=Paper=
{{Paper
|id=Vol-1812/JARCA16-paper-9
|storemode=property
|title=Dynamic Management of Appointments in Sanitary Environments: A Systematic Literature Review
|pdfUrl=https://ceur-ws.org/Vol-1812/JARCA16-paper-9.pdf
|volume=Vol-1812
|authors=Virginia Cid-de-la-Paz,Andrés Jiménez-Ramírez,María José Escalona
}}
==Dynamic Management of Appointments in Sanitary Environments: A Systematic Literature Review==
https://ceur-ws.org/Vol-1812/JARCA16-paper-9.pdf
Dynamic Management of Appointments in Sanitary Environments: a Systematic
Literature Review
Virginia Cid-de-la-Paz, Andrés Jiménez-Ramírez and María José Escalona
Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
virginia.cid@iwt2.org, {ajramirez, mjescalona}@us.es
Abstract complain about the lack of availability. To mitigate this
discontent, we might think of reducing the time of patient
The aim of this study is to provide an extensive care sessions. However, in Spain only six minutes per
systematic literature review about the use of
patient is allocated in average. In fact, health professionals
dynamic programming in the management of
are disappointed with it since they have to make quick
appointments in health centers, providing a view decisions about the health of their patients. Thus, the
of the current research environment. Dynamic
scheduling systems of appointments are in the intersection
programming of appointments improves the
between efficiency and the correct access to health
efficiency through algorithmic decision support services.
tools. This technology has used successfully in
In this paper we offer a comprehensive research study
other industries such as airlines, car rental
on the programming of dynamic appointments in health
agencies and hotels. The application of this environments. These models have the potential to improve
technique to the health environment has attracted
efficiency through algorithmic decision support tools.
the interest of many academics in the last 50
This technology has used successfully in other industries
years because it is very useful to improve the such as airlines, car rental agencies and hotels (Talluri and
access and the quality of health systems and also
Van Ryzin, 2004). We believe that decision support
reduce the cost. However, the use of these
techniques can reduce costs and improve access to health
techniques in health settings is not trivial because services simultaneously.
every decision is vital for patients. In addition,
Designing a dynamic appointment scheduling system
we must consider other important and complex
aims to adapt to the demand, with the availability of the
factors such as emergencies. Therefore, we hope resources, and, at the same time, optimize the use of those
to analyze the current state of this technology in
resources and minimizes the waiting times that patients
the health environment, identifying keys for
suffer. In addition, it is imperative to take into account
future research. and understand the health environment in which we are,
outpatient, hospital, specialized centers, etc. It is
1 Introduction necessary to pay special attention to the factors that make
The objective of this work is to provide an extensive appointment scheduling challenging. In conclusion, to
review of the literature about the use of dynamic offer a roadmap in appointment management design in
programming in the management of appointments in health centers.
health centers. This theme has attracted the interest of Waiting time and congestion in waiting rooms are two
many academics over the past 50 years, from the of the few tangible elements of quality. Surveys indicate
pioneering works of Bailey (1952) and Lindley (1952). that excessive waiting time is often the main reason why
Health care providers are under great pressure to reduce patients are dissatisfied with the health services offered
costs and improve the quality of service. In recent years, (Huang, 1994).
given the greater emphasis on preventive medicine, the Many factors affect the performance of appointments
ambulatory or the primary level of health are gradually systems. The delay of patients and specialists, as well as
becoming an essential component in health care. possible emergencies are the main factors.
When we add factors to health care budgets such as Emergencies are a key factor in the design of a system
aging of the population and the increase of the chronic that allows us to manage efficiently the demand and the
diseases, it is not surprising that there is a growing resources. A good appointment system should provide
pressure on health service to improve the efficiency. convenient access to health services for all patients.
Appointment systems can be a source of dissatisfaction However, how do we prioritize emergencies? Patients'
for patients and healthcare professionals. Patients often needs have different degrees of urgency, and the decision-
Copyright @ by the paper’s authors. Copying permitted for private and
academic purposes.
