Holmstrom, Paul; Elf, Marie, "Staff retention and job satisfaction at a hospital clinic- a case study", 2004 July 25-2004 July 29

Online content

Fullscreen
Supporting Material is available for this work. For more information, follow the link from
the Table of Contents to "Accessing Supporting Material".
Table of Contents

Staff retention and job satisfaction at a hospital clinic
- a case study

Paul Holmstrém, BA
Master Student at the IT-University of Géteborg
Management Consultant, fluidminds
Fallstrémsgatan 8
SE 431 41 Mélndal, Sweden
+46 31 706 3200
paul@holmstrom.se

Marie Elf, MSc
PhD student at Chalmers University of Technology, Department of Architecture in Gothen-
burg and Institution of Public Health and Caring Sciences. Uppsala University
Nissers vag 3
SE 791 82 Falun, Sweden
+46 23 22 311
marie.elf@|tdalarna.se

In this study system dynamics has been used to explore staff retention and job satisfaction at
a maternity department, which was in an unfavourable spiral of attrition after an expansion
period. This raised the issue about how to stop this downward spiral. To understand and ex-
plore this a causal loop diagram and a system dynamics model were developed, integrating
factors of attrition and hiring rates, workload and qualitative contents of the work. The causal
loop diagram shows an unbalanced system, which may spiral favourably or unfavourably
after a relatively small disturbance. The system dynamics model shows that an unfavourable
spiral may be reversed by qualitative interventions. The conclusions are that system dynamics
is an interesting method, which may increase the understanding of the factors determining
staff retention, job satisfaction and work pressure in a hospital setting. There is need for fur-

ther examination of the qualitative factors incorporated in the model.

129)
INTRODUCTION

There is a shortage of professionals in health care in Sweden as well as in other Western
World countries. This problem will probably be accentuated in the future (Swedish National
Board of Health and Welfare 2000; County Council Association 2002; Werk6 2003). The
shortage may be due to change pressure forced by a financing cutback (which probably will
continue). Health care managers and providers are therefore forced to find more efficient and
effective ways of producing health care while at the same time improving the quality of pa-
tient care. During the last 10 years the health care sector has gone through a period of turmoil
with organisational changes, including altered political and economical conditions. There has
been a positive development with improvements in effectiveness, but also alarming reports of
high stress levels leading to exhausted staff, increasing short-term sick leave and reduced job
satisfaction. This has in turn resulted in an increase in staff turnover. A consequence is a spi-
ral of increasing wages in order to attract staff. Thus, it is important for the health care sector

to influence this situation in order to achieve continuous quality and effectiveness.

There is sparse evidence of organisational and management factors that have an impact on
health care practice and health outcomes (West 2001). West (West 2001) claims there are
reports on performance measurement but less on performance management and little on the
determinants of performance. However, some organisational factors have been identified as
important for health care outcomes, for example continuing training and education, leader-
ship style, project management, staff recognition, dedicated time and resources for improve-
ment projects (Shortell et al. 2000; Thomson et al. 2003). It also has been documented that
staff shortages influences the quality of care (Aiken 2001; Aiken, 2002; Needleman, 2002),
as there seems to be a correlation between on, one hand, the number of staff and, on the other

hand, patient mortality and severe complications.

A staff cutback may lead to decreased competence in the organisation, which could result in
additional difficulty in recruiting qualified professionals. Aiken and co-workers (Aiken 1998;
2001; Buchan 1999) have in several studies explored factors that influence the attraction of a
workplace. Crucial factors are high staffing levels and a high nurse-to-patient ratio. Wages, a
flexible working schedule, and job prospects are central factors for job satisfaction. Thus,
support to individuals to develop their potential, and to increase their autonomy seems to be

important factors as well as for experiencing quality of work (Aiken 2002; Buchan 1999;

2. (29)
West 2001). Other important factors for job satisfaction are interdisciplinary relationships,
possibilities of improving work quality and a decentralized organisation (Thomson et al.
2003). Adams and co-workers (Adams 1998) suggested that quality improvement has bene-
fits on professional satisfaction, and that this may influence productivity and staff motivation

to perform well.

Thus, workforce management aims at sustaining a high quality in health care. In this study,
we will consider how factors which management can control, such as training and quality

development, may increase productivity and improve the quality of care.

Problem context and description

The present project began with an organisational review of a ward at a hospital clinic that had
recently undergone a substantial expansion (the number of birthing capacity was increased
from 1500 to 2200 per year). The ward manager was overworked and splitting the unit was

considered.

During the study it was discovered that the staff increase had led to a lack of perceived staff
continuity and a reduction in job satisfaction. There had also been an increase in the short-
term sick leave. As the hospital is in a geographic location where there is a chronic shortage
of midwives and a high staff turnover in general, the reduced job satisfaction could possibly

lead this clinic into an unfavourable spiral of perpetual dissatisfaction and staff turnover.

The hospital management was concerned with the increase in short-term sick leave, as this
leads to higher costs. The organisation realized the problem at hand, but searched for solu-

tions, which might not resolve the problem.

Actions by the authors

A first survey was carried out in the autumn and winter of 2002. The issues identified turned
out to be complex. The conclusions of the report have been generalized and presented in the
causal loop diagram (Figure 1). The diagram indicated several reinforcing loops that cause an
unfavourable downward spiralling development, resulting in work pressure and job dissatis-

faction and staff attrition.

The case study presented here uses System Dynamics to scrutinize the structure and behav-

iour of work pressure and job satisfaction. In previous studies empirical approaches have

3 (29)
been used to study workload and job satisfaction in health care organisations. However, there
are few published studies that have taken a comprehensive approach to this problem (West
2001). Thus, there is sparse scientific evidence of the impact that managerial factors as pre-

sented in this study have on outcomes such as job satisfaction.

Aim
The main purpose of the study was to identify variables that influence staff turnover and job
satisfaction. A second purpose was to explore positive interventions and to estimate how

strong they need to be in order to turn a negative trend.

