A Clinical Decision Support System for an Antimicrobial

Stewardship Program

F. Palacios

, M. Campos

, J. M. Juarez

, S. E. Cosgrove

, E. Avdic

, B. Canovas-Segura

A. Morales

, M. E. Martínez-Nuñez

, T. Molina-García

, P. García-Hierro

and J. Cacho-Calvo

Intensive Care Unit, University Hospital of Getafe, Getafe, Spain

Computer Science Faculty, University of Murcia, Murcia, Spain

Antimicrobial Stewardship Program, The Johns Hopkins Hospital, Baltimore, MD, U.S.A

Pharmacy, University Hospital of Getafe, Getafe, Spain

Microbiology, University Hospital of Getafe, Getafe, Spain

Keywords: Decision Support System, Antimicrobial Stewardship Program.

Abstract: The World Health Organization has declared that antimicrobial resistance is a major public health issue and

one of the three greatest threats to human health. Antimicrobial Stewardship Programs, ASP, are

institutional approaches to curb the threat of antimicrobial resistance, improve the safety of patients

receiving antibiotics, and decrease antibiotic costs. Medical informatics in all areas, particularly the

Electronic Health Record (EHR), has become a paradigm of modern medicine. An intelligent system

integrated in EHR can play an important role in facilitating ASP activities. In this article we describe the

experience of integration of a newly developed clinical decision support system, WASPSS, into an

antimicrobial stewardship program in a mid-size hospital.

1 INTRODUCTION

According to the Center of Disease Control and

Prevention (CDC), each year in the United States, at

least 2 million people become infected with bacteria

that are resistant to antibiotics and at least 23,000

people die each year as a direct result of these

infections (CDC, 2013). The European Union

estimates that 25,000 people die due to the same

problem, at a cost of 1.5 billion Euros per year

(ECDC, 2009). Many more people die from other

conditions that are complicated by an antibiotic-

resistant infection.

Antibiotics are unique drugs due to their high

efficacy in terms of the reduction of morbidity and

mortality. At the same time, they are the only drugs

in which the use of the agent in one patient can

affect use in another patient via development of

resistance. Almost all medical specialties use

antibiotics, although it had been demonstrated that

education in appropriate antibiotic use is lacking in

medical school and training programs. Choosing the

correct agent can also be impacted by this lack of

knowledge particularly given the complexities of

modern hospital patients. It is also important to bear

in mind the ethical considerations of dealing with

the global problem of antibiotic resistance while

offering the care to the individual patient.

Antimicrobial Stewardship Programs, ASPs,

have been proposed as a solution to the global threat

of antibiotic resistance (Doron and Davidson, 2011;

Nathan and Cars, 2014). ASPs have proven to be

effective at improving patient outcomes, reducing

the use of antibiotics, and controlling costs

(Carling

et al., 2003). A key issue in ASP is the use of

Clinical Decision Support Systems (CDSSs), along

with the meaningful use of Electronic Health

Records (EHRs) (Blumenthal and Tavenner, 2010)

that promote and incentivize the use of health

information technologies, and, more specifically, the

use of CDSSs in the United States.

A review of recent articles on CDSSs for

infectious disease management shows that the trend

in CDSSs is to focus on infection control,

surveillance, alerts and reporting. In general, they

are directed at a limited number of users, mainly

infection preventionists and pharmacists who use

this technology to identify patients that may need

496

Palacios, F., Campos, M., Juarez, J., Cosgrove, S., Avdic, E., Canovas-Segura, B., Morales, A., Martínez-Nuñez, M., Molina-García, T., García-Hierro, P. and Cacho-Calvo, J.

A Clinical Decision Support System for an Antimicrobial Stewardship Program.

DOI: 10.5220/0005824904960501

In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2016) - Volume 5: HEALTHINF, pages 496-501

ISBN: 978-989-758-170-0

therapy modification. Nevertheless, ASP influence

goes further than those points and the CDSS should

consider other functionalities to support ASP

activities and ways of breaking the barriers of CDSS

adoption that are not yet identified.

The University Hospital of Getafe in Spain,

UHG, has recently implemented an ASP program

named PAMACTA (Program for Multidisciplinary

Assistance and Control of Antimicrobial Therapy).

The UHG, is a mid-size hospital (approx. 600 beds),

covering most medical specialties. In this paper, we

describe the practical reasons that have inspired the

development of a CDSS called WASPSS (Wise

Antimicrobial Stewardship Program Support

System). We show how the recommendations for the

ASP can be translated into an intelligent system

beyond the functionalities of the CDSS already

described in the literature.

