COST-EFFECTIVENESS STUDY OF THE NEW INFECTION...

COST-EFFECTIVENESS STUDY OF THE NEW

INFECTION CONTROL PROGRAMME IN THE ICU OF

THE COPA D’OR HOSPITAL

Héctor Crespo Revuelta

Projeto de Graduação apresentado ao

Curso de Engenharia de Produção da

Escola Politécnica, Universidade Federal

do Rio de Janeiro, como parte dos

requisitos necessários à obtenção do

título de Engenheiro.

Orientadores: Roberto Ivo da Rocha Lima Filho

Julia Lima Fleck

Fernando Bozza

Rio de Janeiro

JULHO de 2018

COST-EFFECTIVENESS STUDY OF THE NEW INFECTION CONTROL

PROGRAMME IN THE ICU OF THE COPA D’OR HOSPITAL


PROJETO DE GRADUAÇÃO SUBMETIDO AO CORPO DOCENTE DO CURSO DE

ENGENHARIA DE PRODUÇÃO DA ESCOLA POLITÉCNICA DA UNIVERSIDADE

FEDERAL DO RIO DE JANEIRO COMO PARTE DOS REQUISITOS NECESSÁRIOS

PARA A OBTENÇÃO DO GRAU DE ENGENHEIRO DE MATERIAIS.

Examinada por:

____________________________________________

Roberto Ivo da Rocha Lima Filho

____________________________________________

Julia Lima Fleck

____________________________________________

Fernando Bozza

RIO DE JANEIRO, RJ - BRASIL

MARÇO DE 2018

Crespo Revuelta, Héctor

Cost-effectiveness study of the new infection control

programme in the icu of the copa d’or hospital/ Héctor

Crespo Revuelta. – Rio de Janeiro: UFRJ/ Escola

Politécnica, 2018.

X, 49 p.: il.; 29,7 cm.

Orientadores: Roberto Ivo da Rocha Lima Filho

Projeto de Graduação – UFRJ/ Escola Politécnica/

Curso de Engenharia de Produção, 2018.

Referências Bibliográficas: p.

1.Cost-Effectiveness Analysis. 2.MDR Bacteria. 3.

ICU. 4. Infection Control Programme

I. Ivo da Rocha Lima Filho, Roberto. II. Universidade

Federal do Rio de Janeiro, Escola Politécnica, Curso de

Engenharia de Produção. III. Adjunct Professor.

Agradecimentos

Gostaria primeiramente de agradecer à toda a minha família e em especial, minha

mãe María Ángeles Revuelta Quintanilla, meu pai Andrés Crespo Rupérez por serem a base

da minha formação e por todos os sacrifícios que fizeram para que eu tivesse todas as

oportunidades que tive.

Este trabalho é o resultado de uma pesquisa realizada em colaboração entre a UFRJ,

PUC e o Hospital Copa D’Or. Gostaria, portanto, de agradecer a facilidade para desenvolver

o projeto entre as três grandes organizações.

O caminho até o final deste projeto foi para mim uma luz de inspiração e exemplo.

Julia Fleck, Roberto Ivo e Fernando Bozza, além de ser grandes pessoas são grandes

professionais, sendo uma referência absoluta e uma ajuda constante. É incrível como uma

pessoa pode influenciar tanto na vida das outras, não tenho mais que palavras de

agradecimento para vocês por representar tanto para mim esse último ano.

Também gostaria de agradecer a Leila Dantas, por tanta ajuda durante a realização do

projeto e a todos os funcionários do Copa D’Or que estiveram sempre dispostos a ajudar.

Por fim, gostaria de agradecer a todos aqueles outros que, de alguma forma, tiveram

um papel nessa jornada.

Muito obrigado.

Resumo do Projeto de Graduação apresentado à Escola Politécnica/ UFRJ como parte dos

requisitos necessários para a obtenção do grau de Engenheiro de Materiais.

COST-EFFECTIVENESS STUDY OF THE NEW INFECTION CONTROL PROGRAMME IN

THE ICU OF THE COPA D’OR HOSPITAL


Julho de 2018

Orientadores: Roberto Ivo da Rocha Lima Filho Julia Lima Fleck Fernando Bozza

Curso: Engenharia de Produção

Resumo: As bactérias multirresistentes são atualmente um dos problemas mais críticos e

perigosos do sistema de saúde. Os pacientes das unidades de terapia intensiva (UTI)

representam o grupo de risco mais grande para contrair esses organismos multirresistentes. O

principal objetivo do estudo é avaliar se o novo programa de controle de infecções do

hospital Copa D’Or é custo efetivo, desde uma perspectiva do hospital e um horizonte

temporal da vida dos pacientes. Também é desenvolvido uma metodologia de cálculo para o

QALY (Anos de Vida Ganhados Ajustados por Qualidade de Vida), que é uma medida da

efetividade da intervenção. O novo controle de infecções evitou 38 casos, o que levou a uma

melhora na efetividade. O indicador para avaliar se o projeto foi custo efetivo foi a Relação

Custo-Efetividade Incremental (RCEI), que para nosso estudo teve um valor de

,

que supõe um 0.18% do Produto Interno Bruto per capita brasileiro, muito menor do que as

recomendações da literatura. Portanto, o novo programa de controle de infecções foi muito

custo-efetivo. Além disso, depois de realizar um analise de sensibilidade considerando que o

número de casos colonizados também deveria ser reduzido com a nova estratégia, o projeto

passaria a ser econômico com 33 casos evitados de colonização, uma hipótese razoável.

Palavras-chave: Cost-Effectiveness Analysis, MDR Bacteria, ICU, Infection Control

Programme.

Abstract of Undergraduate Project presented to POLI/UFRJ as a partial fulfillment of the

requirements for the degree of Engineer.

COST-EFFECTIVENESS STUDY OF THE NEW INFECTION CONTROL PROGRAMME IN

THE ICU OF THE COPA D’OR HOSPITAL


July 2018

Advisors: Roberto Ivo da Rocha Lima Filho

Julia Lima Fleck Fernando Bozza

Course: Industrual Engineering

Abstract: Multidrug resistant (MDR) bacteria are currently one of the most dangerous

and critical problems on the health system. Patients in intensive care units (ICU) present the

greatest risk to contract these multi-resistant organisms. The main objective of this study is to

assess the cost-effectiveness of the new MDR infection control program set at Copa D’Or

hospital ICU, from a hospital perspective with a time horizon for the calculation of lifetime.

The secondary objective is to develop a QALYs (Quality Adjusted Life Years, which is a

measure of the intervention effectiveness) calculation methodology. The new control

programme avoided 38 infection cases what led to an improve in the effectiveness due to an

extra cost. The cost-effectiveness was measured with the Incremental Cost-Effectiveness

Ratio (ICER), that in our study was equal to

which is a 0.18% of the Brazilian

GDP per capita, much lower than the cost-effectiveness thresholds given in the literature.

Therefore, the new control infection programme was very cost-effective. Moreover, after

performing a sensitivity analysis considering that the number of colonization cases should be

also reduced with the new control strategy, this became cost-saving from 33 avoided

colonization cases, a very reasonable assumption.

Keywords: Cost-Effectiveness Analysis, MDR Bacteria, ICU, Infection Control Programme.

INDEX

LIST OF FIGURES ............................................................................................................ 9

LIST OF TABLES ............................................................................................................ 10

1 SUMMARY .............................................................................................................. 11

2 INTRODUCTION ..................................................................................................... 12

2.1 Objectives .......................................................................................................... 13

2.2 Motivation .......................................................................................................... 13

2.3 Justification ........................................................................................................ 13

2.4 Contribution ....................................................................................................... 13

2.5 Structure ............................................................................................................. 14

3 THEORETICAL BACKGROUND .......................................................................... 15

3.1 Colonization and Infection ................................................................................. 15

3.2 Multidrug Resistant Infections ........................................................................... 16

3.3 Infection Control Programmes and Measures.................................................... 16

3.4 Brazilian Health System .................................................................................... 18

3.5 The Rede D’Or São Luiz ................................................................................... 19

3.6 Copa D’Or Hospital ........................................................................................... 19

3.7 Cost-Effectiveness Analysis .............................................................................. 20

3.7.1 QALY ......................................................................................................... 25

3.7.2 ICER ........................................................................................................... 28

3.7.3 Cost-Effectiveness Threshold ..................................................................... 29

4 REVIEW OF THE LITERATURE ........................................................................... 31

4.1 National Papers .................................................................................................. 31

4.2 International Papers ........................................................................................... 32

5 METHODOLOGY .................................................................................................... 34

5.1 Copa D’Or infection control programs .............................................................. 34

5.1.1 Targeted Strategy ........................................................................................ 34

5.1.2 Universal Strategy ...................................................................................... 36

5.2 Data Bases .......................................................................................................... 37

5.2.1 Surtómetro .................................................................................................. 37

5.2.2 Infected Patient Worksheet ......................................................................... 37

5.2.3 EPIMED ..................................................................................................... 37

5.2.4 Access ......................................................................................................... 38

5.3 Cost .................................................................................................................... 38

5.3.1 Screening Cost ............................................................................................ 40

5.3.2 Contact Precaution Cost ............................................................................. 41

5.3.3 Infection Cost ............................................................................................. 42

5.4 Effectiveness ...................................................................................................... 43

5.4.1 Study Particularities .................................................................................... 45

5.4.2 QALY Calculation ...................................................................................... 46

5.4.3 QALYs Gained ........................................................................................... 49

5.4.4 ICER ........................................................................................................... 50

6 RESULTS.................................................................................................................. 51

6.1 General Results .................................................................................................. 51

6.1.1 Non-MDR Patients ..................................................................................... 51

6.1.2 MDR Colonized Patients ............................................................................ 53

6.1.3 MDR Infected Patients ............................................................................... 54

6.2 Cost .................................................................................................................... 56

6.2.1 Screening Cost ............................................................................................ 56

6.2.2 Contact Precaution Cost ............................................................................. 57

6.2.3 Infection Cost ............................................................................................. 58

6.2.4 Total Cost ................................................................................................... 59

6.3 Effectiveness ...................................................................................................... 59

