This dataset comprises physician-level entries from the 1906 American Medical Directory, the first in a series of semi-annual directories of all practicing physicians published by the American Medical Association [1]. Physicians are consistently listed by city, county, and state. Most records also include details about the place and date of medical training. From 1906-1940, Directories also identified the race of black physicians [2].This dataset comprises physician entries for a subset of US states and the District of Columbia, including all of the South and several adjacent states (Alabama, Arkansas, Delaware, Florida, Georgia, Kansas, Kentucky, Louisiana, Maryland, Mississippi, Missouri, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, West Virginia). Records were extracted via manual double-entry by professional data management company [3], and place names were matched to latitude/longitude coordinates. The main source for geolocating physician entries was the US Census. Historical Census records were sourced from IPUMS National Historical Geographic Information System [4]. Additionally, a public database of historical US Post Office locations was used to match locations that could not be found using Census records [5]. Fuzzy matching algorithms were also used to match misspelled place or county names [6].The source of geocoding match is described in the “match.source” field (Type of spatial match (census_YEAR = match to NHGIS census place-county-state for given year; census_fuzzy_YEAR = matched to NHGIS place-county-state with fuzzy matching algorithm; dc = matched to centroid for Washington, DC; post_places = place-county-state matched to Blevins & Helbock's post office dataset; post_fuzzy = matched to post office dataset with fuzzy matching algorithm; post_simp = place/state matched to post office dataset; post_confimed_missing = post office dataset confirms place and county, but could not find coordinates; osm = matched using Open Street Map geocoder; hand-match = matched by research assistants reviewing web archival sources; unmatched/hand_match_missing = place coordinates could not be found). For records where place names could not be matched, but county names could, coordinates for county centroids were used. Overall, 40,964 records were matched to places (match.type=place_point) and 931 to county centroids ( match.type=county_centroid); 76 records could not be matched (match.type=NA).Most records include information about the physician’s medical training, including the year of graduation and a code linking to a school. A key to these codes is given on Directory pages 26-27, and at the beginning of each state’s section [1]. The OSM geocoder was used to assign coordinates to each school by its listed location. Straight-line distances between physicians’ place of training and practice were calculated using the sf package in R [7], and are given in the “school.dist.km” field. Additionally, the Directory identified a handful of schools that were “fraudulent” (school.fraudulent=1), and institutions set up to train black physicians (school.black=1).AMA identified black physicians in the directory with the signifier “(col.)” following the physician’s name (race.black=1). Additionally, a number of physicians attended schools identified by AMA as serving black students, but were not otherwise identified as black; thus an expanded racial identifier was generated to identify black physicians (race.black.prob=1), including physicians who attended these schools and those directly identified (race.black=1).Approximately 10% of dataset entries were audited by trained research assistants, in addition to 100% of black physician entries. These audits demonstrated a high degree of accuracy between the original Directory and extracted records. Still, given the complexity of matching across multiple archival sources, it is possible that some errors remain; any identified errors will be periodically rectified in the dataset, with a log kept of these updates.For further information about this dataset, or to report errors, please contact Dr Ben Chrisinger (Benjamin.Chrisinger@tufts.edu). Future updates to this dataset, including additional states and Directory years, will be posted here: https://dataverse.harvard.edu/dataverse/amd.References:1. American Medical Association, 1906. American Medical Directory. American Medical Association, Chicago. Retrieved from: https://catalog.hathitrust.org/Record/000543547.2. Baker, Robert B., Harriet A. Washington, Ololade Olakanmi, Todd L. Savitt, Elizabeth A. Jacobs, Eddie Hoover, and Matthew K. Wynia. "African American physicians and organized medicine, 1846-1968: origins of a racial divide." JAMA 300, no. 3 (2008): 306-313. doi:10.1001/jama.300.3.306.3. GABS Research Consult Limited Company, https://www.gabsrcl.com.4. Steven Manson, Jonathan Schroeder, David Van Riper, Tracy Kugler, and Steven Ruggles. IPUMS National Historical Geographic Information System: Version 17.0 [GNIS, TIGER/Line & Census Maps for US Places and Counties: 1900, 1910, 1920, 1930, 1940, 1950; 1910_cPHA: ds37]. Minneapolis, MN: IPUMS. 2022. http://doi.org/10.18128/D050.V17.05. Blevins, Cameron; Helbock, Richard W., 2021, "US Post Offices", https://doi.org/10.7910/DVN/NUKCNA, Harvard Dataverse, V1, UNF:6:8ROmiI5/4qA8jHrt62PpyA== [fileUNF]6. fedmatch: Fast, Flexible, and User-Friendly Record Linkage Methods. https://cran.r-project.org/web/packages/fedmatch/index.html7. sf: Simple Features for R. https://cran.r-project.org/web/packages/sf/index.html

