The social environment represents the external conditions under which people engage in social activity within their community. It includes aspects of social opportunity, leisure and recreation, education, access to health services, health status and participation in democratic processes. Fourteen indicators have been used to assess aspects of quality of the social environment.

De-identified survey results from the "Landscape of Family Medicine in India" survey administered to family physicians in India who were members of the Academy of Family Physicians. A respondent-driven sampling approach was used to increase our reach. The survey was administered between November 2020 and March 2021

Canada’s average population to specialist physician ratio has been 1100:1 for over a decade. Low ratios are generally associated with urban areas. The region with the highest ratio is located in north central Newfoundland, a region with relatively few people but even fewer physician resources, including family physicians.

Number and percentage of persons who had a regular family physician.

The objective is to ensure that providers who bill Federal health care programs do not submit claims for services furnished, ordered or prescribed by an excluded individual or entity. The LEIE is updated monthly with all individuals and entities who have been excluded from participation in Federal health care programs. Providers who bill Medicare, Medicaid, or other Federal health care programs must ensure that they know what individuals or entities are excluded and not bill for their services (e.g., a pharmacy should not bill Medicaid for a drug prescribed by an excluded physician nor for drugs dispensed by an excluded pharmacist).

The average number of physicians per 1,000 inhabitants in Colombia was forecast to continuously increase between 2024 and 2029 by in total 0.2 physicians (+8.2 percent). After the seventh consecutive increasing year, the number of physicians is estimated to reach 2.68 physicians and therefore a new peak in 2029. Depicted here is the average number of physicians per one thousand people. Thereby physicians include medical specialists as well as general practitioners. A data point thereby denotes the weighted average across the depicted geographical unit.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

During 1997 close to 80% of Canadians made use of the services of a family physician. For Canada as a whole, and for each province, the majority of the population, close to 58%, visited a family physician more than twice during that time period. Health services utilization patterns, for both individuals and for regions, are influenced by factors like age, gender, self-rated health status, education, and income.

An important aspect of health care is the distance a person has to travel to get medical services. This map shows the average distance that people in each census division have to travel to reach the nearest family physician living in the same province or territory. (A family physician deals with the day-to-day health problems of family members, and is therefore considered to be a "non-specialist"). The pattern shows that people in the continuously-settled parts of Canada rarely have to travel more than 25 kilometres to see family physicians, whereas people in the sparsely settled parts often have to travel much greater distances.

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 2023. GP Practice; Primary Care Network (PCN); Sub Integrated Care Board Locations (SICBL); Integrated Care Board (ICB) 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 PCN; SICBL; ICB 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. 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.

Attendance and clinical information for all general practice interactions: includes patients symptoms, investigations, diagnoses, prescribed medication and referrals to tertiary care.

This dataset covers 83% of the population of Wales and 80% of GP practices in Wales. It is linkable with anonymised fields for individuals and GPs to other datasets, including bespoke project specific cohorts. Each GP practice uses a clinical information system to maintain an electronic health record for each of their patients; capturing the signs, symptoms, test results, diagnoses, prescribed treatment, referrals for specialist treatment and social aspects relating to the patients home environment.

The majority of the data is entered by the clinician during the patient consultation. Test results are electronically transferred from secondary care systems.

There are no standard rules for recording data within primary care clinical information systems. Therefore, each individual clinician can record information in their own way. The majority use Read Code Terminology, however, sometimes this is applied behind the scenes by the clinical system and sometimes local codes are used. Read codes are not as precise as ICD 10 or OPCS codes.

Coding standards have been agreed on for conditions monitored by the QOF (Quality Outcomes Framework) returns. Since the implementation of QOF these conditions have been coded in a more consistent way.

Time coverage varies between each practice.

