scholarly journals Use of Electronic Health Records to Develop and Implement a Silent Best Practice Alert Notification System for Patient Recruitment in Clinical Research: Quality Improvement Initiative

10.2196/10020 ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. e10020 ◽  
Author(s):  
Connor Devoe ◽  
Harriett Gabbidon ◽  
Nina Schussler ◽  
Lauren Cortese ◽  
Emily Caplan ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Electronic Health Records ◽  
Clinical Research ◽  
Best Practice ◽  
Research Quality ◽  
Quality Improvement Initiative ◽  
Patient Recruitment ◽  
Health Records ◽  
Notification System ◽  
Best Practice Alert

scholarly journals Use of Electronic Health Records to Develop and Implement a Silent Best Practice Alert Notification System for Patient Recruitment in Clinical Research: Quality Improvement Initiative (Preprint)

2018 ◽  
Author(s):  
Connor Devoe ◽  
Harriett Gabbidon ◽  
Nina Schussler ◽  
Lauren Cortese ◽  
Emily Caplan ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Clinical Research ◽  
Best Practice ◽  
Screening Method ◽  
Research Quality ◽  
Quality Improvement Initiative ◽  
Screening Methods ◽  
Participant Recruitment ◽  
Use Of Resources ◽  
Best Practice Alert

BACKGROUND Participant recruitment, especially for frail, elderly, hospitalized patients, remains one of the greatest challenges for many research groups. Traditional recruitment methods such as chart reviews are often inefficient, low-yielding, time consuming, and expensive. Best Practice Alert (BPA) systems have previously been used to improve clinical care and inform provider decision making, but the system has not been widely used in the setting of clinical research. OBJECTIVE The primary objective of this quality-improvement initiative was to develop, implement, and refine a silent Best Practice Alert (sBPA) system that could maximize recruitment efficiency. METHODS The captured duration of the screening sessions for both methods combined with the allotted research coordinator hours in the Emerald-COPD (chronic obstructive pulmonary disease) study budget enabled research coordinators to estimate the cost-efficiency. RESULTS Prior to implementation, the sBPA system underwent three primary stages of development. Ultimately, the final iteration produced a system that provided similar results as the manual Epic Reporting Workbench method of screening. A total of 559 potential participants who met the basic prescreen criteria were identified through the two screening methods. Of those, 418 potential participants were identified by both methods simultaneously, 99 were identified only by the Epic Reporting Workbench Method, and 42 were identified only by the sBPA method. Of those identified by the Epic Reporting Workbench, only 12 (of 99, 12.12%) were considered eligible. Of those identified by the sBPA method, 30 (of 42, 71.43%) were considered eligible. Using a side-by-side comparison of the sBPA and the traditional Epic Reporting Workbench method of screening, the sBPA screening method was shown to be approximately four times faster than our previous screening method and estimated a projected 442.5 hours saved over the duration of the study. Additionally, since implementation, the sBPA system identified the equivalent of three additional potential participants per week. CONCLUSIONS Automation of the recruitment process allowed us to identify potential participants in real time and find more potential participants who meet basic eligibility criteria. sBPA screening is a considerably faster method that allows for more efficient use of resources. This innovative and instrumental functionality can be modified to the needs of other research studies aiming to use the electronic medical records system for participant recruitment.

scholarly journals Utilizing an Electronic Health Record System to Improve Vaccination Coverage in Children

2010 ◽  
Vol 01 (03) ◽  
pp. 221-231 ◽  
Author(s):  
A. Oster ◽  
G. H. Yeh ◽  
J. Magno ◽  
H. M. Paek ◽  
L. Au
Keyword(s):  
Quality Improvement ◽  
Electronic Health Records ◽  
Childhood Vaccination ◽  
Ambulatory Setting ◽  
Quality Improvement Initiative ◽  
Local Health ◽  
Childhood Immunization ◽  
Health Records ◽  
Bar Code ◽  
Electronic Health

