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Table 4 Relationships between well-being and patient safety

From: Integrating teamwork, clinician occupational well-being and patient safety – development of a conceptual framework based on a systematic review

Study

Topic

Primary topic

Sample & setting

Design & data collection methods

Assessment of variables

Analyses

Findings

Outcomes & effect sizes

Quality scored

Arakawa et al., 2011 [98]

Relationships between nurses’ work, health, and lifestyle characteristics and medical errors and incidents

yes

6445 nurses, 99 hospitals, Japan

Cross sectional self-report questionnaire

Well-being: SF-36 scales mental health and vitalitya

Patient safety: Number of incidents and errors during the previous 6 months

Logistic regression

No association between

1) mental health

2) vitality

and medical errors and incidents

1) NS

2) NS

9 (16)

Arimura et al., 2010 [99]

Relationships between work characteristics, sleepiness, mental health state and self-reported medical errors

yes

454 nurses, 2 general hospitals, Japan

Cross sectional self- report questionnaire

Well-being: GHQ-28a, daytime sleepiness (Epworth sleepiness scale)

Patient safety: medical errors during past month

Multiple logistic regression

1) Poorer mental health is associated with higher occurrence of medical errors

2) Daytime sleepiness is not associated with higher occurrence of medical errors

1) OR = 1.1, p < 0.05, 95 % CI 1.0 – 1.1

2) NS

(8 predictors altogether)

105 (16)

Chen et al., 2013 [114]

Relationships between burnout, job satisfaction and medical malpractice

yes

809 physicians, Taiwan

Cross-sectional self-report questionnaire

Well-being: MBIa

Patient safety: experiences of medical malpractice

Univariate logistic regression

1) Emotional exhaustion is associated with higher risk of medical malpractice, whereas

2) depersonalization and

3) personal accomplishment are associated with lower risk of medical malpractice

1) OR = 1.50, 95 % CI 0.68 –1.95

2) OR = 0.74, 95 % CI 0.40 –1.36

3) OR = 0.76, 95 % CI 0.07 –1.05

6 (16)

Cimiotti et al., 2012 [104]

Relationships between nurse staffing, burnout, and hospital infections

yes

7076 nurses, 161 hospitals, USA

Cross-sectional self-report questionnaire,

hospital records

Well-being: MBIa

Patient safety: catheter-associated urinary tract & surgical site infections

Linear regression

Burnout is positively associated

1) catheter-associated urinary tract and

2) surgical site infections

1) β = 0.82, p < .05

2) β = 1.56, p < .01

10.5 (16)

Fahrenkopf et al., 2008 [106]

Relationships between depression, burnout, and medication errors

yes

123 residents, 3 pediatric hospitals, USA

Cross-sectional self-report questionnaire, record review

Well-being: MBIa

Patient safety: medical errors (self-report & chart reviews)

Cluster adj. Poisson analysis,

Fisher’s exact test

1) Burnt out residents perceive their number of errors to be higher than residents who are not burnt out

2) Burnt out residents are more likely to attribute errors to sleep deprivation

3) No significant differences in error rates detected in chart reviews between both groups

1) Mhigh burnout = 2.3, Mlow burnout = 1.0, p = 0.002

2) 29 % vs. 10 %, p = 0.05

3) NS

[]b

8 (16)

Garrouste-Orgeas et al., 2015 [116]

Relationships between medical errors, burnout, depression, and safety culture

yes

1534 nurses, physicians, & other healthcare staff, 31 ICUs, France

Cross-sectional self-report questionnaire,

hospital records and observations

Well-being: MBIa

Patient safety: Medical error

Negative binomial regression

Burnout is not associated with medical error

NS

10.5 (15)

Halbesleben et al., 2008 [22]

Relationships between nurse burnout and patient safety perceptions/reporting behavior

yes

148 nurses, 1 hospital, USA

Cross sectional self- report questionnaire

Well-being: Emotional Exhaustion and Depersonalizationa

Patient safety: AHRQ Patient Safety Culture Surveya & frequency of incident reports

Multiple linear regression

1) Emotional exhaustion and depersonalization predict patient safety dimensions

a) safety grade

b) safety perception

c) near-miss reporting frequency

2a) Emotional exhaustion and b) depersonalization do not predict patient safety dimension event reports