6.3.1 First Period ................................................................................................. 59

6.3.2 Second Period ............................................................................................. 60

6.3.3 QALY gained ............................................................................................. 62

6.4 ICER .................................................................................................................. 63

6.5 Sensitivity Analysis ........................................................................................... 64

7 CONCLUSION ......................................................................................................... 66

8 LIMITATIONS AND FUTURE STUDIES ............................................................. 69

9 BIBLIOGRAPHY ..................................................................................................... 70

LIST OF FIGURES

Figure 1 - Brazilian Health System. Adapted from [15] .................................................. 18

Figure 2 - Copa D'Or Hospital .......................................................................................... 19

Figure 3 - Age frequency of Copa D'Or ICU patients ...................................................... 20

Figure 4 - Four Quadrants of a Cost-Effectiveness Study [27] ........................................ 24

Figure 5 - QALYs calculation [28] ................................................................................... 26

Figure 6 - EQ-5D-3L questionnaire adapted from the EuroQol Group ............................ 27

Figure 7 - Scheme of Targeted Control Strategy .............................................................. 35

Figure 8 - Scheme of Universal Control Strategy ............................................................ 36

Figure 9 - Study groups .................................................................................................... 45

Figure 10 - Study groups and periods for the analysis ..................................................... 46

Figure 11 - Age Frequency Non-MDR Patients ............................................................... 52

Figure 12 - LOS Frequency Non-MDR Patients .............................................................. 53

Figure 13 - Age Frequency MDR Colonized Patients ...................................................... 54

Figure 14 - LOS Frequency MDR Colonized Patients ..................................................... 54

Figure 15 - Age Frequency MDR Infected Patients ......................................................... 55

Figure 16 - LOS Frequency MDR Infected Patients ........................................................ 56

Figure 17 - Sensitivity Analysis ....................................................................................... 65

LIST OF TABLES

Table 1 - Non-MDR Patients Statistics ............................................................................ 52

Table 2 - MDR Colonized Patients Statistics ................................................................... 53

Table 3 - MDR Infected Patients Statistics ....................................................................... 55

Table 4 - Screening Cost Data .......................................................................................... 57

Table 5 - Contact Precaution Cost Data ........................................................................... 58

Table 6 - Infection Cost Data ............................................................................................ 59

Table 7 - LYs Period 1 ...................................................................................................... 60

Table 8 - Total LYs ........................................................................................................... 61

Table 9 - QALYs per group .............................................................................................. 62

Table 10 - QALYs gained per avoided case ..................................................................... 63

Table 11 - Main QALY outcomes .................................................................................... 63

1 SUMMARY

Multidrug resistant (MDR) bacteria are currently one of the most dangerous and critical

problems on the health system. MDR infected patient’s outcomes are worse as compared to

non-resistant infected patients and this is associated to a higher length of stay, mortality and

morbidity. Patients in intensive care units (ICU) present the greatest risk to contract these

multi-resistant organisms since they normally have severe illness, immunosuppression, and

extended lengths of stay, which are risk factors associated with health-care associated

infections (HAIs). Our study focuses on a new infection control program at Copa D’Or

Hospital (Rio de Janeiro, Brazil), where there was a transition between a targeted screening

program to a universal screening program in order to reduce the MDR infected cases.

The main objective of this study is to assess the cost-effectiveness of the new MDR

infection control program set at Copa D’Or hospital ICU, from a hospital perspective with a

time horizon for the calculation of lifetime. The secondary objective is to develop a QALYs

(Quality Adjusted Life Years, which is a measure of the intervention effectiveness that

considers the patient length of life and adjusted with a patient quality of life score)

calculation methodology.

The new control programme avoided 38 infection cases what led to an improve in the

effectiveness due to an extra cost. The cost-effectiveness was measured with the Incremental

Cost-Effectiveness Ratio (ICER), that in our study was equal to

which is a 0.18%

of the Brazilian GDP per capita, much lower than the cost-effectiveness thresholds given in

the literature. Therefore, the new control infection programme was very cost-effective.

Moreover, after performing a sensitivity analysis considering that the number of colonization

cases should be also reduced with the new control strategy, this became cost-saving from 33

avoided colonization cases, a very reasonable assumption.

2 INTRODUCTION

Multidrug resistant (MDR) bacteria are currently one of the most dangerous and critical

problems on the health system. As the World Health Organization (WHO) states,

“Antimicrobial resistance is an increasingly serious threat to global public health that requires

action across all government sectors and society” [1]. Many organizations and articles have

reported worldwide this issue and the critical increasing rates of these resistant organisms

[1]–[5]. For instance, each year an estimated 720,000 healthcare-associated infections (HAIs)

or more occur in US acute-care hospitals [6].

There are several problems related to the rise of the MDR bacteria. MDR infected

patient’s outcomes are worse as compared to non-resistant infected patients and this is

associated to a higher length of stay, mortality and morbidity [2], [6]–[8]. Due to the

bacteria’s resistance against antibiotic, their use grows extremely [9], [10]. Therefore, this

type of infections is linked with larger costs, both for isolation measures as well as for a

higher use of drugs [11]. This increase in antibiotic use leads to higher rates of MDR bacteria,

creating a vicious cycle.

Patients in intensive care units (ICU) present the greatest risk to contract these multi-

resistant organisms since they normally have severe illness, immunosuppression, and

extended lengths of stay , which are risk factors associated with health-care associated

infections (HAIs) [12]. These HAIs are a huge problem from the hospital perspective as we

commented previously, and therefore to prevent and control this issue some measures are

normally established. The infection control programs at hospitals are a generalized health

policy which can be settled in different ways. These programs include measures such as hand

hygiene, contact precaution, isolation or MDR bacteria screenings [13], [14]. These measures

are intended to minimize spread of infection associated with health care, avoiding direct

contact between patients and healthcare staff as in the case of contact precaution measures or

between patients with the isolation, or performing screening tests in order to detect multidrug

resistant organisms (MDROs).

Our study focuses on a new infection control program at Copa D’Or Hospital (Rio de

Janeiro, Brazil), where there was a transition between a targeted screening program to a

universal screening program in order to reduce the MDR infected cases. A cost-effectiveness

analysis (CEA) is performed to assess the new infection control program from both the

financial as well as the clinical perspective.

Cost-effectiveness modelling can guide public policy and institutional investment

decisions by quantifying the long-term health and economic consequences attributable to

different strategies, and aid in the understanding of the full impact of the infections.

2.1 Objectives

The main objective of this study is to assess the cost-effectiveness of the new MDR

infection control program set at Copa D’Or hospital ICU, from a hospital perspective with a

time horizon for the calculation of lifetime.

The secondary objective is to develop a QALYs (Quality Adjusted Life Years, which is a

measure of the intervention effectiveness that considers the patient length of life and adjusted

with a patient quality of life score) calculation methodology, since in the current literature

there is not a clear description and it is supposed to be an important tool in conducting cost-

effectiveness analysis.

2.2 Motivation

Nowadays the humanity is participating in many huge advances which can be used to

develop the world. All the knowledge can be applied to the society in order to improve the

lives of the population. For instance, mathematics and other areas can be applied to the real

world trying to make it more balanced and less unequal, and they can help other parts of the

society as the health sector or the education to sustain growth and development.

This social application of my engineering background is my biggest motivation to

orientate all I have learnt during my academical life and therefore, helping in the health sector

is the main personal objective of the study.

2.3 Justification

The cost-effectiveness analysis (CEA) for health interventions is still an underutilized

practise. Although the CEA is a powerful tool to guide the allocation and efficient use of

economic resources considering the health benefits of the interventions, it has only recently

begun being utilised by the health organizations. In order to increase the literature about this

topic the study tries to develop a CEA methodology to assess the new intervention at the

Copa D’Or hospital.

2.4 Contribution

The main contribution of this paper is to evaluate the new intervention of the Copa D’Or

hospital in order to give an economic conclusion.

Moreover, in order to improve the literature about the effectiveness on the health sector

and to help next studies, the used QALY calculation methodology is clearly explained.

2.5 Structure

In Sections 3 and 4, a review of the literature will be exposed to contextualize the

problem of the MDR infections at ICUs of the hospitals, the measures utilised to control and

prevent, and to understand the cost-effectiveness analysis (CEA) on the health sector,

presenting some previous cases as well.

In Section 5, the framework of our study will be explained presenting the actual and the

previous infection control programs at Copa D’Or hospital, the considered costs and the

effectiveness calculation. For the last one, it will be explained the QALY calculation

methodology, aiming to develop the literature on this topic.

In Section 6 and 7, the results will be commented and discussed in order to give some

conclusions and to assess the cost-effectiveness of the new intervention.

3 THEORETICAL BACKGROUND

Multidrug resistant (MDR) bacteria are well-recognized to be one of the most important

current public health problems. There are three main issues that underlie the serious risk

associated to the growth of the MDR infections cases:

i. Clinical outcomes of MDR infected and colonized patients are worse as

compared to the rest of the patients. MDROs carriers are related to higher length

of stay, mortality and morbidity [2], [6]–[8]. Moreover, the emergence of

multidrug-resistant bacteria (MDRB) has become a real problem particularly for

patients admitted to intensive care units (ICU) who present greatest danger to

contract these multi-resistant organisms since they normally have severe illness,

immunosuppression, and extended lengths of stay , which are risk factors.

ii. Added cost caused by the MDR infections due to the use of particular measures

and treatments as isolation, screening tests or antibiotics. For example, in the

United States, the extra cost related to infections caused by resistant organisms as

compared to susceptible organisms was estimated between $21 billion and $34

billion per year [15].

iii. In critical care units, there is extensive antibiotic use, which leads and promotes

the rise of MDROs, which at the same time influences in the extra use of drugs.

Some vital concepts will be explained below to give a clear understanding of the

problem and the proposed solution, revising the main literature about the cost-effectiveness

studies and multidrug resistant infections.

3.1 Colonization and Infection

For the purposes of our study, it is convenient to understand the difference between

colonization and infection, since both are going to be a decisive factor for the cost and the

effectiveness.