In: Zoe Falomir, Juan A. Ortega (eds.): Proceedings of JARCA 2016,
Almería, Spain, June 2016, published at http://ceur-ws.org
making process we are proposing must be automatic. That number of patients that can be placed in a time zone, the
is, decisions must be made before having complete prioritization of patients, and the function to be optimized.
information about urgency. In addition, we find other characteristics to consider in the
In conclusion, we wish to deepen in this theme and process of patients’ arrivals, like the possible
present the general considerations to be taken into account unpunctuality or absence of patients and/or professionals,
in the modeling of problems. Therefore, we provide a as well as urgencies.
taxonomy of the methodologies used in the existing On the other hand, (D Gupta and Denton, 2008) present
literature and we can help to understand how to model a a constructive criticism of the studies which are done until
dynamic appointment system. the date. As a consequence, this article proposes other
aspects, besides those mentioned in (Cayirli and Veral,
2 Review Process 2009). Such aspects have to be taken into account as main
attributes when we want to develop a dynamic
This study has been undertaken as a systematic literature appointment management system: service time (e.g.,
review (SLR) based on the original guidelines as proposed difficult to assign a fixed time to a Surgery), doctor's and
by Kitchenham (B.A. Kitchenham et al., 2004) to achieve patient's preferences (e.g., a patient usually wants to see
the goal described in Section 1: provide an extensive your doctor, schedules) and indirect waiting time (e.g.,
review of the literature about the use of dynamic time from appointment until appointment day). Also, this
programming in the management of appointments in work studies the complexity of these properties in a
health centers. A systematic literature review allow sanitary environment (outpatient, outpatient appointment
identifying, evaluating and interpreting all available and surgery). This aspect is very interesting and adverts us
research data relevant to a particular research question in a how we must design a tool to support decision making in
specific investigation area. The guides proposed, which appointment management exclusively for physicians and
are among the most widely accepted in software the environment, without considering patients.
engineering, have been followed to carry out this work. From these reviews, we pretend to make a study to see
These guidelines establish that a review should the advances made in the technique to the present date.
comprise three phases: planning, conducting and For that, we focus on all the studies that consider the
reporting. The planning activity deals with developing the patient as the main user to take into account. Also, it is
review protocol as well as deciding how the researchers important not only to take into account the patient waiting
should work and interact to conduct the review. This time on the day of their appointment, but also to
protocol prescribes a controlled procedure for executing contemplate the time that passes from an appointment
the review and includes research questions, search and until the date of the appointment, because, surely, it is
evaluation strategies, inclusion/exclusion criteria, quality related to the probabilities of cancellation and delay.
assessment, data collection form and methods of analysis. Based on these, some questions are asked to be
The second phase focuses on executing the protocol as it completed in this new systematic review of the literature.
has been defined. Finally, the last phase describes how the RQ1. Are there currently applications that use dynamic
final report has been elaborated. programming to help manage patients in the healthcare
environment?
2.1 Research Questions RQ2. Are the patient's preferences taken into account
To begin the present study, we search similar systematic when making an appointment?
reviews following the planned searches that its described RQ3. What health environments have adopted dynamic
in the present and the following subsection. The results programming for managing appointments? Differences to
obtained are described below. keep in mind?
Two literature reviews were found. Both are from more RQ4. How to mitigate the effects of cancellations and
than five years ago, but they are very useful to start in the non-presentations of patients?
world of dynamic appointment management, as well as RQ5. Is the time between the request of the
recognizing the main properties to take into account. Due appointment and the day of the appointment (indirect
to its high interest and although one of them is of the year time) taken into account?
2003 and fails one of the quality requirements mentioned RQ6. How to manage emergencies and their priorities?
in section 2.3, it has been considered.
On the one hand, in the oldest review of the selected 2.2 Search Strategy
ones, made by (Cayirli and Veral, 2009), we can find an This section details how the search for related articles has
analysis of the main characteristics to take into account been done. The keywords used and the chosen
when you want to design a system to manage bibliographic engines are presented.
appointments in a health environment as faithful as At first, some keywords were defined which were
possible. Among other properties, we focus on those increasing as related articles were found since we learned
properties that make appointment’s programming a from the keywords of those articles found.
challenge. Among them, it is necessary to highlight the
After several tests, the keywords are concluded in article has been in circulation for several years and its number
Table 1. of citations has not increased in relation, we can consider it as a
signal of the quality of that article.
A1. Health B1.Dynamic C1.Appointment D1. Programming E1. Review
Table 3. Inclusion and exclusion criteria
D2. Scheduling E2. Software
Table 1 Keywords
However, it should be mentioned that in the second
phase (i.e., publications since 2006), some articles have
In addition, Table 2 presents the search expressions not been taken into account for the article. Although it
representing the different combinations of keywords done does not achieve the requirement, it is very useful to
for the search. immerse ourselves in the world of dynamic programming
in healthcare environments, giving an overview of
“A1 AND B1 AND D2” Health dynamic scheduling everything that has to be taken into account. Therefore, it
was decided not to exclude them.
