Available via license: CC BY 4.0
Content may be subject to copyright.
Healthcare 2019, 7, 116; doi:10.3390/healthcare7040116 www.mdpi.com/journal/healthcare
Article
Developmental Changes in the Philippine Health
System: Accomplishments, Successes and Challenges
Xerxes Seposo
1,2
1
School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki 852-8523, Japan
2
Faculty of Management and Development Studies, University of the Philippines Open University,
Los Banos, Laguna 4031, Philippines
* Correspondence:
seposo.xerxestesoro@nagasaki-u.ac.jp
Received: 19 September 2019; Accepted: 10 October 2019; Published: 14 October 2019
Abstract: The Philippine health system has undergone various changes which addressed the needs
of the time. These changes were reflected in the benchmarks and indicators of performance of the
whole health system. To understand how these changes affected the health system (HS), this study
determined the changes in the Philippine health system in relation to different health domains
(health determinants, financing, and management/development). Two HS periods were identified,
namely, health system period 1 (HS 1) from 1997–2007 and health system period 2 (HS 2) from 2008–
2017. Each HS period was assessed based on three domains. The first two domains were
quantitatively assessed based on an interrupted time-series method, while the third one underwent
a comparative analysis using two Health Systems in Transition reports (2011 and 2018). This study
was able to assess the developmental changes in the Philippine health system. Specifically, the
(health determinant) maternal mortality rate (MMR) significantly decreased by three maternal
deaths per 100,000 live births, the (health financing) tobacco excise tax increased by 13,855 (in
Million PhP) in HS 2, and there was (health management/development) an improvement in access
to health facilities. However, there was an indication of retrogressive progress with some challenges
in HS 1 which remained unaddressed in HS 2. While it seems promising that the health system has
progressed with improvements apparent in both health outcomes (e.g., MMR) and health financing
(e.g., tobacco excise tax), such improvements were overshadowed by the inefficiencies, which were
not addressed by the current health system (HS 2), thus making it more retrogressive than
progressive.
Keywords: Philippines; health systems; health determinant; health financing; health management
1. Introduction
Health systems are structurally complex frameworks of intertwined operations which serve as
a means in achieving pre-defined health goals set by an institution [1]. Health systems exist to
complement other sectoral systems but are primarily dedicated in addressing the need of health care.
Earlier records of existing health care systems were from the 600 BC where Charodes ordered that all
citizens of Athens will have the right to access free medical care [2]. These so-called health care
systems were not entirely “structurally systematic”, instead, these were unorganized and selective
efforts to highlight the importance of (individual) health. Since then, various governments have
engineered to create health systems which would go beyond personal/individual health to a broader
societal breadth. Decades and centuries of development led to major health care system movements
centered in Europe (UK), Asia (China), and North America (United States).
The National Health Service (NHS) of the UK was established in 1948 to render health care
services at the national level coverage [3]. Its primary focus from 1950 to 1970 was on the
modernization of facilities and technologies for improved health care delivery services. On the other
Healthcare 2019, 7, 116 2 of 18
side of the world, in China, since the founding of the People’s Republic in 1949, Meng et al. [4]
emphasized that the “formation and development of the health system, especially the organization
and governance structure, have been closely related to political, economic and administrative
reforms”. The main mover in the changes in China’s health system was mainly due to the country’s
economic pursuits which lasted for more than 30 years [4]. In the 1980s, the implementation of
China’s Open Door Policy has allowed an influx of foreign investments, which then allowed the
country to bolster its health financing schemes, which are linked to the economic developments
brought forth by the policy [5]. Then there is the US health system, which began in the private sector
and took flight in the 1960s as a state-regulated program [6]. The health system founded from the
private sector’s perspective had a domino effect on the rise of the private insurance system. Private
health insurance in the United States had its beginnings around the early 1930s, with the
establishment of non-profit Blue Cross plans for hospital care and soon after Blue Shield plans for
physician care [6,7]. Whereas in the Philippines, the earliest concept of public health was introduced
by the Franciscan Friars in 1577 [8]. Various developments with respect to health have been fostered
by the previous colonizers. The Spaniards instituted the Superior Board of Health and Charity in
1888, whereas the Americans helped in the installation of a more formal health administration
through the (1) Act 1507 of the Philippine Commission in 1901 setting up the Board of Health of the
Philippine Islands, and (2) Act 307 through 309, which provided provincial and municipal boards for
health. [8]. Forty years later, the Philippines independently created its own health system in 1941,
where the Department of Health was separated from the Department of Health and Public Welfare
and was established as a separate entity [9]. The Philippine health system operates in a devolved
manner owing to the local government code of 1991, whereby services were mostly under the
jurisdiction of the local governments, with supplementary services such as major national programs,
which include but are not limited to immunization, tuberculosis, nutrition, etc. Decentralization of
health services became a center piece of the Philippine health system.
Each of these health systems have been tailor-fitted for the specific situation for each country.
The Philippines’, in particular, is unique from other major countries’ health systems as it is one of the
few archipelagic country health systems. The Philippines’ health system provides an opportunity for
examining the pertinent health system challenges geographically diversified countries experience.
Likewise, as health systems change through time, temporal developmental changes though apparent,
have not been elucidated and their assessment remains a challenge. While there have been numerous
legislations which introduced changes in the Philippine health system [10], most of the major changes
happened from or took effect relatively near to 2008. These health system-related changes included
the universal access to cheaper and quality medicines (in 2008), FOURmula One for Health, an
operational framework for health reform agenda which started from 2005 but gained momentum in
2007, and inception of the Philippine Facility Enhancement Program in 2008, among others [10]. With
these major developments, it is thus important to understand the developmental changes in the
Philippine health system, particularly focusing on the past decades’ health systems’ (Health System
1: 1997–2007 versus Health System 2: 2008–2017) accomplishments, successes, and challenges.
