ArticlePDF Available

Waiting lists in Dutch health care: An analysis from an organization theoretical perspective

Authors:

Abstract

To develop propositions on why public policies towards decreasing waiting list in health care can be expected to be unsuccessful. On the basis of a case study of public policies directed towards the reduction of the waiting lists in health care a number of propositions are formulated explaining why this policy has turned out to be ineffective. The propositions are based on theoretical insights form the field of organizations studies about the behavior of organizations and professionals. It is demonstrated that public policies on reducing waiting lists in the Dutch health care system are likely to be ineffective because the policy-making strategies used are based on unrealistic assumptions about the behavior of organizations and professionals who are expected to reduce the waiting lists. Although the propositions are based on established organization literature, empirically they are only based on one case study. In order to develop effective policy interventions it is important to be realistic about the behavior and strategies of the actors towards which the policy is directed. Moreover, rather than directing exclusive attention to those waiting, it is important for policy makers to address the interdependencies of the organizational field in which waiting lists occur. This paper gives directions to policy makers who need to deal with complex and interdependent problems.
Waiting lists in Dutch health care
An analysis from an organization theoretical
perspective
Patrick Kenis
Department of Organisation Studies, Tilburg University, Tilburg,
The Netherlands
Abstract
Purpose To develop propositions on why public policies towards decreasing waiting list in health
care can be expected to be unsuccessful.
Design/methodology/approach On the basis of a case study of public policies directed towards
the reduction of the waiting lists in health care a number of propositions are formulated explaining
why this policy has turned out to be ineffective. The propositions are based on theoretical insights
form the field of organizations studies about the behavior of organizations and professionals.
Findings It is demonstrated that public policies on reducing waiting lists in the Dutch health care
system are likely to be ineffective because the policy-making strategies used are based on unrealistic
assumptions about the behavior of organizations and professionals who are expected to reduce the
waiting lists.
Research limitations/implications Although the propositions are based on established
organization literature, empirically they are only based on one case study.
Practical implications In order to develop effective policy interventions it is important to be
realistic about the behavior and strategies of the actors towards which the policy is directed. Moreover,
rather than directing exclusive attention to those waiting, it is important for policy makers to address
the interdependencies of the organizational field in which waiting lists occur.
Originality/value This paper gives directions to policy makers who need to deal with complex
and interdependent problems.
Keywords Waiting lists, Medical care, Health services, The Netherlands
Paper type Research paper
Introduction
Although The Netherlands is generally considered as one of the showcases of a modern
welfare state, it is characterized by the peculiarly phenomenon of long waiting lists in
its health care system. At the moment about 350,000[1] persons are on one or the other
waiting list for health care services. For example, in mental health care the situation is
as follows: patients have to wait 7 weeks for registration, 15 weeks for being informed
about the type of help they need, and dependent on the care necessary, 14 weeks for
access to extramural care and 29 weeks for access to intramural care.
In order to deal with the waiting lists and the political discussions accompanying
them, the former Dutch minister of health decided during her 8-year period in charge to
make extra money available in order to reduce the length of the lists. On top of the
regular budget for health care about e3 billion was earmarked in 1999-2001 in order to
reduce the length of the waiting lists. This extra financial input had, however, no
impact. There are still approximately 350,000 persons waiting for some type of cure or
care, which is the same number of persons as before.
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1477-7266.htm
JHOM
20,4
294
Journal of Health, Organization and
Management
Vol. 20 No. 4, 2006
pp. 294-308
q Emerald Group Publishing Limited
1477-7266
DOI 10.1108/14777260610680104
Waiting lists are in principal something rather simple: a waiting list is an overview
of clients which have a valid indication for cure or care, but for which the indicated
cure or care did not yet (completely) start (NIZW, 2000). And also the explanation for
the existence of waiting lists is rather simple: waiting lists develop when there is a
discrepancy between the demand for cure and care and the supply of cure and care
(Vissers, 2000). Practice shows, however, that waiting lists are very hard to reduce.
The question is why?
The present paper formulates a number of theoretical propositions about why the
strategies chosen to reduce waiting lists did hardly produce any result. The propositions
are deduced form insights form organization theory. This implies that the answers to the
question why waiting lists are difficult to reduce are related to the behavior and
structure of organizations in the health care sector. It will be demonstrated that the
initiatives, which intend to govern the health care sector in general and the problem of
waiting lists in particular, are based on unrealistic assumptions about the behavior and
strategies of organizations. On the basis of more realistic assumptions about
organizations an alternative strategy to deal with waiting lists is proposed.
The above will be demonstrated on the basis of four propositions:
(1) Extra resources do not automatically reduce the waiting lists in cure and care.
(2) Counting and publishing the number of those waiting contributes hardly to the
reduction of the waiting lists, but produces a number of unintended negative
consequences.
(3) Not every organization in the field of cure or care has by definition an interest in
reducing waiting lists.
(4) In order to reduce the waiting lists, instead of managing those waiting, it is
important to manage the interdependencies of the organizational field.
The propositions formulated here are hypothetical and are the result of a combination
of theoretical considerations and empirical indications. Empirical evidence was
gathered from official reports, academic journals and articles from the press. The
theoretical framework for assessing the information is based on a tradition in
organization science which is based on the assumption that things in and around
organizations are often not the way they “should” be.
P1. Extra resources do not automatically reduce the waiting lists in cure
and care
As stated earlier, a waiting list is the result of a discrepancy between demand and
supply. The larger the demand and/or the smaller the supply, the longer the waiting
list[2]. A logical way to reduce waiting lists would consequently be to reduce the
demand and/or to increase the supply. Within the Dutch system it is, however,
virtually impossible to reduce the demand for cure and care since there exist strong
formal rights with regard to receiving cure and care (legal rights which can only be
changed in the mid- or long-term).
What is possible, is to increase the supply by providing more resources. That is
exactly what the ministry of health, welfare and sports (VWS) has been doing in
the last years. The Ministry spent in the years 1999-2001 approximately an extra
e3 billion in order to increase the volume of the sector (Ministerie van VWS, 2001a, b).
Waiting lists in
Dutch health
care
295
In addition, other resources such as a “waiting-list brigade,” a high level “taskforce,”
organizational “platforms” and homepages (www.wachtlijstaanpak.nl and www.
nietafwachten.nl) were created. Resource endowment for the health sector in The
Netherlands is also in general not worse than in many other countries (The Netherlands
spends 8.8 percent of its BNP on cure and care, which is about the European average).
Empirical studies carried out in The Netherlands and elsewhere show, however,
that the input of extra resources does not automatically lead to a shortening of the
waiting lists (Taskforce aanpak wachtlijsten, 2001, p. 20; Breedveld et al., 2000, p. 182;
Laeven et al., 2000a, b, p. 6). Research in the UK and Canada arrives at similar
conclusions, i.e. spending extra resources does not automatically results in shorter
waiting lists (Frankel, 1991; Newton et al., 1996; Wood and Thomas, 1985, p. 89; Yates,
1991). The fact that extra resources do hardly influence the length of waiting lists is
something, which comes as a surprise to policy makers. From the point of view of
organizational sciences it is much less surprising.
An approach which assumes that an increase in input (i.e. resources for cure and
care) will automatically lead to an increase in output (i.e. less people waiting) is based
on the theoretical assumption that the output can be governed through the input or, in
other words, that output and input are coupled in a logical way. This is by the way an
idea, which is generally speaking strongly anchored in our modernist-rationalist way
of thinking (Sanderson, 2000, p. 445).
Since, the pioneering work of Herbert Simon we know that such rational assumptions
are not consistent with observations of empirical reality. More than 40 years of
organizational research in the tradition of Simon (Simon, 1962, 1965; March and Simon,
1958; Cohen et al., 1972; Weick, 1979; March and Olsen, 1984; Brunsson, 1985, 1989) has
clearly demonstrated that organizational and policy problems are often characterized by
a high level of complexity. This means that a large number of factors are responsible for
the outcome of processes, that these factors do influence each other in mutual ways and
that we lack knowledge to predict the consequences of action. All this has to do with the
fact that we operate on the basis of “bounded rationality.” Limitations in intellectual
capacities, time and other resources do not allow making all-embracing evaluations of
the different alternative strategies to reach a goal. Given a certain level of complexity of a
problem it will become impossible to react in an equally complex way. The consequence
is that decisions are often taken which are based on a simplified vision of the problem,
which results in inappropriate or even pathological consequences (Kenis, 2001).
