Technological Adjuncts to Streamline Patient Recruitment, Informed Consent, and Data Management Processes in Clinical Research: Observational Study
BackgroundPatient recruitment and data management are laborious, resource-intensive aspects of clinical research that often dictate whether the successful completion of studies is possible. Technological advances present opportunities for streamlining these processes, thus im...
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| Format: | Article |
| Language: | English |
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JMIR Publications
2025-01-01
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| Series: | JMIR Formative Research |
| Online Access: | https://formative.jmir.org/2025/1/e58628 |
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| author | Jodie Koh Stacey Caron Amber N Watters Mahesh Vaidyanathan David Melnick Alyssa Santi Kenneth Hudson Catherine Arguelles Priyanka Mathur Mozziyar Etemadi |
| author_facet | Jodie Koh Stacey Caron Amber N Watters Mahesh Vaidyanathan David Melnick Alyssa Santi Kenneth Hudson Catherine Arguelles Priyanka Mathur Mozziyar Etemadi |
| author_sort | Jodie Koh |
| collection | DOAJ |
| description |
BackgroundPatient recruitment and data management are laborious, resource-intensive aspects of clinical research that often dictate whether the successful completion of studies is possible. Technological advances present opportunities for streamlining these processes, thus improving completion rates for clinical research studies.
ObjectiveThis paper aims to demonstrate how technological adjuncts can enhance clinical research processes via automation and digital integration.
MethodsUsing one clinical research study as an example, we highlighted the use of technological adjuncts to automate and streamline research processes across various digital platforms, including a centralized database of electronic medical records (enterprise data warehouse [EDW]); a clinical research data management tool (REDCap [Research Electronic Data Capture]); and a locally managed, Health Insurance Portability and Accountability Act–compliant server. Eligible participants were identified through automated queries in the EDW, after which they received personalized email invitations with digital consent forms. After digital consent, patient data were transferred to a single Health Insurance Portability and Accountability Act–compliant server where each participant was assigned a unique QR code to facilitate data collection and integration. After the research study visit, data obtained were associated with existing electronic medical record data for each participant via a QR code system that collated participant consent, imaging data, and associated clinical data according to a unique examination ID.
ResultsOver a 19-month period, automated EDW queries identified 20,988 eligible patients, and 10,582 patients received personalized email invitations. In total, 1000 (9.45%) patients signed consents to participate in the study. Of the consented patients, 549 unique patients completed 779 study visits; some patients consented to the study at more than 1 time period during their pregnancy.
ConclusionsTechnological adjuncts in clinical research decrease human labor while increasing participant reach and minimizing disruptions to clinic operations. Automating portions of the clinical research process benefits clinical research efforts by expanding and optimizing participant reach while reducing the limitations of labor and time in completing research studies. |
| format | Article |
| id | doaj-art-07bb564c14c541e6ba210cfe5d5deb19 |
| institution | Kabale University |
| issn | 2561-326X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Formative Research |
| spelling | doaj-art-07bb564c14c541e6ba210cfe5d5deb192025-01-29T15:46:15ZengJMIR PublicationsJMIR Formative Research2561-326X2025-01-019e5862810.2196/58628Technological Adjuncts to Streamline Patient Recruitment, Informed Consent, and Data Management Processes in Clinical Research: Observational StudyJodie Kohhttps://orcid.org/0009-0004-5339-8945Stacey Caronhttps://orcid.org/0009-0002-5133-5188Amber N Wattershttps://orcid.org/0009-0008-5933-2188Mahesh Vaidyanathanhttps://orcid.org/0000-0003-4311-8896David Melnickhttps://orcid.org/0000-0002-1535-697XAlyssa Santihttps://orcid.org/0009-0005-7321-1807Kenneth Hudsonhttps://orcid.org/0009-0001-6774-0551Catherine Arguelleshttps://orcid.org/0009-0000-1978-1255Priyanka Mathurhttps://orcid.org/0000-0001-9040-9835Mozziyar Etemadihttps://orcid.org/0000-0002-6324-9220 BackgroundPatient recruitment and data management are laborious, resource-intensive aspects of clinical research that often dictate whether the successful completion of studies is possible. Technological advances present opportunities for streamlining these processes, thus improving completion rates for clinical research studies. ObjectiveThis paper aims to demonstrate how technological adjuncts can enhance clinical research processes via automation and digital integration. MethodsUsing one clinical research study as an example, we highlighted the use of technological adjuncts to automate and streamline research processes across various digital platforms, including a centralized database of electronic medical records (enterprise data warehouse [EDW]); a clinical research data management tool (REDCap [Research Electronic Data Capture]); and a locally managed, Health Insurance Portability and Accountability Act–compliant server. Eligible participants were identified through automated queries in the EDW, after which they received personalized email invitations with digital consent forms. After digital consent, patient data were transferred to a single Health Insurance Portability and Accountability Act–compliant server where each participant was assigned a unique QR code to facilitate data collection and integration. After the research study visit, data obtained were associated with existing electronic medical record data for each participant via a QR code system that collated participant consent, imaging data, and associated clinical data according to a unique examination ID. ResultsOver a 19-month period, automated EDW queries identified 20,988 eligible patients, and 10,582 patients received personalized email invitations. In total, 1000 (9.45%) patients signed consents to participate in the study. Of the consented patients, 549 unique patients completed 779 study visits; some patients consented to the study at more than 1 time period during their pregnancy. ConclusionsTechnological adjuncts in clinical research decrease human labor while increasing participant reach and minimizing disruptions to clinic operations. Automating portions of the clinical research process benefits clinical research efforts by expanding and optimizing participant reach while reducing the limitations of labor and time in completing research studies.https://formative.jmir.org/2025/1/e58628 |
| spellingShingle | Jodie Koh Stacey Caron Amber N Watters Mahesh Vaidyanathan David Melnick Alyssa Santi Kenneth Hudson Catherine Arguelles Priyanka Mathur Mozziyar Etemadi Technological Adjuncts to Streamline Patient Recruitment, Informed Consent, and Data Management Processes in Clinical Research: Observational Study JMIR Formative Research |
| title | Technological Adjuncts to Streamline Patient Recruitment, Informed Consent, and Data Management Processes in Clinical Research: Observational Study |
| title_full | Technological Adjuncts to Streamline Patient Recruitment, Informed Consent, and Data Management Processes in Clinical Research: Observational Study |
| title_fullStr | Technological Adjuncts to Streamline Patient Recruitment, Informed Consent, and Data Management Processes in Clinical Research: Observational Study |
| title_full_unstemmed | Technological Adjuncts to Streamline Patient Recruitment, Informed Consent, and Data Management Processes in Clinical Research: Observational Study |
| title_short | Technological Adjuncts to Streamline Patient Recruitment, Informed Consent, and Data Management Processes in Clinical Research: Observational Study |
| title_sort | technological adjuncts to streamline patient recruitment informed consent and data management processes in clinical research observational study |
| url | https://formative.jmir.org/2025/1/e58628 |
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