Summary Background: Electronic Health Records (EHR) are widely believed to improve quality of care and effectiveness of service delivery. Use of EHR to improve childhood immunization rates has not been fully explored in an ambulatory setting. Objective: To describe a pediatric practice’s use of Electronic Health Records (EHR) in improving childhood immunization. Methods: A multi-faceted EHR-based quality improvement initiative used electronic templates with pre-loaded immunization records, automatic diagnosis coding, and EHR alerts of missing or delayed vaccinations. An electronic patient tracking system was created to identify patients with missing vaccines. Barcode scanning technology was introduced to aid speed and accuracy of documentation of administered vaccines. Electronic reporting to a local health department immunization registry facilitated ordering of vaccines. Results: Immunization completion rates captured in monthly patient reports showed a rise in the percentage of children receiving the recommended series of vaccination (65% to 76%) (p<0.000). Bar-code technology reduced the time of immunization documentation (86 seconds to 26 seconds) (p<0.000). Use of barcode scanning showed increased accuracy of documentation of vaccine lot numbers (from 95% to 100%) (p<0.000). Conclusion: EHR-based quality improvement interventions were successfully implemented at a community health center. EHR systems have versatility in their ability to track patients in need of vaccines, identify patients who are delayed, facilitate ordering and coding of multiple vaccines and promote interdisciplinary communication among personnel involved in the vaccination process. EHR systems can be used to improve childhood vaccination rates.

Piloting the EHR4CR Feasibility Platform across Europe

2014 ◽  
Vol 53 (04) ◽  
pp. 264-268 ◽  
Author(s):  
R. Bache ◽  
M. McGilchrist ◽  
C. Daniel ◽  
M. Dugas ◽  
F. Fritz ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Clinical Research ◽  
Test Data ◽  
Data Access ◽  
Data Warehouses ◽  
University Hospitals ◽  
Local Networks ◽  
Health Records ◽  
Electronic Health ◽  
Set Up

SummaryBackground: Pharmaceutical clinical trials are primarily conducted across many countries, yet recruitment numbers are frequently not met in time. Electronic health records store large amounts of potentially useful data that could aid in this process. The EHR4CR project aims at re-using EHR data for clinical research purposes.Objective: To evaluate whether the protocol feasibility platform produced by the Electronic Health Records for Clinical Research (EHR4CR) project can be installed and set up in accordance with local technical and governance requirements to execute protocol feasibility queries uniformly across national borders.Methods: We installed specifically engineered software and warehouses at local sites. Approvals for data access and usage of the platform were acquired and terminology mapping of local site codes to central platform codes were performed. A test data set, or real EHR data where approvals were in place, were loaded into data warehouses. Test feasibility queries were created on a central component of the platform and sent to the local components at eleven university hospitals.Results: To use real, de-identified EHR data we obtained permissions and approvals from ‘data controllers‘ and ethics committees. Through the platform we were able to create feasibility queries, distribute them to eleven university hospitals and retrieve aggregated patient counts of both test data and de-identified EHR data.Conclusion: It is possible to install a uniform piece of software in different university hospitals in five European countries and configure it to the requirements of the local networks, while complying with local data protection regulations. We were also able set up ETL processes and data warehouses, to reuse EHR data for feasibility queries distributed over the EHR4CR platform.

scholarly journals Clinical Research Informatics: Contributions from 2017

2018 ◽  
Vol 27 (01) ◽  
pp. 177-183 ◽  
Author(s):  
Christel Daniel ◽  
Dipak Kalra ◽  
Keyword(s):  
Electronic Health Records ◽  
Clinical Research ◽  
Association Studies ◽  
Bias Reduction ◽  
Lessons Learned ◽  
Editorial Team ◽  
Private Industry ◽  
Health Records ◽  
Clinical Research Informatics ◽  
Electronic Health