Waiting lists seem indeed to be an almost ideal typical example of a problem which
is characterized by a high level of complexity. The demand as well as the supply side
are constantly influenced by a great number of factors which at the same influence
each other mutually and this not always in a linear manner: the need for care or cure,
the population structure, epidemiological factors, the way the insurance companies
assess future needs, the number of personnel, the efficiency of the cure and care
process, changes in the emancipation of citizens, the situation on the labor market,
technological developments in the medical sector, existing capacities for child care, etc.
But not only is a single waiting list influenced by such factors, other waiting lists
(which are on their turn also influenced by a large number of factors) also influence the
length of the waiting list: the waiting list for registration at the polyclinic, the waiting
list for medical examination at the polyclinic, the waiting list for the hospital, the
waiting list for care at home, the waiting list for the nursing home, etc.
JHOM
20,4
296
Given the complexity of the waiting list phenomenon, as described before, it does
not come as a surprise that regulating the input not automatically leads to the expected
outputs. The fact that policy makers nevertheless keep believing in such an approach
could be explained by two facts: first their underestimation of the complexity of the
problem, and/or secondly their overestimation of their own capabilities (Sanderson,
2000, p. 441). Such attitudes not only produce a generally inappropriate reaction to the
waiting list problem. It even often produces further breeding grounds for such
approaches. Often it is stated that the strategy followed should be enforced in order to
get better grip on the system. This is a reaction, which is quite common according to
the organizational literature. In cases where problems or situations get out of control,
further centralization is often seen as the solution (Chisholm, 1989, p. 6). Especially, in
the public sector problems are often seen as a lack of coordination. Almost
automatically the reaction is then to strengthen central coordination. Enforcing central
coordination does, however, according to what we know from organization science, not
necessarily lead to more effective strategies. Even worse, there are good reasons to
believe that it often produces negative consequences:
P2. Counting and publishing the number of those waiting contributes
hardly to the reduction of the waiting lists, but produces a number of
unintended negative consequences
A common answer to complex problems is to chart them by collecting data (Boyne and
Gould-Williams, 2001; Chisholm, 1989, pp. 6-9; The Economist, 2001a, b). This answer
could also be observed in the Dutch health care system. One of the central spearheads
in the response to waiting lists has been the development of a central registration and
publication of the number of persons waiting for cure and care. A taskforce coordinates
this approach for the care sector and the counting in the cure sector is coordinated by
the Dutch Association of Hospitals (NVZ). On the one hand, is counting of course an
important task since it produces some sort of indication for the problem load and it
allows to monitor whether the waiting lists reduce or increase over time. On the other
hand, it can be said that the importance, which is attributed to such counting, is based
on a number of behavioral assumptions which, again on the basis of what we know
from organization science, can be misleading. First, the assumption that counting
persons waiting can be done in an accurate way. Secondly, the assumption that the
transparency produced by waiting lists induces persons to select those organizations,
which have shorter waiting lists. Thirdly, the assumption that adequate information
will allow organizations to develop adequate responses to the problem.
All three assumptions are based on good intentions but again contradict with insights
from the organizational science literature. On the basis of this literature one could assume
that counting has hardly any effect on the length of the waiting lists. Moreover, it could be
expected that such counting produces unintended negative consequences.
The first assumption, i.e. that the numbers collected give a clear indication of the
demand of cure and care, is probably only partially the case. Even if we assume that
the registration system is solid and that all organizations involved put the same energy
in the same way in registering those waiting (which is according to some reports
doubtful, see, e.g. Breedveld et al., 2000, p. 182) the problem remains that a great
number of things can happen in the situation of someone waiting. The change can be
the consequence of a worsening or improvement of the patient’s situation, the
Waiting lists in
Dutch health
care
297
becoming available of alternative forms of care or cure, changes in the family
composition, information about the length of the waiting list, etc. It is not clear which
percentage of a waiting list is influenced by such factors but it could be considerable.
But in general, it could be stated that the more individualistic society becomes, the
more difficult it will be to grasp these demands within organizational frameworks and
to map them (Globerman, 1991, p. 256). A reaction to this situation by Dutch policy
makers is that the indications will have to be updated more regularly. A polemic
reaction to this could be that this could lead to “indication-actualization-waiting-lists.”
A second assumption, which lies at the basis of the registration and making public of
the number of persons on waiting lists is that these provide instruments to allow clients
to take more rational decisions with regard to their cure and care consumption. It is clear
that publication of waiting list data can increase the transparency and choice for the
consumers. But it is further assumed that they will, on the basis of such information, be
mobile towards those organizations which have shorter or no waiting lists at all. This
could, consequently, lead to a situation where the average waiting time is reduced. But
also this assumption is less obvious than one would like to believe. Clients are not
necessarily mobile with regard to their consumption of care and cure. Often they want to
be treated in their direct environment since trust in persons and organizations play an
important role in the consumption of cure and care (FEM/de Week, 2000; Kersboom and
Geleen, 2000; Ministerie van VWS, 2001a, b). Moreover, it has been observed that shorter
waiting lists produce additional demands, which consequently results in the fact that the
length of the waiting lists increases again. This can happen because “hidden demand”
becomes visible or through the referral strategies of medical doctors. Two British
researchers demonstrated that the referral strategies are influenced by the reported
length of the waiting list (Smethurst and Williams, 2001). They statistically confirmed
that the longer a general practitioner expected a patient to have to wait, the less the
chance was that he would refer the patient. The consequence being that an increased
availability of specialists does not contribute to decreasing waiting lists. This because
the system adapts in such a way to that a new equilibrium is reached, with the same
waiting lists as before. Their explanation for this phenomenon is based on complexity
theory, which claims that the characteristics of complex systems cannot in a predictable
way be deduced form its separate composed parts, but that they are the results of the
interaction between those. They summarize their research as follows: “Hamsters run
freely on wheels and a doctor’s work may be compared by running on a health service
wheel ... The faster one runs the faster the wheel turns (Smethurst and Williams, 2001).
Similar phenomena have also been observed in the Dutch health care system (Taskforce
aanpak wachtlijsten, 2001; School, 2000).
A third assumption, which generally legitimizes the collection of information, is that
information can contribute to the solution of problems. This is an assumption about
which Simon (1983, p. 3) made the following critical remark: “One kind of optimism, or
supposed optimism, argues that if we think hard enough, or rational enough, we can
solve all our problems.” There are, however, indications that this is not necessarily
the case. Such an indication is that information collection is often legitimized with the
statement that it will lead to further insights and consequently a solution to the
problem, but that the recommendations are most of the time of a rather general nature.
For example, a report which presents an impressive and highly detailed collection of
waiting list data in the area of care concludes the following: “Central in the solution of
JHOM
20,4
298
the waiting lists is the extension of capacities in order to provide more care in the
sector” (own translation, Taskforce aanpak wachtlijsten, 2000).
Moreover, information about the quantity and type of persons waiting does not,
however, automatically contain information on how to reduce waiting lists. According to
Wildavsky (1973, p. 132; zie ook Sanderson, 2000, p. 441) “can [there] be no planning
without the ability to cause other people to act differently than they would otherwise act.”
Another explanation for the fact that information not necessarily contributes to the
solution of a problem, claims that information is often collected for other reasons than
contributing to the solution of a problem. Thus, far, there is lack of empirical evidence to
proof this thesis but on the basis of organization theory it can at least hypothetically be
put forward. In particular, the neo-institutionalist organization theory assumes that
what organizations do should not necessary be interpreted as being a contribution to
their effectiveness, but rather as a contribution to their legitimacy. This means that
organizations do not aim to increase their efficacy, but rather aim at contributing
towards the confirmation of certain values and expectations (Meyer and Rowan, 1977;
Powell and DiMaggio, 1991). On the basis of such a perspective the hypothesis could be
formulated that the reasons way information is collected is in the first place an indication
for confirming to certain expectations (i.e. undertaking action). McKevitt and Lawton
(1996) indeed demonstrated in a study in the UK, that the collection of data about results
in the first place was a consequence of pressure to confirm to certain expectations rather
than to contribute to organizational change or an improvement of services.
What has been illustrated so far is that it could be expected, at least according to
organization theory, that reporting waiting lists contributes less to shortening these
lists than one would generally expect. The reason being that reporting is often based
on a number of unrealistic assumptions.