Distribution of responses from physicians and patients’ family members to question 1.1 and 1.2. Figure S2. Distribution of responses from physicians and patients’ family members to question 1.2 and 2.2. Figure S3. Distribution of responses from physicians to question 1.3. Figure S4. Distribution of responses from physicians and patients’ family members to question 1.4 and 2.4. Figure S5. Distribution of responses from physicians and patients’ family members to question 1.5 and 2.5. Figure S6. Distribution of responses from physicians and patients’ family members to question 1.6 and 2.6. Figure S7. Distribution of responses from physicians and patients’ family members to question 1.7 and 2.7. Figure S8. Distribution of responses from physicians and patients’ family members to question 1.8 and 2.8. Figure S9. Distribution of responses from physicians and patients’ family members to question 1.9 and 2.9. Figure S10. Distribution of responses from physicians and patients’ family members to question 1.10 and 2.10. (ZIP 702 KB)

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 September 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.

Abstract copyright UK Data Service and data collection copyright owner.The National Patient Survey Programme is one of the largest patient survey programmes in the world. It provides an opportunity to monitor experiences of health and provides data to assist with registration of trusts and monitoring on-going compliance. Understanding what people think about the care and treatment they receive is crucial to improving the quality of care being delivered by healthcare organisations. One way of doing this is by asking people who have recently used the health service to tell the Care Quality Commission (CQC) about their experiences. The CQC will use the results from the surveys in the regulation, monitoring and inspection of NHS acute trusts (or, for community mental health service user surveys, providers of mental health services) in England. Data are used in CQC Insight, an intelligence tool which identifies potential changes in quality of care and then supports deciding on the right regulatory response. Survey data will also be used to support CQC inspections. Each survey has a different focus. These include patients' experiences in outpatient and accident and emergency departments in Acute Trusts, and the experiences of people using mental health services in the community. History of the programme The National Patient Survey Programme began in 2002, and was then conducted by the Commission for Health Improvement (CHI), along with the Commission for Healthcare Audit and Inspection (CHAI). Administration of the programme was taken over by the Healthcare Commission in time for the 2004 series. On 1 April 2009, the CQC was formed, which replaced the Healthcare Commission. Further information about the National Patient Survey Programme may be found on the CQC Patient Survey Programme web pages. The Primary Care Trusts: Patient Survey, 2008 focused on people's experiences of primary care services, such as general practitioner (GP) practices and dentistry. It was conducted in every primary care trust (PCT) in England during January-April 2008 using a sample of people registered with a GP. Main Topics: Topics covered include: visits to local health centres/general practitioners in last 12 months; waiting time for appointments; time spent with doctor; other health professionals or pharmacists seen; referrals to hospitals or specialists; trust in doctors; whether patient treated with respect and dignity; medications prescribed; adequacy of information received; dental treatment; blood pressure checks; advice received regarding diet; exercise; smoking cessation; alcohol consumption; whether patient suffers from debilitating condition; patient's age; gender and ethnic group. Simple random sample

The number of physicians in Argentina was forecast to continuously increase between 2024 and 2029 by in total 1.5 thousand physicians (+0.86 percent). According to this forecast, in 2029, the number of physicians will have increased for the sixth consecutive year to 176.63 thousand physicians. Depicted here is the estimated number of physicians in the geographical unit at hand. Thereby physicians include medical specialists as well as general practitioners.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of physicians in countries like Paraguay and Uruguay.

In family households Health Insurance Coverage Statistics for 2022. This is part of a larger dataset covering consumer health insurance coverage rates in Doctor Phillips, Florida by age, education, race, gender, work experience and more.

A point layer of GP Plus Health Care Centres and GP Plus Super Clinics. The Super Clinics are a joint initiative of the Australian and South Australian Governments. GP Plus Health Care Centres and GP Plus Super Clinics: - work closely with general practice and other services to better respond to the health needs of local communities, - complement the services offered by general practice, - help people take control of their own health care, stay healthy and to avoid unnecessary hospitalisation. This is NOT a dataset of General Practitioners.Zipped shapefile - point location for GP Plus clinics

The number of physicians in Ghana was forecast to continuously increase between 2024 and 2029 by in total 2.1 thousand physicians (+26.92 percent). After the tenth consecutive increasing year, the number of physicians is estimated to reach 9.94 thousand physicians and therefore a new peak in 2029. Depicted here is the estimated number of physicians in the geographical unit at hand. Thereby physicians include medical specialists as well as general practitioners.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of physicians in countries like Ivory Coast and Nigeria.

