| Literature DB >> 29367886 |
Manpreet Singh Khurmi1, Felix Sayinzoga2, Atakilt Berhe1, Tatien Bucyana2, Assumpta Kayinamura Mwali3, Emmanuel Manzi1, Maharajan Muthu1.
Abstract
BACKGROUND ANDEntities:
Keywords: Bottleneck Analysis; Lives Saved Tool; Maternal and Newborn Health; Neonatal Mortality; Rwanda
Year: 2017 PMID: 29367886 PMCID: PMC5777390 DOI: 10.21106/ijma.214
Source DB: PubMed Journal: Int J MCH AIDS ISSN: 2161-864X
Figure 1Political and Administrative Maps of Rwanda; Source: UN Country Data and Rwanda Development Board: http://www.theiguides.org/public-docs/guides/rwanda
Mortality profile of maternal and child health, decline and proposed targets in Rwanda[6]
| Reference period | Point decline 2015-2000 | % decline 2015-2000 | MDG Goals | HSSP III | ||||
|---|---|---|---|---|---|---|---|---|
| 2000 | 2005 | 2010 | 2015 | By 2015 | 2018 | |||
| Under 5 mortality rate (per 1000) | 196 | 152 | 76 | 50 | 146 | 74 | 52 | 42 |
| Infant mortality rate (per 1000) | 107 | 86 | 50 | 32 | 75 | 70 | −28 | 22 |
| Neonatal mortality rate (per 1000) | 44 | 37 | 27 | 20 | 24 | 55 | 12 | 10 |
| Maternal mortality ratio (per 1 lakh) | 1071 | 750 | 476 | 210 | 861 | 80 | 268 | 220 |
| Total fertility rate | 6 | 6.1 | 4.6 | 4.2 | 1.8 | 30 | 4.5 | 3.4 |
Figure 2Decline in Key Mortality indicators in Rwanda, 2000 to 2015; Source: Rwanda Demographic and Household Survey Reports
Figure 3Population Pyramid of Rwanda
Figure 4Assessment framework for NCS Study in Rwanda Source: Adapted from WHO HSS building blocks framework
Projections in key mortality rates using LiST
| Indicator | 2015 | 2020 | 2025 | 2030 |
|---|---|---|---|---|
| Under five mortality rate | 50 | 45 | 34 | 29 |
| Infant mortality rate | 32 | 29 | 21 | 16 |
| Neonatal mortality rate | 20 | 18 | 11 | 8 |
| Maternal mortality ratio | 210 | 165 | 95 | 80 |
Figure 5Projections using LiST Tool in the year 2020, 2025 and 2030
Household population and characteristics according to age, sex, and urbanicity
| Age range | Urban | Rural | Rwanda | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Male | Female | Total | Male | Female | Total | Male | Female | Total | |
| < 5 | 14.6 | 13.8 | 14.2 | 15.9 | 13.9 | 14.9 | 15.7 | 13.9 | 14.8 |
| 5-9. | 13.8 | 12 | 12.9 | 16.7 | 14.6 | 15.6 | 16.2 | 14.2 | 15.1 |
| 10-14. | 11.6 | 10.4 | 11 | 14.8 | 13 | 13.8 | 14.2 | 12.5 | 13.3 |
| 15-19 | 9.4 | 12.1 | 10.8 | 10.6 | 9.2 | 9.9 | 10.4 | 9.7 | 10 |
| 20-24 | 10.9 | 11.9 | 11.4 | 7.2 | 8.1 | 7.6 | 7.8 | 8.7 | 8.3 |
| 25-29 | 10.5 | 10.7 | 10.6 | 6.9 | 7.5 | 7.2 | 7.5 | 8.1 | 7.8 |
| 30-34 | 9.5 | 9 | 9.3 | 6.9 | 7.3 | 7.1 | 7.4 | 7.6 | 7.5 |
| 35-39 | 5.7 | 6.1 | 5.9 | 4.4 | 5.4 | 4.9 | 4.6 | 5.5 | 5.1 |
| 40-44 | 4.4 | 4.2 | 4.3 | 3.5 | 4.5 | 4 | 3.7 | 4.4 | 4.1 |
| 45-49 | 3 | 2.7 | 2.8 | 3 | 3.6 | 3.3 | 3 | 3.4 | 3.2 |
| 50-54 | 2.2 | 1.9 | 2.1 | 2.9 | 3.3 | 3.1 | 2.7 | 3.1 | 2.9 |
| 55-59 | 1.3 | 1.7 | 1.5 | 2.4 | 3 | 2.7 | 2.2 | 2.8 | 2.5 |
| 60-64 | 1.1 | 1.1 | 1.1 | 1.7 | 2.2 | 2 | 1.6 | 2 | 1.8 |
| 65-69 | 0.7 | 0.6 | 0.7 | 1.1 | 1.3 | 1.2 | 1 | 1.2 | 1.1 |
| 70-74 | 0.4 | 0.8 | 0.6 | 0.8 | 1.3 | 1.1 | 0.8 | 1.2 | 1 |
| 75-79 | 0.3 | 0.5 | 0.4 | 0.5 | 0.8 | 0.6 | 0.4 | 0.7 | 0.6 |
| 80+ | 0.3 | 0.6 | 0.4 | 0.8 | 1 | 0.9 | 0.7 | 0.9 | 0.8 |
Projected decline in key indicators
| 2000 | 2015 | % decline 2015-2000 | 2030 | |
|---|---|---|---|---|
| Under 5 mortality rate (per 1000) | 196 | 50 | 74 | 13 |
| Infant mortality rate (per 1000) | 107 | 32 | 70 | 9 |
| Neonatal mortality rate (per 1000) | 44 | 20 | 55 | 9 |
