This is a publication on maternity activity in English NHS hospitals. This report examines data relating to delivery and birth episodes in 2021-22, and the booking appointments for these deliveries. This annual publication covers the financial year ending March 2022. Data is included from both the Hospital Episodes Statistics (HES) data warehouse and the Maternity Services Data Set (MSDS). HES contains records of all admissions, appointments and attendances for patients admitted to NHS hospitals in England. The HES data used in this publication are called 'delivery episodes'. The MSDS collects records of each stage of the maternity service care pathway in NHS-funded maternity services, and includes information not recorded in HES. The MSDS is a maturing, national-level dataset. In April 2019 the MSDS transitioned to a new version of the dataset. This version, MSDS v2.0, is an update that introduced a new structure and content - including clinical terminology, in order to meet current clinical practice and incorporate new requirements. It is designed to meet requirements that resulted from the National Maternity Review, which led to the publication of the Better Births report in February 2016. This is the third publication of data from MSDS v2.0 and data from 2019-20 onwards is not directly comparable to data from previous years. This publication shows the number of HES delivery episodes during the period, with a number of breakdowns including by method of onset of labour, delivery method and place of delivery. It also shows the number of MSDS deliveries recorded during the period, with breakdowns including the baby's first feed type, birthweight, place of birth, and breastfeeding activity; and the mothers' ethnicity and age at booking. There is also data available in a separate file on breastfeeding at 6 to 8 weeks. The count of Total Babies includes both live and still births, and previous changes to how Total Babies and Total Deliveries were calculated means that comparisons between 2019-20 MSDS data and later years should be made with care. The MethodfDelivery measure counting babies has been replaced by the DeliveryMethodBabyGroup measure which counts deliveries, and the smoking at booking and folic acid status measures have been renamed - these changes have been made to better align this annual publication with the Maternity Services Monthly Statistics publication. Information on how all measures are constructed can be found in the HES Metadata and MSDS Metadata files provided below. In this publication we have also included an interactive Power BI dashboard to enable users to explore key NHS Maternity Statistics measures. The purpose of this publication is to inform and support strategic and policy-led processes for the benefit of patient care. This report will also be of interest to researchers, journalists and members of the public interested in NHS hospital activity in England. Any feedback on this publication or dashboard can be provided to enquiries@nhsdigital.nhs.uk, under the subject “NHS Maternity Statistics”.

This is a publication on maternity activity in English NHS hospitals. This report examines data relating to delivery and birth episodes in 2023-24, and the booking appointments for these deliveries. This annual publication covers the financial year ending March 2024. Data is included from both the Hospital Episodes Statistics (HES) data warehouse and the Maternity Services Data Set (MSDS). HES contains records of all admissions, appointments and attendances for patients admitted to NHS hospitals in England. The HES data used in this publication are called 'delivery episodes'. The MSDS collects records of each stage of the maternity service care pathway in NHS-funded maternity services, and includes information not recorded in HES. The MSDS is a maturing, national-level dataset. In April 2019, the MSDS transitioned to a new version of the dataset. This version, MSDS v2.0, is an update that introduced a new structure and content - including clinical terminology, in order to meet current clinical practice and incorporate new requirements. It is designed to meet requirements that resulted from the National Maternity Review, which led to the publication of the Better Births report in February 2016. This is the fifth publication of data from MSDS v2.0 and data from 2019-20 onwards is not directly comparable to data from previous years. This publication shows the number of HES delivery episodes during the period, with a number of breakdowns including by method of onset of labour, delivery method and place of delivery. It also shows the number of MSDS deliveries recorded during the period, with a breakdown for the mother's smoking status at the booking appointment by age group. It also provides counts of live born term babies with breakdowns for the general condition of newborns (via Apgar scores), skin-to-skin contact and baby's first feed type - all immediately after birth. There is also data available in a separate file on breastfeeding at 6 to 8 weeks. For the first time information on 'Smoking at Time of Delivery' has been presented using annual data from the MSDS. This includes national data broken down by maternal age, ethnicity and deprivation. From 2025/2026, MSDS will become the official source of 'Smoking at Time of Delivery' information and will replace the historic 'Smoking at Time of Delivery' data which is to become retired. We are currently undergoing dual collection and reporting on a quarterly basis for 2024/25 to help users compare information from the two sources. We are working with data submitters to help reconcile any discrepancies at a local level before any close down activities begin. A link to the dual reporting in the SATOD publication series can be found in the links below. Information on how all measures are constructed can be found in the HES Metadata and MSDS Metadata files provided below. In this publication we have also included an interactive Power BI dashboard to enable users to explore key NHS Maternity Statistics measures. The purpose of this publication is to inform and support strategic and policy-led processes for the benefit of patient care. This report will also be of interest to researchers, journalists and members of the public interested in NHS hospital activity in England. Any feedback on this publication or dashboard can be provided to enquiries@nhsdigital.nhs.uk, under the subject “NHS Maternity Statistics”.