Specific assessment of the developmental changes between Health System 1 (HS 1) and Health
System 2 (HS 2) in terms of three domains—namely, (a) health determinant, (b) health financing, and
(c) health development/management—were carried out.
2. Materials and Methods
The health system goals highlighted in the WHO Framework for Health System Performance
Assessment [11]—namely, (a) health, (b) fair financing and financial risk protection, and (c)
responsiveness—were operationalized into the three domains in this study, which were (1) health
determinant, (2) health financing, and (3) health management/development. Murray, et al. [11]
emphasize the monitoring of these three intrinsic goals as a main basis for health system performance.
In brief, the first goal regarding health anchors to the prime motivation of a health system, and that
is to improve the health of the population. This can be represented by a non-exhaustive list of health
determinants, which include the incidence of a disease in the population, life expectancy, and
Healthcare 2019, 7, 116 3 of 18
mortality rates. The second goal focuses on the financial aspect of the health system, both in the
household and society levels. This can be represented by the household level contribution to the
health system or funding streams coming from either internal tax revenues or external donor aids.
Lastly, responsiveness tackles the expectations of the population regarding the health system catering
to the population’s needs. The health system responds to the population’s needs via provision of
services and is closely linked to health administration/management. Addressing previously
encountered health system related issues, through improved health management and administration,
constitute health system responsiveness. In this study, the variables representing the health
determinants and health financing were selected based on whether they satisfy the conceptual
definitions of health system goals of “health” and “fair financing and financial risk protection” as
highlighted in the WHO Framework for Health System Performance Assessment, and if they have
existing annual data.
Each of the domains were analyzed separately with the respective data and methods to be used,
as shown in Figure 3. A mixed method was utilized to analyze each domain, quantitative for health
determinant and health financing, whereas qualitative for health management/development. Data
used in the respective analyses are summarized in Supplementary Materials Table S1.
2.1. Data Description
2.1.1. Health Determinant Domain
Health determinant data, such as life expectancy at birth, maternal mortality rate, infant
mortality rate, HIV incidence, TB incidence, severe wasting, and overweight, were obtained from
online data sources, as shown in Table S1 with the corresponding variable description and source
summarized in Table S2. While there are numerous candidates for health determinants (e.g., cancer
and other chronic diseases), due to the annual data unavailability which could match the time
periods, only the aforementioned health determinant data were analyzed.
2.1.2. Health Financing Domain
Data for health financing were obtained from the World Bank (WB) database. Total health
expenditure in terms of percentage of GDP (%GDP) was extracted from the WB world development
indicators database [12]. While there may be other variables which could represent total health
expenditure, Mcintyre, et al. [13] argue that the “percentage of GDP provides a basis in advocating
an in increase in both government resource mobilization and spending on the full range of human
rights and social determinants of health in situations where governments are not presently providing
maximum available resources”.
2.1.3. Health System Management/Development Domain
Main data source for analyses included the grey literature of the Health Systems in Transition
(HIT) reports (2011 and 2018 versions) of the Philippine Health System. In support to the HIT reports
are the NHA reports, as well as Philippine Institute of Development Studies (PIDS) reports, together
with some relevant legal statutes (republic act and implementing rules and regulations) passed or
took effect during the specific periods.
3. Analyses
3.1. Interrupted Time Series
Data from the health determinant and health financing domains were analyzed using an
interrupted time-series (ITS) technique. This is a quasi-experimental design, which aims to evaluate
the impact of interventions in a longitudinal framework of observations [14,15]. Interrupted time
series has been gaining traction and has been implemented in health care studies which assess the
attribution of the changes an intervention has introduced compared to a no-intervention scenario
Healthcare 2019, 7, 116 4 of 18
[14–16]. It is characterized by the temporal, time-related changes through the difference in the trend
of pre- and post-periods of interest. In this case, the pre-period was the 1997–2007 health system,
while the post-period was 2008–2017. The selection of the division of the periods was based on the
major changes which occurred starting from or relatively near to 2008, as highlighted in Dayrit et al.
[10]. In this study, 2008 was assumed as a pivotal point where major changes after 1991 were
introduced to the health system. The proposition is, if the changes implemented in or relatively near
to 2008 had not happened, would the health system, in terms of the health determinant, health
financing, and health management components, remain the same? In effect, there were two health
system periods, before and after the major changes. We then used this division to assess progress in
the health system.
The ITS was parameterized as in Equation (1) below:
y𝛽
𝛽
𝑇𝛽
𝑝𝑎𝑟 𝛽
𝑝𝑎𝑟: 𝑇 𝜀
(1)
whereby, y is the parameter of interest (either health determinant or health financing domain
variables), T is the time component, whereas par is the binary variable indicating the 1997–2007
(valued to be 0) and 2008–2017 (valued to be 1) health systems; ε is the error term representing the
uncertainty in the model [17]. The cut off period for the ITS was set at 1997/1998–2007 and 2008–
2017/2018. At least five continuous annual data points should be available for the ITS analysis. If the
number of continuous data points for each period was less than five or if the data points were not
continuous, the mean of the data points was utilized instead; as shown in Figure 1 below.
Figure 1. Analysis strategies subject to the availability of the data points for each variable. ITS =
interrupted time-series.
