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• Comparative Study BMC Public Health

• . 2019 Jan 22;19(1):97. doi: 10.1186/s12889-019-6442-9.

Too much medicine? Scientific and ethical issues from a comparison between two conflicting paradigms

Francesco Attena  ¹ Affiliations

• PMID: 30669992
• PMCID: PMC6341674
• DOI: 10.1186/s12889-019-6442-9

Free PMC article

Abstract

Background: The role of medicine in society appears to be focused on two views, which may be summarized as follows: “Doing more means doing better” (paradigm A) and “Doing more does not mean doing better” (paradigm B).

Main body: I compared paradigms A and B both in terms of a single clinical condition and in the general context of a medical system. For a single clinical condition, I analyzed breast cancer screening. There are at least seven interconnected issues that influence the conflict between paradigms A and B in the debate on breast cancer screening: disconnection between research and practice; scarcity of information given to women; how “political correctness” can influence the choice of a health policy; professional interests; doubts about effectiveness; incommensurability between harms and benefits; and the difficulty in making dichotomous decisions with discrete variables. As a general approach to medicine, the main representative of paradigm A is systems medicine. As representatives of paradigm B, I identified the following approaches or movements: choosing wisely; watchful waiting; the Too Much Medicine campaign; slow medicine; complaints against overdiagnosis; and quaternary prevention. I showed that both as a single condition and as a general approach to medicine, the comparison was entirely reducible to a harm-benefit analysis; moreover, in both cases, the two paradigms are in many respects incommensurable. This transfers the debate to the ethical level; consequently, scientists and the public have equal rights and competence to debate on this subject. Moreover, systems medicine has many ethical problems that could limit its spread.

Conclusion: I made some hypotheses about scenarios for the future of medicine. I particularly focused on whether systems medicine would become increasingly accessible and widespread in the population or whether it would be downsized because its promises have not been maintained or ethical problems will become unsustainable.

Below is the full article, for those of you interested in more information. It is a bit esoteric, unless you are an academic. The abstract above will do for most of my readers.

Keywords: Breast cancer screening; Ethics; Harm-benefit assessment; Incommensurability; Paradigm; Systems medicine; Too much medicine.

D E B A T E Open Access
Too much medicine? Scientific and ethical
issues from a comparison between two
conflicting paradigms
Francesco Attena