Births that occurred by hospital name. Birth events of 5 or more per hospital location are displayed

This dataset contains counts of live births for California counties based on information entered on birth certificates. Final counts are derived from static data and include out of state births to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all births that occurred during the time period.

The final data tables include both births that occurred in California regardless of the place of residence (by occurrence) and births to California residents (by residence), whereas the provisional data table only includes births that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by parent giving birth's age, parent giving birth's race-ethnicity, and birth place type. See temporal coverage for more information on which strata are available for which years.

California Birth Report totals by Birth Characteristics to inform the public, stakeholders, and researchers.

The DHCS Medi-Cal Birth Statistics tables present the descriptive statistics for California resident births that occurred in a hospital setting, including data on maternal characteristics, delivery methods, and select birth outcomes such as low birthweight and preterm delivery. Tables also include key comorbidities and health behaviors known to influence birth outcomes, such as hypertension, diabetes, substance use, pre-pregnancy weight, and smoking during pregnancy.

DHCS additionally presents birth statistics for women participating in the Medi-Cal Fee-For-Service (FFS) and managed care delivery systems, as well as births financed by private insurance, births financed by other public funding sources, and births among uninsured mothers. Medi-Cal data reflect mothers that were deemed as Medi-Cal certified eligible.

Note: Data for maternal comorbidities including hypertension, diabetes, and substance use have been provisionally omitted among calendar years 2020-2022 for the time being.

BackgroundLengths of hospital stay (LoS) after childbirth that are too long have a number of health, social and economic drawbacks. For this reason, in several high-income countries LoS has been reduced over the past decades and early discharge (ED) is increasingly applied to low-risk mothers and newborns.MethodsWe conducted a population-based study investigating LoS after chilbirth across all 12 maternity centres of Friuli Venezia-Giulia (FVG), North-Eastern Italy, using a database capturing all registered births in the region from 2005 to 2015 (11 years). Adjusting for clinical factors (clinical conditions of the mother and the newborn), socio-demographic bakground and obstetric history with multivariable logistic regression, we ranked facility centres for LoS that were longer than our proposed ED benchmarks (defined as >2 days for spontaneous vaginal deliveries and >3 days for instrumental vaginal deliveries). The reference was hospital A, a national excellence centre for maternal and child health.ResultsThe total number of births examined in our database was 109,550, of which 109,257 occurred in hospitals. During these 11 years, the number of births significantly diminished over time, and the pooled mean LoS for spontaneous vaginal deliveries in the whole FVG was 2.9 days. There was a significantly decreasing trend in the proportion of women remaining admitted more than the respective ED cutoffs for both delivery modes. The percentage of women staying longer that the ED benchmarks varied extensively by facility centre, ranging from 32% to 97% for spontaneous vaginal deliveries and 15% to 64% for instrumental vaginal deliveries. All hospitals but G were by far more likely to surpass the ED cutoff for spontaneous deliveries. As compared with hospital A, the most significant adjusted ORs for LoS overcoming the ED thresholds for spontaneous vaginal deliveries were: 89.38 (78.49–101.78); 26.47 (22.35–31.36); 10.42 (9.49–11.44); 10.30 (9.45–11.21) and 8.40 (7.68–9.19) for centres B, D, I, K and E respectively. By contrast the OR was 0.77 (95%CI: 0.72–0.83) for centre G. Similar mitigated patterns were observed also for instrumental vaginal deliveiries.ConclusionsFor spontaneous vaginal deliveries the mean LoS in the whole FVG was shorter than 3.4 days, the average figure most recently reported for the whole of Italy, but higher than other countries’ with health systems similar to Italy’s. Since our results are controlled for the effect of all other factors, the between-hospital variability we found is likely attributable to the health care provider itself. It can be argued that some maternity centres of FVG may have had ecocomic interest in longer LoS after childbirth, although fear of medico-legal backlashes, internal organizational malfunctions of hospitals and scarce attention of ward staff on performance efficiency shall not be ruled out. It would be therefore important to ensure higher level of coordination between the various maternity services of FVG, which should follow standardized protocols to pursue efficiency of care and allow comparability of health outcomes and costs among them. Improving the performance of FVG and Italian hospitals requires investment in primary care services.