Not only does counting and reporting not necessarily contribute to a solution of the
problem, it could even be hypothesized that it has unintended negative consequences. On
the basis of organization theory the following negative consequences could be expected:
Costs
It is clear that a central reporting system generates substantial direct and indirect
costs. This, on the coordinating as well on the level of the single organizations, which
have to provide the information. The direct costs for the registration of persons waiting
for care is for one year approximately e30 million. The indirect costs are very difficult
to estimate.
Strategic behavior
A disadvantage of the reporting of waiting lists can be that it produces strategic
behavior. It can lead to short-term decisions or can induce the prioritizing of the
treatment of simple disorders because they can be treated faster (The Economist,
2001a; de Brauw, 2001).
False security
The false precision and rigidity of counts produce a false security and can as such
produce failures. As Mintzberg (1987, p. 26) stated: ... setting oneself on a
predetermined course in unknown waters is the perfect way to sail straight into an
iceberg.”
Waiting lists in
Dutch health
care
299
Misuse
Numbers can by definition be falsified. For political, election campaign or other reasons
organization can have an interest in announcing increases or decreases in the length of
waiting lists. There are no direct proofs that this has so far been the case in The
Netherlands but in other countries (UK and Sweden) with waiting lists in cure and care
such incidents have been reported (Pickin et al., 2001).
Legitimacy of policy
Organizations which are, in the first place, confronted with their institutional
environment can hardly be assessed on the basis of their outcome (e.g. hospitals,
schools, ministries). They will consequently give priority to increasing their legitimacy
compared to increasing their effectiveness. On the one hand, it seems thus plausible
that the health ministry orders the collection of waiting lists information especially
since as such a signal is given that “something is done.” On the other hand, the type of
information which is collected can, however, be used by others as an indicator for the
effectiveness of the health ministry (i.e. the number of people waiting for cure and/or
care). This leads to a situation where an organization which can hardly be assessed on
outcome indicators, is nevertheless by its environment assessed on such criteria and
consequently undermines its own legitimacy. That this is the case Netherlands is
reflected in many newspaper articles and political commentaries:
P3. Not every organization in the field of cure or care has by definition an
interest in reducing waiting lists
A third assumption which is characteristic for the discussion about responding to waiting
lists is that waiting are believed to be seen as something negative by the organizations
concerned. Although this might be a wishful situation, on the basis of what organization
theories learn us, it has to be concluded that this is far from necessarily the case. The fact
that waiting lists are the result of an organized and interdependent care and cure field does
not yet mean thata care- and cure-fieldwide norm exists which says that waiting lists have
to be eliminated (what Scharpf (1994) calls a “system rationality”). In addition, from a
theoretical point of view, there is no necessity why organizations in the care and cure field
should see the elimination of waiting lists as one of their central goals. This point has
extensively been put forward by those organizational researchers, which use the political
metaphor to analyze organizational behavior (Lammers, 1993; March and Olsen, 1984).
Such a model describes inter- and intra-organizational systems as a conglomeration of
parties. Here norm orientation is not seen as the driving force of organizations or
inter-organizational fields.
The fact that groups within organizations or the organizations within
organizational fields behave as “parties is explained in the organizational literature
along different lines. It could result from the fact that they have to take different
stakeholders into account (Provan and Milward, 1995, pp. 10, 21). Or, by the fact that
the earlier described interdependencies constitutes a source of uncertainty, which is
reduced through strategic behavior (Chisholm, 1989, p. 43).
In what follows, I will illustrate that the responses to long waiting lists in the Dutch
cure and care sector are, in the first place, not characterized by a “system rationality”
but rather by “partial interests” (Scharpf, 1994). What shall become clear is that when
policy makers assume the existence of a system rationality, which in practice is absent,
JHOM
20,4
300
however, does probably more harm than good. This point will be demonstrated by
describing in short the type of interests different stakeholders can have with respect to
the reduction of waiting lists.
Patients
A survey carried out by NIPO shows that 65 percent of the persons asked consider
waiting lists in care and cure unacceptable (Metro, 2000). Interesting is, however, that
those who have probably the highest interest in the reduction of waiting lists are at the
same time the least organized group in the care and cure field. Patients have indeed
some alternatives in dealing with waiting lists (e.g. treatment in other countries, legal
procedures and access to a small number of private clinics). Such alternatives are,
however, only realistic to a limited extend, they produce (often substantial) extra costs
for the patients and can be expected to increase conflicts of interests in a Dutch context.
Ministry of VWS (Dutch Health Ministry)
It is clear that the ministry itself is a conglomerate of many different interests, but in
general it could be said that the ministry as such has an interest in the reduction of waiting
lists. The ministry is formally speaking responsible for the quality, the accessibility and
the efficacy of cure and care. On the other hand, cost containment is always also seen as
one of their main goals. Consequently, it could be stated that the longer the waiting lists are
the better the cost containment goal is reached[3]. On the basis of a rational organization
approach it seems impossible to reconcile two goals which are so contrary. Approaches
inspired by neo-institutional thinking argue, however, that this should not necessarily be a
problem: administrations are not in the first place assessed or rewarded on the basis of
their output or outcome but on whether or not they have tackled a problem (Kneissler,
1996, p. 144). Or as Lindblom (1959) formulated it: ... the test of a good policy is whether it
commands sufficient support to be adopted, not whether it will actually achieve some
grand objective.”. Or, as stated by the “radical institutionalist” Brunsson (1989, pp. 233-4):
“Sin and hypocrisy are necessary to the creation and preservation of high morals” and are
consequently important in the survival strategy of political organizations[4].
Medical doctors
The most important aim for doctors is to be able to provide services of high quality to
those who need them most. Doctors, who are, as a result of the long waiting lists, not
anymore able to provide these types of services will presumably give high priority to
the reduction of waiting lists. But there are also good reasons why it is not interesting
for doctors to tackle waiting lists. This is, for example, the case for those doctors which
so far have no waiting lists and who would have to make sacrifices in their available
capacities when others start tackling waiting lists[5]. Another reason why doctors not
necessarily have an interest in an active response to waiting lists has to do with the fact
that they are in the first place confronted with disciplinary courts which judge them on
the patients they have treated and not on the patients they have not treated.
Health insurance companies
Also for insurance companies there can be at the same time reasons why they could be
interested in tackling waiting lists and reasons why they should not be interested in doing
so. Announcing responses to waiting lists can be interesting for competitive reasons
Waiting lists in
Dutch health
care
301
(given the fact that health insurance companies in The Netherlands are private companies)
or in order to anticipate court rulings. On the other hand, it can be observed that insurance
companies so far have taken hardly any structural measures to deal with waiting lists.
This provoked the following statement by surgeon de Brauw (2001, pp. 36-7): “... when
budgets are tight, is the cheapest patient the non-treated patient” (own translation).
Care and cure providers
Also for the care and cure providers it cannot be stated by definition, that they have an
interest in reducing waiting lists. Take the example of a hospital as an organization
being characterized by diverging interests. This means that it is often the case that
each unit works for itself and nobody necessarily is interested in the end result.
Surgeon De Brauw (2001):
A unit with empty beds does as a rule not take patients from a unit which is more than fully
occupied. The atmosphere in a hospital is characterized by a each for itself-attitude of the
different units.
Moreover, the fact that hospitals are not necessarily interested in the reduction of waiting
lists is also related to the regulatory regime in which they have to operate. Given the design
of the regime, hospitals have no interest in treating more patients. The financing of
hospitals in The Netherlands is not based on their primary process, i.e. treatment
of patients, but is in the first place based on their facilities and services such as the number
of specialists, the costs of the building, the kitchen, the pharmacy, the heating, etc. The
consequence of such a regulation is that a hospital has no incentive in carrying out
surgeries, which are better for the patient (e.g. in terms of admission duration, pain, and
revalidation) when they are more expensive. Since, no real tariffs for the treatment of
patients are calculated and since hospitals do not receive a financial compensation for
services and treatments a more expensive form of treatment automatically means a larger
cost for the hospital. In addition, a hospital does receive part of its budget on the basis of
the admission duration which also means that surgeries which result in shorter admission
time are less interesting for the hospital. All this means that hospitals not only do not
necessarily have an interest in reducing waiting lists but that they often even have
incentives to contribute to increasing the length of waiting lists.
The above should not be read as an accusation of egoistic parties but rather as a
confirmation of claims made by organization theory, i.e. that organizations and
inter-organizational relations are often characterized by different, divergent and
incompatible interests on the basis of which it becomes difficult to implement
strategies in a predefined manner.