Background
Current tendencies regarding the role of medicine in so-
ciety and about the extent of interventions for a popula-
tion appear to be focused on two opposite views, or
paradigms. Those paradigms may be summarized as fol-
lows. According to paradigm A (PA), “Doing more
means doing better.”Conversely, according to paradigm
B (PB), “Doing more does not mean doing better.”
In the past, these two views have had their various ad-
vocates. Against the excess of ineffective treatments, the
movement of therapeutic nihilism took place at the end
of the nineteenth century. However, in the early twenti-
eth century, doctors had to choose between Galenic
methods (purges, emetics, and bloodletting) and the
Hippocratic method (wait, observe, console) [1]. Cur-
rently, the highest expression of PA is found in systems
biology and systems medicine [2]. By contrast, PB is
Correspondence: francesco.attena@unicampania.it
Department of Experimental Medicine, School of Medicine, University of
Campania, Via Luciano Armanni 5, 80138 Naples, Italy
© The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Attena BMC Public Health (2019) 19:97
https://doi.org/10.1186/s12889-019-6442-9represented by various approaches and movements that
oppose the excesses of modern medicine. The propensity
toward PA or PB is also an attitude of individual health
operators in terms of being more or less interventionist.
The propensity may also be a cultural feature of particu-
lar nations; for example, the United States is a typical
PA country.
Since its origins, modern medicine has become pro-
gressively more invasive into people’s lives and into soci-
ety in general in pursuit of its goal of always seeking to
improve. Beyond the purpose of doing more and doing
something better, the main reasons for such develop-
ments are well known. From the perspective of the citi-
zen, the reasons are as follows: improving the quality of
life; the obsessive search for well-being; unrealistic ex-
pectations about the ability of medicine to solve all
health problems; health anxiety (i.e. the distress, anxiety
or sensation of serious illness, often unfounded, that a
person feels regarding his/her personal health); the
changed doctor-patient relationship from a paternalistic
to an equal one. From the medical viewpoint, these new
attitudes have led to greater medical-legal disputes and
the birth of defensive medicine. Lastly, health industries
foster health consumerism for the purpose of pursuing
profits through increasingly expensive drugs and con-
stant technological innovation. All these modern condi-
tions are closely related and lead (both in the clinic and
in terms of prevention, both diagnostically and thera-
peutically) toward medical interventionism rather than
non-interventionism.
At the individual level, the best-known consequences of
this hyper-interventionism have been overdiagnosis and
overtreatment [3]; at the social level, the consequences
have been the concept of medicalization in the negative
sense and the problem of economic unsustainability of
public health systems. These negative consequences and
the anomalies of Kuhnian language have given rise to PB
following the classic scheme of a paradigm shift [4].
The present study makes a comparison between PA
and PB. It mainly does so in terms of clinical practice
and preventive diagnosis: it adopts this approach be-
cause early diagnosis underscores the main differences
between the two paradigms. Moreover, the two para-
digms are compared with respect to a single clinical con-
dition and with the general medical system. Maintaining
Kuhnian terminology, I apply the concept of incommensur-
ability in both situations. Incommensurability is deeper and
better suited to the needs of the present discussion than
other more generic concepts, such as incomparability, dis-
similarity, and divergence. I are aware that the rigid oppos-
ition between these two points of view is somewhat
artificial, the reality is more nuanced than the two para-
digms indicate. Therefore, this simplification allow us to
formulate a more linear and comprehensible reasoning.
Incommensurability
Incommensurability has different meanings. In mathem-
atics, it signifies that items cannot be precisely measured
and compared using some common scale of unit of
values. However, in the present study, I use the term in
a way similar to the Kuhnian sense. In that sense, scien-
tific theories are incommensurable if scientists cannot
discuss them using a shared nomenclature that allows
direct comparison of theories to determine which is
more valid or useful. The reason for that lack of com-
parison is that the theories belong to two different scien-
tific paradigms [4].
In this study and following the above definition, I use the
term “incommensurability”in two ways: with respect to a
single disease and with respect to the entire medical system.
A) Incommensurability of harm-benefit assessment.
This occurs when the harms and benefits for a particular
disease affect different domains of health status [5],
which generates a conflict between PA and PB. Of
course, I are aware that there are many conditions in
which the harms and benefits can be compared through
a common denominator (for example, mortality,
quality-adjusted life-years); however, I believe that the
incommensurability of harms and benefits is an underes-
timated topic, and so I addressed the following
condition.
B) Incommensurability between paradigms. In the first
instance, I assumed that PA and PB ignore each other:
they do not have a common language and do not try to
work together to find a shared solution. Ultimately, a
comparison between PA and PB is entirely reducible to a