Number and percentage of live births and fetal deaths (stillbirths), by place of birth (hospital or non-hospital), 1991 to most recent year.

Number and percentage of live births, by month of birth, 1991 to most recent year.

This dataset presents the rate of delivery episodes where the mother is aged under 18 years. It is based on pooled data over five years and includes only those births that occurred in NHS hospitals or similar institutions, excluding deliveries at home, in private hospitals, or other non-standard settings. The indicator provides insight into teenage pregnancy trends and supports public health efforts aimed at reducing early motherhood.

Rationale

Reducing the number of births to teenage mothers is a key public health objective, as early motherhood is often associated with poorer health, educational, and economic outcomes for both mother and child. This indicator helps monitor progress in reducing teenage pregnancies and informs targeted interventions.

Numerator

The numerator includes the total number of maternal episodes where the mother is aged between 12 and 17 years, and the episode type is recorded as a delivery (type '2') or other delivery event (type '5'). Deliveries that occurred at a domestic address, in a private hospital, or in another institution are excluded. Data is sourced from the Secondary Uses Service (Inpatient Data Set).

Denominator

The denominator includes the total number of maternal episodes with a valid maternal age, where the episode type is '2' (delivery) or '5' (other delivery event), and the place of delivery is not a domestic address, private hospital, or other institution. Data is also sourced from the Secondary Uses Service (Inpatient Data Set).

Caveats

Deliveries that occur at home or in private hospitals are not included in this dataset. Additionally, sub-national counts of 8 and above are rounded to the nearest 5 for disclosure control. The data is pooled over five years to ensure statistical robustness.

External references

For more information, visit the Public Health England Fingertips Profile.

Localities ExplainedThis dataset contains data based on either the resident locality or registered locality of the patient, a distinction is made between resident locality and registered locality populations:Resident Locality refers to individuals who live within the defined geographic boundaries of the locality. These boundaries are aligned with official administrative areas such as wards and Lower Layer Super Output Areas (LSOAs).Registered Locality refers to individuals who are registered with GP practices that are assigned to a locality based on the Primary Care Network (PCN) they belong to. These assignments are approximate—PCNs are mapped to a locality based on the location of most of their GP surgeries. As a result, locality-registered patients may live outside the locality, sometimes even in different towns or cities.This distinction is important because some health indicators are only available at GP practice level, without information on where patients actually reside. In such cases, data is attributed to the locality based on GP registration, not residential address.

Click here to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.

This dataset contains counts of live births for California as a whole based on information entered on birth certificates. Final counts are derived from static data and include out of state births to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all births that occurred during the time period.

The final data tables include both births that occurred in California regardless of the place of residence (by occurrence) and births to California residents (by residence), whereas the provisional data table only includes births that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by parent giving birth's age, parent giving birth's race-ethnicity, and birth place type. See temporal coverage for more information on which strata are available for which years.