According to the Gale Encyclopaedia of Medicine [16], colonization is the presence of

bacteria on a body surface (like on the skin, mouth, intestines or airway) without causing

disease in the person. This last part is very important since the colonization is not perceptible

without screening the patient.

Infection is the invasion of a host organism's bodily tissues by disease-causing

organisms. Infection also results from the interplay between pathogens and the defences of

the hosts they infect. In this case, the infection causes a disease in the person being

perceptible for the health professionals [16].

Infections can be divided into community onset and nosocomial acquisition. The widely

used cut-off to distinguish between these two categories is whether the onset of infection was

within the first 48 hours of hospitalization (community-onset) or later (nosocomial) [10]. The

majority of the MDR infections are nosocomial and therefore there must be a big effort on the

infection control programmes in the hospitals to reduce them.

As it will be shown later, being infected or colonized by an MDR organism leads to

higher length of stay (LOS) in the hospital and it is related with higher mortality rates. That

will influence both in the efficiency and in the costs. High LOS affects the cost and the

effectiveness, and on the other hand, higher mortality rates lead to a reduction in the

effectiveness of the strategy.

3.2 Multidrug Resistant Infections

The term “multidrug resistant” (MDR), which is also a fundamental key for our study is

more confusing since there is not an established definition. Various definitions have been

used for the term MDR during recent years [17]. Give definition just to understand the

problem.

Definition of multi-drug resistant organism:

Carbapenem-resistant Enterobacteriaceae (CRE)

Methicillin-resistant Staphylococcus aureus (MRSA)

Extended spectrum β-lactamases (ESBLs)

Vancomycin-resistant Enterococcus (VRE)

Carbapenem-resistant Acinetobacter

Carbapenem-resistant Pseudomonas

3.3 Infection Control Programmes and Measures

An infection control programme aims to prevent and control infected cases at the

hospital. It must have different components as basic measures for infection control, education

and training of health care workers, protection of health care workers, identification of

hazards and minimizing risks and routine practices [18].

Particular needs have to be considered in the management of infected patients, however

it is also necessary to take care of the colonized patients, which cannot be easily detected.

Infection control practices can be grouped in two categories:

1. Standard precautions require that health care workers assume that the blood and body

substances of all patients are potential sources of infection, regardless of the

diagnosis, or presumed infectious status. For example, hand hygiene or the use of

personal protective equipment when handling blood, body substances, excretions and

secretions.

2. Additional precautions are needed for diseases transmitted by air, droplets and

contact. For example, contact precautions measures.

Both measures affect the hospital cost, representing a material cost (gloves, masks,

etc…) and wasted time of the hospital personnel (washing their hands, putting on the contact

precaution material, etc…).

In these infection control programmes there can be also active control measures. The

most common strategies are screening and isolation.

The screening strategy is to perform an MDR bacteria test on patients in order to

identify colonized or infected cases. Those screenings can be targeted, focused just on

risk patients, or universal, where the test is performed on all the patients. The multiple

types of surveillance differ on the frequency (for all the incoming patients, just for

risk patients, per week, etc…) and the target. This measure also represents a cost for

the hospital, including the material cost of the tests and the personnel time.

This surveillance control is normally combined with other strategies as isolation,

which is the use of physical barriers and spatial separation in managing patients with

an increased likelihood of transmitting infectious agents (colonized and infected

patients) to other patients or staff members. This strategy involves more effort on the

contact precaution measures explained above, which also represent a higher cost per

patient on the precaution material and on the personnel time.

3.4 Brazilian Health System

The Brazilian health care system was restructured with the Brazilian Constitution of

1988 which became a universal system guaranteed by the creation of the Unified Health

System (Sistema Único de Saúde, SUS).

This health system is formed by the public and private sector as it can be seen in the

Figure 1. The public system provides integral attention, universal and free access to the health

services both to public as well to private users. On the other hand, the private system includes

supplementary services (health insurances and health care operators) and disbursement

systems [15].

Figure 1 - Brazilian Health System. Adapted from [15]

3.5 The Rede D’Or São Luiz

Founded in 1977, Rede D’Or São Luiz is one of the largest private companies of

hospitals in Brazil, with presence in the States of Rio de Janeiro, São Paulo, Distrito Federal

and Pernambuco. With more than 34,000 employees and 87,000 affiliated doctors, the

company is among the largest employers in the country. Through D’Or Oncology Group, a

reference in the diagnosis and treatment of cancer, in addition to the States already

mentioned, the Rede (network) also is present in the States of Ceará, Bahia and Tocantins.

Currently, the group operates 27 hospitals, 34 oncological clinics and two hospitals

under management and two under construction. It has 4,400 beds, with plans to double this

number to 8,500 beds by 2020.

Together, the hospitals performed in 2015, more than 3.0 million emergency cares,

25,000 births, 195,000 surgeries and 270,000 hospitalizations [19].

3.6 Copa D’Or Hospital

The Copa D’Or hospital was founded in 2000 from the desire of creating a new model of

hospital management in Rio de Janeiro. A hospital which could offer cutting-edge

technology, highly qualified professionals and five stars services. A place where the people

could find safety and comfort to take care of their health. That desire made the Copa D’Or

hospital an important reference when talking about excellence in the Brazilian health sector.

Located in the neighbourhood of Copacabana, the Copa D’Or hospital is recognized as one of

the most important centres with constant investments in technology and latest generation

treatments [20].

Figure 2 - Copa D'Or Hospital

The hospital is situated in one of the richest parts of Brazil and moreover with a higher

life expectancy than the rest of Brazil [20], 77.78 years old against 75.8. As it can be seen in

Figure 3, the cohort is quite elderly.

The cohort mean age for the adult ICU is 68.56 years old while the median is 72 years

old. The first quartile is 57 years old and the third is 83 years old. Those can be factors to be

considered in the analysis due to the great age of the cohort.

Figure 3 - Age frequency of Copa D'Or ICU patients

3.7 Cost-Effectiveness Analysis

Cost-effectiveness analysis (CEA) is increasingly becoming more common on the health

policies as the community goes towards allocating effectively the resources in order to

increase globally the service for the community.

Cost-effectiveness analysis of health sector interventions was first used in the 1960s [21].

Since 1970, the amount of published studies has grown until becoming an excellent strategy

to use and allocate the investments efficiently showing an increasingly concern about the

health sector resources [22].

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CEA is a powerful tool to assess the best opportunity among two or more health

interventions or strategies. This type of analysis compares the cost of an intervention against

its effectiveness, normally using one intervention as reference and therefore working with

incremental costs and outcomes, relating the financial and scientific implications. The ratio

calculated (Incremental Cost-Effectiveness Ratio, ICER) is a measure of the additional cost

per outcome gained with each intervention. The lowest ratio would represent the most cost-

effectiveness strategy.

Before starting the analysis, it is necessary to define the perspective of the study. This

perspective will influence the considered costs and the selected effectiveness. This point of

view can be of the society, govern, hospital, patient, provider, etc… For this study the

adopted perspective will be hospital perspective since the analysis is carried out in

collaboration with the Copa D’Or Hospital.

Apart from the perspective of the study, it is also necessary to set the time horizon of the

analysis which will affect the cost and the effectiveness as well. Depending on the study, the

horizon can just include the hospital stay, some years after discharge or can go towards the

death of the patients, normally matching age and gender with the survival rates of the

country. For the purpose of this study, the adopted horizon time will be a lifetime horizon

since it is necessary to evaluate the post-discharge period of the cohort, which will largely

influence due to the high mean age of the Copa D’Or Hospital patients as it will be shown

later.

To follow properly this paper is also important to understand the different ways to

measure the effectiveness. The effectiveness can be calculated specifically for each

intervention where there is a specific context as number of detected cases or number of

avoided infected/death cases. However, this has been gradually replaced by studies using

more general measures of health outcome, leading to a different type of cost-effectiveness

analysis in which outcomes are expressed in units of utility (e.g., such as the quality-adjusted

life-year, QALY or the disability-adjusted life-year, DALY). These utility indicators are a

specific measure of the effectiveness, taking into account the health status of the patient.

Since they express the outcomes in a general way, not for a specific context of the

intervention, the comparison between policies in different disease areas with diverse

mortality and morbidity is enormously facilitated. This allows to assess different projects to

allocate more efficiently the resources from a health policy perspective.

A basic approach to understand the cost-effectiveness (or cost-utility) studies is to plot

the cost and effectiveness of the new intervention, taking as reference the previous

intervention, in four quadrants as shown in the Figure 4.

The upper plot shows with an “X” the reference point, which would be the current

situation, and it represents the centre of the four quadrants. The new intervention (or possible

interventions) may have higher or lower cost and higher or lower effectiveness, falling in one

of the four quadrants around the reference situation.

If the new intervention falls into the quadrant where it has higher effectiveness and lower

cost, that would indicate that it is dominant and therefore it should be adopted as it is shown

in the middle graph of the Figure 4, without the need of further analysis. If it is known that

the intervention falls into the quadrant where it has lower effectiveness and higher cost, that

would indicate that is dominated and it should be rejected without further calculations. On the

other hand, if the new intervention falls into one of the quadrants where it has higher

effectiveness and higher cost or lower effectiveness and lower cost, the most cost-

effectiveness strategy would be the one with the lowest ICER (Incremental Cost

Effectiveness Ratio, which will be explained later) and then it should be compared to the

cost-effectiveness threshold, which would be the willingness to pay for improvements in

health. This factor is also a major source of debate since it can be set in many different ways

[23]. One possibility would be, as the World Health Organization’s Choosing Interventions

that are Cost–Effective (WHO-CHOICE) project proposed in 2001, a cost-effectiveness

thresholds of 1 to 3 times the per capita gross domestic product (GDP) per quality-adjusted

life year (QALY) or disability-adjusted life year (DALY) [24], although that recommendation

was recently criticized on the grounds that it lacked the necessary specificity for countries’

decision-making processes and could lead to mistaken resource allocation decisions [25]. As

[26] says, “cost-effectiveness thresholds used to date—such as the WHO estimates—are too

high and should not be used to inform resource allocation decisions”. It will be explained

later (3.7.3 Cost-Effectiveness Threshold), the position for this concept adopted for this

study.

