Emergency medical services (EMS) workforce demographics in the United States do not reflect the diversity of the population served. Despite some efforts by professional organizations to create a more representative workforce, little has changed in the last decade. This scoping review aims to summarize existing literature on the demographic composition, recruitment, retention, and workplace experience of underrepresented groups within EMS. Peer-reviewed studies were obtained from a search of PubMed, CINAHL, Web of Science, ProQuest Thesis and Dissertations, and non-peer-reviewed (“gray”) literature from 1960 to present. Abstracts and included full-text articles were screened by two independent reviewers trained on inclusion/exclusion criteria. Studies were included if they pertained to the demographics, training, hiring, retention, promotion, compensation, or workplace experience of underrepresented groups in United States EMS by race, ethnicity, sexual orientation, or gender. Studies of non-EMS fire department activities were excluded. Disputes were resolved by two authors. A single reviewer screened the gray literature. Data extraction was performed using a standardized electronic form. Results were summarized qualitatively. We identified 87 relevant full-text articles from the peer-reviewed literature and 250 items of gray literature. Primary themes emerging from peer-reviewed literature included workplace experience (n = 48), demographics (n = 12), workforce entry and exit (n = 8), education and testing (n = 7), compensation and benefits (n = 5), and leadership, mentorship, and promotion (n = 4). Most articles focused on sex/gender comparisons (65/87, 75%), followed by race/ethnicity comparisons (42/87, 48%). Few articles examined sexual orientation (3/87, 3%). One study focused on telecommunicators and three included EMS physicians. Most studies (n = 60, 69%) were published in the last decade. In the gray literature, media articles (216/250, 86%) demonstrated significant industry discourse surrounding these primary themes. Existing EMS workforce research demonstrates continued underrepresentation of women and nonwhite personnel. Additionally, these studies raise concerns for pervasive negative workplace experiences including sexual harassment and factors that negatively affect recruitment and retention, including bias in candidate testing, a gender pay gap, and unequal promotion opportunities. Additional research is needed to elucidate recruitment and retention program efficacy, the demographic composition of EMS leadership, and the prevalence of racial harassment and discrimination in this workforce.

The National Ambulatory Medical Care Surveys (NAMCS) supply data on ambulatory medical care provided in physicians' offices. The 2003 survey contains information from 28,738 patient visits to 1,215 physicians' offices. Data are available on the patient's smoking habits, reason for the visit, expected source of payment, the physician's diagnosis, and the kinds of diagnostic and therapeutic services rendered. Other variables cover drugs/medications ordered, administered, or provided during office visits, with information on medication code, generic name and code, brand name, entry status, prescription status, federal controlled substance status, composition status, and related ingredient codes. Information is also included on the physician's specialization and geographic location. Demographic information on patients, such as age, sex, race, and ethnicity, was also collected.

Online Doctor Consultation Market Outlook

According to our latest research, the global Online Doctor Consultation Market size reached USD 14.8 billion in 2024, reflecting a robust expansion driven by the increasing adoption of digital healthcare services. The market is projected to grow at a CAGR of 17.2% from 2025 to 2033, with the total market value expected to reach USD 50.7 billion by 2033. This significant growth is primarily attributed to the rising demand for convenient, accessible, and cost-effective healthcare solutions, as well as the ongoing integration of advanced technologies such as AI and telemedicine platforms into mainstream medical practices.

The surge in market growth is being propelled by several key factors, most notably the global shift towards digitalization in healthcare. The COVID-19 pandemic acted as a catalyst, accelerating the adoption of telehealth and online doctor consultation services as patients and providers sought to minimize physical interactions. This shift has persisted beyond the pandemic, with patients increasingly valuing the convenience and safety of remote consultations. Moreover, rapid advancements in mobile technology and widespread internet penetration have made online doctor consultations more accessible, even in remote and underserved regions. The integration of artificial intelligence and machine learning for patient triage, symptom checking, and personalized healthcare recommendations further enhances the efficiency and reliability of these services, contributing to market expansion.

Another critical growth driver for the online doctor consultation market is the growing prevalence of chronic diseases and the increasing need for continuous medical monitoring. Chronic conditions such as diabetes, hypertension, and cardiovascular diseases require regular follow-ups and timely interventions, which online consultation platforms are uniquely positioned to provide. These platforms facilitate seamless communication between patients and healthcare providers, enabling timely adjustments to treatment plans and medication. Additionally, the availability of specialist consultations across various domains, including pediatrics, psychiatry, dermatology, and cardiology, has broadened the appeal of online doctor consultations among diverse patient demographics. The adoption of electronic health records and interoperability standards further streamlines the consultation process, enhancing the overall patient experience.

The online doctor consultation market is also benefiting from favorable regulatory environments and supportive government initiatives in several regions. Many countries have introduced policies to reimburse telemedicine services and have relaxed regulations around remote prescribing and cross-border consultations. These regulatory changes have significantly lowered barriers to entry for both patients and providers. Furthermore, the proliferation of health insurance plans that cover telehealth services has encouraged more individuals to utilize online consultations. The increasing investment by both public and private sectors in telemedicine infrastructure, coupled with strategic partnerships between technology companies and healthcare providers, is expected to sustain the market's upward trajectory in the coming years.

From a regional perspective, North America continues to dominate the online doctor consultation market, accounting for the largest share in 2024, followed closely by Europe and the Asia Pacific region. The high adoption rates in North America can be attributed to advanced healthcare infrastructure, high internet penetration, and a favorable regulatory landscape. Europe is witnessing rapid growth due to increased awareness and government support for digital health initiatives. Meanwhile, the Asia Pacific region is emerging as a lucrative market, driven by large populations, rising smartphone usage, and growing investments in healthcare technology. Latin America and the Middle East & Africa are also experiencing steady growth, albeit at a slower pace, as they gradually overcome infrastructural and regulatory challenges.

Profile of psychiatric symptoms among people with schizophrenia and attending the follow-up service at Jimma University Medical Center, psychiatric clinic (n = 351).

Profile of quality of life among people with schizophrenia and attending the follow-up service at Jimma University Medical Center, psychiatric clinic (n = 351).