This statistical release makes available the most recent monthly data on NHS-funded maternity services in England, using data submitted to the Maternity Services Data Set (MSDS). This is the latest report from the newest version of the data set, MSDS.v.2, which has been in place since April 2019. The new data set was a significant change which added support for key policy initiatives such as continuity of carer, as well as increased flexibility through the introduction of new clinical coding. This was a major change, so data quality and coverage has initially reduced from the levels seen in earlier publications. We expect the completeness to improve over time as occurred with the previous version of the MSDS, and are looking at ways of supporting improvements. This month three new measures have been included in this publication for the first time: the proportion of women placed under the care of a Family Nurse Partnership, the proportion of women recorded as not smoking during pregnancy as measured at booking and 36 weeks gestation, and the proportion of women with cephalic presentation who went on to have a spontaneous birth. Two measures were new in the publication last month: the proportion of women booking onto maternity services who have a valid London Measure of Unplanned Pregnancy score recorded, and the proportion of women who meet the criteria to be recommended aspirin during pregnancy. Most of these new measures are included in the new 'Pregnancy' grouping. This new data can be found in the Measures file available for download and further information on these new measures can be found in the accompanying Metadata file. The data derived from SNOMED codes is being used in some measures such as those for smoking at booking and birth weight, and others will follow in later publications. SNOMED data is also included in some of the published Clinical Quality Improvement Metrics (CQIMs), where rules have been applied to ensure measure rates are calculated only where data quality is high enough. System suppliers are at different stages of developing their new solution and delivering that to trusts. In some cases, this has limited the aspects of data that could be submitted to NHS Digital. To help Trusts understand to what extent they met the Clinical Negligence Scheme for Trusts (CNST) Data Quality Criteria for Safety Action 2, we previously produced data files during the scheme months which contained information for data providers showing their performance against all MSDS-derived Safety Action 2 criteria. We are reviewing how similar data quality information may be more regularly included in publications in the future. These statistics are classified as experimental and should be used with caution. Experimental statistics are new official statistics undergoing evaluation. More information about experimental statistics can be found on the UK Statistics Authority website. Please note that the percentages presented in this report are based on rounded figures and therefore may not total to 100%.

Care for women around the time they are giving birth is an essential, time critical service that cannot be deferred. As such, it has been provided throughout the COVID-19 pandemic, and maternity staff have not been redeployed to support other services. The way that some elements of this care are provided has changed in response to COVID-19 however, to minimise the risk of infection and to allow services to continue to provide safe care during times when a high number of staff may be off work, for example due to needing to isolate. Guidance issued by the Scottish Government and Royal College of Obstetricians and Gynaecologists to maternity services at the height of the first wave of the pandemic noted that: * It may be necessary for services to temporarily suspend the option for women to deliver at home or in midwife led units, and to concentrate delivery care within obstetric units * Additional restrictions on the use of water births were recommended * Care pathways for women requiring induction of labour should be amended to ensure the early stages of the induction process were delivered on an outpatient basis wherever possible * Services should consider deferring a planned induction of labour or elective caesarean section if a woman was isolating due to having COVID-19, or having been in contact with a case, if it was safe to do so * Services should support low risk women in the early latent phase of labour to remain at home wherever possible * In general, strict restrictions on visitors for patients in hospital were advised, however women giving birth could still be accompanied by their chosen birth partner 'Induction of labour' is when a woman is given a medical intervention to start her labour rather than waiting for labour to start spontaneously. It is offered because there are medical reasons meaning it is considered safer (for the mother or baby) for the baby to be born, or because a woman is past her 'due date'. There are different approaches to inducing labour, for example using medicines, a medical 'balloon' device that sits at the neck of the womb, and/or breaking the woman's waters. This dataset shows information on induction of labour, presented at Scotland and NHS Board level. Scotland level data is also available by age group and deprivation category. The information on induction of labour presented in this dataset is taken from hospital discharge records, specifically records relating to the care of women delivering a singleton live birth (i.e. one baby, not twins or more) at 37-42 weeks gestation (i.e. up to 3 weeks before or after their due date). This data is also available on the COVID-19 Wider Impact Dashboard. Additional data sources relating to this topic area are provided in the Links section of the Metadata below. Further information based on SMR02 data is also available from the annual Births in Scottish Hospitals report. Information on COVID-19, including stay at home advice for people who are self-isolating and their households, can be found on NHS Inform. All publications and supporting material to this topic area can be found in the weekly COVID-19 Statistical Report. The date of the next release can be found on our list of forthcoming publications.