Research questions
¢ Which is the main causal feedback structure of the system underlying the staff turn-
over and job satisfaction influencing effectiveness and productivity in the hospital
ward under investigation?
¢ Which are the leverage points by way of which a policy may impact this system fa-
vourably?
¢ Which are some of the policies that may be developed for the purpose of improving

the behaviour of the system by way of the leverage points identified?

Hypothesises
¢ The unfavourable behaviour can be triggered and reinforced by relatively small dis-
turbances.
¢ The unfavourable spiral can be reversed by factors such as quality development,

training and co-operation between professionals.

METHOD

System Dynamics was used as the preferred method of analysis since the method explicitly
presents the relationship between the variables in a non-linear, dynamic feedback system
(Sterman 2000).

Procedure
A semi-structured interview instrument was developed, with open-ended questions such as
the content of the daily work, decision-making, patient flows and the opinion about the or-

ganisation at the unit. 25 professionals and managers were interviewed. The answers were

4 (29)
analyzed using a social analytical approach (Rowbottom 1977) as well as an epistemologi-
cal/cybernetic approach (Krogh 1995; Watzlawick 1984). The purpose was to understand the
entire social context as well as the behaviour of the individual and the social structure within

the context. The intention was to uncover the underlying system that caused the problem.

A causal feedback loop diagram was developed initially, to show the structure of the system.
The first tentative causal loops were built on the reported findings of the organisational study.
The interview notes were reviewed to confirm and develop causal diagrams portraying the
underlying causal structure of the organisation. The final causal diagram is shown in Figure

1. The diagram was later on transformed into a stock and flow diagram.

The personnel department gave historical data, such as number of staff, recruitment and turn-
over, sick leave for the past three years. These data were used as input and to validate the
effects of the model. Published empirical data were also used to determine effects of profes-

sional knowledge, education, cooperation and quality development.

A literature review was conducted at an early stage of the modelling process. Empirical
studies concerning job satisfaction, quality of care and workload or work pressure in health

care were searched for in the literature review.

The model was created incrementally by modelling and validating the baseline of each sub-

section. Finally the sections were brought together into an overall model for experimentation.

5 (29)
FEEDBACK STRUCTURES

Births
Siilie Ratio inexperienced/experienced staff
* ™.
* R4 + + -
Seis Continuity
Ratio complicated/normal births Ratio new/old staff
Birthing workload ss = hoje) skills
Maternity workload a
+ Work pressure
- (mp Temps +
* cialization
Capacity Sickness

Sickness (R3 Recruitment

R6

Job satisfaction Desired staff

* - Employed staff
i) Attrition “
@}

jeputation recruitment

Reputation experienc

Managerial levers
Goal descriptioy

Interprofessional-cooperation
Knowledge&skills\development

Quality developm

Figure 1. Feedback structures of staff retention and job satisfaction

The feedback structure is basically a set of self-reinforcing loops making it sensitive to out-
side influences. There are only two balancing loops and they have delays, indicating that any
change in the external input will create a spiralling dissatisfaction or satisfaction, only to be
tempered by time and by alternative changes in the input. For instance, if the work pressure
increases it will lead to a decrease in job satisfaction. A decline in job satisfaction will cause
an increase in staff attrition and the reinforcing structure pulls into action. The feedback
structures developed in the model are shown in Figure 1. We have chosen not to describe the
causal diagram or the specific loops in detail; our purpose is to point out the dominance of the

reinforcing loops.

There are two clusters, which influences the system and determine the direction of the rein-
forcing structure. One cluster of factors lies outside the power of the management, such as the
number of births and the political and financial decisions, which determine the capacity of the
wards. The other cluster, which management can influence, consists of inter-professional
cooperation, quality development as well as knowledge and skills development. When attri-

tion increases, there is a risk that the managers seek quick solutions, such as attracting new

6 (29)
staff with higher pay instead of addressing work pressure and dissatisfaction with the job
situation. The diagram highlights the main factors that interact to affect job satisfaction and
work pressure. This pattern may cause the managers of the organisation to:
¢ Prevent staff turnover by increasing job satisfaction and decreasing work pressure.
¢ Increase the good will of the organisation (staff reputation) since that will affect the
possibility to recruit needed individuals.

¢ Improve the possibility for individual development and quality improvement.

MODEL STRUCTURE - STOCKS AND FLOWS

Saft sls Employed Stall <7
Skills development Permanently employed
process ‘+ }_ Long-term temps

Vacation temps

| 4
‘Scheduln <—! |
7_¥ a ae ‘Staff continuity [7
Short term illness vy | Sauical
Daily scheduling perenne socialization
Short term temps + lob satistaction \7 Hq process
Work pressure |—_- +]
Job satisfaction

—___—=#F External staff reputation

ry

Bithing

Normal births
Complicated births
Workload

Figure 2. Overview of the model structure with key variables

In the model we have used some particular definitions, which we describe below:

One issue, identified in the interviews, was described as staff continuity. In an organization
staffed around the clock, the year around, staff does usually not work in fixed teams. The
more staff are rotated among shifts the more they perceived a lack of continuity. This is also
exacberated when new staff is employed and during the vacation period. As the normal shift
rotation is held constant during the studied time period, we have chosen only to model the
introduction of new and temporary staff, defining what we have called a socialization proc-

ess, described in more detail on page 10.

7 (29)
As will be seen further on, noise is part of the model. This has been included deliberately to
reflect the conclusions of the interviews. There is considerable variation in birthing, leading
to peaks, which lead to memories of workload. Also there is a significant flux in taking in
temporary staff, also leading to significant memories of disruption in perceived staff continu-
ity. Our experience is that a model just showing averages and excluding noise will not readily

be seen, by hospital staff, as reflecting their reality.

