Creating a Medication Therapy Observational Research Database from an Electronic Medical Record: Challenges and Data Curation
Ontology highlight
ABSTRACT:
SUBMITTER: Rodle W
PROVIDER: S-EPMC10849827 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The use of electronic medical record (EMR) data is necessary to improve clinical research efficiency. However, it is not easy to identify patients who meet research eligibility criteria and collect the necessary information from EMRs because the data collection process must integrate various techniques, including the development of a data warehouse and translation of eligibility criteria into computable criteria. This research aimed to demonstrate an electronic medical records retrieval system (ERS) and an example of a hospital-based cohort study that identified both patients and exposure with an ERS. We also evaluated the feasibility and usefulness of the method. The system was developed and evaluated. In total, 800 000 cases of clinical information stored in EMRs at our hospital were used. The feasibility and usefulness of the ERS, the method to convert text from eligible criteria to computable criteria, and a confirmation method to increase research data accuracy. To comprehensively and efficiently collect information from patients participating in clinical research, we developed an ERS. To create the ERS database, we designed a multidimensional data model optimised for patient identification. We also devised practical methods to translate narrative eligibility criteria into computable parameters. We applied the system to an actual hospital-based cohort study performed at our hospital and converted the test results into computable criteria. Based on this information, we identified eligible patients and extracted data necessary for confirmation by our investigators and for statistical analyses with our ERS. We propose a pragmatic methodology to identify patients from EMRs who meet clinical research eligibility criteria. Our ERS allowed for the efficient collection of information on the eligibility of a given patient, reduced the labour required from the investigators and improved the reliability of the results.
| S-EPMC3533000 | biostudies-literature
Project description:This study investigated burden of 'not well-controlled' asthma, overall and by Global Initiative for Asthma (GINA) Step, among treated asthma patients in Practice Fusion's research database. Asthma control (Asthma Control Test [ACT]) was stratified by GINA Step; prevalence ratios were estimated using Poisson regression with robust variance controlled for confounders. ACT scores ≤19 reflect not well-controlled; >19 reflect 'well-controlled' asthma. Of 15,579 patients, 30% had not well-controlled asthma at index date. The proportion of patients with not well-controlled asthma increased from GINA Step 1 (29%) to Step 5 (45%). Compared with Step 1, the proportion of patients with not well-controlled asthma was 0.87-times lower in Step 2, 1.10-times greater in Step 4, and 1.37-times greater in Step 5. Results suggest that despite available treatments, patients remain symptomatic across GINA Steps in real-world primary care and specialist outpatient practices, with incremental disease burden and unmet medical need in these populations.
| S-EPMC10140050 | biostudies-literature
Project description:Recent successes in the use of gene sequencing for patient care highlight the potential of genomic medicine. For genomics to become a part of usual care, pertinent elements of a patient's genomic test must be communicated to the most appropriate care providers. Electronic medical records may serve as a useful tool for storing and disseminating genomic data. Yet, the structure of existing EMRs and the nature of genomic data pose a number of pragmatic and ethical challenges in their integration. Through a review of the recent genome-EMR integration literature, we explore concrete examples of these challenges, categorized under four key questions: What data will we store? How will we store it? How will we use it? How will we protect it? We conclude that genome-EMR integration requires a rigorous, multi-faceted and interdisciplinary approach of study. Problems facing the field are numerous, but few are intractable.
| S-EPMC4489153 | biostudies-literature
Project description:Unstructured data encountered during retrospective electronic medical record (EMR) abstraction has routinely been identified as challenging to reliably abstract, as these data are often recorded as free text, without limitations to format or structure. There is increased interest in reliably abstracting this type of data given its prominent role in care coordination and communication, yet limited methodological guidance exists.As standard abstraction approaches resulted in substandard data reliability for unstructured data elements collected as part of a multisite, retrospective EMR study of hospital discharge communication quality, our goal was to develop, apply and examine the utility of a phase-based approach to reliably abstract unstructured data. This approach is examined using the specific example of discharge communication for warfarin management.We adopted a "fit-for-use" framework to guide the development and evaluation of abstraction methods using a 4-step, phase-based approach including (1) team building; (2) identification of challenges; (3) adaptation of abstraction methods; and (4) systematic data quality monitoring.Unstructured data elements were the focus of this study, including elements communicating steps in warfarin management (eg, warfarin initiation) and medical follow-up (eg, timeframe for follow-up).After implementation of the phase-based approach, interrater reliability for all unstructured data elements demonstrated ?'s of ?0.89-an average increase of +0.25 for each unstructured data element.As compared with standard abstraction methodologies, this phase-based approach was more time intensive, but did markedly increase abstraction reliability for unstructured data elements within multisite EMR documentation.