It must be considered that the graphs in Figure 3 could alternatively be plots with

incremental axes, namely incremental cost and incremental effectiveness. That would also be

interesting since the ICER is an incremental ratio.

There are some problems surrounding the cost-effectiveness analysis and they are all

related with the lack of literature about the topic:

i. Firstly, there is not a common consensus about the outcomes indicators which should

be applied (avoided cases, detected cases, life years gained, QALYs gained, DALYs

gained…), and they vary largely along the literature. This leads to different natures of

the ICERs calculated and therefore the impossibility to compare them. In order to

compare two projects of different health areas, a common definition of the outcome

indicator should be set up. That would be very beneficious for the health policy of a

hospital, municipium, city, State or the whole world, since the resources could be

allocated more efficiently. The scientific community needs a standardized

methodology to improve the comparability in cost-effectiveness analyses of different

health-care interventions.

ii. Secondly, the cost-effectiveness threshold should be defined for each scenario:

hospital, municipium, city, etc; considering the specific circumstances of the study.

iii. The cost-effectiveness analysis is an important economic evaluation that takes into

consideration effectiveness outcomes. However, it cannot be the only source of

evaluation to assess the introduction of a new intervention.

Figure 4 - Four Quadrants of a Cost -Effectiveness Study [27]

3.7.1 QALY

The concept of the Quality-Adjusted Life-Year (QALY) is widely used in the cost-

effectiveness health studies to guide health-care resource allocation decisions. This concept is

a measure of health effectiveness, taking into account the patient length of life and adjusted

with the patient quality of life.

QALYs are calculated by considering the life-years of a patient weighted for each time

period by their quality, which is measured with a quality-of-life coefficient and accumulated

over the relevant time horizon to yield QALYs. That coefficient goes from 0 to 1, where 0

would represent the death and 1 the patient perfect health. The QALY concept includes both

the quantity and quality of life lived.

Generally, the QALYs for a patient could be calculated as:

And then, considering the utility weights constant during the different periods of time of

the patient life, the QALYs per patient would be:

Graphically, the calculation of the QALYs can be shown as:

Figure 5 - QALYs calculation [28]

Figure 5 illustrates the influence of the time and the quality of life. In the “y” axis the

utility weight is represented, which goes from 0 to 1, and in the “x” axis the time is

represented which goes until the death of the patient. As it can be deduced, the area under

each curve represents the QALYs for each strategy (with and without treatment).

Additionally, the difference between those areas would be the QALYs gained which is an

important factor to calculate the ICER, as incremental effectiveness.

A positive point of the QALY is that it can be aggregated across the individuals and used

for the group, as it will be done and explained in this analysis. Moreover, as it is a general

measure of the effectiveness, it allows to compare different projects from diverse areas.

The part of the QALY which is related with the time is calculated with the life years

associated to the patient, from the intervention to the final of the time horizon. This time

horizon should be the patient life to consider the whole effect of the intervention.

The quality of life is measured with the utility weights. These weights can be calculated

with diverse methods, from expert opinions on quality life to the perspective of those who are

living a life with health impairment (data collected via survey). This last alternative is the

most common and it is normally carried with the EQ-5D survey. The EQ-5D tends to be the

method of choice in most cost-utility studies and it has two types of weights, which differ on

the number of health states: EQ-5D-3L and EQ-5D-5L. The EQ-5D questionnaire is

completed in relation to five domains: mobility, self-care, usual activities, pain/discomfort

and anxiety/depression. For each domain, there are three or five levels of response, depending

on the utility weight calculated: individuals are asked whether they have no problems, some

problems or severe problems, as shown in Figure 6 the example of EQ-5D-3L calculation.

The answers given with some additional information for the five areas are then transformed

to generate a summary score, which indicates the overall utility. In total there are 245

possible health states for this example, formed by different combinations of the levels. The

EQ-5D is a cognitively simple questionnaire that is well suited for self-completion by

participants via postal surveys, at clinics and face-to-face interviews and that it is widely used

in the scientific papers [27].

Figure 6 - EQ-5D-3L questionnaire adapted from the EuroQol Group www.euroqol.org

The utility weights have a verified dependence with gender and age [29]–[32] and

therefore the EQ-5D-3L index values should be calculated for the total cohort and by gender

and age groups. These may not always exist the possibility of carrying the survey for the

whole cohort, so the utility weights have to be estimated. Here it is seen the importance of

working with standardized weights in order to use the same for all the related studies. This is

quite complicated because they also depend on the region among other factors, but it should

be a state duty to calculate these scores to have consistent analysis.

Benefits incurred today are usually valued more highly than benefits occurring in the

future. Discounting health benefits reflects society's preference for benefits to be experienced

in the present rather than the future, based on the concept of “positive time preference”,

meaning that society prefers to benefit sooner rather than later [33]. The use of the

discounting rate is widely used and supported in the literature, and moreover, there are many

values of discounting rates, being the majority between 3-5% [34]. Low rates lead to

prioritization of immediate policies and therefore they work against long-term public health

measures. Neither theoretical nor empirical arguments are adequate to determine an optimal

solution regarding which discounting method and/ or discount rate should be used [34].

The use of discounting rates for the QALY is not going to be considered in this study

since that value should be set by the decision-making organism in order to establish a health

policy for all the projects.

3.7.2 ICER

The incremental cost-effectiveness ratio (ICER) is a summary indicator representing the

cost-effectiveness of an intervention, evaluating both the economic value as well as the

clinical. This ratio is firstly compared with an intervention alternative to choose the most

cost-effective among the alternatives, if any, and then with a cost-effectiveness threshold in

order to decide whether choosing the new intervention is an efficient use of resources. If for a

studied intervention the ICER is above this threshold it will be considered too expensive and

thus should not be funded, whereas if the ICER falls below the threshold the intervention can

be judged cost-effective.

The ICER is calculated by dividing the difference in total costs (incremental cost) by the

difference in the chosen measure of health outcome or effect (incremental effect) to provide a

ratio of ‘extra cost per extra unit of health effect’ [35]. The most frequently measure of health

effect used in the literature is the QALY and DALY, enabling ICERs to be compared across

disease areas when that health effect measure is common.

Where and represent the cost and the effect of the new intervention and where

and are the cost and effect of the reference intervention.

Cost is normally expressed in monetary units and the intervention effect, as it was

commented above, and effectiveness can be represented with QALY. Therefore, the equation

would be the following:

3.7.3 Cost-Effectiveness Threshold

After calculating the incremental cost-effectiveness ratio (ICER) and selecting among

the alternatives, if any, the most cost-effective, it is necessary to compare the ratio with a

cost-effectiveness threshold, or in other words, the willingness to pay for improvements in

health.

As it was commented in 3.7 Erro! Fonte de referência não encontrada., this factor is a

huge source of debate since it will determine if the intervention is cost-effective, and

therefore the threshold should be calculated in accordance with the specific characteristics of

the study and its context. For our paper, because there are no set thresholds for Brazil or for

the Copa D’Or hospital, the cost-effectiveness is going to be established according to the

values in the literature.

There are some examples of policies which have set cost-effectiveness.:

i. Ireland (EUR 45,000/QALY) [36]

ii. UK (GBP 20.00 - GBP 30.00/QALY) [37]

iii. Thailand (1.0-1.5 per capita GDP/QALY) [38]

iv. World Health Organization (WHO) recommendation of three times the per capita

gross domestic product (GDP) per quality-adjusted life year (QALY) or disability-

adjusted life year (DALY) [24]. However that recommendation was recently

criticized on the grounds that it lacked the necessary specificity for countries’

decision-making processes and could lead to mistaken resource allocation decisions

[25].

For the specific case of Brazil, no explicit value has been set for the cost-effectiveness

threshold in the Public Healthcare System (Sistema Único de Saúde – SUS) to be applied by

the National Commission for Technology Incorporation (COMISSÃO NACIONAL DE

INCORPORAÇÃO DE TECNOLOGIAS NO SUS – CONITEC) [39].

Researchers from the University of York presented a threshold range for Brazil of 21% -

67% of the GDP per capita [40], although it not explicit the denominator. This value is quite

lower than the one proposed by the WHO, as it is declared in [26] where it contests the high

values established for the cost-effectiveness threshold.

Due to the small number of CONITEC reports with recommendations that included the

ICER calculation, it is not possible to identify an adequate threshold for Brazil based on

retrospective analysis of the recommendations. In addition to the small number, the economic

assessments used heterogeneous ratios ($/QALY, $/DALY, or $/years of life), far short of the

expected international standard for methodological quality [41].

There are some criticisms of the threshold calculated just with an economical

perspective, since it should also consider other factors as epidemiologic, cultural or political.

It is clear that, to assess the CEA there must be a cost-effectiveness threshold, however due to

the lack of justified values specific for each country, the scientific community and the public

organisations should be encouraged to develop a context-specific threshold for decision-

making supported by legislation.

For all the reasons above, the cost-effectiveness threshold used for this study is going to

be the value presented by the researchers from the University of York since is the most

restrictive and it is expressed by QALYs gained which is the most used effectiveness

measure.

4 REVIEW OF THE LITERATURE

In this section a brief review about the literature of this topic will be exposed. In all the

papers analysed, the outcomes were obtained from mathematical models as Markov model,

simulating the new interventions effects. Those outcomes were normally converted to

QALYs and then compared to the cost calculating the ICER. However, the measures utilised

vary widely along the literature. It is not the purpose of this study to show the results of the

reviewed papers and thus it will be just explained the outcomes and methodologies employed

by them.

4.1 National Papers

In the national paper “Cost effectiveness of chemo hormonal therapy in patients with

metastatic hormone-sensitive and non-metastatic high-risk prostate cancer” [42], after

simulating the results the ICER is calculated with the QALYs gained, without explaining the

methodology to obtain it, and then is compared to the cost-effectiveness threshold proposed

by the WHO, such that less than the Brazilian per capita gross domestic product (GDP) per

QALY is very cost-effective and between 1 to 3 times the per capita GDP per QALY is cost-

effective.