Employed staff
—— LongTermsick
Regular Staff
—— +
a ie) Dpaoesatisfaction
Basel TSickFP=C ici hate AvghéngSickTime _annualAttrition _)
(Probability ToQuit
sseffectont ts (p———-7 rae
linge, ett sobsatisaction | | stat Totalatsition
es fe \ <
So IntoWorkRate AttritionRate
LeaveRate,
samanoghiatleyrone —_XOF O Oo
[=a ‘ActualStaffLevel AverageLeaveTime LeaveFraction
BackToWork
7 "StaftNeed rs
DesirédStaffLevel /
Employed longterm temporaries : OnLeave \ Employed staff available

| for scheduling
EmployedTemps ETintroPeriod

ax Re ly 5 _x« 2 staff = pe)
: 4 \, _staffSeason
eTneifte EToatrtiate eninngfate “lease esl
bipiighetsns
Summer vacation temps Pst tS Wceiclt

Hireate |SuiTempFrac /

\ Uf SumTemp Intro SumTempStaff SumTempstatt
@ é 2 [

sirens suTempintoWork sutempLayrt —

Figure 3. Regular staff, long-term and summer vacation temporaries

The employed staff sector (Figure 3) shows that there are several factors determining the
number of employed staff in the organisation. For instance, the rate of long-term sick indi-
viduals, the attrition rate and the hiring rate. The staff can leave the organisation entirely or

temporarily, being long-term sick or on leave for studies or parenthood.

Individuals are hired when there is an actual deficit in actual staff level. The actually em-
ployed staff is the total of permanently employed staff, including those who are long-term
sick or on long term leave for education or parenthood. The introduction time for newly em-
ployed is one month during which they work alongside experienced staff in order to become

familiar with the staff and routines at the department. The staff available for scheduling con-

8 (29)
sists of the permanently employed staff (excluding those being long term absent), the long-
term temporaries and the summer temporaries. Job satisfaction influences the probability that

individuals leave the organisation for reasons such as other jobs or sickness.

The situation is changed during the summer, when one third of the ordinary staff is on vaca-
tion, in three periods of three weeks. This period ranges from mid June to mid August. The
desired summer staff level determines the number of summer temporaries hired. The intro-
duction time for the summer temporaries is also four weeks. The summer period is perceived

as disruptive with staff discontinuity, reduced experience and increased work pressure.

The staff on long term leave (education or parenthood) is replaced with long-term temporar-
ies. But staff on long-term sick leave is not replaced in this way, as they can return at short

notice.

Birthing

FractionComplicated NormLabourTime NormMaternityTime

- ou

ie ‘
Ne IBirthi Ne AfterC: \
jormalBirthing | pallormAfterCare

5: — -

NormHomeGoing

a
nd
AnnualBirths-ry P Nat 4
2 "a = @
% Complicated Bifths ComplLabour} ate “ ‘ComplHomeGoing
S&S 2 _/CompBirthin, | 7 ComplAfterCare

a ComplLabourTime of
oO oO

TotalBitthing
imaternityTime

PinkNoiceC TovalMaternity—
4 Cor
st MaternityBedCap :

BirtStaffCapUtiliz ~——fatBedDtil_ oi)

ActualComplicatedRatio
MatBEdOverload

Figure 4. Structure of the comprehensive birthing process

The childbirth model includes two parallel and isomorphic processes, normal and compli-
cated birthing. A normal situation is a birth without any complications neither for the mother
or the baby (Figure 4). The model has a pink noise function to reflect the considerable varia-
tions in day-to-day birthing, The normal birthing process as well as the aftercare is shorter

than for the complicated birthing. The fraction of complicated births is 20%, but varies con-

9 (29)
siderably, affecting work pressure. The model also takes into consideration the annual sea-

sonal variation in birthing.

The capacity constraint in birthing is the number of available midwives being able to handle
two parallel birthings each. The capacity has been set to be able to handle the peaks, which
leads to a low average utilization. However, in the maternity wards, the number of beds is the
constraining factor. Patients spend longer time in Maternity than in Birthing, so the variation

in influx is dampened, enabling a higher utilization.

The staff talks about the complicated rate being 20%, but due to the longer time in birthing as

well as maternity, these represent 30% of capacity utilization.

Staff continuity

JobSatisfaction

BaseSocHireFrac

. sOulalizedHired
IntoWorkRate ETLAoffRate
AttrifionRate

ETHiringRate

ee sophie '
a

Unsocializedhired écialization Leaving 1

LsReturn 1
SocializationTime

: SickRate
Sra
BackToWork v

LeaveRate

SumTempStaff.

ReturnRate

LU LeaveAndSick 1
TotalShortTemp

TimeTolncreaseCont

NormalisingOfCont

ug ©

MemoryOfCont.
ContinuityéffectOnwP

Figure 5. Socialisation process of newly hired staff and perceived continuity

Most new employees are unknown and not yet socialized into the organisation (Figure 5).
The socialization process takes an average of one year, as shift work and rotating schedules
means that it takes time to get to know everybody and learn and adapt to how they work.
Doctors, midwives and auxiliary nurses all use judgment in their work and it takes time to

mutually adjust in the work with newcomers. However, a fraction of the new employees are

10 (29)
former temporaries and are considered as already being socialized. That fraction is influenced
by job satisfaction. A higher job satisfaction leads to more temporary workers seeking per-

manent employment.

The unit of measure is “units of socialization”. A newly employed person enters the stock of
“unsocialized” staff and gradually “seeps” into being socialized, as she/he becomes partially

known in the organisation.

Memories from periods of declined continuity last for a time even if the situation is changed
to the better. Thus, there is an information delay in the state of memory of continuity among

the staff. In particular, the impact of the summer temporaries lingers for almost half a year.

Skills coflow
MemoryOfReputation
y, _-&p_ Base aphiveFrac =
Expediencedtired /
IntoWorkRate
d ETLiyoftRate
i A. ; Attrifionrate 77
/ ETHiringRate-—-———~
f inexperiensed =, Expelfenced \
V7 \
G3
ee) =o, ?
InexperiencedHired —} “tearing > Leaving 2
Q Cy LsReturn 2 re
InexpSkillFrac he, GERRI ——~ SickRate
2 o. LsRafe2
‘SumTempStaft-— BackToWork oy =
_ “ SkillsFactor “i Epanehates
ReturnRate

LeaveAndSick 2

TotalShortTemp

Figure 6. From novice to expert

Figure 6 illustrates the learning process (coflow). The department recruits both individuals
that are newly examined and individuals that are experienced (skilled). New staff directly
from nursing school cannot contribute as much as the skilled employees. An inexperienced
midwife has 60% of the skills of an experienced midwife, here defined as 0.6 units of knowl-
edge. It takes on average one year to become fully skilled. During that period the new staff is
scheduled in the same way as other staff, leading to an increase in work pressure, as they

need support.