Clinical Trials Support Services Market Outlook

According to our latest research, the global Clinical Trials Support Services market size reached USD 24.6 billion in 2024, reflecting the sector’s robust expansion and vital role in healthcare innovation. The market is projected to grow at a CAGR of 7.8% from 2025 to 2033, with the total market value anticipated to reach USD 48.7 billion by 2033. This impressive growth trajectory is primarily driven by the increasing volume and complexity of clinical trials, rapid technological advancements, and the rising outsourcing of clinical development activities by pharmaceutical, biotechnology, and medical device companies.

One of the most significant growth factors fueling the Clinical Trials Support Services market is the accelerating rate of drug and medical device development worldwide. The global pharmaceutical pipeline is expanding rapidly, with a notable increase in the number of compounds entering various phases of clinical evaluation. This surge is further propelled by the urgent need for innovative therapies to address chronic diseases, rare disorders, and emerging health threats. As regulatory requirements become more stringent and the demand for faster time-to-market intensifies, sponsors are increasingly relying on specialized support services to navigate the intricacies of trial design, regulatory compliance, patient recruitment, and data management. These services not only ensure adherence to global standards but also help optimize resource allocation and reduce overall development timelines, making them indispensable in today’s competitive landscape.

Another key driver is the growing trend toward the globalization of clinical trials. Sponsors are expanding their research footprints into diverse geographies to access broader patient populations, enhance recruitment rates, and generate more comprehensive efficacy and safety data. This globalization necessitates a robust infrastructure for site management, logistics, and regulatory consulting that can adapt to regional variations in healthcare systems, patient demographics, and regulatory frameworks. The increasing complexity of multi-regional trials has created a strong demand for integrated support services capable of managing cross-border operations, ensuring data integrity, and maintaining regulatory compliance across multiple jurisdictions. This trend is further amplified by advancements in digital health technologies, such as electronic data capture and remote monitoring, which are streamlining trial processes and enabling real-time decision-making.

The rise of precision medicine, decentralized clinical trials, and patient-centric approaches is also shaping the future of the Clinical Trials Support Services market. Sponsors are embracing innovative trial designs and leveraging artificial intelligence, machine learning, and big data analytics to enhance patient recruitment, improve protocol adherence, and generate actionable insights from complex datasets. These technological advancements are driving demand for specialized data management, laboratory, and logistics services that can support adaptive trial models, virtual site visits, and remote patient monitoring. As the industry continues to evolve, service providers with advanced capabilities in digital health, real-world evidence generation, and regulatory strategy will be well-positioned to capture new growth opportunities.

From a regional perspective, North America continues to dominate the Clinical Trials Support Services market, accounting for the largest share in 2024, followed closely by Europe and the Asia Pacific region. The United States, in particular, remains at the forefront due to its well-established healthcare infrastructure, strong regulatory environment, and concentration of leading pharmaceutical and biotechnology companies. However, Asia Pacific is witnessing the fastest growth, driven by increasing investments in healthcare infrastructure, rising patient populations, and favorable government initiatives to attract clinical research. Europe maintains a steady growth trajectory, supported by robust regulatory frameworks and an expanding ecosystem of contract research organizations (CROs). Latin America and the Middle East & Africa are also emerging as attractive destinations for clinical trials, supported by improving regulatory environments and growing healthcare investments.

Abstract

The IDHS is part of the worldwide Demographic and Health Surveys program, which is designed to collect data on fertility, family planning, and maternal and child health.

The main objective of 2007 IDHS was to provide detailed information on population, family planning, and health for policymakers and program managers. The 2007 IDHS was conducted in all 33 provinces in Indonesia. The survey collected information on respondents’ socioeconomic background, fertility levels, marriage and sexual activity, fertility preferences, knowledge and use of family planning methods, breastfeeding practices, childhood and adult mortality including maternal mortality, maternal and child health, and awareness and behavior regarding HIV/AIDS and other sexually-transmitted infections.

The 2007 IDHS was specifically designed to meet the following objectives: - Provide data concerning fertility, family planning, maternal and child health, maternal mortality, and awareness of AIDS/STIs to program managers, policymakers, and researchers to help them evaluate and improve existing programs; - Measure trends in fertility and contraceptive prevalence rates, analyze factors that affect such changes, such as marital status and patterns, residence, education, breastfeeding habits, and knowledge, use, and availability of contraception.; - Evaluate achievement of goals previously set by the national health programs, with special focus on maternal and child health; - Assess men’s participation and utilization of health services, as well as of their families; - Assist in creating an international database that allows cross-country comparisons that can be used by the program managers, policymakers, and researchers in the area of family planning, fertility, and health in general.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men age 15-54

Kind of data

Sample survey data

Sampling procedure

Administratively, Indonesia is divided into 33 provinces. Each province is subdivided into districts (regency in areas mostly rural and municipality in urban areas). Districts are subdivided into subdistricts and each subdistrict is divided into villages. The entire village is classified as urban or rural.

The 2007 IDHS sample is designed to provide estimates with acceptable precision for the following domains: - Indonesia as a whole; - Each of 33 provinces covered in the survey, and - Urban and rural areas of Indonesia

The census blocks (CBs) are the primary sampling unit for the 2007 IDHS. The sample developed for the 2007 National Labor Force Survey (Sakernas) was used as a frame for the selection of the 2007 IDHS sample. Household listing was done in all CBs covered in the 2007 Sakernas. This eliminates the need to conduct a separate household listing for the 2007 IDHS.

A minimum of 40 CBs per province has been imposed in the 2007 IDHS design. Since the sample was designed to provide reliable indicators for each province, the number of CBs in each province was not allocated proportional to the population of the province nor proportional by urban-rural classification. Therefore, a final weighing adjustment procedure was done to obtain estimates for all domains.

The 2007 IDHS sample is selected using a stratified two-stage design consisting of 1,694 CBs. Once the number of households was allocated to each province by urban and rural areas, the number of CBs was calculated based on an average sample take of 25 selected households. All evermarried women age 15-49 and all unmarried persons age 15-24 in these households are eligible for individual interview. Eight households in each CB selected for the women sample were selected for male interview.