So far it has been argued that organization theory could explain why tackling waiting
lists in cure and care is much less straightforward than is generally assumed. The
question remains, however, whether organization theory can also contribute insights
with regard to how waiting lists could actually be tackled. This questions leads to P4:
P4. In order to reduce the w aiting lists, instead of managing those waiting,
it is important to manage the interdependencies of the organizational field
On the basis of organization theory, solving problems is a matter of coordination[6].
As should have become clear from P1, P2 and P3 there are different fundamental
reasons why coordination in the case of the waiting lists is far from straightforward.
JHOM
20,4
302
What would be needed, again on the basis of the previous analysis, is a form of
coordination, which helps to solve problems in situations, which are characterized by
complexity, a large number of organizations and even more interests.
The reasoning by policy makers is often different. Historically, the reaction to this
kind of situations has often been that better coordination is needed; this on its turn has
often resulted in a plead for reducing fragmentation, to improve the integration of
organizations and to improve vertical control (Chisholm, 1989, p. 17; Mayntz, 1993;
Kenis and Schneider, 1991). What is striking is that improved coordination is often
equated with more centralization: “Where a need for coordination is perceived, the
reflexive response is centralization” (Chisholm, 1989, p. 13).
Organization science does certainly not question the fact that a proper response to a
problem such as waiting lists requires more coordination. Also is centralization not by
definition seen as an ineffective way of coordination (Mintzberg, 1979; Perrow, 1986:
Chapter 1). What is, however, questioned in organization science is that improved
coordination can only be achieved by improved centralization or that the market is the best
coordination mechanism by definition. Also will organization science avoid relapsing in a
pessimistic nihilism when confronted with chaos and complexity (Sanderson, 2000, p. 445).
What organization science can contribute, is to produce a diagnosis of the problem
in order to propose an effective form of coordination. Different approaches differ with
respect to what should be central in such a diagnosis. Diagnosis can be based on a
logistic approach (Laeven et al., 2000a; Vissers, 2000), they can be based on the
strategic capacities of organizations (Ganz, 2000), they can be based on power
differences within and between organizations (Perrow, 1986: Chapter 8), or they can be
based on approaches to increase the efficiency of single organizations (Groot, 2001), etc.
What I propose as a basis for the diagnosis of the waiting list phenomenon is an
analysis of the interdependency of the organizational field in which waiting lists are
produced[7]. The choice of interdependence as a criterion for diagnosis relates to the
assumption that inter-organizational systems are more effective when the form of
coordination is congruent with the type and degree of interdependency; and this
according to the following rule: the more interdependency, the more coordination but
never more than absolute necessary (Chisholm, 1989, p. 191).
On the basis of this perspective, the design of coordination mechanisms as an
answer to problems, without a diagnosis of the type and degree of interdependence or
on the basis of wrong assumptions about these interdependencies, can be a risky and
expensive enterprise (see in this respect Simon’s (1973) analysis about dealing with
ill-structured problems). This could entail the nucleus for an explanation for the
ineffective response to waiting lists, i.e. that the approach to deal with waiting lists is
characterized by a discrepancy between de degree of interdependence of the problem
and the type and of coordination of the response.
Central coordination in the governance of highly interdependent systems is from an
organizational theory point of view for different reasons problematic. Simon (1969,
1973) argued that a high level of interdependency is “deviation amplifying,” which
means that a change in one part can reproduce itself throughout the entire system in an
uncontrolled manner and thus can produce unintended negative consequences. Central
governance implies also that things have to be done which are virtually impossible:
having available an action plan on the basis of cause-effect relationships; effective
communication to those who have to implement the action plan; and, making sure that
Waiting lists in
Dutch health
care
303
the plan is accepted by those who have to implement it (see P1, P2 and P3 and
Chisholm, 1989, p. 29).
Apart from the fact that central coordination seems not to be effective in situations of
high interdependency, it can moreover produce rather negative consequences. Central
coordination can artificially increase the interdependency between the different
components. The consequence being that ever more coordination is needed among a
broader spectrum of interests, which increases the cognitive complexity even more.
On the contrary, a diagnosis could help to reduce the complexity of the system, which
implies that less coordination, becomes necessary. Simon (1969) claims that even the
most interdependent systems are “often nearly decomposable.” Often interdependencies
can be reduced in such ways that only loose ties remain and consequently the cognitive
complexity of the problem is decreased. This means on its turn that less heavy
coordination mechanisms can be used to arrive at a satisfactory level of coordination.
Such a perspective means that diagnosis implies in the first place collecting information
on the basis of which it becomes possible to assess whether existing interdependencies
in decision making can be separated. This means that already the diagnosis of
interdependency can increase the chance for effective coordination (Chisholm, 1989,
pp. 53-4). Relevant aspects of interdependency in such a diagnosis are: the number of
parties in the system, the type of interdependency (bilateral or multilateral), the
circumstances under which interdependencies appear and the forms of interdependency
(natural, artificial and voluntary interdependency) (Chisholm, 1989, pp. 190-1). On the
basis of network analysis such interdependencies could be mapped and analyzed (Kenis
and Knoke, 2002; Scott, 2000; Brandes et al., 1999). On the basis of such a diagnosis two
things can be done: “decomposing” of the system and consequently research into simpler
forms of coordination. Such an approach aims to reduce the cognitive complexity of the
problem (P1), which implies also that the number of parties which is necessary to arrive
at a satisfactory solution, decreases (P3). This also means that the potential number of
conflicts of interests decreases (Chisholm, 1989, p. 54)[8].
In order to make the above argument somewhat more concrete I present a couple of
initiatives which aim at the reduction of the waiting lists and which are, probably
unconsciously, based on such an interdependency approach.
One of the often-heard reactions to waiting lists is “getting around the rules.”
Getting around the rules is often nothing else than decreasing interdependency. See, for
example, the article which appeared in a national newspaper with the title “Health care
is ripe for civil disobedience” (own translation):
Patients have to be washed before 10 a.m. and have had their breakfast ... This produces
enormous peaks for the staff. If you explain to a patient that a care institution is a more
satisfactory working place if the times in which care has to be provided is managed
somewhat more flexible, the client shall readily accept to get his slice of bread a little bit later
(Volkskrant, 2001).
A similar example is the “brutal way of care assignment in Flevoland”:
Such a care assignment team is a most effective example to tackle waiting list ... They look
for empty places and empty hours, and if the indicated care is not available at that moment,
than we check which type of care is available at that moment ... Only later we are concerned
about the budget-line which will cover it ... (Nieuwsbrief aanpak wachtlijsten, 2001).
JHOM
20,4
304
These are just some examples which demonstrate the more general point, i.e. that
dealing with waiting-lists could be less dependent on a “epidemiology” of those waiting
than on an “epidemiology” of the interdependencies of the system. In case the
assumption about the importance of interdependence is adequate, it seems reasonable
to test reforms and initiatives on their interdependency effects. Also considering that it
is hardly possible to test new strategies and initiatives on their effects on the length of
waiting lists, it seems more appropriate to test new strategies and initiatives on their
effects on the interdependency of the health care system.
Findings of this paper might be relevant beyond the field of waiting lists in Dutch
health care. It has been regularly observed that the health care systems in particular
and any larger policy field in general is very difficult to reform or that tackling
problems within such systems often fails. What is demonstrated here, is that more
attention should be devoted to the behavior and the structure of organizations in
the analysis and management of such cases. Often broader strategies and policies are
based on assumptions, which do not comport with the actual behavior of organizations.
Given the central position organizations have in such strategies and policies they are
thus doomed to fail almost by definition. What is suggested here is that the situation of
organizations in general and their interdependency relations in particular have to be
understood in order to produce effective strategies or policies.
Notes
1. In a population of approximately 16,000,000.
2. One can distinguish between planning waiting lists and “problematic” waiting lists. With
the help of planning waiting lists a provider can tune the stream of clients in such a way that
the capacity of the organization is optimally used and the working-load of the personnel is
not too much subject to fluctuations (Laeven and van Rooij, 1999). Problematic waiting lists
are characterized by the fact that acceptable waiting times are exceeded. Whenever in this
text waiting lists are mentioned I refer to “problematic waiting lists.”
3. Especially in the economic literature are waiting lists often seen as a “alternative rationing
device” (Martin and Smith, 1999).
