Provincial Reproductive Health

PROVINCIAL REPRODUCTIVEHEALTH & MPS PROFILE

OF INDONESIA(2001-2006)

Departemen Kesehatan RI World Health Organization

World Health Organization 2008

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Printed in IndonesiaWorld Health OrganizationJakarta Country OfficeBina Mulia 1 Bld, 9th FloorJl. H. R. Rasuna Said Kav. 10, KuninganPh. : (62-21) 520-43-49Fax. : (62-21) 520-11-64

Provincial Reproductive Health & MPS Profile of Indonesia

Technical Contributors:

Dr. Lukman Hendro Laksmono,Dr. Lukas C. Hermawan,

Dr. Laura GuarentiMrs. Riznawaty Imma Batubara

Consultants:Ms. Gretchen Antelman, MPH Sc.DDr. Fransisca Romana Habsari E.P.

Maps:Mr. Adnan Saleh

Data Collectors:Mrs. Rizki Primaswastya

Ms. Hepa Susami

Photos Credit:

Ms. Giulia BesanaMr. Totok Waluyatmoko

Administrative Support:Mrs. Siti SubiantariMs. Nurhayati NopyMr. Adhi Kawidastra

Design & Layout:PT. Cakra Satria Bhakti

West Kalimantan.................................................................................... 131

Central Kalimantan ................................................................................ 137

South Kalimantan .................................................................................. 143

East Kalimantan .................................................................................... 149

North Sulawesi ...................................................................................... 155

Central Sulawesi .................................................................................... 161

South Sulawesi ...................................................................................... 167

Southeast Sulawesi ............................................................................... 173

Gorontalo ............................................................................................... 179

West Sulawesi ....................................................................................... 185

NTB ...................................................................................................... 191

NTT ....................................................................................................... 197

Maluku ................................................................................................... 203

North Maluku ........................................................................................ 209

West Papua ........................................................................................... 215

Papua .................................................................................................... 221

Annexes

Maps

1. Population density by Province

2. First Antenatal Care (ANC) Visit by Province

3. Delivery by Skilled Birth Attendants (SBA) by Province

4. Postpartum and Neonatal Visit by Province

5. Proportion of Villages with Community Midwives by Province

Foreword by Director of Maternal Health .............................................. 5

Remarks by Director General of Community Health Ministry of Health Republic of Indonesia ...................................................................... 5

Introduction ........................................................................................... 7

Nanggroe Aceh Darussalam ................................................................ 29

North Sumatra ....................................................................................... 35

West Sumatra ........................................................................................ 41

Riau ..................................................................................................... 47

Jambi ..................................................................................................... 53

South Sumatra....................................................................................... 59

Bengkulu ................................................................................................ 65

Lampung ................................................................................................ 71

Bangka Belitung .................................................................................... 77

Kepri Islands .......................................................................................... 83

DKI Jakarta ............................................................................................ 89

West Java .............................................................................................. 95

Central Java .......................................................................................... 101

Yogyakarta ............................................................................................. 107

East Java ............................................................................................... 113

Banten ................................................................................................... 119

Bali ...................................................................................................... 125

CONTENTS

3Provincial Reproductive Health & MPS Profi le of Indonesia

6. Proportion of Districts with at Least 4 Puskesmas Trained in Basic Emergency Obstetric and Neonatal Care (BEONC) by Province

7. Proportion of Districts with Met-Need for Basic Emergency Obstetric and Neonatal Care (BEONC) by Population by Province (1 BEONC per 125,000 Population)

8. Proportion of Districts with at Least 1 Comprehensive Emergency Obstetric and Neonatal Care (CEONC) Hospital by Province

9. Proportion of Districts with Met-Need for Comprehensive Emergency Obstetric and Neonatal Care (CEONC) by Population by Province (1 CEONC per 500,000 Population)

10. Proportion of Treated Obstetric Complications by Provice

11. Proportion of Treated Neonatal Complications by Provice

12. Maternal Mortality Ratio by Province

13. Neonatal Mortality Rate by Province

14. Contraceptive Prevalence Rate by Province

Remarksby

Director General of Community HealthMinistry of Health

Republic of Indonesia

The International Consensus of the International Conference on Population and Development (ICPD) in Cairo 1994 had a new paradigm of reproductive health, which altered the previous orientation from placing human as an object in population control to be a subject. Indonesia, being one of the countries that have agreed upon the new paradigm, has undertaken a number of initiatives to ensure the optimal implementation of reproductive health programmes.

The right and reproductive health aspects are very broad relating to the overall human life cycles starting from the periods of pregnancy, birth, childhood, adolescent, adult, up to eld-erly. Aside from the length of age period, reproductive health problems are also exceptionally complex, starting from pregnancy and delivery-related problems, sexually transmitted and de-generative diseases. The underlying factors are varied; starting from the educational, health, religious and social-cultural aspects.

The major problem that requires special attention and largely defines the survival of a nation is the high maternal mortality ratio (MMR). In principal, majority of maternal deaths are avoid-able despite the resources limitation. However, to undertake the appropriate initiative, correct information as the reference for decision-makers is required.

The Reproductive Health Profile contains various maps and tables used to obtain an overview on the progress of implementation of reproductive health programmes from health initiative, resources and status.

The user is expected to utilize the gained information to critically evaluate the existing serv-ices and programmes as well as carry out necessary follow-ups to promote the reproductive health programmes.

Our appreciation and thank go to all stakeholders, especially to WHO and GTZ that have helped in the development and printing of Reproductive Health Profile. It is expected that the document is beneficial to the effort to accelerate reduction of maternal mortality ratio and neonatal mortality rate in Indonesia.

Jakarta, November 2007Director General of Community Health

Ministry of Health R.I.

Dr Sri Astuti S. Soeparmanto, MSc.(PH) Jakarta, December 2007

Forewordby

Director of Maternal Health

Let us extend our great blessing to God The Almighty who has helped us in the formulation of National Reproductive Health Profile 2001 2005, which is expected to be used as one of the facilities to monitor the updated implementation of reproductive health, relating to the overall human life cycles starting from pregnancy, birth, childhood, adolescent, adult, up to elderly. This document is particularly featuring more details on data starting from the periods of pregnancy, delivery, postpartum, family planning, up to newborn.

The National Reproductive Health Profile consists of 38 chapters containing maps and tables complemented with the narration based on the indicators of minimal service standard, health initiatives, human resources and health status. The data sources were taken from the provin-cial monthly report and Indonesian Health Demography Survey (SDKI) for Family Planning and Newborn data. The user of this document is expected to know the description of health initiatives, resources and status in order to achieve the goal of National Mid-Term Develop-ment Plan (RPJMN) 2009 and the MDG 2015.

We would like to convey our sincere appreciation and thank to all stakeholders who have contributed in the formulation of this document. Our similar appreciation and thank also goes to WHO for their valuable contribution in the overall process of formulating this document.

The National Reproductive Health Profile contains maps and tables used as a description on the updated implementation of reproductive health programmes addressed to the policy-mak-ers to make future planning.

Any constructive suggestions and inputs are welcomed in order to improve the document.

Jakarta, December 2007Director of Maternal Health

Ministry of Health R.I.

Dr Sri Hermiyanti, MSc.

D E PA RT E M E N K E S E H ATA N R IDIREKTORAT JENDERAL BINA KESEHATAN MASYARAKAT

JL. HR. RASUNA SAID BLOK X5 KAPLING 4-9 JAKARTA 12950 Telp Dirjen 5203871, Set. Ditjen 5221225-5221226

Telp.: Dit Bina Kes Ibu 5221229, Dit Bina Kes Anak 5273422, Dit Bina Kes Komunitas 5221228, Dit Bina Gizi Masyarakat 5210176, Dit Bina Kes Kerja 527526

D E PA RT E M E N K E S E H ATA N R IDIREKTORAT JENDERAL BINA KESEHATAN MASYARAKAT

JL. HR. RASUNA SAID BLOK X5 KAPLING 4-9 JAKARTA 12950 Telp Dirjen 5203871, Set. Ditjen 5221225-5221226

Telp.: Dit Bina Kes Ibu 5221229, Dit Bina Kes Anak 5273422, Dit Bina Kes Komunitas 5221228, Dit Bina Gizi Masyarakat 5210176, Dit Bina Kes Kerja 527526

INTRODUCTION


The Republic of Indonesia is a nation of over 17,500 islands (6000 inhabited) in South East Asia, and the worlds largest archipelagic state. With a population of over 220 million, it is the worlds fourth most populous country and the most populous Muslim-majority nation. The country shares land borders with Papua New Guinea, East Timor, and Malaysia and by sea Indonesia neighbors Singapore, The Philippines and Australia. The capital, Jakarta, is on Java and is the nations largest city, followed by Surabaya, Bandung, Medan, and Semarang.