(meta-) assessment between the harms and benefits.
I begin my analysis with an examination of a single
disease: I present, as an example, the debate about breast
cancer screening. I then investigate PA and PB in the
general context of medical systems.
Incommensurability of harm-benefit assessment
Debate about breast cancer screening
Breast cancer screening is a good example of a conflict
between two different approaches to screening: PA fa-
vors performing it; PB does not. Moreover, breast cancer
screening is particularly interesting because it is a
much-debated topic. There are at least seven intercon-
nected issues that influence the conflict between PA and
PB: disconnection between research and practice; scar-
city of information given to women; how “political cor-
rectness”can influence the choice of a health policy;
professional interests; doubts about effectiveness; incom-
mensurability between harms and benefits; and the diffi-
culty in making dichotomous decisions with continuous
variables.
The first four items are not strictly scientific issues
with respect to PA. Unlike with the many doubts
Attena BMC Public Health (2019) 19:97 Page 2 of 8highlighted by scientific debate, the benefits and effect-
iveness of screening are still overestimated in clinical
practice [6–8]. For many health operators, the difficulties
include updating procedures (disconnection between re-
search and practice); at the population level, the infor-
mation to women is still partly biased toward screening
(scarcity of information given to women) [9, 10]. In
many countries (and in my experience, it is certainly the
case in Italy), it is not possible to speak against screen-
ing; according to [11], even some scientists have sacri-
ficed sound scientific principles to arrive at politically
acceptable results. Finally, many health operators can
distort the judgment about the utility of screening owing
to their particular interests in the field (e.g., as radiolo-
gists, surgeons, breast specialists) [12].
From a scientific perspective (the final three items in
the above list) the debate about breast cancer screening
is intense and engaged on two levels. The first level con-
cerns effectiveness: beside the great amount of studies
which have summarized the effectiveness of breast can-
cer screening [13–17], other studies have strongly ques-
tioned the ability of screening to reduce mortality [18–
22]. If the effectiveness is accepted, the second level of
discussion concerns the harm-benefit ratio: on the one
hand, prevention of breast cancer mortality, and on the
other hand, diagnostic anticipation, false positives, false
positives after biopsy, and overdiagnosis [23–27].
The Canadian Task Force calculated that in the
age-group of 40–49 years for each death from breast can-
cer prevented, it is necessary to screen 2108 women for
11 years, with 690 false positives and 75 false positives
after biopsy. For the age-range of 50–69 years, the figures
are 721 women, 204 false positives, and 26 false positives
after biopsy [28]. Overdiagnosis is a recent, controversial
issue owing to the difficulties involves in calculation [29].
The Independent UK Panel on Breast Cancer Screening
calculated that for each death from breast cancer pre-
vented, there are three overdiagnoses [13]. A more recent
study investigated age-specific overdiagnosis for ductal
carcinoma in situ and invasive breast cancer; it obtained a
wide range of results: less than 1% among 40-year-old
women with a screen detected cancer, up to 30% at age
80 years for ductal carcinoma in situ [30].
The US Preventive Service Task Force (USPSTF) recom-
mends biennial screening mammography for women aged
50–74 years as a B recommendation. The task force makes
that recommendation using a rather convoluted statement:
“The USPSTF recommends the service. There is high cer-
tainty that the net benefit is moderate or there is moderate
certainty that the net benefit is moderate to substantial”[16].
Incommensurability and undecidability
It is necessary to determine what these data tell us about
the harm-benefit ratio. From a scientific viewpoint, the
data are not very enlightening owing to the difficult in
assessing that ratio. From an ethical perspective, an in-
soluble dilemma results. The dilemma arises mainly be-
cause in this example, harms and benefits are
incommensurable. First, they belong to substantially dif-
ferent domains [5], i.e., preventing death versus various
harms. Second, regarding the difficulty in making di-
chotomous decisions on continuous variables, that
means (simplifying the argument), how many overdiag-
noses (or, e.g., false positives) are acceptable for each
prevented death.
Borrowing the language of mathematics and comput-
ability theory, undecidability derives from incommensur-
ability, i.e., the impossibility of constructing a rule that
leads to a correct yes-or-no answer. Thus, given the
same initial conditions of scientific data, the final choice
in conducting or not conducting screening is an ethical,
not a scientific, issue. Scientists and the public have
equal rights and competence to express an opinion on
this subject. Indeed, the most recent and increasingly
shared solution to the problem has been to release the
final decision (and the dilemma!) to women [28]. How-
ever, new problems arise from this new approach since
women’s preference collides with uncertainty about the
benefits and harms; moreover, the transfer of responsi-
bility is a forcing of the informed choice and can cause
trouble to women [31]. The Population-based Research
Optimizing Screening through Personalized Regimens