| S-EPMC5024721 | biostudies-literature
Project description:The National Comprehensive Cancer Network expanded their lung cancer screening (LCS) criteria to comprise one additional clinical risk factor, including chronic obstructive pulmonary disease (COPD). The electronic medical record (EMR) is a source of clinical information that could identify high-risk populations for LCS, including a diagnosis of COPD; however, an unsubstantiated COPD diagnosis in the EMR may lead to inappropriate LCS referrals. We aimed to detect the prevalence of unsubstantiated COPD diagnosis in the EMR for LCS referrals, to determine the efficacy of utilizing the EMR as an accurate population-based eligibility screening "trigger" using modified clinical criteria. We performed a multicenter review of all individuals referred to three LCS programs from 2012 to 2015. Each individual's EMR was searched for COPD diagnostic terms and the presence of a diagnostic pulmonary functionality test (PFT). An unsubstantiated COPD diagnosis was defined by an individual's EMR containing a COPD term with no PFTs present, or the presence of PFTs without evidence of obstruction. A total of 2834 referred individuals were identified, of which 30% (840/2834) had a COPD term present in their EMR. Of these, 68% (571/840) were considered unsubstantiated diagnoses: 86% (489/571) due to absent PFTs and 14% (82/571) due to PFTs demonstrating no evidence of postbronchodilation obstruction. A large proportion of individuals referred for LCS may have an unsubstantiated COPD diagnosis within their EMR. Thus, utilizing the EMR as a population-based eligibility screening tool, employing expanded criteria, may lead to individuals being referred, potentially, inappropriately for LCS.
| S-EPMC7136785 | biostudies-literature
Project description:IntroductionElectronic medication administration record (eMAR) systems are promoted as a potential intervention to enhance medication safety in residential aged care facilities (RACFs). The purpose of this study was to conduct an in-practice evaluation of an eMAR being piloted in one Australian RACF before its roll out, and to provide recommendations for system improvements.MethodsA multidisciplinary team conducted direct observations of workflow (n=34 hours) in the RACF site and the community pharmacy. Semi-structured interviews (n=5) with RACF staff and the community pharmacist were conducted to investigate their views of the eMAR system. Data were analysed using a grounded theory approach to identify challenges associated with the design of the eMAR system.ResultsThe current eMAR system does not offer an end-to-end solution for medication management. Many steps, including prescribing by doctors and communication with the community pharmacist, are still performed manually using paper charts and fax machines. Five major challenges associated with the design of eMAR system were identified: limited interactivity; inadequate flexibility; problems related to information layout and semantics; the lack of relevant decision support; and system maintenance issues. We suggest recommendations to improve the design of the eMAR system and to optimize existing workflows.DiscussionImmediate value can be achieved by improving the system interactivity, reducing inconsistencies in data entry design and offering dedicated organisational support to minimise connectivity issues. Longer-term benefits can be achieved by adding decision support features and establishing system interoperability requirements with stakeholder groups (e.g. community pharmacies) prior to system roll out. In-practice evaluations of technologies like eMAR system have great value in identifying design weaknesses which inhibit optimal system use.
| S-EPMC4287675 | biostudies-literature
Project description:We describe quality improvement and practice-based research using the electronic medical record (EMR) in a community health system-based department of neurology. Our care transformation initiative targets 10 neurologic disorders (brain tumors, epilepsy, migraine, memory disorders, mild traumatic brain injury, multiple sclerosis, neuropathy, Parkinson disease, restless legs syndrome, and stroke) and brain health (risk assessments and interventions to prevent Alzheimer disease and related disorders in targeted populations). Our informatics methods include building and implementing structured clinical documentation support tools in the EMR; electronic data capture; enrollment, data quality, and descriptive reports; quality improvement projects; clinical decision support tools; subgroup-based adaptive assignments and pragmatic trials; and DNA biobanking. We are sharing EMR tools and deidentified data with other departments toward the creation of a Neurology Practice-Based Research Network. We discuss practical points to assist other clinical practices to make quality improvements and practice-based research in neurology using the EMR a reality.
| S-EPMC4634157 | biostudies-literature
Project description:With increasingly ubiquitous electronic medical record (EMR) implementation accelerated by the adoption of the HITECH Act, there is much interest in the secondary use of collected data to improve outcomes and promote personalized medicine. A plethora of research has emerged using EMRs to investigate clinical research questions and assess variations in both treatments and outcomes. However, whether because of genuine complexities of modeling disease physiology or because of practical problems regarding data capture, data accuracy, and data completeness, the state of current EMR research is challenging and gives rise to concerns regarding study accuracy and reproducibility. This work explores challenges in how different experimental design decisions can influence results using a specific example of breast cancer patients undergoing excision and reconstruction surgeries from EMRs in an academic hospital and the Veterans Health Administration (VHA) We discuss emerging strategies that will mitigate these limitations, including data sharing, application of natural language processing, and improved EMR user design.