4. Brunsson (1989, p. 19) defines political organizations as follows: “This organization has no
need at all to produce coordinated action; its only basis for legitimation is that it reflects
inconsistent norms. Instead of seeking niches like the action organization and satisfying one
need or interest at a time, the political organization reflects a variety of ideas and demands
and satisfies the expectations of diverse groups in its environment.”
5. As is illustrated in the following observation by a surgeon: “Also the discussion with other
specialists about the redistribution of capacities turns out to be to sensitive. The breast
reduction operation of a 75-year-old patient by a plastic surgery produces a lot of discussion
in my hospital. Is such an operation necessary given the fact that our cancer patients have to
wait too long for their surgery?” (own translation, de Brauw, 2001, p. 18)
6. Coordination means ... to place things in proper position relative to each other and to the
system of which they form parts-to bring into proper combined order as parts of a whole.
It means, in essence, to bring about some kind of order ... (Chisholm, 1989, p. 13) and
coordination describes both a process the act of coordinating and a goal. If coordination
is considered as an end state, the result of some process, it is defined as “harmonious
combination of agents or functions toward the production of a result” (Chisholm, 1989, p. 28).
7. Interdependence can be defined as follows: “Within each set, each decision-maker is in such a
relation to each other decision-maker that unless he deliberately avoids doing so (which may
Waiting lists in
Dutch health
care
305
or may not be possible), he interferes with or contributes to the goal achievement of each
other decision-maker, either by direct impact or through a chain of effects that reach any
given decision-maker only through effects on others” (Lindblom, 1965, pp. 21-2).
8. This is by the way also consistent with a radical-institutionalist point of view, which states
that it is not necessarily advantageous that parties are interdependent. Brunsson (1989,
p. 230) states, for example, that: “If managers and ‘actors’ are kept apart, life is easier for both
parties” and ... to change products is a difficult organizational action, and action is the
weakness of organizations whose main strength is politics.”
References
Boyne, G. and Gould-Williams, J. (2001), “Planning and performance in public organisations: an
empirical analysis”, paper presented at the Fifth International Research Symposium in
Public Management, Barcelona.
Brandes, U., Kenis, P. and Wagner, D. (1999), “Centrality in policy network drawings”,
Proceedings of the 7th Symposium on Graph Drawing (GD’99), Lecture Notes in Computer
Science, 1731, Springer Verlag, New York, NY.
Breedveld, E. et al. (2000), Invloed op de wachtlijst, ZorgOnderzoek Nederland, Den Haag.
Brunsson, N. (1985), The Irrational Organization, Wiley, Chichester.
Brunsson, N. (1989), The Organization of Hypocrisy, Wiley, Chichester.
Chisholm, D.W. (1989), Coordination without Hierarchy; Informal Structures in
Multiorganizational Systems, University of California Press, Oxford.
Cohen, M., March, J.G. and Olsen, J.P. (1972), “A garbage can model or rational choice”,
Administrative Science Quarterly, Vol. 17 No. 1, pp. 1-25.
de Brauw, M. (2001), De wachtlijst en andere gezondheidszorgen, Uitgeverij G.A. van Oorschot,
Amsterdam.
FEM/DeWeek (2000), “De rugzakpatie
¨
nt”, FEM/DeWeek, July 5.
Frankel, S. (1991), “Health needs, health-care requirements, and the myth of infinite demand”,
Lancet, Vol. 337, pp. 1588-90.
Ganz, M. (2000), “Resources and resourcefulness: strategic capacity in the unionization of
California agriculture, 1959-1966”, American Journal of Sociology, Vol. 105 No. 4,
pp. 1003-62.
Globerman, S. (1991), “A policy analysis of hospital waiting lists”, Journal of Policy Analysis and
Management, Vol. 10 No. 2, pp. 247-62.
Groot, W. (2001), “Gezondheidszorg presteert ver beneden beschikbare capaciteit”, de Volkskrant,
Augustus 2.
Kenis, P. (2001), “The case of HIV and blood supply in Germany”, in Bovens, M., t’Hart, P. and
Peters, G. (Eds), Success and Failure in Public Governance: A Comparative Analysis,
Edward Elgar, Aldershot.
Kenis, P. and Knoke, D. (2002), “How organizational field networks shape interorganizational
tie-formation rates”, Academy of Management Review, Vol. 27 No. 2, pp. 275-93.
Kenis, P. and Schneider, V. (1991), “Policy networks and policy analysis: scrutinizing a new
analytical toolbox”, in Marin, B. and Mayntz, R. (Eds), Policy Networks: Empirical Evidence
and Theoretical Considerations, Campus/Westview, Frankfurt am Main/New York, NY,
pp. 25-59.
Kerseboom, J. and Geelen, K. (2000), “Ik voel me, zeg maar, machtiger”, Maandblad Geestelijke
Volksgezondheid, Vol. 55 No. 1, pp. 27-39.
JHOM
20,4
306
Kneissler, T. (1996), Verwaltungen jenseits der Zweckrationalita
¨
t, Nomos Verlagsgesellschaft,
Baden-Baden.
Laeven, A.M.W. and van Rooij, P.M. (1999), Wachtlijsten voor medisch-specialistische zorg in
ziekenhuizen. Resultaten van de landelijke enque
ˆ
te patie
¨
ntenwachtlijsten per 1 maart 1999,
Nzi, Utrecht.
Laeven, A.M.W. et al. (2000a), De achterkant van de wachtlijst. Een verkennend onderzoek naar de
achterliggende factoren van de wachtlijstproblematiek, Prismant, Utrecht.
Laeven, A.M.W. et al. (2000b), Het wachtlijstfonds 1999. De Derde Inhaalslag, Prismant, Utrecht.
Lammers, C.J. (1993), Organiseren van bovenaf en van onderop, Het Spectrum B.V., Utrecht.
Lindblom, C.E. (1959), “The science of ‘muddling through’”, Public Administration Review,
Vol. 19, pp. 79-99.
Lindblom, C.E. (1965), The Intelligence Of Democracy. Decision Making Through Mutual
Adjustment, Free Press, New York, NY.
McKevitt, D. and Lawton, A. (1996), “The manager, the citizen, the politician and performance
measures”, Public Money & Management, Vol. 16 No. 3, pp. 49-54.
March, J.G. and Olsen, J.P. (1984), “Organizing political life: what administrative reorganization
tells us about government”, American Political Science Review, Vol. 88, pp. 281-96.
March, J.G. and Simon, H.A. (1958), Organizations, Wiley, New York, NY.
Martin, S. and Smith, P.C. (1999), “Rationing by waiting lists: an empirical investigation”, Journal
of Public Economics, Vol. 71, pp. 141-64.
Mayntz, R. (1993), “Governing failures and the problem of governability: some comments on a
theoretical paradigm”, in Kooiman, J. (Ed.), Modern Governance. New Government-Society
Interactions, Sage, London, pp. 9-20.
Metro (2000), “Onderzoek: thuiszorg voor veel verbetering vatbaar”, Metro, Maart 20.
Meyer, J.W. and Rowan, B. (1977), “Institutionalized organizations: formal structure as myth and
ceremony”, American Journal of Sociology, Vol. 83, pp. 340-63.
Ministerie van VWS (2001a), Jaarbeeld Zorg 2000, Ministerie van VWS, Den Haag.
Ministerie van VWS (2001b), Vraag aan bod. Hoofdlijnen van vernieuwing van het zorgstelsel,
Ministerie van VWS, Den Haag.
Mintzberg, H. (1979), The Structuring of Organizations, Prentice-Hall, Englewood Cliffs, NJ.
Mintzberg, H. (1987), “The strategy concept II: another look at why organizations need
strategies”, California Management Review, Vol. 16, pp. 44-53.
Newton, J.N. et al., (1996), “Waiting list dynamics and the impact of earmarked funding”,
British Medical Journal, Vol. 311, pp. 783-5.
Nieuwsbrief aanpak wachtlijsten (2001), Nieuwsbrief aanpak wachtlijsten, Ministerie van VWS
(Ministry of Health, Welfare and Sports), The Hague.
NIZW (2000), Thesaurus zorg en welzijn 2001, NIZW, Utrecht.
Perrow, C. (1986), Complex Organizations: A Critical Essay, Random House, New York, NY.
Pickin, M. et al., (2001), “‘General practitioners’ reasons for removing patients from their lists:
postal survey in England and Wales”, British Medical Journal, Vol. 322 No. 12.5, pp. 1158-9.