Data on visits to physician offices, hospital outpatient departments and hospital emergency departments by selected population characteristics. Please refer to the PDF or Excel version of this table in the HUS 2019 Data Finder (https://www.cdc.gov/nchs/hus/contents2019.htm) for critical information about measures, definitions, and changes over time. Note that the data file available here has more recent years of data than what is shown in the PDF or Excel version. Data for 2017 physician office visits are not available. SOURCE: NCHS, National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey. For more information on the National Ambulatory Medical Care Survey and the National Hospital Ambulatory Medical Care Survey, see the corresponding Appendix entries at https://www.cdc.gov/nchs/data/hus/hus17_appendix.pdf.

The US Healthcare Visits Statistics dataset includes data about the frequency of healthcare visits to doctor offices, emergency departments, and home visits within the past 12 months in the United States by age, race, Hispanic origin, poverty level, health insurance status, geographic region and other characteristics between 1997 and 2016.

The Study of Women's Health Across the Nation (SWAN), is a multi-site longitudinal, epidemiologic study designed to examine the health of women during their middle years. The study examines the physical, biological, psychological, and social changes during this transitional period. The goal of SWAN's research is to help scientists, health care providers, and women learn how mid-life experiences affect health and quality of life during aging. The data include questions about doctor visits, medical conditions, medications, treatments, medical procedures, relationships, smoking, and menopause related information such as age at pre-, peri- and post-menopause, self-attitudes, feelings, and common physical problems associated with menopause.The study is co-sponsored by the National Institute on Aging (NIA), the National Institute of Nursing Research (NINR), the National Institutes of Health (NIH), and the NIH Office of Research on Women's Health. The study began in 1994. Between 1996 and 1997, 3,302 participants joined SWAN through 7 designated research centers. The research centers are located in the following communities: Detroit, MI; Boston, MA; Chicago, IL; Oakland and Los Angeles, CA; Newark, NJ; and Pittsburgh, PA. SWAN participants represent five racial/ethnic groups and a variety of backgrounds and cultures. This is the next phase of data collection after the original collection of the screening data (ICPSR 4368).

Despite decades of low utilization, telemedicine adoption expanded at an unprecedented rate during the COVID-19 pandemic. This study examined quantitative and qualitative data provided by a national online sample of 228 practicing physicians (64% were women, and 75% were White) to identify facilitators and barriers to the adoption of telemedicine in the United States (U.S.) at the beginning of the COVID-19 pandemic. Logistic regressions were used to predict the most frequently endorsed (20% or more) barriers and facilitators based on participant demographics and practice characteristics. The top five reported barriers were: lack of patient access to technology (77.6%), insufficient insurance reimbursement (53.5%), diminished doctor-patient relationship (46.9%), inadequate video/audio technology (46.1%), and diminished quality of delivered care (42.1%). The top five reported facilitators were: better access to care (75.4%), increased safety (70.6%), efficient use of time (60.5%), lower cost for patients (43%), and effectiveness (28.9%). Physicians’ demographic and practice setting characteristics significantly predicted their endorsement of telemedicine barriers and facilitators. Older physicians were less likely to endorse inefficient use of time (p < 0.001) and potential for medical errors (p = 0.034) as barriers to telemedicine use compared to younger physicians. Physicians working in a medical center were more likely to endorse inadequate video/audio technology (p = 0.037) and lack of patient access to technology (p = 0.035) as a barrier and more likely to endorse lower cost for patients as a facilitator (p = 0.041) than providers working in other settings. Male physicians were more likely to endorse inefficient use of time as a barrier (p = 0.007) than female physicians, and White physicians were less likely to endorse lower costs for patients as a facilitator (p = 0.012) than physicians of color. These findings provide important context for future implementation strategies for healthcare systems attempting to increase telemedicine utilization.