The population is expected to grow to around 315 million in 2035 based on the current estimated annual growth rate of 1.25%. Population density varies considerably by region from only 11 people per square kilometer in Maluku/Papua to more than 1000 in Java.

Overall, Indonesias urban population has grown 15% since 2000, and is expected to continue to expand to 54% by 2010. While the average proportion of people living in urban areas is nearly

INTRODUCTION

Figure 1. Percentage of urban and poor populations, by province (BPS, 2006)

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half (48%), this ranges from 18% in East Nusa Tenggara to over 60% in East Kalimantan, Banten, Yogyakarta, and Jakarta. See Figures 1 and 2 for provincial and regional rates of urban and poor population, respectively.

Administratively, Indonesia consists of 33 provinces including the capital, Jakarta. Each has its own political legislature and is headed by a governor. The provinces are subdivided into regen-cies (kabupaten) and cities (kota), which are further subdivided into sub-districts (kecamatan), and again into villages (kelurahan or desa). Four provinces have special status: Aceh, Jakarta, Yogyakarta and Papua. This special status provides greater legislative privileges and a higher degree of autonomy from the central government in comparison to other provinces.

Organization of the Health System

The Government of Indonesia has employed a tiered approach representing a continuum of care from provincial and district public hospitals down to the sub-district and village level health facili-ties. At the sub-district level, primary health centers (puskesmas) are staffed with doctors, nurses, and midwives, and are equipped to provide primary health care services to an area with about 30,000 population, or about 10 villages. The clinics offer a package of basic services including maternal and child health, family planning, out-patient care and communicable disease control (TB DOTS, STIs). They also serve as primary level referral facilities linking patients to district hospitals. A number of health centers with beds have been established in order to provide service on site when referral to a district hospital is impractical. The puskesmas are supported by over 20,000 sub-health centers, mobile health centers, and village-based maternity huts.1

Health access, particularly for pregnancy and delivery care, has been even more decentralized with a recent program (1989-1998) under the Ministry of Health which deployed approximately 54,000 village midwives as part of an initiative to ensure greater access to trained delivery provid-ers. These midwives are called bidan di desa (midwife in the village). Currently, there are still over 30,000 village midwives taking part in the program. In addition, private midwives with more

1 Country Health Profile (accessed at: http://www.searo.who.int/LinkFiles/Indonesia_indonesia1.pdf, April 2007)

established clinics who are able to achieve certain skill and facility standards have worked under the midwife professional association (IBI), with support from USAID, to form an official private practice standardization and accreditation program called Bidan Delima. There are over 3000 midwives in this program in selected provinces, with hopes of growing the program further to im-prove professional and technical standards in midwifery nationwide. Finally, private doctors and specialists provide antenatal and delivery care services as well.

To further strengthen maternal and child health care services, since the mid-1980s Integrated Service Posts (posyandu) were established at villages to provide community-based and com-munity-organized programs mainly targeted at addressing nutrition, diarrhea, family planning, vaccination and general maternal and child health. Fieldworkers and community cadres of the National Family Planning Coordinating Agency (BKKBN) have played an important role in mobiliz-ing community members by providing health information, and encouraging women and adoles-cents to come to the posyandu or puskesmas to get basic maternal and family health care, and family planning services.

Following the implementation of decentralization in 2001, the 440 districts or regencies have be-come the key administrative units responsible for providing most government services, including primary health care. Significant budget control and health planning responsibility has been moved from central level directly to the districts, with limited provincial involvement. The central Ministry of Health has maintained functions over communicable diseases, setting quality standards, na-tional indicators and targets, overseeing standardized training modules for health professionals, overseeing pharmaceutical regulation, and advocating with the national government for continued health financing, and increased access of the poor to public health services.

Local Area Monitoring and Health Data Collection

Local Area Monitoring (SSM) describes the system by which much of the health management information system data is collected, recorded and reported. Fieldworkers and cadres maintain detailed records of their activities and services, and health outcomes in their respective areas. These data are reported to the district/sub-district health centers (puskesmas), which are then reported to district officials, and forwarded to provincial officials for consolidation and reporting to the Ministry of Health. Districts compile their reports quarterly; provinces compile reports annually and submit to central level annually.

The reproductive health information system (HIS) datasets from the districts/provinces used in these profiles are from 2005. These data are reported in excel format on five separate work-sheets. They outline data at district level providing provincial totals and simple indicator calcula-tions. Data include demographics (population, pregnancies, deliveries, newborn born), number of people who received services according to a range of indicators relevant to reproductive health and national targets, health facilities, health personnel, maternal and neonatal deaths, stillbirths, causes of maternal death, and timing of neonatal death.

Public and private hospitals report directly to the province. Hospital data is not compiled by dis-trict; only provincial totals are calculated. The hospital HIS data relevant to reproductive health includes total births in hospital, total complications managed, by type of complication (bleeding,

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sumatra java kalimantan sulawesi bali, nusa tenggara maluku, papua

Figure 2. Percentage of urban and poor, by region (BPS, 2006)

% urban % poor

INTRODUCTION


infection, eclampsia, abortion, other), c-sections, and mortality by cause. Hospital data is com-piled at central level, and availability of these data can be delayed. The most recently compiled hospital database available for these profiles is from 2004.

Health Indicators and Outcomes

Despite an average annual economic growth rate of 5%, Indonesias social indicators reflect considerable inequity. Nearly 17% of all Indonesians are classified as below the poverty line (about IDR 4000/day/capita), but poverty rates by region range from 10% in Kalimantan to 31% in Maluku/Papua.2 An estimated 49% of Indonesians live on less than USD 2 per day (IDR 18,000).3 Adult female literacy is relatively high at 87%, ranging from 68% in Papua to 99% in North Sulawesi.4

Although communicable diseases remain the main cause of mortality, Indonesia is also experi-encing an epidemiological transition driven by a higher prevalence of non-communicable, life-style related diseases. The proportion of smokers is steadily increasing all over Asia, particularly among young people. In 2003, over 1 in 5 Indonesians were estimated to smoke daily. In con-trast, only 3 out of 4 (77%) Indonesians have access to safe water (91% in urban areas; 67% in rural areas).5

Economic development and social investment has facilitated a significant decline in both the infant and under-5 mortality rates over the past 30 years. Current estimates are 28 infant deaths (

INTRODUCTION

10Provincial Reproductive Health & MPS Profile of Indonesia

Provincial reproductive health profiles were prepared using HIS data reported by each province from 2001-2005, and hospital datasets of 2001 and 2004. The following categories were reviewed in each province: Health facilities, number of basic and comprehensive emergency obstetric care facilities, health personnel, antenatal care coverage, skilled birth attendance coverage, postnatal/neonatal care coverage, maternal and neonatal deaths and hospital-level statistics on obstetric complications, c-sections, and maternal mortality.

The 2005 dataset was described in the most detail. Health personnel were described using both 2001 and 2005 datasets to detect increasing or decreasing trends in coverage over time. Ante-natal attendance of at least four visits (K4), skilled birth attendance, and maternal mortality was assessed for all years between 2001 and 2005 (where data were reported). A final summary table of key indicators was prepared to compare key indicators in 2001, 2005, and national targets for 2007 and 2010.

All tables were formulated in order to describe the data in a standardized manner for each prov-ince (though some adjustments were made for some provinces due to data omissions) and to enable provincial comparisons of selected indicators.

A Note on Data Quality

The overall data quality of health facility and health personnel reports was poor. Almost every province submitted incomplete data on some or all of these indicators, for some or all districts.

Data on demographic events (population, pregnancies, deliveries and newborn born), and servic-es provided was generally more complete than data on health infrastructure. However, detection of pregnancy risk and management of complications was less accurate and complete compared to more basic (and perhaps more easily defined) indicators such as antenatal care and birth at-tendance.

Mortality data also appeared to be poor. Maternal mortality ratios calculated for each year did not show interesting or believable trends. Stillbirths and neonatal deaths were significantly under-reported by all provinces. Based on estimates, HIS reported maternal deaths likely represented only as much as half of expected deaths, and stillbirths/neonatal deaths maybe one-third or fewer. Provincial estimates of mortality rates were not available, therefore it was impossible to even esti-mate which provinces may have under-reported more or less than the others. It is also not likely that the same rate of under-reporting applies to all districts.

This variability in reporting completeness and quality makes it very difficult to draw any valid con-clusions from comparing provinces to one-another. Although these data are presented in each profile, and provincial comparisons are compiled in this chapter, extreme caution is advised in their interpretation. More valid conclusions may be drawn from regional-level comparisons (i.e. Java compared to Sumatra).