1a) βexhaustion = −0.40, p < 0.01,

βdepersonlization = −0.16, p < 0.05, R2 = 0.22, [f2 = 0.28]b,c

1b) βexhaustion = −0.84, p < 0.001, βdepersonlization = −0.26, p < 0.05, R2 = 0.36, [f2 = 0.56]b, c

1c) βexhaustion = −0.14, p < 0.05,

βdepersonlization = −0.36, p < 0.01, R2 = 0.18, [f2 = 0.22]b, c

2a) NS

2b) NS

13.5 (16)

Halbesleben & Rathert, 2008 [107]

Relationship between physician burnout and patient satisfaction and patient recovery time after hospital discharge

yes

178 patient and physician dyads, 1 hospital, USA

Cross-sectional self- report questionnaire

Well-being: MBIa, patients’ perception of physician depersonlization

Patient safety: recovery time: 1-item patient self-report

Path analysis,

Pearson’s correlation

1) Good overall model fit

2) Positive correlation between patient recovery time and a) depersonalization

b) but not emotional exhaustion

c) or personal accomplishment

3) Positive correlation between patients’ perception of physician depersonalization and recovery time

4) No correlation between physician emotional exhaustion and recovery time

1) GFI = 0.99, CFI = 1.00, NNFI = 1.02, AIC = −2.98, BIC = −8.45, RMSEA = 0.00

2a) r = 0.44, p < 0.05

2b) NS

2c) NS

3) r = 0.32, p < 0.05

4) NS

12 (16)

Hayashino et al., 2012 [108]

Hope moderates relationship between distress and medical errors

yes

836 physicians, Japan

Longitudinal self-report questionnaire

Well-being: MBIa (time 1)

Medical errors: self-report (time 2)

Poisson regression

High scores in

1) emotional exhaustion

2) depersonalization

and low scores in

3) personal accomplishment

at time 1 are associated with medical errors at time 2

1) IRR = 2.34, p < 0.0001

2) IRR = 2.72, p < 0.0001

3) IRR = 0.62, p = 0.001

9.5 (16)

Hunziker et al., 2012 [109]

Influence of self-reported, biochemical and physiological stress on cardio-pulmonary resuscitation (CPR) performance

yes

28 residents, teaching hospital, Switzerland

Self-report questionnaire, video observation of simulated resuscitation

Well-being: Stress/overload index (self-report; blood cortisol, heart rate)

Patient safety: performance (time until CPR is started and hands-on time)

Multiple linear regression

1) Stress/overload is positively associated with

a) time to start CPR

b) but not hands-on-time during resuscitation

2) Heart rate is positively associated with

a) hands-on-time

b) and negatively with time to start CPR during resuscitation

3a) Cortisol level and

b) heart rate variability

do not predict

c) hands-on-time and

d) time to start CPR

4) The difference of

a) stress/overload

b) cortisol level

c) heart rate variability before to during resuscitation

do not predict

d) hands-on-time or

e) time to start CPR

5) The difference of heart rate before to during resuscitation predicts

a) hands-on-time and

b) time to start CPR

1a) β/B = 12.01, 95 % CI 0.65 – 23.36, p = 0.04

1b) NS

2a) β/B = 2.22, 95 % CI 0.53 – 3.92, p = 0.015

2b) β/B = −0.78, 95 % CI 1.44 to −0.11, p = 0.027

3 ac) NS

3ad) NS

3bc) NS

3bd) NS

4ad) NS

4ae) NS

4bd) NS

4be) NS

4 cd) NS

4ce) NS

5a) β/B = 2.73, 95 % CI 0.48 – 4.99, p = 0.022

5b) β/B = −1.12, 95 % CI −1.91 to −0.33, p = 0.01

(no information regarding standardization of coefficients)

12.5 (15)

Jones et al., 2012 [100]

Effect of incident seriousness and work-based support on negative positive affect

yes

171 nurses, 4 hospitals, UK

Cross-sectional & longitudinal between & within-person design, diary study

Well-being: Positive & Negative Affect Scale (PANAS) and mood diary entriesa

Patient safety: nurse-reported incidents

Random-effects multilevel model

1) Interaction of incident occurrence and seriousness leads to elevated negative affect during remainder of shift