“A1 AND B1 AND D2 AND E1” Health dynamic scheduling review
2.4 Quality criteria
“A1 AND B1 AND C1 AND D2” Health dynamic appointment In this section, we determine the quality criteria. Once the
scheduling
articles have exceeded the criteria of admission and
exclusion, the article’ properties are evaluated to know
“A1 AND B1 AND C1” Health dynamic appointment
their quality. Each quality judgment can take the values
“B1 AND C1 AND E2 AND A1” Dynamic scheduling software yes or no and, in some cases, including the value
health “partially”. All the quality criteria considered and their
possible values are explained in Table 4.
Table 2 Search terms
In order to perform the search, we considered the Google QA Values
Scholar, Fama (catalog of magazines and books of the O Yes: it is possible to read and understand
QA1. Is the text readable? without being an expert on the subject.
University of Seville), IEEE, Scopus and PubMed data O Partially: In certain aspects, it is necessary
sources. In them, the search expressions (cf. Table 2) were prior experience.
introduced for obtaining new revisions and studies that O No: difficult to understand.
conclude some of the challenges raised in section 2.1. QA2. Limitations have been O Yes: define the limits of the study done.
The articles collected from the different databases were described? O No: does not describe the boundary of the
study developed.
managed through the Mendeley tool.
QA3.There are future lines of O Yes: present a series of ideas to continue the
2.3 Inclusion and exclusion criteria research? research.
O No: there are not claims on possible
Thereafter, we define the admission and exclusion criteria. innovations.
With those criteria, we justify whether to consider or not
O Yes: presents the results obtained in the
the articles which are found on the aforementioned search QA4. Have the results been study.
presented?
engines. Thus, we can identify the most relevant articles O Partially: reference to other articles.
O No: does not clarify the results of the
to develop our review of the literature. investigation.
The inclusion/exclusion criteria are carried out in five
QA5. Has the algorithm been O Yes: health domain analysis.
phases presented in Table 3. tested? O No: the characteristics of the health area are
not detailed.
Phase Inclusion/exclusion criteria O Yes: health domain analysis.
QA6. Has the health application
O No: the characteristics of the health area are
environment been described?
not detailed.
P1 Article related to dynamic scheduling of appointments in the
health field. Inclusion of keywords. QA7. Has the cost function to O Yes: description of the function to be
optimize been defined? maximized or minimized.
Publications since 2006 O No: the optimization function is not
P2
detailed.
P3 Availability of the full text for free. Tabla 4. Quality criteria
P4 Not duplicated
2.5 Characterization Scheme
P5 Number of citations relevant, always keeping in mind its year In order to evaluate and classify the selected articles, a
of publication. If an article has been released in a date close to scheme dedicated to organizing and cataloging the
the present, it is logical to find few citations. However, if an
information found in the articles is made. Thus, it is easy In Table 5 we illustrate the schema definition, and in
to have an overview of each article. Based on this scheme, section 3.2 we instantiate it with the selected articles.
we describe the results obtained responding to the
research questions described in section 2.1.
Characterization Scheme
Element Characteristic Value
General Author {}
Information
Year {}
Title {}
Number of citations {}
Journal {}
Source {}
Theoretical/experimental {Theoretical with reviews to experimental studies,
theoretical studies, experimental studies}
Modelling Area of application {External consultations, treatment, surgery,
outpatients clinics, nursing, combination of the
above}
Delays {Theoretical, Experimental, No}
Cancellations {Theoretical, Experimental, No}
Patient’s preferences {Theoretical, Experimental, No}
Emergencies {Theoretical, Experimental, No}
Prioritization of emergencies {Theoretical, Experimental, No}
Attention to the time passed {Theoretical, Experimental, No}
between the request of the
appointment and the day of the
appointment
Cost function to optimize {Patient waiting time, physician downtime, cost
reduction, time from appointment request to
appointment day, combination of the above}
Results Results presented {Yes (mentioning other studies), Yes, No}
Test results {simulation, case study, both, Statistical, No (is a
literature review)}
Table 5. Characterization Scheme
With the General Information element we pretend to
collect the main characteristics of the selected articles,
including the Author, Year, Title of the article, the Journal
and the Source where it was written.
In the Modelling, it is tried to visualize in which
articles we can find answers to the research questions
RQ2, RQ3, RQ4, RQ5 and RQ6, as well as for QA6 and
QA7 quality criteria.
Finally, we expose the form of resolution and the
response of the QA4 and QA5 quality criteria in the
Result element.
