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Leaving Nursing: Predictors of nursing drop-out and switching between sectors* Audrey Laporte, Ruth Croxford, Andrea Baumann, Linda O’Brien–Pallas, Raisa Deber.

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  1. Leaving Nursing:Predictors of nursing drop-out and switching between sectors*Audrey Laporte, Ruth Croxford, Andrea Baumann, Linda O’Brien–Pallas, Raisa Deber * This project has benefited from funding support provided by CIHR (Grant # 64240, “Where do nurses work? Work setting and work choice”) and the From Medicare To Home and Community (M-THAC) Research Unit

  2. Data Source • To practice in Ontario, nurses must register annually with the College of Nurses of Ontario (CNO) • CNO data for 1993-2002 were merged on a unique registration number. • Observed career paths of 191,916 nurses registered in Ontario.

  3. Demographics

  4. Proportion of Nurses by Sector 1997

  5. A word about wages…. • No wage info in the registration data base but unionization concentrated in sectors • e.g. virtually all hospital and most long-term care nurses are unionized and are paid on an 8-step grid corresponding to year of experience • Most home care nurses are not unionized • RPNs paid on a separate grid • The ONA is the trade union representing nurses in province-wide collective bargaining

  6. Analysis 1 Dropping Out of the Pool • The pool of nurses can be variously defined as including those who currently: • Work as nurses in Ontario (‘actives’) • Are registered but not working as nurses (‘eligibles’) • Are registered but work outside Ontario • Are NOT registered & are under 65 yrs of age • We focus here on predictors for the retention of those working in nursing in Ontario since policy change can more readily influence these workers in the short to medium term(i.e. active pool)

  7. Included: 145,864 nurses who were either already nursing in Ontario in 1993 or registered for the first time in 1993-2002 and found nursing work in Ontario. • Excluded: • Registered in Ontario prior to 1993 but did not work as a nurse in 1993/1994. • New registrants who did not work as a nurse during the first two years. • Dropping out: a period of two consecutive years during which the nurse did not work as a nurse in Ontario. • Proportional hazard survival analysis to identify predictors of “time to drop out”.

  8. Determinants of ‘Drop Out’ Training/Employer factors Baseline: RN with no additional education, only one employer, working full-time, living in the Central/Toronto region, aged 40-44 yrs, working in a Hospital

  9. Determinants of ‘Drop Out’ Age at the start of observation Baseline: RN with no additional education, only one employer, working full-time, living in the Central/Toronto region, aged 40-44 yrs, working in a Hospital

  10. Determinants of ‘Drop Out’ Age at the start of observation Baseline: RN with no additional education, only one employer, working full-time, living in the Central/Toronto region, aged 40-44 yrs, working in a Hospital

  11. Interactions

  12. Analysis 2“Stickiness”: Do nurses who remain stay in the same sector?

  13. The two most recent years (2001 and 2002) were examined. Only nurses who worked in both years (N = 95,000) were included. • 11.6% changed sectors. • Hospital sector: 6% switched. • Long-term care sector: 12% switched. • Community sector: 15% switched. • ‘Other’ sector: 23% switched. • RNs (11%) versus RPNs (15%). • Single employer (9%) versus multiple employers (22%).

  14. Who Switches?

  15. Who switches?

  16. Who switches?

  17. Analysis 3: Where do They go When they Switch • Multinomial logit regression analysis was used to examine where nurses went when they left a sector.

  18. Young nurses are the most likely to change sectors (23% vs. 16% of those age >= 30), and much more likely to leave Ontario (1.6% vs. 0.3%). • RPNs are more likely to switch into the LTC setting than are nurses, and less likely to leave the LTC setting if they work there. • RNs who have a university degree are more likely to switch into the community sector, and much less likely to leave it if they are there.

  19. Conclusions (1) • More likely to drop out: • RPNs • Males • Younger nurses (20-29 yrs) even after allowing for temporary absences. • Older nurses, with more experience • Part-timers • Nurses in the Community and Long-Term Care sectors • Those who obtained additional education after they started working

  20. Conclusions(2) • Less likely to drop out: • Those with multiple employers (may reflect increased need for income (i.e. family bread-winner)

  21. Conclusions-Switching • Nurses more likely to switch: • Multiple employers • Males • Casual and Part-timers • RPNs • Outside the Hospital sector

  22. Conclusions (2)-Switching • LTC: • RPNs and those with longer job tenure less likely to switch • More educated and multiple employers more likely to switch • Hospital & Community: • RPN, casual/PT, multiple employers more likely to switch • More educated in community less likely to switch but more likely to do so in hospital sector

  23. Policy Implications • RPNs are more likely to ‘drop-out’ and they are important to the LTC sector, which is itself associated with higher risk of ‘drop out’. • The non-hospital sectors are affected disproportionately by nursing departures • Policies designed to curb the loss of nurses to the profession must be sector specific. • Higher departure rates among younger nurses suggest that shortages may be perpetuated into the future. • Factors that affect retention in the profession are not the same as those that determine retention in a sector.

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