Note: See detailed description of sample design in APPENDIX B of the survey report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2007 IDHS used three questionnaires: the Household Questionnaire (HQ), the Ever-Married Women’s Questionnaire (EMWQ) and the Married Men’s Questionnaire (MMQ). In consultation with BKKBN and MOH, BPS made a decision to base the 2007 IDHS survey instruments largely on the questionnaires used in the 2002-03 IDHS to facilitate trend analysis. Input was solicited from other potential data users, and several modifications were made to optimize the draft 2007 IDHS instruments to collect the needs for population and health data. The draft IDHS questionnaires were also compared with the most recent version of the standard questionnaires used in the DHS program and minor modifications incorporated to facilitate international comparison.

The HQ was used to list all the usual members and visitors in the selected households. Basic information collected on each person listed includes: age, sex, education, and relationship to the head of the household. The main purpose of the HQ was to identify women and men who were eligible for the individual interview. Information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, construction materials used for the floor and outer walls of the house, and ownership of various durable goods were also recorded in the HQ. These items reflect the household’s socioeconomic status.

The EMWQ was used to collect information from all ever-married women age 15-49. These women were asked questions on the following topics:: - Background characteristics (marital status, education, media exposure, etc.) - Knowledge and use of family planning methods - Reproductive history and fertility preferences - Antenatal, delivery and postnatal care - Breastfeeding and infant feeding practices - Vaccinations and childhood illnesses - Practices related to the malaria prevention - Marriage and sexual activity - Woman’s work and husband’s background characteristics - Infant’s and children’s feeding practices - Childhood mortality - Awareness and behavior regarding AIDS and other sexually transmitted infections (STIs) - Sibling mortality, including maternal mortality.

The MMQ was administered to all currently married men age 15-54 living in every third household in the IDHS sample. The MMQ collected much of the same information included in the EMWQ, but was shorter because it did not contain questions on reproductive history, maternal and child health, nutrition and maternal mortality. Instead, men were asked about their knowledge and participation in health-care-seeking practices for their children.

Cleaning operations

All completed questionnaires for the IDHS, accompanied by their control forms, were returned to the BPS central office in Jakarta for data processing. This consisted of office editing, coding of openended questions, data entry, verification, and editing computer-identified errors. A team of 42 data entry clerks, data editors and data entry supervisors processed the data. Data entry and editing was carried using a computer package program called CSPro, which was specifically designed to process DHS-type survey data. During the preparation of the data entry programs, a BPS staff spent several weeks at ORC Macro offices in Calverton, Maryland. Data entry and editing activities, which began in September, 2007 were completed in March 2008.

Response rate

In general, the response rates for both the household and individual interviews in the 2007 IDHS are high. A total of 42,341 households were selected in the sample, of which 41,131 were occupied. Of these households, 40,701 were successfully interviewed, yielding a household response rate of 99 percent.

In the interviewed households, 34,227 women were identified for individual interview and of these completed interviews were conducted with 32,895 women, yielding a response rate of 96 percent. In a third of the households, 9,716 eligible men were identified, of which 8,758 were successfully interviewed, yielding a response rate of 90 percent. The lower response rate for men was due to the more frequent and longer absence of men from the household.

Note: See summarized response rates by place of residence in Table 1.2 of the survey report.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2007 Indonesia Demographic and Health Survey (IDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2007 IDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall.

*In this analysis, we used adoption of a “basic” electronic medical record system as the outcome. This definition was taken from Jha and DesRoches, and required a system to include electronic management of demographic information, computerized provider order entry, and lab and imaging results [3], [4]. We began our analysis by conducing bivariate analyses, to determine which of a series of candidate predictors appeared to have a relationship with the outcome variable. We used the following candidate predictors: patient age, gender, race/ethnicity, and source of payment, and, at the hospital level, region, metropolitan vs. non-metropolitan (i.e. urban vs. rural), ownership, and teaching status. Candidate predictors were eliminated from further consideration if bivariate chi-squared testing resulted in a p-value≥0.20. Remaining candidate predictors were fitted to a multivariate logistic regression model, constructed via stepwise backward elimination until all remaining independent covariates had p

Data for this publication are extracted each month as a snapshot in time from the Primary Care Registration database within the NHAIS (National Health Application and Infrastructure Services) system. This release is an accurate snapshot as at 1 January 2021. GP Practice; Primary Care Network (PCN); Sustainability and transformation partnership (STP); Clinical Commissioning Group (CCG) and NHS England Commissioning Region level data are released in single year of age (SYOA) and 5-year age bands, both of which finish at 95+, split by gender. In addition, organisational mapping data is available to derive STP; PCN; CCG and Commissioning Region associated with a GP practice and is updated each month to give relevant organisational mapping. Quarterly publications in January, April, July and October will include Lower Layer Super Output Area (LSOA) populations and a spotlight report. The outbreak of Coronavirus (COVID-19) has led to changes in the work of General Practices and subsequently the data within this publication. Until activity in this healthcare setting stabilises, we urge caution in drawing any conclusions from these data without consideration of the country's circumstances and would recommend that any uses of these data are accompanied by an appropriate caveat. Note: An error was identified on 20/1/2021 in the practice mapping file where practices had duplicate entries for different extract dates. This has now been corrected so that each practice has one extract date. The mapping file has been replaced and is therefore affixed with '_v2' to reflect this. This error does not affect the patients registered at a GP practice data itself.

Abstract

The 2015-16 Armenia Demographic and Health Survey (2015-16 ADHS) is the fourth in a series of nationally representative sample surveys designed to provide information on population and health issues. It is conducted in Armenia under the worldwide Demographic and Health Surveys program. Specifically, the objective of the 2015-16 ADHS is to provide current and reliable information on fertility and abortion levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of young children, childhood mortality, maternal and child health, domestic violence against women, child discipline, awareness and behavior regarding AIDS and other sexually transmitted infections (STIs), and other health-related issues such as smoking, tuberculosis, and anemia. The survey obtained detailed information on these issues from women of reproductive age and, for certain topics, from men as well.

