BEU, Alm.del - 2023-24 - Bilag 234: Orientering om betydningen af decentral og tværfaglig ledelse for sygefravær på sygehuse, fra beskæftigelsesministeren

Beskæftigelsesudvalget 2023-24, Sundhedsudvalget 2023-24
BEU Alm.del Bilag 234, SUU Alm.del Bilag 368
Offentligt

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

, Thomas Clausen

, Ann Dyreborg Larsen

, Jonas Kirchheiner Rasmussen

Lykke Margot Ricard

and Peter Hasle

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]

Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus,

Denmark

National Research Center for the Working Environment, Copenhagen,

Denmark

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

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.

BEU, Alm.del - 2023-24 - Bilag 234: 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

BEU, Alm.del - 2023-24 - Bilag 234: 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

BEU, Alm.del - 2023-24 - Bilag 234: 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

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

BEU, Alm.del - 2023-24 - Bilag 234: 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

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%

134) and second wave 79% (n

108)). The most pre-

dominant job type was nurse (64% (n

105) and 62%

85)) followed by physician (25% (n

41) and 28%

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%

BEU, Alm.del - 2023-24 - Bilag 234: Orientering om betydningen af decentral og tværfaglig ledelse for sygefravær på sygehuse, fra beskæftigelsesministeren

Table 1

Descriptive statistics for main study variables for the respondents in the first and second survey wave

2nd data wave

City Hospital 2

10.47 (8.24)

165

11.37 (8.32)

8.33

11.52

40.28

24.85

20.99

12.35

13.00 (8.75)

51.39

105

63.64

66.67

25.35

18.29

18.52

74.65

134

81.71

81.48

30.56

24.85

27.16

51.39

56.36

46.91

21.43

57.14

75.00

25.00

55.36

37.50

7.14

11.09 (6.99)

18.06

18.79

25.93

21.43

43.64

165

100

59.12

40.88

137

108

137

%/mean

(SD)

%/mean

(SD)

%/mean

(SD)

%/mean

(SD)

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)

Frontline managers

Prætorius et al.

BMC Health Services Research

Ward-level sickness absence %/year

< 3%

3–6%

> 6%

(2024) 24:816

Gender

Woman

Man

Job type

Nurse

Physician

Other

Management experi-

ence (years)

94.62

5.38

16.13

26.88

25.81

31.18

10.75

23.66

65.59

48.61

23.61

27.78

22.22

20.83

30.56

26.39

20.61

28.48

23.64

27.27

18.18

23.64

58.18

18.06

10.91

81.94

147

89.09

Management training

96.30

3.70

24.69

19.75

27.16

28.40

9.88

23.46

66.67

87.50

12.50

35.71

21.34

21.43

25.00

20.36

44.64

127

92.70

7.30

29.20

20.44

24.82

25.55

16.06

26.28

57.66

Page 6 of 13

Yes

Span of control (# employees)

0–9

10–14

15–24

> 24

Care task type

Acute

Elective

Both or others

BEU, Alm.del - 2023-24 - Bilag 234: 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

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

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

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

BEU, Alm.del - 2023-24 - Bilag 234: Orientering om betydningen af decentral og tværfaglig ledelse for sygefravær på sygehuse, fra beskæftigelsesministeren

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

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

Reference

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

1.16

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

Reference

0.16

0.26

0.30

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

95%-CI

Model 2

Model 3

Model 4

95%-CI

0.24

Crude

Prætorius et al.

BMC Health Services Research

1st wave

= 165

0.65

Score on additive

index on decen-

tralized decision

authority*

1.54

(2024) 24:816

0.78

0.69

0.21

2nd wave

= 137

0.89

Score on additive

index on decen-

tralized decision

authority*

0.93

0.57

0.59

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

Model 1: Adjusted for hospital

Model 2: Adjusted for hospital, managers’ job category, management training, and management tenure

Model 3: Adjusted for hospital, managers’ job category, management training, management tenure, and span of control

Model 4: Adjusted for hospital, managers’ job category, management training, management tenure, span of control, and acute tasks

Tests if the result is different for each group

Page 8 of 13

BEU, Alm.del - 2023-24 - Bilag 234: Orientering om betydningen af decentral og tværfaglig ledelse for sygefravær på sygehuse, fra beskæftigelsesministeren

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

95%-CI

Model 1

Model 2

Model 3

Model 4

95%-CI

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

= 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

= 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

Model 1: Adjusted for hospital

Model 2: Adjusted for hospital, managers’ job category, management training, and management tenure

Model 3: Adjusted for hospital, managers’ job category, management training, management tenure, and span of control

Model 4: Adjusted for hospital, managers’ job category, management training, management tenure, span of control, and acute tasks

P-value for OR-estimates

Page 9 of 13

BEU, Alm.del - 2023-24 - Bilag 234: Orientering om betydningen af decentral og tværfaglig ledelse for sygefravær på sygehuse, fra beskæftigelsesministeren

Table 4

Results from the ordinal logistic regression analysis on the association between cross-functional decision authority and ward-level sickness absence

Crude

0.05

0.98

1.07

0.38

0.08

0.16

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

0.13

0.15

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

0.29; 2.92

0.31; 2.86

0.11; 0.99

0.01; 0.47

0.12

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

0.02

Reference

0.29; 3.21

0.33; 3.20

0.12; 1.26

0.01; 0.56

0.18

Model 1

Model 2

Model 3

Model 4

95%-CI

0.06

Prætorius et al.

BMC Health Services Research

1st wave

= 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

= 137

Not at all

To a lesser extent

To some extent

To a great extent

To a very great extent

Model 1: Adjusted for hospital

Model 2: Adjusted for hospital, managers’ job category, management training, and management tenure

Model 3: Adjusted for hospital, managers’ job category, management training, management tenure, and span of control

Model 4: Adjusted for hospital, managers’ job category, management training, management tenure, span of control, and acute tasks

Tests if the result is different for each group

Information on cross-functional decision authority missing for 2 persons

Page 10 of 13

BEU, Alm.del - 2023-24 - Bilag 234: 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,

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

and

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

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

BEU, Alm.del - 2023-24 - Bilag 234: 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 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.

BEU, Alm.del - 2023-24 - Bilag 234: 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.