Editor s Note: This online data supplement contains supplemental material that was not included with the published article by Denise A. Davis and Melanie D. Napier, Strategically Addressing the Nurse Shortage: A Closer Look at the Nurse Funders Collaborative, Health Affairs 27, no. 3 (2008): 876-881 (10.1377/hlthaff.27.3.876) Appendix: Data Supplement This appendix contains supplementary information about the data and exhibits. 1. Search Criteria We searched the grant description and recipient name of the tax forms for the key term nurs*. 1 Results from each of these searches were analyzed to identify unique grants and later combined into one database. Additionally, a Grant Visualizer tool allowed us to geographically map funding patterns using the same search criteria. The same search was used to search two federal grant databases The Catalog of Federal Domestic Assistance and the Tracking Accountability in Government Grants System (TAGGS) to gather information on the cost, duration, and purpose of federal nursing grants. 2 By March of 2007, more than 95-99 percent of 2004 tax forms had been uploaded. 2. Data Limitations The major limitation of this analysis is that it relies on private funders self-reported descriptions of how they distributed their grants on the 990PF tax forms. In their descriptions, funders provided varying levels of detail about what grant money was used to fund. All the categorical classifications we made were constrained by the information they provided. We often took into consideration the type of grantee (educational institution, professional organization, 1
etc.), as well as the description that the funding organization provided, to make an appropriate categorization. When necessary, we also looked at a funder s history of funding a particular grantee as well as the funder s stated grant-making objective (i.e. to support nursing students while they are in nursing school). All of these factors influenced how private grants were classified. This was especially true in cases where a grant could have fit into more than one category. For example, depending on the grant, supply and demand could be an issue for those in long-term care and geriatrics or nursing education or other nursing professions. In those cases where there was ambiguity about a grant s classification, the context was taken into account. Ultimately, each grant was assigned into a single category to avoid double counting. Additionally, it was more difficult to procure reliable data about federal government grants due to the absence of a central depository of all types of grantee information. Therefore we used multiple sources and cross-referenced them to fill in missing information. In particular, the Tracking Accountability in Government Grants System (TAGGS) database did not seem to include grants in the form of loans, loan guarantees, interest subsidies, or insurance. There were three government nursing loan programs for which we were not able to obtain individual grantee information: the Nurse Faculty Loan Program, the Nursing Student Loan Program, and the Nursing Education Loan Repayment Program. For these three, we used the Catalog of Federal Domestic Assistance to find grant amounts given in particular fiscal years. The absence of stateby-state recipient data for the three government programs meant that we could not discuss or depict funding amounts geographically. For this reason, there is no map showing the states which received government grants. 3. Rationale behind categorical classifications 2
The categories were modified from a funding matrix that Collaborative members had created to identify the nursing issues they were actively funding in at every level (philanthropy, federal government and the private sector). The original funding matrix was comprised of 39 different subcategories within five major nursing areas Nursing Supply & Demand, Nurse Education, Nursing Long-Term Care (LTC) & Geriatrics, Nursing Profession, and Nursing Emerging Issues. We added the three categories of Nursing Research, Capital Improvements and Other, and included additional subcategories to reflect the grant-making we observed. A summary table of all the categories and subcategories used throughout the paper is below in Exhibit 1S. Exhibit 1S: Nursing Categories Capital Improvements Nurse Education Nursing Emerging Issues Nursing LTC & Geriatrics Nursing Profession Nursing Supply & Demand Nursing Research Other Equipment, Nursing School Construction, Patient Facility Construction Faculty Recruitment & Curriculum Development, Scholarship, Training Cultural Competency, Diversity, Language, Special Populations, Technology Education & Fellowships, Geriatric Nurses & Workforce Development, Home Health Care, LTC Leadership, QI, Workforce Development Retention & Recruitment, Workforce Studies Research Program Support, Operating Support Although the categories are described in the text (and below in the section: Data Discussion of the Remaining categories), it is worth noting the following: 1) the nurse education category included training at all levels (Associates, Diploma, Baccalaureate/BSN, 3
Masters, Doctoral) and included any licensed practical nurse (LPN), nursing assistant or advanced nursing practice training; and 2) the nursing research category included research done by nursing students, faculty and professionals as well as research done by others on topics that impact the nursing profession. Also note that there is the potential for some overlap in categories. This was especially true among the emerging issues subcategories. Diversity and language were similar with the distinction that grants that addressed language were specifically more concerned with communication between nurses and patients. The main focus of diversity grants was on increasing the presence of ethnic and culturally varied individuals at all levels of nursing education and practice. Grants that were classified as cultural competency encompassed training for nurses in the customs, traditions and cultures of minority groups. Grants in the special populations subcategory include those that provided nursing services to particular hard-to-reach and vulnerable populations (i.e. homeless individuals, HIV-infected individuals, disabled individuals, foster children, etc.). 4. Data Discussion of Remaining Categories Additional Characteristics of Nurse Funders A total of 1908 private foundations funded nursing initiatives from 2000 to 2004. Thirtytwo percent of the foundations were consistent funders, meaning they contributed to nursing for at least three years out of the five year period examined. Of the ten government agencies that funded nursing during that same period, seven were consistent funders. 3 Private & Government Agency Funding Distribution 4