These data come from surveillance activities conducted by the Guttmacher Institute over several decades, collecting or compiling data for the period 1994 through 2016. These activities track the numbers of women who have a potential demand for contraceptive care (because they are of reproductive age, sexually active and not seeking to become pregnant), the subset of these women who likely need public support for care (because of their family income level or their age), the numbers of women who receive contraceptive services from publicly funded clinics, and the numbers of clinics providing publicly supported contraceptive services. These efforts have been conducted periodically, typically about every five years, but at times the intervals between efforts were shorter or longer than five years. The most recent data were collected or compiled for 2015 (women served) and 2016 (women with potential demand for services). This release includes two separate datasets. Dataset 1, "Need for contraceptive services," provides county-level aggregate data for 6 different years (1995, 2000, 2002, 2006, 2010, and 2016). For each county, the data represent estimates of the number of women who have a potential demand for contraceptive services and the number who likely need public support for care, both in total, and according to key socio-demographic characteristics. Dataset 2, "Clinics providing contraceptive services and women served," provides county-level aggregate data for six different years (1994, 1997, 2001, 2006, 2010, and 2015). For each county, the data represent the number of publicly funded clinics according to clinic type and funding status and the number of female contraceptive patients served at those clinics.

BackgroundReductions in hemoglobin A1c (HbA1C) have been associated with improved cardiovascular outcomes and savings in medical expenditures. One public health approach has involved pharmacists within primary care settings. The objective was to assess change in HbA1C from baseline after 3–5 months of follow up in pharmacist-managed cardiovascular risk reduction (CVRR) clinics.MethodsThis retrospective cohort chart review occurred in eight pharmacist-managed CVRR federally qualified health clinics (FQHC) in Indiana, United States. Data were collected from patients seen by a CVRR pharmacist within the timeframe of January 1, 2015 through February 28, 2020. Data collected include: demographic characteristics and clinical markers between baseline and follow-up. HbA1C from baseline after 3 to 5 months was assessed with pared t-tests analysis. Other clinical variables were assessed and additional analysis were performed at 6–8 months. Additional results are reported between 9 months and 36 months of follow up.ResultsThe primary outcome evaluation included 445 patients. Over 36 months of evaluation, 3,803 encounters were described. Compared to baseline, HbA1C was reduced by 1.6% (95%CI -1.8, -1.4, p

Following the 2016 US Presidential election, immigration enforcement became more aggressive, with variation by state and region depending on local policies and sentiment. Increases in enforcement created an environment of risk for decreased use of health care services among especially among Latino families. of Hispanic ethnicity and/or from Latin American origin (as a group subsequently referred to as Latino). For Latino children with chronic health conditions, avoidance of routine health care can result in significant negative health consequences such as disease progression, avoidable use of acute health care services, and overall increased costs of care. To investigate for changes in visit attendance during the periods before and since increased immigration enforcement, we extracted data on children followed by subspecialty clinics of one healthcare system in the US state of North Carolina during 2015–2019. For each patient, we calculated the proportion of cancelled visits and no-show visits out of all scheduled visits during the 2016–2019 follow-up period. We compared patient characteristics (at the 2015 baseline) according to whether they cancelled or did not show to any visits in subsequent years by clinic and patient factors, including ethnicity. Data were analyzed using multinomial logistic regression of attendance at each visit, including an interaction between visit year and patient ethnicity. Among 852 children 1 to 17 years of age (111 of Latino ethnicity), visit no-show was more common among Latino patients, compared to non-Latino White patients; while visit cancellation was more common among non-Latino White patients, compared to Latino patients. There was no significant interaction between ethnicity and trends in visit no-show or cancellation. Although differences in pediatric specialty clinic visit attendance by patient ethnicity were seen at study baseline, changing immigration policy and negative rhetoric did not appear to impact use of pediatric subspecialty care.

