The Victorian Emergency Minimum Dataset (VEMD) contains information detailing presentations at Victorian public hospitals with designated Emergency Departments. For the purposes of this report, patients presenting for family violence reasons are identified by the ‘human intent’ data item.

At the Emergency Department, the clinician assesses the most likely human intent. Patients presenting for family violence reasons are those that presented with a human intent injury of 'Maltreatment, assault by domestic partner' or 'Child neglect/maltreatment by parent or guardian'. The VEMD information published under the Family Violence Database (FVDB) focuses on the demographic characteristics as well as the nature and cause of their injuries of the patients presenting for family violence reasons. The FVDB only reports on family violence (FV) related patients (as indicated by the human intent data item). Therefore, when there is a reference in the FVDB to 'patients', this only includes family violence related patients presenting to a public hospital in Victoria.

The counting unit for the VEMD is the patient presenting at a Victorian public hospital. In the dataset there is one record per patient. However, persons can present multiple times at the emergency department and thus have multiple records in the VEMD.

The Drug Abuse Warning Network (DAWN) is a nationally representative public health surveillance system that has monitored drug related emergency department (ED) visits to hospitals since the early 1970s. First administered by the Drug Enforcement Administration (DEA) and the National Institute on Drug Abuse (NIDA), the responsibility for DAWN now rests with the Substance Abuse and Mental Health Services Administration's (SAMHSA) Center for Behavioral Health Statistics and Quality (CBHSQ). Over the years, the exact survey methodology has been adjusted to improve the quality, reliability, and generalizability of the information produced by DAWN. The current approach was first fully implemented in the 2004 data collection year. DAWN relies on a longitudinal probability sample of hospitals located throughout the United States. To be eligible for selection into the DAWN sample, a hospital must be a non-Federal, short-stay, general surgical and medical hospital located in the United States, with at least one 24-hour ED. DAWN cases are identified by the systematic review of ED medical records in participating hospitals. The unit of analysis is any ED visit involving recent drug use. DAWN captures both ED visits that are directly caused by drugs and those in which drugs are a contributing factor but not the direct cause of the ED visit. The reason a patient used a drug is not part of the criteria for considering a visit to be drug-related. Therefore, all types of drug-related events are included: drug misuse or abuse, accidental drug ingestion, drug-related suicide attempts, malicious drug poisonings, and adverse reactions. DAWN does not report medications that are unrelated to the visit. The DAWN public-use dataset provides information for all types of drugs, including illegal drugs, prescription drugs, over-the-counter medications, dietary supplements, anesthetic gases, substances that have psychoactive effects when inhaled, alcohol when used in combination with other drugs (all ages), and alcohol alone (only for patients aged 20 or younger). Public-use dataset variables describe and categorize up to 22 drugs contributing to the ED visit, including toxicology confirmation and route of administration. Administrative variables specify the type of case, case disposition, categorized episode time of day, and quarter of year. Metropolitan area is included for represented metropolitan areas. Created variables include the number of unique drugs reported and case-level indicators for alcohol, non-alcohol illicit substances, any pharmaceutical, non-medical use of pharmaceuticals, and all misuse and abuse of drugs. Demographic items include age category, sex, and race/ethnicity. Complex sample design and weighting variables are included to calculate various estimates of drug-related ED visits for the Nation as a whole, as well as for specific metropolitan areas, from the ED visits classified as DAWN cases in the selected hospitals.This study has 1 Data Set.