The 2015-16 ADHS results are intended to provide information needed to evaluate existing social programs and to design new strategies to improve the health of and health services for the people of Armenia. Data are presented by region (marz) wherever sample size permits. The information collected in the 2015-16 ADHS will provide updated estimates of basic demographic and health indicators covered in the 2000, 2005, and 2010 surveys.

The long-term objective of the survey includes strengthening the technical capacity of major government institutions, including the NSS. The 2015-16 ADHS also provides comparable data for longterm trend analysis because the 2000, 2005, 2010, and 2015-16 surveys were implemented by the same organization and used similar data collection procedures. It also adds to the international database of demographic and health–related information for research purposes.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15-49

Universe

The survey covered all de jure household members (usual residents), children age 0-4 years, women age 15-49 years and men age 15-49 years resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was designed to produce representative estimates of key indicators at the national level, for Yerevan, and for total urban and total rural areas separately. Many indicators can also be estimated at the regional (marz) level.

The sampling frame used for the 2015-16 ADHS is the Armenia Population and Housing Census, which was conducted in Armenia in 2011 (APHC 2011). The sampling frame is a complete list of enumeration areas (EAs) covering the whole country, a total number of 11,571 EAs, provided by the National Statistical Service (NSS) of Armenia, the implementing agency for the 2015-16 ADHS. This EA frame was created from the census data base by summarizing the households down to EA level. A representative probability sample of 8,749 households was selected for the 2015-16 ADHS sample. The sample was selected in two stages. In the first stage, 313 clusters (192 in urban areas and 121 in rural areas) were selected from a list of EAs in the sampling frame. In the second stage, a complete listing of households was carried out in each selected cluster. Households were then systematically selected for participation in the survey. Appendix A provides additional information on the sample design of the 2015-16 Armenia DHS. Because of the approximately equal sample size in each marz, the sample is not self-weighting at the national level, and weighting factors have been calculated, added to the data file, and applied so that results are representative at the national level.

For further details on sample design, see Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Five questionnaires were used for the 2015-16 ADHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, the Biomarker Questionnaire, and the Fieldworker Questionnaire. These questionnaires, based on The DHS Program’s standard Demographic and Health Survey questionnaires, were adapted to reflect the population and health issues relevant to Armenia. Input was solicited from various stakeholders representing government ministries and agencies, nongovernmental organizations, and international donors. After all questionnaires were finalized in English, they were translated into Armenian. They were pretested in September-October 2015.

Cleaning operations

The processing of the 2015-16 ADHS data began shortly after fieldwork commenced. All completed questionnaires were edited immediately by field editors while still in the field and checked by the supervisors before being dispatched to the data processing center at the NSS central office in Yerevan. These completed questionnaires were edited and entered by 15 data processing personnel specially trained for this task. All data were entered twice for 100 percent verification. Data were entered using the CSPro computer package. The concurrent processing of the data was an advantage because the senior ADHS technical staff were able to advise field teams of problems detected during the data entry. In particular, tables were generated to check various data quality parameters. Moreover, the double entry of data enabled easy comparison and identification of errors and inconsistencies. As a result, specific feedback was given to the teams to improve performance. The data entry and editing phase of the survey was completed in June 2016.

Response rate

A total of 8,749 households were selected in the sample, of which 8,205 were occupied at the time of the fieldwork. The main reason for the difference is that some of the dwelling units that were occupied during the household listing operation were either vacant or the household was away for an extended period at the time of interviewing. The number of occupied households successfully interviewed was 7,893, yielding a household response rate of 96 percent. The household response rate in urban areas (96 percent) was nearly the same as in rural areas (97 percent).

In these households, a total of 6,251 eligible women were identified; interviews were completed with 6,116 of these women, yielding a response rate of 98 percent. In one-half of the households, a total of 2,856 eligible men were identified, and interviews were completed with 2,755 of these men, yielding a response rate of 97 percent. Among men, response rates are slightly lower in urban areas (96 percent) than in rural areas (97 percent), whereas rates for women are the same in urban and in rural areas (98 percent).

The 2015-16 ADHS achieved a slightly higher response rate for households than the 2010 ADHS (NSS 2012). The increase is only notable for urban households (96 percent in 2015-16 compared with 94 percent in 2010). Response rates in all other categories are very close to what they were in 2010.

Sampling error estimates

SAS computer software were used to calculate sampling errors for the 2015-16 ADHS. The programs used the Taylor linearization method of variance estimation for means or proportions and the Jackknife repeated replication method for variance estimation of more complex statistics such as fertility and mortality rates.

A more detailed description of estimates of sampling errors are presented in Appendix B of the survey final report.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months - Nutritional status of children based on the NCHS/CDC/WHO International Reference Population - Vaccinations by background characteristics for children age 18-29 months

See details of the data quality tables in Appendix C of the survey final report.

Abstract

The Indonesia Demographic and Health Survey (IDHS) is part of the worldwide Demographic and Health Surveys program, which is designed to collect data on fertility, family planning, and maternal and child health. The 2002-2003 IDHS follows a sequence of several previous surveys: the 1987 National Indonesia Contraceptive Prevalence Survey (NICPS), the 1991 IDHS, the 1994 IDHS, and the 1997 IDHS. The 2002-2003 IDHS is expanded from the 1997 IDHS by including a collection of information on the participation of currently married men and their wives and children in the health care.

The main objective of the 2002-2003 IDHS is to provide policymakers and program managers in population and health with detailed information on population, family planning, and health. In particular, the 2002-2003 IDHS collected information on the female respondents’ socioeconomic background, fertility levels, marriage and sexual activity, fertility preferences, knowledge and use of family planning methods, breastfeeding practices, childhood and adult mortality including maternal mortality, maternal and child health, and awareness and behavior regarding AIDS and other sexually transmitted infections in Indonesia.