While the minimum number of observations to carry out ITS was 3 [18], in this study, variables
with at least 5 temporally consecutive observations before and after 2008 were analyzed (for ITS). On
the other hand, the mean was taken for variables which were either (a) non-consecutive 5
observations or (b) less than 5 observations.
The variables/ parameters subject to ITS analyses were:
a) Life expectancy;
b) Maternal mortality rate;
c) Infant mortality rate;
d) HIV prevalence;
e) TB prevalence;
f) Total health expenditure;
g) Tobacco excise taxes.
While the following variables were averaged for each health system:
a) Malnutrition (wasting);
b) Overweight;
Healthcare 2019, 7, 116 5 of 18
c) HIV expenditure.
3.2. Comparative Analysis
To facilitate the health system management/development analysis, a comparative analysis was
conducted utilizing the papers of Romualdez et al. [9] and Dayrit et al. [10], which represented health
system period 1 (HS 1) from 1997–2007 and health system period 2 (HS 2) from 2008–2017,
respectively. Each of the reports were summarized into four components, namely, (a) Feature, (b)
Challenges, (c) Reforms, and (d) Laws/Statutes passed/enforced (during the said period). “Feature”
reflects the characteristics inherent to the health system, with ample focus on the strengths.
“Challenge” are the health issues or problems arising under the HS period. “Reforms” are the
innovations introduced in the said HS, and “Laws” are landmark statutes passed/enforced.
After summarizing the report into these four components, only the “Feature” and “Challenge”
components were utilized to represent health system development. In this study, HS development
was defined in terms of being (a) Progressive or (b) Retrogressive using matched variables from the
HS 1 and HS 2. Progressive classification was defined in terms of two aspects: (a) Challenge changed
to Feature; (b) Feature retained as Feature. When a challenge in HS 1 becomes a feature of HS 2, it
means that HS 2 was able to progressively address the challenge. While, if the feature remains the
same between two health systems, it only signifies that HS 2 was able to maintain that current feature.
The HS 2 was retrogressive if a feature in HS 1 became a challenge in HS 2. Similarly, if a challenge
in HS 1 remained to be a challenge in HS 2, it only indicated that there was not much progress in
addressing such a challenge. A graphical summary is shown in Figure 2.
Figure 2. Graphical summary of health system development.
Healthcare 2019, 7, 116 6 of 18
Figure 3. The health system analysis methodological framework.
Healthcare 2019, 7, 116 7 of 18
All quantitative analyses were done using R statistical programming.
4. Results
From the health determinants, only TB prevalence had an apparent distinction among the two
health system periods, with an apparent decrease in the previous one and a subsequent increase in
TB cases in the succeeding health system period. There was no distinct trend for maternal mortality
rate, while there was decreasing and increasing trends for infant mortality rate and HIV prevalence,
respectively. All the data utilized in this study are reflected in Table S1.
Figure 4. Health determinants in various health systems.
Figure 5. Health financing parameters (total health expenditure, HIV expenditure, tobacco excise tax)
in either of the health system periods.
All three health financing parameters increased with time, with an apparent and extensive
increase with the excise tax from tobacco, representing the tobacco excise tax measures.
In Table 1, there was no significant change in life expectancy in either of the HS. While we
observed relatively positive changes in HS 2, such as a statistically significant decrease in Maternal
Mortality Rate (MMR) (a decrease of approximately three maternal deaths per 100,000 live births)
and an increase in excise tax funds, a majority of health determinants such as infant mortality rate,
HIV incidence, and TB incidence increased coupled with a decreased THE.
In Figure 6, we can observe that both malnutrition and overweight population increased by
37.5% and 91.9%, respectively. Both of which signify that non-communicable diseases have been on
the rise in the Philippines, which may indicate some levels of underperformance in HS 2. We can find
a rather interesting trend, in which though HIV expenditure, through both the local funds and foreign
aids, increased significantly in HS 2, we still see an increasing trend of HIV incidence in the same
period—a possible indication of either underperformance in disease prevention or an increase in
detection rate.
Healthcare 2019, 7, 116 9 of 18
Figure 6. Malnutrition: Prevalence of severe wasting, weight for height (% of children under 5); overweight: prevalence of overweight, weight for height (% of
children under 5); HIV expenditure: inflation-adjusted HIV expenditure (in USD millions); mean representation of the selected health determinant (malnutrition
and overweight), and health financing (inflation-adjusted HIV expenditure) variables.
Healthcare 2019, 7, 116 10 of 18
5. Discussion
This study was able to assess the developmental changes in the Philippine health system in the
past decade. While there was progress in different health system components from the HS 1 to HS 2,
the overall health system performance was retrogressive with major challenges still being carried
over to HS 2.
In Table 1, there was a significant decrease in the number maternal deaths in HS 2 than in HS 1.
However, all other health determinants were found to be retrogressive. In the case of health financing,
while THE decreased in HS 2, other health financing variables increased. The tobacco excise tax
significantly increased coupled with the doubling of HIV expenditure in the past decade. As for the
health system management/development, though there were some progressive changes in the health
systems (increase in health financing, increase in health facility access, increase in social health
insurance coverage, and improved waiting time). Taking all developmental changes into account,
overall, the health system is still facing the challenge of retrogressive progress.
Table 1. Interrupted time series results for each variable of interest.
Health Domain Variables Estimate Standard Error p-Value
Health determinants
Life Expectancy −0.007 0.005 -
Maternal Mortality Rate (MMR) −3.25 0.435 ***
Infant Mortality Rate (IMR) 0.260 0.015 ***
HIV Incidence 965 57.5 ***
TB Incidence 13.7 0.086 ***
Health financing Total Health Expenditure (THE) −0.135 0.048 **
Tobacco Excise Taxes 13855 2824 ***
p-value: *** p < 0.001; ** 0.001 < p ≤ 0.05; * 0.05 < p ≤ 0.10; - statistically not significant.