Objectives: To summarize key contributions to current research in the field of Clinical Research Informatics (CRI) and to select best papers published in 2017. Method: A bibliographic search using a combination of MeSH descriptors and free terms on CRI was performed using PubMed, followed by a double-blind review in order to select a list of candidate best papers to be then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the editorial team was organized to finally conclude on the selection of best papers. Results: Among the 741 returned papers published in 2017 in the various areas of CRI, the full review process selected five best papers. The first best paper reports on the implementation of consent management considering patient preferences for the use of de-identified data of electronic health records for research. The second best paper describes an approach using natural language processing to extract symptoms of severe mental illness from clinical text. The authors of the third best paper describe the challenges and lessons learned when leveraging the EHR4CR platform to support patient inclusion in academic studies in the context of an important collaboration between private industry and public health institutions. The fourth best paper describes a method and an interactive tool for case-crossover analyses of electronic medical records for patient safety. The last best paper proposes a new method for bias reduction in association studies using electronic health records data. Conclusions: Research in the CRI field continues to accelerate and to mature, leading to tools and platforms deployed at national or international scales with encouraging results. Beyond securing these new platforms for exploiting large-scale health data, another major challenge is the limitation of biases related to the use of “real-world” data. Controlling these biases is a prerequisite for the development of learning health systems.

Adoption of Electronic Health Care Records

2013 ◽  
pp. 148-165
Author(s):  
Jerald D. Hatton ◽  
Thomas M. Schmidt ◽  
Jonatan Jelen
Keyword(s):  
Electronic Health Records ◽  
New Technologies ◽  
Phenomenological Study ◽  
Cost Effective ◽  
Research Quality ◽  
Control Cost ◽  
Health Records ◽  
The Usa ◽  
Electronic Health ◽  
Support Of Research

Political, economic, and safety concerns have militated for the adoption of Electronic Health Records by physicians in the United States, but current rates of adoption have failed to penetrate the 50% level. A qualitative phenomenological study of practicing physicians reveals stumbling blocks to adoption. Maintaining a physician’s perceived sense of control of the process is key. Electronic Health Records (EHRs) are critical to the support of research, quality control, cost reduction, and implementation of new technologies and methods in healthcare. Progress in the USA towards adoption of standardized EHRs has been halting. The authors discuss the results of a phenomenological study of physicians and draw conclusions that will assist all stakeholders in building a more consistent, comprehensive, and cost-effective healthcare system. When attempting to persuade physicians to migrate to an EMR-based solution, a strong focus on the control that physicians will have should be emphasized. The transition to an EHR system is eased by clearly articulating early in the process the potential benefits and the degree of control physicians can have in the use of the applications.

scholarly journals Barriers and facilitators to data quality of electronic health records used for clinical research in China: a qualitative study

BMJ Open ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. e029314 ◽  
Author(s):  
Kaiwen Ni ◽  
Hongling Chu ◽  
Lin Zeng ◽  
Nan Li ◽  
Yiming Zhao
Keyword(s):  
Qualitative Study ◽  
Electronic Health Records ◽  
Clinical Research ◽  
Data Quality ◽  
Healthcare Professionals ◽  
Barriers And Facilitators ◽  
Health Records ◽  
Improve Data Quality ◽  
Electronic Health

ObjectivesThere is an increasing trend in the use of electronic health records (EHRs) for clinical research. However, more knowledge is needed on how to assure and improve data quality. This study aimed to explore healthcare professionals’ experiences and perceptions of barriers and facilitators of data quality of EHR-based studies in the Chinese context.SettingFour tertiary hospitals in Beijing, China.ParticipantsNineteen healthcare professionals with experience in using EHR data for clinical research participated in the study.MethodsA qualitative study based on face-to-face semistructured interviews was conducted from March to July 2018. The interviews were audiorecorded and transcribed verbatim. Data analysis was performed using the inductive thematic analysis approach.ResultsThe main themes included factors related to healthcare systems, clinical documentation, EHR systems and researchers. The perceived barriers to data quality included heavy workload, staff rotations, lack of detailed information for specific research, variations in terminology, limited retrieval capabilities, large amounts of unstructured data, challenges with patient identification and matching, problems with data extraction and unfamiliar with data quality assessment. To improve data quality, suggestions from participants included: better staff training, providing monetary incentives, performing daily data verification, improving software functionality and coding structures as well as enhancing multidisciplinary cooperation.ConclusionsThese results provide a basis to begin to address current barriers and ultimately to improve validity and generalisability of research findings in China.

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