Notice of Special Interest (NOSI): Research to Improve the Interpretation of Patient-Reported Outcomes at the Individual Patient Level for Use in Clinical Practice

Notice Number: NOT-OD-20-079

Key Dates
Release Date: March 24, 2020
First Available Due Date: June 05, 2020
Expiration Date: January 08, 2022

Related Announcements
None

Issued by
Office of Behavioral and Social Sciences Research (OBSSR)

National Human Genome Research Institute (NHGRI)

National Institute on Aging (NIA)

National Institute on Alcohol Abuse and Alcoholism (NIAAA)

National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)

National Institute on Deafness and Other Communication Disorders (NIDCD)

National Institute of Mental Health (NIMH)

National Institute of Neurological Disorders and Stroke (NINDS)

National Institute of Nursing Research (NINR)

National Institute on Minority Health and Health Disparities (NIMHD)

National Center for Complementary and Integrative Health (NCCIH)

National Cancer Institute (NCI)

All applications to this funding opportunity announcement should fall within the mission of the Institutes/Centers. The following NIH Offices may co-fund applications assigned to those Institutes/Centers.

Division of Program Coordination, Planning and Strategic Initiatives, Office of Disease Prevention (ODP)

Office of Research on Women's Health (ORWH)

Purpose

A patient-reported outcome (PRO) is defined as any report of a person’s health status including symptoms, function and well-being, that is gathered directly from a patient, without interpretation of that report by a clinician, observer, or anyone else. PROs are critical for the support of patient-centered care, as they provide information from the patient’s perspective, and offer important information to improve patient-clinician communication, decision-making, and care delivery. PROs are increasingly being used by clinical stakeholders (e.g., providers, care delivery systems, payers and regulators) to characterize individual patients’ symptoms and functional status and the change in outcomes over time. Thus, PROs are becoming an important piece of information for clinical decision-making, including shared decision-making. The purpose of this Notice of Special Interest (NOSI) is to stimulate research that contributes to the evidence base for precise and accurate PRO score interpretation at the individual patient level for use in clinical practice.

Background

The National Institutes of Health (NIH) has made considerable investments in the development and testing of PROs to provide the research community with robust tools to monitor and evaluate patient health. The validity, reliability, and utility of PRO measures have been studied extensively in a variety of clinical conditions and among diverse populations for use and interpretation of group level differences. Given the efficiency and greater accessibility of PROs via electronic health record (EHR) systems, clinicians are increasingly interested in using these well-validated PROs to inform individual treatment and care decisions for their patients. There are many existing PRO systems widely in use in clinical settings. A few examples include but are certainly not limited to: HealthMeasures which is comprised of the Patient Reported Outcomes Measurement Information System(R) (PROMIS(R)), the NIH Toolbox for Assessment of Neurological and Behavioral Function (NIH Toolbox); the Neurology Quality of Life Measurement System (Neuro-QoL), and The Adult Sickle Cell Quality of Life Measurement Information System (ASCQ-Me); EQ-5D and EQ-5D-Y; SF-36; and QuoLO™.

Research to support the use of these measures for interpreting individual level differences within and between individuals in various clinical contexts, is sparse. For some assessment tools, interpretive thresholds, reference values, and minimally important differences informing clinical care have been developed. However, these thresholds are empirically derived from group-level data. Thus, their value for interpreting scores or making clinical decisions and predictions for individual patients is unclear. Furthermore, measurement error, along with intra-individual variability, may confound the interpretation of scores at the individual patient level. Sensitivity and specificity are critical when PRO measures are employed in clinical decision-making. Given that both underdiagnosis and overdiagnosis can result in adverse outcomes, research is needed to better understand the appropriate clinical interpretation of PRO scores for individual patients in a variety of disease and healthcare contexts. Thus, it is vital that the use of PROs to guide clinical decision-making at the individual level be supported by a robust evidence base.

This NIH NOSI encourages grant applications for research that develops evidence needed to support the interpretation of existing, well-validated PROs for use in clinical care settings. The focus of this NOSI is on self-report (PRO) measures that: a) have already been developed and validated for use in clinical research and have strong, demonstrated psychometric properties, and b) are currently being used, or could have utility, in clinical practice. Specifically, this Notice calls for methodological studies that provide meaningful interpretation of PRO scores collected and acted upon at the individual patient level for use in clinical decision-making.

This NOSI is not intended to encourage the development, testing, or validation of new PRO measures or to study methods for electronic PRO data capture or the presentation of PRO summaries to clinicians or patients.