A description of the funding that went to nursing education, nursing emerging issues, and nursing supply/demand is found in the text of the paper. The remaining grant money was divided as follows: Nursing long-term care & geriatrics initiatives received the most funding from private foundations after nurse education. The vast majority of funding in this category (69 percent) supported home health care, described as nursing services rendered in the home, community, and parish as well as the organizations that provided those services. Home health care grants totaled $65.8 million. Over $12 million (13 percent) went to grants for geriatric education and fellowships, while $13 million was used for geriatric nurses and workforce development. The final 5 percent ($4.3 million) was used to fund nurses who provided long-term care services. Total grant funding for nursing long-term care & geriatrics was $95 million. Grants to the nursing profession category accounted for 9 percent ($34 million) of private foundation grant money. Within the category of nursing profession, 48 percent ($16 million) of funds went to nursing leadership initiatives and 41 percent ($14 million) was for workforce development. Grants toward quality improvement studies made up the remainder of funding. Grants in the capital improvements and other categories each garnered 10 percent of total private foundation funding. Sixty-four percent ($23.2 million) of capital improvements funds went to increase educational capacity by building or renovating nursing schools. Another 23 percent ($8.4 million) was for patient facilities, such as renovating nurses stations in nursing facilities. The final 13 percent ($4.6 million) was for large equipment purchases. Capital improvements accounted for 23 percent of large grants, and was the only area, besides the leadership subcategory, in which large grants accounted for more than small grants. Funding in 5
the other category was to support operations (56 percent) and general programs (44 percent). Capital improvements and other grants each totaled approximately $36 million. Since 88 percent of government grants went towards nursing education and research, the remaining 12 percent $136 million was divided among several categories. Four percent of funds were used to fund diversity and technology grants within the category of nursing emerging issues. Diversity in the nursing workforce is one of the target areas authorized by Congress and HRSA has a program devoted to the topic area. 4 Nursing long-term care & geriatrics grants, specifically education, fellowships, home health care, and workforce development received 3 percent in all; nursing profession received 2 percent, particularly for quality improvement initiatives; operating and program support also received 2 percent. Government contributions may be underreported because of the difficulty of obtaining comprehensive funding data that extends back to 2000. 5. Additional Exhibit Data Exhibit 2S Exhibit 2S depicts the nursing areas large private funders, small private funders and government funders gave grants to. Large Funders Small Funders All Private Funders Government Funders 23% 0% 11% 2 1% 39% 13% 3% 1% 8% 4% 40% 10% 10% 9% 39% 49% 1% 0% 39% 4% 27% 4% 25% 3% 3% Nurse Education Nursing Supply & Demand Nursing Research Nursing Emerging Issues Nurse LTC & Geriatrics Capital Improvements Other Nursing Profession Exhibit 2S: Funding Patterns, 2000 2004. Source: Private: 990PF tax forms, FoundationSearch.com by Metasoft Systems, obtained 3/07; Government: Catalog of Federal Domestic Assistance and the Tracking Accountability in Government Grants System. 6
6. Private Foundation Map Data We understand that it is helpful to visualize the contribution from private foundations as a whole. The map of the private foundation contribution is below in Exhibit 3S: WA OR NV CA MT ID WY UT CO AZ NM AK HI ND SD NE KS TX OK MN IA MO AR LA WI IL MI IN OH KY TN MS AL Legend WV VA GA Up to $2 million $2 million - $6 million $6 million - $10 million $10 million & Up NC SC PA FL VT NY ME NH MA RI CT NJ DE MD DC Exhibit 3S: U.S. States (and D.C.) which have received grants from private foundations, 2000 2004. Source: 990PF tax forms, FoundationSearch.com by Metasoft Systems. Notes: Includes 2004 990PF data through March 2007. Heavy line separates states into regions: Northeast, Midwest, Southeast, West and Southwest. 5 1 Using the asterisk ( nurs* ) signifies a wildcard search, which allowed us to search as broadly as possible for all permutations of terms that contain nurs. 2 Both databases accessible online at http://12.46.245.173/cfda/cfda.html and http://taggs.hhs.gov/index.cfm (both accessed 5 February 2008). 3 These agencies are: Health Resources and Services Administration (HRSA), the National Institute of Nursing Research (NINR) at the National Institutes of Health (NIH), Agency for Health Research and Quality (AHRQ), Centers for Medicare and Medicaid (CMS), Health and Human Services (HHS), Substance Abuse and Mental Health Services Administration (SAMHSA) and Indian Health Service (IHS). 4 Authorizing legislation can be found at: http://bhpr.hrsa.gov/nursing/legislation.htm (accessed 5 February 2008). 5 Midwest = IA, IL, IN, KS, MI, MN, MO, ND, NE, OH, SD, WI; Northeast (incl. DC) = CT, DE, MA, MD, ME, NJ, NY, NH, PA, RI, VT; Southeast = AL, AR, FL, GA, KY, LA, MS, NC, SC, TN, VA, WV; Southwest = AZ, NM, OK, TX; West = AK, CA, CO, HI, ID, MT, NV, OR, UT, WA, WY. 7