BackgroundHigh-risk pregnancies, such as twin pregnancies, deserve particular attention as mortality is very high in this group. With a view to inform policy and national guidelines development for the Sustainable Development Goals, we reviewed national training materials, guidelines, and policies underpinning the provision of care in relation to twin pregnancies and assessed care provided to twins in 8 Eastern and Southern African countries: Kenya, Malawi, Mozambique, Rwanda, Tanzania, Uganda, Zambia, and Zimbabwe.Methods and findingsWe located policies and guidelines by reviewing national repositories and by contacting experts to systematically map country-level maternal and newborn training materials, guidelines, and policies. We extracted recommendations for care for twins spanning ante-, intra-, and postpartum care that typically should be offered during twin pregnancies and childbirth. We compared care provided for mothers of twins to that provided for mothers of singletons during the ante-, intra-, and postpartum period and computed neonatal mortality rates using the most recent Demographic and Health Surveys (DHS) data for each country. There was a paucity of guidance on care specifically for twin or multiple pregnancies: None of the countries provided clear guidance on additional number of antenatal care visits or specific antenatal content, while 7 of the 8 countries recommended twins to be delivered in a comprehensive emergency obstetric and neonatal care facility. These results were mirrored by DHS results of 73,462 live births (of which 1,360 were twin) indicating that twin pregnancies did not receive more frequent or intensified antenatal care. The percentage of twin deliveries in hospitals varied from 25.3% in Mozambique to 63.0% in Kenya, and women with twin deliveries were between 5 and 27 percentage points more likely to deliver in hospitals compared to women with singleton live births; this difference was significant in 5 of the 8 countries (t test p

The variables contained in the data sets are primarily concerned with perinatal outcomes and maternal health. A number of variables with respect to the social and economic status of the mothers and their families were also included (ie. Occupation, Marital status, Region). While all nine data sets are centered around these common themes and hold many variables in common, each data set has a unique combination of variables. The types of fields are wide-ranging but are primarily concerned with infant birth, maternal health, and socioeconomic status. The clinical records of the Boston Lying-in inpatient and outpatient services, and those of the New England Hospital maternity unit, are housed in the Rare Book Room, Francis A. Countway Library of Medicine, Harvard University, Boston, Massachusetts. While the information found in these records varied somewhat from one hospital to the next, each set of records was consistent throughout the period under review. Four data bases were established, one consisting exclusively of white patients for each of the three clinics and one composed of all black patients from both services of the Boston Lying-in. The four sample populations were constituted in the following ways. The clinical records of the New England Hospital’s maternity clinic exist in continuous series from 1872 to 1900. All births were recorded because there were fewer than 200 deliveries annually. The patient registers of the Boston Lying-in inpatient service span the years 1886-1900, with a gap in 1893 and 1894. A random sample of 200 cases was chosen for each year. The same procedure was followed at the outpatient clinic, whose case files extend from 1884 to 1900, excepting those years in which all were recorded because fewer births occurred, and a short period when all cases were noted even though they totaled more than 200. Because the number of black patients was small, and because the birth weight experience of blacks was distinctive in some important respects, a fourth file was created consisting of all blacks in the Lying-in inpatient and outpatient records. The preliminary data bases consisted of 3480, 2503, 3654, and 373 cases, respectively. The birth weight means in the Lying-in inpatient sample are accurate to 79 grams, and those of the outpatient clinic sample to 65 grams, at the 95 percent confidence level.

This dataset reports the crude rate of emergency hospital admissions for asthma among children and young people aged under 19. It provides a measure of the burden of acute asthma episodes requiring urgent medical care and serves as an important indicator of respiratory health and healthcare access for this age group.

Rationale Reducing hospital admissions caused by asthma in children and young people is a key public health objective. High admission rates may reflect poor asthma control, environmental triggers, or gaps in primary care and early intervention. Monitoring this indicator supports efforts to improve asthma management and reduce preventable hospitalisations.

Numerator The numerator is the number of emergency hospital admissions for individuals aged under 19 with a primary diagnosis of asthma, identified using ICD-10 codes J45 (Asthma) and J46 (Status asthmaticus). Data are sourced from the Secondary Uses Service (SUS).

Denominator The denominator is the total population of children and young people aged under 19, based on 2021 Census data.

Caveats The data reflect episodes of admission rather than individual patients, meaning multiple admissions by the same person are counted separately. Hospital admission rates may also be influenced by local variations in referral and admission practices, as well as differences in asthma prevalence. NHS England has identified a data quality issue, though further detail is not specified in this summary.