Powell, W.W. and DiMaggio, P.J. (1991), The New Institutionalism in Organizational Analysis,
The University of Chicago Press, Chicago, IL.
Provan, K.G. and Milward, H.B. (1995), “A preliminary theory of interorganizational network
effectiveness: a comparative study of four community mental health systems”,
Administrative Science Quarterly, Vol. 40, pp. 1-33.
Waiting lists in
Dutch health
care
307
Sanderson, I. (2000), “Complexity, evaluation and evidence-based policy”, paper presented for the
European Evaluation Society Conference, Lausanne.
Scharpf, F.W. (1994), “Politiknetzwerke als steuerungssubjekte”, in Derlien, H. et al. (Eds),
Systemrationalita
¨
t und Partialinteresse, Nomos Verlagsgesellschaft, Baden-Baden,
pp. 381-407.
School, M.A.A. (2000), Openbaarmaking wachttijden via kabeltelevisie, Prismant, Utrecht.
Scott, J. (2000), Social Network Analysis. A Handbook, Sage, London.
Simon, H.A. (1962), “The architecture of complexity”, Proceedings of the American Philosophical
Society, Vol. 106, pp. 467-82.
Simon, H.A. (1965), Administrative Behavior, Free Press, New York, NY.
Simon, H.A. (1969), The Sciences of the Artificial, MIT Press, Cambridge, MA.
Simon, H.A. (1973), “The structure of ill structured problems”, Artificial Intelligence, Vol. 4,
pp. 181-201.
Simon, H.A. (1983), Reason in Human Affairs, Stanford University Press, Stanford, CA.
Smethurst, D.P. and Williams, H.C. (2001), Power laws: are hospital waiting lists
self-regulating?”, Nature, Vol. 410, pp. 652-3.
Taskforce aanpak wachtlijsten (2000), Analyse landelijke inventarisatie wachtlijstgegevens
verpleging en verzorging, Rapport, Den Haag.
Taskforce aanpak wachtlijsten (2001), Analyse landelijke inventarisatie wachtlijstgegevens
verpleging en verzorging, Rapport, Den Haag.
The Economist (2001a), “Missing the point”, The Economist, April 28.
The Economist (2001b), “The trouble with targets”, The Economist, April 28.
Vissers, J. (2000), “Ketengericht wachtlijstmanagement”, in Boon, L. (Ed.), Ontwikkelingen in de
gezondheidszorg. Vraagsturing en zorgketens, Stichting Sympoz, Amstelveen, pp. 89-96.
Volkskrant (2001), “Ziekenzorg is toe aan ‘burgerlijke ongehoorzaamheid’”, Volkskrant, February
22.
Weick, K.E. (1979), The Social Psychology of Organizing, Addison-Wesley, Reading, MA.
Wildavsky, A. (1973), “If planning is everything, maybe its nothing”, Policy Sciences, Vol. 4,
pp. 127-53.
Wood, T.J. and Thomas, S.C. (1985), “Waiting lists an overview”, Australian Health Review,
Vol. 8 No. 2, pp. 88-95.
Yates, J. (1991), “Lies, damned lies and waiting lists”, British Medical Journal, Vol. 303, p. 802.
Further reading
Trouw (2000), “Hogere dosis bestraling om wachtlijsten te bekorten”, Trouw, September 21.
Corresponding author
Patrick Kenis can be contacted at: p.kenis@uvt.nl
JHOM
20,4
308
To purchase reprints of this article please e-mail: reprints@emeraldinsight.com
Or visit our web site for further details: www.emeraldinsight.com/reprints
... Preferably, this could be done in collaboration with care providers. Distribution of guidelines without mechanisms to foster adherence might create a feeling of false security for guideline developers or administrative management [25]. The true waiting times might be hidden from view. ...
... Care providers suggested that steps taken to correct waiting times should be based on an analysis of causes of long waiting times rather than regulated though economic sanctions. This aligns with earlier studies highlighting that data presentation is not enough to shorten queues [25]. ...
... Empirical studies show that waiting lists themselves [32,33] and exception codes [34] are open to manipulation. Some show that complying with data collection may primarily aim to meet expectations rather than improve services [35], especially if presentation of data is combined with an incentive system [25]. Furthermore, care providers have been seen to game waiting list reporting even though it had economic disadvantages (i.e., they would have been given increased funding if the true length of the queues were known) [34]. ...
Article
Full-text available
Background Access to health care is an essential health policy issue. In several countries, waiting time guarantees mandate set time limits for assessment and treatment. High-quality waiting time data are necessary to evaluate and improve waiting times. This study’s aim was to investigate health care providers and administrative management professionals’ perceptions of validity and usefulness of waiting time reporting in specialist care. Methods Semi-structured interviews (n = 28) were conducted with administrative management and care professionals (line managers and care providers) in specialized clinics in the Stockholm Region, Sweden. Clinic-specific data from the waiting time registry was used in the care provider interviews to assess face validity. Clinics were purposefully sampled for maximum variation in complexity of care, volume of production, geographical location, private or public ownership, and local waiting times. Thematic analysis was used. Results The waiting time registry was perceived to have low validity and usefulness. Perceived validity and usefulness were interconnected, with mechanisms that reinforced the connection. Structural and cognitive barriers to validity included technical and procedural errors, errors caused by role division, misinterpretation of guidelines, diverging interpretations of nonregulated cases and extensive willful manipulation of data. Conclusions We identify four misconceptions underpinning the current waiting time reporting system: passive dissemination of guidelines is sufficient as implemented, cognitive load of care providers to report waiting times is negligible, soft-law regulation and presentation of outcome data is sufficient to drive improvement, and self-reported data linked to incentives poses a low risk of data corruption. To counter low validity and usefulness, we propose the following for policy makers and administrative management when developing and implementing waiting time monitoring: communicate guidelines with instructions for operationalization, address barriers to implementation, ensure quality through monitoring of implementation and adherence to guidelines, develop IT ontology together with professionals, avoid parallel measurement infrastructures, ensure waiting times are presented to suit management needs, provide timely waiting time data, enable the study of single cases, minimize manual data entry, and perform spot-checks or external validity checks. Several of these strategies should be transferable to waiting time monitoring in other contexts.
... Practices related to the Process dimension. According to organizational theory, solving business problems is a matter of coordination (19). In most studies, policymakers intended to reduce process fragmentation, improving integration and vertical control (23). ...
... However, the long waiting lists prevent them from providing high-quality service to their patients. In this context, they will presumably give high priority to reducing waiting lists (19). ...
Article
Full-text available
Objective To identify the managerial actions proposed and employed to reduce the waiting time to initiate oncological treatments in the public health system and its application in Latin America. Method We searched seven databases in December 2020. Search terms were conceptualized into three groups: waiting time, cancer, and terms related to public sector. The eligibility criteria included theoretical or empirical academic articles written in English, Spanish, or Portuguese, that focused on managerial solutions to face oncological healthcare queues' dilemma. Results The search returned 1 255 articles, and 20 were selected and analysed in this review. Results show that most of the proposals are related to the process and people dimensions. The actions related to the process dimension were mainly associated with programming new treatment pathways and integrating cancer systems. People's dimension initiatives referred mostly to task forces and groups of specialists. Some initiatives were related to implementing technological solutions and the technology dimension, mainly concerning radiotherapy devices' acquisition. Conclusion Few studies focus on analysing actions to minimize waiting time to initiate oncological treatments. The prevalence of conceptual and illustrative case studies indicates the lack of research maturity on this theme. Future studies should focus on setting the field's theoretical foundations, considering the existing paradigms, or developing new ones. There is a need for empirical studies applying a multidisciplinary approach to face the oncological treatment waiting time challenge and proposing new and innovative initiatives.
... Previous research with much larger investments to tackle waiting lists by reducing backlogs has been ineffective. 7 31 Kenis argued that attempts to combat waiting lists by simply adding resources to increase supply without changes to service delivery ignores the complexity of the problem. 31 The reduction in waiting time, at minimal cost to the health system, supports previous findings that waiting times are not typically a result of lack of capacity, but related to suboptimal allocation of resources. ...
... 7 31 Kenis argued that attempts to combat waiting lists by simply adding resources to increase supply without changes to service delivery ignores the complexity of the problem. 31 The reduction in waiting time, at minimal cost to the health system, supports previous findings that waiting times are not typically a result of lack of capacity, but related to suboptimal allocation of resources. 32 Shorter waiting times have been shown to be associated with improved patient outcomes and may alleviate some of the anxiety patients experience while awaiting health interventions. ...