Research questions responsive to this NOSI may include but are not limited to:

Improving Understanding and Interpretation of PRO Scores for Individual Patients

  • What score level, or combination of score levels, would signal the need for clinical action for individual patients?
  • What score differences over time would indicate worsening vs. improvement, onset or resolution of health problems in an individual patient?
  • In what clinical contexts are ecological momentary assessment (EMA) methods interpretable for surveillance, diagnosis, and determination of individual treatment benefit?
  • How should PROs be interpreted differently for individuals with specific clinical conditions, those with multiple conditions, or other high-risk contextual factors? Are these interpretations dependent on different disease phases or treatment trajectories?
  • How should PRO scores be interpreted for individuals within specific healthcare settings (e.g., acute, outpatient, primary, specialty, community, or rehabilitation settings) where PRO scores may be used to inform actions (e.g., hospital discharge, additional assessments, or referral for services)?
  • Can group-level information (such as current reference values) be used to accurately inform individual-level care? Are any modifications or transformations needed to apply this information validly for individual use (e.g., covariate adjustment, more precise score range reference values to define worsening or improvement)?
  • How might other clinically relevant information (e.g., comorbidity, age, sex, social support, self-management, social determinants of health, minority population status) affect the interpretation of individual PROs in clinical practice, and how should this clinically relevant information be incorporated in the interpretation of PROs in clinical practice?
  • What is the relationship between PROs and other clinical indicators such as laboratory tests, biomarkers, or imaging? How should PRO data be integrated with these clinical indicators to improve the sensitivity and specificity of PROs in individual decision-making in diverse patient populations and clinical settings?
  • When using PRO measures for routine surveillance, what are the relationships between frequency of assessment, intra-individual variability, and measure precision and individual-level reliability?

Understanding Bias, Variance, and Error

  • How can ceiling or floor effects in sub-populations be accounted for when applying scores to specific individuals?
  • What are the sources of bias and error that are introduced or amplified when interpreting individual scores based on co-calibrations or crosswalks of PROs measuring the same construct (e.g., can cutoffs scores on one PRO be used as the cutoffs of a co-calibrated or cross-walked PRO)?
  • What are the effects of measurement invariance when interpreting scores for individual patients, and how can these effects be accounted for?
  • What levels of validity, reliability, and responsiveness are needed for interpretation at the individual level? Does recall period influence such interpretations?
  • What is the relationship between the scaling, precision, and accuracy of a measure and its suitability for a specific purpose (e.g. screening versus responder definition) in specific clinical settings serving diverse patient populations?

Some Example Study Questions might include, but are not limited to:

  • How can individual PRO scores (e.g., pain, fatigue, physical function) be used to screen for, or diagnose conditions, diseases or treatment-related symptoms or functional impairments, in order to identify a need for specific care?
  • What PRO score threshold or slope of change over time indicates a need for immediate triage or clinical intervention? For example, what threshold or slope of increased symptom severity (e.g., pain severity, nausea/vomiting, or diarrhea) for an individual patient diagnosed with a particular medical condition or disease would indicate a need for phone or in-person follow-up)? What are the sensitivity and specificity of such PRO indicators? Do the sensitivity and specificity vary based on the treatment regimen for individual patients, particularly for patients from high risk populations?
  • In what contexts are PRO measures more sensitive and specific than are performance-based measures in capturing worsening/improvement in physical functioning over time?
  • Recovery: What PRO score improvement in physical functioning or pain over time indicates achievement of clinical benefit at the individual patient level after a major surgery or medical treatment?
  • Worsening: What score reduction in physical functioning in the first 2 weeks after surgery represents a decline in an individual patient that requires clinical intervention? Are these thresholds for clinical deterioration moderated by baseline age or functional status?
  • How do individual PRO scores predict short-term (3-6 month) and longer-term (1-2 year) worsening or improvement in chronic disease management indicators or risk factors, and functional outcomes (e.g., work, school, family, leisure)? What magnitude or slope of change in individual PRO scores predicts improvement in chronic disease management?
  • How does clinically relevant information (e.g., age, preoperative functional status, comorbid conditions such as depression, use of multiple medications, social determinants of health) affect the interpretation of PROs to determine the appropriate treatment options for any given diagnosis? How should this information be incorporated in the interpretation of PROs in making clinical decisions for individual patients?
  • How can an individual’s PRO score/s (e.g., diabetes distress, depression, fear of hypoglycemia) guide treatment decisions such as referral to behavioral health, medication intensification, regimen simplification, or engagement in chronic disease management education and support? How do these “action” prompting scores vary based on other individual characteristics, type of chronic condition, and/or comorbidities?
  • Which PRO-based values (e.g., continuous score, categorical value such as above or below age-matched cut point, or slope of change over time) best predict functional outcomes at the individual patient level 1 year following particularly intensive or invasive disease treatments (e.g., cancer-directed therapies such as stem cell transplantation, combined modality treatment)?
  • How might PRO data be integrated with clinical indicators to inform individual prevention or treatment recommendations. As an example, could individual A1C data be used along with PRO data to help tailor and improve diabetes prevention or treatment recommendations and shared decision-making processes? Does this vary by individual characteristics, high risk social determinants variables, type of diabetes, and/or comorbidities?
  • How should PROs be interpreted when individuals have more than one chronic medical condition?
  • Should all PRO scores and thresholds be interpreted the same way for different populations? For example, would threshold scores be developed by age or overall health status to inform the care of specific populations (e.g., older adults, children with complex medical needs, pregnant women, women with severe maternal morbidity or at high risk of maternal mortality) or stages in care (e.g., prevention of post-surgical complications, post-partum care)?