External References Fingertips Public Health Profiles – Asthma Admissions (Under 19)

Localities ExplainedThis dataset contains data based on either the resident locality or registered locality of the patient, a distinction is made between resident locality and registered locality populations:Resident Locality refers to individuals who live within the defined geographic boundaries of the locality. These boundaries are aligned with official administrative areas such as wards and Lower Layer Super Output Areas (LSOAs).Registered Locality refers to individuals who are registered with GP practices that are assigned to a locality based on the Primary Care Network (PCN) they belong to. These assignments are approximate—PCNs are mapped to a locality based on the location of most of their GP surgeries. As a result, locality-registered patients may live outside the locality, sometimes even in different towns or cities.This distinction is important because some health indicators are only available at GP practice level, without information on where patients actually reside. In such cases, data is attributed to the locality based on GP registration, not residential address.

Click here to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.

The 1997 the Kyrgyz Republic Demographic and Health Survey (KRDHS) is a nationally representative survey of 3,848 women age 15-49. Fieldwork was conducted from August to November 1997. The KRDHS was sponsored by the Ministry of Health (MOH), and was funded by the United States Agency for International Development. The Research Institute of Obstetrics and Pediatrics implemented the survey with technical assistance from the Demographic and Health Surveys (DHS) program. The purpose of the KRDHS was to provide data to the MOH on factors which determine the health status of women and children such as fertility, contraception, induced abortion, maternal care, infant mortality, nutritional status, and anemia. Some statistics presented in this report are currently available to the MOH from other sources. For example, the MOH collects and regularly publishes information on fertility, contraception, induced abortion and infant mortality. However, the survey presents information on these indices in a manner which is not currently available, i.e., by population subgroups such as those defined by age, marital duration, education, and ethnicity. Additionally, the survey provides statistics on some issues not previously available in the Kyrgyz Republic: for example, breastfeeding practices and anemia status of women and children. When considered together, existing MOH data and the KRDHS data provide a more complete picture of the health conditions in the Kyrgyz Republic than was previously available. A secondary objective of the survey was to enhance the capabilities of institutions in the Kyrgyz Republic to collect, process, and analyze population and health data. MAIN FINDINGS FERTILITY Fertility Rates. Survey results indicate a total fertility rate (TFR) for all of the Kyrgyz Republic of 3.4 children per woman. Fertility levels differ for different population groups. The TFR for women living in urban areas (2.3 children per woman) is substantially lower than for women living in rural areas (3.9). The TFR for Kyrgyz women (3.6 children per woman) is higher than for women of Russian ethnicity (1.5) but lower than Uzbek women (4.2). Among the regions of the Kyrgyz Republic, the TFR is lowest in Bishkek City (1.7 children per woman), and the highest in the East Region (4.3), and intermediate in the North and South Regions (3.1 and3.9, respectively). Time Trends. The KRDHS data show that fertility has declined in the Kyrgyz Republic in recent years. The decline in fertility from 5-9 to 0-4 years prior to the survey increases with age, from an 8 percent decline among 20-24 year olds to a 38 percent decline among 35-39 year olds. The declining trend in fertility can be seen by comparing the completed family size of women near the end of their childbearing years with the current TFR. Completed family size among women 40-49 is 4.6 children which is more than one child greater than the current TFR (3.4). Birth Intervals. Overall, 30 percent of births in the Kyrgyz Republic take place within 24 months of the previous birth. The median birth interval is 31.9 months. Age at Onset of Childbearing. The median age at which women in the Kyrgyz Republic begin childbearing has been holding steady over the past two decades at approximately 21.6 years. Most women have their first birth while in their early twenties, although about 20 percent of women give birth before age 20. Nearly half of married women in the Kyrgyz Republic (45 percent) do not want to have more children. Additional one-quarter of women (26 percent) want to delay their next birth by at least two years. These are the women who are potentially in need of some method of family planning. FAMILY PLANNING Ever Use. Among currently married women, 83 percent report having used a method of contraception at some time. The women most likely to have ever used a method of contraception are those age 30-44 (among both currently married and all women). Current Use. Overall, among currently married women, 60 percent report that they are currently using a contraceptive method. About half (49 percent) are using a modern method of contraception and another 11 percent are using a traditional method. The IUD is by far the most commonly used method; 38 percent of currently married women are using the IUD. Other modern methods of contraception account for only a small amount of