Implementation Status of the National Forum of State Nursing Workforce Centers National

Nursing Workforce Minimum Datasets for

Education, Supply, and Demand Presentation at the June, 2012

Taking the Longview Nurse Workforce ConferenceIndianapolis, IN

 Patricia Moulton, PhD; Pamela Wiebusch, BA; Duane Napier,

MSN, RN; Jeannie Cimiotti, DNSc, RN; Cynthia Bienemy, PhD, RN and

Sandra Anne LeVasseur, PhD, RN 

IOM Future of Nursing Cites the need for improved data collection

and an enhanced information infrastructure as requirements for effective workforce planning and policy making.

Data “on the numbers and types of health professionals currently employed, where they are employed and in what roles” is imperative to the establishment of accurate workforce projection models

Our Story1995: Colleagues in Caring Minimum Supply Dataset

June, 2008: National Forum of State Nursing Workforce Centers Meeting in Denver, CO Identified the problem as a priority Established a subcommittee to assess current data collection practices Set a goal of producing minimum datasets, the set of core data elements

needed for our work

November, 2008: The project design was finalized through a contract between the Center to Champion Nursing in America and the Florida Center for Nursing (acting on behalf of the Forum) Three additional states invited to participate via CCNA State Education

Capacity Teams

A total of 31 states participated in one or more phases of the project

State data assessment (July-December 08)MDS Survey of States (Jan 09)Drafting Workgroups (Feb-March) Data Summit (late March 09)Public Comment Period (May-June 09)Ratification (September 09)Implementation (ongoing)Final data sets are available at:

www.nursingworkforcecenters.org

Where are we Now?Survey of Forum members regarding implementation of all three data sets Summer/Fall 2011

Follow-up validation with each center

30 states completed the survey

2011 Education Data Set StatusVariable

# of States Collecting

Variable 1: Accreditation 19Variable 2: Seats for new students 21Variable 3: Qualified applicants 19Variable 4: Admitted applicants 23Variable 5: New enrollees 21Variable 6: Graduates 26Variable 7: NCLEX Pass Rates 20Variable 8: Total enrollment 22Variable 9: Student gender 20Variable 10: Student race/ethnicity 16Variable 11: Student age 15

Variable 12: Full- and part-time faculty counts 25

Variable 13: Full- and part-time faculty vacancies 19

Variable 14: Highest degree of faculty 20

Variable 15: Faculty gender 16Variable 16: Faculty race/ethnicity 13Variable 17: Faculty age 18

How does that compare to 2008? Accreditation

Seats for New Students

Qualified Applicants

Admitted Applicants

New Enrollees

Graduates

NCLEX Pass Rates

Total Enrollment

Student Gender

Student Race/Ethnicity

Student Age

Faculty Counts

Faculty Vacancies

Highest degree of Faculty

Faculty Gender

Faculty Race/Ethnicity

Faculty Age

0 5 10 15 20 25 30

7

7

9

8

8

11

10

7

7

6

10

10

9

2

2

4

19

21

19

23

21

26

21

22

20

16

15

25

19

20

16

13

18

20112008

Barriers to education data collection include:• firewalls between nursing education programs and the

entity collecting data restricting the use of online surveys • large schools use an administrative assistant to

collect/report data which is not always accurate• issues with differences in common terminology• data collection doesn’t include proprietary institutions• nursing programs answer multiple surveys in the field

and not wanting to respond to another one• slow response rates from Deans/Chairs • cost of data collection• online programs don’t report in and out of state students.

2011 Supply Data Set StatusVariables

# of States Collecting (n)

Variable 1: Gender 22Variable 2: Race/Ethnicity 22Variable 3: Year of birth 24Variable 4: Entry level education 20Variable 5: Highest level of education 21Variable 6: License type 26Variable 7: Year of Initial licensure 17Variable 8: Country of initial licensure 14Variable 9: License Status 18

Variable 10: APN License/Certification 23

Variable 11: Employment status 18

Variable 12: Reason for being unemployed 8

Variable 13: Number of positions employed in 14

Variable 14: Hours worked per week 18Variable 15: Employer’s address 17Variable 16: Employment setting 24Variable 17: Employment position 19Variable 18: Employment specialty 17

How does that compare to 2008? Gender

Race/Ethnicity

Year of Birth

Entry Level Education

Highest Degree

License Type

Year of U.S. licensure

Country of initial licensure

License Status

APRN Licensure/Certification

Employment Status

Reasons for being Unemployed

Number of positions

Hours worked per week

Employer’s address

Employment Setting

Employment Position

Employment Specialty

0 5 10 15 20 25 30

15

16

15

14

16

7

9

4

10

12

5

8

16

15

17

9

10

22

22

24

20

21

26

17

14

18

23

18

8

14

18

17

24

19

17

20112008

Barriers to implementing the supply data set include:low response rates as the survey is not

mandatoryserver outage issues for online survey that

caused a large loss of data issues with surveying and counting nurses in

compact states cost of analyzing survey responses.

2011 Demand Data Set StatusVariables

# of States Collecting

Variable 1: Full-time equivalent positions currently occupied

10

Variable 2: FTE Vacancies currently being recruited on/put on hold/frozen

11

Variable 3: Average full-time workers employed

9

Variable 4: Average part-time workers employed

7

Variable 5: Per diem workers 5

Variable 6: Contract, Agency, and Traveling FTEs

7

Variable 7: FTE Separations 7

Variable 8: FTEs organization intends to employ

5

How does that compare to 2008? FTE positions currently occupied

FTE Vacancies currently being recruited on/put on hold/frozen

Average full-time workers employed

Average part-time workers employed

Per diem workers

Contract, Agency, and Traveling FTEs

FTE Separations

FTEs organization intends to employ

0 2 4 6 8 10 12

8

8

0

0

0

5

7

3

10

11

8

6

3

7

7

6

20112008

Demand data collection barriers include:low response ratesit is time consuming and costlyuse of FTE versus head countsuse of Occupational Employment Statistics

(BLS) data which doesn’t allow breakdown of data into FTE

full time or part time.

Overall Summary of Findings and Policy Implications  The original intention of the Forum’s national minimum data set was to provide an avenue for the collection of a national minimum data set and to enable states to compare their data with other states and with national numbers. Forum and other interested organizations working on putting together National Minimum datasets have many steps to reach this goal. These include:· Determining where the data will be housed and what entity/entities will assemble and maintain the data.· Getting buy-in at the state level for both collecting the minimum dataset and sharing it with the warehousing entity.· Mentoring states with fewer human and fiscal resources in beginning or changing data collection routines.· Determining how the data will be used and under what conditions it will be shared with researchers across the country.· Determining a stable funding source for collection, housing and analysis of data sets.