The PAMACTA team is composed of 9

members. In the current context of economic crisis,

resources are limited, and all specialists have a

modest dedication of time to the project. To begin

with, the team considered the recommendations of

the Infectious Diseases Society of America and

Society for Hospital Epidemiology of America

(IDSA/SHEA) (Dellit et al., 2007), and the

objectives described by CDC (CDC, 2012). One of

the most important recommendations is to define a

multidisciplinary group, thus facilitating

communication and collaboration in order to

improve antibiotic use.

A well-known disadvantage when teams follow

this methodology is the amount of time required by

the ASP to review alerts: 2-3 hours/day, with an

additional 1-2 hours for interventions on actionable

alerts and documentation. In addition, the number of

alerts increases with the number of rules, which are

increasingly specific for the different protocols and

clinical conditions of the patients. The team needs

the support of specific software that will allow them

to focus on key aspects of ASP. The birth of the

WASPSS system at the same time that the team was

created provides the opportunity to focus on current

needs of an ASP team starting from scratch.

The rest of the paper is structured as follows. We

describe the functionalities and analytic capabilities

not yet identified in the CDSS literature for infection

control. In the following two sections we describe

the functionality of the WASPSS system for

supporting the physician and the ASP team in their

respective activities. The intelligent technologies

included in the WASPSS system are described, and,

finally, we provide the conclusions and contributions

of this paper.

2 CDDS FUNCTIONALITIES NOT

YET IDENTIFIED

Since the MYCIN (Buchanan and Shortliffe, 1984)

project, there has been a long history of intelligent

systems working on infection diagnosis and

treatment, dating back to the 1980s (Evans et al.,

1998; Nachtigall et al., 2014). In a previous work,

some authors identified the functional requirements

of a CDSS for infection control (Pestotnik, 2005). A

recent review (Forrest et al., 2014) compared the

functionalities of some commercial CDSSs and

EHRs for infection control. Most of them only focus

on surveillance, alerting, and reporting.

The general difficulties involved in creating

successful CDSSs have been identified (Forrest et

al., 2014), but there are no proposals from the

technical point of view to overcome the economical

and ethical barriers, alert fatigue, and the lack of any

measure of clinical impact. More specific gaps in

functionality are the limited interaction with clinical

guidelines, the difficulty of following up the patient

after the alert, and the difficulty involved in

integrating and sharing knowledge. Regarding the

last point, the number of hand-coded alerts may be

very high (e.g. 1285 best practice alerts (Schulz et

al., 2013)), and their management is very complex

since there is no easy way of updating them or

detecting conflicts.

As regards the users, most of the CDSSs are

focused on prescription support for physicians, and

on helping the treatment reviews carried out by

pharmacists (Calloway et al., 2013). Very few works

highlight the role of microbiologists in ASP (Avdic

and Carroll, 2014).

We realized that the above studies did not focus

on helping the ASP team, and that, some essential

ideas on ASP functions have been overlooked; for

example: a) CDSSs must be multidisciplinary, and

must consider a view adapted for each role; b)

CDSSs must promote and ease communication

between all the participants; c) CDSSs must provide

the most suitable information at the most appropriate

moment to each specific user; d) CDSS must help in

the education of clinical staff members in the

management of antibiotics.

A Clinical Decision Support System for an Antimicrobial Stewardship Program

497

3 SUPPORTING ATTENDING

PHYSICIAN IN THE

TREATMENT OF INFECTIONS

We now describe a process for management of

patients with infections, where we identify the

knowledge needed by the ASP members and the

support that can be offered by WASPSS in each

phase. In general, we can define three phases respect

to the treatment: a) “pre-prescription” phase where

the clinician needs clinical information to diagnose,

b) a “prescription” phase where the clinician selects

the antibiotic according to several criteria and not

only to clinical information, and c) the “post-

prescription” phase with an assessment-review loop

of clinical response.

In the first phase, “pre-prescription”, the actions

are essentially related to the clinical assessment of

the patient, and the use of protocols. The system in

this case should be responsible for proposing

protocols and, according to those protocols, propose

short-term plans and to provide reminders about

information gathering. Table 1 depicts the phases

and the possible actions considered in the CDSS.

In the second phase, a key aspect where the

WASPSS system intervenes is to integrate the

clinical guidelines with the experts’ knowledge. The

system is responsible for including information on

microbiology, pharmacodynamics, pharmacokinetics

as well as local policies of antibiotic use (e.g.

formulary restriction) is needed in the proposal for

empiric treatment. In our case, we think that visual

explanation is a simple way of showing the

rationale; for example, cost and coverage of most

frequent pathogens in the type of culture.

