Beskæftigelsesudvalget 2023-24, Sundhedsudvalget 2023-24
BEU Alm.del Bilag 234, SUU Alm.del Bilag 368
Offentligt
2895902_0001.png
Prætorius et al.
BMC Health Services Research
https://doi.org/10.1186/s12913-024-11234-2
(2024) 24:816
BMC Health Services Research
RESEARCH
Open Access
Impact of decentralized management
on sickness absence in hospitals: a two-wave
cohort study of frontline managers in Danish
hospital wards
Thim Prætorius
1*
, Thomas Clausen
2
, Ann Dyreborg Larsen
2
, Jonas Kirchheiner Rasmussen
2
,
Lykke Margot Ricard
3
and Peter Hasle
3
Abstract
Background
This study explores the impact of decentralized management on the sickness absence among health-
care professionals. Sickness absence is a reliable indicator of employees’ wellbeing and it is linked to management
quality. However, the influence of decentralized management on sickness absence has not been adequately studied.
Methods
The research design combined a two-wave, web-survey of frontline managers in two Danish university
hospitals with administrative data on sickness absence at the ward-level. The first and second wave included data
from 163165 and 137 frontline managers linked to 121 wards and 108 wards. Data was analysed using an ordinal
logistic regression model.
Results
Wards where frontline managers had the highest level of decentralised decision authority compared to none
showed lower odds of ward-level sickness absence (OR
crude
: 0.20, 95% CI: 0.05–0.87). A very high extent of cross-func-
tional decision authority showed lower odds of sickness absence (OR
crude
: 0.08, 95% CI: 0.01–0.49). Overall, the results
showed a clear data trend, although not all results were statistically significant.
Conclusion
Higher levels of decentralized management in wards were positively associated with lower risks
of sickness absence in hospital wards. The study supports future research on how to empower decision autonomy
at the frontline level of management.
Keywords
Decentralised decision authority, Cross-functional decision authority, Decision making, Sickness absence,
Hospitals, Frontline managers
Introduction
Background
*Correspondence:
Thim Prætorius
[email protected]
1
Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus,
Denmark
2
National Research Center for the Working Environment, Copenhagen,
Denmark
3
Department of Technology and Innovation, University of Southern
Denmark, Odense, Denmark
Sickness absence among healthcare staff is high on the
political agenda in the OECD countries. More than ever,
public hospitals face high care demands and with a short-
age of healthcare professionals there is an urgent need
for developing knowledge on how to manage and organ-
ize healthcare work to avoid burnout, absenteeism, and
stabilize retention rates [1–4]. This article contributes to
this discussion by studying the impact of decentralizing
© The Author(s) 2024.
Open Access
This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the
original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or
other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this
licence, visit
http://creativecommons.org/licenses/by/4.0/.
The Creative Commons Public Domain Dedication waiver (http://creativecom-
mons.org/publicdomain/zero/1.0/)
applies to the data made available in this article, unless otherwise stated in a credit line to the data.
SUU, Alm.del - 2023-24 - Bilag 368: Orientering om betydningen af decentral og tværfaglig ledelse for sygefravær på sygehuse, fra beskæftigelsesministeren
Prætorius et al.
BMC Health Services Research
(2024) 24:816
Page 2 of 13
management on ward-level sickness absence. Decentrali-
zation to frontline managers in hospitals is a particularly
important level to zoom in on because managers at the
frontline are directly involved in helping work teams
accomplish collective objectives, and the way manag-
ers manage is linked to the psychosocial work environ-
ment and well-being of healthcare professionals [5–10],
impacting the service performance of hospitals [11,
12].
Managers who give frontline workers adequate resources
and encouragement are also found to strengthen workers’
skill sets who in turn make better decisions [13].
This study adopts the perspective that empowered
frontline managers are fundamental to hospital perfor-
mance [14–16]. To explore this impact further, studies
into enabling management structures [17,
18]
point to
two compelling management aspects related to decen-
tralization. First, delegating decentralization of deci-
sion-making authority to frontline managers [19] is
hypothesized to improve decision-making and collabora-
tion at the frontline of care delivery [20]. Second, man-
agers with cross-functional decision authority can span
and connect across occupational boundaries [21] and is
considered a mechanism for bridging healthcare profes-
sionals and units [22].
Aim and contribution
Compared to previous studies primarily surveying nurse
managers, our study sample consists of nurses and phy-
sicians who jointly undertake the role of frontline man-
agers, exemplifying a recent trend in clinical leadership
models [25]. Second, by investigating decentralized deci-
sion authority and cross-functional decision authority,
we operationalize important elements of complex work
organizations, such as hospitals, where the need for agile
decision making processes are important to facilitate
efficient and high-quality delivery of health care services
involving employees with different professional back-
grounds. The study differs from previous studies on hos-
pital managers focusing on performance management [8]
or specific leadership styles [12] such as distributed [14,
16]
or relation-oriented leadership [5,
26].
Third, we con-
tribute insights complementing research on psychosocial
working conditions (e.g., high workload and low levels
of social capital, job control, and organizational justice)
found to be predictors of sickness absence [27–31]. We
use sickness absence as an outcome measure because it
may be considered an objective and reliable indicator of
employees’ well-being and their work environment [7].
Hypothesis development
The overall purpose of this explorative study is to evalu-
ate the association between decentralized management
in hospitals and sickness absence among healthcare
professionals. We break the concept of decentralized
management into vertical decision authority (who make
decisions about what in the hospital) [19] and cross-func-
tional decision authority (who make decisions outside
their own occupation in the hospital) [17]. By investigat-
ing these two aspects of the managerial role, we analyse
whether a) the level of decentral decision authority and
b) the ability of managers to coordinate task comple-
tion across different job functions is associated with
employee-well-being. These two management aspects
have not been adequately considered nor linked to how
it can improve the work environment in hospitals [23]
and lead to a sustainable psychosocial work environment
[24].
The contribution of the present study is threefold.
First, by deploying an innovative study design using
self-reported questionnaire data from line-managers
combined with register-based information on sickness
absence at the ward-level, we provide novel evidence
on the association between leadership behaviour and
employee well-being and heed the call for performing
rigorous empirical research on the impact of manage-
ment at a time where healthcare systems reorganize to
meet changing demographics and patient demands [12].
Centralization refers to a situation where decision-
making power rests with a central person or team in the
center or at the top of the organizational hierarchy [32].
In contrast, decentralization means that the decision-
making power is delegated to frontline managers or
employees within an organization, and organizations do
it because of the potential it has for improving operations
and task completion [33,
34].
A high level of decentrali-
zation allows employees to make decisions on their own
and empower their autonomy. Organizations delegate
decision authority because there is a limit to how many
people a manager can effectively manage, and delega-
tion can improve decision quality, economise on mana-
gerial attention, and facilitate employee initiative. From
the viewpoint of a manager, delegation also means los-
ing control over delegated decisions that for some can
be challenging to deal with [19,
35, 36].
Moving decision
authority to the frontline manager in hospitals enhance
the room for exercising supportive and flexible leader-
ship behaviours that can meet employees’ specific needs
and situational demands [14,
16].
Delegating decision-
making to the frontline manager also enhances a more
enabling management structure by offering employees
access to information, resources, and opportunities to
influence decisions [1]. Employees are more likely to feel
empowered with adequate discretionary power (needed
as to do their job) with a positive effect on the well-being
of employees working at the frontline. Decentralisation
of decision authority is also attributed to a reduction
SUU, Alm.del - 2023-24 - Bilag 368: Orientering om betydningen af decentral og tværfaglig ledelse for sygefravær på sygehuse, fra beskæftigelsesministeren
Prætorius et al.