Article
Full-text available
Objectives: Timely access to outpatient services is a major issue for public health systems. To address this issue, we aimed to establish the return on investment to the health system of the implementation of an alternative model for access and triage (Specific Timely Appointments for Triage: STAT) compared with a traditional waitlist model. Design: Using a prospective pre-post design, an economic analysis was completed comparing the health system costs for participants who were referred for community outpatient services post-implementation of STAT with a traditional waitlist comparison group. Setting: Eight community outpatient services of a health network in Melbourne, Australia. Participants: Adults and children referred to community outpatient services. Interventions: STAT combined targeted activities to reduce the existing waiting list and direct booking of patients into protected assessment appointments. STAT was compared with usual care, in which new patients were placed on a waiting list and offered appointments as space became available. Outcomes: Health system costs included STAT implementation costs, outpatient health service use, emergency department presentations and hospital admissions 3 months before and after initial outpatient appointment. Waiting time was the primary outcome. Incremental cost-effectiveness ratios (ICERs) were estimated from the health system perspective. Results: Data from 557 participants showed a 16.9 days or 29% (p<0.001) reduction in waiting time for first appointment with STAT compared with traditional waitlist. The ICER showed a cost of A10(95A10 (95% CI -19 to 39) per day reduction in waiting time with STAT compared with traditional waitlist. Modelling showed the cost reduced to A4 (95% CI -25 to 32) per day of reduction in waiting, if reduction in waiting times is sustained for 12 months. Conclusions: There was a significant reduction in waiting time with the introduction of STAT at minimal cost to the health system. Trial registration number: Australian New Zealand Clinical Trials Registry (ACTRN12615001016527).
... Ancak bu önlemler, sağlık hizmetlerinde arz ve talep arasındaki temel dengesizlikleri ele almadığı için yalnızca geçici bir rahatlama sağlamaktadır. Ek kaynakların geri çekilmesinin ardından, bekleme listelerinin tekrar ortaya çıkması kaçınılmazdır (Kenis, 2006). Dolayısıyla, bekleme sürelerini yönetmek ve hastaların zamanında hizmet almasını sağlamak için sistematik ve uzun vadeli çözümlere ihtiyaç duyulmaktadır. ...
Article
Full-text available
Bu çalışmada, bir üniversite hastanesinin nöroloji polikliniğindeki bekleme sürelerini azaltmak ve hizmet verimliliğini artırmak amacıyla M/M/m ve G/G/m kuyruk teorisi modelleri incelenmiştir. Farklı doktor sayıları ve hasta yoğunluğu senaryoları değerlendirilmiş, her iki modelin performansı analiz edilmiştir. Düşük ve orta yoğunluk senaryolarında, G/G/m modelinin daha esnek ve etkili olduğu, bekleme sürelerini ve kuyruk uzunluklarını daha düşük seviyelerde tuttuğu gözlemlenmiştir. M/M/m modeli ise düşük yoğunlukta iyi sonuçlar verse de özellikle yüksek hasta yoğunluğu altında kararsızlık göstermiştir. Analizler, doktor sayısının 9 ila 10 arasında tutulmasının, bekleme sürelerini azaltmada ve hizmet verimliliğini artırmada optimal sonuçlar sağladığını ortaya koymuştur. Yüksek yoğunluk senaryolarında ise her iki modelin de yetersiz kalması, daha gelişmiş simülasyon ve optimizasyon yöntemlerinin kullanılmasını gerekli kılmaktadır. Sonuç olarak, poliklinik hizmet süreçlerinin optimize edilmesi için doktor sayısının dikkatli planlanması, hizmet sürelerindeki belirsizliklerin azaltılması ve G/G/m modelinin tercih edilmesi önerilmektedir. Bu çalışma, operasyonel verimliliğin artırılması ve hasta memnuniyetinin iyileştirilmesi adına önemli stratejiler sunmaktadır. Abstract In this study, M/M/m and G/G/m queueing theory models are investigated to reduce waiting times and improve service efficiency in the neurology outpatient clinic of a university hospital. Different number of doctors and patient density scenarios are evaluated and the performance of both models is analyzed. In low and medium density scenarios, the G/G/m model was found to be more flexible and efficient, keeping waiting times and queue lengths at lower levels. The M/M/m model, on the other hand, showed good results at low density, but showed instability, especially under high patient density. The analysis revealed that keeping the number of doctors between 9 and 10 provides optimal results in reducing waiting times and improving service efficiency. In high density scenarios, both models are inadequate, necessitating the use of more advanced simulation and optimization methods. As a result, it is recommended that the number of doctors should be carefully planned, uncertainties in service times should be reduced and the G/G/m model should be preferred to optimize outpatient service processes. This study provides important strategies for increasing operational efficiency and improving patient satisfaction.
... True capacity shortages are actually infrequent as waiting lists remain constant and do not increase over time without stabilising, which would be the case if demand outstripped capacity [15,16]. Understanding the mechanisms behind queuing and waiting times is therefore crucial [11,17], as is matching demand and capacity more effectively [15]. Waiting lists and waiting times can thus be reduced by acquiring knowledge about accessibility and monitoring demand and capacity variations [16]. ...
Article
Full-text available
Background The aim of this paper is to develop a maturity model (MM) for demand and capacity management (DCM) processes in healthcare settings, which yields opportunities for organisations to diagnose their planning and production processes, identify gaps in their operations and evaluate improvements. Methods Informed by existing DCM maturity frameworks, qualitative research methods were used to develop the MM, including major adaptations and additions in the healthcare context. The development phases for maturity assessment models proposed by de Bruin et al. were used as a structure for the research procedure: (1) determination of scope, (2) design of a conceptual MM, (3) adjustments and population of the MM to the specific context and (4) test of construct and validity. An embedded single-case study was conducted for the latter two - four units divided into two hospitals with specialised outpatient care introducing a structured DCM work process. Data was collected through interviews, observations, field notes and document studies. Thematic analyses were carried out using a systematic combination of deductive and inductive analyses - an abductive approach - with the MM progressing with incremental modifications. Results We propose a five-stage MM with six categories for assessing healthcare DCM determined in relation to patient flows (vertical alignment) and organisational levels (horizontal alignment). Our application of this model to our specific case indicates its usefulness in evaluating DCM maturity. Specifically, it reveals that transitioning from service activities to a holistic focus on patient flows during the planning process is necessary to progress to more advanced stages. Conclusion In this paper, a model for assessing healthcare DCM and for creating roadmaps for improvements towards more mature levels has been developed and tested. To refine and finalise the model, we propose further evaluations of its usefulness and validity by including more contextual differences in patient demand and supply prerequisites.
... Most of them make no particular reference to children with CP and infrequently to vulnerable and complex patients. Furthermore, measures taken to resolve this problem have not been successful [15], even in European countries that belong to the high resource category [12]. ...
... Interventions to reduce waiting time have been reported across a diverse range of services, providing a growing body of evidence to suggest that lengthy waitlists are not inevitable [3][4][5]. A key issue is that evaluations of interventions to reduce delays and improve patient flow in outpatient settings rarely report on sustainability [6] despite the risk that once resources to address the problem are withdrawn, waitlists and delays can return [7]. Given the importance of prompt care for those with suspected or confirmed epilepsy, interventions that lead to sustained reductions of waiting time are imperative. ...
Article
Full-text available
Purpose Delays in outpatient specialist neurologist care for people with epilepsy are common despite recommendations for prompt access. There is evidence to suggest that there are interventions that can minimise waitlists and waiting time. However, little is known about whether such interventions can result in sustained improvements in waiting. The aim of this study was to determine the extent to which an intervention to reduce waiting in an epilepsy specialist outpatient clinic demonstrated sustained outcomes two years after the intervention was implemented. Methods This observational study analysed routinely collected epilepsy clinic data over three study periods: pre-intervention, post-intervention and at two-year follow-up. The intervention, Specific Timely Assessment and Triage (STAT), combined a short-term backlog reduction strategy and creation of protected appointments for new referrals based on analysis of demand. After the initial intervention, there was no further active intervention in the following two years. The primary outcome was waiting measured by 1.) waiting time for access to a clinic appointment, defined as the number of days between referral and first appointment for all patients referred to the epilepsy clinic during the three study periods; and 2.) a snapshot of the number of patients on the waitlist at two time points for each of the three study periods. Results Two years after implementing the STAT model in an epilepsy clinic, median waiting time from post-intervention to two-year follow-up was stable (52–51 days) and the interquartile range of days waited reduced from 37 to 77 days post-intervention to 45–57 days at two-year follow-up, with a reduction in the most lengthy wait times observed. After a dramatic reduction of the total number of patients on the waitlist immediately following the intervention, a small rise was seen at two years (n = 69) which remained well below the pre-intervention level (n = 582). Conclusion The STAT model is a promising intervention for reducing waiting in an epilepsy clinic. While there was a small increase in the waitlist after two years, the median waiting time was sustained.