initiative has been promoted by the US National Cancer
Institute: it is based both on patient preferences and on
optimizing the personalized benefit-harm ratio associ-
ated with screening [32, 33].
Regarding the main topic of my discussion, many sci-
entists seem to ignore this dilemma. Scientists disposed
to PA support the intervention; those disposed to PB
discourage it.
Incommensurability between paradigms
PA: Systems medicine the main representative
Systems medicine is an application in the medical field
of systems biology [34], which developed at the begin-
ning of this century [35]. Systems medicine is also
termed P4 systems medicine (P4SM) because it claims
to be Predictive, Preventive, Personalized, and Participa-
tory. Predictive and Preventive are strictly interrelated
items, as reported by [36]: “Moreover, P4 medicine will
in the future be able to predict the potential future
emergence of disease-perturbed networks in patients
and then design ‘preventive drugs’that will block the
emergence of these disease-perturbed networks and
their cognate diseases.”P4SM is Personalized: it con-
siders each person as a unique individual and not as a
statistical average. Therefore, each person is treated in a
personalized way based on the big data collected during
Attena BMC Public Health (2019) 19:97 Page 3 of 8continuous monitoring. This intervention requires active
participation and a positive contribution from the popu-
lation; in this way, P4SM is able to provide actionable in-
formation, which it can use to improve health.
To achieve the P4 goals, P4SM has to integrate data
from conventional sources (including paper patient re-
cords, clinical and pathological parameters, and molecu-
lar and genetic data) and new sources (originating from
statistical, mathematical, and computational tools). The
procedure requires teams that combine expertise from
different disciplines as well as continuous spatial and
temporal monitoring of every individual. That will allow
the extrapolation, analysis, and relating of a huge
amount of heterogeneous, structured, and unstructured
data (big data) to determine the links between different
phenomena and predict future ones.
To obtain a prediction regarding the status and behav-
ior of a medically monitored person, it is necessary to
proceed according to the following steps [2]. First, it is
necessary to identify the system variables whose meas-
urement and observation can be used to answer a par-
ticular question. Second, the interaction among those
variables has to be characterized at the molecular, cellu-
lar, and whole-body level. Third, the consequences of
such interaction have to be determined using a process
whereby a complex system (the human body) may be
assessed through reduced representation.
The consensus related to this new approach to medi-
cine and its dissemination are highlighted by a number
of international institutions working in the field. Exam-
ples include the Institute for Systems Biology in Seattle,
United States [37], the European Institute for Systems
Biology and Medicine [38], and the Suzhou Institute of
Systems Medicine, China [39].
P4SM is the only international organized movement
for the PA model. However, at the international level, PB
is represented by numerous approaches, movements,
and campaigns, often connected with one another. The
PB approaches include the following: choosing wisely,
watchful waiting, the Too Much Medicine campaign,
slow medicine, complaints against overdiagnosis, and
quaternary prevention. I hope that my list is fully com-
prehensive, and I present below a short summary of each
one.
PB: Approaches and movements
Choosing wisely
Choosing wisely is probably the most widespread and
structured movement featuring PB. Its mission is to pro-
mote dialogue between clinicians and patients by helping
patients choose care that is as follows: supported by evi-
dence; not duplicative of other tests or procedures
already received; free from harm; truly necessary [40].
The core idea is to reduce overutilization of
inappropriate and essentially harmful tests, treatment,
and procedures. This movement is known for having
launched in 2012 a campaign that invites all medical
specialty societies to develop a list of five tests and
procedures that physicians and patients should ques-
tion [41].
Watchful waiting
Watchful waiting is not an organized movement: it is an
approach to health problems. It is an alternative to more
aggressive treatment, whereby time is permitted to pass
before applying a medical intervention or therapy, and it
makes use of patient involvement [42]. Prostate cancer
has received considerable attention in this regard [43].
This approach is also promoted by the National Cancer
Institute, which in its Dictionary of Cancer Terms de-
scribe the concept of watchful waiting as follows:
“Closely watching a patient’s condition but not giving
treatment unless symptoms appear or change. Watchful
waiting is sometimes used in conditions that progress
slowly. It is also used when the risks of treatment are
greater than the possible benefits”[44].
Too much medicine campaign
At the end of the past century, a long debate began with
The BMJ on the theme of “too much medicine?”[45].
The campaign later became formalized and has a dedi-
cated Web site [46], which specifies the following: “The
BMJ’s Too Much Medicine initiative aims to highlight
the threat to human health posed by overdiagnosis and
the waste of resources on unnecessary care. We are part
of a movement of doctors, researchers, patients, and pol-
icymakers who want to describe, raise awareness of, and
find solutions to the problem of too much medicine.”
Slow medicine