BMC Health Services Research
(2024) 24:816
Page 3 of 13
in the risk of numbers of sick days due to a decrease in
job burnout and increase in job satisfaction [24,
29].
We hypothesize that delegation of decision authority
may be associated with lower levels of sickness absence
at the ward level for several reasons. First, delegation
of decision authority may boost job resources – e.g. job
autonomy and supportive leadership behaviours – and
the availability of these job resources may enhance the
possibilities of health care workers to deal with the job
tasks while simultaneously supporting the work-related
well-being of health care workers through higher levels of
work engagement and lower levels of burnout [37]. Sec-
ond, following the meta-analysis from Miraglia and Johns
[38], higher levels of leadership support and job control
are associated with higher levels of job satisfaction and
lower levels of sickness absence. Our first hypothesis can
therefore be formulated as follows:
H1: Decentralization of decision authority in hos-
pitals is associated with a reduced risk of sickness
absence at the ward-level.
Since hospitals are characterized by strong professional
cultures and high specialization, many contextual factors
work against managing across organizational and occu-
pational boundaries [39,
40].
However, increasingly com-
plex care processes and patients’ need for integrated care
makes it critical that frontline managers in hospitals are
capable of supporting collaboration across occupational
boundaries [41,
42].
This development emphasizes a need
for managers who can bridge silos and create linkages
between occupations and groups to move ideas, infor-
mation, people and resources to where they are needed
[17]. A decision-making perspective on the phenomenon
of managing across occupational boundaries can be cap-
tured by the concept of cross-functional decision author-
ity [43] concerned with the degree to which a manager in
a hospital makes decisions outside their own occupation
[12,
21, 44].
At the level of frontline management, cross-
functional decision authority is hypothesised to support
task completion and empower employees by providing
access to supervision, information and resources across
areas of specialisations [1], which is expected to be have
a positive effect on the level of sickness absence in their
wards [5,
7, 27].
Accordingly, we expect that higher levels
of cross-functional decision authority may enhance the
social capital at the ward-level by facilitating collabora-
tion between different professional groups and strength-
ening the social capital in the work-group. Higher levels
social capital at the ward-levels constitutes a job resource
[45] that is associated with a decreased risk of sickness
absence [27]. A meta-analysis [38] also indicates that
social capital in the workplace (i.e., support from co-
workers and supervisors) are indirectly associated with
sickness absence and that the association is mediated by
job satisfaction. Our second hypothesis can thus be for-
mulated as:
H2: Cross-functional decision authority in hospitals
is associated with a reduced risk of sickness absence
at the ward-level.
Methods
Study setting
The study was carried out in two Danish university hos-
pitals. Denmark has a universal, decentralized health sys-
tem, in which the national government provides block
grants from tax revenues to the regions, which operate
hospitals, and to local authorities that, e.g., deliver pre-
vention and rehabilitation services. Hospitals in Denmark
are mainly public, paid through global budgets and case-
based payments. Hospital physicians and nurses are sala-
ried and employed by regional hospitals. All residents are
entitled to publicly financed care, including largely free
primary, specialist, hospital, mental health, preventive,
and long-term care services. In Denmark, the hospital
sector is among the work sectors with the highest preva-
lence of sickness absence with a level of 5.1 percent of the
total working time. In 2019, assistant nurses and nurses
respectively had the highest and fifth highest prevalence
of sickness absence among all professional groups [46].
In Denmark, employees are eligible for sickness absence
benefits if they cannot work due to sickness. Employees
in hospitals owned by the Regional level of government
are entitled to full wages while sickness absent and the
employer is reimbursed by the Municipal level of govern-
ment after 30 days of sickness absence.
Study design and data collection
The target population for the survey was frontline man-
agers with staff responsibility because they manage the
wards where healthcare professionals provide patient
care. The research design consisted of a two-wave web-
survey that was developed for this study using insights
from management theory [12,
33, 44, 47]
(see Supple-
mentary file 1). Survey data was collected in two Danish
university hospitals in the Capital Region of Denmark
(anonymized as City Hospital 1 and City Hospital 2).
Based on a history of collaborating with the study team
on research projects, the executive management team
in the two hospitals granted access to collect the survey
data. To identify our target group, we obtained an admin-
istrative list of managing physicians and nurse managers
from the Capital Region of Denmark. In collaboration
with the two participating hospitals, we identified all
managers from units directly providing care: acute, elec-
tive, a combination or other. The final list was validated
SUU, Alm.del - 2023-24 - Bilag 368: Orientering om betydningen af decentral og tværfaglig ledelse for sygefravær på sygehuse, fra beskæftigelsesministeren
Prætorius et al.
BMC Health Services Research
(2024) 24:816
Page 4 of 13
by the human resource departments to ensure accuracy.
Some wards were managed by a team consisting of a
managing physician and nurse manager, meaning that
the number of managers participating in the survey can
exceed the number of wards. Data were collected from
frontline managers by use of their personal work email.
The first wave of data collection took place from
November 2018 to January 2019 and the second wave
from November 2019 to January 2020. To encourage par-
ticipation, a member of the executive hospital manage-
ment signed the survey invitation, which was distributed
electronically using SurveyXact. To increase the response
rate, three e-mail reminders were sent out in each wave.
Each invitation letter contained information about the
study, a unique survey link, and participation informa-
tion about data protection and anonymity. Participation
was voluntary. In the first wave of data collection, 369
frontline managers received the questionnaire with a
response rate of 58.3% (165 frontline managers). In the
second wave of data collection, 310 frontline managers
received the questionnaire with a response rate of 58.4%
(137 frontline managers). Across the two waves, the same
125 frontline managers responded to the questionnaire in
both. The sample is tied to 121 wards with 3,680 employ-
ees in the first wave and 108 wards with 3,331 employees
in wave two. Due to the low number of observations on
the independent variables, we analysed data from the two
waves independently to identify similarities in the pat-
terns of the results. The employees in the participating
wards were not invited to participate in the survey.
By combining the survey data with administrative
data on sickness absence, the wards represent the unit
of analysis. The first wave of the survey was merged with
register-based data on sickness absence in the 121 wards
from the period of January 2019 to December 2019. The
second wave of the survey was merged with register
based data on sickness absence in the 108 wards from
the period of January 2020 to December 2020. Data was
managed in accordance with GDPR guidelines.
Measures
The construct ‘Decentralization of decision authority’
included five items taken from previously used question-
naires [33,
47]
and reworded to fit the context of hospital
management: who has decision authority with regard to:
1) prioritizing projects at the department, 2) collabora-
tion with other departments at the hospital, 3) decisions
with regard to quality control, 4) significant changes in
patient service, and 5) significant changes in departmen-
tal routines. The response categories were as follows:
the decision authority lies with 1) employees under my
leadership, 2) myself (and co-managers), 3) my immedi-
ate supervisor, 4) the top management. We constructed
an additive index on decentralization of decision author-
ity by counting the number of items where the manager
responds that either the manager or the employees under
his/her supervision had the decision authority. The addi-
tive index ranged from 0–5, where 0 refers to no local
decision authority and the higher the number, the greater
the local decision authority. The internal consistency of
the measures was assessed via Cronbach alphas and lay
above the acceptable threshold of 0.70.