The 2008 National Demographic and Health Survey (2008 NDHS) is a nationally representative survey of 13,594 women age 15-49 from 12,469 households successfully interviewed, covering 794 enumeration areas (clusters) throughout the Philippines. This survey is the ninth in a series of demographic and health surveys conducted to assess the demographic and health situation in the country. The survey obtained detailed information on fertility levels, marriage, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and young children, childhood mortality, maternal and child health, and knowledge and attitudes regarding HIV/AIDS and tuberculosis. Also, for the first time, the Philippines NDHS gathered information on violence against women. The 2008 NDHS was conducted by the Philippine National Statistics Office (NSO). Technical assistance was provided by ICF Macro through the MEASURE DHS program. Funding for the survey was mainly provided by the Government of the Philippines. Financial support for some preparatory and processing phases of the survey was provided by the U.S. Agency for International Development (USAID). Like previous Demographic and Health Surveys (DHS) conducted in the Philippines, the 2008 National Demographic and Health Survey (NDHS) was primarily designed to provide information on population, family planning, and health to be used in evaluating and designing policies, programs, and strategies for improving health and family planning services in the country. The 2008 NDHS also included questions on domestic violence. Specifically, the 2008 NDHS had the following objectives: Collect data at the national level that will allow the estimation of demographic rates, particularly, fertility rates by urban-rural residence and region, and under-five mortality rates at the national level. Analyze the direct and indirect factors which determine the levels and patterns of fertility. Measure the level of contraceptive knowledge and practice by method, urban-rural residence, and region. Collect data on family health: immunizations, prenatal and postnatal checkups, assistance at delivery, breastfeeding, and prevalence and treatment of diarrhea, fever, and acute respiratory infections among children under five years. Collect data on environmental health, utilization of health facilities, prevalence of common noncommunicable and infectious diseases, and membership in health insurance plans. Collect data on awareness of tuberculosis. Determine women's knowledge about HIV/AIDS and access to HIV testing. Determine the extent of violence against women. MAIN RESULTS FERTILITY Fertility Levels and Trends. There has been a steady decline in fertility in the Philippines in the past 36 years. From 6.0 children per woman in 1970, the total fertility rate (TFR) in the Philippines declined to 3.3 children per woman in 2006. The current fertility level in the country is relatively high compared with other countries in Southeast Asia, such as Thailand, Singapore and Indonesia, where the TFR is below 2 children per woman. Fertility Differentials. Fertility varies substantially across subgroups of women. Urban women have, on average, 2.8 children compared with 3.8 children per woman in rural areas. The level of fertility has a negative relationship with education; the fertility rate of women who have attended college (2.3 children per woman) is about half that of women who have been to elementary school (4.5 children per woman). Fertility also decreases with household wealth: women in wealthier households have fewer children than those in poorer households. FAMILY PLANNING Knowledge of Contraception. Knowledge of family planning is universal in the Philippines- almost all women know at least one method of fam-ily planning. At least 90 percent of currently married women have heard of the pill, male condoms, injectables, and female sterilization, while 87 percent know about the IUD and 68 percent know about male sterilization. On average, currently married women know eight methods of family planning. Unmet Need for Family Planning. Unmet need for family planning is defined as the percentage of currently married women who either do not want any more children or want to wait before having their next birth, but are not using any method of family planning. The 2008 NDHS data show that the total unmet need for family planning in the Philippines is 22 percent, of which 13 percent is limiting and 9 percent is for spacing. The level of unmet need has increased from 17 percent in 2003. Overall, the total demand for family planning in the Philippines is 73 percent, of which 69 percent has been satisfied. If all of need were satisfied, a contraceptive prevalence rate of about 73 percent could, theoretically, be expected. Comparison with the 2003 NDHS indicates that the percentage of demand satisfied has declined from 75 percent. MATERNAL HEALTH Antenatal Care. Nine in ten