The goal of the Chicago Women's Health Risk Study (CWHRS) was to develop a reliable and validated profile of risk factors directly related to lethal or life-threatening outcomes in intimate partner violence, for use in agencies and organizations working to help women in abusive relationships. Data were collected to draw comparisons between abused women in situations resulting in fatal outcomes and those without fatal outcomes, as well as a baseline comparison of abused women and non-abused women, taking into account the interaction of events, circumstances, and interventions occurring over the course of a year or two. The CWHRS used a quasi-experimental design to gather survey data on 705 women at the point of service for any kind of treatment (related to abuse or not) sought at one of four medical sites serving populations in areas with high rates of intimate partner homicide (Chicago Women's Health Center, Cook County Hospital, Erie Family Health Center, and Roseland Public Health Center). Over 2,600 women were randomly screened in these settings, following strict protocols for safety and privacy. One goal of the design was that the sample would not systematically exclude high-risk but understudied populations, such as expectant mothers, women without regular sources of health care, and abused women in situations where the abuse is unknown to helping agencies. To accomplish this, the study used sensitive contact and interview procedures, developed sensitive instruments, and worked closely with each sample site. The CWHRS attempted to interview all women who answered "yes -- within the past year" to any of the three screening questions, and about 30 percent of women who did not answer yes, provided that the women were over age 17 and had been in an intimate relationship in the past year. In total, 705 women were interviewed, 497 of whom reported that they had experienced physical violence or a violent threat at the hands of an intimate partner in the past year (the abused, or AW, group). The remaining 208 women formed the comparison group (the non-abused, or NAW, group). Data from the initial interview sections comprise Parts 1-8. For some women, the AW versus NAW interview status was not the same as their screening status. When a woman told the interviewer that she had experienced violence or a violent threat in the past year, she and the interviewer completed a daily calendar history, including details of important events and each violent incident that had occurred the previous year. The study attempted to conduct one or two follow-up interviews over the following year with the 497 women categorized as AW. The follow-up rate was 66 percent. Data from this part of the clinic/hospital sample are found in Parts 9-12. In addition to the clinic/hospital sample, the CWHRS collected data on each of the 87 intimate partner homicides occurring in Chicago over a two-year period that involved at least one woman age 18 or older. Using the same interview schedule as for the clinic/hospital sample, CWHRS interviewers conducted personal interviews with one to three "proxy respondents" per case, people who were knowledgeable and credible sources of information about the couple and their relationship, and information was compiled from official or public records, such as court records, witness statements, and newspaper accounts (Parts 13-15). In homicides in which a woman was the homicide offender, attempts were made to contact and interview her. This "lethal" sample, all such homicides that took place in 1995 or 1996, was developed from two sources, HOMICIDES IN CHICAGO, 1965-1995 (ICPSR 6399) and the Cook County Medical Examiner's Office. Part 1 includes demographic variables describing each respondent, such as age, race and ethnicity, level of education, employment status, screening status (AW or NAW), birthplace, and marital status. Variables in Part 2 include details about the woman's household, such as whether she was homeless, the number of people living in the household and details about each person, the number of her children or other children in the household, details of any of her children not living in her household, and any changes in the household structure over the past year. Variables in Part 3 deal with the woman's physical and mental health, including pregnancy, and with her social support network and material resources. Variables in Part 4 provide information on the number and type of firearms in the household, whether the woman had experienced power, control, stalking, or harassment at the hands of an intimate partner in the past year, whether she had experienced specific types of violence or violent threats at the hands of an intimate partner in the past year, and whether she had experienced symptoms of Post-Traumatic Stress Disorder related to the incidents in the past month. Variables in Part 5 specify the partner or partners who were responsible for the incidents in the past year, record the