The 2002-2003 IDHS was specifically designed to meet the following objectives: - Provide data concerning fertility, family planning, maternal and child health, maternal mortality, and awareness of AIDS/STIs to program managers, policymakers, and researchers to help them evaluate and improve existing programs - Measure trends in fertility and contraceptive prevalence rates, analyze factors that affect such changes, such as marital status and patterns, residence, education, breastfeeding habits, and knowledge, use, and availability of contraception - Evaluate achievement of goals previously set by the national health programs, with special focus on maternal and child health - Assess men’s participation and utilization of health services, as well as of their families - Assist in creating an international database that allows cross-country comparisons that can be used by the program managers, policymakers, and researchers in the area of family planning, fertility, and health in general.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men age 15-54

Kind of data

Sample survey data

Sampling procedure

SAMPLE DESIGN AND IMPLEMENTATION

Administratively, Indonesia is divided into 30 provinces. Each province is subdivided into districts (regency in areas mostly rural and municipality in urban areas). Districts are subdivided into subdistricts and each subdistrict is divided into villages. The entire village is classified as urban or rural.

The primary objective of the 2002-2003 IDHS is to provide estimates with acceptable precision for the following domains: · Indonesia as a whole; · Each of 26 provinces covered in the survey. The four provinces excluded due to political instability are Nanggroe Aceh Darussalam, Maluku, North Maluku and Papua. These provinces cover 4 percent of the total population. · Urban and rural areas of Indonesia; · Each of the five districts in Central Java and the five districts in East Java covered in the Safe Motherhood Project (SMP), to provide information for the monitoring and evaluation of the project. These districts are: - in Central Java: Cilacap, Rembang, Jepara, Pemalang, and Brebes. - in East Java: Trenggalek, Jombang, Ngawi, Sampang and Pamekasan.

The census blocks (CBs) are the primary sampling unit for the 2002-2003 IDHS. CBs were formed during the preparation of the 2000 Population Census. Each CB includes approximately 80 households. In the master sample frame, the CBs are grouped by province, by regency/municipality within a province, and by subdistricts within a regency/municipality. In rural areas, the CBs in each district are listed by their geographical location. In urban areas, the CBs are distinguished by the urban classification (large, medium and small cities) in each subdistrict.

Note: See detailed description of sample design in APPENDIX B of the survey report.

Mode of data collection

Face-to-face

Research instrument

The 2002-2003 IDHS used three questionnaires: the Household Questionnaire, the Women’s Questionnaire for ever-married women 15-49 years old, and the Men’s Questionnaire for currently married men 15-54 years old. The Household Questionnaire and the Women’s Questionnaire were based on the DHS Model “A” Questionnaire, which is designed for use in countries with high contraceptive prevalence. In consultation with the NFPCB and MOH, BPS modified these questionnaires to reflect relevant issues in family planning and health in Indonesia. Inputs were also solicited from potential data users to optimize the IDHS in meeting the country’s needs for population and health data. The questionnaires were translated from English into the national language, Bahasa Indonesia.

The Household Questionnaire was used to list all the usual members and visitors in the selected households. Basic information collected for each person listed includes the following: age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. In addition, the Household Questionnaire also identifies unmarried women and men age 15-24 who are eligible for the individual interview in the Indonesia Young Adult Reproductive Health Survey (IYARHS). Information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, construction materials used for the floor and outer walls of the house, and ownership of various durable goods were also recorded in the Household Questionnaire. These items reflect the household’s socioeconomic status.

The Women’s Questionnaire was used to collect information from all ever-married women age 15-49. These women were asked questions on the following topics: • Background characteristics, such as age, marital status, education, and media exposure • Knowledge and use of family planning methods • Fertility preferences • Antenatal, delivery, and postnatal care • Breastfeeding and infant feeding practices • Vaccinations and childhood illnesses • Marriage and sexual activity • Woman’s work and husband’s background characteristics • Childhood mortality • Awareness and behavior regarding AIDS and other sexually transmitted infections (STIs) • Sibling mortality, including maternal mortality.

The Men’s Questionnaire was administered to all currently married men age 15-54 in every third household in the IDHS sample. The Men’s Questionnaire collected much of the same information included in the Women’s Questionnaire, but was shorter because it did not contain questions on reproductive history, maternal and child health, nutrition, and maternal mortality. Instead, men were asked about their knowledge and participation in the health-seeking practices for their children.

Cleaning operations

All completed questionnaires for IDHS, accompanied by their control forms, were returned to the BPS central office in Jakarta for data processing. This process consisted of office editing, coding of open-ended questions, data entry, verification, and editing computer-identified errors. A team of about 40 data entry clerks, data editors, and two data entry supervisors processed the data. Data entry and editing started on November 4, 2002 using a computer package program called CSPro, which was specifically designed to process DHS-type survey data. To prepare the data entry programs, two BPS staff spent three weeks in ORC Macro offices in Calverton, Maryland in April 2002.

Response rate

A total of 34,738 households were selected for the survey, of which 33,419 were found. Of the encountered households, 33,088 (99 percent) were successfully interviewed. In these households, 29,996 ever-married women 15-49 were identified, and complete interviews were obtained from 29,483 of them (98 percent). From the households selected for interviews with men, 8,740 currently married men 15-54 were identified, and complete interviews were obtained from 8,310 men, or 95 percent of all eligible men. The generally high response rates for both household and individual interviews (for eligible women and men) were due mainly to the strict enforcement of the rule to revisit the originally selected household if no one was at home initially. No substitution for the originally selected households was allowed. Interviewers were instructed to make at least three visits in an effort to contact the household, eligible women, and eligible men.

Note: See summarized response rates by place of residence in Table 1.2 of the survey report.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2002-2003 Indonesia Demographic and Health Survey (IDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents

Socio-demographic characteristics of maternal and child health service providers in Wolaita Zone public hospital, Southern Ethiopia, 2023.

Students from the Chinese ethnic group had the highest entry rate into higher education in every year from 2006 to 2024.

Administrative information about individuals in Wales that use NHS services; such as address and practice registration history. It replaced the NHS Wales Administrative Register (NHSAR) in 2009.

Data drawn from GP practices via Exeter System.

This dataset provides linkage from anonymous individual to anonymous residences, thus enable to group households of individuals.

The single views are now provisioned to new projects and described here, the metadata for the old three-view WDSD version can be found in a separate legacy metadata entry.