Filipino mothers received some antenatal care (ANC) from a medical professional, either a nurse or midwife (52 percent) or a doctor (39 percent). Most women have at least four antenatal care visits. More than half (54 percent) of women had an antenatal care visit during the first trimester of pregnancy, as recommended. While more than 90 percent of women who received antenatal care had their blood pressure monitored and weight measured, only 54 percent had their urine sample taken and 47 percent had their blood sample taken. About seven in ten women were informed of pregnancy complications. Three in four births in the Philippines are protected against neonatal tetanus. Delivery and Postnatal Care. Only 44 percent of births in the Philippines occur in health facilities-27 percent in a public facility and 18 percent in a private facility. More than half (56 percent) of births are still delivered at home. Sixty-two percent of births are assisted by a health professional-35 percent by a doctor and 27 percent by a midwife or nurse. Thirty-six percent are assisted by a traditional birth attendant or hilot. About 10 percent of births are delivered by C-section. The Department of Health (DOH) recommends that mothers receive a postpartum check within 48 hours of delivery. A majority of women (77 percent) had a postnatal checkup within two days of delivery; 14 percent had a postnatal checkup 3 to 41 days after delivery. CHILD HEALTH Childhood Mortality. Childhood mortality continues to decline in the Philippines. Currently, about one in every 30 children in the Philippines dies before his or her fifth birthday. The infant mortality rate for the five years before the survey (roughly 2004-2008) is 25 deaths per 1,000 live births and the under-five mortality rate is 34 deaths per 1,000 live births. This is lower than the rates of 29 and 40 reported in 2003, respectively. The neonatal mortality rate, representing death in the first month of life, is 16 deaths per 1,000 live births. Under-five mortality decreases as household wealth increases; children from the poorest families are three times more likely to die before the age of five as those from the wealthiest families. There is a strong association between under-five mortality and mother's education. It ranges from 47 deaths per 1,000 live births among children of women with elementary education to 18 deaths per 1,000 live births among children of women who attended college. As in the 2003 NDHS, the highest level of under-five mortality is observed in ARMM (94 deaths per 1,000 live births), while the lowest is observed in NCR (24 deaths per 1,000 live births). NUTRITION Breastfeeding Practices. Eighty-eight percent of children born in the Philippines are breastfed. There has been no change in this practice since 1993. In addition, the median durations of any breastfeeding and of exclusive breastfeeding have remained at 14 months and less than one month, respectively. Although it is recommended that infants should not be given anything other than breast milk until six months of age, only one-third of Filipino children under six months are exclusively breastfed. Complementary foods should be introduced when a child is six months old to reduce the risk of malnutrition. More than half of children ages 6-9 months are eating complementary foods in addition to being breastfed. The Infant and Young Child Feeding (IYCF) guidelines contain specific recommendations for the number of times that young children in various age groups should be fed each day as well as the number of food groups from which they should be fed. NDHS data indicate that just over half of children age 6-23 months (55 percent) were fed according to the IYCF guidelines. HIV/AIDS Awareness of HIV/AIDS. While over 94 percent of women have heard of AIDS, only 53 percent know the two major methods for preventing transmission of HIV (using condoms and limiting sex to one uninfected partner). Only 45 percent of young women age 15-49 know these two methods for preventing HIV transmission. Knowledge of prevention methods is higher in urban areas than in rural areas and increases dramatically with education and wealth. For example, only 16 percent of women with no education know that using condoms limits the risk of HIV infection compared with 69 percent of those who have attended college. TUBERCULOSIS Knowledge of TB. While awareness of tuberculosis (TB) is high, knowledge of its causes and symptoms is less common. Only 1 in 4 women know that TB is caused by microbes, germs or bacteria. Instead, respondents tend to say that TB is caused by smoking or drinking alcohol, or that it is inherited. Symptoms associated with TB are better recognized. Over half of the respondents cited coughing, while 39 percent mentioned weight loss, 35 percent mentioned blood in sputum, and 30 percent cited coughing with sputum. WOMEN'S STATUS Women's Status and Employment.