type and length of the woman's relationship with each of these partners, and provide detailed information on the one partner she chose to talk about (called "Name"). Variables in Part 6 probe the woman's help-seeking and interventions in the past year. Variables in Part 7 include questions comprising the Campbell Danger Assessment (Campbell, 1993). Part 8 assembles variables pertaining to the chosen abusive partner (Name). Part 9, an event-level file, includes the type and the date of each event the woman discussed in a 12-month retrospective calendar history. Part 10, an incident-level file, includes variables describing each violent incident or threat of violence. There is a unique identifier linking each woman to her set of events or incidents. Part 11 is a person-level file in which the incidents in Part 10 have been aggregated into totals for each woman. Variables in Part 11 include, for example, the total number of incidents during the year, the number of days before the interview that the most recent incident had occurred, and the severity of the most severe incident in the past year. Part 12 is a person-level file that summarizes incident information from the follow-up interviews, including the number of abuse incidents from the initial interview to the last follow-up, the number of days between the initial interview and the last follow-up, and the maximum severity of any follow-up incident. Parts 1-12 contain a unique identifier variable that allows users to link each respondent across files. Parts 13-15 contain data from official records sources and information supplied by proxies for victims of intimate partner homicides in 1995 and 1996 in Chicago. Part 13 contains information about the homicide incidents from the "lethal sample," along with outcomes of the court cases (if any) from the Administrative Office of the Illinois Courts. Variables for Part 13 include the number of victims killed in the incident, the month and year of the incident, the gender, race, and age of both the victim and offender, who initiated the violence, the severity of any other violence immediately preceding the death, if leaving the relationship triggered the final incident, whether either partner was invading the other's home at the time of the incident, whether jealousy or infidelity was an issue in the final incident, whether there was drug or alcohol use noted by witnesses, the predominant motive of the homicide, location of the homicide, relationship of victim to offender, type of weapon used, whether the offender committed suicide after the homicide, whether any criminal charges were filed, and the type of disposition and length of sentence for that charge. Parts 14 and 15 contain data collected using the proxy interview questionnaire (or the interview of the woman offender, if applicable). The questionnaire used for Part 14 was identical to the one used in the clinic sample, except for some extra questions about the homicide incident. The data include only those 76 cases for which at least one interview was conducted. Most variables in Part 14 pertain to the victim or the offender, regardless of gender (unless otherwise labeled). For ease of analysis, Part 15 includes the same 76 cases as Part 14, but the variables are organized from the woman's point of view, regardless of whether she was the victim or offender in the homicide (for the same-sex cases, Part 15 is from the woman victim's point of view). Parts 14 and 15 can be linked by ID number. However, Part 14 includes five sets of variables that were asked only from the woman's perspective in the original questionnaire: household composition, Post-Traumatic Stress Disorder (PTSD), social support network, personal income (as opposed to household income), and help-seeking and intervention. To avoid redundancy, these variables appear only in Part 14. Other variables in Part 14 cover information about the person(s) interviewed, the victim's and offender's age, sex, race/ethnicity, birthplace, employment status at time of death, and level of education, a scale of the victim's and offender's severity of physical abuse in the year prior to the death, the length of the relationship between victim and offender, the number of children belonging to each partner, whether either partner tried to leave and/or asked the other to stay away, the reasons why each partner tried to leave, the longest amount of time each partner stayed away, whether either or both partners returned to the relationship before the death, any known physical or emotional problems sustained by victim or offender, including the four-item Medical Outcomes Study (MOS) scale of depression, drug and alcohol use of the victim and offender, number and type of guns in the household of the victim and offender, Scales of Power and Control (Johnson, 1996) or Stalking and Harassment (Sheridan, 1992) by either intimate partner in the year prior to the death, a modified version of the Conflict Tactics Scale (CTS)