Due to the inability to verify the data quality at the district and even the provincial level, caution is also advised in interpreting the meaning of individual provinces or districts highlighted as under-

performers on specific indicators. Sometimes, certain areas will repeatedly appear as having low coverage which likely reflects real problems in those areas. Other times, areas may appear as under-performers simply because of errors or omissions in their HIS data reports. All areas highlighted as being at particular risk should be investigated more closely and directly through site visits to those areas, situational analyses, and meetings with health providers and health officials for a more accurate picture of health status in those communities.

Districts or provinces may also wish to review their HIS reports on an ongoing basis, from 2006 and later, to correct problems in data quality or consistency, and identify potential service gaps.

Increased utilization of data to provide feedback to health workers and to assist in health planning should lead to better quality data being collected, and better-directed health resources to problem areas. Provincial health officials who can link hospital and provincial data will also be in a better position to contribute to a more integrated and effectively implemented reproductive health pro-gram overall. Quality of care, and accessibility and responsiveness of hospitals to the community is central to improving access to emergency obstetric/neonatal care which will lead to reductions in maternal and neonatal mortality.

Health Facilities and Personnel

Health facility data includes both public and private hospitals, hospitals with specialists (obstetrics and pediatrics), puskesmas, puskesmas with doctors, puskesmas with beds, and puskesmas that have received training in basic emergency obstetric care (BEONC, or PONED).

BEONC training involves three people from each puskesmas (doctor, nurse, and midwife) and covers topics such as pre-eclampsia, shoulder dystocia, vacuum extraction, postpartum hemor-rhage, postpartum fever, management of low birth weight newborn, hypoglycemia, icterus/hyper-bilirubin, feeding problems, asphyxia, respiratory problems, neonatal (LBW) convulsion, referral and transportation. The training is seven days long and costs IDR 9.3 million for three persons (one facility).

Health personnel data includes total specialists (obstetrics, pediatrics), total general practitioners, ANC trained nurses, total midwives and key characteristics of midwives. One of these character-istics is APN training which prepares individual midwives (including private practitioners) in active management of 3rd stage of labor, management of hemorrhage and neonatal asphyxia. The train-ing is 10 days long and includes a clinical practicum. It costs IDR 4.4 million per midwife. The aim is to concentrate training on skill areas most likely to reduce maternal and neonatal mortality.

Compilation Figure 3 shows the proportion of villages with a bidan di desa, and proportion of midwives who have received APN training. Most provinces have bidan di desa coverage of less than 60%, and the level of APN training is low.

Figure 4 describes the proportion of all puskesmas with beds, and the proportion of all puskesmas who have received BEONC training. This figure shows that most provinces have not succeeded in providing the skills to all health teams working at puskesmas likely to provide delivery care.

INTRODUCTION


Table 1 ranks provinces on the proportion of APN trained midwives, and the proportion of BEONC puskesmas, as a percentage of all midwives and all puskesmas, respectively.

Table 1. Provinces by rank according to APN training and BEONC puskesmas% midwives with APN training % BEONC puskesmas

Worst ranking provinces (

INTRODUCTION


Primary Health Care Indicators: Methodology Note

All indicators rely on the accuracy of numerators and denominators to reflect a true picture of health service coverage. At the national level, the MOH has standard formulas to estimate the number of pregnancies and deliveries in the country overall. The smaller the areas such formulas are applied to, however, the less accurate the resulting estimates become because their accuracy relies on a provincial estimate of the crude birth rate (CBR). The most recently available provin-cial estimates for CBR were from 2000 (BPS), and they varied substantially by province. CBRs could be calculated from reported newborn/reported population, but that would not allow for an independent assessment of the accuracy of those reported events by province in HIS data.

Therefore, CBR estimates from 2000 were used for 26 provinces to calculate estimated pregnan-cies and deliveries. CBRs from host provinces were applied to seven additional provinces that

are now separate (Kepri/Riau, Bangka Belitung/South Sumatra, Banten/West Java, Gorontalo/North Sulawesi, West Sulawesi/South Sulawesi, North Maluku/Maluku, and West Papua/Papua). The overall country CBR was 22.2, but the range was from 16.9 (Yogyakarta) to 27.8 (Papua).

The ratio of reported to calculated events was used to evaluate the accuracy of reported events. Over the whole country, the ratio of reported to estimated pregnancies was 100.8, and reported deliveries/estimated deliveries was 100.7, which means that reported events were quite accu-rate overall. Three-quarters of all provinces had reported/estimated ratios between 95 and 105 indicating relatively high accuracy of counted events, and little bias toward under-counting or over-counting.

The ratio of reported to estimated events was evaluated for each district in each province to de-termine if the province had systematically calculated those events using a standard multiplier or

Figure 3. Proportion of all villages with midwife living in village, and proportion of allmidwives with APN training, by province (HIS 2005; data not reported by all provinces)

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Figure 4. Proportion of all puskesmas with beds, and proportion puskesmas with BEONCtraining, by province (HIS 2005; data not reported by all provinces)

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not. Only one province, East Java, appeared to do this. A few minor errors were also identified during this process. West Sumatra did not submit population or delivery data, so deliveries were estimated according to reported pregnancies (94.7%). Maluku submitted pregnancy and delivery data that reflected very large errors in several districts (under and over-reporting), so estimated pregnancies and deliveries were calculated using standard MOH formulas. North Sumatra and South Sumatra had obvious errors in one district, each, so events for those district only were estimated. The remaining 28 provinces appeared to submit actual counts of pregnancies and de-liveries that appeared valid and consistent with expectations and with one-another (see Appendix for more detail on data corrections).

There is no standard MOH formula for determining the expected number of newborn born accord-ing to total population, pregnancies or deliveries. Therefore, this was calculated using 2005 data from the country overall. Each provincial report of newborn was first evaluated according to re-

ported deliveries. Four provinces were excluded from the multiplier calculation due to substantial errors in one or more districts, or lack of reporting delivery data altogether. Three provinces were excluded because reported newborn were either the same or greater than reported deliveries. The data from the remaining 26 provinces was totaled, and the proportion of newborn to deliveries was calculated (96.2%). This multiplier was then used to estimate reported newborn, by district, in the four provinces that reported invalid data, and to make other minor corrections to reported newborn in three additional provinces.

Overall, an average of 2.4% of the population was reported to be pregnant in 2005 (range: 1.6 in Yogyakarta to 3.0 in Riau).

Antenatal Care Coverage

INTRODUCTION


Key concepts in evaluating antenatal care coverage are access and retention. Access is mea-sured by the K1 indicator (referred to as ANC1 in the profiles) which measures the proportion of pregnant women who have completed at least one antenatal visit. Retention is measured by the K4 indicator (ANC4) which measures the proportion of pregnant women who have completed at least four antenatal visits, the standard recommendation for pregnant women not experiencing any complication or sign of illness/risk. The difference between K1 and K4 reflects the level of missed opportunities to the health care system these are the women who proved to be able to access care, but did not comply with the recommended number of visits. This difference reflects potential gaps in quality of care and potential benefits to closing those gaps.

Figure 5 shows the K4 coverage and K1-K4 difference by province. The majority of provinces range between 70-80% for K4 coverage. The difference between access (K1) and retention (K4) ranges from 5% to over 20%. Overall access (K1) can be estimated by adding the differ-ence to the K4 bar. Most provinces have good access to antenatal care, but vary more in their performance on keeping women in the antenatal care system throughout pregnancy. Table 2 ranks provinces according to these two indicators. Only five provinces met or exceeded the 2007 national target for K4 (84%).

Skilled Birth Attendance

Increasing the proportion of women who are delivered by a skilled health professional is prob-ably the most important first step toward reducing maternal and early neonatal mor-tality in any country. Insuring that those skilled birth attendants are well trained, have necessary equipment, practice infec-tion control and other basic skills, and are supported by a functional referral network including transportation and hospital ac-cess are also critical factors. However, the effectiveness of all of these quality of care components depends first on whether women are using skilled birth attendants.

The last two demographic health surveys shows that the national estimates of the rates of SBA coverage (doctor, nurse or midwife attend-ing) and deliveries at a health facility (public or private) have increased substantially between 1997 and 2002. HIS data from 2005 support this estimated increase in SBA coverage, with 22 provinces reporting rates at 70% or higher (see Table 3 and Figure 6).

Postnatal (Neonatal) Care Coverage

Table 2. Proportion of pregnant women who attend 4 visits of antenatal care, and pro-portion of women who attend some ANC, but not the full 4 visits

At least 4 ANC visits (K4)Difference between

K4 and K1 (women with

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This indicator measures both maternal postpartum access to care, and neonatal care. The tim-ing of the KN1 visit should be with 2 days of birth/delivery, and the KN2 visit before 28 days postpartum. There may be some lack of precision in this indicators definition and understanding in the field, and in the actual services provided at KN visits. It is likely that many visits are focused on the neonate rather than the postpartum mother, and that important signs of maternal illness or risk in the mother could easily be missed by the health system as a result. In 2002/3, the IDHS reported data somewhat outside of the definition of this indicator, however, 62% attended a post-natal checkup within 2 days of delivery, and 17.5% did not attend any postnatal care.