The basic purpose of the Health Interview Survey is to obtain information about the amount and distribution of illness, its effects in terms of disability and chronic impairments, and the kind of health services people receive. Household variables in this data collection include type of living quarters, size of family, number of families in household, and geographic region. Person variables include sex, age, race, marital status, veteran status, education, income, industry and occupation codes, and limits on activity. The Condition, Doctor Visit, and Hospital files contain information on each reported condition, two-week doctor visit, or hospitalization (twelve-month recall), respectively. The Health Insurance Supplement contains the same information as the Person file and additional questions about health insurance plans. The type of plan, including private, Medicare, Medicaid, military and other plans, and coverage or reasons for lack of coverage are provided. The Alcohol/Health Practices Supplement includes information on diet, smoking and drinking habits, and health problems. The Doctor Services Supplement supplies data on visits to doctors or other health professionals, reasons for visits, health conditions, and operations performed. The Bed days and Dental Care Supplement contains information on the number of bed days, the number of and reason for dental visits, treatment(s) received, type of dentist seen, and travel time for visit. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR -- https://doi.org/10.3886/ICPSR08603.v4. We highly recommend using the ICPSR version as they made this dataset available in multiple data formats.

The purpose of the Health Interview Survey is to obtain information about the amount and distribution of illness, its effects in terms of disability and chronic impairments, and the kinds of health services people receive. There are five types of records in this core survey, each in a separate data file. The Person File (Part 1) includes information on sex, age, race, marital status, Hispanic origin, education, veteran status, family income, family size, major activities, health status, activity limits, employment status, and industry and occupation. These variables are found in the Conditions, Doctor Visits, and Hospital Episodes Files as well. The Person File also supplies data on height, weight, bed days, doctor visits, hospital stays, years at residence, and region variables. The variables in the Household File (Part 2) include type of living quarters, size of family, number of families in the household, presence of a telephone, number of unrelated individuals, and region. The Conditions File (Part 3) contains information for each reported health condition, with specifics on injury and accident reports. The Hospital Episodes File (Part 4) provides information on medical conditions, hospital episodes, type of service, type of hospital ownership, date of admission and discharge, number of nights in hospital, and operations performed. The Doctor Visits File (Part 5) documents doctor visits within the time period and identifies acute or chronic conditions. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR -- https://doi.org/10.3886/ICPSR08337.v4. We highly recommend using the ICPSR version as they made this dataset available in multiple data formats.

Abstract (en): The purpose of the Health Interview Survey is to obtain information about the amount and distribution of illness, its effects in terms of disability and chronic impairments, and the kinds of health services people receive. There are five types of records in this core survey, each in a separate data file. The variables in the Household File (Part 1) include type of living quarters, size of family, number of families in the household, presence of a telephone, number of unrelated individuals, and region. The Person File (Part 2) includes information on sex, age, race, marital status, Hispanic origin, education, veteran status, family income, family size, major activities, health status, activity limits, employment status, and industry and occupation. These variables are found in the Condition, Doctor Visit, and Hospital Episode Files as well. The Person File also supplies data on height, weight, bed days, doctor visits, hospital stays, years at residence, and region variables. The Condition File (Part 3) contains information for each reported health condition, with specifics on injury and accident reports. The Hospital Episode File (Part 4) provides information on medical conditions, hospital episodes, type of service, type of hospital ownership, date of admission and discharge, number of nights in hospital, and operations performed. The Doctor Visit File (Part 5) documents doctor visits within the time period and identifies acute or chronic conditions. A sixth file has been added, along with the five core files. The Health Insurance File (Part 6) documents basic demographic information along with medical coverage and health insurance plans, as well as differentiates between hospital, doctor visit, and surgical insurance coverage. Civilian, noninstitutionalized population of the United States. A multistage probability sample was used in selecting housing units. 2010-09-30 Frequencies and variable labels that were previously incorrect have been corrected.2010-09-09 A technical error has been found and resolved in the processing procedure, in which defined file sets did not match subsequent data sets.2010-09-02 SAS, SPSS, and Stata setup files have been added. Some corresponding documentation has been updated and pre-existing data files have been replaced. A sixth dataset has been added in place of the National Health Survey Procedure Documentation, which can now be found with all other corresponding and added documentation.2006-01-18 File CB8337.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads. face-to-face interviewThese data files contain weights that must be used in any analysis.Per agreement with NCHS, ICPSR distributes the data files and text of the technical documentation for this collection as prepared by NCHS.

Impact of longitudinal adherence on future viral load and CD4 countb'*'.

Study implications for vaccine outreach strategies.

Demographic characteristics and nutrition status of SIVH children less than 18 years resettling to the US, 2009–2017 (n = 15,729)a.

Key themes.

Multivariable multinomial logistic regression of pediatric specialty clinic visit outcome during 2016–2019, interacting visit year and race/ethnicity (N = 9,346 visits).