This is the analysis conducted and dataset for the study entitled "Factors associated with university and hospital mistreatment in medical students from seven Latin American countries".

This project consisted of an evaluation of an elder abuse program run by the New York Police Department and Victim Services Research. The focus of the study was domestic elder abuse, which generally refers to any of several forms of maltreatment, physical abuse, sexual abuse, psychological abuse, neglect, and/or financial exploitation of an older person. The program, conducted in New York City public housing, had two complementary parts. First, public housing projects in Manhattan were assigned to one of two levels of public education (i.e., to receive or not to receive educational materials about elder abuse). Once the public education treatment had been implemented, 403 older adult residents of the housing projects who reported elder abuse to the police during the next ten months were assigned to one of two levels of follow-up to the initial police response (i.e., to receive or not to receive a home visit) as the second part of the project. The home visit intervention consisted of a strong law enforcement response designed to prevent repeat incidents of elder abuse. A team from the Domestic Violence Intervention and Education Program (DVIEP), consisting of a police officer and a social worker, followed up on domestic violence complaints with a home visit within a few days of the initial patrol response. Victims were interviewed about new victimizations following the intervention on three occasions: six weeks after the trigger incident, six months after the trigger incident, and twelve months after the trigger incident. Interviews at the three time points were identical except for the omission of background information on the second and third interviews. Demographic data collected during the first interview included age, gender, ethnicity, education, employment, income, legal relationship with abuser, living situation, number of people in the household, and health. For each time point, data provide measures of physical, psychological, and financial abuse, knowledge of elder abuse, knowledge and use of social services, satisfaction with the police, assessment of service delivery, and self-esteem and well-being. The DVIEP databases maintained on households at each of the three participating Police Service Areas (PSAs) were searched to identify new police reports of elder abuse for households in the sample within 12 months following the trigger incident. Variables from the DVIEP databases include age, race, ethnicity, and sex of the victim and the perpetrator, relationship of perpetrator to victim, type of abuse reported, charge, whether an arrest was made, if an order of protection had been obtained, if the order of protection was violated, use of weapons, if the victim had been injured, and if the victim was taken to the hospital. Several time lapse variables between different time points are also provided.

The Sexual Assault Centre program provides crisis support and intervention services to victims of sexual assault, abuse and/or incest survivors. Services include:

• accompanying a victim to court, hospital or police station
• counselling services (both one-on-one and group)
• sexual violence education
• training for professionals and members of the public
• information and referrals

The Drug Abuse Warning Network (DAWN) is a nationally representative public health surveillance system overseen by the Substance Abuse and Mental Health Services Administration (SAMHSA) that continuously monitors drug-related visits to hospital emergency departments (EDs). A DAWN case is any ED visit where recent drug use is a direct or contributing factor for the ED visit. The dataset includes information obtained from medical records, including patient demographics, a list of up to 16 drugs involved in the ED visit, toxicology confirmation, route of administration, type of case, and disposition of the patient following the visit. For patient confidentiality, primary sampling units (PSUs) and strata identification values are randomized each year. "Legacy" DAWN datasets contain data collected between 1992 and 2011. The DAWN surveillance system was re-established in 2018 and resumed data collection.

This study addressed the question of whether women who were sexually abused as children were at increased risk of either sexual abuse or domestic violence victimization later in life. It also investigated the role of other potential risk factors, including family background, sexual behavior, alcohol problems, and a woman's own aggressive behavior. The investigators sought to answer the following questions: (1) Are victims of child sexual abuse at increased risk of adolescent or adult sexual victimization as compared to nonvictims? (2) Are victims of child sexual abuse at increased risk of physically violent nonsexual victimization as compared to nonvictims? (3) How is the risk of sexual revictimization and physical victimization among abuse survivors affected by their engaging in violent behavior, such as physical fighting, engaging in heavy drinking, and practicing risky sexual behavior, such as having multiple sexual partners? (4) Were women who reported drinking problems and physical fighting in Wave 2 at increased risk of domestic violence victimization at Wave 3, compared to the other child abuse victims in the study? This study consisted of a secondary analysis of selected variables collected during two waves of a three-wave prospective study of the consequences of child abuse and sexual assault for adult, adolescent, and child victims (McCahill, Meyer, and Fischman, 1979). During the first wave of the study, data were gathered on 206 girls ranging in age from 10 months to 12 years who were victims of reported cases of sexual abuse and who were examined at a municipal hospital in 1973-1975. In 1990 and 1991, follow-up interviews (Wave 2) were conducted with 136 of the original 206 girls, then aged 18 to 31. During this wave, a comparison group of girls treated at a hospital for reasons other than child sexual abuse was matched to the 206 victims on the basis of race, age, and date of hospital visit, for purposes of analysis of their official criminal records. The criminal records data are not included in this data collection. Also, none of the women in the comparison group were interviewed during Wave 2. In 1996 and 1997, another wave of follow-up interviews (Wave 3) was conducted. Using the same criteria as in Wave 2, a new matched comparison group was identified, resulting in an additional 85 girls in the sample. Of the 174 women interviewed during Wave 3, 80 were known victims of child sexual abuse who also had been interviewed during Wave 2. The data in Part 2 (Wave 3 Women Also Interviewed at Wave 2) are a subset of Part 1 (All Wave 3 Interviews). Part 1 variables supply information on self-reported family history of substance abuse and criminal activity, parental care and neglect, and family violence when the respondent was a child. Topics focusing on respondents' current (adult) experiences include violence in relationships, injuries as a result of domestic violence, use of a weapon during domestic violence, sexual history, sexual victimization, and parental attachment. Variables in Part 2 cover parental affection and support received by the respondent when she was a teenager, history of fighting, physical abuse by a partner, dating and sexual history, alcohol abuse, and sexual victimization. Demographic variables (found in Part 1 only) include age, marital status, race, and education.