| Maternal mortality ratio (per 1 lakh) | 1071 | 210 | 80 | 42 |
| Total fertility rate | 6 | 4.2 | 30 | 2.94 |
Source: Rwanda Demographic and Household Survey Reports
Strength, weaknesses, opportunities and threat (SWOT) analysis
| Strength | Weakness | Opportunities | Threats |
|---|---|---|---|
| Good Governance and leadership – Policies and Protocols are in place and strategic documents have been developed | Implementation of policies is weak at facility levels e.g., practice of hand washing, infection control practices | Growing focus on newborn health so policies and technical documents can be revised and strengthened and other evidence-based interventions can be implemented | |
| Budget available for strengthening labor room and neonatology units | Space is limited and the costs for setting up units are high. The current norms do not include | Funds from donor agencies owing to growing focus on newborn health | High out of pocket expenses incurred by community in care seeking |
| Highly motivated staff at all levels and recruited HR have strong commitment to improve health systems | Specialist Doctors are in short supply. Due to less number of academic institutes, the number of new doctors recruited will remain low. High staff turnover. | Willingness to learn and make a change in reducing newborn mortality. | Loss of skills learnt through training due to high turnover |
| Maternal and neonatology units are available including KMC wards | Units lack space and too much overcrowding due to high number of admissions in some units. Management of equipment e.g., lack of knowledge to operate radiant warmers especially at health centers, replacement of phototherapy tunes, cleaning of filters in oxygen concentrators. Some of the components of Essential newborn care e.g., Prevention of Hypothermia, counseling on Breastfeeding. Assured Referral transport mechanisms e.g., Preapproval of transport by confirmation from higher level referral center, avoidance of referral for cases that can be managed locally etc., Quality of care protocols for infection control are not being implemented | Increased number of maternal and neonatology units even upcoming hospitals such as Gisenyi Hospitals | |
| Availability of norms for setting up newborn care units | Lack of maintenance mechanisms and knowledge among health staff especially at health center levels. | Strengthen existing protocols with maintenance mechanisms and guidelines | |
| Excellent awareness of the public health care facilities especially type of treatment available at neonatology units. Aware about some of the danger signs in newborns | Lack of support from family especially during prolonged admissions | Motivated community health workers acting as a bridge between health systems and community. Young population of the country who can adopt healthy behaviors | Out of pocket expenses incurred in care seeking leading to request by family for early discharge from facilities. Uninsured population that constitutes around 21% of the population |
| Strong HMIS, Rapid SMS model and use of data in planning | Use of management tools to strengthen facilities e.g., Delivery points – high case load facilities is not being done but can be prioritized for planning. Use of Death audits and live data to monitor each and every newborn admitted and prompt action | Review of newborn care tools in other countries and develop or adapt real time monitoring of data | |
Bottleneck analysis
| Social norms | There are no major bottlenecks in terms of care seeking or traditional practices |