11 (29)
Memories of the perceived skills among the staff persist over time, generating inertia to the
perceived change of the actual state. The staff has bad experience of periods of several novice
individuals within the organisation, which creates discontinuity. Bad experience and memo-

ries about this periods remains for a while even if the actual situation has been improved.

Scheduling

‘AvgShortSickTime ie

SchedulabeStaff Getting Well WvprtimeRate StaffOnOvertime

@

ChapGelnAvailable

ShortTermTemp

AvailableStaff Short eemTempHireRate

WorkPressure

PinkNoiseS

BasicStaffl®
ShortTermTempDeficit,

Seasonadjust

‘SummStaffLevel

Figure 7. Structure of short - term sickness, overtime and temporaries

This section handles daily scheduling and the need to hire short-term temporaries due to un-
derstaffing and short-term illness. When employees report in sick at short notice, somebody
on the preceding shift working overtime usually replaces them, apart from that temps are
used. A pink noise function has been added to reflect the fluctuations in illness. Work pres-
sure can also influence the sick. A higher degree of work pressure will results in an increased

rate of short-term sickness.

If the proportion of short-term temporaries is high it will reduce the perceived continuity and

increase the work pressure for the remaining staff.

Work pressure and job satisfaction
This model sector illustrates job satisfaction, work pressure and external staff reputation and

the factors influencing those variables.

12 (29)
Job satisfaction

External staff
WorkPlessure reputation

Work Pressure

NormalisingofSkil WeihtOFCont

ContinuityElfectOnwP

MemoryOfSkN /eighOFSkill

knowskilDevelopment_
a if
i Weightorcpdnss. ©
fa WeieNotComplicated
ActuaCompleHfOnW tio WeightOFrAMlemonss ¢
iano gn : TimeToDecreaseReputation
mn WeightOfMatBEd :

| Changeinttrizi6h TimeTolncreaseReputation

@

froryAdjustmpntAtertffony-yofAttrition
(

ChangeinReputation

MemoryOfReputation

AttritionRate
TimeToDecreaseAttrition

TimeTolncreaseAttrition

Figure 8. Work pressure, job satisfaction and external staff reputation

There are several factors that determine the work pressure, such as the number of birthings,
ratio of complicated birthing, as well as the ratios of socialized and skilled midwives. All

determinants of work pressure have informational delays built in.

Job satisfaction is also determined by work pressure, quality development, knowledge devel-
opment and interprofessional co-operation. The existence of care programs and goal descrip-
tion will influence the job satisfaction. These variables were chosen based on the interviews
as well as research. Factors, such as the possibility for the professionals to work with quality
development and investments on the professional’s knowledge development, increase the job
satisfaction (Adams et al. 1998; Aiken et al. 2002)). Interprofessional cooperation and a clear
apparent goal of the work may enhance the job satisfaction (Aiken et al. 2002; Thomson et al.

2003; Shortell et al. 2000).

The external staff reputation is essential for the recruitment of new employees. Due to the
competitiveness in attracting staff it is important to have a good reputation. We suggest that
the external staff reputation is mainly dependent on those factors which can be observed from
the outside, such as attrition, quality development and interprofessional cooperation, but also
work pressure, goal descriptions and care programs (Figure 8).

13 (29)
VALIDATION OF THE MODEL

In the validation process the equations and behaviour of each sector were reviewed. These
were compared with data available from interviews and data collection. Consistency was ob-
tained by specifying the units of measurements for each variable and checking for unit con-
sistency. The quantitative data such as the number of staff, long-term sickness and number of
temporaries that were built into the model were received from the hospital administration.
When using parameters that needed a judgmental estimation, the base was empirical studies
presented in the literature. Further on, the preceding interviews and our own modelling expe-
riences were used as a base for judgmental estimations of parameters such as the learning
time for a midwife to be an experienced midwife and the value of cooperation between pro-

fessionals.

The model was developed as a system under ideal conditions. Initially the submodels were
stabilized with real figures and estimated variable numbers that should correspond to an ideal
but realistic situation. When this step was performed the model was tested and simulated with
extreme input values. This was performed to test the robustness of the model under varied
conditions. The submodels were then put together to the whole and subjected to varied data,

within the expected ranges.

The baseline simulation is based on the present situation with a birthing capacity of 2200 per

year and the corresponding staff levels.

Validation baseline runs
Figures 9-13 show validation baseline runs to compare and analyze with later simulations.
The intention with the baseline run was to set up the model so that it reproduces the behav-

iour of the present system.

The time period in the simulations is months. The simulations run over time of three years.
The employed staff and the newly born are simulated as discrete individuals as the popula-
tions are so small that the effects of using discrete units are significant. However, the short-
term sickness and short-temporaries are non-discrete since they can be off or be hired part

time of a day.

14 (29)
Figure 9 illustrates the variation in employed staff throughout the year and how this influ-
ences the number of newly employed staff introduced into the organisation. The model re-
produces the pattern of the historical data obtained from the department and shows the stabil-

ity and variation expected in a baseline model.

Be seat 2: Staffintra 3: LongTermSick 4 OnLeave
] 100

i

2 50:

4

1

2 ai 3 3 =

H ii 2. ro Fn ae

7.00 9.75 18:50 27.25 36.00
Page 1 Months 12.27 tor 1 jan 2004
aaF 7 Staff levels

Figure 9 Staff stocks

BF 1: Memoryorcont 2: Continuity

2] :

IA

4] 0,

7.00 O75 7850 27.25 36.00

Page 1 Months 12.27 tor 1 jan 2004
ae/ ? Continuity

Figure 10. Perceived staff continuity

Figure 10 shows the validation run for the perceived continuity and the memory of the conti-
nuity. The continuity declines during the summer periods when there are numerous summer
temporaries. A new employed individual has to go through a “socialization” process to get to
know the regular staff and the routines at the department. There is a corresponding dip in the

skills level.