An important factor would be to take advantage

of microbiologists’ expertise in the interpretation of

the susceptibility tests and antibiogram. The

introduction of EUCAST expert rules (Leclercq et

al., 2013)

for intrinsic resistance and exceptional

resistance phenotypes with local adaptations could

help a better and wider interpretation of the test.

In the third phase, post-prescription, the role of

an infectious diseases specialist, microbiologist and

pharmacist in the ASP team is even more relevant.

Once the culture results with susceptibilities and

minimum inhibitory concentrations are available, it

is possible to detect any inappropriate selection of

antibiotics, and to avoid the failure of treatment due

to factors such us under-dosing (not ensuring the

elimination of the pathogen), adverse effects, or

reinfection. At this moment, recommendations such

as the early isolation of the patient according to local

policies are important. For example, a local policy in

the UHG is not to use ciprofloxacine against E.coli

in urinary tract infections due to a resistance of 43%.

By including pharmacokinetics and

pharmacodynamics as criteria, we facilitate the

selection of both drug and dosing regimen, with the

aim of inhibiting the microbe and improving the

clinical response of the patient. The dosage selected

should result in adequate therapeutic concentrations

at the site of infection for a sufficient time without

causing side effects or toxicity.

In this step, the system should enter in a loop that

should include the evolution and previous

assessment rather than simply evaluating each action

individually to avoid false positive alerts that would

eventually be overridden by the ASP team and the

physician. When the clinician actually feels a

patient-centered care culture involving close

supervision of the patient’s evolution, it is possible

to improve the treatment of the patient.

4 SUPPORTING ASP ACTIONS

Apart from patient care, the ASP team is responsible

for defining actions in a wide number of contexts

that are not directly related to antibiotic supervision.

Some of these functions are the actions related with

infection prevention, educational actions,

information diffusion, and the definition of policies.

In this section we describe four aspects where the

WASPSS system is supporting these ASP functions.

First, the CDSS must adapt to the methodology

of work proposed by the ASP team. In the case of

the UHG, the use of department representatives with

different roles and views in the CDSS is essential for

creating a general culture of rational antibiotic use,

and enable as many alerts as possible to be

monitored.

At the same time, WASPSS strengthens the

communication links between the attending

physicians and the respective experts in pharmacy,

microbiology and infectious diseases. Previous study

evaluated the effect of different methods of

communication of ASP recommendations using

variety of technologies (phone, pager, email)

(Cosgrove et al., 2007). Nevertheless, they did not

focus on the content of the messages and the positive

reinforcement, since the communication mode was

only used to send alerts or warnings. From an

educational point of view, the objective is twofold:

on the one hand to report possible errors, and, on the

other hand to provide feedback and positive

reinforcement when the patient care is going well.

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Table 1: CDSS actions in the patient management phases.

Pre-prescription Prescription Post-prescription

- Proposal of protocols

- Calculation of severity indexes

- Therapeutic threshold for antibiotic

administration

- Planning of tests and information

gathering reminders

- Interpretation of antibiogram with

expert rules

- Stratified, combined and dual cross

cumulative antibiogram

- Visualization of therapeutic options

- Sorted visualization of criteria

- Pharmacy alerts

- Alert of alteration of biochemical

control of organs

- De-escalation proposal

- Isolation proposal

- Proposal of new test

- Evaluation and prediction of

systemic inflammatory response

We have included a bidirectional communication

channel that also involves the physician in the ASP

team, and that facilitates access to clinical

information about the patient.

Another role of ASP team is to review the

current knowledge and to evaluate the quality of

care. The ASP team can leverage the analytic

capabilities of the CDSS to include local habits of

use of antibiotics and the local microbiology in the

process of reviewing the clinical guidelines and

protocols.

A third role of the ASP is the global surveillance

and monitoring of antibiotic use and resistance. The

monitoring of both clinical and process outcomes is

important for proposing new actions, and also for

removing measures or policies that are not having

any real impact on patient safety, economy or

antibiotic resistance. In this case, the use of business

intelligence technologies allows the creation of

meaningful and actionable reports that facilitate the

decision-making process.

The last activity we highlight is education.

Education on the best use of antibiotics may be one

of the highest impact activities in patient safety

through the protection of antibiotics and the

reduction of resistances. The ASP team can analyze

the use of the CDSS, the type of alerts fired, the type

of recommendations accepted and rejected, the

deviations from protocols and the local habits of use

of antibiotics in a number of dimensions, such as the

experience of the physicians, in order to assess the

competence of the different disciplines, services and

roles.

