As was the case when the original Minimum Data Set (MDS) was created and matched to Medicare claims, the manuscripts published that established the validity of various scales and data elements are among the most cited papers in the literature on nursing homes (see Appendix A - see below). We anticipate that manuscripts emerging from this effort will also be amongst the most cited in the future as researchers increasingly rely upon this enriched data source for clinical and comparative effectiveness studies.

Examples of the types of validation that are of interest include:

• The completeness of clinical data ranging from quantitative laboratory tests, vital sign records, medication administration records, and medical orders;
• The frequency, validity, and utility of cognitive, mood, pain, and other clinical assessments in the EHR (beyond measures already in the MDS);
• The prevalence, frequency, validity, and sensitivity of vital sign data and blood glucose monitoring;
• The periodicity of medication prescriptions and changes for common drug classes;
• The validity of the medication order data relative to data in the electronic medication administration record (eMAR);
• The prevalence, frequency, and validity of advance directive orders;
• Text-based documentation in interdisciplinary progress notes that might improve the sensitivity or specificity of capturing prevalence and change in behavioral and mood symptoms; and
• Establishing the validity of any of the clinical data elements by comparing them across diverse resident populations assumed to differ on blood sugar levels, blood pressure, or drugs used.

2023 Real World Data Scholars **CLOSED**

No upcoming RFAs at this time.

An informational webinar will be hosted to provide potential applicants with an overview of the program and application details. Potential applicants will have the opportunity to ask questions. Pre-registration is required.

• Tuesday, June 13, 2023 at 3:00 PM ET: Watch the webinar recording

Answers to frequently asked questions are provided here. If you have further questions, please contact RWDScholars@brown.edu

AcademyHealth 2023 Annual Research Meeting | June 24-27, 2023

Dr. Vincent Mor, one of the LTC Data Cooperative’s principal investigators, will be at AcademyHealth’s 2023 Annual Research Meeting June 24-27, 2023 and will be available to meet with potential applicants in attendance. Interested attendees can set up a meeting with Dr. Mor at AcademyHealth by contacting RWDScholars@brown.edu to schedule a time.

GSA 2023 Annual Scientific Meeting | November 8, 2023

Real World Data Scholars will be expected to attend a pre-conference workshop hosted by the LTC Data Cooperative team at the Gerontological Society of America’s Annual Scientific Meeting on Wednesday, November 8, 2023 at 1:00PM ET in Tampa, Florida. Applicants should include approximately $2,000 in direct costs in their proposed budget to cover the costs of travel, accommodation, and attendance. More information on the workshop and how to register can be found here: https://www.gsa2023.org/Program/Workshops.

Awards are for 12 months and up to $50,000 in direct costs. Indirect costs are capped at 8% consistent with similar NIH educational awards. Applicants must be associated with an academic institution or academic medical center. No research may be performed outside of the United States.

Applicants must be citizens or permanent residents of the United States.  Applicants from under-represented racial and ethnic groups as well as individuals with disabilities are strongly encouraged to apply.

Investigators at all levels are welcome to apply. We encourage applications from advanced graduate students, post-doctoral fellows, and early-career faculty who are interested in developing their expertise and experience in working with EHR data.  Applicants should be experienced with using large-scale administrative and/or clinical data (e.g., EHR data, Medicare claims, Minimum Data Set, registry data, etc.) Individuals with a background in pharmacoepidemiology, natural language processing, or clinical investigations are also encouraged to apply.

Applications must be submitted as a single PDF via email to RWDScholars@brown.edu.

The application period will open on Friday, June 16, 2023 at 9:00 AM ET. Applications may be submitted no later than Friday, August 4, 2023 at 5:00 PM ET.

Proposal Content

Full applications will include the following content, not to exceed 3 pages total in Arial Font 11 or Times New Roman 12, 1 inch margins:

• PHS 398 Form Page 1: Face Page (not included in page limit)
• Applicant Section (limit to 2 pages)
  • Applicant Information and Goals for Career Development, including the applicant’s interest in aging research, long-term care, and/or EHR data and how this training period may lead to future research.
  • Applicant’s Background, including current and prior experience in research related to working with large-scale administrative and/or clinical data.
  • Examples of analytic experience with big data, such as sample code, published papers, work samples, etc. (This can be submitted in the form of an appendix or a link to the information on the internet which reviewers can access).
• Analytic plan (limit to 1 page)
  • Choose one of the types of interest for validation listed under the “Program Description & Goals” section (see above) of this RFA and draft a sample analytic plan.
  • The analytic plan should include a research question, a summary of which data elements and measures would be used from the EHR data (technical user guide will be released June 16, 2023 HERE), a description of how the data might be integrated and structured into a hierarchical and/or longitudinal file, the types of descriptive analyses that might be performed, and the relevance of the question to the goal of establishing the validity of the data.
• Letter of support (not included in page limit)
  • A letter of support is required from the applicant’s supervisor (e.g graduate supervisor, faculty mentor or Department Chair) that addresses the applicant’s experience using large-scale administrative or clinical data and validation, their fit with the Real World Data Scholars Program, and that they agree to allow the applicant to spend the proposed percent effort on the program’s activities.
• Updated NIH Biosketch (not included in page limit)
• PHS Form Page 4 Detailed Budget for Initial Budget Period (Direct Costs Only) with detailed budget justification (not included in page limit)

Awards are for 12 months and up to $50,000 in direct costs. Indirect costs are capped at 8%. Applicants must submit a detailed budget and accompanying budget justification for expenses and salary support. The expected time commitment should be commensurate with the partnership activities proposed, with a suggested range of 25% to 50% of an applicant’s effort for up to 12 months. Applicants who are already recipients of training grant or career development awards are still eligible to apply, however, the budget amount requested should not be for the investigators’ salary support but can be used for other purposes. Applicants should include costs for their travel, accommodation, and attendance to one 4 day in-person meeting (the Gerontological Society of America’s Annual Scientific Meeting) in Tampa, FL from November 8-12. Registration rates can be found here.

For eligibility, program, and budget-related questions, or to set up a time to meet with Dr. Vince Mor at the AcademyHealth 2023 Annual Research Meeting, please contact RWDScholars@Brown.edu. For general information on the LTC Data Cooperative, please visit www.ltcdatacooperative.org.

Hawes C, Morris JN, Phillips CD, Mor V, Fries BE, Nonemaker S. Reliability estimates for the Minimum Data Set for nursing home resident assessment and care screening (MDS). The Gerontologist. 1995 Apr 1;35(2):172-8. https://academic.oup.com/gerontologist/article-abstract/35/2/172/602293

Saliba D, DiFilippo S, Edelen MO, Kroenke K, Buchanan J, Streim J. Testing the PHQ-9 interview and observational versions (PHQ-9 OV) for MDS 3.0. Journal of the American Medical Directors Association. 2012 Sep 1;13(7):618-25.  https://www.sciencedirect.com/science/article/pii/S152586101200182X

Thomas KS, Dosa D, Wysocki A, Mor V. The minimum data set 3.0 cognitive function scale. Medical care. 2017 Sep;55(9):e68.  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4567556/

Hartmaier SL, Sloane PD, Guess HA, Koch GG, Mitchell CM, Phillips CD. Validation of the minimum data set cognitive performance scale: agreement with the mini-mental state examination. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences. 1995 Mar 1;50(2):M128-33.
https://academic.oup.com/biomedgerontology/article-abstract/50A/2/M128/539144

Morris JN, Fries BE, Morris SA. Scaling ADLs within the MDS. J Gerontol A Biol Sci Med Sci. 1999 Nov;54(11):M546-53. https://pubmed.ncbi.nlm.nih.gov/10619316/

Fries BE, Simon SE, Morris JN, Flodstrom C, Bookstein FL. Pain in U.S. nursing homes: validating a pain scale for the minimum data set. Gerontologist. 2001 Apr;41(2):173-9. doi: 10.1093/geront/41.2.173. PMID: 11327482.

Rahman M, Tyler D, Acquah JK, Lima J, Mor V. Sensitivity and specificity of the Minimum Data Set 3.0 discharge data relative to Medicare claims. Journal of the American Medical Directors Association. 2014 Nov 1;15(11):819-24. https://www.sciencedirect.com/science/article/pii/S1525861014003971

Bélanger, E, Thomas, KS, Jones, RN, Epstein-Lubow, G, Mor, V. Measurement validity of the Patient-Health Questionnaire-9 in US nursing home residents. Int J Geriatr Psychiatry. 2019; 34: 700– 708.
https://doi.org/10.1002/gps.5074