Health and medical insurance companies experienced significant fluctuations in performance in recent years. The onset of COVID-19 led to a substantial increase in healthcare spending in 2020 and 2021, as demand for medical services surged. Consequently, investment in health insurance witnessed a dramatic rise, contributing to robust revenue growth during these years. However, with inflation peaking in 2022, consumer purchasing power diminished, causing households to reduce their spending on health insurance. This factor, coupled with a slowdown in health expenditure growth as the immediate pandemic effects waned, resulted in meager revenue growth for insurers in 2022, a notable deceleration compared to prior years. The industry performed better in 2023 as low inflation enabled consumers to more easily afford health insurance, with revenue then rising significantly in 2024 due to soaring investment income. More broadly, providers have been influenced by slowing healthcare inflation, despite a historically rapid rise in prior decades. For example, from 1970 to 2010, health expenditures skyrocketed, buoyed by substantial innovations. However, recent years have seen this growth plateau. This is attributed to a shift toward less costly innovation, focusing more on pharmaceutical advancements rather than costly healthcare system overhauls. Consequently, providers have faced slower revenue growth. Consolidation has risen as the industry’s largest players have used economies of scale, acquisitions and advertising to take over more of the market. Regardless, internal competition has soared as more providers have entered the industry to capture new revenue streams due to rising short-term health spending and the aging of the US population, constraining profit. Overall, revenue for health and medical insurance companies has swelled at a CAGR of 3.8% over the past five years, reaching $1.5 trillion in 2025. This includes a 2.5% rise in revenue in that year. The industry's landscape is set for further evolution over the next five years. Anticipated steady economic growth, with GDP projected to rise and unemployment to remain low, is likely to bolster health insurance revenue streams, primarily through heightened spending on employer-sponsored and private health plans. However, the potential for economic disruptions, such as the implementation of tariffs, could affect providers’ stability. As the population ages and healthcare demand grows, insurers will seek to tailor their policies to address the needs of an older demographic, necessitating comprehensive services. Overall, revenue for health and medical insurance providers is forecast to expand at a CAGR of 2.7% over the next five years, reaching $1.8 trillion in 2030.

Legacy metadata for the discontinued three-view WDSD version. The views now provisioned to new projects have 'SINGLE' in their title and are found in the main WDSD metadata entry, which is separate to this one.

Administrative information about individuals in Wales that use NHS services; such as address and practice registration history. It replaced the NHS Wales Administrative Register (NHSAR) in 2009.

Data drawn from GP practices via Exeter System.

This dataset provides linkage from anonymous individual to anonymous residences, thus enable to group households of individuals.

Abstract

The 2010 Armenia Demographic and Health Survey (2010 ADHS) is the third in a series of nationally representative sample surveys designed to provide information on population and health issues. It is conducted in Armenia under the worldwide Demographic and Health Surveys program. Specifically, the 2010 ADHS has a primary objective of providing current and reliable information on fertility levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of young children, childhood mortality, maternal and child health, and awareness and behavior regarding AIDS and other sexually transmitted infections (STIs). The survey obtained detailed information on these issues from women of reproductive age and, for certain topics, from men as well.

The 2010 ADHS results are intended to provide information needed to evaluate existing social programs and to design new strategies to improve health of and health services for the people of Armenia. Data are presented by region (marz) wherever sample size permits. The information collected in the 2010 ADHS will provide updated estimates of basic demographic and health indicators covered in the 2000 and 2005 surveys.

The long-term objective of the survey includes strengthening the technical capacity of major government institutions, including the NSS. The 2010 ADHS also provides comparable data for longterm trend analysis in Armenia because the 2000, 2005, and 2010 surveys were implemented by the same organisation and used similar data collection procedures. It also adds to the international database of demographic and health–related information for research purposes.

The 2010 ADHS was conducted by the National Statistical Service (NSS) and the MOH of Armenia from October 5 through December 25, 2010.

Kind of data

Sample survey data

Sampling procedure

The sample was designed to permit detailed analysis-including the estimation of rates of fertility, infant/child mortality, and abortion-at the national level, for Yerevan, and for total urban and total rural areas separately. Many indicators can also be estimated at the regional (marz) level.

A representative probability sample of 7,580 households was selected for the 2010 ADHS sample. The sample was selected in two stages. In the first stage, 308 clusters were selected from a list of enumeration areas in a subsample of a master sample derived from the 2001 Population Census frame. In the second stage, a complete listing of households was carried out in each selected cluster. Households were then systematically selected for participation in the survey.

All women age 15-49 who were either permanent residents of the households in the 2010 ADHS sample or visitors present in the household on the night before the survey were eligible to be interviewed. Interviews were completed with 5,922 women. In addition, in a subsample of one-third of all of the households selected for the survey, all men age 15-49 were eligible to be interviewed if they were either permanent residents or visitors present in the household on the night before the survey. Interviews were completed with 1,584 men.

Appendix A of the Final Report provides additional information on the sample design of the 2010 Armenia DHS.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were used in the ADHS: a Household Questionnaire, a Woman’s Questionnaire, and a Man’s Questionnaire. The Household Questionnaire and the individual questionnaires were based on model survey instruments developed in the MEASURE DHS program and questionnaires used in the previous 2005 ADHS. The model questionnaires were adapted for use by NSS and MOH. Suggestions were also sought from a number of nongovernmental organizations (NGOs). The questionnaires were developed in English and translated into Armenian. They were pretested in July 2010.

The Household Questionnaire was used to list all usual members of and visitors to the selected households and to collect information on the socioeconomic status of the household. The first part of the Household Questionnaire collected for each household member or visitor information on their age, sex, educational attainment, and relationship to the head of household. This information provided basic demographic data for Armenian households. It also was used to identify the women and men who were eligible for an individual interview (i.e., women and men age 15-49). In the second part of the Household Questionnaire, there were questions on housing characteristics (e.g., the flooring material, the source of water, and the type of toilet facilities), on ownership of a variety of consumer goods, and on other aspects of the socioeconomic status of the household. In addition, the Household Questionnaire was used to obtain information on each child’s birth registration, ask questions about child discipline and child labor, and record height and weight measurements of children under age 5.