Another Brazilian article [43] also simulates the outcomes with a Markov model. The

QALY is calculated from the number of avoided cancer cases and then the ICER is compared

to the Brazilian GDP. It uses discounting rates for both costs and outcomes, and it also

performs sensitivity analysis to assess the robustness of the study, with the discount rate and

assumed income data.

As it can be seen, both articles use the national GDP per capita or multiples of it as cost-

effectiveness threshold. They also employed the QALY as effectiveness measure. However,

as it was commented in the previous section (3.7.3 Cost-Effectiveness Threshold), due to the

small number of CONITEC reports with recommendations that included the ICER

calculation, it is not possible to identify an adequate threshold for Brazil based on

retrospective analysis of the recommendations, and in consequence neither a effectiveness

measure.

4.2 International Papers

In “A decade of investment in infection prevention: A cost effectiveness analysis” [44],

the authors present a cost-effectiveness analysis of some infection prevention programs. The

principal health effectiveness outcome are the QALYs gained, and then together with the

incremental cost, the ICER is calculated and compare with a threshold generally assumed in

the United States: an ICER less than $50,000 is cost-effective and one more than $100,000 is

not. Normally, the utility weights are obtained from the literature, but in this case the utility

scores were obtained from the Cost-Effectiveness Analysis Registry of the Institute for

Clinical Research and Health Policy Studies, Tufts Medical Centre, which is a database of

cost-effectiveness studies containing diverse information.

“Universal or targeted approach to prevent the transmission of extended spectrum beta-

lactamase-producing Enterobacteriaceae in intensive care units: a cost-effectiveness analysis”

[45] was carried in 2017, and from a stochastic model the number of infections is obtained.

After calculating the cost and the health benefits, measured in number of avoided infected

cases, the ICER is calculated to choose the most cost-effective intervention. In this case, it

cannot be compared with a general threshold since the effectiveness measure is a specific

value for the context, so it is worth just to choose between the different intervention

proposals.

The recent paper “Screening test recommendations for methicillin-resistant

Staphylococcus aureus surveillance practices: A cost-minimization analysis” [46] focused on

the cost of the different interventions. In this case is a cost-minimization analysis is

performed, a different approach of economic analysis, however it is interesting due to the

costs considered: screening cost, contact precaution cost and open day cost. This last cost is

an interesting propose of the risk of transmission for having a colonized patient in the

common hospital space and it will be commented later.

“Cost-effectiveness analysis of universal screening for carbapenemase-producing

Enterobacteriaceae in hospital inpatients” [47] assesses the cost effectiveness of screening all

hospital inpatients for carbapenemase-producing Enterobacteriaceae (CPE) at the time of

hospital admission, compared to not screening. With a Markov model the principal outcomes

(colonization cases, infection cases, deaths…) are calculated. Then the effectiveness is

calculated as QALYs gained, and the ICER is compared to a cost-effectiveness threshold of

$100,000/QALY gained, approximately two times the United States gross domestic product

per capita.

“The potential economic value of screening hospital admissions for Clostridium

difficile” [48] simulates some possible control infection programs to assess the most cost-

effective. The effectiveness measure chosen is the QALY. Once again, the QALY calculation

is not fully explained.

The National Health Service (NHS) England introduced national mandatory screening of

all admissions for methicillin-resistant Staphylococcus aureus (MRSA) in 2010, and [13]

aimed to assess the effectiveness and cost-effectiveness of this policy. From the mathematical

model the main outcomes are obtained, expressing the effectiveness as QALY and

establishing a willingness-to-pay threshold of £30 000/QALY recommended by the NHS.

In the paper “Recommendations for Methicillin-Resistant Staphylococcus aureus

Prevention in Adult ICUs: Cost-Effectiveness Analysis” [49] a cost-effectiveness analysis is

performed using a Markov model from the hospital perspective and with a time horizon of 1

year of methicillin-resistant S aureus prevention strategies. Since the time horizon is quite

low, the differences between the control strategies are not tangible. As compared with

screening and isolation, the standard practice in ICUs at that moment and in our case as well,

targeted decolonization, and universal decolonization are less costly and more effective. This

is an interesting fact since decolonization is an intervention not contemplated in our study and

according to the paper more cost-effective than screening and isolation. The threshold used

on this paper was $100,000 per QALY gained.

In the paper “Cost-Effectiveness of Strategies to Prevent Methicillin-Resistant

Staphylococcus aureus Transmission and Infection in an Intensive Care Unit” [50] the

effectiveness is calculated just with avoided colonized and infected cases, and therefore the

number of deaths is not important. The main outcomes are the costs per avoided case,

comparing that ratio among all the strategies to choose the most cost-effectiveness.

In “Methicillin-Resistant Staphylococcus aureus Prevention Strategies in the ICU: A

Clinical Decision Analysis” [51], a decision-analytic model with deterministic and

probabilistic analyses was performed to obtained the cost and number of infections associated

to some prevention policies. For the effectiveness the QALY was chosen as main measure,

just calculated after the patient discharge and taking into account that ICU patients have a

higher mortality than the healthy population. Cost-effectiveness planes and acceptability

curves were plotted for various willingness-to pay thresholds to address uncertainty.

5 METHODOLOGY

5.1 Copa D’Or infection control programs

Before starting it is necessary to explain how both the targeted infection control program

and the universal control program work. It is going to be defined the main measures to

understand the study outcomes.

5.1.1 Targeted Strategy

This infection control program was set until the end of 2016. The main measures which

have influence on the study are:

i. Admission MDR screening of risk patients (definition of risk patients given below)

ii. During the analysis of this screening test the patient is isolated

iii. If the culture is positive, the patient stays isolated until the discharge or death

iv. If the culture is negative, the patient occupies a normal ICU bed

Definition of multi-drug resistant organism:

Carbapenem-resistant Enterobacteriaceae (CRE)

Methicillin-resistant Staphylococcus aureus (MRSA)

Extended spectrum β-lactamases (ESBLs)

Vancomycin-resistant Enterococcus (VRE)

Carbapenem-resistant Acinetobacter

Carbapenem-resistant Pseudomonas

Risk patient is defined with at least one of these characteristics:

Patient with hospital stay, radiotherapy, chemotherapy or haemodialysis in the last 6

months

Patient transferred from another health institution where stayed more than 24 hours

Patient transferred from another health institution where was involved in an invasive

procedure

Patient from home care

Prior history of infection or colonization by MDR organism in the last 6 months

Schematically the targeted strategy can be seen in the Figure 7. Due to the targeted

control strategy could happen that there were colonized patients not isolated, involving a

huge risk of multi-drug resistant organism transmission. This problem would be solved with

the universal control strategy since the weekly screenings would identify those patients

isolating them.

Figure 7 - Scheme of Targeted Control Strategy

5.1.2 Universal Strategy

The new infection control program was firstly used at the beginning of 2017. The main

measures which have influence on the study are:

Admission MDR screening of risk patients (definition of risk patients given above)

During the analysis of the screening test the patient is isolated

If the culture is positive, the patient stays isolated until the discharge or death

If the culture is negative, the patient is moved to a normal ICU bed

For all ICU patients with a hospital stay longer than 7 days weekly screening are

performed

The big difference between both strategies is the weekly screening for all the patients. It

can be observed the huge increase on the number of screening tests carried which has a huge

influence in the cost, both the screening cost, since there is a large difference on the number

of exams, and the contact precaution costs, due to the rise on the number of people isolated.

Figure 8 - Scheme of Universal Control Strategy

5.2 Data Bases

5.2.1 Surtómetro

The CCIH (Commission of the Hospital Infection Control) uses a worksheet for each

multi-drug resistant organism defined by the Copa D’Or (CRE, MRSA, ESBLs, VRE,

Carbapenem-resistant Acinetobacter and Carbapenem-resistant Pseudomonas) and it feeds it

with new infection and colonization cases of these bacteria’s, separated by sector and

detecting the possible outbreaks. Among the information available more important for this

study:

Patient name

ICU unit

Type of culture

Culture date

Type of bacteria

5.2.2 Infected Patient Worksheet

The CCIH also uses another worksheet to write down all the infections involved in the

ICU. In this case, both the MDR infections and non-MDR infections are considered. Among

the information available more important for this study:

Patient name

ICU unit

Type of culture

Culture date

Type of bacteria

5.2.3 EPIMED

EPIMED is a software used in the Brazilian ICUs, developed by the Brazilian

Association of Intensive Medicine (AMIB) in collaboration with Epimed Solutions, business

related to the clinic information management which has the objective of improving the

efficiency of the hospital care. EPIMED has data from the all ICU patients saving the clinic

information more relevant.

The project aims to characterize the epidemiologic profile of the ICU patients to

orientate health policies and strategies to improve the service at the hospital. Among the

information available more important for this study:

Patient name

Patient record number

Birthday

Age

Gender

Hospital admission date

Unit admission date

Hospital discharge type (discharge or death)

Unit discharge type (discharge or death)

Hospital discharge date

Unit discharge date

5.2.4 Access

In order to link the different databases, the software Access was used. Microsoft Access

is a Database Management System (DBMS) from Microsoft that combines the relational

Microsoft Jet Database Engine with a graphical user interface and software development

tools. Like relational databases, Microsoft Access also allows you to link related information

easily. It can also import or link directly to data stored in other applications and databases.

[52]

5.3 Cost

The cost associated to the infection control programs vary depending on the strategy:

targeted or universal screening. The main considered costs in this study are:

Screening costs: Cost of the screening tests and laboratory personnel time.

Contact precaution costs: Cost of contact precautions measures and personnel time.

Infection costs: Cost directly related to the infection as the antibiotics

Obviously, the screening cost associated with the universal strategy is going to be much

higher than the targeted strategy, since screening will be performed on all patients, both at the

admission and weekly thereafter.