Application and Submission Information

IC Specific Application and Submission Information:

All submissions should indicate that they are in response to NOT-OD-20-079 in Field 4.b on the SF 424 form.

Prior to submission, investigators are strongly encouraged to contact the IC scientific contacts listed in this Notice for advice on alignment with program priorities and polices.

The following funding opportunity announcements (FOAs) or their reissued equivalents must be used for submissions for this initiative. Although NCI and NINDS are not listed as a Participating Organization in all the FOAs listed below, applications for this initiative will be accepted provided that the NOSI is listed in Field 4.b on the SF 424.

Applications nonresponsive to terms of this NOSI will be withdrawn from consideration for this initiative.

Activity Code

FOA

R01

PA-19-056 - NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed)

R21

PA-19-053 - NIH Exploratory/Developmental Research Grant Program (Parent R21 Clinical Trial Not Allowed)

Although NCI and NINDS is not listed as a Participating Organization in all the FOAs listed above, applications for this initiative will be accepted.

Applications nonresponsive to terms of this NOSI will be withdrawn from consideration for this initiative.

 

Inquiries

Please direct all inquiries to:


Scientific/Research Contact(s)

Ashley Wilder-Smith, Ph.D., MPH
National Cancer Institute (NCI)
Telephone: 240-276-6714
Email: smithas@mail.nih.gov

Dave Kaufman, Ph.D.
National Human Genome Research Institute (NHGRI)
Telephone: 301-594-6907
Email: dave.kaufman@nih.gov


Molly Wagster, Ph.D.
National Institute on Aging (NIA)
Telephone: 301-496-9350
Email: wagsterm@nia.nih.gov

Jonathan King, Ph.D.
National Institute on Aging (NIA)
Telephone: 301-402-4156
Email: kingjo@mail.nih.gov

Mariela C. Shirley, Ph.D.
National Institute on Alcohol Abuse and Alcoholism (NIAAA)
Telephone: 301-402-9389
Email: shirleym@mail.nih.gov

Stephanie M. George, PhD, MPH, MA
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Telephone: 301-594-4974
Email: stephanie.george@nih.gov

Lana Shekim, Ph.D.
National Institute on Deafness and Other Communication Disorders (NIDCD)
Telephone: 301-496-5061
Email:  shekiml@nidcd.nih.gov

Claudia Moy, Ph.D.
National Institute of Neurological Disorders and Stroke (NINDS)
Telephone: 301-496-9135
Email:  cm384s@nih.gov

Jenni Pacheco, Ph.D.
National Institute of Mental Health (NIMH)
Telephone: 301-443-3645
Email: jenni.pacheco@nih.gov

Martha Matocha, Ph.D.
National Institute of Nursing Research (NINR)
Telephone: 301-594-2775
Email: matocham@mail.nih.gov

Larissa Avilés-Santa, M.D., M.P.H.
National Institute on Minority Health and Health Disparities (NIMHD)
Telephone: 301-827-6924
Email: avilessantal@nih.gov

Lanay M. Mudd, Ph.D.
National Center for Complementary and Integrative Health (NCCIH)
Telephone: 301-594-9346
Email:lanay.mudd@nih.gov

Elizabeth Ginexi, Ph.D.
NIH Office of Behavioral and Social Sciences Research (OBSSR)
Telephone: 301-594-4574
Email: LGinexi@mail.nih.gov

Margaret Bevans, PhD, RN, FAAN
NIH Office of Research on Women’s Health (ORWH)
Telephone: 301-496-3934
Email: Margaret.Bevans@nih.gov

Kay L. Wanke, PhD, MPH
NIH Office of Disease Prevention (ODP)
Telephone: 301-451-1856
Email: kay.wanke@nih.gov