10. WHOは何をしているのか
• Production of global public goods
• 国際基準・ガイドラインの作成
• Management of externalities across countries
• 国際保健規則の順守しているか査察・監視
• Mobilization of global solidarity
• 技術⽀援・資⾦供与
• Stewardship
• 決議・条約の制定
11
N Engl J Med 2013; 368:936-942. DOI: 10.1056/NEJMra1109339
2019/12/27
14. UHCキューブ
15
funds.Waitingtimesforservicesmayvarygreatlyfromonecountrytoano
some expensive services might not be provided and citizens may contri
a different proportion of the cos
the form of direct payments.
Nevertheless, everyone
these countries has access to
of services (prevention, promo
treatment and rehabilitation)
nearly everyone is protected f
severe financial risks thank
prepayment and pooling of fu
Thefundamentalsarethesame
if the specifics differ, shaped by
expectations of the population
the health providers, the poli
environment and the availab
of funds.
Countries will travel diffe
paths towards universal cover
depending on where and how
start, and make different cho
along the three axes outline
Fig. 1.2. For example, in sett
Fig.1.2. Three dimensions to consider when moving towards universal
coverage
Direct costs:
proportion
of the costs
covered
Population: who is covered?
Include
other
services
Extend to
non-covered
Reduce
cost sharing
and fees
Current pooled funds
Services:
which services
are covered?
Source: the World health report:
health systems financing: the path
to universal coverage (p. 12), by
World Health Organization, 2010,
Geneva: WHO Press.
3つのcoverageで評価
• Population coverage
• Service coverage
• Financial coverage
2019/12/27
15. 国⺠皆保険は必ずしもUHCではない
16
funds.Waitingtimesforservicesmayvarygreatlyfromonecountrytoano
some expensive services might not be provided and citizens may contri
a different proportion of the cos
the form of direct payments.
Nevertheless, everyone
these countries has access to a
of services (prevention, promot
treatment and rehabilitation)
nearly everyone is protected f
severe financial risks thank
prepayment and pooling of fu
Thefundamentalsarethesamee
if the specifics differ, shaped by
expectations of the population
the health providers, the poli
environment and the availab
of funds.
Countries will travel diffe
paths towards universal cover
depending on where and how
start, and make different cho
along the three axes outlined
Fig. 1.2. For example, in sett
Fig.1.2. Three dimensions to consider when moving towards universal
coverage
Direct costs:
proportion
of the costs
covered
Population: who is covered?
Include
other
services
Extend to
non-covered
Reduce
cost sharing
and fees
Current pooled funds
Services:
which services
are covered?
1958年の国保法改正により
⼈⼝カバー率がほぼ100%なった
1961年の国保の⾃⼰負担割合は
5割。⾼額療養費制度は未導⼊
2019/12/27
16. 保健システム強化を怠ると既存リソースの奪い合
いになる
17
for this improved reporting over time, comparison of services across years are adjusted for the population providing data by district and year.
The HMIS annual district forms available for 2005/2006 and 2006/2007 were not consistently available with 23 and 24 forms available, respectively, of a pos-
sible 56 original districts. Due to the low proportion of data available from these first 2 years of the study for this HMIS 128 form they were not included in this
table, regression modelling or graphs.
a
Linear regression slope of change in outcome rate per year.
b
Reports obtained as a percent of the total possible.
Table 5 IRRs and 95% CIs of the medium and high tertiles of patients on ART relative to the lowest ART tertile on district non-HIV care out-
puts, from district monthly routine HMIS data reports (2005/2006–2010/2011, 6 years)
Non-HIV care
output indicator
Medium investment in relation to low
investment IRR (95% CI, P-value)
High investment in relation to low
investment IRR (95% CI, P-value)
Number of
monthly
reports
with data
Denominator variable
for rates (model
exposure)
Outpatient visits for
children aged 4 and
younger
0.93 (0.90–0.96, <0.001) 0.89 (0.85–0.94, <0.001) 3419 Population
In-facility deliveries 0.96 (0.93–0.99, 0.020) 0.95 (0.91–1.00, 0.033) 3425 Population
DPT3 for children
younger than 1 year
of age
1.00 (0.96–1.03, 0.778) 0.94 (0.90–0.99, 0.017) 3419 Deliveries
TB tests 0.88 (0.83–0.94, <0.001) 0.78 (0.72–0.85, <0.001) 3369 Population
Malaria blood smears
conducted
0.99 (0.94–1.03, 0.519) 1.01 (0.94–1.07, 0.835) 3430 Population
Maternal deaths 0.93 (0.81–1.06, 0.292) 0.87 (0.73–1.04, 0.134) 3357 Deliveries
Source of data and notes: Uganda HMIS monthly data from Districts (based on the UgHMIS123 form), as collected by the research teams from each of
Uganda’s 112 districts. Control variables in the models include sanitation at the district level (% of population with pit latrines), % of eligible children enrolled in
elementary schools at the district level and HIV prevalence at the 10-region level. Additional control variables include year and month of source data, to control
for seasonal variation and a variety of annual factors. The unit of analysis is ‘District Month’. IRRs can be interpreted as the relative rate of the outcome measure
in relation to the lowest investment PEPFAR tertile when all other variables are held constant (i.e. considering the number of people on PEPFAR-supported ART
Health Policy and Planning, 31, 2016, 897–909. doi: 10.1093/heapol/czw009
2019/12/27
20. UHCサービス・カバレッジ・インデックス(SCI)
21
(2), and the Sustainable Development Goal aim
of achieving UHC for all by 2030 (3).