The contact precaution cost is going to be higher for the universal strategy a priori, since

there will be more patients in the isolation rooms at least during the analysis of the culture at

the admission. However, it could happen the opposite and at the end the universal strategy

having a lower cost due to the decrease of the infected patients that have high length of stay

(LOS) in the hospital. Another factor that must be considered is the isolation of the colonized

patients which will be greater for the universal control because in the previous situation many

colonized patients were not detected. For all of these reasons the contact precaution cost is

going to be decisive in the analysis of the total cost, since it is not clear without previous

calculations whether it is going to be higher or lower after the new intervention.

The infection cost is supposed to decrease due to the hypothetical reduction of infected

patients. This cost is measured as the antibiotic cost which are supplied to the infected

patients.

The hospital perspective will be followed on this study to calculate the costs and in order

to have coherence with the objective of the paper. It could be supposed that there are always

the same number of ICU patients, so the only difference would be the number of isolated and

non-isolated patients.

It is important to remember that all the calculated costs are incremental since the main

outcome is the Incremental Cost-Effectiveness Ratio (ICER), so for each cost it will be

calculated the monetized variation of both interventions. Moreover, due to the necessity of

coherence in the denominator with the QALY to calculate the ICER, the common

denominator selected was the “number of admissions”.

The incremental final cost will be the sum of all the incremental costs:

As it was said before, the common denominator of all the cost and therefore the

denominator of the incremental cost is “Number of admissions”.

5.3.1 Screening Cost

The screening costs is calculated from the cost of the material screening tests and the

personnel time spent to analyse the cultures. The following cost are considered:

Laboratory supplies (LS)

Laboratory technician time (LTT)

Nurse collection time (NCT)

5.3.1.1 Laboratory Supplies Cost

The laboratory supplies costs are calculated directly from the cost of a positive culture

and the cost of a negative culture. The hospital already had that information so combining it

with the incremental number of positive and negative test per number of admissions, it can be

obtained.

5.3.1.2 Laboratory technician time

The cost associated to the laboratory technician time can be calculated as the monetized

time spent to analyse the culture. This time is higher for a positive culture than for a negative

one since the process includes additional steps in the case of a positive culture.

5.3.1.3 Nurse collection time

The cost associated to the laboratory technician time can be calculated as the monetized

time spent by the nurse to collect the culture:

5.3.2 Contact Precaution Cost

The contact precaution cost is the cost associated to the contact precautions material and

personnel time spent on contact precaution measures:

Material cost: gloves and gown used in isolation rooms ( )

Doctors and nurses time: Contact measures time, number of visits and salary ( )

It can be calculated as:

Where,

All the costs above represent an incremental cost, including the total contact precaution

cost. The reason of computing the contact precaution cost as the sum of those two costs is

because it depends on the type of patient and their length of stay in the isolation room, which

vary among them: Infected, colonized or non-MDR carrier (patient who is just in the isolation

room under the screening).

For our study, it can be supposed that the risk patients that are isolated at the admission

do not vary since the screening protocol did not change regarding to the admission.

Therefore, the , which is incremental is null.

5.3.2.1 Material Cost

The material cost includes the use of gloves and gowns used each time a healthcare staff

goes into the isolated room.

5.3.2.2 Personnel time

This cost is related to the personnel time spent in the contact precaution measures before

going into the isolated room. It is considered as personnel the nurses and doctors.

5.3.3 Infection Cost

The infection cost is associated to the antibiotic cost and therefore it can be expressed as:

5.4 Effectiveness

The chosen indicator to measure the new infection control program effectiveness is the

Quality-Adjusted Life Years (QALYs) gained in order to have a notion of both the quality

and quantity of the patients’ life. However, this coefficient is directly related to the number of

avoided cases of colonization and infection, since they are obviously a main measure of the

infection control program effectiveness. Therefore, the objective is to translate the number of

avoided cases of colonization and infection into number of life years (LYs) gained, and then

in combination with specific utility weights reach the QALYs gained.

Consequently, the QALYs gained are a measure of the LYs gained, which in turn comes

from the number of avoided infection and colonization and their associated mortality together

with the extra length of stay (LOS) in the hospital. The LYs gained are a measure of the

quantity, and to introduce the quality the LYs are weighted with utility scores. QALYs are

calculated by considering the life-years of a patient weighted for each time period by their

quality, which is measured with a quality-of-life coefficient and accumulated over the

relevant time horizon to yield QALYs.

As it was explained in the section 3.7.1, the QALYs per person can be calculated in a

general way as:

Where the utility weight will depend on the health period of the patient. As it can be seen

the QALY measures the time in combination with the life quality.

Since the utility scores are normally calculated as constant for a health period, the

integral can be considered as:

Since our analysis is focused on a patient cohort, the QALY calculation must consider

the whole pool of patients, taking into account the gender and age as influence factors for

both the patient lifetime and life quality. On the one hand, the life expectancy varies

depending on the age, but also between men and women. On the other hand, the utility

weights should be calculated for the total cohort and by gender and age groups as it was

explained in the section 3.7.1-QALY, and therefore the QALY per person considering the

whole cohort would be calculated as:

Simplifying that equation for the same reason given above, the QALY calculation would

be:

5.4.1 Study Particularities

For our analysis, patients are divided into six study groups which have different LYs and

utility weights. The next 6 groups will be analysed:

1. Non MDR patients: This group has the utility weight lower than normal hospital

patients. Moreover, the mortality rate of ICU patients is higher than the rest of the

population during the first 15 years, and then it reaches the same level.

2. Non MDR fatal patients: This group dies during the ICU stay.

3. MDR colonized patients: This group stay longer than the “Non-MDR patients” at ICU

during the hospital stay due to the colonization. After that, it recovers and get the

same health level than the normal ICU patients.

4. MDR colonized fatal patients: This group dies during the ICU stay.

5. MDR infected patients: This group stay longer than the “Non-MDR patients” and

“MDR colonized patients” at ICU and with a lower utility weight due to the infection.

After that, it recovers and get the same health level than the normal ICU patients.

6. MDR infected fatal patients: This group dies during the ICU stay.

To illustrate better these study groups the next figure is presented:

Figure 9 - Study groups

For the QALY calculation, each group is divided in two periods since the utility weights

and mortality rates are different:

1. During hospitalization: The length of stay in the hospital depends on the group, the

age and gender. Utility weight are supposed to vary depending on the age and gender

as was explained above and they can be calculated with the EQ-5D survey, for

instance. However, due to the lack of time and resources to perform surveys, the

weights for this study will be taken from the Cost-Effectiveness Analysis Registry of

the Institute for Clinical Research and Health Policy Studies, Tufts Medical Centre

[53], which is a database of cost-effectiveness studies where it can be found diverse

information.

2. After discharge: The remaining LYs for each period depends on the age and gender

due to the life expectancy. The utility weigh is considered the same for all the patients

and constant.

In order to understand better this particularity, the following figure is presented:

Figure 10 - Study groups and periods for the analysis

5.4.2 QALY Calculation

The QALY per person for each group is calculated as the sum of each period. It must be

considered that some groups (2, 4 and 6) do not outlive their hospitalization and thus do not

have second period. Both the utility weights and time depend on the study group and also on

the gender and age. Therefore, the calculation for each group would be:

5.4.2.1 First Period: Hospital Stay

For the first period, the two factors more important are the length of stay (LOS) and the

mortality, which vary largely among non-MDR patients, MDR-colonized and MDR-infected.

After analysing the data, it was assumed that the gender does not influence the LOS or the

mortality and therefore the QALY can be calculated as:

As it was discussed in the section 3.7.1-QALY and it can be deduced from the equation,

the utility weights should depend on the age. However, because of the lack of time and

resources the weights have been estimated without considering that influence. Consequently,

the equation would be:

5.4.2.2 Second Period: Post Discharge

After discharge the three survival groups (1,3 and 5) are equivalently treated, having the

same health status and in consequence the same utility score, which is assumed constant. That

utility weight is estimated for ICU patients after discharge in [51], [54] as 0.677.

Since this study is working with incremental variables, there is no need to consider that

ICU patients post-discharge have a higher mortality rate than the health population [55].

Therefore, to estimate the total patient life years, the life expectancy tables are used:

Finally, the QALYs calculation for the second period is calculated as:

The age expected is obtained from the life expectancy tables of Brazil [56] and depends

on the current age and gender. It is important to remember that the QALY is calculated using

both QALYs accrued during hospital stay as well as post-discharge, where age and sex

matched survival rates.

5.4.3 QALYs Gained

From the QALYs calculation for each study group, the QALYs gained per avoided

infection and colonization case can be calculated. Firstly, the QALY is obtained for each

health group:

Non-MDR carriers

MDR Colonized

MDR Infected

Then, the QALYs gained per avoided infection and colonization case can be calculated

from the total QALY of each health group:

To sum up, health benefits achieved through infections avoided were summarised by

changes in quality-adjusted life-years (QALYs) and estimated over patients’ lifetimes, with

use of QALYs gained during patient stays (over the simulation period), and post-discharge,

with use of discounted quality-adjusted life expectancies.

5.4.4 ICER

The denominator for the is also “Number of admissions” since

“Number of avoided cases” is referred to it. Consequently, since both and

are referred to the same common denominator, the ICER is consistent and it can be

easily calculated as:

6 RESULTS

6.1 General Results

Firstly, it is going to be presented some general data to understand the cohort in order to

give some conclusions afterwards. The data are divided in the three main health groups:

Non-MDR patients

MDR colonized patients

MDR infected patients

6.1.1 Non-MDR Patients

Non-MDR patients is the biggest group, with a similar percentage of males and females

and a mean age relatively lower than in the other two health groups (MDR-colonized and

MDR-infected) as it can be seen in the Table 1. This cohort has a low mortality rate and

length of stay (LOS) at the ICU, and the LOS standard deviation is also small compared to

the other two health groups where it varies largely among patients.

Number of Patients 17435

%Male 47.44%

%Female 52.56%

%Dead 6.37%

%Discharge 93.63%

Mean Age (Years) 66.44

Median Age (Years) 70

Mean LOS (Days) 6.97

LOS First Quartile (Days) 3

LOS Median (Days) 5

LOS Third Quartile (Days) 9

LOS Standard Deviation (Days) 5.55 Table 1 - Non-MDR Patients Statistics

It can be observed in the Figure 12 that the LOS frequency profile follows a distribution

similar to chi-squared where the tendency is very smooth. As it going to be presented later, it

is strictly differentiated from the colonized and infected patients where the LOS varies so

much what leads to a higher LOS standard deviation.

