The DHR program funds research that demonstrates how digital healthcare solutions can be designed and implemented to improve healthcare system performance and patient health outcomes. Our funded research focuses on advancing patient safety, care, and shared decision making without placing excessive burden on users, including patients, physicians, and other members of care teams.
This report highlights research stories that showcase significant findings and impact under each theme. The research stories are identified as completed or emerging (newly funded) research.
- Completed research: 28 grants and 3 contracts recently ended.
- Emerging research: 23 grants recently awarded.
In 2022, the DHR program managed 108 grants and seven research contracts across the three main themes:
Engaging and Empowering Patients
Engaging and empowering patients in their own healthcare leads to improvements in safety, quality, and satisfaction of care. Use of digital healthcare tools, like patient portals, smartphones, or mobile apps, can facilitate patient engagement and empower patients and their caregivers to participate more actively in their own health self-management, chronic care management, and wellness at the many points of interaction with the healthcare system.
In 2022, DHR invested $72.3 million in grants and contracts across the lifetime of the projects to help patients, families, and health professionals work together as partners in promoting care improvements over the duration of the projects.
Research Stories by Subtheme
Below are research stories told in the investigator’s own words organized by subtheme.
A mobile application designed to facilitate asthma self-management and shared decision making through patient-reported outcomes can improve care, asthma control, and knowledge, as well as decrease healthcare utilization
A patient-facing app simplifying the information patients and caregivers receive has the potential to better engage patients and families in their healthcare post-discharge and reduce adverse events.
Enhancing personalized care decisions, using technology designed with human factors engineering approaches, can improve breast cancer care quality.
Other Research by Subtheme
The research stories highlighted in this report are only a subset of the work that AHRQ funds. The following table includes additional research related to Engaging and Empowering Patients that was either completed or newly awarded in 2022. To search the entire portfolio of research, please visit AHRQ Funded Projects.
Mobile health applications adapted with automated learning algorithms can target specific health conditions, such as improving the management of diabetes and depression while delivering adaptive messages based on patients' behaviors.
The use of a mobile health application can improve chronic disease self-management and medication adherence for people with HIV.
Expansion of an evidence-based digital health intervention for attention deficit hyperactivity disorder in children that is focused on improving communication and care coordination across multiple points of care has the potential to improve outcomes for this group of individuals.
While “cold” texting of patients to suggest screening for diabetes is feasible from a technological and governance perspective, more research is needed to inform how to better engage patients.
The use of Support-Engage-Empower-Diabetes (SEE-Diabetes), a user-centered shared decision-making module, may improve self-care behaviors and outcomes for older adults with diabetes.
Use of a standards-based shareable, interoperable patient-facing clinical decision support tool for high blood pressure management has the potential to improve outcomes by empowering patients and providing them the tools to better engage in the self-management of their high blood pressure.
Identifying and characterizing the factors differentiating patient portal users from nonusers within population subgroups can inform clear design guidelines to represent the diverse needs of patients to increase access and utilization of patient portals.
The use of Substitutable Medical Applications Reusable Technologies (SMART®) on Fast Healthcare Interoperability Resources (FHIR®) standards has the potential to improve guideline-directed medication therapy in those with heart failure, and if successful, the approach could reduce heart failure hospital admissions and be applied to other chronic conditions.
A multicomponent digital health solution has the potential to improve glycemic control and outcomes in Medicaid-enrolled pregnant individuals with type 2 diabetes.
A family-centered multi-component digital tool with an innovative communication approach may reduce childhood obesity risk, as well as contribute to the limited evidence base of effective, culturally relevant mHealth tools for minority, at-risk populations.
Using CareHeroes, an application to support caregivers of those living with dementia, has the potential to support caregivers by making information on dementia readily available and creating the ability to track and share information about the impacted person between caregivers and providers.
Measuring patient-reported outcomes for pain management after certain dental procedures with a mHealth platform is feasible and improves patient-provider communication, patient-provider relationship, and the ability to manage pain medication prescribing.
The use of a virtual reality app has the potential to be a cost-effective way to alleviate pain, reduce the need for opioids, and improve outcomes for children needing at-home dressing changes for burn injuries.