Monitoring UHC progress in the SDG era:
the service coverage index
The UHC SCI, which is the official measure
for SDG indicator 3.8.1 (4), was developed
14 indicators are not meant as a complete or
exhaustive list of health services and inter-
ventions covered in a given country’s UHC
programmes, nor do they measure the health
impact of these services. But they do pro-
vide a strong signal on the coverage of health
services needed by most populations across
sociodemographic settings.
Individual indicators have been proposed
as alternative intervention measures for the
UHC SCI (1,6), such as coverage of measles-
containing vaccine and second doses diph-
theria, tetanus, pertussis, rather than three
doses (DTP3). But in testing the effects of
substituting for alternatives five UHC SCI indi-
cators (Annex A1.1), the overarching results
do not vary from the approved 14 indicator
methodology (8).
Calculated for 183 Member States (Annex
A1.1), the UHC SCI is presented on a scale
of 0 to 100, since service coverage is typi-
cally measured on a scale of 0 to 100%, with
higher scores indicating better performance.
So, nearing or reaching 100 on the index can
be interpreted as meeting the SDG target.
Geometric means are used rather than arith-
metic means as they favour equal coverage
across services as opposed to higher cover-
age for some services at the expense of oth-
ers. Because the index is based on geometric
means and involves scaling non-intervention
coverage tracer indicators, reported values
do not directly translate to the percentage of
the population covered by UHC services (see
Annex A1.2 for more detail). But they can be
viewed as performance scores.
FIGURE 1.1 The UHC service coverage index (SCI): summary of
tracer indicators and computation
Reproductive, maternal, newborn and child health
1. Family planning (FP)
2. Antenatal care, 4+ visits (ANC)
3. Child immunization (DTP3)
4. Careseeking for suspected pneumonia
(Pneumonia)
Infectious disease control
1. TB effective treatment (TB)
2. HIV treatment (ART)
3. Insecticide-treated nets (ITN)
4. At least basic sanitation (WASH)
Noncommunicable diseases
1. Normal blood pressure (BP)
2. Mean fasting plasma glucose (FPG)
3. Tobacco nonsmoking (Tobacco)
Service capacity and access
1. Hospital bed density (Hospital)
2. Health worker density (HWD)
3. IHR core capacity index (IHR)
RMNCH = (FP · ANC · DTP3 · Pneumonia)1⁄4
Infectious = (ART · TB · WASH · ITN)1⁄4
if high malaria risk
Infectious = (ART · TB · WASH)1⁄3
if low malaria risk
NCD = (BP · FPG · Tobacco)1⁄3
Capacity = (Hospital · HWD · IHR)1⁄3
UHC service coverage index = (RMNCH · Infectious · NCD · Capacity)1⁄4
Note: For more detail on UHC SCI calculation methods, see Annex A1.2.
Source: Primary Health Care on the Road to Universal Health Coverage: 2019 Global Monitoring Report. WHO
• 16つあったUHC追跡指標のうち、データが
⼊⼿可能な14つを幾何平均したもの
• NCDに関しては、追跡指標の妥当性に検討
の余地あり
2019/12/27
21. ⾼所得国になるほどUHC SCIは⾼い
22
and the European (77) and Western Pacific
Regions (77). Even so, regional averages can
conceal inequalities, with some regions with
relatively high overall scores still having
some countries with low values (Figure 1.4).
All World Bank income groups also demon-
strated improvements on the UHC SCI since
2000 (Figure 1.3b). High-income countries had
Trends across UHC service coverage
domains
Globally, the infectious disease component
of the UHC SCI improved the fastest, with a
pronounced acceleration around 2005 (Fig-
ure 1.5). Among the indicators in the UHC
SCI infectious disease component, faster
FIGURE 1.4 Country-level UHC SCI values in 2017 varied – often substantially – within WHO regions
UHC SCI, 2017
70–7980 or more 60–69 50–59 40–49 Less than 40 Data not available Not applicable
Note: This map has been produced by the World Health Organization (WHO). The boundaries, colours or other designations or denominations used in this map
and the publication do not imply, on the part of the World Bank or WHO, any opinion or judgement on the legal status of any country, territory, city or area or of its
authorities, or any endorsement or acceptance of such boundaries or frontiers.