We measured the degree of exercising ‘cross-functional
decision authority’ – i.e., make decisions across functions
[12,
44]
– with the question ‘to what extent do you on a
daily basis exercise management for other occupational
groups than your own’. It was measured using a 5-point
Likert scale ranging from ‘not at all’ to ‘to a very great
extent’. This measure drew on the concept of boundary-
spanning leadership, and it was self-developed to meet
the research aim for which it was not possible to find a
suitable and pre-used questionnaire.
The survey data came from a larger questionnaire cov-
ering: respondent characteristics (e.g., profession and
management experience); management responsibilities
(e.g., operations); unit characteristics (e.g., type and size);
management team (e.g., composition and span of con-
trol) and coordination mechanisms (e.g., plans, rules and
roles).
The data on the outcome measure of sickness absence
at the ward-level was obtained from administrative data-
bases from the Capital Region of Denmark known to be
highly reliable and accurate and have limited issues of
biased or missing data [48]. To handle the different num-
ber of employees per ward, the annual number of absent
days was calculated against the expected annual work-
ing days at each ward, and finally categorized the ordinal
variable as: 1
=
less than 3% sickness absence, 2
=
3–6%
sickness absence, and 3
=
more than 6% sickness absence.
If we assume that the expected annual working days/year
are approx. 220, then less than 3% reflect 6,5 days of sick-
ness absence per year. By categorising sickness absence as
an ordinal variable, it was possible to use ordinal logistic
regression analysis, which allows for greater contrast in
sickness absence than can be obtained in standard logis-
tic regression models with only two outcomes. Further,
this type of analysis does not assume normality, linearity
or homoscedasticity, which are seldom obtainable with
data on sickness absence [49].
Covariates
Manager and hospital ward characteristics were included
as covariates because of their potential influence on lead-
ership, the work environment or sickness absence [50].
All covariates were included a priori, and then tested in
different models to see if they change the results. The
SUU, Alm.del - 2023-24 - Bilag 368: Orientering om betydningen af decentral og tværfaglig ledelse for sygefravær på sygehuse, fra beskæftigelsesministeren
Prætorius et al.
BMC Health Services Research
(2024) 24:816
Page 5 of 13
following covariates was utilised from the surveys: Man-
ager characteristics: sex (female, male, other, do not want
to inform); job category (doctor, nurse, other); manage-
ment training (yes/no); years of management experience
(numerical); number of employees working under their
management (1
=
0–9 employees, 2
=
10–14 employ-
ees, 3
=
15–24 employees, 4
=
more than 24 employees).
Hospital ward characteristic: performing acute care tasks
(yes/no); and hospital (1 or 2).
Statistical analysis
Descriptive analyses assessed the hospital and ward-level
according to characteristics of the hospitals and front-
line managers. The association between each of the two
structural aspects of cross-functional decision authority
and decentralization of decision authority and sickness
absence was analysed using multinomial logistic regres-
sion models. Because the ordinal response categories
have an order, we refer to this as ordinal logistic regres-
sion analysis [51]. This analytical approach models the
relationship between an ordinal response variable, in
this case sickness absence, and one or more explanatory
variables here the ‘cross-functional decision authority’
variable based on a 5-point Likert scale, and the ‘decen-
tralization of decision authority’ on an ordinal scale. The
ordinal logistic regression analyses were performed using
the PROC GENMOD procedure in SAS version 9.4 (SAS
Institute Inc., Cary, NC, USA).
To study the two hypotheses, we analysed the asso-
ciations between the following items and the sickness
absence data that we were granted access to:
The additive index on decentralized decision author-
ity and sickness absence measured as annual sickness
absence at ward-level in the year after the start of
data collection.
Decentralized decision authority single items and
sickness absence measured as annual sickness
absence at ward-level in the year after the start of
data collection to test if any of the single item are
more important than others.
Cross-functional decision authority single item and
sickness absence measured as annual absence at
ward-level in the year after the start of data collec-
tion.
We made the following adjustment in a total of four
models: hospital (model 1); model 1 plus managers’ job
category, management training and years of manage-
ment experience (model 2); model 2 plus span of control
(model 3); model 3 plus acute tasks (model 4).
The analyses were stratified by survey wave (1 or 2).
The two waves were treated separately due to differences
in both questionnaire responses and ward-level sickness
absence. Results from the same department were treated
as repeated measurements (repeated subject in the SAS
procedure PROC GENMOD), e.g., if the management is
shared between a managing physician and a nurse man-
ager. The overall level of statistical significance was set at
0.05.
The interpretation of the ordinal regression model is:
when the sickness absence scale is demarcated as 1 (= less
than 3% absence per year), 2 (= 3–6%absence per year)
and 3 (= more than 6% absence per year) then an OR of
0.40 means that the odds of “3” vs “1 or 2” are 60% lower
among the exposed group than in the reference group.
It also means that the odds of “2” vs “1” are 60% lower
among the exposed group than the reference group. The
assumption of the cumulative logistic regression is that
the odds ratio for being in category “3” vs “1 or 2” is the
same as the odds ratio for being in category “2” vs. “1”..
Validity and reliability
Prior to the first wave of the survey and to test its face
validity, the questionnaire was evaluated by and revised
according to the inputs from 10 frontline managers work-
ing in the two hospitals. Because the data on the decen-
tralization of decision authority and cross-functional
decision authority have been gathered as self-reported
survey data, they could be subject to recall-bias, but it is
difficult to obtain information on these variables in any
other way. Common method bias is a risk when correlat-
ing data in the same survey or between latent constructs
based on self-reported items and believed leadership
qualities. However, since we combine the self-reported
survey data (i.e., our predictor variables) with adminis-
trative data (i.e., sickness absence as the outcome variable
at the ward-level), these risks of common method bias
have been mitigated [52].
Results
Table 
1
shows the descriptive statistics for the variables
studied. The table is stratified by data wave and hos-
pital and shows that around 80% of the study popula-
tion of frontline managers were women (first wave 82%
(n
=
134) and second wave 79% (n
=
108)). The most pre-
dominant job type was nurse (64% (n
=
105) and 62%
(n
=
85)) followed by physician (25% (n
=
41) and 28%
(n
=
38)). On average, the managers had around twelve
years of management experience (11years (n
=
165) and
12 years (n
=
137)) and a high percentage had received
management training (89% (n
=
147) and 93% (n
=
127)).
The span of control varied from zero to more than 24
persons in both waves. Of the wards in the first and sec-
ond data wave, 18 and 16% performed acute tasks, 26
and 24% were primarily elective, and the remaining 58%
SUU, Alm.del - 2023-24 - Bilag 368: Orientering om betydningen af decentral og tværfaglig ledelse for sygefravær på sygehuse, fra beskæftigelsesministeren
2895902_0006.png
Table 1
Descriptive statistics for main study variables for the respondents in the first and second survey wave
2nd data wave
City Hospital 2
N
72
13
37
22
53
18
37
29
6
72
10.47 (8.24)
165
11.37 (8.32)
81
8.33
19
11.52
10
40.28
41
24.85
17
20.99
12.35
13.00 (8.75)
51.39
105
63.64
54
66.67
25.35
30
18.29
15
18.52
14
31
21
4
56
74.65
134
81.71
66
81.48
42
30.56
41
24.85
22
27.16
32
51.39
93
56.36
38
46.91
12
21.43
57.14
75.00
25.00
55.36
37.50
7.14
11.09 (6.99)
18.06
31
18.79
21
25.93
12
21.43
43.64
165
100
81
59.12
56
40.88
137
33
50
54
108
29
85
38
14
137
%/mean
(SD)
N
%/mean
(SD)
N
%/mean
(SD)
N
%/mean
(SD)
N
Total
City Hospital 1
City Hospital 2
Total
%/mean (SD)
100
24.09
36.50
39.42
78.83
21.17
62.04
27.74
10.22
12.22 (8.11)
1st data wave
City Hospital 1
%/mean
(SD)
56.36
19.35
60.22
20.43
87.10
12.90
73.12
12.90
13.98
12.06 (8.37)
N
Frontline managers
93
Prætorius et al.