The dataset consists of police reports entered in the police case management system where the victim was a child aged 4-5 years. The data were mainly formed based on information collected from the free-form texts on the reports. The archived data include information in statistical format on all reports that were entered in the system in 2017 where the name of the crime was listed as petty assault or assault. In cases where the crime was listed as both petty assault and assault, the archived data record the case as an assault. The original research was partly funded by Tampere University Hospital. The data include information on the type of crime disclosed in the report as well as categorised information on the person who suspected a crime had taken place, the person who reported the suspected crime, and the suspect. Additionally, the data include information on the origin of the suspicion described in the report, how long a crime had been suspected, and how much of a delay there was in reporting the suspected crime. The child's gender and whether the child's parents were together were also recorded in the data.

The Drug Abuse Warning Network (DAWN) is a nationally representative public health surveillance system that has monitored drug related emergency department (ED) visits to hospitals since the early 1970s. First administered by the Drug Enforcement Administration (DEA) and the National Institute on Drug Abuse (NIDA), the responsibility for DAWN now rests with the Substance Abuse and Mental Health Services Administration's (SAMHSA) Center for Behavioral Health Statistics and Quality (CBHSQ). Over the years, the exact survey methodology has been adjusted to improve the quality, reliability, and generalizability of the information produced by DAWN. The current approach was first fully implemented in the 2004 data collection year. DAWN relies on a longitudinal probability sample of hospitals located throughout the United States. To be eligible for selection into the DAWN sample, a hospital must be a non-Federal, short-stay, general surgical and medical hospital located in the United States, with at least one 24-hour ED. DAWN cases are identified by the systematic review of ED medical records in participating hospitals. The unit of analysis is any ED visit involving recent drug use. DAWN captures both ED visits that are directly caused by drugs and those in which drugs are a contributing factor but not the direct cause of the ED visit. The reason a patient used a drug is not part of the criteria for considering a visit to be drug-related. Therefore, all types of drug-related events are included: drug misuse or abuse, accidental drug ingestion, drug-related suicide attempts, malicious drug poisonings, and adverse reactions. DAWN does not report medications that are unrelated to the visit. The DAWN public-use dataset provides information for all types of drugs, including illegal drugs, prescription drugs, over-the-counter medications, dietary supplements, anesthetic gases, substances that have psychoactive effects when inhaled, alcohol when used in combination with other drugs (all ages), and alcohol alone (only for patients aged 20 or younger). Public-use dataset variables describe and categorize up to 22 drugs contributing to the ED visit, including toxicology confirmation and route of administration. Administrative variables specify the type of case, case disposition, categorized episode time of day, and quarter of year. Metropolitan area is included for represented metropolitan areas. Created variables include the number of unique drugs reported and case-level indicators for alcohol, non-alcohol illicit substances, any pharmaceutical, non-medical use of pharmaceuticals, and all misuse and abuse of drugs. Demographic items include age category, sex, and race/ethnicity. Complex sample design and weighting variables are included to calculate various estimates of drug-related ED visits for the Nation as a whole, as well as for specific metropolitan areas, from the ED visits classified as DAWN cases in the selected hospitals.This study has 1 Data Set.