Figure 1. Inclusion criteria
3 Results
This section presents the results obtained after doing the
planning described in section 2. First, we explain the
results obtained in the various searches performed. After
that, we evaluate these articles according to the quality
criteria defined in section 2.4.
3.1 Search results
The search process was developed with the keywords
described in section 2.2 and introducing them into the Figura 2. Exclusion criteria
bibliographic engines specified in section 2.2. Once the
The inclusion/exclusion phase that restricts most the
results were obtained, it was checked which the inclusion
search is the first. With the first criteria, we are sure that
and exclusion criteria. After this, the number of articles
we select articles related to the management of dynamic
was considerably reduced, finding difficulties to select a
appointments in health environment, and the keywords are
number of notable articles to perform a good systematic
chosen are in the article.
review.
Subsequently, phase 2 (i.e., articles published in the last
The first search was made in Google Scholar, not
ten years) also excludes a considerable number of studies.
finding any new articles in the other databases, besides
This criterion helps us to make a review of the most
those already provided by Google Scholar. In addition,
current literature.
FAMA is discarded since it was not possible to collect
any article related to the subject. 3.2 Analysis of selected articles
In Figure 1 and Figure 2 we can graphically display the
number of articles included and excluded by inclusion and Finally, we highlight eight articles by instantiating the
exclusion criteria respectively. schema definition designed in section 2.5 (Table 6 – Table
13).
Schema of Appointment scheduling in health care: Challenges and opportunities article
Element Characteristic Value
General Author Diwakar Gupta and Brian Denton
Information
Year 2008
Title Appointment scheduling in health care: Challenges
and opportunities
Number of citations 385
Journal IIE Transactions
Source Graduate Program in Industrial & Systems
Engineering, Department of Mechanical Engineering,
University of Minnesota
Theoretical / Experimental Theoretical with reviews of experimental studies
Modelling Area of application Combination (External consultation, Outpatient clinic
and Surgery)
Delays Theoretical
Cancellations Theoretical
Patients’ preferences Theoretical
Emergencies Theoretical
Priority of emergencies Theoretical
Attention to the time passed Theoretical
between the request of the
appointment and the day of the
appointment
Cost function to optimize Combination of waiting time suffered by the patients
and time of inactivity of the doctor)
Results Results presented Yes (mentioning other studies)
Test results No (it is a literature review)
Table 6. Schema of Appointment scheduling in health care: Challenges and opportunities article
Schema of Outpatient Scheduling in Health Care: a Review of Literature article
Element Characteristic Value
General Author Tugba Cayirli and Emre Veral
Information
Year 2003
Title Outpatient Scheduling in Health Care: a Review of
Literature
Number of citations 535
Journal Production and Operations Management Society
Source Hofstra University, Department of Management,
New York
Theoretical / Experimental Theoretical with reviews of experimental studies
Modelling Area of application External consultation
Delays Experimental
Cancellations No
Patient’s preferences No
Emergencies Experimental
Priority of emergencies No
Attention to the time passed No
between the request of the
appointment and the day of the
appointment
Cost function to optimize Combination of waiting time suffered by the patients
and time of inactivity of the doctor)
Results Results presented Yes (mentioning other studies)
Test results No (it is a literature review)
Table 7. Schema of Outpatient Scheduling in Health Care: a Review of Literature article
Schema of Dynamic Scheduling of Outpatient Appointments Under Patient No-Shows and
Cancellations article
Element Characteristic Value
General Author Nan Liu, Serhan Ziya and Vidyadhar G. Kulkarni
Information
Year 2010
Title Dynamic Scheduling of Outpatient Appointments
Under Patient No-Shows and Cancellations.
139
Number of citations
-
Journal
Source Department of Statistics and Operations Research,
University of North Carolina
Theoretical / Experimental Experimental
Modelling Area of application External consultations
Delays Experimental
Cancellations Experimental
Patient’s preferences Experimental
Emergencies No
Priority of emergencies No
Attention to the time passed Experimental
between the request of the
appointment and the day of the
appointment
Cost function to optimize Cost reduction
Results Results presented Yes
Test results simulation
Table 8. Schema of Dynamic Scheduling of Outpatient Appointments Under Patient No-Shows and Cancellations article
Schema of Designing appointment scheduling systems for ambulatory care services article
Element Characteristic Value
General Author Tugba Cayirli, Emre Veral and Harry Rosen
Information
Year 2006
Title Designing appointment scheduling systems for
ambulatory care services.