2a) Incident occurrence

2b) but not incident seriousness

lead to reduced positive affect during remainder of shift

1) β = 0.07, z = 3.5, p < 0.005

2a) β = −2.39, z = 1.99, p < 0.05

2b) NS

13 (16)

Kirwan et al., 2013 [105]

Relationships between working environment, burnout and patient safety

no

1397 nurses, 108 wards, 30 hospitals, Ireland

Cross-sectional self-report questionnaire

Well-being: MBIa

Patient safety: one item from AHRQa, adverse events

Multilevel regression

Emotional exhaustion on ward level does not predict

1) nurse-rated patient safety or

2) reporting of adverse events

1) NS

2) NS

12.5 (16)

Klein et al., 2010 [110]

Relationship between burnout and self-reported quality of care

yes

1311 surgeons, 489 hospitals, Germany

Cross sectional self- report questionnaire

Well-being: Copenhagen Burnout Inventory (CBIa)

Patient safety: Quality of care: frequency of diagnostic and therapeutic errors (Chirurgisches Qualitätssiegel survey CQS)

Multivariate logistic regression

1) Burnout is associated with

1a) lower quality of diagnosis/therapy

1b) more diagnostic errors

1c) more therapeutic errors among males

2) Unclear association of burnout with

2a) lower quality of diagnosis/therapy

2b) more diagnostic errors

2c) more therapeutic errors

among females

1a) OR = 1.71, 95 % CI 1.10 – 2.64

1b) OR = 1.94, 95 % CI 1.35 – 2.79

1c) OR = 2.56, 95 % CI 1.66 – 3.96

2a-c) contradictory information regarding significance in text and table

10.5 (16)

Maiden et al., 2011 [101]

Relationship between moral distress, compassion fatigue, and causes of medication errors

yes

205 nurses, ICU, USA

Cross sectional self-report questionnaire, focus group

Well-being: Moral distress scalea

Compassion fatigue: Professional Quality of Life Scalea

Patient safety: Medication Administration Error Surveya

Pearson’s correlation

1) Positive correlation between moral distress and

a) transcription related medication errors and

b) physician communication related medication errors

c) but not with medication packaging

d) pharmacy processes

2) Compassion fatigue is positively correlated with

a) transcription related medication errors

but not with medication error due to

b) physician communication

c) medication packaging

d) pharmacy processes

1a) r = 0.20, p = 0.05

1b) r = 0.24, p = 0.01

1c) NS

1d) NS

2a) r = 0.15, p = 0.05

2b) NS

2c) NS

2d) NS

9 (16)

Merlani et al., 2011 [13]

Relationships between hospital, patient, and clinician characteristics and burnout/stress

yes

3052 physicians, nurses, and nurse-assistants, 74 ICUs, Switzerland

Cross-sectional self-report questionnaire, record review

Well-being: MBIa, 1 stress item

Patient safety: mortality rates and length of stay (unit records)

Multivariate logistic regression

1) Mortality is associated with higher level of burnout

2) Length of stay is not associated with burnout

1) OR = 1.060, p = 0.04, 95 % CI 1.003 – 1.120

2) NS

12.5 (16)

Prins et al., 2009 [97]

Relationships between self-reported errors, burnout, and engagement

yes

2115 residents, The Netherlands

Cross-sectional self- report questionnaire

Well-being: Utrecht Burnout Scale (UBOS)a, Utrecht Work Engagement Scale (UWES)a

Patient safety: medical errors

Pearson’s correlation

1) Errors due to wrong actions/inexperience

a) are positively correlated with emotional exhaustion

b) depersonalization

c) and negatively correlated with personal accomplishment

2) Errors due to wrong actions/inexperience are not correlated with

d) vigor

e) dedication

f) absorption

3) Errors due to lack of time

a) are positively correlated with emotional exhaustion

b) depersonalization

c) and negatively correlated with personal accomplishment

4) Errors due to lack of time are negatively correlated with

a) vigor

b) dedication

c) absorption

1a) r = 0.20, p < 0.001

1b) r = 0.29, p < 0.001

1c) r = −0.05, p < 0.001

2a) NS

2b) NS

2c) NS

3a) r = 0.43, p < 0.001

3b) r = 0.42, p < 0.001

3c) r = −0.08, p < 0.001

4a) r = −0.23, p < 0.001

4b) r = −0.24, p < 0.001

4c) r = −0.11, p < 0.001

10.5 (16)