The degree to which artificial intelligence healthcare research is informed by data and stakeholders from community settings has not been previously described. As communities are the principal location of healthcare delivery, engaging them could represent an important opportunity to improve scientific quality. This scoping review systematically maps what is known and unknown about community-engaged artificial intelligence research and identifies opportunities to optimize the generalizability of these applications through involvement of community stakeholders and data throughout model development, validation, and implementation. Embase, PubMed, and MEDLINE databases were searched for articles describing artificial intelligence or machine learning healthcare applications with community involvement in model development, validation, or implementation. Model architecture and performance, the nature of community engagement, and barriers or facilitators to community engagement were reported according to PRISMA extension for Scoping Reviews guidelines. Of approximately 10,880 articles describing artificial intelligence healthcare applications, 21 (0.2%) described community involvement. All articles derived data from community settings, most commonly by leveraging existing datasets and sources that included community subjects, and often bolstered by internet-based data acquisition and subject recruitment. Only one article described inclusion of community stakeholders in designing an application–a natural language processing model that detected cases of likely child abuse with 90% accuracy using harmonized electronic health record notes from both hospital and community practice settings. The primary barrier to including community-derived data was small sample sizes, which may have affected 11 of the 21 studies (53%), introducing substantial risk for overfitting that threatens generalizability. Community engagement in artificial intelligence healthcare application development, validation, or implementation is rare. As healthcare delivery occurs primarily in community settings, investigators should consider engaging community stakeholders in user-centered design, usability, and clinical implementation studies to optimize generalizability.

The goal of this study was to compile and analyze data about incidents of domestic violence in San Diego County, California, in order to enhance understanding of the nature and scope of violence against women. The following objectives were set to achieve this goal: (1) to develop a standardized interview instrument to be used by all emergency shelters for battered women in the region, and (2) to conduct interviews with shelter staff. For this study, the San Diego Association of Governments (SANDAG) collected information about domestic violence in San Diego County from clients admitted to battered women's shelters. The Compilation of Research and Evaluation (CORE) intake interview (Part 1) was initiated in March of 1997. Through this interview, researchers gathered data over a 22-month period, through December 1998, for 599 clients. The CORE discharge interview (Part 2) was theoretically completed at the time of exit with each client who completed the CORE intake interview in order to document the services received. However, data collection at exit was not reliable, due to factors beyond the researchers' control, and thus researchers did not receive a discharge form for each individual who had an intake form. For Part 1 (Intake Data), demographic variables include the client's primary language, and the client and batterer's age, education, race, how they supported themselves, their annual incomes, and their children's sex, age, and ethnicity. Other variables cover whether the client had been to this shelter within the last 12 months, the kind of housing the client had before she came to the shelter, person's admitted along with the client, drug and alcohol use by the client, the batterer, and the children, relationship between the client and the batterer (e.g., spouse, former spouse), if the client and batterer had been in the military, if the client or children were military dependents, the client's citizenship, if the client and batterer had any physical/mental limitations, abuse characteristics (e.g., physical, verbal, sexual, weapon involved), and the client's medical treatment history (e.g., went to hospital, had been abused while pregnant, witnessed abuse while growing up, had been involved in other abusive relationships, had attempted suicide). Additional variables provide legal information (number of times police had been called to the client's household as a result of domestic violence, if anyone in the household had been arrested as a result of those calls, if any charges were filed, if the client or batterer had been convicted of abuse), if the client had a restraining order against the batterer, how the client found out about the shelter, the number of times the client had been admitted to a domestic violence shelter, the client's assessment of her needs at the time of admittance, and the interviewer/counselor's assessment of the client's needs at the time of admittance. Part 2 (Discharge Data) provides information on services the client received from the shelter during her stay (food, clothing, permanent housing, transitional housing, financial assistance, employment, education, medical help, assistance with retrieving belongings, assistance with retrieving/replacing legal documents, law enforcement, temporary restraining order), and services this client received as a referral to another agency (attorney, divorce, child care, counseling, transportation, safety plan, victim/witness funds, mental health services, department of social services, Children's Services Bureau, help with immigration, drug treatment).

