on EuroQoL health utility measure), and prevalence of moderate-to-severe low back pain and moderate-to-severe shoulder pain. We applied models to a national EHR database (Clinical Practice Research Datalink) to obtain national estimates of each indicator for three successive years.ResultsThe optimal models included recorded demographics, deprivation, consultation frequency, analgesic and antidepressant prescriptions, and multimorbidity. Applying models to national EHR, we estimated that 31.9% of adults (≥35 years) presenting with non-inflammatory musculoskeletal disorders in England in 2016/17 experienced high impact chronic pain. Estimated population health levels were worse in women, older aged and those in the most deprived neighbourhoods, and changed little over 3 years.ConclusionNational and subnational estimates for a range of subjective indicators of non-inflammatory musculoskeletal health conditions can be obtained using information from routine electronic health records.
| S-EPMC8487274 | biostudies-literature
Project description:Importancerisk factors for delirium in hospital inpatients are well established, but less is known about whether delirium occurring in the community or during an emergency admission to hospital care might be predicted from routine primary-care records.Objectivesidentify risk factors in primary-care electronic health records (PC-EHR) predictive of delirium occurring in the community or recorded in the initial episode in emergency hospitalisation. Test predictive performance against the cumulative frailty index.DesignStage 1: case-control; Stages 2 and 3: retrospective cohort.Settingclinical practice research datalink: PC-EHR linked to hospital discharge data from England.SubjectsStage 1: 17,286 patients with delirium aged ?60 years plus 85,607 controls. Stages 2 and 3: patients???60 years (n =?429,548 in 2015), split into calibration and validation groups.MethodsStage 1: logistic regression to identify associations of 110 candidate risk measures with delirium. Stage 2: calibrating risk factor weights. Stage 3: validation in independent sample using area under the curve (AUC) receiver operating characteristic.Resultsfifty-five risk factors were predictive, in domains including: cognitive impairment or mental illness, psychoactive drugs, frailty, infection, hyponatraemia and anticholinergic drugs. The derived model predicted 1-year incident delirium (AUC?=?0.867, 0.852:0.881) and mortality (AUC?=?0.846, 0.842:0.853), outperforming the frailty index (AUC?=?0.761, 0.740:0.782). Individuals with the highest 10% of predicted delirium risk accounted for 55% of incident delirium over 1 year.Conclusionsa risk factor model for delirium using data in PC-EHR performed well, identifying individuals at risk of new onsets of delirium. This model has potential for supporting preventive interventions.
| S-EPMC7297278 | biostudies-literature
Project description:Participation rates in colorectal cancer screening are below recommended European targets.To evaluate the effectiveness of an alert in primary care electronic medical records (EMRs) to increase individuals' participation in an organised, population-based colorectal cancer screening programme when compared with usual care.Cluster randomised controlled trial in primary care centres of Barcelona, Spain.Participants were males and females aged 50-69 years, who were invited to the first round of a screening programme based on the faecal immunochemical test (FIT) (n = 41 042), and their primary care professional. The randomisation unit was the physician cluster (n = 130) and patients were blinded to the study group. The control group followed usual care as per the colorectal cancer screening programme. In the intervention group, as well as usual care, an alert to health professionals (cluster level) to promote screening was introduced in the individual's primary care EMR for 1 year. The main outcome was colorectal cancer screening participation at individual participant level.In total, 67 physicians and 21 619 patients (intervention group) and 63 physicians and 19 423 patients (control group) were randomised. In the intention-to-treat analysis screening participation was 44.1% and 42.2% respectively (odds ratio 1.08, 95% confidence interval [CI] = 0.97 to 1.20, P = 0.146). However, in the per-protocol analysis screening uptake in the intervention group showed a statistically significant increase, after adjusting for potential confounders (OR, 1.11; 95% CI = 1.02 to 1.22; P = 0.018).The use of an alert in an individual's primary care EMR is associated with a statistically significant increased uptake of an organised, FIT-based colorectal cancer screening programme in patients attending primary care centres.
| S-EPMC4917051 | biostudies-literature
Project description:BackgroundThe mission of medical schools is a sustainable commitment to orient education, research, and services based on the priorities and expectations of society. The most common complaints of patients from comprehensive health service centers (CHSCs) based on the data from electronic health records were assessed in order to determine primary health care (PHC) priorities for the educational planning of medical students in Iran.MethodsA population-based national study was designed to assess clinical complaints of patients in all age groups who were referred to CHSCs at least once to be visited by physicians. All the data in the census were extracted from electronic health records in PHC system during 2015-2020, classified by the International Classification of Primary Care 2nd edition (ICPC-2e-English), and statistically analyzed. The total number of complaints that were recorded in the system was 17,430,139.Results59% of the referring patients were women. The highest number of referrals was related to the age group of 18-59 years (56.9%), while the lowest belonged to the elderly people (13.3%). In all age and sex groups, the first ten complaints of patients with three top priorities in each category included process (follow-up, consultation, and results exam), digestive (toothache and gum complaint, abdominal pain, and diarrhea), respiratory (cough, sore throat, and runny nose), general (fever, pain, and weakness and fatigue), musculoskeletal (back pain, leg complaint, and knee injuries), endocrine and nutritional (weight gain, Feeding problem, and weight loss), cardiovascular (hypertension, palpitations, and Postural hypotension), neurological (headache, dizziness, and paralysis), sexual dysfunction (vaginal complaint, discharge, and irregular menstruation), and dermatological (pruritus, rash, and inflammation) problems.ConclusionHigh priorities in referring to PHC had a key role in assessing the country's health needs. Since this study was in line with the national pattern of complaints and patients' profile, the present findings can be helpful to amend policy-making, educational planning and curricula development in medical schools.