2019/12/27
22. UHC SCIは世界全体で改善傾向あり
23
14 • Monitoring population coverage with health services: SDG 3.8.1
FIGURE 1.3 The UHC SCI improved from 2000 to 2017 in all WHO regions and World Bank income groups
Value of UHC SCI Value of UHC SCI
0
20
40
60
80
100
20172015201020052000
Region of the AmericasEuropean Region
Western Pacific Region
World
Eastern Mediterranean Region
South-East Asia Region
African Region
0
20
40
60
80
100
20172015201020052000
World
Low income
Lower middle income
Upper middle income
High income
2019/12/27
24. 破滅的なOOPSは特に中所得国でみられる
25
Global Monitoring Report on Financial Protection in Health 2019 • 13
FIGURE 2 There are large variations within regions in the percentage of people with catastrophic health
spending, as tracked by Sustainable Development Goal indicator 3.8.2
Percentage of the population with out-of-pocket health spending exceeding 10% or 25% of the household budget, most recent year available
10% threshold 25% threshold
3.28–6.690.20–3.28 6.69–12.59 12.59–54.20
Data not available Not applicable
0.44–1.090.01–0.44 1.09–2.53 2.53–22.16
Data not available Not applicable
Note: These maps have been produced by the World Health Organization (WHO). The boundaries, colours or other designations or denominations used in this
map and the publication do not imply, on the part of WHO or the World Bank, any opinion or judgement on the legal status of any country, territory, city or area or
of its authorities, or any endorsement or acceptance of such boundaries or frontiers.
Source: Global database on financial protection assembled by WHO and the World Bank, 2019 update.
Source: Global Monitoring Report on Financial Protection in Health 2019. WHO & WBG2019/12/27
25. 世界全体として保健医療サービスの利⽤による破
滅的なOOPSを被っている家計は増えてる
26
hold budget increased from 1.7% to 2.9% (Fig-
ure 2.3).
All WHO regions saw increases in the num-
ber of people and percentage of population
with catastrophic health spending between
2000 and 2015 (Figure 2.4). The highest
and the Western Pacific Region.6
In the South-East Asia Region and the Euro-
pean Region, the rate of increase between
2010 and 2015 in the number of people and
percentage of the population with catastrophic
health spending as tracked by SDG indicator
3.8.2 was worse than that between 2005 and
2010.7
In the African Region and the Western
Pacific Region, there was a marginal decline
in the percentage of the population with cat-
astrophic health spending between 2010 and
2015 but not in the number of people.8
The
Region of the Americas was the only region
where the number of people and percentage
of the population with catastrophic health
spending at both thresholds fell between 2010
and 2015 (Annex 2.1).9
High-income countries had the lowest
number and percentage of people with cat-
astrophic health spending exceeding both
thresholds of the SDG indicator 3.8.2 in 2000.
But between 2000 and 2015, they experienced
a steady increase in the number of people and
percentage of the population spending more
than 10% or 25% of the household budget on
health out of pocket10
(Figure 2.5).
Low-income countries had the highest
number and percentage of people with out-of-
pocket health spending exceeding the 10% and
25% thresholds in 2000,11
but after an initial
FIGURE 2.3 Globally, financial protection against
out-of-pocket health spending decreased
continuously between 2000 and 2015, as tracked by
Sustainable Development Goal indicator 3.8.2
Percentage of the population with out-of-pocket health spending
exceeding 10% or 25% of the household budget
10% threshold 25% threshold
0
5
10
15
2015201020052000
Source: Global monitoring report on financial protection in health 2019 (4).
• 所得が増えれば保健医療サービスへの需要
が⾼まり、主に⺠間による⾼度・⾼額な医
療サービスの提供も増える
• しかし国の保健財政制度の整備が追いつか
ないことが多い
Source: Global Monitoring Report on Financial Protection in Health 2019. WHO & WBG2019/12/27
26. もっと勉強したい⽅へ
27
Tracking universal health coverage:
2017 Global Monitoring Report
Primary Health Care on the Road
to Universal Health Coverage
Global Monitoring Report on
Financial Protection in Heath 2019
2019/12/27
29. グローバルヘルス業界においてエントリー・レベ
ルの求⼈は1割未満しかない
30
RESEARCH ARTICLE Open Access
Mapping the global health employment
market: an analysis of global health jobs
Jessica M. Keralis1*
, Brianne L. Riggin-Pathak2
, Theresa Majeski3
, Bogdan A. Pathak2
, Janine Foggia3
,
Kathleen M. Cullinen4
, Abbhirami Rajagopal3
and Heidi S. West5
Abstract
Background: The number of university global health training programs has grown in recent years. However, there
is little research on the needs of the global health profession. We therefore set out to characterize the global health
employment market by analyzing global health job vacancies.
Keralis et al. BMC Public Health (2018) 18:293
https://doi.org/10.1186/s12889-018-5195-1
2019/12/27