HIS data from 2005 is reported in Table 3 by province. Generally, the rate of KN1 is higher than the IDHS estimate of 2002 in most provinces.

Table 3. SBA and KN1 coverageCoverage of deliveries with a skilled birth

attendant Coverage of 1st postnatal / neonatal visit

Worst ranking provinces (SBA or KN1 coverage

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Maternal and Neonatal Deaths

A total of 4169 maternal deaths were reported for 2005 in Indonesia, or only 87 / 100,000 es-timated live births. This current MMR based on actual reported deaths is less than half of the lowest current estimate of the MMR in Indonesia. The WHO/UNICEF/UNFPA estimates the MMR to be 230; the most recent estimate from the IDHS was 307 (2002/3).

Figure 7 shows maternal mortality ratios from the years 2001-2004 are similarly under-reported by about 60%. A slight decline is observed from 2004, but with substantial rates of under-report-ing, continued reporting errors cannot be ruled out as an explanation for the observed reduction in MMR.

Table 4 ranks all provinces by total number of reported deaths through the HIS in 2005. Figure 8 shows each provinces total number of reported deaths, with summary totals (per 1000 reported

deaths) which describe the proportion of all maternal deaths contributed by each re-gion. For example, 20.7% of all maternal deaths occurred in Sumatra region in 2005 (or 207/1000 reported deaths). Java accounted for over 46% of all deaths, Kalimantan only 5.5%, Sulawesi 11%, Bali/Nusa Tenggara 11% and Maluku/Papua 5%.

Figure 9 shows each provinces maternal mortality ratio, with summary ratios calculated for each region. There is significant variability in MMRs within all regions except Kaliman-tan. Table 5 ranks each province by MMR: East Nusa Tenggara, Maluku, Kepri, North Maluku and Gorontalo have the highest reported MMR (>200). These five provinces represent four different regions, under-scoring the diversity of the country with regard to health indicators and access to quality care.

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Figure 6. Proportion (%) of all deliveries attended by a skilled health provider,by province (HIS 2005)

INTRODUCTION


The regional MMRs show that Maluku/Papua has the highest MMR at 188, followed by Bali/Nusa Tenggara (170) and Sulawesi (122). Kalimantan and Sumatra have similar ratios (78 and 80 respectively). Java has the lowest reported MMR at 74, although the island accounts for nearly half of all deaths due to the fact that 58% of the population of Indonesia lives on Java.

Hospital data report maternal deaths that occur in hospital. The proportion of maternal deaths in hospital is a crude measure of the accessibility of hospitals in the event of an obstetric emer-gency. If a higher proportion of maternal deaths are occurring in hospital, this likely means that women having a complication during pregnancy or delivery were able to access tertiary care prior to death. The timing of access would be important to further understand this indicator. If most women who died are accessing too late for the hospital to effectively intervene, then midwives skills, referral and transportation systems should be reviewed. If most women who died were actually delivered in hospital, then the quality of care at hospitals should be reviewed further (training, skills, staffing, equipment, quality assurance, etc.).

Figure 10 shows this indicator (hospital deaths 2004 / all reported deaths in 2004) by province. It ranges from zero to over 80%. Table 6 ranks all provinces by the proportion of reported deaths occurring in hospital. Eleven provinces were below 10%, and only three provinces were above 50%. This indicator could not be calculated for 8 provinces due to missing 2004 maternal mortal-ity reports from either the hospital or the community, or both. When these rankings are compared to actual MMR (Table 5), 7 of 11 worst ranked provinces had MMRs over 100, while only 4 of 11 moderately ranked provinces had MMRs over 100. This suggests that this indicator has some validity in evaluating progress toward reducing maternal mortality. However, caution is advised in over-interpreting this indicator. This measure is highly subject to error if hospital data are incom-plete, which they likely are.

Reported causes of maternal deaths support international data citing hemorrhage as the leading cause. Eclampsia is the 2nd leading cause of death in almost every province. Infection gener-

Figure 5. Proportion (%) of pregnant women who attend the 4th antenatal visit (K4),and % who attend some antenatal care, but not the recommended four visits (K1-K4),

by province (HIS 2005)

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k4 k1-k4

INTRODUCTION


ally accounts for a very small proportion of deaths, though it may be more under-re-ported than other causes due to difficulty in diagnosing infection as a primary cause of death in cases occurring in the community. The biggest concern about these data (see Figure 11); however, is the very high rate of unattributed maternal deaths to other or unknown causes. This is equally true of hospital data where there should be a far higher proportion of deaths attributed to an

underlying causes than actually observed in most provincial hospital reports.

In summary, because there is consistent evidence of under-reporting of maternal deaths in all provinces, and no guarantee that provinces under-report at similar rates, extreme caution is ad-vised in over-interpreting these reported rates of maternal mortality. Key interpretations of the above data that are most likely to be valid are:

Under-reporting maternal mortality is a significant problem in all provinces.

There is no evidence of any significant decline in maternal mortality since 2001.

The largest number of maternal deaths occurs in Java, though the individual risk of death per woman in Java may be lower than other regions of Indonesia.

Women living in Maluku/Papua region, and East or West Nusa Tenggara (not Bali) face the highest individual risk of maternal death.

These disparities in maternal mortality rates by region (and province) suggest that different provinces may require different interventions to further reduce maternal mortality. Provincial level situation analyses of factors contributing to maternal mortality should be under-taken.

The rate of deaths occurring in hospital as a proportion of all maternal deaths may be an impor-tant indicator to monitor as a measure of access to emergency obstetric care.

Table 4. Reported Maternal Deaths, HIS 2005Worst ranking provinces (>200)

Jawa Tengah 61Jawa Barat 624Jawa Timur 41Nusa Tenggara Timur 0

Other provincesSulawesi Selatan 16Riau 15Banten 15Sumatera Utara 15Nanggroe Aceh Darussalam 11Sumatera Barat 110Nusa Tenggara Barat 10Sulawesi Tengah Kepri Lampung 4Maluku Papua 5DKI 0Kalimantan Barat 0Sulawesi Utara 6Sulawesi Tenggara 62Jambi 60Kalimantan Selatan 5Kalimantan Timur 5Sumatera Selatan 54Maluku Utara 46Gorontalo 45Kalimantan Tengah 42D.I Yogyakarta Bali 5Bangka Belitung 0Sulawesi Barat 2Bengkulu 26Irian Jaya Barat 1

TOTAL 416

307 307 307 307 307

230 230 230 230 230

100 97 97 82 87

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2001 2002 2003 2004 2005

MMR

WHO/UNICEF estimate

IDHS estimate

Figure 7. Maternal Mortality Ratio (reported deaths / 100,000 estimated live births), 2001-05compared to MMR estimates from WHO/UNICEF (2006) and IDHS (2002/3)

INTRODUCTION


Hospital Management of Maternal and Neonatal Complications

Hospital data show that most pregnant women treated in hospital are classified as complicated cases. Complicated deliveries were reported by cause: bleeding, eclampsia, infection, abortion, or other. Deliveries counted only in the c-section column of the data report (thus, not assigned to an underlying reason for the c-section) were not counted as complicated. The proportion of hospital deliveries classified as complicated ranged from less than 8% in the Maluku Islands to 74% in Jambi and West Papua (89%). Nearly three-quarters (24) of all provinces reported rates between 40 and 65%. It is clear that most hospitals primarily manage complicated deliveries, and

Community and health providers (including those in hospital) may be poorly trained in assigning a likely cause of maternal death. Further efforts should be directed toward ensuring higher level medical review of a significant proportion of maternal deaths as part of better understanding risks and opportunities for prevention.

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Figure 8. Maternal deaths (HIS 2005), by province andregional proportion of every 1000 reported deaths (brown bars)

INTRODUCTION


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Figure 9. Maternal Mortality Ratio, by province (HIS 2005)(reported deaths / 100,000 reported newborn), and

MMR by region (brown bars; rep dths / 100,000 estimated live births)

Table 5. Maternal Mortality Ratio (reported maternal deaths / 100,000 estimated live births, HIS 2005)Worst ranking provinces (>200)

Nusa Tenggara Timur 00Maluku 25Kepri 255Maluku Utara 221

Moderate provinces (from 60-200)Papua 16Sulawesi Tengah 164Sulawesi Utara 160Riau 14Sulawesi Tenggara 12Sulawesi Barat 12Bangka Belitung 121Sumatera Barat 115Nanggroe Aceh Darussalam 10Jawa Tengah 106Irian Jaya Barat 105Nusa Tenggara Barat 104Sulawesi Selatan Jambi 6Kalimantan Tengah Kalimantan Timur D.I Yogyakarta Kalimantan Selatan 0Kalimantan Barat 2Jawa Barat 6Banten 6Jawa Timur 65Bengkulu 60

Best ranking provinces (below 60)Bali 56Lampung 52Sumatera Utara 46DKI Sumatera Selatan 2

TOTAL

INTRODUCTION


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Figure 10. Estimated proportion (%) of all maternal deaths occurring in hospital(HIS 2004 reported deaths as proportion of 2004 hospital data reports of deaths;

non-reporting districts excluded)

Table 6. Percent of maternal deaths (2004) oc-curring in hospital

Worst ranking provinces (

INTRODUCTION


Figure 11. Causes of maternal deaths as proportion (%) of total reported deaths,by province (HIS 2005)

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bleeding eclampsia infection unk / other

see relatively few normal deliveries (Table 7 and Figure 12).