BMC Health Services Research
Ward-level sickness absence %/year
< 3%
18
3–6%
56
> 6%
19
(2024) 24:816
Gender
Woman
81
Man
12
Job type
Nurse
68
Physician
12
Other
13
Management experi-
ence (years)
94.62
5.38
16.13
26.88
25.81
31.18
10.75
23.66
65.59
35
48.61
17
23.61
20
27.78
30
39
96
16
22.22
45
15
20.83
39
22
30.56
47
19
26.39
34
20.61
28.48
23.64
27.27
18.18
23.64
58.18
13
18.06
18
10.91
3
20
16
22
23
8
19
54
59
81.94
147
89.09
78
93
Management training
96.30
3.70
24.69
19.75
27.16
28.40
9.88
23.46
66.67
49
7
20
12
12
12
14
17
25
87.50
12.50
35.71
21.34
21.43
21.43
25.00
20.36
44.64
127
10
40
28
34
35
22
36
79
92.70
7.30
29.20
20.44
24.82
25.55
16.06
26.28
57.66
Page 6 of 13
Yes
88
No
5
Span of control (# employees)
0–9
15
10–14
25
15–24
24
> 24
29
Care task type
Acute
10
Elective
22
Both or others
61
SUU, Alm.del - 2023-24 - Bilag 368: Orientering om betydningen af decentral og tværfaglig ledelse for sygefravær på sygehuse, fra beskæftigelsesministeren
Prætorius et al.
BMC Health Services Research
(2024) 24:816
Page 7 of 13
performed combinations of acute and elective tasks, or
other care tasks.
Table 
2
shows the ordinal logistic regression analy-
ses on decentralized decision authority measured as
an additive index and ward-level sickness absence. The
analyses are stratified by data wave and are in four mod-
els adjusted for hospital, manager’s job category (doc-
tor, nurse or other), management training, management
tenure, span of control, and providing acute tasks. The
results indicate a tendency in both waves, namely that
higher levels of decision authority are associated with
lower risk of sickness absence at the ward-level. However,
only few of the reported odds ratios in Table 2 are statis-
tically significant and none of the overall tests are statis-
tically significant. Stepwise adjustment for the included
covariates (Model 1- 4) did not substantially change the
risk estimates.
Table 
3
shows the ordinal logistic regression analyses
on decision authority measured as single items and sick-
ness absence at the ward-level. The analyses are stratified
by data wave and in four models adjusted for hospital,
manager’s job category, management training, manage-
ment tenure, span of control, and acute tasks. The results
indicate that the items ‘prioritizing projects at the depart-
ment’, ‘collaborations with other departments’, ‘making
decisions regarding quality control’, ‘making significant
changes in patient service’ and ‘significant changes in the
routines of the departments’ were associated with lower
risk of ward-level sickness absence. Across the models,
only the item ‘making significant changes in patient ser-
vice’ for wave two had a statistically significant associa-
tion with sickness absence at the ward-level.
Table 
4
shows the ordinal logistic regression model
where ward-level sickness absence was stepwise adjusted
for the relevant covariates. The results show that the
higher the extent of cross-functional decision author-
ity, the lower the odds of ward-level sickness absence.
Adjusting for the covariates in Model 1–4 only change
the risk estimates a little. The results are statistically sig-
nificant for the first wave. The risk estimates from both
waves and for all models show the same tendency.
Discussion
Principal Results and Comparison with Prior Work
The increase in care and work complexity in hospitals
alongside growth in staff turnover and sickness absence
requires appropriate and efficient management and deci-
sion authority at the right level in the organization [14,
15].
Our first hypothesis expected that decentraliza-
tion of decision authority would result in lower levels of
sickness absence in the wards. The absolute effect sizes
shown in the odds ratios (for index-scores of 3, 4 and 5,
albeit statistically non-significant) suggest that wards
where frontline managers’ report higher levels of decen-
tralized decision-making authority have lower levels of
registered sickness absence. Adjusting for relevant covar-
iates (hospital, managers’ education, management train-
ing, tenure of the individual manager, span of control, and
acute tasks) did not change the results. While our meas-
ure on decentralization of decision-making authority
does not necessarily correlate with supportive leadership
behaviours, it is likely that frontline managers with high
levels of decision-making authority have better oppor-
tunities for exhibiting supportive leadership behaviours.
A further explanation is that decision-making authority
gives employees the experience of having greater work
control, which according to previous studies reduce
absence from work [53]. When studying the individual
items that make up the composite measure of decentral-
ized decision-making authority, the analyses only yielded
few statistically significant associations. We found, how-
ever, that three of the five items in the measure exhibited
higher correlations with the outcome measure. The self-
reported ability to make decisions on ‘significant changes
in patient services’ had the strongest association with
sickness absence at the ward-level, which is in line with
other studies that find that the ability to focus on the core
task in doing their job (taking care of patients) is impor-
tant for employee well-being [54]. Our analysis also indi-
cates that the possibility for frontline managers to make
decisions on collaborations with other departments and
quality control are determinants of workers well-being as
measured by sickness absence.
Our second hypothesis expected that cross-functional
decision authority would be associated with lower lev-
els of sickness absence at the ward-level. In both waves
of the study we observed tangible reductions in the
odds ratios as the participants reported higher levels
of cross-functional decision authority. Relatedly, the
analysis suggests a similar pattern in both waves and
when adjusting for factors such as hospital, manager’s
job category, management training, tenure of the indi-
vidual manager, span of control, and acute tasks. This
indicates that frontline managers who hold a leader-
ship role for a variety of professional groups in hospital
settings may facilitate interdisciplinary completion of
work tasks. This highlights that to facilitate the coor-
dinated efforts of a multi-professional group of work-
ers, managers must be more attentive towards bridging
knowledge across boundaries and providing the neces-
sary decision-making information, something previ-
ous studies have found to empower frontline workers
[1,
55].
