Notice of Special Interest (NOSI): New Information Technology-Enabled Care Delivery Models to Improve Depression Care in Cancer

Application or LOI Due Date
First Available Due Date: 10/5/21. Expiration Date: 3/8/24
Brief Description


This Notice of Special Interest (NOSI) highlights interest of the National Cancer Institute (NCI)’s Division of Cancer Control and Population Sciences in receiving investigator-initiated applications for conducting research on the design and implementation of new information technology (IT)-enabled care delivery models to improve depression-related care in cancer.


Depression is common in cancer and contributes to adverse outcomes including a worse quality of life, decreased adherence to treatments, and increased mortality. The U.S. Preventive Services Task Force (USPSTF) recommends screening all adults for depression based on the availability of several validated, accurate instruments for the screening and diagnosis of depression and effective treatments for depression. For adult cancer patients, the American Society of Clinical Oncology has issued guidelines on screening, assessment, and care of anxiety and depressive symptoms. The collaborative care delivery model is better than usual care in identifying and effectively treating cancer patients with depression, however, this care delivery model is not widely used.

Despite the feasibility of screening for depression in routine oncology practice and the availability of effective treatments and a proven care delivery model, depression in cancer patients is under-diagnosed and under-treated. In the absence of systematic screening, oncologists often fail to diagnose depression in cancer patients. Many cancer patients with depression do not receive effective depression treatment.

Barriers to better management of depression in cancer patients include:

  • a shortage of mental health providers, especially in rural areas;
  • the time and resources needed to coordinate care; and
  • inadequate communication between the patient and the physician due to time constraints during a clinic visit.

IT can overcome several barriers to the delivery of depression care by oncologists. The recent increase in use of telehealth is an opportunity to improve the virtual delivery of depression care. For example, telehealth can be used to connect psychiatrists with community oncologists to help take care of cancer patients with depression. Applications for mobile devices can be used to screen for depression and to monitor effectiveness of treatments for depression. Mobile applications can also be used to deliver behavioral interventions. The USPSTF recommends depression screening be implemented with adequate systems in place to ensure accurate diagnosis, effective treatment, and appropriate follow-up of patients with depression. IT has an important role to play in a systems-based approach to improve the screening, diagnosis, and treatment of depression in cancer patients.

Research Objectives

The overall objectives of the NOSI are to support:

1) Development of new, IT-based delivery models and test their efficacy in improving screening and management of depression in cancer patients,

2) Evaluation of the effectiveness of IT-based delivery models in a variety of oncology practice settings, especially those serving under-served populations, and

3) Evaluation of the sustainability and scalability of these new IT-based delivery models.

The NOSI encourages research that includes:

  • Established instruments to screen and diagnose depression and established treatments for depression as part of the new IT-based delivery model.
  • Design and evaluation considerations of the IT-based delivery model that include the likelihood of its long-term use within an oncology practice setting (sustainability) and implementation across a variety of oncology practice settings (scalability). All oncology practice settings are within the scope of this notice.
  • Human-centered design approach to design and implement new IT applications. An understanding of the clinical tasks, workflow and teamwork in an oncology practice setting will help in designing IT that is easy-to-use and clinically useful. Applications that develop and evaluate new IT to better support clinical tasks, workflow and teamwork are strongly encouraged.
  • Design of IT for the use of one or more of the following: individual clinicians, clinical teams, patients, and patient caregivers. The IT may be used to improve communication, coordination of care, and support of care delivery tasks. The IT may be used to deliver evidence-based interventions. The IT may be used to collect, share or analyze data or present data for clinical decision-making. The IT design and implementation considerations need to include use of existing standards and best practices to facilitate interoperability between IT systems while protecting a patient's privacy and ensuring compatibility with the care delivery organization's cyber-security procedures and processes.
  • Research on populations that experience inequities in access to care, have limited access to broadband and digital technologies, have low health or digital literacy (or both), and have worse cancer outcomes compared to the general population.
  • Research that examines how IT-based delivery models can be implemented without creating or exacerbating health disparities, as well as research that examines how these delivery models can be used to address health disparities and promote health equity.
  • Interventional research and observational research methods may be used.
  • Outcomes of interest include, but are not limited to, those listed in the examples of research questions.

Examples of research encouraged by the NOSI include, but are not limited to, studies that:

  • Evaluate the impact of IT-based delivery models for diagnosis or treatment (or both) of depression on depression-related outcomes in cancer patients.
  • Evaluate the impact of the IT-based delivery models for diagnosis or treatment (or both) of depression on treatment adherence, patient-provider communication, patient satisfaction, and other cancer care delivery-related processes.
  • Evaluate the impact of the IT-based delivery models for diagnosis or treatment (or both) of depression on provider-level outcomes such as provider satisfaction, and communication and coordination among clinicians.
  • Understand the tasks, and the time and cognitive burden of performing the tasks, imposed by the IT-based models for diagnosis or treatment (or both) of depression on providers, patients, and their caregivers.
  • Evaluate the characteristics of the clinicians, clinical teams, and the organizations in which the clinicians work, that influence effectiveness of the IT-based delivery models for diagnosis or treatment (or both) of depression.
  • Evaluate the characteristics of the patients and their caregivers (including the IT used by them) that influence effectiveness of the IT-based delivery models for diagnosis or treatment (or both) of depression
  • Evaluate the factors that affect scalability and sustainability of implementation of the IT-based delivery model for diagnosis or treatment (or both) of depression in diverse oncology practice settings, especially those serving under-served populations.
  • Evaluate how the components of the new delivery model (e.g., personnel, type of technology, integration in workflow, intensity of communication and monitoring) contribute to its effectiveness.

NIH Research Project Grant Program (R01) may support projects that integrate and evaluate IT-based interventions to screen, diagnose and/or treat depression in cancer patients. NIH Exploratory/Developmental Research Grant Award (R21) may support formative work to develop IT-based interventions or examine their impact in pilot studies.

Applicants are encouraged to identify the aspects of IT-based care delivery model that are being tested to isolate their effects on variability in specified patient outcomes. Examination of interactions at multiple levels (i.e. patient, provider, and care delivery system-level) or intervene at multiple levels are also of interest.