Number of citations 209
Journal -
Source Hofstra University, Department of Management
Theoretical / Experimental Experimental
Modelling Area of application Outpatients clinics
Delays Experimental
Cancellations No
Patient’s preferences No
Emergencies Experimental
Priority of emergencies No
Attention to the time passed No
between the request of the
appointment and the day of the
appointment
Cost function to optimize Combination of waiting time suffered by the patients
and time of inactivity of the doctor)
Results Results presented Yes
Test results simulation
Table 9. Schema of Designing appointment scheduling systems for ambulatory care services article
Schema of Dynamic multi-appointment patient scheduling for radiation therapy article
Element Characteristic Value
General Author Walter J. Gutjahr, Marion S. Raunerb
Information
Year 2012
Title An ACO algorithm for a dynamic regional nurse-
scheduling problem in Austria
Number of citations 41
Journal Elsevier
Source Sauder School of Business, University of British
Columbia
Theoretical / Experimental Experimental
Modelling Area of application Treatment
Delays Experimental
Cancellations No
Patient’s preferences Theoretical
Emergencies Experimental
Priority of emergencies No
Attention to the time passed No
between the request of the
appointment and the day of the
appointment
Cost function to optimize Waiting time patients
Results Results presented Yes
Test results simulation
Table 10. Schema of Dynamic multi-appointment patient scheduling for radiation therapy article
Schema of Dynamic scheduling with due dates and time windows: an application to chemotherapy
patient appointment booking article
Element Characteristic Value
General Author Yasin Gocgun and Martin L. Puterman
Information
Year 2014
Title Dynamic scheduling with due dates and time
windows: an application to chemotherapy patient
appointment booking
Number of citations
10
Journal
Health Care Management Science
Source Centre for Maintenance Optimization Reliability
Engineering, Department of Mechanical Industrial
Engineering, University of Toronto and Operations
and Logistics Division, Sauder School of Business,
University of British Columbia,
Theoretical / Experimental Experimental
Modelling Area of application Treatment
Delays Experimental
Cancellations Experimental
Patient’s preferences No
Emergencies Experimental
Priority of emergencies Experimental
Attention to the time passed No
between the request of the
appointment and the day of the
appointment
Cost function to optimize Cost reduction
Results Results presented Yes
Test results simulation
Table 11. Schema of Dynamic scheduling with due dates and time windows: an application to chemotherapy patient appointment
booking article
Schema of Clinic Overbooking to Improve Patient Access and Increase Provider Productivity article
Element Characteristic Value
General Author Linda R. LaGanga and Stephen R. Lawrence
Information
Year 2007
Title Clinic Overbooking to Improve Patient Access and
Increase Provider Productivity
Number of citations 180
Journal Decision Sciences Institute
Source Mental Health Center of Denver and University of
Colorado at Boulder
Theoretical / Experimental Experimental
Modelling Area of application Outpatients clinics
Delays Experimental
Cancellations Experimental
Patient’s preferences No
Emergencies Experimental
Priority of emergencies No
Attention to the time passed No
between the request of the
appointment and the day of the
appointment
Cost function to optimize Cost reduction
Results Results presented Yes
Test results simulation
Table 12. Schema of Clinic Overbooking to Improve Patient Access and Increase Provider Productivity article
Schema of Revenue management for a primary care clinic in the presence of patient choice article
Element Characteristic Values
General Author Diwakar Gupta and Lei Wang
Information
Year 2008
Title Revenue management for a primary care clinic in the
presence of patient choice.
Number of citations 119
Journal Operations Research
Source Department of Mechanical Engineering, University
of Minnesota, Minneapolis, Minnesota and SmartOps
Corporation, Pittsburgh, Pennsylvania
Theoretical / Experimental Experimental
Modelling Area of application Outpatients clinics
Delays No
Cancellations No
Patient’s preferences No
Emergencies Experimental
Priority of emergencies Experimental
Attention to the time passed No
between the request of the
appointment and the day of the
appointment
Cost function to optimize Cost reductions
Results Results presented Yes
Test results Statistical
Table 13. Schema of Revenue management for a primary care clinic in the presence of patient choice article
We study the distribution of these articles over time close to the current year. On the contrary, it is easier to
thanks to Figure 3. find articles related to the subject before 2010. However,
we wanted to maintain the initial idea, in order to try to
write a literature review as current as possible.
With relation to the source of each article, note that all
articles have been found in all of the chosen bibliographic
sources. That is, no article was discovered exclusively in
any of the sources.