Patients with an alcohol abuse disorder exhibit several medical characteristics and social determinants, which suggest a greater vulnerability to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and a worse course of the coronavirus disease 2019 (COVID-19) once infected. During the first wave of the COVID-19, most of the countries have register an increase in alcohol consumption. However, studies on the impact of alcohol addiction on the risk of COVID-19 infection are very scarce and inconclusive. This research offers a descriptive observational retrospective cohort study using real world data obtained from the Electronic Health Records. We found that patients with a personal history of alcohol abuse were 8% more likely to extend their hospitalization length of stay for 1 day (95% CI = 1.04–1.12) and 15% more likely to extend their Intensive Care Unit (ICU) length of stay (95% CI = 1.01–1.30). They were also 5.47 times more at risk of needing an ICU admission (95% CI = 1.61–18.57) and 3.54 times (95% CI = 1.51–8.30) more at risk of needing a respirator. Regarding COVID-19 symptoms, patients with a personal history of alcohol abuse were 91% more likely of exhibiting dyspnea (95% CI = 1.03–3.55) and 3.15 times more at risk of showing at least one neuropsychiatric symptom (95% CI = 1.61–6.17). In addition, they showed statistically significant differences in the number of neuropsychiatric symptoms developed during the COVID-19 infection. Therefore, we strongly recommend to warn of the negative consequences of alcohol abuse over COVID-19 complications. For this purpose. Clinicians should systematically assess history of alcohol issues and drinking habits in all patients, especially for those who seek medical advice regarding COVID-19 infection, in order to predict its severity of symptoms and potential complications. Moreover, this information should be included, in a structured field, into the Electronic Health Record to facilitate the automatic extraction of data, in real time, useful to evaluate the decision-making process in a dynamic context.

Firearms, knife- and sharp-instrument offences, offences involving a corrosive substance, hospital admissions for assault with sharp objects, fraud, offences flagged as domestic abuse-related, corruption, anti-social behaviour, perceptions, and non-notifiable incidents.

The National Mental Health Services Survey (N-MHSS) is an annual survey designed to collect statistical information on the numbers and characteristics of all known mental health treatment facilities within the 50 States, the District of Columbia, and the U.S. territories. In every other year, beginning in 2014, the survey also collects statistical information on the numbers and demographic characteristics of persons served in these treatment facilities as of a specified survey reference date. The N-MHSS is the only source of national and State-level data on the mental health service delivery system reported by both publicly-operated and privately-operated specialty mental health treatment facilities, including: public psychiatric hospitals; private psychiatric hospitals, non-federal general hospitals with separate psychiatric units; U.S. Department of Veterans Affairs medical centers; residential treatment centers for children; residential treatment centers for adults; outpatient or day treatment or partial hospitalization mental health facilities; and multi-setting (non-hospital) mental health facilities. The N-MHSS complements the information collected through SAMHSA's survey of substance abuse treatment facilities, the National Survey of Substance Abuse Treatment Services (N-SSATS). Treatment facility Information from the N-MHSS is used to populate the mental health component of SAMHSA's online Behavioral Health Treatment Services Locator. http://findtreatment.samhsa.gov/This study has 1 Data Set.