The model behaves as expected. Individuals are aware of the periods when there is a high
amount of new employees or a high fraction of temporaries since the skills level is reduced.
These periods recur each summer. The memory of those periods remains for a long time. In

the validation run we set the retention memory time to be 2 months, which shows behaviour
15 (29)
in line with the interviews. Several of the staff expressed that they remember periods with
discontinuity for a long time. Figure 11 shows the same pattern but with the memory of the
staffs skills.

Bi: woneessure

7.00 9375 18°50 2725 36.00
Page 1 Months 12.27 tor 1 jan 2008
asf 7? Untitied

Figure 11. Variation of the work pressure

The work pressure is determined by workload in birthing and maternity, ratio of complicated
births, continuity and skills. The baseline run shows that there is a significant variation of the
work pressure related to birth overload but also to the periods of discontinuity (Figure 11).
The component factors of work pressure were weighted so as to correspond to the effect ac-

cording to the interviews.

JD 1: sobsatisfaction
1 2.

ite 1
eet pee i  eet
1 of
Too 975 1350 22s 36.00
Page 1 Months 12.27 tor 1 jan 2004
ae 7? Job satisfaction

Figure 12. Job satisfaction

The validation run for job satisfaction was performed in the same way as the validation for
the work pressure. The factors that are assumed to influence the job satisfaction were
weighted based on the interviews as well as literature. The diagram (Figure 12) shows that

there is a significant variation in job satisfaction related to different periods of continuity and

16 (29)
number of births. Job satisfaction is based on two dynamic factors and five static parameters.
The two dynamic factors are work pressure and attrition, the latter having a “demoralizing”
effect. The five static parameters are quality development, interprofessional cooperation,
knowledge and skill development, goal descriptions and care programs. These qualitative
parameters were mentioned by many in the interviews and are also described in the literature
to be important for job satisfaction. The baseline values were estimations of how the hospital

rates as compared to other hospitals.

B® 1: Reputation 2: MemoryOfReputation

yo

2] ' WT

al 1

7.00 975 18:50 27.25, 36.00

Page 1 Months 12.27 tor 1 jan 2004
ae 7? Reputation

Figure 13. The external staff reputation

Figure 13 illustrates the validation run for the external staff reputation. The external reputa-
tion is based on the same factors as for job satisfaction, however with different weighting.
Attrition has been given a high weight as information of conditions at a workplace spreads
with people who have left. Also the qualitative factors have been given higher weight re-
flecting that opinions about the hospital are spread by participation in e.g. conferences. The

informational delay times have also been set significantly longer for the external reputation.

RESULTS OF THE SIMULATIONS

One of the hypotheses in present study was that qualitative efforts might have a stabilizing
effect and thereby reducing attrition and increasing job satisfaction. Three sets of simulations
were run accordingly. The first series were variations of the baseline run in order to test

strategies for reducing attrition.

The intention of second series was to simulate the effects of political decision to increase the

birthing capacity from 1500 to the present level of 2200. This was actually done about two

1729)
years ago, in order to increase the birthing capacity in the region. The clinic has a natural
intake from its local area, after the expansion they also took in patients redirected from more

distant hospitals.

The third set of simulations were to address the fact that staff which were long-term sick,
were replaced by short-term temps as well as the steady state error incurred by the delay be-

tween attrition and recruitment.

The following questions were a base for the experimentations:
¢ What will happen to the attrition rate when the state of the system is changed?
¢ What will happen to the attrition rate when the qualitative factors of the work are
changed?

¢ What is the effect on continuity and skill when the birthing capacity is increased?

Baseline variations

The baseline series are based on the present birthing capacity of 2200 per year and the corre-
sponding staff and bed capacity. The purpose was to test strategies to reduce attrition. The
work pressure and job satisfaction receives a jolt each summer when temporaries are hired
during the summer vacation (Figure 14). This is most clearly seen in the graph showing per-

ceived staff continuity (Figure 15).

SD 1: Jovsatisfaction 2: WorkPressure
1 2
3]
J 2
1 2
2] Tha f Seen
1
al of
00 oT5 7250 a5 3600

age 1 Months 12.27 tor 1 jan 2004

aee ? Job satisfaction

Figure 14. Relationship between work pressure and job satisfaction

18 (29)
JB 1: Memoryofcont 2: Continuity

See

z| o.

7.00 975 18.50 27.25 36.00
Page 1 Nonths 175. s6n21 dec 2003
aee* 7? Continuity

Figure 15. Perceived continuity

The total attrition during the simulation of three years is 18 persons (Table 2). To get an indi-
cation of the vacation related effect, a simulation was performed with the assumption that all
vacations were spread out over the whole year. The condition was a correspondingly higher
staff level, with no temporaries. This reduced the total attrition to 15 individuals per year.
Thus, the effect of the discontinuity of the summer temporaries leads to an increased attrition
of one person per year. In other words, spreading the vacation could be one strategy to reduce
attrition. However, not being able to get a summer holiday for the ordinary staff may de-
crease job satisfaction. This assumption is not modelled since empirical data is lacking to

support that statement.

The department allocates six education days per employee and year. According to the inter-
views this is considered as generous and is perceived as higher than what many other hospi-
tals offer. However, the content of the education is also considered as one-way communica-
tion (more as lectures) and lacking in focus. In other qualitative improvements efforts the

department is considered as being under par, when compared to other hospitals.

Apart from the baseline run two simulations were performed. In the qualitative run at a me-
dium level, each of the parameters was set to 1. In the “high qualitative run”, a redistribution
of efforts from knowledge and skills development to more on-the-job related development
such as quality improvements work and interprofessional cooperation. Also, an increase in
management related tasks such as goal descriptions and care programs were performed. An
assumption was done that the redistribution could be done without increasing the total costs

(Table 1).