While it seems promising that the health system has progressed with improvements apparent
in both health outcome (i.e., MMR) and health financing aspect (i.e., tobacco excise tax), such
improvements were overshadowed by the overwhelming inefficiencies which were not addressed by
the current health system, thus leading it to be retrogressive rather than progressive.
The Philippine health system has progressed in one way or another, but there are some
developmental aspects which remained unaddressed. Utilizing the whole period data, we can
observe only a few variables which indicate a definite trend. In Figure 4, IMR is gradually decreasing,
whereas HIV incidence has increased rapidly through the years. In health financing, as shown in
Figure 5, all variables increased through the years. However, Figures 4 and 5 may not be enough to
understand how the health system progressed amidst the various changes it had undergone through
time, particularly with the major changes in 2008. The succeeding sub-headings focus on how the
health system changed (comparing HS 1 and HS 2) based on the premises of: (a) health determinants,
(b) health economics/financing, and (c) health system management/development.
5.1. On Health Determinants
Among the health determinants, only MMR significantly progressed in HS 2 compared to HS 1.
The progress in MMR can be attributed to the improvement in the health service facilities as well as
the increase in access to health services highlighted in Table 2 (HS 2: Feature 9). Reforms such as the
HFEP and the DOH deployment program (in HS 2) are essential components in health service
accessibility in the rural areas. All other health determinants increased in HS 2. The IMR increased,
with approximately three infant deaths per 10,000 live births, there were 965 new HIV positive cases,
and 14 new TB cases in HS 2 (shown in Table 1).
Healthcare 2019, 7, 116 11 of 18
Table 2. Summary table of the Features, Challenges, Reforms, and the pertinent Laws/Statutes passed and enforced during the respective health systems.
Health System 1 (1997–2007) Health System 2 (2008–2017)
Features
1. Decreasing Maternal Mortality Rate (MMR)/Infant Mortality
Rate (IMR)
1. Expansion of PhilHealth coverage; however, low financial
protection
2. Private health sector constituted bigger proportion in health
service delivery than public health sector
2. Data gathering was existent; however
,
intensified and
modernized effort is needed
3. Decentralization of health care services (fragmented health
service delivery)
3. Intersectoral approaches to health and in its investment
programming at the national and local levels (unified targeting
for poor, etc.)
4. Emphasis on primary health care 4. Increase in client satisfaction to government health services
5. Rapid increase in nursing schools 5. Concerted efforts to ensure health care data privacy
6. Introduction of health technology assessment (HTA) by
PhilHealth (in identifying priority problems on the use of
medical technologies needing systematic assessment)
6. Care-seeking behavior was dictated by ability to pay
7. Increasing PhilHealth coverage 7. Waiting time improved
8. Waiting time/hospital length of stay decreased 8. Treatment seeking attitude improved among households
9. Migration of health workers, particularly nurses 9. Increased use of rural health units, decrease use of private
clinics
10. Increase in health financing 10. MMR decreased due to the increased facility-based
deliveries and skilled birth attendants
11. Existence of palliative care (cancer patients)
12. Success in closing the gender gap
13. Disaster health management system in place
14. Increase in health financing
Challenges
1. Rising non-communicable diseases (NCDs) 1. Problems with devolved health financing and service
delivery (fragmented strategy)
2. High cost of accessing health service 2. Uneven distribution of health staff across the country
(concentrated in National Capital Region)
3. Low level financial protection 3. Uneven distribution of health facilities across the country
(concentrated in NCR)
4. High out-of-pocket (OOP) payments 4. TB Directly Observed Treatment Short Course (DOTS)
accreditation is low
Healthcare 2019, 7, 116 12 of 18
5. Absence of an integrated curative and preventive network 5. Overregulation of programs (National TB Program and
PhilHealth)
6. Weak health information system/governance 6. High OOP payments
7. Absence/lack of access of private sector data 7. Even though health services were utilized, this did not
directly translate to health status improvement
8. PhilHealth still used paper-based claims management 8. PhilHealth insurance claims stagnated at 33%
9. Lack of health service information (PhilHealth) 9. Hospital bed availability was a difficulty
10. Weak/non-existent structures in engaging community and
patient participation with regard to health decision-making
10. Geographical constraints in service delivery (geographically
isolated and disadvantaged areas)
11. Members’ perceptions are that they have insufficient
information and that the transactional requirements to make
claims were too large
11. Stigma (HIV) and self-stigma (TB) were major barriers to
care
12. Low sponsored program PhilHealth utilization rate 12. Obesogenic environment; life-style related health problems
13. Uneven distribution of PhilHealth accredited providers (35%
of doctors are in NCR) 13. Air pollution and household air pollution
14. Uneven distribution of health facilities and beds across the
country
14. Low childhood immunization due to the fact of
religious/cultural beliefs, as well as lack of coordination among
public sector
15. Lack of geriatric facilities and services 15. Healthcare provision tended to be either underprovided or
overprovided, and costly
16. Adherence to clinical practice guidelines were loose
17. Patient safety data was lacking
18. Health equity issues included the apparent urban–rural
divide
19. Health technology assessment (HTA) was yet to be fully
established
20. Health data acquisition was still restricted (private sector,
public sector, PhilHealth)
21. Fragmented nature of health financing, devolved structure
of service delivery, and mixed public–private health system
posed immense challenges in monitoring health sector
performance
22. Issues with conflict of interest (physician-owned pharmacy)
Healthcare 2019, 7, 116 13 of 18
Reforms
1. Primary health care focus 1. Primary health care expansion due to the intensified HFEP
2. Health Facility Enhancement Program (HFEP) 2. Deployment programs of the DOH and Local Government
Units (LGUs)
3. Health sector reform agenda (HSRA) launched
4. Corporatization of hospitals under HSRA
Health-related laws
accompanying or
independent of the
reforms
1. Republic Act No. 8344 “An Act Prohibiting the Demand of
Deposits or Advance Payments for the Confinement or
Treatment of Patients in Hospitals and Medical Clinics in Certain
Cases”
1. Sin Tax Law of 2014
2. Republic Act No. 7305 “Magna Carta for Public Health
Workers” 2. National Health Insurance Act of 2013
3. Republic Act No. 9184 “Government Procurement Reform
Act” 3. Reproductive Health Law of 2012
4. National Health Insurance Act of 1995 amended to Republic
Act No. 9241 4. Tuberculosis Law of 2016
5. 1988 Generics Act
,
amended to Republic Act No. 9502
“Cheaper and Quality Medicines Act”
NCR = National Capital Region.