| S-EPMC5933881 | biostudies-literature
Project description:BackgroundPoor medication adherence is common; however, few mechanisms exist in clinical practice to monitor how patients take medications in outpatient settings.ObjectiveThis study aimed to pilot test the Electronic Medication Complete Communication (EMC2) strategy, a low-cost, sustainable approach that uses functionalities within the electronic health record to promote outpatient medication adherence and safety.MethodsThe EMC2 strategy was implemented in 2 academic practices for 14 higher-risk diabetes medications. The strategy included: (1) clinical decision support alerts to prompt provider counseling on medication risks, (2) low-literacy medication summaries for patients, (3) a portal-based questionnaire to monitor outpatient medication use, and (4) clinical outreach for identified concerns. We recruited adult patients with diabetes who were prescribed a higher-risk diabetes medication. Participants completed baseline and 2-week interviews to assess receipt of, and satisfaction with, intervention components.ResultsA total of 100 patients were enrolled; 90 completed the 2-week interview. Patients were racially diverse, 30.0% (30/100) had a high school education or less, and 40.0% (40/100) had limited literacy skills. About a quarter (28/100) did not have a portal account; socioeconomic disparities were noted in account ownership by income and education. Among patients with a portal account, 58% (42/72) completed the questionnaire; 21 of the 42 patients reported concerns warranting clinical follow-up. Of these, 17 were contacted by the clinic or had their issue resolved within 24 hours. Most patients (33/38, 89%) who completed the portal questionnaire and follow-up interview reported high levels of satisfaction (score of 8 or greater on a scale of 1-10).ConclusionsFindings suggest that the EMC2 strategy can be reliably implemented and delivered to patients, with high levels of satisfaction. Disparities in portal use may restrict intervention reach. Although the EMC2 strategy can be implemented with minimal impact on clinic workflow, future trials are needed to evaluate its effectiveness to promote adherence and safety.
| S-EPMC6829279 | biostudies-literature
Project description:Background: Drug-induced kidney injury (DIKI) is one of the most common complications in clinical practice. Detection signals through post-marketing approaches are of great value in preventing DIKI in pediatric patients. This study aimed to propose a quantitative algorithm to detect DIKI signals in children using an electronic health record (EHR) database. Methods: In this study, 12 years of medical data collected from a constructed data warehouse were analyzed, which contained 575,965 records of inpatients from 1 January 2009 to 31 December 2020. Eligible participants included inpatients aged 28 days to 18 years old. A two-stage procedure was adopted to detect DIKI signals: 1) stage 1: the suspected drugs potentially associated with DIKI were screened by calculating the crude incidence of DIKI events; and 2) stage 2: the associations between suspected drugs and DIKI were identified in the propensity score-matched retrospective cohorts. Unconditional logistic regression was used to analyze the difference in the incidence of DIKI events and to estimate the odds ratio (OR) and 95% confidence interval (CI). Potentially new signals were distinguished from already known associations concerning DIKI by manually reviewing the published literature and drug instructions. Results: Nine suspected drugs were initially screened from a total of 652 drugs. Six drugs, including diazepam (OR = 1.61, 95%CI: 1.43-1.80), omeprazole (OR = 1.35, 95%CI: 1.17-1.54), ondansetron (OR = 1.49, 95%CI: 1.36-1.63), methotrexate (OR = 1.36, 95%CI: 1.25-1.47), creatine phosphate sodium (OR = 1.13, 95%CI: 1.05-1.22), and cytarabine (OR = 1.17, 95%CI: 1.06-1.28), were demonstrated to be associated with DIKI as positive signals. The remaining three drugs, including vitamin K1 (OR = 1.06, 95%CI: 0.89-1.27), cefamandole (OR = 1.07, 95%CI: 0.94-1.21), and ibuprofen (OR = 1.01, 95%CI: 0.94-1.09), were found not to be associated with DIKI. Of these, creatine phosphate sodium was considered to be a possible new DIKI signal as it had not been reported in both adults and children previously. Moreover, three other drugs, namely, diazepam, omeprazole, and ondansetron, were shown to be new potential signals in pediatrics. Conclusion: A two-step quantitative procedure to actively explore DIKI signals using real-world data (RWD) was developed. Our findings highlight the potential of EHRs to complement traditional spontaneous reporting systems (SRS) for drug safety signal detection in a pediatric setting.
| S-EPMC9543451 | biostudies-literature