19 (29)
Table 1. Qualitative input variables at different levels

Input parameters Base conditions | Medium level efforts | High level efforts
Quality development 0,85 1,00 1,20
Interprofessional cooperation 0,80 1,00 1,20
Knowledge and skill develop- 1,25 1,00 1,15
ment

Goal descriptions 0,85 1,00 1,25
Care Programs 0,90 1,00 1,25

Table 2. Attrition rate by year and totally

Year Base conditions | Medium level efforts | High level efforts
1 8 7 3
2 3 2 2
3 7, 6 6
Total 18 15 il

In the simulation at the medium level the total attrition is the same as for the spread vacation
simulation. This indicates that it might be fairly easy and not costly to reduce the attrition
caused by periods of high hiring of temporaries. Also, it indicates that by redistributing ex-

isting development costs it would be possible to reduce attrition even further.

A simulation was run where we replaced the long-term sick with long term temps, and an-
other where we took into consideration the steady state error in the staff stock due to the de-
lay between attrition and recruitment. Both simulations had the expected outcomes on the

staff levels, but showed no change in the staff attrition.

Capacity increase (Quantum jump) variations

The baseline simulation was revised to include a “quantum jump” in birthing capacity, from
1500 to 2200 per year, along with corresponding increases in staffing and maternity beds and
birthing rooms. This was planned in advanced and executed in an organized way so that all
the required resources were in place. Staff was recruited and in place at the time of increase.
The model was altered so as to allow an extra inflow of staff and a ramping up of all other
necessary parameters. The increase in capacity takes place in the first month of the second

year of the simulation.

20 (29)
BP: stat 2: Staffintro 3: LongTermSick 4 OnLeave

a ——

4 0 2. ss 2: oo,
1.00 9.75 18:50 2728 36.00
Page 1 Months 13.07 tor 1 jan 2004
aeF 6? Staff levels

Figure 16. “Quantum jump” of new employees due to capacity increasing

As expected, this has a significant effect on the perceived continuity (Figure 17). Continuity
has not quite recovered after the following summer vacation and drops even further as there
is a sudden influx of new staff. Then comes the next summer vacation before continuity has
recovered. This is confirmed by the interviews carried out in the autumn of year two, the or-

ganisation feels that it is in disarray and that it is full of newly employed.

J 1: comity 2: MemeryotCont

1 1
3]
ie ‘ ,
2 E
1

1
Hy 9
2]
2 of
To0 975 7350 22s 36.00
Page 1 Months 16.57 s6n21 dec 2003
ae 7? Continuity

Figure 17. Continuity after capacity increasing

Naturally, this has an effect on work pressure and job satisfaction, which both deviate signifi-

cantly at the moment of the capacity increase (Figure 18).

21 (29)
JD 1: sobsatisfaction 2: WorkPressure

al ,

3] of

Too 375 7850 272s 36.00
Page 1 Months 13.07 tor 1 jan 2004
aee* 7? Job satisfaction

Figure 18. Work pressure and job satisfaction related to capacity increasing

In reality this lead to significant attrition (Table 2). Staff experienced a connection between
the reduction of continuity and a reduction of taking collective responsibility for the whole
work setting. Further on, the staff stated that when continuity declines, the work pressure
increases and as a consequence employees quit. Thus, it is important to ask what strategies
management could have pursued to counteract the situation and not resort to wage escalation

when recruiting the replacements.

Searching for other possible solutions, three further simulations were performed. A revised
base run (taking into consideration the lower staff level of year 1), and the same assumptions
for qualitative factors as for the baseline variations i.e. a medium and a high effort level (Ta-

ble 1).

Table 3. Attrition by year and totally

Year | Base | Quantum Jump | Medium level efforts | High level efforts
i 6 6 4 2
2 3 7 i 2
3 7 7 i 6
Total 16 20 18 10

The table 3 shows the attrition rate at the “quantum jump”. The increase in capacity leads to a
significant increase in attrition in the second year. Four additional individuals leave the or-
ganisation compared to the baseline simulation. In the baseline simulation the medium quali-
tative efforts were enough to compensate the vacation effect shown in table 2. In present

simulation the medium investment in qualitative factors is not sufficient to fully counter the

22 (29)
effect of the sudden increase of capacity. The simulations show that the high qualitative ef-
forts have the same high effect on attrition as in the baseline simulations and well compensate

the undesired effects of the capacity increase.

DISCUSSION AND CONCLUSIONS

A point of departure was how to attain a qualitative and a good health care setting in a situa-
tion of change and turmoil. The main purpose was to investigate variables that influence the
job satisfaction and staff turnover A second purpose was to explore the positive interventions

and estimate how strong they need to be in order to turn a negative situation.

To sum up, the simulations results confirm one of the hypothesises, that the system is rela-
tively easily disturbed, by such a commonplace circumstance as the summer vacation, and
that it is possible to compensate that effect by efforts such as quality improvement work and
other factors under the control of the management. The pattern of the summer vacation period
is an important indication of what happens in a situation when the combined effect of many
new employees, the impact of the managerial factors on the clinical outcomes such as quality,
effectiveness and productivity are not fully explored. These latter factors were not measured
and could therefore not model explicitly. However, the results showed that continuity affects
work pressure and job satisfaction. Thus, it could be assumed that the perceived continuity is

a key dimension of effectiveness and productivity.

The development of a model is important since the shortage of hospital workers is a crucial
problem in health care today. Health care is exposed to extensive change pressure. Organisa-
tional changes, alterations of political and economical condition, but also a knowledge explo-
sion with new treatment alternatives have created a situation of perpetual change. The finan-
cial cutbacks have forced all involved to find more efficient and effective ways of working

and yet still emphasizing improvements in the quality of patient care (SOSFS 2001).

There are distressing reports of high stress that health care workers are exposed to which
cause job dissatisfaction, burnout and staff turnover. At the same time, several reports indi-
cates that job satisfaction is essential for the motivation to perform a good job (Aiken et al.
1998; Sullivan et al. 1999). The demands on the professional will not end. Thus, action based
on managerial efforts presented in this study such as knowledge development and quality

improvements are particularly urgent if the expectations of an effective and high quality

23 (29)
health care are to be realized. If a workplace should be considered as attractive and creates
job satisfaction, the individual should be able to perform high-quality work. This is a motiva-
tion factor in itself for individual (Herzberg 1968) Thus, it is important that work conditions

do not hinder the individual to do good work.