The rate of c-sections among all hospital deliveries, ranging from 11% to 81%, has to be consid-ered that can be high given the high rate of complicated deliveries in hospitals. A more accurate analysis at the cause of c-section is very important and urgent. Nearly three-quarters (24) of all provinces report c-section rates above 20%.

The rate of hospital delivery among all reported pregnancies is very low (Table 8). It ranges from as low as 1% (Aceh, North Sumatra) to just over 13%.(North Sulawesi, Gorontalo, Jakarta). Two-thirds (22) of all provinces fall between 2% and 6%. The rate of c-sections provided among all deliveries is even lower, ranging from 0.3% to 7% in Jakarta. Only six provinces reported a rate over 2% (see Figure 13).

This low rate of c-sections suggests extremely poor access to appropriate medical care and surgi-cal intervention if required. Internationally, from 5-15% are expected to require delivery by c-sec-

tion for optimal maternal/neonatal outcome. In provinces where c-section rates are relatively high (Bali, Jakarta), it is likely that some of those c-sections were not medically necessary. However, the far larger problem is the predominance of women who require surgical delivery but are not accessing it. With an estimated 5.1 million deliveries per year in Indonesia, at least 250,000 c-sections (5%) would be medically necessary to save the mother or neonate, yet only 71,000 were reported in 2004.

The IDHS estimated that 4.1% of all deliveries were by c-section in 2002/3. If this is true, then the number of women treated in hospital, and the number of c-sections performed is significantly un-der-reported in the hospital database. These are critically important indicators that help provinces and the Ministry of Health monitor the progress of safe motherhood initiatives. Ensuring complete hospital data on these key indicators will provide a far clearer picture of progress, or lack thereof, toward making pregnancy safer in Indonesia.

Case fatality rates (CFR) as reported by hospitals range from zero to just over 5% (WHO > 1%).

INTRODUCTION


Table 7. Proportion of all hospital deliveries classified as complicat-ed, and c-section rate among hospital deliveries.% complicated

(among hospital obstetric cases)% delivery by c-section

(among hospital deliveries)Maluku 8 Papua 11Maluku Utara 8 Irian Jaya Barat 11Papua 25 Maluku 12Nusa Tenggara Timur 28 Maluku Utara 12D.I Yogyakarta 33 Sumatera Selatan 14Sumatera Utara 34 Sulawesi Tenggara 16DKI 36 Nusa Tenggara Timur 16Kalimantan Barat 41 Bengkulu 17Sulawesi Utara 41 Bangka Belitung 19Gorontalo 41 Kepri 21Bangka Belitung 42 Riau 21Kalimantan Timur 42 Sulawesi Utara 23Nanggroe Aceh Darus-salam 45 Gorontalo 23

Bali 47 Kalimantan Barat 24Sumatera Selatan 47 Nusa Tenggara Barat 25Kepri 47 Kalimantan Timur 28Riau 47 Jawa Tengah 31Jawa Timur 49 Lampung 32Lampung 50 D.I Yogyakarta 32Sulawesi Tenggara 50 Sulawesi Selatan 32Jawa Barat 52 Sulawesi Barat 32Sulawesi Selatan 53 Sumatera Barat 33Sulawesi Barat 53 Kalimantan Tengah 33Sumatera Barat 55 Sulawesi Tengah 36Sulawesi Tengah 56 Jawa Barat 38Jawa Tengah 56 Jawa Timur 38Kalimantan Tengah 57 Banten 39

Banten 58 Nanggroe Aceh Darus-salam 44

Kalimantan Selatan 58 Kalimantan Selatan 45Bengkulu 62 Bali 47Nusa Tenggara Barat 64 DKI 52Jambi 74 Jambi 54Irian Jaya Barat 89 Sumatera Utara 81

Figure 12. Hospital c-section rate (%) among all hospital deliveries,and % of hospital deliveries classified as complicated (bleeding, eclampsia, infection, other)

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c-section rate in hosp % complicated deliveries

WHO indicate that CFR should be > 1% to indicate good quality of care). The majority of provinc-es report rates in the moderate range (

INTRODUCTION


Figure 13. Rate (%) of hospital delivery among all pregnant women, and rate (%) of c-sectionsamong all deliveries, by province (2004 hospital report, 2004 reported pregnancies and

deliveries)

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% pregnant women delivering at hospital % of all deliveries by c-section

INTRODUCTION


Table 8. Overall rates of hospital delivery, and delivery by c-section among all reported pregnancies or deliveries through the HIS (2004)

% hospital delivery(among reported pregnancies)

% delivery by c-section (among reported deliveries)

Poor coverage (less than 2%) Poor coverage (less than 1%)

Nanggroe Aceh Darussalam 1.0 Sulawesi Tenggara 0.3

Sumatera Utara 1.1 Nanggroe Aceh Darussalam 0.5Kalimantan Selatan 1.4 Sumatera Selatan 0.6Jambi 1.6 Bangka Belitung 0.6Kalimantan Tengah 1.8 Kalimantan Tengah 0.6Moderate coverage (2-6%) Maluku 0.6Lampung 2.0 Maluku Utara 0.6Sulawesi Tenggara 2.1 Bengkulu 0.7Sulawesi Selatan 2.3 Lampung 0.7Sulawesi Barat 2.3 Kalimantan Selatan 0.7Jawa Barat 2.7 Papua 0.7Nusa Tenggara Barat 2.9 Irian Jaya Barat 0.7Bangka Belitung 3.0 Sulawesi Selatan 0.8Banten 3.0 Sulawesi Barat 0.8Sumatera Barat 3.5 Nusa Tenggara Barat 0.8Bengkulu 3.8 Nusa Tenggara Timur 0.8Sumatera Selatan 3.9 Sumatera Utara 0.9Jawa Timur 3.9 Jambi 0.9Kepri 4.3 Moderate coverage (1-2%)Riau 4.3 Kepri 1.0Jawa Tengah 4.6 Riau 1.0Nusa Tenggara Timur 4.6 Jawa Barat 1.1Sulawesi Tengah 4.7 Sumatera Barat 1.2Maluku 4.9 Banten 1.2Maluku Utara 4.9 Kalimantan Barat 1.3Kalimantan Barat 5.2 Jawa Tengah 1.6Papua 6.0 Jawa Timur 1.7Irian Jaya Barat 6.0 Sulawesi Tengah 1.8Best ranking coverage (7% or higher) Best ranking coverage (2% or higher)D.I Yogyakarta 7.4 Kalimantan Timur 2.3Kalimantan Timur 7.9 D.I Yogyakarta 2.5Bali 12.3 Sulawesi Utara 3.2Sulawesi Utara 13.2 Gorontalo 3.2Gorontalo 13.2 Bali 6.0DKI 13.3 DKI 7.2

Table 9. Case fatality rate (%) among all maternal complications treated in hospital (2004)

Lowest ranking provinces (2% CFR or higher)

Bengkulu 5.2Sumatera Utara 3.5Kalimantan Selatan 2.5Maluku 2.4Maluku Utara 2.4DKI 2.3Jawa Tengah 2.0

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INTRODUCTION


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Figure 14. Case fatality rate (%) of all complicated deliveries at hospital (2004 hospital report)

Specific Methodology Notes and Data Cleaning / Corrections

Data are submitted on 5 spreadsheets, Lampiran 1-5. Total populations reported in both lamp 3 and lamp5. Pregnancies are reported on Lamp1 and Lamp2. Where the same data appear on two different Lampiran sheets, discrepancies did occur in some districts/rovinces.

Total population from Lamp3 was synchronized with Lamp5:

SUMBAR only population reported from 2001-2005 was in 2003. Therefore, population was taken from the BPS website for that province.

SUMSEL population on Lamp3 not equal to Lamp 5 due to an obvious data entry error corrected.

JABAR population on Lamp3 not equal to Lamp 5 in several districts, and one obvious data entry error was detected. Error cor-rected, then used Lamp3 values where they were different from Lamp5.

JAMBI, BANTEN, KALTENG, SULTENG, NTT population on Lamp3 not equal to Lamp 5 in several districts; used Lamp3 val-ues where different.

