HWSMHuman Whole Salivary Mucin Fraction
HWSMHuman Whole Salivary Mucins
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HWSM creates one record for each NCLEX-RN test taker, with information on age, sex, state, and educational level.
In Step 1 of the HWSM, individuals in the base year micro data are aged forward according to their age-sex specific survival rates.
Depending upon the value of the random number and estimated probability of dying, records in the HWSM micro data file are deleted.
HWSM assumes these numbers of 2012 graduates would continue annually throughout the forecast window (the nation would produce 62,500 new RNs [baccalaureate level] and 87,700 new RNs [less than the baccalaureate level]).
For ages below 50 years, HWSM calculates the age-sex specific participation rates directly.
HWSM determines the expected number of hours worked for RNs projected to be active in the workforce using a two-step regression model.
The HWSM estimates the baseline supply for each modeled health occupation separately, using person-level data to characterize providers' age, sex, education, training, and geographic location.
Important strengths of the HWSM include application of a consistent approach to analyzing supply and demand across practitioner type and medical discipline; use of microsimulation methodologies to ensure representativeness and provide reliable population-level estimates; and the capability to simultaneously examine the impact of multiple health care drivers, including population growth, changing demographics, health status, and expanded health insurance coverage.
A major limitation of the HWSM lies in its assumption of baseline equivalence.
HRSA anticipates that future versions of the HWSM will allow more nuanced modeling of these factors.
While this is similar to other workforce projections, HRSA is continuing to build new capabilities into the HWSM to expand its scenario modeling capabilities and produce ranges of supply and demand.
The HWSM projections reflect baseline assumptions regarding supply, demand, new entrants into each profession, retirement patterns, and provider-utilization ratios.