Figure 11 - Age Frequency Non-MDR Patients

0

500

1000

1500

2000

2500

0

1

5

10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

10

0

10

5

Age Frequency

Figure 12 - LOS Frequency Non-MDR Patients

6.1.2 MDR Colonized Patients

The MDR Colonized Patients analysed are a small number compared to the patients

without MDROs since with the previous control infection programme there were many

colonized that were not detected. The mortality rate reaches to almost 50%, a really high

mortality considering that the patient is just colonized, not presenting symptoms. At the same

time, the mean age is seven years older than for non-MDROs carriers, and the mean LOS is

also higher compared to the previous health group with an elevated LOS standard deviation

as it can be seen in Table 2.


%Male 50.90%

%Female 49.10%

%Dead 49.10%

%Discharge 50.90%





LOS Median (Days) 27

LOS Third Quartile (Days) 48

LOS Standard Deviation (Days) 23.05 Table 2 - MDR Colonized Patients Statistics

0

500

1000

1500

2000

2500

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

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17

18

19

20

y m

ayo

r...

LOS Frequency

Figure 13 - Age Frequency MDR Colonized Patients

Figure 14 - LOS Frequency MDR Colonized Patients

6.1.3 MDR Infected Patients

This group has the worst clinic outcomes, with the longest LOS and a similar mortality

rate than MDROs colonized patients, although a bit higher. The mean age of these patients is

88.81 years old, more than 20 years older than the patients without MDROs and 16 years

higher than colonized patients. This fact must be considered when giving the final

conclusions in order to understand some of the study outcomes. The LOS standard deviation

is very high as in the case of colonized patients, and it can be seen in the Figure 16 that the

LOS varies so much among patients.


0

5

10

15

20

25

30

35

0 1 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100

Age Frecuency

[NOMBRE DE CATEGORÍA]

0

2

4

6

8

10

12

14

1

4

7

10

13

16

19

22

25

28

31

34

37

40

43

46

49

52

55

58

61

64

67

70

LOS Frequency

%Male 52.19%

%Female 47.81%

%Dead 50.51%

%Discharge 49.49%





LOS Median (Days) 72

LOS Third Quartile (Days) 121.5

LOS Standard Deviation (Days) 62.58 Table 3 - MDR Infected Patients Statistics

Figure 15 - Age Frequency MDR Infected Patients

-

0

10

20

30

40

50

60

0 1 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100

Age Frecuency

[NOMBRE DE CATEGORÍA]

0

5

10

15

20

25

30

35

LOS Frequency

Figure 16 - LOS Frequency MDR Infected Patients

6.2 Cost

6.2.1 Screening Cost

Following the Eq.6, the incremental screening cost would be:

Where the main contribution is the laboratory supplies (LS) cost:

Used data in Eq.7, Eq.8 and Eq.9 are shown in the Table 4 where prices are given in

BRL and time in hours. The huge incremental number of screenings is due to the new

infection control programme:

Price per screening and times were obtained from Copa D’Or Hospital

The salaries are the gross salaries of the Copa D’Or Hospital workers

Cost (LS) Price per screening + 10

Price per screening - 7

Cost (NCT) Collection culture time per screening 0.01

Salary nurse/Hour 4.17

Cost (LTT) Technician time per screening + 3.00

Technician time per screening - 0.17

Salary laboratory technician/Hour 4.17

Targeted

Nº screenings + per admission 3%

Nº screenings – per admission 6%

Nº Total screenings per admission 9%

Universal

Nº screenings per admission 25%

Nº screenings - per admission 332%

Nº Total screenings per admission 357%

Total

Incremental nº screening + per admission 22%

Incremental nº screening - per admission 326%

Incremental nº screening per admission 348% Table 4 - Screening Cost Data

6.2.2 Contact Precaution Cost

Following the Eq.10 the contact precaution cost is calculated, considering for our study

that the under-screening patients is null and that the number of detected colonization is going

to increase. In the first case, the screening protocol did not change regarding to the admission

and thus the incremental number of under-screening patients is considered null. In the case of

the number of colonizations, due to the universal weekly screenings the number of detected

colonizations have increased and therefore that supposes a higher cost since there will be

more patients isolated. On the other hand, the number of infection cases has decreased with

the new control strategy and consequently that component of the contact precaution cost has

been reduced. It must be calculated that cost to understand how will affect this new infection

control programme.

In the Table 5 it can be seen the data used in the Eq.11-Eq.15 to calculate the material

cost and the cost associated to the healthcare staff where prices are given in BRL and time in

hours.

The number of visits was calculated from data collected at Copa D’Or Hospital

The material cost was obtained from (?)

The salaries are the gross salaries of the Copa D’Or Hospital workers

Infection Cost (M) Material Cost/Visit 0.48

Nº Visits/Patient/Day 49.24

Isolation LOS 36.50

Cost (PT)

Time Nurse/Visit 0.001

Nº Nurse visits per patient per day 41.44

Isolation LOS 36.50

Nurse Salary/Hour 233.33

Time Doctor per visit 0.001

Nº Doctor visits per patient per day 5.36

Isolation LOS 36.50

Doctor Salary/Hour 400.00

Colonization

Cost (M)

Material Cost/Visit 0.48

Nº Visits/Patient/Day 49.24

Isolation LOS 15.99

Cost (PT)

Time Nurse/Visit 0.00

Nº Nurse visits per patient per day 41.44

Isolation LOS 15.99

Nurse Salary/Hour 233.33

Time Doctor per visit 0.00

Nº Doctor visits per patient per day 5.36

Isolation LOS 15.99

Doctor Salary/Hour 400.00

Incremental number of infected per admission -0.97%

Incremental number of colonized per admission 0.95%

Number patients under screening per admission 0%

Table 5 - Contact Precaution Cost Data

It can be seen that the new control infection strategy has supposed a reduction of the total

contact precaution cost, since the reduction with the avoided infection cases is higher than the

rise of the component of the contact precaution cost by the increment of the detected

colonization cases.

6.2.3 Infection Cost

According to the Eq.17 the infection cost would be:

Again, due to the negative incremental number of MDR infection cases, the infection

cost has been reduced from the previous control strategy. In the Table 6 it can be seen the

main data used to calculate the infection cost where prices are given in BRL:

The antibiotic cost per patient was obtained from

Infection

Cost

Antibiotic Cost per patient 2000

Incremental number of MDR infection cases per admission -0.97% Table 6 - Infection Cost Data

6.2.4 Total Cost

Following the Eq.5 the incremental total cost per admission would be:

The new infection control strategy has an incremental cost of 4.29 BRL per admission,

however at the same time it has some benefits that are going to be measure in the next section

in order to compare them and to assess if the new intervention is cost-effectiveness.

6.3 Effectiveness

6.3.1 First Period

Following the section 5.4 the effectiveness is calculated as QALYs per patient. From the data

of all the ICU patients the LYs during the hospitalization (First Period) are obtained and

expressed in the Table 7 in years for each study group.

1. Non MDR patients

2. Non MDR fatal patients

3. MDR colonized patients

4. MDR colonized fatal patients

5. MDR infected patients

6. MDR infected fatal patients

LYs During Hospitalization

Without MDR Group 1 0.02

Group 2 0.03

MDR Colonized Group 3 0.09

Group 4 0.08

MDR Infected Group 5 0.27

Group 6 0.22 Table 7 - LYs Period 1

As it was expected, the infected patients have the highest LOS, next by the colonized

patients. During the hospitalization the utility weights will depend on the health status of the

patient, considering two:

i. Patients without MDROs and MDR colonized patients: These patients have a

utility weight equal to 0.66, which was obtained from the Cost-Effectiveness

Analysis Registry of the Institute for Clinical Research and Health Policy

Studies, Tufts Medical Centre.

ii. MDR infected patients: This group which is formed by the Group 5 and Group 6,

has a utility weight during the non-infected hospitalization of 0,66 as in the

previous case, and a score of 0,6 during the infected hospitalization period, which

were obtained from the same database. Obviously, this last score must be lower

than the previous one since the health status is worse. The period without

MDROs was obtained from the clinical data and it represents a 45.6% of the total

LOS.

6.3.2 Second Period

According to the Eq.24 the estimation of the total LYs per patient, which depend on the

age and percentage of males and females and consequently it depends on the study group, it

is shown in the in years:

Total LYs


Group 2 0.03


Group 4 0.08


Group 6 0.22 Table 8 - Total LYs

As the Group 2, Group 4 and Group 6 do not survive to the hospital stay, the total LYs

are the same that the LYs in the first period. On the other hand, the Group 1 (patients without

MDROs) has a higher total LYs than the Group 3 (MDR colonized patients) and Group 6

(MDR infected patients) because of the younger age profile. It can be appreciated the big

dependence on the age with the Brazilian life expectancy table used [56]:

Age

2016

Total Men Women

0 75.8 72.2 79.4

1 75.8 72.3 79.3

5 72.0 68.5 75.5

10 67.0 63.6 70.6

15 62.1 58.7 65.7

20 57.5 54.1 60.8

25 52.9 49.8 56.0

30 48.3 45.3 51.1

35 43.7 40.9 46.4

40 39.1 36.5 416

45 34.7 32.2 37

50 30.3 28.0 32.5

55 26.2 24.1 28.2

60 22.3 20.3 24.0

65 18.5 16.8 20.0

70 15.1 13.6 16.3

75 12.1 10.8 13.0

80 years

and over 9.5 8.5 10.2

Then, according to the Eq.26, the LYs for the second period is calculated:

LYs Post Discharge


Group 2 0.00


Group 4 0.00


Group 6 0.00

The utility weight used for the second period is estimated for ICU patients after

discharge in [51], [54] as 0.677, constant for each group.