The Woman’s Questionnaire obtained information from women age 15-49 on the following topics: - Background characteristics - Pregnancy history - Antenatal, delivery, and postnatal care - Knowledge, attitudes, and use of contraception - Reproductive and adult health - Childhood mortality - Health and health care utilization - Vaccinations of children under age 5 - Episodes of diarrhea and respiratory illness of children under age 5 - Breastfeeding and weaning practices - Marriage and recent sexual activity - Fertility preferences - Knowledge of and attitudes toward AIDS and other sexually transmitted diseases - Woman’s work and husband’s background characteristics

The Man’s Questionnaire, administered to men age 15-49, focused on the following topics: - Background characteristics - Health and health care utilization - Marriage and recent sexual activity - Attitudes toward and use of condoms - Knowledge of and attitudes toward AIDS and other sexually transmitted diseases - Attitudes toward women’s status

Cleaning operations

Data Processing

The processing of the ADHS results began shortly after fieldwork commenced. Completed questionnaires were returned regularly from the field to NSS headquarters in Yerevan, where they were entered and edited by data processing personnel who were specially trained for this task. The data processing personnel included a supervisor, a questionnaire administrator (who ensured that the expected number of questionnaires from all clusters was received), several office editors, 12 data entry operators, and a secondary editor. The concurrent processing of the data was an advantage because the senior DHS technical staff were able to advise field teams of problems detected during the data entry. In particular, tables were generated to check various data quality parameters. As a result, specific feedback was given to the teams to improve performance. The data entry and editing phase of the survey was completed in March 2011.

Response rate

A total of 7,580 households were selected in the sample, of which 7,043 were occupied at the time of the fieldwork. The main reason for the difference is that some of the dwelling units that were occupied during the household listing operation were either vacant or the household was away for an extended period at the time of interviewing. The number of occupied households successfully interviewed was 6,700, yielding a household response rate of 95 percent. The household response rate in urban areas (94 percent) was slightly lower than in rural areas (97 percent).

In these households, a total of 6,059 eligible women were identified; interviews were completed with 5,922 of these women, yielding a response rate of 98 percent. In one-third of the households, a total of 1,641 eligible men were identified, and interviews were completed with 1,584 of these men, yielding a response rate of 97 percent. Response rates are slightly lower in urban areas (97 percent for women and 96 percent for men) than in rural areas where rates were 99 and 97 percent, respectively.

Sampling error estimates

Detailed information on sampling errors is provided in Appendix B of the Final Report.

Abstract

The 1993 Ghana Demographic and Health Survey (GDHS) is a nationally representative survey of 4,562 women age 15-49 and 1,302 men age 15-59. The survey is designed to furnish policymakers, planners and program managers with factual, reliable and up-to-date information on fertility, family planning and the status of maternal and child health care in the country. The survey, which was carried out by the Ghana Statistical Service (GSS), marks Ghana's second participation in the worldwide Demographic and Health Surveys (DHS) program.

The principal objective of the 1993 GDHS is to generate reliable and current information on fertility, mortality, contraception and maternal and child health indicators. Such data are necessary for effective policy formulation as well as program design, monitoring and evaluation. The 1993 GDHS is, in large measure, an update to the 1988 GDHS. Together, the two surveys provide comparable information for two points in time, thus allowing assessment of changes and trends in various demographic and health indicators over time.

Long-term objectives of the survey include (i) strengthening the capacity of the Ghana Statistical Service to plan, conduct, process and analyze data from a complex, large-scale survey such as the Demographic and Health Survey, and (ii) contributing to the ever-expanding international database on demographic and health-related variables.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men age 15-59

Kind of data

Sample survey data

Sampling procedure

The 1993 GDHS is a stratified, self-weighting, nationally representative sample of households chosen from 400 Enumeration Areas (EAs). The 1984 Population Census EAs constituted the sampling frame. The frame was first stratified into three ecological zones, namely coastal, forest and savannah, and then into urban and rural EAs. The EAs were selected with probability proportional to the number of households. Households within selected EAs were subsequently listed and a systematic sample of households was selected for the survey. The survey was designed to yield a sample of 5,400 women age 15-49 and a sub-sample of males age 15-59 systematically selected from one-third of the 400 EAs.

Note: See detailed description of sample design in APPENDIX A of the survey report.

Mode of data collection

Face-to-face

Research instrument

Survey instruments used to elicit information for the 1993 GDHS are 1) Household Schedule 2) Women's Questionnaire and 3) Men's Questionnaire.

The questionnaires were structured based on the Demographic and Health Survey Model B Questionnaire designed for countries with low levels of contraceptive use. The final version of the questionnaires evolved out of a series of meetings with personnel of relevant ministries, institutions and organizations engaged in activities relating to fertility and family planning, health and nutrition and rehabilitation of persons with disabilities.

The questionnaires were first developed in English and later translated and printed in five major local languages, namely: Akan, Dagbani, Ewe, Ga, and Hausa. In the selected households, all usual members and visitors were listed in the household schedule. Background information, such as age, sex, relationship to head of household, marital status and level of education, was collected on each listed person. Questions on economic activity, occupation, industry, employment status, number of days worked in the past week and number of hours worked per day was asked of all persons age seven years and over. Those who did not work during the reference period were asked whether or not they actively looked for work.

Information on the health and disability status of all persons was also collected in the household schedule. Migration history was elicited from all persons age 15 years and over, as well as information on the survival status and residence of natural parents of all children less than 15 years in the household.

Data on source of water supply, type of toilet facility, number of sleeping rooms available to the household, material of floor and ownership of specified durable consumer goods were also elicited.

Finally, the household schedule was the instrument used to identify eligible women and men from whom detailed information was collected during the individual interview.

The women's questionnaire was used to collect information on eligible women identified in the household schedule. Eligible women were defined as those age 15-49 years who are usual members of the household and visitors who spent the night before the interview with the household. Questions asked in the questionnaire were on the following topics:

• Background Characteristics
• Reproductive History
• Contraceptive Knowledge and Use
• Pregnancy and Breastfeeding
• Immunization and Health
• Marriage
• Fertility Preferences
• Maternal Mortality
• Husband's Background and Women's Work
• Knowledge of AIDS and Other Sexually Transmitted Diseases (STDs).