The capacity of the midwives was modelled and defined as the amount of births the profes-
sionals were capable of handling during normal circumstances. This definition is close to the
meaning of productivity. The concept does not declare anything about the quality of the
births they manage to handle. Traditionally, health care quality has been assessed in terms of
efficiency i.e. the productivity of health care. In other words, “the number of patients treated
in the shortest time”. This output indicates whether the chosen treatment is the right one in
productivity or technical terms. This outcome does not identify, for instance, the patient’s
feelings, comfort, and quality of life during or after treatment. Thus, effectiveness is con-

cerned with the degree to which treatment is beneficial to the patient (Campbell 2000).

In the interviews, the staff expressed that in periods with a high proportion of newly em-
ployed the work setting was dissatisfactory. The staff skills declined and the work was less
organised. This situation may have implications for the health and safety of mothers and ba-
bies. The capacity, i.e. the number of births, may be the same but the quality of the care is
probably influenced negatively. Results from other studies show that serious events are based
on shortage in knowledge of the health care staff. Inexperienced staff is not fully capable to
discover a patient’s health problems and need in time. Thus, risks for serious complication
enhance (Aiken et al. 2002; Aiken et al. 2002; Lundstrom et al. 2002; Needleman et al.
2002).

Birthing is a highly technical setting and the margins between failure and success are small.
In the delivery process the physical health status is of great importance. However, the mid-
wife has to be able to meet each mother’s individual health and need of care. It is a complex
task, including both pain relief, anxiety and to support the initial bounding process between
the mother and infants (McKenna et al. 2002; Liu et al. 2002). It is important for avoiding
posttraumatic crises both for the woman and child and avoiding later utilization of health

care.

The employees that are satisfied with their job are likely to remain at their work, leading to

lower staff turnover. Probably, experience has a feedback on performance from several per-

24 (29)
spectives. Experienced individuals are probably more inclined to influence decisions at the
work place. This is needed for the development of praxis and for care improvement. Partici-
pation and share of decisions in work gives more satisfaction among the employees. Thus,
staff skills are of great importance to attain a high quality of care but also for the ability to
improve the praxis. Furthermore, health care is based on teamwork. In extreme and acute
conditions it is essential that each one in the team knows exactly what to do and what their
colleagues are doing, in order to achieve good results. Good teamwork is evaluated between
individuals that have been working together for a while. The teamwork can be challenged
when new individuals enter the organisation. In the present study it is suggested that this is an

important factor of job satisfaction.

To conclude, as shown in the study, there are factors beyond merely external conditions such
as number of births that are of relevance regarding how to retain staff in the organisation.
Those factors may be quality improvement, knowledge development and interprofessional

teamwork.

Method discussion

There are some limitations of the model and the modelling process. There is a lack of em-
pirical data in the model, especially for variables such as work pressure, job satisfaction and
quality factors. When we went into the modelling phase the hospital was suddenly under
threat of closure. Management was busy handling the political situation and we were unable
to obtain additional data. Thus, the model is not comprehensive and involved some vague
variables. However, the primary aim with the model was not to present exact quantitative
figures and solutions of the personnel situation at the department. Rather the aim was to
demonstrate that it is desirable and possible to involve some hypothesis from the scientifi-
cally literature of what creates job satisfaction in health care organisations. The aim was to
study if the qualitative factors presented in the literature generate the dynamics that was ex-

pected in the literature.

Ideally, the model process should have involved a team from the hospital for validation of the
model. The reliability and usefulness of the model would have been more valid if a group of
experienced individuals had been involved in the process. However, the circumstances at the
hospital during the modelling process made it impossible to continue with the project. On the
other hand, both the modellers have long experience from health care and can thus be viewed

as expert in the field. Reviewed health care scientific literature was used as a base for the
25 (29)
modelling. Thus, the developed model is not very specific, but can be generalized to other

health care settings with similar problems.

The staff, long-term temporaries and births were modelled as discrete entities. In these cases
it is appropriate to handle people as discrete, whole individuals. The organisation hires whole
individuals and women deliver whole babies. One strong argument against this procedure
may be that people in this kind of organisations work part time and thus the staff should be
handle as continuously variables. Short-term sickness and temporaries was modelled as con-

tinual variables since one individual can be away from the work part of a day.

The challenge with the model was to capture the structure and behaviour of the factors that
determines job satisfaction, work pressure and the external staff reputation. The clear effects
of the simulation may be mainly due to two factors, i.e. the weightings used to define job
satisfaction and the non-linear relation between job satisfaction and attrition. The relation-
ships were modelled as linear, which is acceptable within the ranges of the model. However,
it would be desirable to continue to develop the model together with professionals from the
hospital to identify and describe the non-linear relationships. This would be necessary to test

major departures in policy.

It may have been important to include a wage variable for several reasons. The wages are
essential for the external staff reputation and thus for the recruiting process. Wages can be a
competitive instrument between hospitals. Further on, professionals in health care have indi-
vidual wages related to achievement. Thus, it may be important to relate wages to the per-
ceived job satisfaction since the wage is a receipt and a confirmation for a good performance.
On the other hand wage escalation may be seen as an archetypal “quick fix” and the purpose

with present study was to find alternative strategies.

Implication for research

Increasing the job satisfaction of hospital workers is one of the most important challenges for
the health care in the future. The present model has shown that factors such as quality im-
provement and cooperation between professionals may be important for job satisfaction and
staff retention. As these have such a significant impact it would be interesting to research
these further and gather more data so as to refine the model in this respect. Thus, there is a
need for further empirical work to explore the importance of those relationships. In the future

it is also important to further analyse the effect of job satisfaction on quality outcomes such

26 (29)
as patients well-being and health. The question should be: how could we develop the struc-

ture and organisation for the possibility to improving the care for the patient.

Implication for practice

It is important for the managers to have a tool that gives possibilities to explore and control
actions in the organisation. Modelling gives the potential to explicitly clarify the work of
management, but also to discuss policy questions within the organisation. In the present
study, we show that it may have been possible for the management to avert the attrition
caused by the capacity increase. This did not happen in reality; probably because of the man-
agement was occupied planning the extension in localities and recruiting the new staff. Being
busy with this they were not able to foresee the human resources effects. This is most likely

to be a common problem in other similar situation.