| Legislation/Policy (Strategic plan MCH 2013-18) | Policies are already in policy, however, strategic plans needs to be revised to include social determinants of health in planning. |
| Budget/expenditure | Budget has been year marked for various activities, however, costing and release of funds is delayed |
| Management/coordination | At the national level there is a management structure that meets regularly once every three months and also various technical groups that have been constituted that meet regularly |
| Socio-cultural beliefs and practices | There are no major bottlenecks in terms of socio culture beliefs and practices |
| Availability of essential commodities (Adequate/inadequate) | Drugs and equipment required for Newborn care have been supplied to various neonatology units, however, mechanisms and protocols for using and maintaining these equipment are missing |
| Availability of human resources | There is HR shortage both for specialists (neonatologists, regular doctors) and also nurses |
| Physical accessibility and financial accessibility | Geographic access is an issue and there are some health centers located far off from district hospital, so delay in referring patients is an issue |
| Initial utilization | The initial utilization of services by beneficiaries is good, they have good aware about treatment available at neonatology units and there are no major bottleneck in this |
| Timely continuous utilization | With increase of utilization, timely continuous utilization is low and the major reason is lack of support from family especially in cases needing a longer duration of treatment |
| Effective quality coverage | Quality coverage and quality of care is a major bottleneck identified. Protocols for hand washing, infection control practices, disinfection are completely lacking. |
Baseline coverage and target for the year 2020, 2025 and 2030
| Name of intervention | Baseline coverage | Source of data | Target (all values in %) | ||
|---|---|---|---|---|---|
| 2015 | 2020 | 2025 | 2030 | ||
| Tetanus toxoid vaccination | 82.4% | RDHS 2014-15 | 90 | 95 | 100 |
| IPTp or ITN | 67.7% | RDHS 2014-15 | 90 | 95 | 100 |
| Syphilis detection and treatment | 84.7% | HMIS 2015 | 90 | 95 | 100 |
| Calcium supplementation | NA | NA | 50 | 70 | 90 |
| Micronutrient supplementation | NA | NA | 50 | 70 | 90 |
| Balanced energy supplementation | NA | NA | 50 | 70 | 90 |
| Hypertensive disorder case management | NA | NA | 50 | 70 | 90 |
| Diabetes case management | NA | NA | 50 | 70 | 90 |
| Malaria case management | NA | NA | 50 | 70 | 90 |
| Magnesium sulphate management of pre-eclampsia | NA | NA | 50 | 70 | 90 |
| Fetal growth restriction detection and management | NA | NA | 50 | 70 | 90 |
| Skilled birth attendance | 90.7% | RDHS 201415 | 90.7 | 95 | 100 |
| Exclusive breastfeeding at 1 month | 93.5% | RDHS 201415 | 93.5 | 95 | 100 |
| Clean postnatal practices | NA | NA | 50 | 70 | 90 |
| Chlorhexidine | NA | NA | 50 | 70 | 90 |
| Hand washing with soap | NA | NA | 50 | 70 | 90 |
| Maternal Sepsis case management | NA | NA | 50 | 70 | 90 |
| Case management of premature babies | NA | NA | 90 | 95 | 100 |
| Oral antibiotics for neonatal sepsis | NA | NA | 50 | 70 | 90 |
| Active management of 3rd stage of labor | NA | NA | 68 | 95 | 100 |
Health management information system analysis from Jan 1, 2015 to Dec 31, 2015 (TG: include this table in landscape)