In this way, it is possible to design the content of

training activities that could reduce the distance

between junior and senior physicians, to unify

criteria and policies in the use of antibiotics, to raise

awareness on the problem of antibiotic resistance.

5 INTELLIGENT

TECHNOLOGIES IN WASP

In order to cover all the above aspects, we propose

the inclusion of three specific technologies in

WASPSS: a) knowledge management, b) intelligent

data analysis and mining, and c) visualization.

One of the main barriers in CDSSs is the

integration of data. This is partially solved by means

of interoperability, communication and vocabulary

standards. However, we think that knowledge is far

more important than data, and a knowledge

management methodology is a key element in

integrating experts’ knowledge, clinical guidelines,

local habits of use and knowledge discovered in the

database. We use the same representation framework

for clinical guidelines and protocols, rules for

adverse effect or interactions, phenotypes to create

more specific rules, and even patient clinical data.

Intelligent data analysis and data mining are used

to increase the amount of knowledge available in the

CDSS. There are a number of techniques that can be

used for a number of tasks. In this sense, we are not

only looking for classification models, but

actionable knowledge that allows the ASP to act in

any of their functions. For example, we use data

mining techniques to discover subgroups of patients

whom the antibiotic therapy is failing. Other

applications include the use the data analysis to help

the epidemiologist in the analysis of patterns of

appearance of resistances, or analysis of the use of

the CDSS to detect, for example, what antibiotics

are the causes of more alerts.

We put particular emphasis on new visualization

techniques of patient status, protocols, and, in

general, all the criteria to assist the physician in

choosing the most appropriate antibiotics. Improved

CDSSs must include innovative visualization

techniques to provide a simple and intuitive way of

summarizing as much information as possible, both

A Clinical Decision Support System for an Antimicrobial Stewardship Program

499

for helping in the prescription and for overall

monitoring.

The use of visual analytics techniques to display

patterns and models enables an agile review of

discovered knowledge and its incorporation into the

knowledge base. In this way, it is possible to analyze

and to contrast the current local use and effect of

antibiotics with respect to clinical guidelines and

protocols.

6 CONCLUSIONS

In this article we have presented the first experiences

of an ASP team in a mid-size hospital in Madrid,

Spain, and the opportunities identified in the

development of an intelligent system to help them

called WASPSS. We think the presence of a CDSS

is even more important in a context of limited

resources. In this context, as an interpretation of the

basic principle of Evidence Based Medicine, a

contribution of this paper is to highlight an extension

of the definition of ASP team that includes all the

physicians of the hospital.

From the user point of view, we highlight some

of the functionalities not previously mentioned in

other research articles on CDSS but which form part

of the current development of WASPSS:

- Multidisciplinary: current CDSSs only

consider one type of user, while the ASP is

a multidisciplinary approach by definition.

Different experts should be able to

introduce their knowledge into the system

and to have a customized view of the

information.

- Continuous: WASPSS focuses not on only

one stage of the treatment of infections, but

considers an integral view of the

management of patient and information. In

this way, we can follow up the patients and

increase patient safety, helping to solve the

ethical dilemma for the physician.

- Modular: WASPSS allows knowledge

modules to be created for the disciplines in

such a way that it can be shared between

different settings.

- Shareable: the knowledge modules can be

shared between different instances of

WASPSS in different hospitals.

- Adaptive: the knowledge modules can be

customized to the current context of the

hospital. They also allow the integration of

clinical guidelines and local protocols.

- Interoperable: although WASPSS can work

standalone, we are integrating it with the

current EHR system of the hospital.

- Accurate: we aim to avoid false positive

alarms with more personalized rules in

subgroup of patients.

- Communicative: WASPSS does not focus

only on reporting or launching alarms, but

it also promotes the bidirectional

communication between the different

clinical specialists and the ASP team.

- Documental: WASPSS provides a way of

documenting both plans and decisions on

patient management. It is essential during

night, shift changes, and weekends where

different physicians with probably less

knowledge on specific patients are on duty.

- Educational: WASPSS allows the

identification of specific points to be

included in the educational program of the

hospital. What is more, it can be used as a

teaching platform.

ACKNOWLEDGEMENTS

This work was partially funded by the Spanish

Ministry of Economy and Competitiveness under the

WASPSS project (Ref: TIN2013-45491-R) and by

European Fund for Regional Development (EFRD).

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