The data collected through the APGAR test aimed to measure family functions and changes in a postmodern context. Over three years, this study has been conducted to 77 individuals, 71 of whom were adults while the remaining 6 were underage people. These participants belong to 37 families from different social strata in the city of Quito-Ecuador, which were selected through convenience and non-probabilistic sampling. The APGAR design used a modification of the work [1], extrapolated to the Ecuadorian context. The data has been collected, cleaned, and unified in a single file in a CSV structured format and without missing values. The participants’ personal information has been concealed to guarantee their identity remains anonymous. Additionally, those who participated in the project have given their consent for the use of their information for academic purposes, which include: scientific journals, presentations, and digital academic repositories. The structured data, within the file, has a distribution in the form of rows and columns. Each row (instance) represents an APGAR test executed on an individual, while the columns represent the different variables (attributes) of the dataset. Each APGAR test has metadata collected during the process. The metadata corresponding to the informative data of the individuals are located in attributes 1 to 7 of the dataset and their description is as follows. • Person_ID: Identifier of each individual who participated in the APGAR test. Discrete quantitative variable. • Year: Data collection year. Discrete quantitative variable. • Family_ID: Unique identifier of each family. Discrete quantitative variable. • Age: Participant age in years. Discrete quantitative variable. • Familiar_Rol: Self-identification of the role played by the individual in the family. Nominal qualitative variable with open categories. Seven different classes were identified: father, mother, son, daughter, nephew, grandmother, and stepfather. • Gender: Self-identification of the individual's gender. Nominal qualitative variable with open categories. Two classes were identified: male and female. • Location: Geographical location of the family home. Nominal qualitative variable with closed categories determined by the official zones that make up the metropolitan district of Quito. Nineteen classes were identified in total. In the Ecuadorian context, a person is of legal age if he has reached an age equal to or greater than 18 years. Therefore, in order to discern these two segments of subpopulations within the family, the design of two different question types for the APGAR tests was required. The Questions (Qi) for adults were: • Q1: I am satisfied with the help I receive from my family when I have a problem or need. • Q2: I am satisfied with the participation that my family gives me and allows me. • Q3: I am satisfied with how my family accepts and supports my desire to undertake new activities. • Q4: I am satisfied with how my family expresses affection and responds to my emotions, such as anger, sadness, love, etc. • Q5: I am satisfied with how we share in my family: a) time to be together, b) spaces in the house, c) money. The Questions (Qi) for underage people were: • Q1: When I am worried about anything, I can ask my family for help. • Q2: I like how my family talks and shares their problems with me. • Q3: I like how my family allows me to do the new things I want to do. • Q4: I like what my family does when I am happy, sad, angry, etc. • Q5: I like how my family and I spend time together. On the other hand, for each question, 5 possible answers were designed with different weights based on a linear symmetric likert scale, and with the same ratings for adults and underage people. The Likert scale weighted Answers (Ai), offered for the participants were: • A1: Never (0 Points) • A2: Almost Never (1 Point) • A3: Sometimes (2 Points) • A4: Almost Always (3 Points) • A5: Always (4 Points) Variables 8 to 32 correspond to the execution of the APGAR test, per se, and were coded in the form of a tuple, Question-Answer (Qi-Aj). The ‘i’ value identifies the 5 types of questions, while the ‘j’ index determines the 5 types of answers. All the tuples Qi-Aj were encoded through a boolean variable (0/1). Where ‘0’ indicates the absence of a value in the tuple and ‘1’ the presence of a value in the tuple. All the APGAR tests were taken in Spanish since it is the official language of Ecuador, and then transcribed into English. Although the data has been collected by using the APGAR test to measure family functions and their changes in the postmodern context, it is important to note that the collected data could be used for other different purposes.