3.3 Quality of selected articles
Having commented the selected articles, we proceed to
Figure 3. Distribution in time of articles evaluate the quality of these according to the norms
Although we initially wanted to obtain articles from the defined in section 2.4. This evaluation is shown in Table
last 10 years, we can conclude that this claim was too 14.
ambitious. We have got only eight articles and few are
QA1 QA2 QA3 QA4 QA5 QA6 QA7
Appointment scheduling in Yes Yes Yes Partially Partially Yes Yes
health care Challenges and
opportunities
Outpatient Scheduling in Health Yes Yes Yes Partially Partially Yes Yes
Care: a Review of Literature
Dynamic Scheduling of Partially Yes Yes Yes Yes Yes Yes
Outpatient Appointments
Under Patient No-Shows and
Cancellations
Designing appointment Partially Yes Yes Yes Yes Yes Yes
scheduling systems for
ambulatory care services
Dynamic multi-appointment Partially Yes No Yes Yes Yes Yes
patient scheduling for radiation
therapy
Dynamic scheduling with due Partially Yes No Yes Yes Yes Yes
dates and time windows: an
application to chemotherapy
patient appointment booking
Clinic Overbooking to Improve Partially Yes Yes Yes Yes Yes Yes
Patient Access and Increase
Provider Productivity
Revenue management for a Partially Yes No Yes Yes No Yes
primary care clinic in the
presence of patient choice.
Table 14. Quality os articles
In Figure 4 we visualize the percentage of quality, of the patient, two theoretically and one experimentally.
differentiating the possible values that can take, indicated in This may be due, as mentioned (Liu, Ziya, and Kulkarni
section 2.4. 2010), to the difficulty to design models that take into
account the needs of patients, obtaining complex
mathematical models. In addition, in his experimental study,
he concludes that such models have an arduous
computation, despite being able to make a model in which
the patient is presented with a set of possibilities in which to
put only his appointment. That is, from my point of view,
the preferences of the patient are not being considered in the
model, e.g., to contemplate their working hours. In these
studies, the system gives to the patient a set of optional days
to choose which one is preferred.
Therefore, we should continue to investigate and research
Figure 4. Quality evaluation
on how to keep patient preferences in the model.
Finally, it should be emphasized that none of the three
The QA2 and QA7 quality criteria are perfectly satisfied articles say that contemplating these priorities can produce
with 100% of acceptance. On the one hand, we found, penalties in the function to be optimized. It's just a design
thanks to QA1, that reading about 60% of the articles is a bit challenge.
difficult if one is not an expert in these topics. On the other
RQ3. What health environments have been
hand, almost 40% of the articles do not present any review
implemented dynamic programming in managing of
to future investigations, fact remarkable. Related to the appointments? Differences to keep in mind?
results and the test of algorithms (i.e., QA4 and QA5), we Practically all studies have been done in all possible
were satisfied with the conclusion of the evaluation, since health areas: outpatient clinics, external consultations,
all of the selected articles present results or they are tested. nursing, treatment and surgery. We have not found articles
Finally, in terms of QA6, we find that only an article does that have tried to simulate the operation of a hospital. It is
not describe the sanitary environment of application. logical because is easier to start reproducing smaller
environments.
4 Discusion In Figure 5 we show the distribution of articles by area of
application.
In this section, we answer the research question defined in
section 2.1 considering the knowledge assimilated from the
set of articles. Note that the main objective is to know the
current state of dynamic programming in the management in
health centers, focusing on certain challenges launched by
(D Gupta and Denton, 2008). Therefore, the analysis will
divide this section into parts, each one corresponding to one
of the research questions.
RQ1. Are there currently applications that use
dynamic programming to help manage patients in the
healthcare environment?
Despite intense research on software that supports
dynamic appointment management in health environments,
no article has been got in which the implantation of this
technique in a real sanitary environment is reflected.
Figure 5. Distribution by area of application
RQ2. Are the patient's preferences taken into account
when making an appointment? It is not surprising that the sum of each block shown in
A fundamental idea, launched by (D Gupta and Denton Figure 6 illustrates more than eight articles because several
2008). It is a factor that should not be neglected because it articles dealt with more than one application domain.
directly affects the probability of cancelling an appointment Studying this graphic we discerned that we find more
or being delayed. This relationship is completely logical. If articles related to the Ambulatory environment, followed
the patient's preferences are not taken into account, the closely by the External Consultations since both domains
patient can lose the interest in the appointment, favouring are similar.
