How the Louisiana Public Health Institute Adapted Learning Health Systems to Streamline Clinical Studies
Guest post by Harshal Shah, senior director, healthcare, Persistent Systems, and Thomas Carton, chief business development officer, Louisiana Public Health Institute
A critical aspect of clinical research today is patient-centered studies, which provide the insights that empower doctors, clinicians, and patients to make better informed care and treatment decisions. But the challenge is building an effective system to gather and share data across multiple systems and empower researchers and stakeholders within health-focused organizations to easily compare different types of interventions, conduct pragmatic clinical research and translate the benefits of that research into medical practice.
The Louisiana Public Health Institute (LPHI) has implemented a system that has accomplished this lofty goal.
LPHI’s work focuses on uncovering complementary connections across sectors to combine the social, economic, and human capital needed to align action for health. It champions health for people, within systems, and throughout communities.
The primary challenge lies in integrating a seamless data workflow across health systems and integrating network activities into the work of existing clinical teams, and a workflow that is flexible to meet each organization’s specific clinical and research needs. There is also a great need for onboarding participating staff members who can help educate patients about a study and set realistic expectations around the trial. The technology they use needs to enable physicians and patients to make informed decisions in real-time.
The non-profit organization created (and now serves as the coordinating center of) a Clinical Data Research Network, REACHnet, that increased the capacity of regional learning health systems to conduct patient-centered clinical studies. This network centers around a robust data infrastructure with a patient engagement platform for study recruitment, data collection and connection to clinical records.
REACHnet addressed these key aspects by designing the network with the following principles:
Targeted patient engagement – The patient engagement infrastructure of REACHnet uses a web- or tablet-based platform in examination rooms, which is electronic medical record (EMR)-agnostic. These web- or tablet-based platforms, developed by Persistent Systems, are pre-loaded with the pragmatic trial app suite (PTAS) that facilitates patient engagement with targeted educational and research content. Through what is termed as the Health in Our Hands (HiOH) patient network, the PTAS facilitates patient enrollees to engage with the research studies and programs. The dashboard provided by PTAS is currently equipped with visual graphics, charts and analysis to show patients how the study is progressing and how it could affect them. If required, the dashboard can also provide the possible treatment options and the current evidence available.
The application suite is user-friendly and allows patients to interact with the study easily, share data and access information both inside and outside the clinical settings via a personal patient portal. Enrollees receive health information, research results and opportunities to participate in new studies through the HiOH patient network. This continuous engagement between the patients and the researchers, clinicians and doctors ensures the longevity of participants’ interest in the studies, which is crucial to the success of clinical research.
Data access and seamless integration into workflow – The basis for a learning health system is conducting pragmatic research that requires healthcare organizations to embed clinical research into the workflow of healthcare delivery systems rather than just organize them in controlled conditions. Data is gathered at multiple sites within the network and sent to the REACHnet data center. Data collected at each site, whether inside or outside a clinical setting is associated with a Global Patient Identification (GPID) system that matches patients without the sharing of identifiable information. Selected information is pulled in by REACHnet for conducting various studies and comparing different interventions based on these GPIDs.
Since REACHnet uses a common data model (CDM) to prepare retrospective and prospective research and prep-to-research queries, PTAS can quickly sync to data in the CDM to push targeted content to patients. This completes the engagement loop across a clinical workflow and provides access to data in real-time.