Optimizing Care Delivery for Clinicians
Supporting clinicians and other healthcare professionals by maximizing their ability to provide high-quality and safe healthcare to patients leads to improved health outcomes. For example, using digital health research to optimize clinical decision making by delivering the right information to the right people at the right times, allows clinicians to make the best treatment decisions, while also ensuring that technology is designed in a way that supports cognitive work and does not introduce or increase provider burden.
In 2022, the DHR program invested $55.2 million over the duration of research on projects that focused on optimizing care delivery for clinicians, including research on using effective clinical decision support (CDS) interventions to improve care, using real-time digital healthcare data to improve timely treatment or diagnosis, and technology solutions to improve medication safety.
Research Stories by Subtheme
Below are research stories told in the investigator’s own words organized by subtheme.
Implementing CancelRx, an e-prescribing tool to electronically communicate medication discontinuation orders between electronic health records and pharmacies, showed an immediate and persistent reduction in prescriptions that were dispensed after discontinuation.
Tools like ASPIRE that integrate fall prevention clinical decision support and patient resources may better support patient self-care and adoption of evidence-based recommendations.
A methodology for scaling patient-centered outcomes research into interoperable, shareable clinical decision support tools that are actively maintained with current evidence has the potential to close the evidence-into-practice gap, leading to better patient outcomes.
Use of an artificial intelligence algorithm that would allow for screening mammography interpretation and same-day diagnostic imaging has the potential to vastly shorten the time from an abnormal screening mammogram to diagnostic workup, resolving false positives in a timelier fashion, and reducing the anxiety incurred in patients by long wait times for diagnostic evaluation.
An artificial intelligence digital health tool that identifies patients on the verge of clinical deterioration may allow for faster intervention and a reduction in morbidity and mortality.
Using the clinical decision support system Enhancing Quality of Prescribing Practices for Older Adults Discharged from the Emergency Department significantly reduces the prescribing of potentially inappropriate medications in the emergency department setting.
Other Research by Subtheme
The research stories highlighted in this report are only a subset of the work that AHRQ funds. The following table includes additional research related to Optimizing Care Delivery for Clinicians that was either completed or newly awarded in 2022. To search the entire portfolio of research, please visit AHRQ Funded Projects.
Computerized alerts can prevent errors and improve clinical documentation by prompting prescribers to double check the patient, the drug, and the diagnosis whenever a drug being ordered does not match any diagnosis in the patient’s problem list.
A perioperative clinical decision software platform outperformed the standard medication administration and documentation workflow by improving efficiency and quality of care while receiving higher usability ratings from clinicians.
Innovations in drug allergy picklists, particularly using enhanced dynamic picklists, are a promising solution to support real-time allergy reconciliation, improve documentation among providers, and reduce cognitive burden.
Using interoperable standards to create a reusable, shareable, and scalable system for patient shared decision aids has the potential to scale these important shared decision-making tools widely and improve patient-centered outcomes.
CDS Connect offers a public platform for authoring and sharing interoperable clinical decision support resources. Health information technology developers, clinical informaticists, and healthcare system leaders can leverage each other’s experiences and tools to reduce the burden of developing and implementing CDS, thus making it easier overall to advance evidence into clinical practice through CDS.
Creating clinical decision support artifacts that are shareable, interoperable, and scalable may allow for wider dissemination of patient-centered outcomes research related guidelines.
Clinical decision support embedded within a provider’s workflow combined with a continuing medical education program increases a provider’s awareness of medications and conditions that increase the risk of Torsades des Pointes, an uncommon, but life-threatening cardiac arrhythmia.
The design, development, and implementation of the app Tapering And Patient Reported outcomes for Chronic Pain Management (TAPR-CPM) led to the identification of strategies, facilitators, and barriers to implementation that provide insight for future digital healthcare interventions.
The use of clinical decision support for adults with prediabetes improves clinical processes and may lead to improved outcomes.
Applying novel machine learning methodologies in real time to readily available risk and prognostic data in electronic health records could contribute to the development of a timely, accurate, and scalable approach to inform personalized childhood asthma treatment at the point of care.
