EarthWorks Geospatial Catalog

Registered Nurse Shortage Areas, California, 2015

This polygon shapefile contains registered nursing shortage areas (RNSAs) in California for 2014. The Commission uses the RNSA as only one of many factors to determine Song-Brown funding for nursing education programs. The RNSA does not in itself determine funding or funding levels. The method for determining the RNSA is a function of the number of licensed nurses (supply) and patient volume (demand). The analysis performed uses annual data requested from the Board of Registered Nurses and patient count - hospital utilization data from OSHPD HIRC and compiled/analyzed on a county basis. Final designation is determined when a county (1) lacks a general acute care hospital (GAC) and a long-term care (LTC) facility and (2) is above the mean ratio of available nurses to patient volume. The ratio is the total number of bed days for GACs and LTC facilities multiplied by .08 and divided by the number of registered nurses (RNs) in the specific county. Three factors are used in defining nursing shortages: (1) California counties (as the geographic unit for analysis), (2) California registered nurse data of all active licenses by county from the Board of Registered Nursing (BRN), Department of Consumer Affairs , and (3) the patient day and census data from all LTCs and GACs from OSHPD. OSHPD maintains data on patient volume for GACs and LTCs. These data are maintained in the OSHPD Automated Licensing Information and Report Tracking System (ALIRTS) program. These locations employ nearly 70% of the total nursing workforce in California. No current data exist on patient volume for the other 30% of the workforce. OSHPD facility census data for year of evaluation were obtained by county. There are more licensed bed days in LTCs than GACs in California and LTCs only account for 5% of the registered nurse workforce. Therefore, a scale factor representing the percent of the nursing workforce at LTCs in this function was applied to ensure the census data were not skewed. A total census was created by summing the two numbers and a ratio was used of census divided by registered nurses for each of the 58 counties. Ratio Equation: SUM(CensusDaysGAC + [(PatientDaysLTC) * 0.08]) / RNCount. Where: CensusDaysGAC is the number of days a patient is occupying a bed in General Acute Care Hospitals in year of evaluation. PatientDaysLTC is the number of days a patient is occupying a bed in Long-Term Care Facilities in year of evaluation. RNCount is the number of licensed, active registered nurses per county in year of evaluation .These data were collected beginning in October 2014.Data collection begins in October 2014. The data being analyzed are for 2014 (year of evaluation). Total Population was taken from American Community Survery 2010 Estimates.There will always be a lag (of a year or more) due to the availability of the data. The reports to the Commission are usually presented at the public meeting for registered nursing programs every year. This version was presented to the Commission on March 4, 2015. This layer is part of the Healthcare Atlas of California.The Commission requires a quantitative, repeatable and meaningful way of ranking applications whose past graduates and training facilities operate in areas of unmet need (e.g. shortages). Determining nursing shortage areas is extremely different than determining physician shortage areas. Nurses are nearly entirely employed at licensed health facilities, while physicians have multiple practice locations in the field. Therefore, the Commission has adopted a California Registered Nurse Shortage Area (RNSA) as a function of (1) facilities at which nurses are predominantly employed (2) the volume of patients at these facilities and (3) available licensed nurses to work at these locations. This function provides an aggregate ratio of patient demand to nurse availability. For this designation, counties are used as the analytical unit.
California. Office of Statewide Health Planning and Development
Nurses, Health services accessibility, Medically underserved areas, and Health
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