The stepwise adjustment for span of control in
the statistical analyses had little impact on the observed
associations between predictors and outcomes. This
finding is noteworthy, because previous studies have
SUU, Alm.del - 2023-24 - Bilag 368: Orientering om betydningen af decentral og tværfaglig ledelse for sygefravær på sygehuse, fra beskæftigelsesministeren
2895902_0008.png
Table 2
Results from multinomial logistic regression analysis of the association between the additive index on decentralized decision authority and ward-level sickness absence
Model 1
A
95%-CI
0.18
Reference
0.18; 2.34
0.49; 4.83
0.26; 2.38
0.18; 1.90
0.04; 1.05
0.13
Reference
0.17; 4.60
0.22; 3.85
0.14; 2.21
0.13; 2.58
0.05; 0.87
0.25
0.06; 1.07
0.25
0.71
0.16; 3.09
0.77
0.16; 3.66
0.06; 1.09
0.63
0.16; 2.43
0.61
0.15; 2.54
1.01
0.25; 4.12
1.07
0.24; 4.78
0.96
0.19; 4.79
0.92
0.17; 4.90
1
Reference
1
Reference
1
1.03
1.05
0.54
0.72
0.22
0.24
0.17
Reference
0.19; 5.66
0.23; 4.82
0.13; 2.30
0.14; 3.59
0.05; 0.97
0.21
0.04; 1.14
0.21
0.04; 1.28
0.22
0.64
0.19; 2.22
0.68
0.18; 2.56
0.73
0.78
0.24; 2.53
0.82
0.24; 2.76
0.80
1.65
0.49; 5.58
1.61
0.44; 5.89
1.65
0.47; 5.86
0.25; 2.62
0.20; 2.64
0.04; 1.22
0.14
1
1.16
0.99
0.49
0.65
0.18
Reference
0.19; 7.12
0.20; 4.86
0.11; 2.22
0.12; 3.47
0.05; 1.06
0.69
0.18; 2.64
0.69
0.17; 2.79
0.72
0.18; 2.89
1
Reference
1
Reference
1
Reference
0.16
0.26
0.30
1
0.67
1.57
0.73
0.70
0.18
Reference
0.16; 2.82
0.42; 5.91
0.21; 2.53
0.19; 2.67
0.03; 1.14
0.19
P
E
OR
95%-CI
OR
95%-CI
OR
95%-CI
OR
P
E
P
E
P
E
Model 2
B
Model 3
C
Model 4
D
95%-CI
P
E
0.24
Crude
Prætorius et al.
BMC Health Services Research
OR
1st wave
N
= 165
0
1
1
0.65
Score on additive
index on decen-
tralized decision
authority*
2
1.54
(2024) 24:816
3
0.78
4
0.69
5
0.21
2nd wave
N
= 137
0
1
1
0.89
Score on additive
index on decen-
tralized decision
authority*
2
0.93
3
0.57
4
0.59
5
0.20
*Based on answers about who can make decisions on: Prioritizing projects at the department, Collaborations with other departments at the hospital, Decisions regarding quality control, Significant changes in patient
service, and Significant changes in departmental routines
A
Model 1: Adjusted for hospital
B
Model 2: Adjusted for hospital, managers’ job category, management training, and management tenure
C
Model 3: Adjusted for hospital, managers’ job category, management training, management tenure, and span of control
D
Model 4: Adjusted for hospital, managers’ job category, management training, management tenure, span of control, and acute tasks
E
Tests if the result is different for each group
Page 8 of 13
SUU, Alm.del - 2023-24 - Bilag 368: Orientering om betydningen af decentral og tværfaglig ledelse for sygefravær på sygehuse, fra beskæftigelsesministeren
2895902_0009.png
Table 3
Results from multinomial logistic regression analysis of the association on the five items on decentralized decision authority and ward-level sickness absence
Crude
OR
95%-CI
P
E
OR
95%-CI
OR
95%-CI
OR
P
E
P
E
95%-CI
Model 1
A
Model 2
B
Model 3
C
P
E
Model 4
D
OR
95%-CI
P
E
Prætorius et al.
BMC Health Services Research
1st wave
0.83 0.46; 1.50 0.54
0.61 0.33; 1.14 0.12
0.76 0.38; 1.52 0.43
0.52 0.24; 1.11 0.11
0.91 0.49; 1.70 0.77
0.82 0.43; 1.56 0.54
0.63 0.34; 1.17 0.15
0.58 0.31; 1.10 0.07
0.97 0.50; 1.88 0.92
0.51 0.23; 1.14 0.12
0.92 0.48; 1.73 0.79
0.77 0.39; 1.54 0.47
0.66 0.35; 1.22 0.19
0.66 0.34; 1.27 0.19
0.95 0.48; 1.87 0.88
0.81 0.30; 1.67 0.57
0.66 0.35; 1.26 0.21
0.78 0.39; 1.56 0.48
0.50 0.23; 1.08 0.10
0.88 0.46; 1.66 0.70
0.77 0.40; 1.50 0.45
0.55 0.29; 1.04 0.05
0.87 0.45; 1.68 0.68
0.79 0.44; 1.41 0.42
0.77 0.43; 1.28 0.38
Item
0.75 0.42; 1.34 0.32
0.65 0.34; 1.24 0.19
0.80 0.38; 1.67 0.56
0.50 0.23; 1.11 0.11
0.97 0.51; 1.87 0.96
0.72 0.36; 1.44 0.36
0.69 0.37; 1.30 0.15
0.62 0.31; 1.23 0.15
0.77 0.37; 1.70 0.70
0.75 0.42; 1.35 0.33
0.64 0.33; 1.22 0.17
0.89 0.42; 1.87 0.75
0.52 0.24; 1.15 0.12
0.97 0.50; 1.87 0.91
0.70 0.33; 1.47 0.35
0.70 0.36; 1.36 0.29
0.61 0.30; 1.26 0.18
0.60 0.32; 1.54 0.40
N
= 165
1. Prioritizing projects at the department
(2024) 24:816
2. Collaborations with other departments at the hospital 0.60 0.32; 1.13 0.12
3. Decisions regarding quality control
4. Significant changes in patient service
5. Significant changes in departmental routines
2nd wave Item
N
= 137
1. Prioritizing projects at the department
2. Collaborations with other departments at the hospital 0.55 0.29; 1.04 0.07
3. Decisions regarding quality control
4. Significant changes in patient service
0.30 0.13; 0.67 < 0.01 0.31 0.13; 0.73 < 0.01 0.30 0.13; 0.71 < 0.01 0.27 0.12; 0.65 < 0.01 0.27 0.12; 0.58 < 0.01
5. Significant changes in departmental routines
A
Model 1: Adjusted for hospital
B
Model 2: Adjusted for hospital, managers’ job category, management training, and management tenure
C
Model 3: Adjusted for hospital, managers’ job category, management training, management tenure, and span of control
D
Model 4: Adjusted for hospital, managers’ job category, management training, management tenure, span of control, and acute tasks
E
P-value for OR-estimates
Page 9 of 13
SUU, Alm.del - 2023-24 - Bilag 368: Orientering om betydningen af decentral og tværfaglig ledelse for sygefravær på sygehuse, fra beskæftigelsesministeren
2895902_0010.png
Table 4
Results from the ordinal logistic regression analysis on the association between cross-functional decision authority and ward-level sickness absence
Crude
OR
0.05
1
0.98
1.07
0.38
0.08
0.16
1
0.58
0.42
0.24
0.17
0.02; 1.25
0.19
0.03; 1.25
0.19
0.05; 1.15
0.25
0.07; 0.93
0.25
0.07; 0.91
0.03; 1.22
0.10; 1.84
0.43
0.13; 1.39
0.41
0.13; 1.30
0.12; 2.79
0.64
0.18; 2.24
0.66
0.19; 2.34
Reference
1
Reference
1
Reference
0.13
0.15
1
0.69
0.41
0.22
0.19
Reference
0.18; 2.62
0.12; 1.44
0.05; 0.89
0.03; 1.25
0.01; 0.49
0.08
0.01; 0.51
0.09
0.02; 0.55
0.08
0.13; 1.17
0.38
0.12; 1.17
0.35
0.11; 1.07
0.32
0.36; 3.16
1.06
0.35; 3.19
1.03
0.35; 3.04
0.94
0.32; 2.99
1.04
0.33; 3.27
0.97
0.31; 3.06
0.91
Reference
Reference
Reference
Reference
0.29; 2.92
0.31; 2.86
0.11; 0.99
0.01; 0.47
0.12
1
0.76
0.44
0.25
0.20
Reference
0.19; 2.99
0.12; 1.60
0.06; 1.10
0.03; 1.37
0.96
1.03
0.39
0.09
0.04
0.03
95%-CI
P
E
OR
95%-CI
OR
95%-CI
OR
95%-CI
P
E
P
E
P
E
0.02
Reference
0.29; 3.21
0.33; 3.20
0.12; 1.26
0.01; 0.56
0.18
Model 1
A
Model 2
B
Model 3
C
Model 4
D
OR
95%-CI
P
E
0.06
Prætorius et al.