PAPUA only 10 of 20 districts reported pop. Looked up total popula-tion of Papua + IRJABAR (2,646,489; BPS 2005), subtract-ed reported pop from IRJABAR (only in Lamp3), and used remaining (1,847,695) as pop for Papua. This provides the most accurate estimate of total population in Papua, but cannot be broken down by district.

Reported pregnancies, deliveries and live births (bayi)

1. Synchronization of Lamp1 bumil with Lamp2 bumil, by district. Where values different, determined which was more reasonable based on: Bulin < bumil Bayi < bulin

2. Ensured that all provincial totals (for all events and services) were summed by formula. Many provinces had entered actual numbers, which may or may not have been accurate total sums. Double-checked row-range of formulas and corrected some errors.

3. Other minor data adjustment decisions were made. These are described in respective profiles.

Indicator calculation

1. Indicators were calculated for each district. Coverage was then evaluated by district for data validity. Coverage reported at very high rates (over 110% usually) or very low rates (

INTRODUCTION


Acronyms / Abbreviations

ANC Antenatal CareAPN Basic Delivery Care (Bahasa: Asuhan Pelatihan Normal)BEONC Basic Emergency Obstetric and Neonatal CareBKKBN Badan Koordinasi Keluarga Berencana Nasional (National Family Planning Co-

ordinating Board)CFR Case Fatality Rate (deaths / obstetric complications)C-section c/s Caesarean sectionDEPKES Departemen Kesehatan (Ministry of Health, Indonesia)HIS Health Information SystemIBI Ikatan Bidan Indonesia (Indonesia Midwives Assocation)IDHS/DHS Indonesian Demographic Health SurveyIDR Indonesian RupiahK1, K4 I and IV Antenatal Visit KN1, KN2 I and II Post Partum - Neonatal VisitMMR Maternal Mortality Ratio (maternal deaths / 100,000 live births)MOH Ministry of Health, Indonesia (Department of Health)MPS Making Pregnancy Safer national program/planPGDON Life Saving Skill (LSS)Polindes Pos Bersalin Desa (village birthing post)PONED Pelayanan Obstetric Neonatal Emergency Dasar (Basic Emergency Obstetric

and Neonatal Care/BEONC)PONEK Pelayanan Obstetric Neonatal Emergency Komprehensif (Comprehensive

Emergency Obstetric and Neonatal Care/CEONC)Posyandu Pos Pelayanan Terpadu (integrated health post)Puskesmas Pusat Kesehatan Masyarakat (community health center)SBA Skilled birth attendantSSM Local Area Monitoring (Bahasa: Pemantauan Wilayah Setempat)STI Sexually transmitted diseaseTB TuberculosisTBA Traditional Birth Attendant (dukun)UNICEF United Nations Childrens FundUNFPA United Nations Regulation FundUSAID US Agency for International DevelopmentWHO World Health Organization

Provinces

NAD Nanggroe Aceh Darussalam (Aceh)SUMUT North Sumatra (Sumatera Utara)SUMBAR West Sumatra (Sumatera Barat)KEPRI Kepulauan Riau (Riau Islands)RIAU RiauJAMBI JambiSUMSEL South Sumatra (Sumatera Selatan)

BABEL Bangka BelitungBENGKULU BengkuluLAMPUNG Lampung

DKI Dearah Khusus Ibukota (Jakarta)JABAR West Java (Jawa Barat)JATENG Central Java (Jawa Tengah)DIY Dearah Istimewah Yogyakarta (Yogyakarta)JATIM East Java (Jawa TImur)BANTEN Banten

KALBAR West Kalimantan (Kalimantan Barat)KALTENG Central Kalimantan (Kalimantan Tengah)KALTIM East Kalimantan (Kalimantan Timur)KALSEL South Kalimantan (Kalimantan Selatan)

SULUT North Sulawesi (Sulawesi Utara)SULTENG Central Sulawesi (Sulawesi Tengah)SULSEL South Sulawesi (Sulawesi Selatan)SULTRA Southeast Sulawesi (Sulawesi Tengarra)SULBAR West Sulawesi (Sulawesi Barat)GORONTALO Gorontalo

BALI BaliNTB West Nusa Tenggara (Nusa Tenggara Barat)NTT East Nusa Tenggara (Nusa Tenggara Timur)

MALUKU MalukuMALUT North Maluku (Maluku Utara)IRJABAR West Papua / West Irian Jaya (Papua Barat / Irian Jaya Barat)PAPUA Papua

Nanggroe Aceh Darussalam, hereafter referred to as Aceh, was the closest point of land to the epicenter of the massive Indian Ocean earth-quake in December 2004, which triggered a tsunami that devastated much of the western coast of the province, including part of the capital of Banda Aceh. From 130,000 - 238,000 persons were dead or missing, with a further 500,000 plus being made home-less. The tsunami reached 3-5 kilometers inland along much of the coast. The scale of destruction, and sub-sequent relief efforts to rebuild the infrastructure and economy led to a peace agreement between the government of Indonesia and the Free Aceh

Movement (GAM).

Because of the total disruption of routine health services and reporting in 2005 following the de-struction of the capital city and more, the health information system dataset for 2005 was under-standably not updated. Therefore, most health indicators are calculated using 2004 data.

The total population of Aceh in 2004 was 4.3 million, accounting for 9% of the population and Sumatra, and nearly 2% of the total population of Indonesia. Aceh is divided into 21 districts (17 kabupaten + 4 kota [cities]) with a total of 6378 villages. The capital is Banda Aceh.

Aceh has a far lower urban population (29%) and higher poor population (29%) compared to the national average. Adult female literacy is higher than the national rate at 94%.

The total fertility rate (2.4) and crude birth rate (22.8) are similar to the national average. The modern contraceptive prevalence rate is not estimated as the IDHS was not conducted there. However, the percentage of women 15-48 who have ever used contraception (58%) is lower than the national average (74%).

Health Facilities

Aceh reports 27 hospitals, 17 public and 10 private (three districts did not report). There are 27 specialists in Ob/Gyn and 20 in pediatrics, all based at public hospitals.

Only 18 hospitals (all public) are certified in Comprehensive Emergency Obstetric and Neonatal Care (CEONC). About half of all districts (11 of 21) report at least one CEONC hospital, and B. Aceh reports having 6 (though some may have been destroyed in the tsunami). Districts with no CEONC coverage are: Aceh Besar, Simeulu, Singkil, Kota Lokseumawe, Gayo Lues, Ab-diya, Aceh Jaya, Nagan Raya and Bener Meriah. Some private hospitals may have CEONC certification, but there are no data reported from private hospitals on this indicator.

Aceh reports 256 puskesmas (primary health centers) with 229 puskesmas-based general practi-tioners. However, only one-third (32%) of puskesmas have beds for in-patient care. The popula-tion covered by each puskesmas, on average, meets the recommended standard.


2

NaNggROE aCEhDaRUSSalam (NaD)

SOCIAL DEMOGRAPHY NAD NationalTotal population (2005) 1 4,271,596 220,659,431Percent urban population (2005) 2 2 4Percent poor population (2004) 2 2 1Adult female literacy rate (2004) 2 4 Population density (km sq.; 2005) 2 116

Life expectancy at birth (2002) 2 Male: 66Female: 70Male: 64Female: 68

Annual growth rate (2000-2005) 2 0.55 1.34

Women of reproductive age 1,001,260 51,732,453 4

Total fertility rate / 1000 women 2.4 2 2.6 6

Crude birth rate / 1000 pop. (2000) 5 22.8 22.0

Percentage of women 15-49 who have ever used contra-ception 2 57.5 74.1

Modern contraceptive prevalence (%) 6 No DHS 56.7Unmet need for contraception (%) 6 No DHS 8.61 From provincial health data reports.2 Beberapa Indikator Penting Sosial-Ekonomi Indonesia, Edisi Juli 2006, BPS.3 Provincial website did not provide data tables on population by age and gender. This number calculated from total popula-

tion, using national ratio of women of reproductive age to total population in Indonesia (23.44%).4 From http://www.bps.go.id/sector/population/pop2000.htm, census data, table 7.5 BPS 20006 IDHS 2002/3

GEOGRAPHYTotal land area (km2) 56,500Number of districts 21Kabupaten (regencies) 1Kota (municipalities) 4Kecamatan (sub-districts) 24Kelurahan/Desa (villages) 6

Source: Beberapa Indikator Penting Sosial-Ekonomi Indonesia, Edisi Juli 2006, BPS.

first on districts with no BEONC or CEONC facility (see those highlighted above). The cost per puskesmas team (3 persons) to be trained in BEONC is IDR 9.3 million (3.1 per person).

