| Literature DB >> 28298225 |
Giuliano Russo1,2, Carlos André Pires3, Julian Perelman4, Luzia Gonçalves5,6, Pedro Pita Barros7.
Abstract
BACKGROUND: Evidence is accumulating on the impact of the recent economic crisis on health and health systems across Europe. However, little is known about the effect this is having on physicians - a crucial resource for the delivery of healthcare services. This paper explores the adaptation to the crisis of public sector physicians and their ability to keep performing their functions, with the objective of gaining a better understanding of health workers' resilience under deteriorating conditions.Entities:
Keywords: Health services Portugal; Health services economic crisis; Physicians and economic crisis; Physicians resilience and coping strategies; Portugal’s healthcare system
Mesh:
Year: 2017 PMID: 28298225 PMCID: PMC5353948 DOI: 10.1186/s12913-017-2151-1
Source DB: PubMed Journal: BMC Health Serv Res ISSN: 1472-6963 Impact factor: 2.655
Estimates of the logistic model for intention to migrate (N=385)
| Independent variables | Model 1 | Model 2 | ||
|---|---|---|---|---|
| B (se) |
| B (se) |
| |
| Age | −0.069 (0.018) | <0.001 | −0.047 (0.021) | 0.025 |
| Gender (Female) | −0.723 (0.321) | 0.024 | −0.310 (0.383) | 0.419 |
| Civil status (Married/partnership) | ||||
| Single | −0.130 (0.431) | 0.762 | 0.182 (0.517) | 0.724 |
| Divorced | 2.719 (0.557) | < 0.001 | 2.651 (0.656) | < 0.001 |
| Nationality (Other) | 1.799 (0.701) | 0.010 | 2.133 (0.846) | 0.012 |
| Dependents (Yes) | −1.081 (0.443) | 0.015 | −0.441 (0.528) | 0.404 |
| Working hours 2015 (hours/week) | 0.030 (0.011) | 0.004 | 0.019 (0.012) | 0.124 |
| Leisure time 2015 (log (hours/week)) | −0.482 (0.209) | 0.021 | −0.440 (0.252) | 0.081 |
| Health policies that damage public sector | – | – | 0.402 (0.146) | 0.006 |
| Brain Drain | – | – | 0.308 (0.117) | 0.009 |
| Enjoyment of the current working environment | – | – | −0.196 (0.068) | 0.004 |
| Current conditions of my current job | – | – | −0.153 (0.091) | 0.092 |
| Difficulty of finding a job abroad | – | – | −0.155 (0.081) | 0.055 |
| Family ties in Portugal | – | – | −0.126 (0.052) | 0.015 |
Sample characteristics, by healthcare unit
| Total ( | Healthcare units | |||
|---|---|---|---|---|
| Characteristics | HSJ ( | ACES Cascais ( | ACES Amadora ( | |
| Age (Median, IQR) | 43.00 (31–57) | 42.00 (30–55) | 47.00 (33–58) | 43.00 (32–58) |
| Gender (M) n(%) | 208 (43.0%) | 160 (53.0%) | 23 (24.0%) | 25 (29.1%) |
| Married (Y) | 260 (53.7%) | 155 (51.3%) | 54 (56.3%) | 51 (59.3%) |
| Nationality (Pt) | 473 (97.7%) | 298 (98.7%) | 92 (95.8%) | 83 (96.5%) |
| Other physician in family (Y) | 246 (50.8%) | 157 (52.0%) | 42 (43.8%) | 47 (54.7%) |
| Dependents (Y) | 227 (46.9%) | 139 (46.0%) | 47 (49.0%) | 41 (47.7%) |
| Years as Medical Doctor | 18.45 (12.98) | 18.04 (12.98) | 19.60 (12.62) | 18.59 (13.43) |
| Private sector practice (Y) | 185 (38.3%) | 138 (45.8%) | 26 (27.1%) | 21 (24.4%) |
| Junior medical residents | 10 (2.1%) | 10 (3.3%) | 0 (0.0%) | 0 (0.0%) |
| Senior medical residents | 132 (27.3%) | 92 (30.5%) | 17 (17.7%) | 23 (26.7%) |
| Clinicians (no spec.) | 6 (1.2%) | 1 (0.3%) | 3 (3.1%) | 2 (2.3%) |
| Auxiliary assistant | 142 (29.3%) | 80 (26.5%) | 36 (37.5%) | 26 (30.2%) |
| Graduate assistant | 147 (30.4%) | 87 (28.8%) | 32 (33.3%) | 28 (32.6%) |
| Senior graduate assistant | 47 (9.7%) | 32 (10.6%) | 8 (8.3%) | 7 (8.1%) |
| Total weekly working hours (2015): Mean (SD) | 52.00 (13.07) | 55.85 (14.22) | 46.70 (8.55) | 44.97 (6.73) |
| Public weekly working hours (2015): Mean (SD) | 45.64 (11.26) | 47.53 (13.09) | 42.85 (6.61) | 42.29 (5.94) |
| Weekly Leisure Time (2015) Mean (SD) | 15.85 (12.12) | 16.12 (12.82) | 15.71 (11.05) | 15.08 (10.75) |
| Total yearly earnings (2015) (1000*Euros): Mean (SD) | 33,611 (21,020) | 36,347 (24,539) | 30,435 (13,591) | 27,998 (11,415) |
IQR interquartile range; Qualitative variables characterized as n(%)
Fig. 1Working hours and earnings before and after the crisis, per type of physician (means)
Fig. 2Constructed variable of differences in hours worked in public between 2010 and 2015
Estimates of the ordinal model for change in the number of public sector working hours (N=328)
| Independent variables | Model 1 | Model 2 | ||
|---|---|---|---|---|
| B (se) |
| B (se) |
| |
| Type of HCU | ||||
| Other (USF Modelo A + UCSP + USP) | – | – | – | – |
| Hospital | −1.041 (0.244) | <0.001 | −0.910 (0.259) | <0.001 |
| USF Modelo B ( | 0.686 (0.580) | 0.237 | 1.056 (0.654) | 0.106 |
| Age (years) | −0.031 (0.010) | 0.001 | −0.035 (0.010) | 0.001 |
| Private+other working hours 2015 (hours/week) | −0.024 (0.011) | 0.025 | −0.018 (0.012) | 0.131 |
| Valuation of job flexibility and independence | – | – | −0.112 (0.039) | 0.004 |
| Valuation of extra work in public (e.g.,. emergency shifts) | – | – | 0.081 (0.046) | 0.079 |
| Valuation of enjoying of the current working environment | – | – | 0.084 (0.046) | 0.067 |
| Not wanting to disrupt service in my job | – | – | 0.077 (0.034) | 0.023 |