Results of capture-recapture modelling to estimate population size of patients with schizophrenia and bipolar condition in NYGH and NYFHT.

Abstract copyright UK Data Service and data collection copyright owner.The Health Survey for England (HSE) is a series of surveys designed to monitor trends in the nation's health. It was commissioned by NHS Digital and carried out by the Joint Health Surveys Unit of the National Centre for Social Research and the Department of Epidemiology and Public Health at University College London.The aims of the HSE series are:to provide annual data about the nation’s health;to estimate the proportion of people in England with specified health conditions;to estimate the prevalence of certain risk factors associated with these conditions;to examine differences between population subgroups in their likelihood of having specific conditions or risk factors;to assess the frequency with which particular combinations of risk factors are found, and which groups these combinations most commonly occur;to monitor progress towards selected health targetssince 1995, to measure the height of children at different ages, replacing the National Study of Health and Growth;since 1995, monitor the prevalence of overweight and obesity in children.The survey includes a number of core questions every year but also focuses on different health issues at each wave. Topics are revisited at appropriate intervals in order to monitor change. Further information about the series may be found on the NHS Digital Health Survey for England; health, social care and lifestyles webpage, the NatCen Social Research NatCen Health Survey for England webpage and the University College London Health and Social Surveys Research Group UCL Health Survey for England webpage. Changes to the HSE from 2015:Users should note that from 2015 survey onwards, only the individual data file is available under standard End User Licence (EUL). The household data file is now only included in the Special Licence (SL) version, released from 2015 onwards. In addition, the SL individual file contains all the variables included in the HSE EUL dataset, plus others, including variables removed from the EUL version after the NHS Digital disclosure review. The SL HSE is subject to more restrictive access conditions than the EUL version (see Access information). Users are advised to obtain the EUL version to see if it meets their needs before considering an application for the SL version. The Health Survey for England, 2004 (HSE 2004) was designed to provide data at both national and regional level about the population living in private households in England. The sample design of the 2004 survey had two parts: a general population sample that followed the same pattern as in previous years and a minority ethnic 'boost' sample (for the groups covered, see above). The general population sample was half the size of the usual sample. Up to ten adults and up to two children in each household were interviewed, and a nurse visit arranged for those participants in minority ethnic groups who consented. For the ethnic boost sample, all sampled addresses were fully screened and only informants from the specified minority ethnic groups were eligible for inclusion in the survey. Among these, up to four adults and three children were selected for interview. For informants from the specified minority ethnic groups (whether identified in the general population sample or the minority ethnic sample), an interview with each eligible person was followed by a nurse visit. Information was obtained directly from persons aged 13 and over. Information about children under 13 was obtained from a parent with the child present. The survey was conducted throughout the