Health Personnel

There is one Ob/Gyn for every 158,000 and one pediatrician for every 214,000 people. The coverage of GPs could not be calculated because only 6 of 20 districts reported this indicator. Population coverage of midwives meets the recommended standard of 1/3000. However, only 6% of all villages are reported to have a midwife living in the village, with significant decreases since 2001 (two districts did not report this indicator; the significant decline suggest an error in data reporting). Only 11% of all midwives have received APN training and none are reported to have received LSS training.

Primary Health Care Indicators

The data reported in 2005 for pregnancies, deliveries, newborn, service indicators and mortality are identical to the 2004 dataset. This lack of updated data for 2005 is likely due to the chaos and/or lost data following after the tsunami in December 2004. Therefore, this summary is written

Access to Basic Emergency Obstetric Care (BEONC or PONED)Only 13% of all puskesmas report having received training and certification in Basic Emergency Obstetric and Neonatal Care (BEONC). The current World Health Organization (WHO) recom-mended standard for BEONC facilities is 1 for every 125,000 people. Indonesia has adopted this indicator, but translated it to mean at least four BEONC facilities for each district.

There is an average of 1-2 BEONC facilities per district, but the distribution of them is not ad-equate. One district has none (Simeulu), and several districts report only one or two, despite significant population size (Banda Aceh, Pidie, Aceh Utara, Aceh Timur, Tamiang).

On average, the population coverage of BEONC facilities in Aceh just meets the standard of 1/125,000. However, an additional 52 BEONC facilities would be needed to reach 4 per district; and an additional 1 to meet the recommended standard of 1/125,000 population taking into ac-count the distribution of BEONC centers and population coverage within districts.

One immediate step would be to upgrade each puskesmas with a bed to BEONC level, focusing

HEALTH FACILITIES2005 Indonesia minimum

standardCoverage

Public Private

Rows bordered in red are below minimum standard

Total hospitals (general) 1 2 10 -- 3 / 500,000 pop.

Hospitals with CEONC 1 1 Not re-ported

1 CEONC hospital / district

(WHO minimum stan-dard:one / 500,000 pop.)

under the assumption that the most recently available data is from 2004.The Ministry of Health has adopted standard formulas for calculating the annual expected number of pregnancies and deliveries in a given area based on population size and crude birth rate. As-suming a crude birth rate in Aceh of 22.8 (BPS, 2000), the reported pregnancies are about 8% higher than the estimated pregnancies, and reported deliveries are 10% higher than estimated deliveries. The proportion of deliveries to pregnancies, and newborn to deliveries is valid and consistent with the country overall, further supporting the accuracy of the reported events. The likely explanation for the discrepancy between reported and estimated events is that the crude birth rate may be higher than 22.8, or the population may be higher than estimated.

Antenatal Care Coverage

Among reported pregnancies, 81% of the women attended at least one antenatal visit (ANC1). This drops to 72% coverage of 4 total antenatal visits (ANC4), which is below the 2007 target of 84%. Over 23,000 pregnant women never accessed any antenatal care, and nearly 10,000 women who have accessed antenatal care once do not obtain the minimum standard of 4 ante-natal visits. These women are either not adhering to the recommended antenatal schedule or are accessing ANC too late to reach 4 visits. Quality of care, community awareness, and logistical accessibility factors likely account for these missed opportunities.

There is some variation in report-ed antenatal coverage by districts. Five districts reported lower than average rates of ANC1 and ANC4 attendance, respectively: Aceh Timur (59% and 50%), Aceh Tenggara (57% and 52%), Aceh Selatan (73% and 48%), Aceh Jaya (65% and 51%), and Na-gan Raya (48% and 57%).

Skilled Birth Attendance

Only 58% of all reported deliveries are attended by a skilled health professional (SBA=skilled birth attendant). This leaves over 65,000 women delivering without any skilled birth attendant. The national target for skilled birth attendance is 82% by 2007 and 90% by 2010.

Four districts, Aceh Tenggara (44%), Aceh Selatan (46%), Aceh Jaya (44%) and Nagan Raya (40%), report lower skilled birth attendant coverage rates com-pared to the provincial average.

Postpartum (Neonatal) Care Coverage

The proportion of newborn who attend the first neonatal visit (KN1) was not re-ported in 2002-5, but only 54% attended KN2. The latest available data on KN1 was from 2001 which showed 73% atten-dance, but KN2 was not reported in that year. Despite the missing data, it appears than Aceh is well below targets for post-partum/neonatal care coverage.

Two districts, Aceh Jaya (21%) and Na-gan Raya (34%), report lower KN2 coverage rates compared to the provincial average.

Risk Detection and Management of Complications

In Indonesia one of the indicator measuring progress toward making pregnancy safer is the rate of pregnant women detected as at risk by the community, including cadres, TBAs or other lay persons (i.e. non-health professionals). National cutting point for complication in pregnancy stated that 20% of all pregnant women will experience some complication of pregnancy, including a recognizable risk factor for poor maternal or fetal outcome. Therefore over 24,000 pregnant women are expected to be at risk in Aceh annually (20% of all pregnant women reported).

Postpartum / Neonatal CareCoverage 2004 (KN1 not reported)

KN1 onlyor no

postnatal /neonatalcare, 46%

KN1 &KN2, 54%

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DENOMINATORS FOR KEY INDICATORS Number %

Ratio of reported / estimated 1

Reported pregnancies 117,177 2.74% of total population\ 108.4

Reported deliveries 112,212 95.8% of reported pregnancies 109.7

Reported newborn 107,473 95.8% of reported deliveries --1 Estimated pregnancies are calculated according to the MOH formula: (total population * crude birth rate * 1.11)/1000.Estimated deliveries are (total population * crude birth rate * 1.05)/1000.A standardized measure of the accuracy of reported data is if the ratio of reported / estimated is close to 100.Ratios above 100 indicate that there are more reported events than estimated events, suggesting that the crude birth

rate may be higher than estimated, the population may be higher than reported, or there is some double-counting of events.

Ratios below 100 indicate that there are fewer reported events than estimated events, suggesting that the crude birth rate may be lower than estimated, the population may be lower than reported, or there is under-reporting of events.

Antenatal Care Coverage 2004

no ANC19%

ANC1 only8%

ANC1 & 473%

Skilled Birth Attendant Coverage2004

no SBA42% SBA

58%

sion to eclampsia and death.

The number of reported stillbirths and neonatal deaths indicate serious under-reporting. Based on reported data, Aceh has a neonatal mortality rate of only 3.7 compared to a national estimate of 18 neonatal deaths per 1000 births (WHO, 2006). Therefore, it is unlikely that the Aceh data on neonatal mortality are accurate enough to utilize as an outcome indicator.

The ratio of early to late neonatal deaths is not consistent with international estimates, with less than half (48%) of all reported neonatal deaths occurring before the first 7 days. This means that early neonatal deaths are more often missed than late neonatal deaths, though all neonatal deaths appear to be under-reported. WHO estimates that three-quarters of all neonatal deaths in Indonesia occur in the first week of life, suggesting the importance of improving quality and access to pregnancy care, safer delivery and emergency neonatal care (e.g. resuscitation, infection prevention, early detection and treatment, and management of low birth weight).

The reported stillbirth rate is 2.4 in ACEH compared to the national estimate of 17.

Hospital Management of Maternal and Neonatal Complications

Reported data from hospitals in Aceh in-dicate that only about 1% of all deliveries occur in hospital. Nearly half (45%) of these hospital deliveries are classified as complicated.

The case fatality rate for complications among hospital deliveries is moderate at 1.0%, but only 4% of all reported maternal

Overall, less than 6% of these high risk women were detected as be-ing at risk by community members. However, a very high level of preg-nant women were de-tected at risk by a health provider. While a maxi-mum of about 20% of all pregnant women are expected to need risk de-tection, Aceh detected nearly twice this amount, or over 30% of all pregnant women (156% of those expected to be at risk). This finding is hard to interpret. It is possible that the definition and reporting of this indica-tor is inaccurate.

There is no data reported on management of complications, maternal or neonatal.

Maternal and Neonatal Deaths

There were 117 maternal deaths reported in Aceh in 2004 (from 15 of 20 districts only; no new data for 2005 reported). The maternal mortality ratio (MMR) was estimated to be 109. This is smaller than national estimates (MMR=230, range 58 to 440, WHO/UNICEF/UNF-PA, 2000 or MMR=307, IDHS, 2002/3), but is likely to be under-reported given the low rate of skilled birth attendance and incomplete reporting from all dis-tricts.