use among currently married women: pills (2 percent), condoms (6 percent), and injectables and female sterilization (1 and 2 percent, respectively). Thus, the practice of family planning in the Kyrgyz Republic places high reliance on a single method, the IUD. Source of Methods. The vast majority of women obtain their contraceptives through the public sector (97 percent): 35 percent from a government hospital, and 36 percent from a women counseling center. The source of supply of the method depends on the method being used. For example, most women using IUDs obtain them at women counseling centers (42 percent) or hospitals (39 percent). Government pharmacies supply 46 percent of pill users and 75 percent of condom users. Pill users also obtain supplies from women counseling centers or (33 percent). Fertility Preferences. A majority of women in the Kyrgyz Republic (45 percent) indicated that they desire no more children. By age 25-29, 20 percent want no more children, and by age 30-34, nearly half (46 percent) want no more children. Thus, many women come to the preference to stop childbearing at relatively young ages-when they have 20 or more potential years of childbearing ahead of them. For some of these women, the most appropriate method of contraception may be a long-acting method such as female sterilization. However, there is a deficiency of use of this method in the Kyrgyz Republic. In the interests of providing a broad range of safe and effective methods, information about and access to sterilization should be increased so that individual women can make informed decisions about using this method. INDUCED ABORTION Abortion Rates. From the KRDHS data, the total abortion rate (TAR)-the number of abortions a woman will have in her lifetime based on the currently prevailing abortion rates-was calculated. For the Kyrgyz Republic, the TAR for the period from mid-1994 to mid-1997 is 1.6 abortions per woman. The TAR for the Kyrgyz Republic is lower than recent estimates of the TAR for other areas of the former Soviet Union such as Kazakhstan (1.8), and Yekaterinburg and Perm in Russia (2.3 and 2.8, respectively), but higher than for Uzbekistan (0.7). The TAR is higher in urban areas (2.1 abortions per woman) than in rural areas (1.3). The TAR in Bishkek City is 2.0 which is two times higher than in other regions of the Kyrgyz Republic. Additionally the TAR is substantially lower among ethnic Kyrgyz women (1.3) than among women of Uzbek and Russian ethnicities (1.9 and 2.2 percent, respectively). INFANT MORTALITY In the KRDHS, infant mortality data were collected based on the international definition of a live birth which, irrespective of the duration of pregnancy, is a birth that breathes or shows any sign of life (United Nations, 1992). Mortality Rates. For the five-year period before the survey (i.e., approximately mid-1992 to mid1997), infant mortality in the Kyrgyz Republic is estimated at 61 infant deaths per 1,000 births. The estimates of neonatal and postneonatal mortality are 32 and 30 per 1,000. The MOH publishes infant mortality rates annually but the definition of a live birth used by the MOH differs from that used in the survey. As is the case in most of the republics of the former Soviet Union, a pregnancy that terminates at less than 28 weeks of gestation is considered premature and is classified as a late miscarriage even if signs of life are present at the time of delivery. Thus, some events classified as late miscarriages in the MOH system would be classified as live births and infant deaths according to the definitions used in the KRDHS. Infant mortality rates based on the MOH data for the years 1983 through 1996 show a persistent declining trend throughout the period, starting at about 40 per 1,000 in the early 1980s and declining to 26 per 1,000 in 1996. This time trend is similar to that displayed by the rates estimated from the KRDHS. Thus, the estimates from both the KRDHS and the Ministry document a substantial decline in infant mortality; 25 percent over the period from 1982-87 to 1992-97 according to the KRDHS and 28 percent over the period from 1983-87 to 1993-96 according to the MOH estimates. This is strong evidence of improvements in infant survivorship in recent years in the Kyrgyz Republic. It should be noted that the rates from the survey are much higher than the MOH rates. For example, the KRDHS estimate of 61 per 1,000 for the period 1992-97 is twice the MOH estimate of 29 per 1,000 for 1993-96. Certainly, one factor leading to this difference are the differences in the definitions of a live birth and infant death in the KRDHS survey and in the MOH protocols. A thorough assessment of the difference between the two estimates would need to take into consideration the sampling variability of the survey's estimate. However, given the magnitude of the difference, it is likely that it arises from a combination of definitional and methodological differences between the survey and MOH registration system. MATERNAL AND CHILD HEALTH The Kyrgyz Republic has a well-developed health system with an extensive infrastructure of facilities that provide maternal care services. This system includes special delivery hospitals, the obstetrics and gynecology departments of general hospitals, women counseling centers, and doctor's assistant/midwife posts (FAPs). There is an extensive network of FAPs throughout the rural areas. Delivery. Virtually all births in the Kyrgyz Republic (96 percent) are delivered at health facilities: 95 percent in delivery hospitals and another 1 percent in either general hospitals