Healthcare 2019, 7, 116 14 of 18
The summary table from the health systems in transition reports of Romualdez et al. [9] and
Dayrit et al. [10] were outlined in four aspects, namely, (a) Features, (b) Challenges, (c) Reforms, and
(d) health-related Laws accompanying or independent of the reforms. Changes in the health system
were more apparent in HS 2 with major features of health insurance and health facility reforms.
However, such features were also accompanied with challenges related to OOP and NCD-related
health problems.
While there were health reforms in the past HS, IMR progress may have stagnated due to the
presence of socioeconomic factors in relation to within-country inequalities in child health outcomes
[19]. Kraft et al. [19] noted that child mortality in the Philippines may vary in terms of the rural–urban
divide, by province and wealth status. Implementation of these reforms toward the grassroots level
may have been trickling down at a different pace, thus an inequality in terms of the health outcomes
in the provinces exists. This would have later impacts on the national level progress in IMR. This is
further supported by the “Challenges” observed in HS 2 in Table 2, whereby there was an uneven
distribution of health facilities and personnel across the country.
The increasing TB incidence in the country may be related to either (a) the inefficiency of health
interventions in reaching the risk populations or (b) the detection of cases was enhanced. According
to the GBD Tuberculosis Collaboration Group [20], the little or non-improvement in the TB situation
in the Philippines has been linked to the inadequacy of the diagnostic test and its use in the risk
populations (prison inmates and indigenous populations). This is further worsened by the increasing
prevalence of multidrug-resistant TB and extensively drug-resistant TB in the country [21] as well as
the increasing HIV incidence. The link between TB and HIV has been well established, with HIV
infection increasing the risk by 20 times compared to HIV-seronegative individuals in highly
prevalent countries [22]. From 1990 to 2003, HIV infection is one of the key underlying factors for the
1% increase in annual global TB incidence [23]. On the other hand, the increase in TB incidence may
also be explained by the increase in the detection capacity. Vianzon et al. [24] highlighted that the
increase in TB incidence can be attributed to the initiatives of the National TB Program in improving
access to diagnostic and treatment services. Public–private partnerships have also contributed to the
increase in the detection rate of TB incidence [25].
Also, HIV was observed to have increased in HS 2, similar to TB. This may be viewed as an
inefficiency of the health services in reaching at risk populations, otherwise, it may be an efficiency in
the detection rate. There was a significant increase in HIV incidence, with 965 new cases higher—than
in HS 1. Some attributed the increase of HIV incidence to the drug-resistant subtype of HIV, specifically
the change in the typically observed Western subtype B to a more aggressive HIV subtype, AE [26].
However, from the health management side, Farr and Wilson [27] identified that low rates of condom
use, increased casual sex activities, and the widespread misconception about HIV/AIDS has driven the
disease into becoming an epidemic. The stigma regarding HIV/AIDS has been acknowledged in HS 2
(Table 2: Challenge 11) but has not been fully addressed in HS 1. Though there were problems regarding
HIV/AIDS in HS 1, there was no explicit mention of the stigma problems faced by the key populations.
The lack of acknowledgement about the stigma may be due to the less attention it gained during HS 1,
and when the epidemic exponentially increased after 2008, it gained more attention. On the other hand,
the increasing HIV incidence may be related to the increase in the awareness and access to health
services [28]. While this is plausible, the continuous and rapidly increasing rate of HIV incidence may
prove to be more than just the increase in access/awareness; rather, this may be rooted in a more
complex interaction of the previously highlighted molecular and management factors.
Aside from IMR, TB, and HIV increases, malnutrition and overweight increased by 37.5% and
91.9%, respectively (shown in Figure 6; leftmost and center panels). Nutrition-related problems are
precursors to even bigger problems in the Philippines—non-communicable diseases (NCDs). These
constitute 57% of annual deaths in the country, and had been increasing over the last decades [29].
Adair [30] noted that there was a six-fold increase of overweight and obese women from a 6% in 1983–
1984 to a 35% in 1998–1999. The increase in these nutrition-related problems, particularly overweight,
can be explained by the change in food regimens, whereby there is greater consumption of high caloric
and less essential nutrient food sources and is further worsened by the sedentary life style [30].