delays or forgetfulness. On the contrary, Surgery and Treatment are environments
However, few articles discuss this subject. Only three more hostile. More characteristics that are vital must be
articles of the eight contemplated, mention the preferences taken into account in the other domains. For example, for
treatments, we include the articles (Gocgun and Puterman, paradoxically the time increases. Therefore, the
2014; Saur et al., 2012), which are intended to manage experimental studies presented are conclusive.
appointments for the treatment of chemotherapy and RQ5. Is the time between the request of the
radiotherapy respectively. In this scenario, times are appointment and the day of the appointment (indirect
essential to ensure the best saving percentage. Without time) taken into account?
forgetting the urgencies. Moreover, cancellations and delays In the one hand, only (Liu, Ziya, and Kulkarni 2010)
have a great impact on time and, significantly, on costs performs experimental tests trying to minimize the time
because they are expensive treatments. between the day that the patient asked for an appointment,
About surgery, thanks to one of our basic articles (D and the date of the appointment. This topic is already
Gupta and Denton, 2008), we know the difficulty to model mentioned in the previous section because of its intimate
an appointment management system for that environment. relationship with cancellations. However, as discussed
The main impediment is the impossibility of generalizing above, nothing clear can be discerned from this study.
the operating times. Not all bodies are the same, is possible On the other hand, (D Gupta and Denton 2008) claims to
to appear complications in the surgery, and not all surgeons investigate the reason for such cancellations or absences.
operate at the same speed. Of course, without forgetting the RQ6. How to manage emergencies and their
emergencies. The emergencies are vital so we should priorities?
minimize the waiting time of them, without neglecting or It is an essential aspect in the sanitary domains and it is
disfavouring the rest of the patients. difficult to model. In Figure 7 we show a comparison of
Therefore, although all are domains of the health world both properties, urgencies and its prioritization, looking to
and the properties to contemplate are similar, when observe how many of the selected articles perform
designing them it is essential to obtain close appointments, experimental tests contemplating emergencies and also
not very far in time, and it is indispensable to quickly prioritization.
manage urgencies.
RQ4. How to mitigate the effects of cancellations and
non-presentations of patients?
About the possible cancellation or non-presentation of the
patient, we show in Figure 6 the attribute of the schema
definition designed in Section 2.5, with the values obtained
for the set of articles formed.
Figure 7. Emergencies – Priorities
Although five of the articles selected, out of a total of
eight, perform experimental tests attending urgencies, only
two of them consider their prioritization.
Figure 6. Articles that complain in the Cancellations of patient
However, such studies warn of the complexity of
Note that half of the selected articles (four) do not modelling a dynamic appointment management system that
contemplate the possible cancellations, a very common fact accepts urgency. (Caylani, Veral, and Rosen 2006, Gurgun
and for which the dynamic scheduling of appointments and Puterman 2014, Diwakar Gupta and Lei 2008, Laganga
would be a great help. If a patient cancels his appointment, and Lawrence 2007, Saur et al., 2012) save certain time
and we have a dynamic appointment manager, that gap will zones to be used for emergencies. However, if these are not
be reused efficiently. used, it is a waste of time, with its consequent influence on
The experimental study (Liu, Ziya, and Kulkarni 2010) costs. In addition, such time reservation increases the time
reinforces the idea of the close relationship between the time lag between the day that the patient asked for an
from the request of the appointment to the date of the appointment and the day of the provided appointment which
appointment, and the probability of cancellation or absence. is an undesirable fact. Therefore, it is necessary to keep on
However, the three articles that account for cancellations researching.
(Gocgun and Puterman 2014, Laganga and Lawrence 2007,
Liu, Ziya, and Kulkarni 2010) coincide in the following: if
we try to minimize the probability of cancellation,
5 Conclusions and future work all, they are recovering time gaps for possible emergencies,
and if they are not used, we will lose that time.
After performing the analysis, we highlight the key points to Despite the problems still present, decision-making
take into account to model an appointment management techniques are fully applicable in health domains. Although
system for a health environment. the results indicate that the current state of technology is on
The main point is to know the characteristics of the the right way, there is still a long way to obtain reliable
sanitary environment that we wish to model. In this software.