... It follows that a change in the size of a closed waiting list can only be the result of an imbalance between enrolment and admission. Size must swell if the number of enrolments (E) exceeds the number of admissions (A) , and size must shrink if admissions exceed enrolments [2][3][4][5][6][7][8][9][10]. This is the population implied whenever we exclude the patients who experienced a competing outcome [2,11,12] as is commonly done when datasets are assembled at national, provincial, and regional level. ...
Article
Full-text available
Many investigators have hypothesised that an increase in admissions is associated with a decrease in Size. The Size of a waiting list must increase by any excess of additions to the list over deductions from the list. A real change in enrolments (relative to admissions) must therefore correlate directly with any change in the Size of the list while a real change in admissions (relative to enrolments) must correlate indirectly with any change in the Size of the list. But some of the results seem to provide support for an alternative in which an increase in admissions is associated with an increase in Size. When there is a problem, the first hypothesis calls for more resources, and the second for more restraint. We may define the length of wait prospectively , using the distribution of completed waits of those enrolled, or we may define it retrospectively , using the completed waits of those admitted. But our choice has consequences. The relationship between changes in the Length of the subsequent wait and changes in the Size of the list must be direct because changes in Size are directly correlated with a real change in enrolments. Similarly, the relationship between changes in the Length of the prior wait and changes in Size must be indirect because changes in Size are indirectly correlated with a real change in admissions. In this light, the second relationship appears to be an artefact and the second hypothesis a failure of reasoning.
Article
Full-text available
Aim The primary aim of this systematic review of the literature was to determine whether interventions to reduce waiting time in outpatient and community health services can be sustained. The secondary aim was to describe associations between sustainability and features of waiting time interventions and the settings in which they have been implemented. Methods CINAHL, Medline, Embase and Psych Info databases were searched, combining the search concepts ‘waiting time or waiting lists’, ‘outpatient or community care’ and ‘sustainability’. Studies were included if they tested a service-level intervention that aimed to reduce waiting in an outpatient or community setting and reported data with a minimum 12-month follow-up period. Data were extracted and analysed using a descriptive synthesis. Methodological quality was evaluated using the mixed-methods appraisal tool (MMAT). Waiting interventions were rated as sustained, partially sustained or not sustained using predetermined criteria. The Grading of Recommendation, Assessment, Development and Evaluation was used to describe certainty of evidence for different intervention approaches. Results Screening of 7770 studies yielded 22 papers investigating the sustainability of waiting interventions for approximately 150 000 clients. Many were of lesser quality, with 14 not meeting more than 3 of 5 criteria on the MMAT checklist. Intervention types were categorised as referral entry, open access and substitution, used either alone or in combination. There was low certainty evidence that all interventions were associated with sustained reductions in waiting time, often with large effect sizes, but the findings are limited by low methodological quality of many studies and the risk of publication bias. Conclusion Reductions in wait times and waiting lists for health services can be achieved and sustained following interventions, but further high-quality research would better inform service providers about what interventions are most effective and provide the greatest return on investment.
Article
Purpose The purpose of this paper is to explore waiting times in improving access to psychological therapies (IAPT) services before and throughout the COVID-19 pandemic. The paper aims to help develop a better understanding of waiting times in IAPT so that interventions can be developed to address them. Design/methodology/approach IAPT national data reports was analysed to determine access and in-treatment waiting times before, during and after the COVID-19 pandemic. Time-series data was used to examine referral patterns, waiting list size and waiting times between the period of November 2018 and January 2022. The data covers all regions in England where an IAPT service has been commissioned. Findings There was a dramatic drop in referrals to IAPT services when lockdown started. Waiting list size for all IAPT services in the country reduced, as did incomplete and completed waits. The reduction in waiting times was short-lived, and longer waits are returning. Practical implications This paper aims to contribute to the literature on IAPT waiting times both in relation to, and outside of, COVID-19. It is hoped that the conclusions will generate discussion about addressing long waits to treatment for psychological therapy and encourage further research. Originality/value To the best of the authors’ knowledge, there is no published research examining the performance of IAPT waiting times to second appointment. The paper also contributes to an understanding of how IAPT waiting times are measured and explores challenges with the system itself. Finally, it offers an overview on the impact of the COVID-19 pandemic on waiting time performance nationally.
Article
Many formal organizational structures arise as reflections of rationalized institutional rules. The elaboration of such rules in modern states and societies accounts in part for the expansion and increased complexity of formal organizational structures. Institutional rules function as myths which organizations incorporate, gaining legitimacy, resources, stability, and enhanced survival prospects. Organizations whose structures become isomorphic with the myths of the institutional environment-in contrast with those primarily structured by the demands of technical production and exchange-decrease internal coordination and control in order to maintain legitimacy. Structures are decoupled from each other and from ongoing activities. In place of coordination, inspection, and evaluation, a logic of confidence and good faith is employed.
Article
We examine the political history of twelve twentieth-century efforts at comprehensive administrative reorganization in the United States. These efforts account for only a small fraction of administrative changes and do not seem to have had a major impact on administrative costs, efficiency, or control. They have been a source of frustration for presidents and others and have become regular and unlamented casualties of experience. Nevertheless, the idea of comprehensive administrative reorganization has been persistently resurrected by the political system. The history of comprehensive reorganization suggests that short-run outcomes are heavily influenced by the problematics of attention; that influence over long-run administrative development involves affecting gradually evolving systems of meaning; and that reorganization rhetoric and ritual affirm an interpretation of life at least as much as they are bases for short-run political decisions. We suggest some implications of such conclusions for a more general understanding of the organization of political life.
Article
This article reconsiders the question of why organizations really do need strategies, and also shows how some long-held beliefs explain why organizations don't, as well as do, need strategies. It considers the needs for strategy to set direction, focus effort, define the organization, and provide consistency.
Article
The strategy-making process exists in three basic modes: the entrepreneurial mode, where bold decisions are taken by a powerful decision-maker; the adaptive mode, where a coalition of decision-makers reacts to environmental pressures with small, disjointed steps; and the planning mode, where analysts integrate strategic decisions into systematic plans.
Article
The organizational history of American government during the past 100 years has been written principally in terms of the creation of larger and larger public organizations. Beginning with the Progressive movement, no matter the goal, the reflexive response has been to consolidate and centralize into formal hierarchies. That efficiency, effectiveness, and accountability, and the coordination necessary to achieve them, are promoted by such reorganizations has become widely accepted. Borrowing from social psychology, sociology, political science, and public administration, and using the public transit system of the San Francisco Bay area for illustrative purposes, Donald Chisholm directly challenges this received wisdom. He argues that, contrary to contemporary canons of public administration, we should actively resist the temptation to consolidate and centralize our public organizations. Rather, we should carefully match organizational design with observed types and levels of interdependence, since organizational systems that on the surface appear to be tightly linked webs of interdependence on closer examination often prove decomposable into relatively simpler subsystems that may be coordinated through decentralized, informal organizational arrangements. Chisholm finds that informal channels between actors at different organizations prove remarkably effective and durable as instruments of coordination. Developed and maintained as needed rather than according to a single preconceived design, informal channels, along with informal conventions and contracts, tend to match interorganization interdependence closely and to facilitate coordination. Relying on such measures reduces the cognitive demands and obviates the necessity for broadscale political agreement typical of coordination by centralized, formal organizations. They also advance other important values that are frequently absent in formally consolidated organizations, such as reliability, flexibility, and the representation of varied interests. Coordination Without Hierarchy is an incisive, penetrating work whose conclusions apply to a wide range of public organizations at all levels of government. It will be of interest to a broad array of social scientists and policymakers. In an earlier version, Coordination Without Hierarchy received the American Political Science Association 1985 Leonard D. White Award for the best doctoral dissertation in the field of public administration, including broadly related problems of policy formation and administrative theory.