| S. No. | Hospital | Total deliveries | C-section | Live births | Admissions (Neonatology) | Inborn | Outborn | Referred (Newborns referred to higher level=data from maternity) | Died (Death at birth=data from maternity) | % deaths vs. admissions |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Bushenge PH | 1714 | 821 | 1679 | 220 | 127 | 93 | 1 | 15 | 6.8 |
| 2 | Butare Chu Hnr (Huye) | 1861 | 726 | 1824 | NA | NA | NA | 0 | 1 | |
| 3 | Butaro DH | 1259 | 440 | 1229 | 508 | 251 | 257 | 0 | 6 | 1.2 |
| 4 | Byumba DH | 3468 | 1662 | 3399 | 772 | 487 | 285 | 0 | 19 | 2.5 |
| 5 | CHK (CHUK) HNR | 1919 | 870 | 1891 | NA | NA | NA | 4 | 16 | |
| 6 | Gahini DH | 1672 | 632 | 1642 | 454 | 271 | 183 | 0 | 17 | 3.7 |
| 7 | Gakoma DH | 1147 | 533 | 1144 | 106 | 57 | 49 | 16 | 11 | 10.4 |
| 8 | Gihundwe DH | 2262 | 958 | 2233 | 503 | 380 | 123 | 15 | 13 | 2.6 |
| 9 | Gisenyi DH | 4759 | 2452 | 4688 | 1329 | 833 | 496 | 0 | 13 | 1.0 |
| 10 | Gitwe DH | 2122 | 881 | 2119 | 476 | 286 | 190 | 194 | 13 | 2.7 |
| 11 | Kabaya DH | 1931 | 826 | 1888 | 442 | 280 | 162 | 0 | 13 | 2.9 |
| 12 | Kabgayi DH | 4263 | 1861 | 4261 | 864 | 673 | 191 | 44 | 19 | 2.2 |
| 13 | Kabutare DH | 2767 | 1127 | 2716 | 682 | 387 | 295 | 0 | 15 | 2.2 |
| 14 | Kaduha DH | 739 | 284 | 741 | 135 | 81 | 54 | 4 | 7 | 5.2 |
| 15 | Kanombe military hospital | 419 | 225 | 344 | NA | NA | NA | 3 | 1 | NA |
| 16 | Kibagabaga DH | 4813 | 1735 | 4727 | 1116 | 832 | 284 | 84 | 11 | 1.0 |
| 17 | Kibilizi DH | 1739 | 777 | 1730 | 468 | 276 | 192 | 9 | 19 | 4.1 |
| 18 | Kibogora DH | 2605 | 1141 | 2555 | 794 | 514 | 280 | 1 | 10 | 1.3 |
| 19 | Kibungo RH | 3019 | 1344 | 2974 | 713 | 385 | 328 | 0 | 12 | 1.7 |
| 20 | Kibuye RH | 2313 | 800 | 2250 | 397 | 233 | 164 | 1 | 5 | 1.3 |
| 21 | Kigeme DH | 2016 | 948 | 2008 | 662 | 411 | 251 | 141 | 8 | 1.2 |
| 22 | Kinihira PH | 1452 | 698 | 1439 | 371 | 258 | 113 | 0 | 10 | 2.7 |
| 23 | Kirehe DH | 2738 | 976 | 2655 | 726 | 316 | 410 | 2 | 31 | 4.3 |
| 24 | Kirinda DH | 1155 | 608 | 1139 | 379 | 293 | 86 | 195 | 6 | 1.6 |
| 25 | Kiziguro DH | 2670 | 944 | 2550 | 677 | 371 | 306 | 0 | 23 | 3.4 |
| 26 | Masaka DH | 3341 | 1395 | 3287 | 675 | 363 | 312 | 0 | 6 | 0.9 |
| 27 | Mibilizi DH | 2698 | 1303 | 2679 | 621 | 400 | 221 | 3 | 18 | 2.9 |
| 28 | Mugonero DH | 982 | 201 | 948 | 179 | 78 | 101 | 1 | 7 | 3.9 |
| 29 | Muhima DH | 7632 | 2255 | 7563 | 1519 | 1341 | 178 | 590 | 40 | 2.6 |
| 30 | Muhororo DH | 1716 | 619 | 1685 | 445 | 292 | 153 | 0 | 6 | 1.3 |
| 31 | Munini DH | 1328 | 655 | 1310 | 322 | 171 | 151 | 140 | 11 | 3.4 |
| 32 | Murunda DH | 1807 | 874 | 1746 | 459 | 228 | 231 | 0 | 8 | 1.7 |
| 33 | Nemba DH | 1817 | 686 | 1775 | 661 | 443 | 218 | 0 | 12 | 1.8 |
| 34 | Ngarama DH | 1815 | 599 | 1781 | 652 | 397 | 255 | 1 | 10 | 1.5 |
| 35 | Nyagatare DH | 4177 | 1281 | 4040 | 1071 | 730 | 341 | 348 | 36 | 3.4 |
| 36 | Nyamata DH | 3457 | 1369 | 3341 | 706 | 370 | 336 | 378 | 3 | 0.4 |
| 37 | Nyanza DH | 2912 | 1313 | 2889 | 657 | 417 | 240 | 409 | 13 | 2.0 |
| 38 | RemeraRukoma DH | 2226 | 823 | 2209 | 614 | 324 | 290 | 0 | 17 | 2.8 |
| 39 | Ruhango PH | 2065 | 834 | 2063 | 470 | 306 | 164 | 0 | 10 | 2.1 |
| 40 | Ruhengeri RH | 5579 | 2276 | 5522 | 1950 | 1304 | 646 | 0 | 19 | 1.0 |
| 41 | Ruli DH | 1439 | 632 | 1417 | 498 | 318 | 180 | 88 | 6 | 1.2 |
| 42 | Rutongo DH | 1442 | 552 | 1428 | 236 | 140 | 96 | 0 | 0 | 0.0 |
| 43 | Rwamagana PH | 3606 | 1410 | 3507 | 898 | 623 | 275 | 0 | 31 | 3.5 |
| 44 | Rwinkwavu DH | 2725 | 766 | 2655 | 556 | 349 | 207 | 0 | 14 | 2.5 |
| 45 | Shyira DH | 982 | 313 | 982 | 229 | 148 | 81 | 1 | 5 | 2.2 |
| Total | 110568 | 44425 | 108652 | 26212 | 16744 | 9468 | 2673 | 586 | 2.2 | |