systematic review of the literature, we have found modeling In fact, nowadays many clinics continue to manage their
about outpatient centers, outpatient consultations, treatments appointments under the supervision of a person, without any
and surgery. Among them, they present great differences support at all. So, it is necessary to emphasize that this
that have to be considered for a correct modeling of their technology is not being developed to supplant people, only
appointment’s manager. In short, the challenges of the to help them. As stated, this is a domain in which the
health center, as well as its objective, must be clear. mistakes are paid expensive, so it would be helpful to have a
For example, the goal of an outpatient may be to plan the software that calculates the most optimal appointment for
maximum possible number appointments in the day (always the patient who requests it, without losing the person in
on a minimum quality of care). A cancellation per day in charge of full control of the schedule. That is, health
this environment may not have much influence on costs. professionals should not view this technique as a threat
However, if we move to the management of because is only a support for them. So, we must continue
chemotherapy appointments, the indirect waiting time of the working on improving this technique, as well as giving
patient (time it takes from the date that a patient requests for visibility to its advantages in the health world.
an appointment until the date of the appointment) begins to
become vitally important, since the percentage of salvation
depends on it. In addition, cancellations in such expensive
References
treatments are costly. [Bailey, N, 1952], “A Study of Queues and Appointment
As already noted (D Gupta and Denton 2008), the indirect Systems in Hospital Outpatient Departments with Special
waiting time and the probability of cancellation or non- Reference to Waiting Times,” Journal of the Royal
presentation of the patient are closely related. However, Statistical Society 14, 185–199.
after this study, we have not found any methodology to
follow to solve this problem. For example, if we try to [Cayirli, Tugba, and Emre Veral., 2009] “Outpatient
decrease the probability of cancellations, paradoxically the Scheduling in Health Care: A Review of Literature.”
indirect waiting time increases according to (Gocgun and Production and Operations Management 12(4): 519–49.
Puterman 2014, Laganga and Lawrence 2007, Liu, Ziya,
and Kulkarni 2010). [Cayirli, Tugba, Emre Veral, and Harry Rosen.,
As future work, it could be interesting to carry out an 2006]“Designing Appointment Scheduling Systems for
analysis of the cancellations and non-presentations main Ambulatory Care Services.” Health Care Management
causes, in order to better address the problem. Science 9(1): 47–58.
About patient preferences as a method to reduce the
probability of cancellation or non-presentation of the [Gocgun, Yasin, and Martin L. Puterman, 2014] “Dynamic
patient, its modeling and its execution are complex. Scheduling with Due Dates and Time Windows: An
However, we believe that it should continue to be a line of Application to Chemotherapy Patient Appointment
future research. One line of research could be the Booking.” Health Care Management Science 17(1): 60–76.
restructuring of the management of appointments depending
on the social actor who requests it. For example, preventing [Gupta, D, and B Denton, 2008] “Appointment Scheduling
that retired people collapse the earliest appointments in the in Health Care: Challenges and Opportunities.” IIE
morning, when they may be the most accessible for workers. Transactions 40(9): 800–819.
A study of such strategies would be desirable to see if they
would improve the probability of cancellations and [Gupta, Diwakar, and Wang Lei, 2008] “Revenue
forgetting. Management for a Primary-Care Clinic in the Presence of
In short, we must continue to investigate new ways to Patient Choice.” Operations Research 56(3): 576–92.
avoid cancellations and non-presentations by patients, http://search.ebscohost.com/login.aspx?direct=true&db=bth
always keeping in mind their close relationship with the &AN=33204706&site=ehost-live.
indirect waiting time.
Other key pillars in modeling any appointment manager [Huang, X, 1994] “Patient Attitude Towards Waiting in an
for a health care environment are urgencies and their Outpatient Clinic and Its Applications,” Health Services
prioritization. In this regard, we must continue to investigate Management Research,7,2–8.
since the solution proposed by Caylani, Veral, and Rosen
2006, Gurgun and Puterman 2014, Diwakar Gupta and Law [Laganga, Linda R., and Stephen R. Lawrence.,
2008, Laganga and Lawrence 2007, Saur et al. Al., 2012) 2007.]“Clinic Overbooking to Improve Patient Access and
not used the full potential of dynamic programming. After
Increase Provider Productivity.” Decision Sciences 38(2):
251–76.
[LINDLEY, D. V,.(1952] “The Theory of Queues with a
Single Server,” Proceedings Cambridge Philosophy Society,
48, 277–289.
[Liu, N., S. Ziya, and V. G. Kulkarni, 2010] “Dynamic
Scheduling of Outpatient Appointments Under Patient No-
Shows and Cancellations.” Manufacturing & Service
Operations Management 12(2): 347–64.
[Sauré, Antoine, Jonathan Patrick, Scott Tyldesley, and
Martin L. Puterman., 2012] “Dynamic Multi-Appointment
Patient Scheduling for Radiation Therapy.” European
Journal of Operational Research 223(2): 573–84.