A clinical decision support system that uses machine learning combined with clinician perspectives to identify and manage patients with acute respiratory distress syndrome is feasible and outperforms clinician recognition.
Using clinical decision support to alert clinicians about potential factors impacting a patient’s ability to adhere with a care plan leads to the improvement of contextualized care plans that account for those factors.
Several electronic health record (EHR) communication network structures, including network size and betweenness centralization, impacts patients’ survival time such that smaller and more centralized EHR networks are associated with longer survival time.
A training solution using artificial intelligence can be tailored to allow providers to quickly and actively address inadequate training, and thus improving their ability to elicit from patients their own motivations to make healthy behavior changes.
Examining the relationship between nursing documentation patterns and patient outcomes during the COVID-19 pandemic can support better optimization of electronic health record configurations to support nurses to provide better care for patients.
The use of order sets in patients with sepsis reduces order variation and improves outcomes and may be a strategy to adhere to best practices and improve clinical management.
Supporting Health Systems in Advancing Care Delivery
Advancing care delivery at the health systems or organization level, including scaling effective interventions across different platforms, promoting interoperability, and leveraging data and technologies can strengthen healthcare systems and the care they deliver.
In 2022, the DHR program invested $45.4 million across the lifetime of projects on research to advance care delivery and to scale effective digital healthcare intervention across healthcare systems.
Research Stories by Subtheme
Below are research stories told in the investigator’s own words organized by subtheme.
A machine learning, predictive analytic intervention has the potential to improve healthcare, making it more equitable for patients with a non-English language preference and complex care needs by supporting timely interpreter use to facilitate decision making and promote patient-centered care.
A shared decision-making tool to support the appropriate use of low-dose computed tomography screening has the potential to prevent 10,000 or more lung cancer deaths annually in the United States.
Clinical decision support that can be implemented in different types of electronic health records has the potential to scale evidence-based practice across healthcare systems.
Development of a toolkit to facilitate the scale and spread of using patient-reported outcomes among rheumatoid arthritis patients fills an existing gap in national resources to provide support to rheumatologists.
New measures to identify near-miss medication errors are a major advancement in patient safety and can help healthcare systems make ordering even safer.
An enhanced health information exchange platform that improves workflow, interoperability, and visualization of data for inter-hospital transfers may reduce the morbidity and mortality seen today during inter-hospital transfers.
Using machine learning- and artificial intelligence-developed tools in the intensive care unit has the potential to optimize critical care pharmacist resources and improve patient safety by reducing adverse drug events.
Other Research by Subtheme
The research stories highlighted in this report are only a subset of the work that AHRQ funds. The following table includes additional research related to Supporting Health Systems in Advancing Care Delivery that was either completed or newly awarded in 2022. To search the entire portfolio of research, please visit AHRQ Funded Projects.
Bringing together States’ Medicaid medical directors to understand undiscovered challenges facing Medicaid consumers and Medicaid programs in identified areas that may be amenable to improvement through technology innovation.
The use of automated speech recognition and automated machine translation technologies integrated in an asynchronous telepsychiatry application may be a viable language interpretation option for those with limited English proficiency.
The dissemination of a low-cost, user-friendly, culturally competent, evidence-based, scalable intervention to improve the health of young African American women is critical to improving maternal and child health outcomes.
Improving shared decision making for lung cancer screening by adapting and disseminating an interoperable clinical decision support tool and patient-facing app has the potential to reduce lung cancer deaths—the leading cause of cancer-related deaths in the United States.
E-care plan applications that use interoperability standards have the potential to improve care management and care coordination for people with multiple chronic conditions across different healthcare settings.
Applying improved methods to handle missing and misclassified data across databases without the need to share data on the individual level will lead to improvements in data used for population-level research.
Creating tools to automate the assessment and improvement of representational semantic integrity of terminologies in electronic health record databases will lead to improved databases with less redundancy and ambiguity and more robustness for research purposes.
Analyzing electronic health record metadata may help health systems identify gaps, inconsistencies, and inefficiencies in discharge planning to inform improvements in transitions of care.