Value
Constructing generic health value measures may not be possible,25 but assessing the value of health is more
appropriate and having a framework like the triple aim provides a simple
and comprehensive approach. With the complexity of measuring
consequences of disease and the total value of health over various
contexts, starting with pre-set measures to support decision-making is
impossible. 25 This is complicated by substantial
variability in reported healthcare data due to factors such as clinical
inertia, patient expectations, and financial capacity, which differ
greatly among different cultures and countries. It is therefore
suggested to introduce value early in the decision-making process and
work upwards from available data to develop decision options.
Consequently, determining the best value relies on data gathering and
adapting to local factors.
If data on effectiveness, harm, cost, and patient experience is
deficient, then it may be challenging to clearly state the optimal
decision. Hendrikx and colleagues (8) conducted an international
comparative analysis to assess which triple aim measures are being used
to evaluate population management (PM) initiatives. Of the 865 measures
used by 20 PM initiatives, only 11 PM initiatives included all qualities
of care domains. However, each triple aim domain has challenges for
optimum judgment to be made at any of the meta-decision steps. First,
improving the health of populations through healthcare has been measured
by a limited number of studies. A well-known measure is the Center for
Disease Control’s Summary Measures of Population Health,26 which combine information on mortality and
non-fatal health outcomes to represent population health in a single
number. Another example is the quality-adjusted life year (QALY) and the
disability-adjusted life years, which were developed as measurement
units to quantify the burden of disease and injury on human populations.27 Challenges with such measures are that they are as
accurate as the data sources and context from which they were derived.
The variation of healthcare systems, payment structures, and patients’
determinants of health is what makes data deficient.28 Therefore, it may not be suitable for
generalizability, and may not have the statistical accuracy required to
confidently estimate the desired outcomes. Additionally, the available
metrics are never comprehensive enough to assist in all decision areas
in any context’s unique details. Further, a major barrier for QALY is
that it is assigns a weight between 0 (for death) and 1 (100% health)
to each health state and then multiplies that value by how long the
state lasts. 29 This method provides a crude idea for
policy decision-making, but it is difficult to apply at the patient
level.
Regarding cost, it is changing, unsustainable, and not unified for each
encounter, patient, or setting. For example, the financial consequences
after a myocardial infarction in an adult male varies with different
influences on a patient’s life, family, work, and medical resources
utilized. Less attention is paid to eliminating wasteful spending such
as missed prevention, unnecessary service, inefficiently delivered care,
high-priced services, excess admirative costs, and fraud—applicable to
individual and population levels.
An even more challenging area in the value of health is
patient/population values assessment. There are conflicting reports on
the relationship between positive patient experience and patient
outcomes, 30 which is beyond the scope of this review
to investigate. Nevertheless, valuing health is only complete with
patient perspectives, and their judgment of value is best when all
relevant information is available, free of rational flaws like
self-interest. Assessment of such judgment was suggested by using
personal experience over personal preference due to preferences
affecting judgment, or “being guilty of wanting something that could be
detrimental.” 31 A more practical and simpler
approach was then suggested by rationing health care “in terms of how
severely they limit the range of valuable lives individuals can live in
just two dimensions: activity limitations and health-related feelings.”32
The subjective nature of health and well-being ratings by patients may
be biased. For example, the immediate emotional reactions could be
misleading compared to the overall and long-term outcome. Therefore,
deliberative focus groups rather than individual surveys should be used
for such judgments. 32
Reflecting on population value is different from individual-level value.
The population-level value is usually permanent, and the welfare of a
country, context, and population diversity greatly contributes to it.
Contribution to the judgment is the extent that the individual is
involved in decision-making versus the government. For example, some
countries see the introduction of colorectal screening programs by the
government as a necessity, while others do not even if the average
population preference is supportive.
Decisions regarding population needs are dependent on the principles
that governments adopt when they prioritize alternative health programs.
Should governments adopt minimal principles and leave decisions to
individual self-motivation, or should it implement social goals and
expectations for the population? Should the government use coercion to
ensure participation in health programs, or should it use coercion and
information? Answering any of these questions needs
information33. Hausman described how we may reflect on
the policy level of these principles: “the welfarist approach where one
thinks of the government as everybody’s mother with advancing individual
welfare might be requiring intrusions into individual life. Or liberals
who regard the government as a protector, insurer, and arbitrator but
not as an active partner in individual pursuits. The former may promote
passivity in choosing personal priorities in health.”32 These preferences for alternative ethical
principles are called meta-preferences. 33 The best
approach is probably carefully demarcating the line between not harming
and not being harmed in the bargaining in the evaluation step. It is
also important to consider that public value cannot be sensitive to all
relevant details, nor can they be accurately measured. Therefore,
implementing meta-decision while reflecting on patients’ choices, will
build data to inform better future decisions with adaptation to each
country’s norms.
Finally, an essential component of meta-decisions based on the triple
aim is the consideration of possible harm, which is essential when
assessing population health. Harm cannot be reported without being
clearly measured and weighed against effectiveness to assess net
improvement. Potential benefits are not meaningful without the knowledge
and quantification of harmful impacts. Interventions provided by
healthcare services are administered with the best of intentions;
nevertheless, most inevitably cause harm, ranging from minute to
significant. Failure in transparently informing end users of health
interventions’ potential impacts is inconsistent with the ideals in the
triple aim. However, safety assessment is not easily separated from that
of effectiveness.
A challenge of focusing on measures but not the overall value is
evidenced from examples in healthcare where achieving value is
worryingly not always the target but achieving individual measures is.
For example, it has been reported that when improvements as a result of
organizations’ strategies for quality improvement described by the
domains of the triple aim affected revenue in for-profit organizations
with a decrease in patient visits or orders, sustainability of these
strategies were challenged. 34 Similarly, a payment
system initiative used surrogate measures, such as hospital re-admission
for heart failure instead of the target-improved outcome, resulting in
negative patient outcomes due to decrease in needed readmissions,
raising ethical concerns of implementing what is perceived as best
value. 34–36 Thus, meeting the target outcome was
through developing the wrong choice.