The organized movement of slow medicine began in
Italy in May 2011. The background to the movement is
respect for nature and the environment, a sense of just-
ice, and an aversion to waste and consumerism [47].
These ideas are shared with those of another movement,
Slow Food, with whom Slow medicine undertakes con-
tact and collaboration. In the declaration of the slow
medicine movement, seven “poisons”of fast medicine
are described. Collaboration of slow medicine with
choosing wisely came about with the creation of Choos-
ing Wisely Italy [48].
Complaints against overdiagnosis
Overdiagnosis and overtreatment are the most insidious
consequences of overuse of medical interventions [49].
Therefore, all the studies and authors that denounce it
completely belong to PB. Here, the topics are not new;
however, they have gained international resonance in
Attena BMC Public Health (2019) 19:97 Page 4 of 8recent years as mathematical models have been used to
calculate the magnitude of overdiagnosis and overtreat-
ment. Pathirana et al. [50] identified five drivers of overdi-
agnosis: culture; health systems; industry; professionals;
and patients/public.
Quaternary prevention
This approach to medicine has been formalized in the
concept of “quaternary prevention,”and it has particu-
larly developed in the field of general practice [51]. In-
deed the concept of quaternary prevention appears in
the WONCA International Dictionary for General/Fam-
ily Practice, where it is defined as “Action taken to iden-
tify patient at risk of overmedicalization, to protect him
from new medical invasion, and to suggest to him inter-
ventions, which are ethically acceptable”[52].
I now present a comparison between PA and PB. First,
I analyze their sensitivity and specificity; then, I assess
their reduction to a harm-benefit ratio.
Sensitivity and specificity of the two paradigms
As systems medicine, PA pursues the goal of monitoring
(in a continuous spatial and temporal modality) all indi-
viduals. Therefore, owing to this putative ability to pre-
dict and prevent each future disease, PA has a very high
sensitivity: theoretically, almost 100% for any clinical
condition. However, the specificity and positive predict-
ive value are supposedly low, depending on such factors
as the disease, its prevalence, and the threshold used. By
contrast, PB acts with restraint and when there is cer-
tainty of a favorable balance in terms of harms and ben-
efits. Thus, for each disease, PB has a high specificity
and high positive predictive value: only a small part of
the population will be diagnosed and treated, i.e., indi-
viduals who are more probably ill or for whom interven-
tions are more appropriate. Obviously, this approach has
low sensitivity, which entails the risk of losing sick
people. A well-known ancient ethical dilemma, applied
to single clinical problems (as I saw previously with
breast cancer screening), here applies to the whole
population: to include all sick people at the cost of treat-
ing many both overdiagnosed and healthy individuals
(overdiagnosis, overtreatment), or not to include all sick
people (underdiagnosis, undertreatment) with the advan-
tage of not treating healthy individuals.
Reduction of comparison between PA and PB in harm-
benefit assessment
Translating these considerations to the field of
harm-benefit assessment, PA and PB have different ap-
proaches. In brief, PA entails high sensitivity, more bene-
fits, and more harms; PB entails high specificity, fewer
harms, and fewer benefits. Let us imagine ideal condi-
tions under which both PA and PB offer the better
performance. PA attempts to obtain maximum benefits
for the population at the cost of increasing the damage
somewhat (more benefits and a few more harms). PB
tries to achieve minimum harms for the population at
the cost of decreasing the benefits somewhat (fewer
harms and slightly reduced benefits). This is the kind of
incommensurability that I intend to address in compar-
ing PA and PB: it is the impossibility of making a correct
decision starting from these ideal conditions (undecid-
ability). In my opinion, these are the core issues that
arise from such a comparison. Therefore, the questions
“Which is better?”and “Who is right?”are much too
simplistic, or even nonsensical.
Epistemological and ethical issues for PA
Thus, far I have focused on a comparison mainly of
health aspects. If I broaden the horizon, PA, unlike PB,
has epistemological contradictions and ethical troubles;
PB involves potential harm for the population.
From an epistemological perspective, P4SM aims to
achieve a shift in medicine from a reductionist approach
to a holistic one: its tools take into account the complex-
ity of the human body [53]. The main contradiction with
this stance is that the complexity (in which the whole is
greater than the sum of its parts) and holism are epis-
temologically incompatible with the type of predictivity
claimed by P4SM. Thus, its flaunted predictive capacity
could be an illusion. Moreover, I perceive the predictivity
of P4SM as a return to the strictly deterministic ap-
proach to nature and to the human being. That is, if I
consider each person a microcosm, it recalls the old dec-
laration of Laplace’s demon [54]: if a demon knows the
precise location and momentum of every atom in the
universe, their future values for any given time are
entailed. In terms of P4SM, this amounts to the follow-
ing: if big data knows the precise location and momen-
tum of every biological parameter for each individual,
that person’s future values for any given time are
entailed. In conclusion, I believe that P4SM is not a
paradigm change, as suggested in [55]; it is an extreme