year to take into consideration seasonal differences. For the second edition (April 2010), three new children's Body Mass Index (BMI) variables have been added to the general population and ethnic boost data files (bmicat1, bmicat2, bmicat3). The original variables (bmicut, bmicut2, bmicut3) are unreliable and should not be used. Further information is available in the documentation and on the Information Centre for Health and Social Care Health Survey for England web page. Main Topics: The main focus of HSE 2004 for adults from minority ethnic backgrounds was cardiovascular disease (CVD) and related risk factors. In addition to the core HSE topics, a module on complementary therapies and alternative medicine was also included in the main individual questionnaire. At the nurse visit, questions were asked about prescribed medication, vitamin supplements and nicotine replacements. The nurse took the blood pressure of those aged five and over, measured lung function of those aged 7-15, and made waist and hip measurements for those aged 11 and over. Saliva samples were collected from 4-15 year olds and blood samples from those aged 11 and over, including fasting blood from those aged 16 and over. Blood and saliva samples were sent to a laboratory for analysis. Informants in the general population sample, unless they were members of the specified minority ethnic groups, were given a shortened version of the questionnaire covering core topics only. Standard MeasuresGeneral Health Questionnaire (GHQ12)EQ-5D Health State Multi-stage stratified random sample Face-to-face interview Self-completion Clinical measurements Physical measurements CAPI 2005 ACCIDENTS ACUPUNCTURE AGE ALCOHOL USE ALCOHOLIC DRINKS ANTHROPOMETRIC DATA ANXIETY ASIANS ATTITUDES BEDROOMS BLACK PEOPLE CARDIOVASCULAR DISE... CHILDREN CHIROPRACTIC CHRONIC ILLNESS CLINICAL TESTS AND ... CLUBS COMMUNITIES COMPLEMENTARY THERA... CONCENTRATION CONFECTIONERY CONTRACEPTIVE DEVICES COOKING CULTURAL IDENTITY CULTURAL LIFE CYCLING DAIRY PRODUCTS DEBILITATIVE ILLNESS DEPRESSION DIABETES DIET AND EXERCISE DISABILITIES ECONOMIC ACTIVITY EDIBLE FATS EDUCATIONAL BACKGROUND EMOTIONAL STATES EMPLOYEES EMPLOYMENT EMPLOYMENT HISTORY ENGLISH LANGUAGE ETHNIC GROUPS ETHNIC MINORITIES EXERCISE PHYSICAL A... England FAMILIES FATHERS FOLK MEDICINE FOOD FRIENDS FRUIT FURNISHED ACCOMMODA... GARDENING GENDER General health and ... HAPPINESS HEADS OF HOUSEHOLD HEALTH HEALTH ADVICE HEALTH CONSULTATIONS HEALTH PROFESSIONALS HEALTH SERVICES HEART DISEASES HEIGHT PHYSIOLOGY HERBAL MEDICINE HOMEOPATHY HORMONE REPLACEMENT... HOSPITAL OUTPATIENT... HOSPITALIZATION HOURS OF WORK HOUSEHOLD INCOME HOUSEHOLDS HOUSEWORK HOUSING TENURE HUMAN SETTLEMENT HYPNOTHERAPY Health care service... ILL HEALTH INDUSTRIES INFANTS INJURIES JOB HUNTING LANDLORDS LANGUAGES LEGUMES LOCAL COMMUNITY FAC... MARITAL STATUS MEAT MEDICAL DIETS MEDICAL PRESCRIPTIONS MEDICINAL DRUGS MEDITATION MEMBERSHIP MENSTRUATION MENTAL HEALTH MILK MOTHERS MOTOR PROCESSES MOTOR VEHICLES MUSCULOSKELETAL SYSTEM NATIONAL BACKGROUND NEIGHBOURS NURSES OCCUPATIONAL QUALIF... ORGANIZATIONS OSTEOPATHY PAIN PARENT RESPONSIBILITY PASSIVE SMOKING PERSONAL PROTECTIVE... PHYSICAL ACTIVITIES PHYSICIANS PLACE OF BIRTH PREGNANCY PRESERVED FOODS QUALIFICATIONS REFLEXOLOGY RELIGIOUS AFFILIATION RENTED ACCOMMODATION RESIDENTIAL MOBILITY RESPIRATORY TRACT D... SAFETY EQUIPMENT SALT SAVOURY SNACKS SELF EMPLOYED SELF ESTEEM SMOKING SMOKING CESSATION SOCIAL CLASS SOCIAL NETWORKS SOCIAL PARTICIPATION SOCIAL SECURITY BEN... SOCIAL SUPPORT SOCIO ECONOMIC STATUS SPORT STRESS PSYCHOLOGICAL SUPERVISORY STATUS SURGERY TIED HOUSING TOBACCO TOP MANAGEMENT TRUST UNFURNISHED ACCOMMO... VASCULAR DISEASES VEGETABLES VITAMINS WALKING WEIGHT PHYSIOLOGY YOUTH