Healthcare 2019, 7, 116 15 of 18
5.2. On Health Financing
An efficient health financing would promote overall health and improve health status. While the
tobacco excise tax was statistically higher in HS 2, at 13,855 (in Million PhP) and THE decreased by
0.135. The increase in the tobacco excise tax has been linked to improvements in personal health and
eventually for the health system as a whole in the long run. In Lebanon, Salti et al. [31] observed that
the tobacco tax resulted in an estimated 65,000 averted premature deaths, 300 million USD additional
tax revenues, and 23 million USD out-of-pocket spending on health care averted. Both the financial and
health benefits of increasing tobacco taxes result in health gains and savings in health care, which could
influence later on improvement in the health system. In China, Verguet et al. [32] had similar findings
wherein an increase in tobacco tax resulted in a pro-poor policy instrument bringing health and
financial benefits to households and substantial revenues to society. The HIV expenditure (Figure 6;
rightmost panel) paired with the findings about increased incidence can be interpreted in two ways: (a)
inefficient resource use and (b) increase in detection. Though it increased by 82.3% in HS 2, new HIV
cases surged in HS 2, which is quite counterintuitive. This may be linked to inefficient resource use,
particularly in using the current resources to decrease the incidence. On the other hand, it could mean
that resources may have been used to increase detection of new cases. If it is the first one, then this
seemingly increasing resource allocation to the HIV agenda can be an opportunity to look back and
reevaluate resource efficiency subject to the targets and goals set. There were various factors linked to
the worsening HIV epidemic, highlighted previously, and these factors can be candidate starting points,
which can be utilized in re-strategizing how to maximize the use of resources in achieving the desirable
output, outcome, and impact of interest. While if it is the other way around, there is a need to assess the
scale of the operations in what could be the most efficient way to improve current practice.
5.3. On Health Management/Development
The aim of assessing the health management/development was not to judge which health system
is better, rather, if the health system, divided into two periods, was able to progress amidst the
challenges and reforms it has undergone. Both HS 1 and HS 2 had their unique features setting them
apart (as summarized in Table 2). The HS 1 was the precursor of primary health care and social
protection, and these features were further carried over to HS 2, with improvements in health
facilities and health care benefits. In this study, progress was defined in terms of (a) when a feature
in HS 1 was still existing in HS 2 (meaning it was sustained) and (b) when a challenge in HS 1 became
a feature in HS 2 (means the problem was resolved and became an asset in HS 2). On the other hand,
retrogression was defined as (a) when challenges in HS 1 were still existing in HS 2 (unresolved
previous problems) and (b) when features in HS 1 became a challenge in HS 2 (an asset becoming a
problem). Although there were numerous challenges and features (in Table 2), only those matched
ones were included in the assessment in Table 3. Progressive aspects of the health system were
apparent with the increased health financing, social protection, improved waiting time, and
improved access to services and data gathering. However, a big portion of these developments were
retrogressive, such as high OOP, uneven distribution of health facilities and personnel, and
restrictions to health data access, among others. The retrogressive nature of development of the
Philippine health system is related to the unresolved previous problems, partly due to the increasing
challenges and limited resources to resolve existing ones. Even though investments in health are
increasing, so too are the problems, thus these resources are spread thinly creating relatively small
impacts on massive problems, resulting in these problems being unresolved. Constant evaluation of
these programs and projects is needed to determine the evolving problem, and how to provide a way
which adapts with the evolving problem. This is where information and data play a big role. This
challenge has been acknowledged in both HS 1 and HS 2. The private health sector constitutes a large
proportion of the health system and yet there is no access to the information they hold. Similarly, the
public health sector has a weak data gathering, updating, and validation system, which makes health
policy stationary and creates non-adapting solutions to evolving problems. If we have access to this
information, we would have a clearer picture of where we are now, and how to move forward in the
health system.
Healthcare 2019, 7, 116 17 of 18
Table 3. Highlighting the health system development from HS 1 to HS 2 using matched variables.
Health System
Development Health System 1 (1997–2007) Health System 2 (2008–2017)
Progressive
Increase in Health Financing Increase in Health Financing
Increasing PhilHealth coverage Expansion of PhilHealth coverage; however, low financial protection
Waiting time/hospital length of stay decreased Waiting time improved
PhilHealth still used paper-based claims management Data gathering was existent; however, intensified and modernized effort was needed
Absence of an integrated curative and preventive network Increased use of rural health units, decreased use of private clinics
Low sponsored program PhilHealth utilization rate Treatment seeking attitude improved among households
Retrogressive
Introduction of health technology assessment (HTA) by PhilHealth
(in identifying priority problems on the use of medical technologies
needing systematic assessment)
Health technology assessment (HTA) was yet to be fully established
Decentralization of health care services (fragmented health service
delivery)
Fragmented nature of health financing, devolved structure of service delivery, and mixed public–
private health system posed immense challenges in monitoring health sector performance
Rising non-communicable diseases (NCDs) Obesogenic environment; life-style-related health problems
High cost of accessing health service Healthcare provision tended to be either underprovided or overprovided, and costly
Low level financial protection PhilHealth insurance claims stagnated at 33%
High out-of-pocket (OOP) payments High OOP payments
Weak health information system/governance Adherence to clinical practice guidelines were loose
Patient safety data was lacking
Absence/lack of access of private sector data Health data acquisition was still restricted (private sector, public sector, PhilHealth)
Uneven distribution of PhilHealth accredited providers (35% of
doctors are in NCR) Uneven distribution of health staff across the country (concentrated in NCR)
Uneven distribution of health facilities and beds across the country Uneven distribution of health facility across the country (concentrated in NCR)
Challenges in regard to hospital bed availability
Green = Feature; Orange = Challenge; Progressive classification: (a) Challenge changed to Feature; (b) Feature retained as Feature; Retrogressive classification: (a)
Feature changed to Challenge; (b) Challenge retained as Challenge. NCR = National Capital Region.