6.3.3 QALY gained

Finally, weighting the LYs of both periods with the commented scores above, the QALY

for each group is calculated. Then, considering the Eq. 28-30, the QALY is calculated for the

three main health status groups (without MDR, colonized and infected) as it can be seen in

the Table 9, where the “%P” represents the percent of each study group (fatal, non-fatal) for

the belonging health group (non-MDR, MDR Colonized and MDR Infected).

Total QALYs %P Total QALYs per state

Without

MDR Group 1 14.50 0.94

13.58 Group 2 0.02 0.06

MDR

Colonized Group 3 13.81 0.51

7.06 Group 4 0.06 0.49

MDR

Infected Group 5 12.40 0.49

6.21 Group 6 0.14 0.51

Table 9 - QALYs per group

In order to calculate the QALYs gained per avoided infection and colonized case the

Eq.31-32 are used:

QALYs gained per avoided colonization case 6.52

QALYs gained per avoided infection case 7.37 Table 10 - QALYs gained per avoided case

Considering the avoided colonization and infection cases the total QALYs gained can be

calculated. Since the clinical data for the colonization cases in the previous strategy are not

available, it is supposed that the number of incremental colonization cases for the QALYs

gained calculation is null. However, as theoretically the number of colonization cases should

decrease, a sensitivity analysis will be performed later in order to analyse this behaviour. The

number of avoided infected cases with the new strategy is 38, and therefore the total QALYs

gained would be:

Avoided infection cases per year 38

Total QALYs gained 280.12

Nº admissions per year 3904

Total QALY gained per admission 0.07175 Table 11 - Main QALY outcomes

The QALY gained per admission seems a small value but it must be considered that it

depends on the avoided infection and colonization cases per admission which is a really tiny

value.

6.4 ICER

After calculating the incremental cost per admission and the QALYs gained per

admission, the ICER can be calculated following the Eq.34:

To assess the cost-effectiveness of the project the ICER is compared with the Brazilian

GDP per capita (32580.9 BRL) since the main cost-effectiveness threshold are based on a

percentage of the GDP:

The most conservative threshold was given by the University of York of 21% - 67% of

the GDP per capita [40], which is much higher than the result obtained in our study.

Therefore, the new control infection strategy settled at the Copa D’Or hospital has been very

cost-effective.

6.5 Sensitivity Analysis

Due to the lack of information about the number of colonization cases in the previous

strategy, the incremental number of avoided colonizations was supposed null. However, as it

can be inferred theoretically, the number of colonization should decrease due to the reduction

in the transmission of MDROs caused by the new control measures. Therefore, that would

suppose a rise of the total QALYs gained and consequently a lower ICER.

On the other hand, since the number of detected colonization cases have increased with

the new strategy on account of the weekly screenings, the material cost has raised because of

the growth of isolated patients. With the theoretical reduction of colonization cases there

would be a decrease in the total cost of the new intervention and therefore the ICER would be

lower as well.

There must not be confusion with the rise of detected cases and the reduction of the real

cases. The misunderstanding is caused by the fact of the non-detected colonization cases in

the previous strategy, where there were colonized patients not isolated.

Accordingly, the reduction of the number of colonization cases leads to a lower

incremental cost per admission (it may be negative) and to a higher QALYs gained per

admission. Therefore, as less colonization cases lower ICER, as it can be seen in Figure 17

where the sensitivity analysis was performed from 0 colonization cases to 38, which is the

number of avoided infection cases. It has been taken a conservative scenario supposing that

the reduction in the colonization cases should be the same than the avoided the infection

cases.

Figure 17 - Sensitivity Analysis

As it can be seen in the Figure 17, from 33 avoided colonization cases the incremental

cost becomes negative which means that there is a reduction in the total cost with the new

strategy compared to the previous one. From that moment, the new intervention is cost-

saving and there are no doubts that it must be adopted. At the same time, the QALYs gained

per admission keeps growing, however as the growth rate is lower than for the incremental

total cost the ICER is becoming increasingly negative instead of converging to zero, although

in both cases the project is cost-saving and totally cost-effective.

-10

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39

Numer of avoided colonization cases

Main Outcomes vs Avoided Colonization Cases

ICER Incremental Total Cost*10 Total QALYs gained per admission*250

7 CONCLUSIONS

The implementation of the new infection control programme at the ICU of the Copa

D’Or hospital has been very cost-effective as the results shows. The Incremental Cost

Effectiveness Ratio (ICER) was 59.63 BRL per Quality-Adjusted Life-Year (QALY) gained,

which means that the Copa D’Or spends approximately 60 BRL to increment one year in

perfect health conditions the life of the hospital patients. The QALYs gained are a measure of

the health benefits of the new intervention, which aim to be a measure comparable among

different interventions, different patient groups in different clinical areas. It must be

remembered that the main benefit of this study is the number of avoided infection and

colonization cases, however, in order to give a general result that could be studied and

compared with other clinical projects, the QALYs are chosen as the main effectiveness

outcome, which would be a translation of the number of avoided colonization and infection

cases to a general index.

The ICER is a 0.18% of the Brazilian GDP per capita, much lower than the thresholds

recommended in the literature, and therefore the new control infection strategy is situated in

the region very cost-effective. Despite being much lower than the cost-effectiveness

thresholds of the literature, the Copa D’Or hospital, as health decision-making organism,

should develop an own value to analyse the different potential projects and to allocate the

economic resources efficiently, since that value depends heavily on the characteristics of the

decision-making body and obviously it varies according to the objectives and preferences.

A QALY calculation methodology has been developed in order to increase the literature

about this topic. Since the QALY is a general effectiveness measure of an intervention which

can belong to different health areas, it must be understood that the benefit related to the

QALY, as avoided colonization and infection cases in our case, can vary along the projects.

However, it can always be translated into QALYs, and considering the specific periods and

study groups it can be adapted for each case. In our case, there were adopted two calculation

periods and six study groups to model the problem. The periods were selected due to the two

different parts on the patient life, during the hospital stay and the post-discharge, and the six

study groups which were chosen according to the three health status (without MDROs, MDR

colonized and MDR infected) and their two variations (survivor to the hospital stay and death

during the hospitalization). It could happen that in other scenarios the calculation periods or

the study groups vary, but the essence of the methodology would remain calculating the

QALYs for each group and then obtaining the QALYs gained as final outcome.

Due to the lack of information about the total number of MDR colonization cases in the

previous control strategy one of the hypothesis of the study was to assume null the

incremental number of colonization cases. This lack of information was caused by the

absence of symptoms of the colonized patients which together with the previous infection

control strategy that did not have weekly screenings, it made impossible to detect all the cases

of colonization. That scenario without a reduction on the number of colonization cases was

the most conservative, although as it can be inferred theoretically, there should be less cases

of colonization. Therefore, adopting a positive increment of the avoided colonization cases,

the intervention would be more cost-effective since there would be a higher QALYs gained

and a reduction in the incremental total cost, and consequently it would be obtained a lower

ICER as it was shown in the section 6.5-Sensitivity Analysis. This analysis is very illustrative

since the project becomes cost-saving from 33 avoided colonization cases where the new

intervention would be a total success. It is to be recalled that the number of avoided MDR

infections per year was 38 and therefore 33 avoided colonization cases is a reasonable

assumption. Hence, the project is absolutely cost-effective and at the same time it could be

cost-saving.

It is worth commenting that the new infection control programme is very cost-effective

in spite of the high mean age of the ICU Copa D’Or cohort, which influences in the

effectiveness since one of the main components of the QALYs is the quantity of live. The

effectiveness of the infection control programme accounts both on the length of stay and the

period post-discharge, which are related to the MDR infections. The MDR infections have

influence in the LOS and also in the mortality rates which influence the QALY in that period

post-discharge. An old cohort has a lower QALY in that period post-discharge and therefore

the total QALY is smaller than if the cohort were younger.

Even though the cost-effectiveness threshold is sensitive subject since there is not an

agreement about how much it should be that value, in our study it is not necessary since is

very cost-effective and it could even be cost-saving. However, in order to use systematically

the CEA to allocate the resources effectively, the Copa D’Or and all the health organisms,

both public and privates, should define a cost-effectiveness threshold since that value should

be calculated according to their specific characteristics and context.

Concerning the discounting rates, in this study they have not been applied, either for the

cost or the effectiveness. For the case of the cost, the main reason is that the study was

comparing two consecutive situations, a previous and a current strategy, and therefore they

are not compared parallelly along the time. On the other hand, the use of discounting rates for

the QALY is not going to be considered in this study since that value should be set by the

decision-making organism. Low rates lead to prioritization of immediate policies and high

rates favour long-term health measures, and therefore, in order to establish a health policy for

all the projects the Copa D’Or hospital should firstly set a discounting rate according to its

health policy. A possible future study could be to investigate a common discounting rate,

since in these kinds of programmes most of the costs are incurred at the present moment and

health benefits occur in the far future and thus the discounting would have a great impact on

these analyses.

8 LIMITATIONS AND FUTURE STUDIES

In the cost calculation some assumptions were made due to the lack of official

information. In the contact precaution cost, the material cost was not taking from the

expenses of the hospital as it was firstly thought, but it had to be collected from other studies.

The same happened with the cost of the antibiotic treatment per patient, that ideally it would

have been to take it from the expenses of the hospital and however, it had to be collected

from other scientific articles.

The databases were created by different hospital departments what led to some

incompatibilities which could suppose a lack of information. A possible solution would be to

use common patient’s identifiers as the “Patient Record Number”, which is a unique index

for each patient. In that way, there would not be problems to identify the same patient in two

different databases.

The QALY calculation methodology should be standardized in order to create for each

making-decision organism a unique calculation procedure. Therefore, the Copa D’Or should

review the CEA and create its own methodology to assess its different projects equally. The

same happens with the discounting rates, both for the cost and the effectiveness. They

influence heavily on the ICER and hence, they should be calculated and aligned according to

the health politics and objectives.

Some studies should be also carried in order to develop new cost-effectiveness threshold

considering the specific context and characteristics of the health organisms. This value

determines if the intervention is cost-effective and therefore it is highly important to set it

according to the specific economical and clinic considerations of the making-decision

organism.

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