BMC Health Services Research
1st wave
N
= 163*
Not at all
(2024) 24:816
To a lesser extent
To some extent
To a great extent
To a very great extent
2nd wave
N
= 137
Not at all
To a lesser extent
To some extent
To a great extent
To a very great extent
A
Model 1: Adjusted for hospital
B
Model 2: Adjusted for hospital, managers’ job category, management training, and management tenure
C
Model 3: Adjusted for hospital, managers’ job category, management training, management tenure, and span of control
D
Model 4: Adjusted for hospital, managers’ job category, management training, management tenure, span of control, and acute tasks
E
Tests if the result is different for each group
*
Information on cross-functional decision authority missing for 2 persons
Page 10 of 13
SUU, Alm.del - 2023-24 - Bilag 368: Orientering om betydningen af decentral og tværfaglig ledelse for sygefravær på sygehuse, fra beskæftigelsesministeren
Prætorius et al.
BMC Health Services Research
(2024) 24:816
Page 11 of 13
argued that a high span of control is believed to chal-
lenge the basis for performing supervisory and consen-
sual management [56].
Overall, the study findings indicate that decentralized
management both directly and indirectly may constitute
job resources that enhance the capacity of employees to
deal with the work tasks while simultaneously support-
ing the well-being of employees [37]. The two aspects of
decision authority may constitute job resources in their
own right by enhancing the agility of the organization
to deliver efficient and high-quality health care services.
They may also indirectly serve as job resources by foster-
ing supportive leadership behaviours, cross-functional
cooperation, social support and job control that all have
been found to be associated with lower levels of sick-
ness absence [27]. It could be argued that higher levels of
decentralized management could constitute an additional
job demand on line managers negatively impacting their
capacity to provide effective and supportive leadership,
which again could entail an increase in the level of sick-
ness absence. The study findings, however, do not sup-
port such an interpretation.
Practical implications
Study strengths and limitations
By studying how frontline management influences the
sickness absence in hospitals, our findings speak to the
societal challenge of findings ways to reverse the pro-
jected shortage of healthcare staff in OECD countries [1,
4]
that in part results from a poor work environment and
conditions. For example, in Denmark, the hospital sector
is among the work sectors with the highest prevalence
of sickness absence (5.1% of the total working time). At
the same time, care tasks are becoming increasingly com-
plex processes because of shorter in-patient stays, patient
input and process uncertainty, and the need for (a)syn-
chronous work inputs from many healthcare profession-
als and organizational units [57]. As healthcare systems
reorganize to meet those changes and in doing so face the
risk of increasing sickness absence because of the uncer-
tainty it brings [58,
59],
our study provides additional
backing for supporting frontline managers to manage in a
way that fosters collaboration [44] and wellbeing at work
[7] capable of developing a sustainable psychosocial work
environment. The findings also highlight the importance
of having good supervisor-employee relationships, which
especially nurses associate with having adequate discre-
tionary power to do their job [1]. By focusing on enhanc-
ing frontline managers’ decision authority in hospital
settings and on improving other aspects of the psycho-
social work environment, it should be possible to reduce
sickness absence levels and, hence, improve work attend-
ance of hospital employees.
The results reported in this study are consistent across
manager and hospital characteristics and across two
independent survey waves in time at two Danish hospi-
tals. To that end, a number of covariates were included
in the analyses that might constitute potential confound-
ers in the association between the independent and the
dependent variable. This supports the credibility of the
findings of the study. Compared to previous studies pri-
marily surveying nurse managers, our study sample con-
sists of nurses and physicians who jointly undertake the
role of frontline managers, exemplifying a recent trend in
clinical leadership models [25]. The study complements
previous studies on hospital managers focusing on per-
formance management [8] or specific leadership styles
[12] such as distributed [14,
16]
or relation-oriented lead-
ership [5,
26].
Moreover, the study complements research
on psychosocial working conditions (e.g., high workload
and low levels of social capital, job control, and organiza-
tional justice) found to be predictors of sickness absence
[27–31].
Future research should consider the following study
limitations. The study has a relatively small sample size
of frontline managers in the two waves (165 and 137
in the two hospitals), but it was tied to 121 wards with
3,680 employees in round one and 108 wards with 3,331
employees in round two, respectively. The sample size
could also explain why only a few results in Tables 
2,
3
and
4
are statistically significant. Yet, it is impor-
tant to note that the sizes of the observed crude odds
ratios are considerable, suggesting that the analyses are
underpowered and that discarding the results due to
statistical non-significance could lead to drawing ‘false-
negative’ conclusions. The concept of decision author-
ity was captured by five questionnaire items whereas the
more experimental cross-functional decision authority
was captured by only one questionnaire item could sig-
nal a call for a finer-grained understanding of the meas-
ures in future research studies. Because little quantitative
research has measured cross-boundary decision author-
ity, it is relevant to investigate further whether it is a
structural mechanism that positively impacts healthcare
workers’ well-being. Since sickness absence for the sec-
ond wave of the survey was measured during 2020, the
COVID-19 pandemic may have had an impact on the
level of sickness absence in the participating wards. In
Denmark, the COVID-19 lockdown was put into effect
on 11 March, 2020. This must be taken into account
when interpreting the results of the study, but because
the results from the two waves (Table 2 and
3)
show simi-
lar tendencies it suggests that the COVID-19 pandemic
only had a limited impact on the results. It may also be
considered a study limitation that the two waves of the
SUU, Alm.del - 2023-24 - Bilag 368: Orientering om betydningen af decentral og tværfaglig ledelse for sygefravær på sygehuse, fra beskæftigelsesministeren
2895902_0012.png
Prætorius et al.
BMC Health Services Research
(2024) 24:816
Page 12 of 13
study are not fully independent, since some participants
in the first wave also participated in the second wave. To
take this lack of independence into account in the analy-
ses, we analysed the two waves separately.
of questionnaire surveys and medical database research projects to the
research ethics committee system is only required if the project involves
human biological material’ (https://en.nvk.dk/rules-and-guidelines/
act-on-research-ethics-review-of-health-research-projects).
Consent for publication
Not applicable.
Competing interests
All authors declare that they have no conflict of interest in this study.
Received: 5 October 2023 Accepted: 23 June 2024
Conclusion
This two-wave, empirical study of frontline manag-
ers indicate that higher levels of decision authority and
cross-functional decision authority in hospital wards are
positively associated with lower risks of sickness absence.
In this context, the study indicate that decentralized deci-
sion authority and cross-functional decision authority are
important to the work environment in hospitals, and that
the two management factors are capable of mitigating the
challenges arising from hospital specialisation and task
complexity. The study findings support conducting future
research on how to empower healthcare professional’s
decision autonomy at the frontline level of management
in hospital wards.
Supplementary Information
The online version contains supplementary material available at
https://doi.
org/10.1186/s12913-024-11234-2.