| S-EPMC9008379 | biostudies-literature
Project description:RATIONALE: Use of a web-based risk assessment tool may help improve screening rates for colorectal cancer.
PURPOSE: This randomized clinical trial is studying personal electronic health records to see how well they work in improving screening rates for colorectal cancer.
| 2082240 | ecrin-mdr-crc
Project description:Borderline personality disorder (BoPD or BPD) is highly prevalent and characterized by reactive moods, impulsivity, behavioral dysregulation, and distorted self-image. Yet the BoPD diagnosis is underutilized and patients with BoPD are frequently misdiagnosed resulting in lost opportunities for appropriate treatment. Automated screening of electronic health records (EHRs) is one potential strategy to help identify possible BoPD patients who are otherwise undiagnosed. We present the development and analytical validation of a BoPD screening algorithm based on routinely collected and structured EHRs. This algorithm integrates rule-based selection and machine learning (ML) in a two-step framework by first selecting potential patients based on the presence of comorbidities and characteristics commonly associated with BoPD, and then predicting whether the patients most likely have BoPD. Leveraging a large-scale US-based de-identified EHR database and our clinical expert's rating of two random samples of patient EHRs, results show that our screening algorithm has a high consistency with our clinical expert's ratings, with area under the receiver operating characteristic (AUROC) 0.837 [95% confidence interval (CI) 0.778-0.892], positive predictive value 0.717 (95% CI 0.583-0.836), accuracy 0.820 (95% CI 0.768-0.873), sensitivity 0.541 (95% CI 0.417-0.667) and specificity 0.922 (95% CI 0.880-0.960). Our aim is, to provide an additional resource to facilitate clinical decision making and promote the development of digital medicine.
| S-EPMC9279396 | biostudies-literature
Project description:IntroductionElectronic health records offer a valuable resource to improve health surveillance and evaluation as well as informing clinical decision making. They have been introduced in many different settings, including low- and middle-income countries, yet little is known of the progress and effectiveness of similar information systems within Asia. This study examines the implementation of EHR systems for use at a population health level in Asia and to identify their current role within public health, key success factors, and potential barriers in implementation.Material and methodsA systematic search process was implemented. Five databases were searched with MeSH key terms and Boolean phrases. Articles selected for this review were based on hospital provider electronic records with a component of implementation, utilisation, or evaluation for health systems or at least beyond direct patient care. A proposed analytic framework considered three interactive components: the content, the process, and the context.ResultsThirty-two articles were included in the review. Evidence suggests that benefits are significant but identifying and addressing potential challenges are critical for success. A comprehensive preparation process is necessary to implement an effective and flexible system.DiscussionElectronic health records implemented for public health can allow the identification of disease patterns, seasonality, and global trends as well as risks to vulnerable populations. Addressing implementation challenges will facilitate the development and efficacy of public health initiatives in Asia to identify current health needs and mitigate future risks.
| S-EPMC6644215 | biostudies-literature
Project description:BackgroundPrevalence of electronic health records (EHRs) has significantly increased, and EHRs are a known contributor to clinician burnout. However, it is unknown whether the use of multifunctional EHRs is associated with nurse practitioner (NP) burnout in primary care practices. This is a major gap in the literature because 69% of practicing NPs deliver primary care services to patients.PurposeThis study aimed to investigate whether the use of multifunctional EHRs is associated with primary care NP burnout.MethodThis study is a secondary analysis of cross-sectional survey data collected from NPs in two states (Pennsylvania and New Jersey). Nurse practitioners completed surveys measuring burnout, use of multifunctional EHRs, demographics, and characteristics of their practice. Use of multifunctional EHRs was operationalized using two items-computerized capabilities and electronic reminder systems. Burnout was measured using a validated, single item asking NPs to self-report their feelings of burnout. A multilevel cox regression model was built to test for associations between the use of multifunctional EHRs and NP burnout.ResultsOf 396 NPs included, 25.3% reported burnout. The use of multifunctional EHRs did not increase primary care NP burnout (risk ratio = 0.30, 95% confidence interval = 0.13-0.71, p = .01).Implications for practiceWith 25.3% of NPs burned out, it is imperative to reduce NP burnout. However, computerized capabilities and electronic reminder systems did not contribute to feelings of NP burnout. Future research examining other EHR components is needed to understand which features of the EHR contribute to NP burnout.
| S-EPMC8351449 | biostudies-literature