form of the current PA and that Vogt et al. [56] define
as a “technoscientific holism.”
From an ethical viewpoint, several criticisms have been
made. Health anxiety [57] and cyberchondria [58], the
modern versions of old hypochondria, have appeared
and are a consequence of the current trend of medicine
becoming increasingly invasive. The boomerang effect is
that people are not feeling healthier but are constantly
anxious about their health. These conditions could in-
crease with the spread of systems medicine: it could be-
come widely invasive of human life, and it has
implications of social and cultural iatrogenesis up to the
medicalization of health and life itself [56].
Attena BMC Public Health (2019) 19:97 Page 5 of 8Other AA. underline the risks to individuals in the cir-
culation of uncovered negative or potentially discrimin-
atory health-related findings [59]. Mittelstadt and Floridi
[60] consider big data particularly challenging from an
ethical perspective owing to the sensitivity of health data
and the fiduciary nature of health care; they identify 11
ethical risks connected to the spread of big data.
Further difficulties arise from the compatibility of pre-
dictive decisions derived from big data with the princi-
ples of clinical practice and evidence-based medicine.
This is because systems medicine is a top-down model,
providing clinicians with a computer algorithm; it is not
based on clinical evidence and research [61].
Despite these limits, the words of the advocates of sys-
tems medicine are attractive and astonishing because they
promise to free humanity from the burden of disease:
“Regular check-ups will allow the physician to longitudin-
ally follow each patient and detect any perturbation that
might lead to disease long before the onset of disease
symptoms. In this manner, an individual’s wellness can be
preserved without the disease state ever occurring”[62].
Conclusions
What lessons can be drawn from analyzing PA and PB
if—beyond their intentions—neither PA nor PB can keep
their promise of better health? What do we want from
the medicine of the future: greater benefits but greater
harm, or fewer harms and fewer benefits? Different sce-
narios are possible.
Shift to PA
Owing to the ineluctable evolution of science and medi-
cine, PA, as systems medicine, could become increas-
ingly accessible and widespread in the population. Some
or many countries will include systems medicine in their
national health services; accordingly, many people or the
whole population under such health services will be
treated in that way. Therefore, PA could steadily become
the dominant paradigm and PB could become marginal
or disappear.
Shift to PB
Over time, the promises of systems medicine are not
maintained; that is because ethical problems arise, risks
and harms are recognized, and the power of big data
prediction is not realized. Furthermore, if such promises
were partially or totally realized, the management of all
that information would still be difficult, and the costs
would become unsustainable. Together with the down-
sizing of PA, the concepts of overdiagnosis and over-
treatment would become established and spread to the
population. Thus, demand for PB would become domin-
ant, and medicine would be practiced in a more con-
tained, sober, and sustainable manner. PA could
disappear or maintain a niche of activities for a few
health obsessives, who voluntarily wish to undergo con-
tinuous monitoring. This development would be favored
by a change in the world capitalist structure, with a
downsizing of the dominant neoliberalism that is the
cultural ground on which P4SM develops.
Simultaneous presence of PA and PB
If the debate between the two paradigms is intrinsically
undecidable because it is impossible to construct ad-
equate decision making, then the debate could never
end. Therefore, this scenario constitutes the persistence
over time of the equal presence in epistemology and
health policies of these two visions of medicine. PB
could gain more support, continuing to counteract the
excesses of PA and declaring the risks of too much
medicine. PA could be available, free or at a cost, for
people who wish to undergo it.
Harm-benefit assessment between PA and PB
The choice between PA and PB refers essentially to a
harm-benefit ratio. Thus, in the future it will perhaps be
possible to overcome the incommensurability between
them using the same big data as PA and performing a
kind of meta-analysis harm-benefit analysis comparing
PA and PB for all health problems and for all the popu-
lation: ex ante, that could be achieved using sophisti-
cated mathematical models; ex post, the analysis could
compare populations submitted to P4SM with those not
submitted to it. Moreover, it is also likely that in any sce-
nario, the role of patients will become increasingly
decisive.
In conclusion, the future attitude of medicine and
health systems will depend not only on the ability to
demonstrate the best health outcomes but also on a
complex intertwining of political, economic, social, and
cultural factors.
Abbreviations
P4SM: P4 systems medicine; PA: Paradigm A; PB: Paradigm B
Acknowledgements
None.
Funding
None.
Availability of data and materials
Not applicable.
Authors’contributions
The author read and approved the final manuscript.
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Attena BMC Public Health (2019) 19:97 Page 6 of 8Competing interests
The author declares that he has no competing interests.
Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
Received: 7 September 2018 Accepted: 14 January 2019
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