Healthcare 2019, 7, 116 19 of 18
Progressive classification was defined in terms of two aspects: (a) Challenge changed to Feature;
(b) Feature retained as Feature. When a challenge in HS 1 becomes a feature of HS 2, it meant that HS
2 was able to progressively address the challenge. While, if the feature remained the same among the
two health systems, it only signified that HS 2 was able to maintain that current feature. The HS 2
was retrogressive if a feature in HS 1 became a challenge in HS 2. Similarly, if a challenge in HS 1
remained a challenge in HS 2, it only indicated that there was not much progress in addressing such
a challenge. While there were important aspects of progress in the health system, it was still
overwhelmed with challenges which were yet to be addressed. Health financing seemed to have
improved; however, health insurance claims were stagnating and was worsened with the increase in
or reliance on OOPs for health services.
6. Limitations
The study had a few limitations, namely, (a) availability of current data, (b) the number of
observations for ITS, and (c) qualitative analysis.
There are various variables which can represent the health determinants, health financing, and
health management/development domains; however, due to the data limitations, variables which
were readily available or could be extracted were only used. Other health determinants data such as
cancer rates and chronic health outcomes, as well as health financing data (e.g., catastrophic health
spending), could also provide insights in regard to the performance of the health system. Future
studies are encouraged to include these variables if available.
For health management/development, there may be other features and challenges not fully
captured in the summary; however, if such information becomes available in the near future, there is
a need to run a re-analysis. While the current number of observations before and after 2008 were
beyond the minimum number of observations required to do an ITS [18], extending the number of
observations may provide a more robust insight on the estimates. In this study, the quantitative
analyses relied on the available data sources as well as grey literature in assessing the progress of the
Philippine Health System. While the results of the quantitative techniques complemented the
observations from the health transition reports, more detailed insights could have been gained from
in-depth qualitative analyses through focus group discussions (FGDs) and key informant interviews
(KIIs).Focus group discussions and KIIs would be able to provide a grassroots perspective of how the
progress affected the beneficiaries, the people, as well as various insights on how progress was
optimized and the challenges were resolved from a health manager’s perspective. Aside from FGDs
and KIIs, the assessment of quality of life as well as patient satisfaction would provide additional
qualitative evidence in support of the performance of the health system [33]. Further studies
including qualitative analyses are needed to gain more insight into how health system progress is
appraised from a community level perspective.
7. Conclusions
This study assessed the developmental changes in the Philippine health system, particularly
focusing on the past decades’ accomplishments, successes, and challenges. The health system has
progressed, particularly in the improvement of health outcomes (i.e., MMR), increased health
financing, and increase in access to health services. However, there are indications that the overall
health system is retrogressive. There are a multitude of factors which led to a retrogressive status.
Similarly, there are different ways to address these issues, one of which is to constantly monitor and
evaluate under the premise that data should be shared across stakeholders sanctioned by
equivalently strict and secure data sharing/privacy agreements.
Supplementary Materials: The following are available online at www.mdpi.com/xxx/s1, Table S1: Master
dataset of the annual health system performance-related variables, Table S2: Variable description and related
source.
Author Contributions: X.S. conceptualized the topic, collected the data, performed the analysis and wrote the
manuscript.
Healthcare 2019, 7, 116 20 of 18
Funding: This research received no external funding.
Conflicts of Interest: The author declares no conflict of interest.
References
1. Berman, P.; Bitran, R. Health Systems Analysis for Better Health System Strengthening; World Bank:
Washington, DC, USA, 2011.
2. Attali, J. L’ordre Cannibale. Vie et Mort de la Medicine; Grasset: Paris, France, 1979.
3. Cylus, J.; Richardson, E.; Findley, L.; Longley, M.; O’Neill, C.; Steel, D. United Kingdom: Health System
Review. Health Syst Transit. 2015, 17, 1–126.
4. People’s Republic of China Health System Review. Available online:
http://apps.searo.who.int/PDS_DOCS/B5413.pdf (accessed on 14 October 2019).
5. Bohnet, A.; Hong, Z.; Müller, F. China’s open-door policy and its significance for transformation of the
economic system. Intereconomics 1993, 28, 191–197.
6. Rice, T.; Rosenau, P.; Unruh, L.Y.; Barnes, A.J.; Saltman, R.B.; van Ginneken, E. United States of America:
health system review. Health Syst. Transit. 2013, 15, 1–431.
7. Leeds, L.S. Private Health Insurance in the United States: An. Overview; Social Security Administration:
Woodlawn, MD, USA, 1965.
8. Ford, M.J.; Cruz, A.H. The Rural Health Unit in the Philippines. Public Health Rep. 1896-1970 1957, 72, 687–
695.
9. Romualdez, A.G.; dela Rosa, J.F.E.; Flavier, J.D.; Quimbo, S.L.A.; Hartigan-Go, K.Y.; Lagrada, L.P.; David,
L.C. The Philippines Health System Review; World Health Organization Regional Office for the Western
Pacific: Manila, Philippines, 2011.
10. Dayrit, M.M.; Lagrada, L.P.; Picazo, O.F.; Pons, M.C.; Villaverde, M.C. The Philippines Health System Review;
World Health Organization Regional Office for South-East Asia: Manila, Philippines, 2018.
11. Murray, C.J.L.; Frenk, J.; World Health Organization. Global Programme on Evidence for Health, P; A WHO
framework for health system performance assessment; Christopher, J.L., Murray, J.F., Eds.; World Health
Organization: Geneva, Switzerland, 1999.