Objective(s): The 2024 Pediatric Sepsis Data Challenge provides an opportunity to address the lack of appropriate mortality prediction models for LMICs. For this challenge, we are asking participants to develop a working, open-source algorithm to predict in-hospital mortality and length of stay using only the provided synthetic dataset. The original data used to generate the real-world data (RWD) informed synthetic training set available to participants was obtained from a prospective, multisite, observational cohort study of children with suspected sepsis aged 6 months to 60 months at the time of admission to hospitals in Uganda. For this challenge, we have created a RWD-informed synthetically generated training data set to reduce the risk of re-identification in this highly vulnerable population. The synthetic training set was generated from a random subset of the original data (full dataset A) of 2686 records (70% of the total dataset - training dataset B). All challenge solutions will be evaluated against the remaining 1235 records (30% of the total dataset - test dataset C). Data Description: Report describing the comparison of univariate and bivariate distributions between the Synthetic Dataset and Test Dataset C. Additionally, a report showing the maximum mean discrepancy (MMD) and Kullback–Leibler (KL) divergence statistics. Data dictionary for the synthetic training dataset containing 148 variables. NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days. Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at sepsiscolab@bcchr.ca or visit our website.

This dataset presents the crude rate of emergency hospital admissions for epilepsy among children and young people aged under 19. It provides insight into the burden of acute epileptic episodes requiring urgent care and serves as a key indicator of neurological health and service provision for this age group.

Rationale Reducing hospital admissions for epilepsy in children and young people is a public health priority. High admission rates may reflect challenges in managing epilepsy in community settings, medication adherence, or access to specialist care. Monitoring this indicator supports efforts to improve epilepsy management and reduce preventable admissions.

Numerator The numerator is the number of emergency hospital admissions for individuals aged under 19 with a primary diagnosis of epilepsy, identified using ICD-10 codes G40 (Epilepsy) and G41 (Status epilepticus). Data are sourced from NHS England’s Secondary Uses Service (SUS).

Denominator The denominator is the total resident population aged under 19, based on 2021 Census data.

Caveats No specific caveats were noted for this dataset. However, as with all hospital admission indicators, local variations in clinical coding, referral practices, and healthcare access may influence the results.

External References Fingertips Public Health Profiles – Epilepsy Admissions (Under 19)

Click here to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.

Hospital Episode Statistics (HES) is a database containing details of all admissions, A and E attendances and outpatient appointments at NHS hospitals in England. Adult Critical Care (ACC) is a subset of APC data. An Intensive Care Unit (ICU) or High Dependency Unit (HDU) ward in a hospital, known as a critical care unit, provides support, monitoring and treatment for critically ill patients requiring constant support and monitoring to maintain function in at least one organ, and often in multiple organs. Medical equipment is used to take the place of patients’ organs during their recovery. Some critical care units are attached to condition-specific treatment units, such as heart, kidney, liver, breathing, circulation or nervous disorders. Others specialise in neonatal care (babies), paediatric care (children) or patients with severe injury or trauma. Initially this data is collected during a patient's time at hospital as part of the Commissioning Data Set (CDS). This is submitted to NHS Digital for processing and is returned to healthcare providers as the Secondary Uses Service (SUS) data set and includes information relating to payment for activity undertaken. It allows hospitals to be paid for the care they deliver. This same data can also be processed and used for non-clinical purposes, such as research and planning health services. Because these uses are not to do with direct patient care, they are called 'secondary uses'. This is the HES data set. HES data covers all NHS Clinical Commissioning Groups (CCGs) in England, including: private patients treated in NHS hospitals patients resident outside of England care delivered by treatment centres (including those in the independent sector) funded by the NHS Each HES record contains a wide range of information about an individual patient admitted to an NHS hospital, including: clinical information about diagnoses and operations patient information, such as age group, gender and ethnicity administrative information, such as dates and methods of admission and discharge geographical information such as where patients are treated and the area where they live We apply a strict statistical disclosure control in accordance with the NHS Digital protocol, to all published HES data. This suppresses small numbers to stop people identifying themselves and others, to ensure that patient confidentiality is maintained. https://digital.nhs.uk/data-and-information/publications/statistical/hospital-admitted-patient-care-activity