All female respondents with at least one live birth since January 1990 and their children born since 1st January 1990 had their height and weight taken.

The men's questionnaire was administered to men in sample households in a third of selected EAs. An eligible man was 15-59 years old who is either a usual household member or a visitor who spent the night preceding the day of interview with the household.

Topics enquired about in the men's questionnaire included the following: - Background Characteristics - Reproductive History - Contraceptive Knowledge and Use - Marriage - Fertility Preferences - Knowledge of AIDS and Other STDs.

Cleaning operations

Questionnaires from the field were sent to the secretariat at the Head Office for checking and office editing. The office editing, which was undertaken by two officers, involved correcting inconsistencies in the questionnaire responses and coding open-ended questions. The questionnaires were then forwarded to the data processing unit for data entry. Data capture and verification were undertaken by four data entry operators. Nearly 20 percent of the questionnaires were verified. This phase of the survey covered four and a half months - that is, from mid-October, 1993 to the end of February, 1994.

After the data entry, three professional staff members performed the secondary editing of questionnaires that were flagged either because entries were inconsistent or values of specific variables were out of range or missing. The secondary editing was completed on 17th March, 1994 and the tables for the preliminary report were generated on 18th March, 1994. The software package used for the data processing was the Integrated System for Survey Analysis (ISSA).

Response rate

A sample of 6,161 households was selected, from which 5,919 households were contacted for interview. Interviews were successfully completed in 5,822 households, indicating a household response rate of 98 percent. About 3 percent of selected households were absent during the interviewing period, and are excluded from the calculations of the response rate.

Even though the sample was designed to yield interviews with nearly 5,400 women age 15-49 only 4,700 women were identified as eligible for the individual interview. Individual interviews were successfully completed for 4,562 eligible women, giving a response rate of 97 percent. Similarly, instead of the expected 1,700 eligible men being identified in the households only 1,354 eligible men were found and 1,302 of these were successfully interviewed, with a response rate of 96 percent.

The principal reason for non-response among eligible women and men was not finding them at home despite repeated visits to the households. However, refusal rates for both eligible women and men were low, 0.3 percent and 0.2 percent, respectively.

Note: See summarized response rates in Table 1.1 of the survey report.

Sampling error estimates

The results from sample surveys are affected by two types of errors, non-sampling error and sampling error. Non-sampling error is due to mistakes made in carrying out field activities, such as failure to locate and interview the correct household, errors in the way the questions are asked, misunderstanding on the part of either the interviewer or the respondent, data entry errors, etc. Although efforts were made during the design and implementation of the 1993 GDHS to minimize this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be measured statistically. The sample of eligible women selected in the 1993 GDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each one would have yielded results that differed somewhat from the actual sample selected. The sampling error is a measure of the variability between all possible samples; although it is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of standard error of a particular statistic (mean, percentage, etc.), which is the square root of the variance of the statistic. The standard error can be used to calculate confidence intervals within which, apart from non-sampling errors, the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that same statistic as measured in 95 percent of all possible samples with the same design (and expected size) will fall within a range

Background The Society for Acute Medicine (SAM) Benchmark Audit (SAMBA) is a national benchmark audit of acute medical care. The aim of SAMBA19 is to describe the severity of illness of acute medical patients presenting to Acute Medicine within UK hospitals, speed of assessment, pathway and progress seven days after admission and to provide a comparison for each participating unit with the national average (or ‘benchmark’). On average >150 hospitals take part in this audit per year. SAMBA19 summer audit measured adherence to some of the standards for acute medical care. Acute Medical Units work 24-hours per day and 365 days a year. They are the single largest point of entry for acute hospital admissions and most patients are at their sickest within the first 24-hours of admission. This dataset includes • Total number of patients assessed by acute medicine across ED, AMU and Ambulatory Care. • Medical and nursing levels • Severity of illness • Timeliness in processes of care • Clinical outcomes 7 days after admission PIONEER geography The West Midlands (WM) has a population of 5.9million & includes a diverse ethnic, socio-economic mix. There is a higher than average % of minority ethnic groups. WM has a large number of elderly residents but is the youngest population in the UK. There are particularly high rates of physical inactivity, obesity, smoking & diabetes. WM has a high prevalence of COPD, reflecting the high rates of smoking and industrial exposure. Each day >100,000 people are treated in hospital, see their GP or are cared for by the NHS. This is the SAMBA dataset from 4 NHS hospitals. EHR University Hospitals Birmingham NHS Foundation Trust (UHB) is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & 100 ITU beds. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”. Scope: These data come from Queen Elizabeth Hospitals Birmingham, Good Hope Hospital, Solihull Hospital and Heartlands Hospital. All admissions in a pre-defined 24-hour period, the severity of illness, patient demographics, co-morbidity, acuity scores, serial, structured data pertaining to care process (timings, staff grades, specialty review, wards) all prescribed & administered treatments (fluids, antibiotics, inotropes, vasopressors, organ support), all outcomes.
Available supplementary data: More extensive data including granular serial physiology, bloods, conditions, interventions, treatments. Ambulance, 111, 999 data, synthetic data. Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services

This is a MD iMAP hosted service. Find more information at http://imap.maryland.gov. The units of geography used for the 2010 Census maps displayed here are the Zip Code Tabulation Area (ZCTA). ZCTAs are statistical geographic areas produced by the Census Bureau by aggregating census blocks to create generalized areas closely resembling the U.S. Postal Service's postal zip codes. The data collected on the short form survey are general demographic characteristics such as age - race - ethnicity - household relationship - housing vacancy and tenure (owner/renter).Feature Service Link:https://mdgeodata.md.gov/imap/rest/services/Demographics/MD_CensusData/FeatureServer ADDITIONAL LICENSE TERMS: The Spatial Data and the information therein (collectively "the Data") is provided "as is" without warranty of any kind either expressed implied or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct indirect incidental consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.