The predominant cause of maternal death in Aceh is bleeding, followed by infection and eclampsia. Key inter-ventions to reduce risk of hemorrhage should be emphasized (iron deficiency anemia control, trained midwives, ap-propriate use of oxytocics, access to safe blood transfusion/fluid replace-ment). Women with signs or symptoms of hypertensive disorders of pregnancy should be strenuously referred to spe-cialist care at a tertiary hospital, since early delivery by c-section is the most effective measure to prevent progres-

HOSPITAL CASES Number% of

Hospital Cases

% Coverage (reported pregnancies) 1

OB/GYN cases treated at hospital (includes normal deliveries) 114 --

1.0% of all pregnancies

Complicated OB/GYN cases treated at hospital 2 514 45.0 --

Case fatality rate 3 5 1.04.3% of reported maternal

deaths (115 in 2004) occured in hospital

Hospital admissions due to abortion 224 19.6 --Caesarean sections 501 43.9 0.5% of all deliveries1 Denominators from 2004 data were pregnancies: 117,177; deliveries: 112,212.2 Excludes deliveries counted in the c-section column as these may also be counted in complication columns (leading to c-sec-

tion). Includes cases counted in abortion column.3 Obstetric deaths at hospital / obstetric complications treated. Excludes c-sections from the denominator, although deaths

reported in the c-section column are included in the numerator.

Maternal Mortality Ratio 2001-04(deaths / 100,000 reported newborn)

(no death data available for 2005)

156

214

110 109

0

50

100

150

200

250

2001 2002 2003 2004 2005

Causes of Maternal Deaths, 2004

eclampsia12%

bleeding52%

infection16%

other /unknown

20%

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deaths occurred in the hospital.

Nearly 20% of all hospital admissions are due to abortion, indicating a high rate of unsafe abor-tion practices in ACEH. 44% of all deliveries in hospital are by caesarean section. This high c/s rate should be further analyze to understand the implication of it. Indeed, the c-section rate over all deliveries in the province, both reported and estimated, is very low (0.5%) and suggests that there are many women delivering outside of hospitals who would have had better outcomes if delivered by c-section.

Recommendations

Coverage of health personnel and service inputs

1. Review each district highlighted by name in this document for under-performance or unmet need (highlighted in bold in text and tables) to investigate apparent deficiencies (real or poor data reporting?), reasons behind under-performance, and possible solutions.

2. Increase the number of BEONC and CEONC facilities over the province. Ensure minimum standards of distribution across all districts, and correlation with population size, are taken into account in the scale-up plan.

3. Increase the number of midwives who have received APN and BEONC training, particularly in districts reporting none. Ensure that every puskesmas has at least one trained ANC midwife.

4. Increase the number of women who deliver with a skilled birth attendant, and the proportion of newborn and postpartum mothers who receive postnatal care.

5. Improve community detection of women at risk.

6. Initiate or strengthen Maternal and Neonatal Motrality audit at district and health facilities level.

Data quality and reporting

7. Invest in re-training and re-invigorating health officials at all levels on improving the quality BEONC UNMET NEED ACCORDING TO STANDARDS

DistrictTotal

popula-tion

# BEONC in 2005

Total Un-met Need (MOH: 4/ district)

Pop. / BEONC

WHO recommend-ed coverage(1 / 125,000)

Unmet need

(WHO)

1 Sabang 28,657 1 28,657 1 02 B.Aceh 264,097 1 264,097 2 1 A.Besar 306,716 6 0 51,119 04 Pidie 519,417 2 2 259,708 4 25 A.Utara 495,380 2 2 247,690 4 26 A.Tengah 187,824 1 187,824 2 1 A.Timur 316,535 1 316,535 2 A.Tenggara 169,409 1 169,409 2 1 A.Barat 198,257 2 2 99,128 2 0

10 A.Selatan 190,638 1 190,638 2 111 Simeulu 78,126 0 4 -- 1 112 Singkil 147,018 2 2 73,509 2 01 Bireun 350,611 1 116,870 014 Kt.Loksmw 168,404 1 168,404 2 115 Kt.Langsa 136,382 1 136,382 1 016 Gayo Lues 69,146 1 69,146 1 01 Abdiya 118,259 1 118,259 1 01 A.Jaya 80,541 2 2 40,270 1 01 Nagan Raya 114,521 2 2 57,260 1 020 Tamiang 232,174 1 232,174 2 121 B.Meriah 99,484 2 2 49,742 1 0

TOTAL 4,271,596 4 52 125,635 41 1

COVERAGE OF MIDWIFE PERSONNEL

District Total reported de-liveriesTotal APN mid-

wivesTotal LSS mid-

wives1 Sabang 1 4 -- 2 B.Aceh 6,167 6 -- A.Besar 8,032 14 -- 4 Pidie 13,158 6 -- 5 A.Utara 12,694 56 A.Tengah 6,977 4 -- A.Timur 11,943 4 -- A.Tenggara 4,475 4 -- A.Barat 4,035 11 -- 10 A.Selatan 5,190 14 -- 11 Simeulu 1,828 20 -- 12 Singkil 3,481 -- 1 Bireun 9,317 26 -- 14 Kt.Loksmw 4,396 -- 15 Kt.Langsa 3,370 4 -- 16 Gayo Lues 1,970 5 -- 1 Abdiya 3,005 4 -- 1 A.Jaya 2,249 22 -- 1 Nagan Raya 3,343 6 -- 20 Tamiang 5,811 4 -- 21 B.Meriah 0 6 --

TOTAL 112,212 62(1 / 179 deliveries) 5

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and completeness of all health data reported. The tsunami has certainly compromised this system, but the system was already weak before the tsunami as evidenced by lack of data on several indicators since 2001.

8. Conduct periodic (monthly or quarterly) internal data consistency and logical checks at district and provincial levels to improve quality of data.

9. Improve detection and reporting of maternal deaths, stillbirths and neonatal deaths for more

KEY INDICATORS AND NATIONAL TARGETSAceh National Target

2001 2004 * 200 2010ANC1 (K1) 1ANC4 (K4) 5 2 4 5

SBA deliveries 65 5 2 0

Postpartum / Neonatal visit (KN1) Not reported 0

Risk detection of pregnant women by community

The total population of North Sumatra is 12.1 mil-lion, accounting for over 5% of the total popu-lation in Indonesia, and 27% of the population in Sumatra. North Sumatra is divided into 25 districts (18 kabupaten + 7 kota [cities]) with a total of 5612 villages. The capital city is Medan with over 2 mil-lion people.

North Sumatra has a slightly lower urban population (46%) and poor population (15%), compared to the na-tional average. Adult female literacy is above the na-tional rate at 95%.The total fertility rate (3.0) and the crude birth rate (23.8) are above the national average. The

modern contraceptive prevalence is significantly lower (43%) than the national average, and the percentage of young women who have begun childbearing (4%) is less than half the national average. Among all contraceptive users, most women choose injection (30%), oral contracep-tives (25%), traditional methods (18%) or tubal ligation/vasectomy (13%). The rate of using a traditional method of contraception is more than twice as high as the estimate for all provinces in Indonesia.

Health Facilities

North Sumatra reports 107 hospitals, two-thirds private. There are 22 Ob/Gyn and 17 pediatric staff in public hospitals (total: 28), compared to only 14 of each type of specialists in private hos-pitals (total: 79). According to the National Bureau of Statistics (BPS 2005), there are in total 147 total hospitals (28 public and 119 private). This represents a 43% increase in private hospitals since 2001, and also reflects significant under-reporting of private hospital status in the routine health information system.

Only 15 hospitals (all public) are certified as providers of Compre-hensive Emergency Obstetric and Neonatal Care (CEONC). Ten out of 25 districts report having no CEONC hospital (Nias Selatan, Mandailing Natal, Tapanuli Se-latan, Tapanuli Tengah, Hum-bang Hasundatan, Toba Samisir, Samosir, Pak-Pak Bharat, Ser-dang Bedegai, Padang Sidim-puan). Some private hospitals may provide CEONC service, but there are no data reported from private hospitals on this indicator.

North Sumatra has 437 puskesmas (primary health centers), each with as many puskesmas-based general practitioners. However, only 24% of puskesmas have beds for in-patient care. The population covered by each puskesmas, on average, meets the recommended standard.

GEOGRAPHYTotal land area (km2) 72,428Number of districts 25Kabupaten (regencies) 1Kota (municipalities) Kecamatan (sub-districts) 5Kelurahan/Desa (villages) 5612

Source: Beberapa Indikator Penting Sosial-Ekonomi Indonesia, Edisi Juli 2006, BPS.

SOCIAL DEMOGRAPHY North Sumatra NationalTotal population (2005) 1 12,123,360 220,659,431Percent urban population (2005) 2 46 4Percent poor population (2004) 2 15 1Adult female literacy rate (2004) 2 5 Population density (km sq.; 2005) 2 16 116

Life expectancy at birth (2002) 2 Male: 65Female: 69Male: 64Female: 68

Annual growth rate (2000-2005) 2 1.35 1.34

Women of reproductive age 3,060,164 51,732,453 4

Total fertility rate

Provincial Reproductive Health

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Transcript of Provincial Reproductive Health