12. World Bank. World Development Indicators. Availabe online: http://datatopics.worldbank.org/world-
development-indicators/ (accessed on 15 August 2019).
13. Mcintyre, D.; Meheus, F.; Rottingen, J.A. What level of domestic government health expenditure should
we aspire to for universal health coverage? Health Econ. Policy L 2017, 12, 125–137.
14. Penfold, R.B.; Zhang, F. Use of interrupted time series analysis in evaluating health care quality
improvements. Acad Pediatr. 2013, 13, S38–S44.
15. Kontopantelis, E.; Doran, T.; Springate, D.A.; Buchan, I.; Reeves, D. Regression based quasi-experimental
approach when randomisation is not an option: interrupted time series analysis. BMJ 2015, 350, h2750.
16. Bernal, J.L.; Cummins, S.; Gasparrini, A. Interrupted time series regression for the evaluation of public
health interventions: a tutorial. Int. J. Epidemiol. 2017, 46, 348–355.
17. NBER. What’s New in Econometrics?—Difference-in-Differences Estimation. Availabe online:
http://www.nber.org/WNE/lect_10_diffindiffs.pdf (accessed on 18 October 2018).
18. Hawley, S.; Ali, M.S.; Berencsi, K.; Judge, A.; Prieto-Alhambra, D. Sample size and power considerations
for ordinary least squares interrupted time series analysis: a simulation study. Clin. Epidemiol. 2019, 11, 197–
205.
19. Kraft, A.D.; Nguyen, K.H.; Jimenez-Soto, E.; Hodge, A. Stagnant neonatal mortality and persistent health
inequality in middle-income countries: a case study of the Philippines. PLoS ONE 2013, 8, e53696.
20. GBD Tuberculosis Collaboration Group. Global, regional, and national burden of tuberculosis, 1990–2016:
results from the Global Burden of Diseases, Injuries, and Risk Factors 2016 Study. Lancet Infect. Dis. 2018,
18, 1329–1349.
21. Sharma, A.; Hill, A.; Kurbatova, E.; van der Walt, M.; Kvasnovsky, C.; Tupasi, T.E.; Caoili, J.C.; Gler, M.T.;
Volchenkov, G.V.; Kazennyy, B.Y.; et al. Estimating the future burden of multidrug-resistant and
extensively drug-resistant tuberculosis in India, the Philippines, Russia, and South Africa: a mathematical
modelling study. Lancet Infect. Dis. 2017, 17, 707–715.
22. Martinson, N.A.; Hoffmann, C.J.; Chaisson, R.E. Epidemiology of tuberculosis and HIV: Recent advances
in understanding and responses. Proc. Am. Thorac. Soc. 2011, 8, 288–293.
23. Lawn, S.D.; Churchyard, G. Epidemiology of HIV-associated tuberculosis. Curr. Opin. HIV AIDS 2009, 4, 325–
Healthcare 2019, 7, 116 21 of 18
333.
24. Vianzon, R.; Garfin, A.M.; Lagos, A.; Belen, R. The tuberculosis profile of the Philippines, 2003-2011:
advancing DOTS and beyond. West. Pac. Surveill. Response J. 2013, 4, 11–16.
25. Zhang, T.; Guo, L.; Zhang, S.; Liu, W.; Chen, G.; Hui, M.; He, G.; van der Werf, M.J.; van den Hof, S.
Improving detection and notification of tuberculosis cases in students in Shaanxi province, China: An
intervention study. BMC Public Health 2011, 11, 147.
26. Salvana, E.M.T.; Schwem, B.E.; Ching, P.R.; Frost, S.D.W.; Ganchua, S.K.C.; Itable, J.R. The changing
molecular epidemiology of HIV in the Philippines. Int J. Infect. Dis. 2017, 61, 44–50.
27. Farr, A.C.; Wilson, D.P. An hiv epidemic is ready to emerge in the philippines. J. Int. AIDS Soc. 2010, 13, 16.
28. Gokengin, D.; Doroudi, F.; Tohme, J.; Collins, B.; Madani, N. HIV/AIDS: trends in the Middle East and
North Africa region. Int. J. Infect. Dis. 2016, 44, 66–73.
29. WPRO. Noncommunicable Diseases are Top Killers Diseases in the Philippines. Availabe online:
http://www.wpro.who.int/philippines/areas/noncommunicable_diseases/continuation_ncd_area_page/en/
(accessed on 10 January 2019).
30. Adair, L.S. Dra matic ris e in overwei ght and obesity in adult filipino women and r isk of hyper tension. Obes.
Res. 2004, 12, 1335–1341.
31. Salti, N.; Brouwer, E.; Verguet, S. The health, financial and distributional consequences of increases in the
tobacco excise tax among smokers in Lebanon. Soc. Sci. Med. 2016, 170, 161–169.
32. Verguet, S.; Gauvreau, C.L.; Mishra, S.; MacLennan, M.; Murphy, S.M.; Brouwer, E.D.; Nugent, R.A.; Zhao,
K.; Jha, P.; Jamison, D.T. The consequences of tobacco tax on household health and finances in rich and
poor smokers in China: an extended cost-effectiveness analysis. Lancet Glob. Health 2015, 3, E206–E216.
33. Tremolada, M.; Schiavo, S.; Varotto, S.; Basso, G.; Pillon, M. Patient Satisfaction in Italian Childhood Cancer
Survivors: Human Aspects of Treatment as a Key Factor in Patients’ Quality of Life. Health Soc. Work 2015,
40, e148–e155.
© 2019 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