Possible extensions of the model

Mintzberg (1983) describes several archetypal organizational forms, one of them being the
professional bureaucracy, with hospitals and universities as the prime examples. Universities
and most other organizations staffed by professionals solve the vacation problem by cutting
capacity and/or spreading the vacations. During the vacation period hospitals cut capacity in
many clinics and wards, and those units open must be staffed by professional holding requi-

site qualifications.

The professional bureaucracy differs from most other structures as disturbances and dysfunc-
tionalities in the organization can be compensated by professional freedom and development
(Mintzberg 1983). There are three major sources of “disturbances” presented in this study,
the vacation period, the sudden high increase in capacity and the strong noiselike variations
in the workload. This study also suggests that these disturbances can be offset by professional

development.

We suggest that extensions of the model mainly be sought in professional bureaucracies,
which do not cut capacity during the vacation period, and replace those on vacation by pro-

fessionally qualified temporaries. I.e. conditions mainly present in hospitals.

27 (29)
REFERENCES

Adams, A., S. Bond, and C. A. Hale. 1998. Nursing organisational practice and its relation-
ship with other features of ward organisation and job satisfaction. Journal of Ad-
vanced Nursing 27 (6):1212-22.

Aiken, L. H., S. P. Clarke, and D. M. Sloane. 2002. Hospital staffing, organisation, and qual-
ity of care: cross-national findings. Nursing Outlook 50 (5):187-94.

Aiken, L. H., S. P. Clarke, D. M. Sloane, J. Sochalski, and J. H. Silber. 2002. Hospital nurse
staffing and patient mortality, nurse burnout, and job dissatisfaction. JAMA 288
(16):1987-93.

Aiken, L. H., D. M. Sloane, and J. Sochalski. 1998. Hospital organisation and outcomes.
Quality in Health Care 7 (4):222-6.

Campbell, S.M., Roland, M.O., Buetow, S.A. 2000. Defining quality of care. Social Science
& Medicine 51:16611-1625.

County Council Association, the. Svensk hdlso-och sjukvard under 1990 -talet. Utveckling-
stendenser 1992-2000. (The Swedish health care system during the 1990s.
Landstingsforbundet 2002.

Herzberg, Frederick. 1968. Work and the nature of man. London: Staples Press.

Krogh, Georg von. 1995. Organisational epistemology. Basinstock: MacMillan.

Liu, S., M. Heaman, M. S. Kramer, K. Demissie, S. W. Wen, and S. Marcoux. 2002. Length
of hospital stay, obstetric conditions at childbirth, and maternal readmission: a popu-
lation-based cohort study. American Journal of Obstetrics & Gynecology 187 (3):681-
7.

Lundstrom, T., G. Pugliese, J. C. Bartley, J. Cox, and C. Guither. 2002. Organisational and
environmental factors that affect worker health and safety and patient outcomes.
AJIC: American Journal of Infection Control 30 (2):93-106.

McKenna, H., and F. Hasson. 2002. A study of skill mix issues in midwifery: a multimethod
approach. Journal of Advanced Nursing 37 (1):52-61.

Mintzberg, Henry. 1983. Structure in fives : designing effective organizations. Englewood
Cliffs, N.J.: Prentice-Hall.

Needleman, J., P. Buerhaus, S. Mattke, M. Stewart, and K. Zelevinsky. 2002. Nurse-staffing
levels and the quality of care in hospitals. [see comments.]. New England Journal of
Medicine 346 (22):1715-22.

Rowbottom, Ralph. 1977. Social analysis: a collaborative method of gaining usuable scien-
tific knowledge of social institutions. London: Heineman.

Shortell, S. M., R. H. Jones, A. W. Rademaker, R. R. Gillies, D. S. Dranove, E. F. X.
Hughes, P. P. Budetti, K. S. E. Reynolds, and C. Huang. 2000. Assessing the impact
of total quality management and organisational culture on multiple outcomes of care
for coronary artery bypass graft surgery patients. Medical Care 38 (2):207-17.

SOSFS. 2001. SOSFS, 1996:24 Socialstyrelsens foreskrifter och allmanna rad. Kvalitetssys-
tem 1 halso-och sjukvarden (Advisory instructions on quality systems in health care).
Socialstyrelsens férfattningssamling 2001. In Socialstyrelsen forfattningshandbok
(The Swedish National Board of Health and Welfare). Stockholm: Liber AB.

Sullivan Havens D, Aiken LH. 1999. Shaping systems to promote desired outcomes. Journal
of Nursing Administration 29 (2):14-20.

Swedish National Board of Health and Welfare. 2000. Omfattning av administration i varden
(The amount of administrative tasks in health care). Socialstyrelsen www.sos.se 2000
[cited 2000].

28 (29)
Thomson O'Brien, M. A., N. Freemantle, A. D. Oxman, F. Wolf, D. A. Davis, and J. Herrin.
2003. Continuing education meetings and workshops: effects on professional practice
and health care outcomes.

Watzlawick, Paul. 1984. The invented reality. How We Know What We Belive What We
Know. New York: Norton Company.

Werk6, L. 2003. Fran lakarens hjalpreda till jamstalld vardpartner in Swedish (From assistant
to equal care provider). Lakartidningen 100 (19).

West, E. 2001. Management matters: Audit and feedback: effects on professional practice
and health care outcomes. The link between hospital organisation and quality of pa-
tient care. Quality in Health Care 10 (1):40-8.

29 (29)

Back to the Top

Metadata

Resource Type:
Document
Rights:
Date Uploaded:
December 30, 2019

Using these materials

Access:
The archives are open to the public and anyone is welcome to visit and view the collections.
Collection restrictions:
Access to this collection is unrestricted unless otherwide denoted.
Collection terms of access:
https://creativecommons.org/licenses/by/4.0/

Access options

Ask an Archivist

Ask a question or schedule an individualized meeting to discuss archival materials and potential research needs.

Schedule a Visit

Archival materials can be viewed in-person in our reading room. We recommend making an appointment to ensure materials are available when you arrive.