Ramanujam et al., 2008 [102]

Relationship between nurses’ work characteristics, burnout, and patient safety

yes

430 nurses, 2 hospitals, USA

Cross sectional self- report questionnaire

Well-being: Not described, although it can be deducted from the paper that the MBIa was used

Patient safety: nurses’ safety perception

Path analysis

1) Unsatisfactory initial model fit statistics, final model statistics not reported

2) Positive association between depersonalization and perceived patient safety

3) No association between emotional exhaustion and perceived patient safety

1) χ2 = 1100.60, df = 455, χ2/df = 2.419, CFI = 0.876, RMSEA = 0.058

2) β = 0.189, p < 0.001

3) NS

8.5 (16)

Shanafelt et al., 2002 [112]

Prevalence of burnout in medical residents and the relationship to self-reported patient care practices

yes

115 internal medicine residents, USA

Cross sectional self- report questionnaire

Well-being: MBIa

Patient safety: self-developed patient care practices measure

Stepwise logistic regression

1) Overall burnout score is associated with higher levels of

a) monthly

b) weekly suboptimal patient care practices

2) Depersonalization is associated with higher levels of

a) monthly

b) weekly suboptimal patient care practices

3) No associations between

a) emotional exhaustion

b) personal accomplishment and

c) monthly

d) weekly suboptimal patient care practices

1a) OR = 8.3, p < 0.001, 95 % CI 2.6 – 26.5

1b) OR = 4.0, p = 0.036, 95 % CI 1.1 – 14.2

2a) OR = 5.8, p < 0.001, 95 % CI 2.2 – 15.4

2b) OR = 2.8, p = 0.041, 95 % CI 1.1 – 7.7

3 ac) NS

3ad) NS

3bc) NS

3bd) NS

10.5 (16)

Shanafelt et al., 2010 [111]

Relationship between burnout, quality of life, depression and perceived major medical errors

yes

7905 surgeons, USA

Cross sectional self- report questionnaire

Well-being: MBIa

Patient safety: medical errors

Logistic regression

1a) Emotional exhaustion and

b) depersonalization

are associated with higher odds of reporting an error

2) Personal accomplishment is associated with lower odds of reporting an error

1a) OR = 1.048, p < 0.0001, 95 % CI 1.042 – 1.055

1b) OR = 1.109, p < 0.0001, 95 % CI 1.096 – 1.122

2) OR = 0.965, p < 0.0001, 95 % CI 0.955 – 0.975

9 (16)

Squires et al., 2010 [103]

Relationships between nurse leadership, work environment, safety climate, and nurse and patient outcomes

no

600 acute care nurses, USA

Cross sectional self- report questionnaire

Well-being: Emotional Exhaustiona

Patient safety: medication errors and ulcers

Path analysis

1) Very good final model fit

2) No association between pressure ulcers and emotional exhaustion

3) Positive association between medication errors and emotional exhaustion

1) χ2 = 217.6, p < 0.001, SRMR = 0.054, CFI = 0.947, RMSEA = 0.047, PCLOSE = 0.67

2) NS

3) β = 0.14, p < 0.05

12 (16)

Teng et al., 2010 [14]

Interactions between time pressure and burnout on patient safety

yes

458 nurses, 90 units, 2 medical centers, Taiwan

Cross sectional self- report questionnaire

Well-being: MBIa

Patient safety: frequency of adverse events scale

Multiple linear regression

1) Burnout negatively predicts patient safety

2) The interaction of burnout and time pressure negatively predict adverse events

1) β = −0.25, p = 0.00

2) β = −0.08, p = 0.03

R2 = 0.06

[f2 = 0.06]b, c (7 predictors altogether)

13 (16)

Welp et al., 2015 [117]