Additional file 1:
Acknowledgements
The authors would like to thank the Capital Region of Denmark for making the
administrative data for this study available. The authors also want to thank the
two hospitals and the frontline managers who answered the two surveys.
Authors’ contributions
Conceptualization (TP and PH), Methodology (TP, PH, LMR, ADL, TC), Formal
analysis and preparation of tables (ADL, JKR, TC), Writing—Original Draft (TP),
Writing—Review & Editing (TP, PH, LMR, ADL, TC), Funding Acquisition (PH).
Funding
This research was supported by an unconditional grant from the Capital
Region of Denmark. The funding body was not involved in the design of the
study and did not take part in the collection, analysis, or interpretation of the
data, or in writing the manuscript.
Availability of data and materials
The data used in this study are the property of the Capital Region of Denmark.
Restrictions apply to the availability of these data, which were used under
license for the current study, and are not publicly available. Data are, however,
available from the authors upon reasonable request and with permission from
the Capital Region of Denmark.
Declarations
Ethics approval and consent to participate in the study
This study was conducted in accordance with the principles of the Helsinki
Declaration. All respondents consented to participate. As described in the
invitation letter and at the start of the web-based survey, respondents were
informed that by answering the survey they gave consent to participate
and consented that their answers could be used for the stated purpose
of research. Data was managed according to the General Data Protection
Regulation (GDPR) guidelines. According to Danish Law (Section 14, part
2), survey-based studies do not require ethical approval by the Dan-
ish National Committee on Health Research Ethics because ’Notification
References
1. Brunetto Y, Xerri M, Trinchero E, Beattie R, Shacklock K, Farr-Wharton R,
Borgonovi E. Comparing the impact of management on public and
private sector nurses in the UK, Italy, and Australia. Public Manag Rev.
2018;20(4):525–44.
2. Burmeister EA, Kalisch BJ, Xie B, Doumit MAA, Lee E, Ferraresion A, et al.
Determinants of nurse absenteeism and intent to leave: An international
study. J Nurs Manag. 2019;27(7):143–53.
3. Davey MM, Cummings G, Newburn-Cook CV, Lo EA. Predictors of
nurse absenteeism in hospitals: a systematic review. J Nurs Manag.
2009;17(3):312–30.
4. Figueroa CA, Harrison R, Chauhan A, Meyer L. Priorities and challenges for
health leadership and workforce management globally: a rapid review.
BMC Health Serv Res. 2019;19(1):239.
5. Alimo-Metcalfe B, Alban-Metcalfe J, Bradley M, Mariathasan J, Samele C.
The impact of engaging leadership on performance, attitudes to work
and wellbeing at work: a longitudinal study. J Health Organ Manag.
2008;22(6):586–98.
6. Lawrence W, Hine J, Watson D, Smedley J, Walker-Bone K. How to improve
hospital employees’ health and well-being: a staff consultation. BMC
Health Serv Res. 2022;22(1):1488.
7. Mehta A, Mathisen J, Nguyen T, Rugulies R, Hulvej N. Chronic disorders,
work-unit leadership quality and long-term sickness absence among
33 025 public hospital employees. Scand J Work Environ Health.
2022;48(7):560–8.
8. Kerpershoek E, Groenleer M, de Bruijn H. Unintended responses to
performance management in Dutch hospital care: Bringing together
the managerial and professional perspectives. Public Manag Rev.
2016;18(3):417–36.
9. Noblet A, Rodwell J. Identifying the predictors of employee health
and satisfaction in an NPM environment. Public Manag Rev.
2009;11(5):663–83.
10. Sørensen J, Framke E, Clausen T, Garde A, Johnsen N, Kristiansen J,
et al. Leadership quality and risk of long-term sickness absence among
53,157 employees of the Danish workforce. J Occup Environ Med.
2020;62(8):557–65.
11. Weinberg D, Avgar A, Sugrue N, Cooney-Miner D. The importance of
a high-performance work environment in hospitals. Health Serv Res.
2013;48(1):319–32.
12. Elkomy S, Murad Z, Veleanu V. Does leadership matter for healthcare
service quality? Evidence from NHS England. Int Public Manag J.
2020;26:147–74.
13. Bauwens R, Audenaert M, Decramer A. Fostering societal impact and job
satisfaction: the role of performance management and leader–member
exchange. Public Manag Rev. 2019;21(10):1486–515.
14. Jakobsen M, Kjeldsen A, Pallesen T. Distributed leadership and perfor-
mance-related employee outcomes in public sector organizations. Public
Adm. 2021;n/a(n/a).
15. Gilmartin M, D’Aunno T. Leadership research in healthcare. Acad Manag
Ann. 2007;1(1):387–438.
16. Günzel-Jensen F, Jain A, Kjeldsen A. Distributed leadership in health care:
the role of formal leadership styles and organizational efficacy. Leader-
ship. 2018;14(1):110–33.
SUU, Alm.del - 2023-24 - Bilag 368: Orientering om betydningen af decentral og tværfaglig ledelse for sygefravær på sygehuse, fra beskæftigelsesministeren
Prætorius et al.
BMC Health Services Research
(2024) 24:816
Page 13 of 13
17. Gittell J, Douglass A. Relational bureaucracy: Structuring reciprocal relation-
ships into roles. Acad Manag Rev. 2012;37(4):709–33.
18. Prætorius T, Hasle P, Edwards K, Nielsen A. Towards the collaborative hospital
– harnessing the potential of enabling care processes and structures. In: Elg
M, Ellström P-E, Klofsten M, Tillmar M, editors. Sustainable development in
organizations: studies on innovative practices. Edgar Elgar Publishing; 2015.
p. 57–76.
19. Dobrajska M, Billinger S, Karim S. Delegation Within Hierarchies: How Infor-
mation Processing and Knowledge Characteristics Influence the Allocation
of Formal and Real Decision Authority. Organ Sci. 2015;26(3):687–704.
20. Klein K, Ziegert J, Knight A, Xiao Y. Dynamic delegation: Shared, hierarchi-
cal, and deindividualized leadership in extreme action teams. Adm Sci Q.
2006;51(4):590–621.
21. Chreim S, Langley A, Comeau-Vallée M, Huq J-L, Reay T. Leadership as
boundary work in healthcare teams. Leadership. 2013;9(2):201–28.
22. Bolton R, Logan C, Gittell J. Revisiting relational coordination: a systematic
review. J Appl Behav Sci. 2021;57(3):290–322.
23. Boyle TJ, Mervyn K. The making and sustaining of leaders in health care. J
Health Organ Manag. 2019;33(2):241–62.
24. Wagner J, Cummings G, Smith D, Olson J, Anderson L, Warren S. The rela-
tionship between structural empowerment and psychological empower-
ment for nurses: a systematic review. J Nurs Manag. 2010;18(4):448–62.
25. Clouser JM, Vundi NL, Cowley AM, Cook C, Williams MV, McIntosh M, Li J.
Evaluating the clinical dyad leadership model: a narrative review. J Health
Organ Manag. 2020.
26. Stromgren M, Eriksson A, Ahlstrom L, Bergman DK, Dellve L. Leadership
quality: a factor important for social capital in healthcare organizations. J
Health Organ Manag. 2017;31(2):175–91.
27. Török E, Clark A, Jensen J, Lange T, Bonde J, Bjorner J, et al. Work-unit social
capital and long-term sickness absence: a prospective cohort study of 32
053 hospital employees. Occup Environ Med. 2018;75(9):623–9.