Relationships between burnout, demographic and unit characteristics, and patient safety

yes

1425 nurses and physicians, 54 intensive care units, Switzerland

Cross-sectional self-report questionnaire,

hospital records

Well-being: MBIa

Patient safety: standardized mortality ratios, length of stay, clinician-rated patient safety

Hierarchical (multilevel) linear regression

1a) Emotional exhaustion and

1b) depersonalization are negatively associated with clinician-rated patient safety;

c) personal accomplishment is positively associated with clinician-rated patient safety

2a) Emotional exhaustion, but not

2b) depersonalization or

2c) personal accomplishment is positively associated with standardized mortality ratios

3a) Emotional exhaustion,

3b) depersonalization, and

3c) personal accomplishment are not associated with length of stay

1a) B = −0.13, p < .001

1b) B = −0.07, p < .05

1c) B = 0.16, p < .01

2a) β = 0.39, p < .05

2b) NS

2c) NS

3a) NS

2b) NS

2c) NS

15 (16)

West et al., 2006 [113]

Relationships between distress, quality of life and medical errors

yes

184 internal medicine residents, teaching hospital, USA

Longitudinal cohort study,

self-report questionnaire

Well-being: MBIa, fatigue and sleepiness: 2 items

Patient safety: medical errors

Generalized estimation equations (GEE)

1) Higher levels of

a) emotional exhaustion

b) depersonalization are associated with major medical errors in the

c) previous

d) following 3 months

2) Lower levels of personal accomplishment are associated with higher levels of major medical error in the

a) previous

b) following 3 months

1 ac) PE = 4.58, p = 0.002

1bc) PE = 2.45, p = 0.002

1ad) OR = 1.07, p = < 0.001, 95 % CI 1.03 – 1.12

1bd) OR = 1.10, p = 0.001, 95 % CI 1.04 – 1.16

2a) PE = −2.59, p = 0.002

2b) OR = 0.93, p = 0.02, 95 % CI 0.88 – 0.99

12 (16)

West et al., 2009 [23]

Relationships between fatigue, distress, and medical errors

yes

380 internal medicine residents, teaching hospital, USA

Longitudinal cohort study, self-report questionnaire

Well-being: MBIa, fatigue and sleepiness: 2 items

Patient safety: medical errors

Generalized estimation equations (GEE)

Higher levels of

1) sleepiness

2) fatigue

3) emotional exhaustion

4) depersonalization and

5) lower levels of personal accomplishment

are associated with subsequent medical errors

1) OR = 1.10, p = 0.002, 95 % CI 1.03 – 1.16

2) OR = 1.14, p < 0.001, 95 % CI 1.08 – 1.21

3) OR = 1.06, p < 0.001, 95 % CI 1.04 – 1.08

4) OR = 1.09, p < 0.001, 95 % CI 1.05 – 1.12

5) OR = 0.94, p < 0.001, 95 % CI 0.92 – 0.97

13 (16)

Wetzel et al., 2010 [115]

Relationships between stress and surgical performance

yes

30 surgeons, 1 hospital, UK

Cross-sectional self-report questionnaire,

observation of simulated operations

Well-being: State-Trait Anxiety Inventory (STAI)a, heart rate, cortisol, oberver rating

Patient safety: OTASa, End Product Assessment Rating Scale (EPA)

Linear regression

Non-crisis simulation:

No relationship between

1) STAI

2) heart rate

3) cortisol

4) observer stress rating

and

a) OTAS

b) EPA

Crisis simulation:

5) no results reported on relationships between the above variables

6) Interaction between low experience and “stress” (not clear how variable was calculated) predicts lower

a) EPA and

b) OTAS

1a) NS

1b) NS

2a) NS

2b) NS

3a) NS

3b) NS

4a) NS

4b) NS

5) N/A

6a) β = .54, p < .01

6b) β = .65, p < .001

10 (15)

  1. We report not only significant but also non-significant relationships between predictor and outcome variables of interest in this review as hypothesized in the reviewed studies; even if not explicitly stated in the original publication
  2. avalidated instrument
  3. beffect sizes calculated by authors, calculation not possible if brackets empty
  4. cCohen’sƒ2 based on R2 instead of ΔR2
  5. din brackets: maximal possible score