28. Clausen T, Meng A, Borg V. Is Work Group Social Capital Associated With
Sickness Absence? A Study of Workplace Registered Sickness Absence at
the Work Group Level. Saf Health Work. 2020;11(2):228–34.
29. Clausen T, Christensen KB, Sorensen JK, Bjorner JB, Madsen IEH, Borg V,
Rugulies R. The predictive validity of the Danish Psychosocial Work Environ-
ment Questionnaire with regard to onset of depressive disorders and long-
term sickness absence. Ann Work Expo Health. 2023;67(2):195–207.
30. Chenevert D, Jourdain G, Cole N, Banville B. The role of organisational justice,
burnout and commitment in the understanding of absenteeism in the
Canadian healthcare sector. J Health Organ Manag. 2013;27(3):350–67.
31. Enns V, Currie S, Wang J. Professional autonomy and work setting as con-
tributing factors to depression and absenteeism in Canadian nurses. Nurs
Outlook. 2015;63(3):269–77.
32. Mintzberg H. Structure in 5’s: A Synthesis of the Research on Organization
Design. Manage Sci. 1980;26(3):322–41.
33. Miller D, Dröge C. Psychological and Traditional Determinants of Structure.
Adm Sci Q. 1986;31(4):539–60.
34. Leana C. Predictors and consequences of delegation. Acad Manag J.
1986;29(4):754–74.
35. Milton H, Raviv A. Organization Design. Manage Sci. 2002;48(7):852–65.
36. Rantakari H. Employee Initiative and Managerial Control. American Eco-
nomic Journal: Microeconomics. 2012;4(3):171–211.
37. Bakker AB, Demerouti E. The job demands‐resources model: State of the art.
J Manag Psychol. 2007;22(3):309–28.
38. Miraglia M, Johns G. Going to work ill: A meta-analysis of the corre-
lates of presenteeism and a dual-path model. J Occup Health Psychol.
2016;21(3):261–83.
39. Witman Y, Smid GAC, Meurs PL, Willems DL. Doctor in the lead: balancing
between two worlds. Organization. 2010;18(4):477–95.
40. Powell A, Davies H. The struggle to improve patient care in the face of
professional boundaries. Soc Sci Med. 2012;75(5):807–14.
41. Dickinson H, Smith C. Leadership in integrated care. In: Kaehne A, Nies H,
editors. How to deliver integrated care. Bingley: Emerald; 2021. p. 39–57.
42. Kivimäki M, Sutinen R, Elovainio M, Vahtera J, Räsänen K, Töyry S, et al. Sick-
ness absence in hospital physicians: 2 year follow up study on determinants.
Occup Environ Med. 2001;58(6):361–6.
43. Ernst C, Yip J. Boundary spanning leadership: tactics for bridging social
boundaries in organization In: Pittinsky T, editor. Crossing the divide: inter-
group leadership in a world of difference. Boston: Harvard Business School
Press; 2009.
44. McIntosh N, Meterko M, Burgess JJ, Restuccia J, Kartha A, Kaboli P, Charns M.
Organizational predictors of coordination in inpatient medicine. Health Care
Manage Rev. 2014;39(4):279–92.
45. Clark A, Prætorius T, Török E, Hvidtfeldt UA, Hasle P, Rod NH. The impact of
work-place social capital in hospitals on patient-reported quality of care:
a cohort study of 5205 employees and 23,872 patients in Denmark. BMC
Health Serv Res. 2021;21(1):534.
46. Flyvholm M, Thorsen S, Bültmann U. Fraværsrapport 2019. Deskriptiv
analyse af lønmodtagernes sygefravær i Danmark - belyst ud fra register- og
spørgeskemadata [Absence Report 2019. A Descriptive Analysis of Sickness
Absence among Employees in Denmark – using Register and Questionnaire
Data]. Copenhagen: National Research Centre for the Working Environment;
2019.
47. Foss N, Lyngsie J, Zahra S. Organizational design correlates of entrepre-
neurship: The roles of decentralization and formalization for opportunity
discovery and realization. Strateg Organ. 2014;13(1):32–60.
48. Hjollund N, Larsen F, Andersen J. Register-based follow-up of social
benefits and other transfer payments: Accuracy and degree of complete-
ness in a Danish interdepartmental administrative database compared
with a population-based survey. Scandinavian journal of public health.
2007;35(5):497–502.
49. Hensing G. Methodological aspects in sickness-absence research. Scand J
Public Health. 2004;32(63 suppl):44–8.
50. Pihlainen V, Kivinen T, Lammintakanen J. Management and leadership
competence in hospitals: a systematic literature review. Leadersh Health
Serv. 2016;29(1):95–110.
51. Bender R, Grouven U. Ordinal logistic regression in medical research. J R Coll
Physicians Lond. 1997;31(5):546–51.
52. Podsakoff P, MacKenzie S, Lee J, Podsakoff N. Common method biases in
behavioral research: a critical review of the literature and recommended
remedies. J Appl Psychol. 2003;88(5):879–903.
53. Clausen T, Burr H, Borg V. Do psychosocial job demands and job resources
predict long-term sickness absence? An analysis of register-based outcomes
using pooled data on 39,408 individuals in four occupational groups. Int
Arch Occup Environ Health. 2014;87(8):909–17.
54. Sasser M, Sørensen O. Doing a Good Job—the Effect of Primary Task Quality
on Well-Being and Job Satisfaction. Hum Factors Ergon Manuf Serv Ind.
2016;26(3):323–36.
55. Aiken L, Clarke SP, Sloane DM, Sochalski J, Silber JH. Hospital nurse staffing
and patient mortality, nurse burnout, and job dissatisfaction. J Am Med
Assoc. 2002;288(16):1987–93.
56. Kirkpatrick I, Altanlar A, Veronesi G. Hybrid professional managers in health-
care: an expanding or thwarted occupational interest? Public Manag Rev.
2021:1–20.
57. Prætorius T, Becker M. How to achieve care coordination inside health care
organizations: Insights from organization theory on coordination in theory
and in action. International Journal of Care Coordination. 2016;18(4):85–92.
58. Ingelsrud M. Reorganization increases long-term sickness absence at all lev-
els of hospital staff: panel data analysis of employees of Norwegian public
hospitals. BMC Health Serv Res. 2014;14:411.
59. Gronstad A, Kjekshus LE, Tjerbo T, Bernstrom VH. Organizational change and
the risk of sickness absence: a longitudinal multilevel analysis of organiza-
tional unit-level change in hospitals. BMC Health Serv Res. 2019;19(1):895.
60. Laschinger H, Finegan J, Wilk P. Situational and dispositional influences on
nurses’ workplace well-being: the role of empowering unit leadership. Nurs
Res. 2011;60(2):124–31.
61. Sarto F, Veronesi G, Kirkpatrick I. Organizing professionals and their impact
on performance: the case of public health doctors in the Italian SSN. Public
Manag Rev. 2019;21(7):1029–51.
62. Hussain M, Khayat R. The impact of transformational leadership on job satis-
faction and organisational commitment among hospital staff: a systematic
review. J Health Manag. 2021;23(4):614–30.
63. Enwereuzor IK, Ugwu LE. Clarifying the interface between respect-
ful leadership and intention to stay. J Health Organ Manag.
2021;ahead-of-print(ahead-of-print).
64. Aarons GA, Conover KL, Ehrhart MG, Torres EM, Reeder K. Leader-member
exchange and organizational climate effects on clinician turnover inten-
tions. J Health Organ Manag. 2021;35(1):68–87.