Quality Process Measures
The Centers for Medicare & Medicaid Services (CMS) publishes a set of data every quarter covering several measures for process of care for blood clot and stroke. This data is submitted to CMS by the hospitals using clinical chart data.
For more information visit the CMS Hospital Compare Web site.
Readmission rates
Readmission rates includes patients readmitted to a hospital within 30 days of discharge from a previous hospital stay for heart attack, heart failure, or pneumonia. Readmission rates are reported for Medicare patients only. Readmissions rates displayed on this site reflect 3 years of data. For more information, visit the CMS Hospital Compare Web site.
Thirty Day Mortality
CMS 30-day mortality rates take into account deaths within 30 days from all causes after an initial hospitalization with a principal diagnosis of heart attack, heart failure, or pneumonia. Mortality rates are reported for Medicare patients only. Mortality rates displayed on this site reflect 3 years of data. For more information, visit the CMS Hospital Compare Web site.
Inpatient Quality Indicators
The inpatient quality indicators (IQIs) are a set of measures that can be used with hospital inpatient discharge data to provide a perspective on quality. Mortality indicators for inpatient procedures include procedures for which mortality has been shown to vary across institutions and for which there is evidence that high mortality may be associated with poorer quality of care. Utilization indicators examine procedures whose use varies significantly across hospitals and for which questions have been raised about overuse, underuse, or misuse.
Discharge data submitted by the hospitals are entered by IDPH into software provided by the Agency for Healthcare Research and Quality (AHRQ). The measures of care listed are authored by AHRQ.
AHRQ Version 5.0.3 software is utilized with risk adjustment as appropriate. For additional information about AHRQ measures and risk adjustment, read about the Quality Indicators at http://www.qualityindicators.ahrq.gov/.
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Pediatric Quality Indicators
The Pediatric Quality Indicators (PDIs) are a set of measures that reflect quality of care inside hospitals and identify potentially avoidable hospitalizations among children (PDI). They focus on potentially preventable complications and iatrogenic events for pediatric patients treated in hospitals, and on preventable hospitalizations among pediatric patients.
Discharge data submitted by the hospitals are entered by IDPH into software provided by the Agency for Healthcare Research and Quality (AHRQ). The measures of care listed are authored by AHRQ.
AHRQ Version 5.0.3 software is utilized with risk adjustment as appropriate. For additional information about AHRQ measures and risk adjustment, read about the Pediatric Quality Indicators at http://www.qualityindicators.ahrq.gov/.
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Health Care-associated Infection Methodology
Standardized Infection Ratio (SIR)
The standardized infection ratio (SIR) is a measure that compares a facility’s burden of Health care–associated infections (HAI) to a predicted number based on a national referent population. It is a risk-adjusted summary statistic used to measure the relative difference in HAI during a given reporting period compared to that of a national referent population. The SIR adjusts for risk factors found to be significant predictors of HAI incidence in a facility.
The SIR is the ratio of the actual number of HAIs reported to what would be predicted, given the standard population.
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If the SIR value is greater than 1.0, there are more infections than predicted.
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If the SIR value is less than 1.0, then fewer infections occurred than predicted.
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If the facility SIR is 1.0, then the number of observed infections is the same as or similar to the predicted number.
The three categories summarizing how a hospital compares to the national infection data are highlighted below:
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Statistically more (Higher) infections than predicted based on national infection data;
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Statistically fewer (Lower) infections than predicted based on national infection data;
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Statistically similar (Similar) infections as predicted based on the national infection data.
Central Line-Associated Bloodstream Infections
The National Healthcare Safety Network (NHSN), a secure, Internet-based surveillance system managed by the Division of Healthcare Quality Promotion at the Centers for Disease Control and Prevention, is used by all Illinois hospitals with adult, pediatric and neonatal intensive care units to collect data on central line-associated bloodstream infections.
The reporting criteria and methods required by NHSN and a summary of the national level data are detailed on the NHSN Web site.
While the data collection methodology is identical in adult and pediatric intensive care settings, in neonatal intensive care unit (NICU) locations (level III or level II/III), data on central line-associated bloodstream infections are collected for each of five birth-weight categories (<750 g, 751-1000 g, 1001-1500 g, 1501-2500 g, and >2500 g) and for catheter type (central line and umbilical). The risk of bloodstream infections in neonates varies by birth-weight and type of catheter.
NHSN 2015 Baseline
Prior to 2015, the CLABSI predicted number was calculated using the NHSN published device-associated national pooled means (2006-2008 baseline time period) for each individual location. In 2015, the CDC modified the risk adjustment factors that are used to calculate the predicted number of infections in the SIR and updated the national referent population (see CLABSI Risk Adjustment Factors below). Under the 2015 baseline, NHSN started using four separate statistical models based on facility type: acute care hospital, critical access hospital, inpatient rehabilitation facility, and long-term acute care hospital. In addition to the change to risk adjustment factors, SIRs under the new 2015 baseline are calculated using the national data collected during 2015.
CLABSI Risk Adjustment factors
The predicted number of infections is calculated based on 2015 national HAI aggregate data and patient risk at each health facility type. Negative binomial regression models are used to calculate the number of predicted events under the 2015 baseline. For acute care hospitals, the number of predicted events calculated under the 2015 baseline for CLABSI is risk adjusted based on the following factors found to be statistically significant predictors of CLABSI incidence: the CDC location (unit type), medical school affiliation, facility bed size, and facility type. For NICU, birthweight was the statistically significant predictor. None of the risk factors were significant predictors of CLABSI in the critical access settings, therefore, the predicted events are calculated using the overall (unadjusted) national CLABSI experience in critical access hospitals.
Surgical Site Infections (coronary artery bypass surgery (CABG) and knee replacement (KPRO))
Surgical Site Infections (SSIs) are infections that occur in the wound created by an invasive surgical procedure and are one of the most important causes of healthcare-associated infections (HAI). The surgeries monitored for SSI in Illinois include coronary artery bypass surgery (CABG) procedures, and knee replacement (KPRO) surgery.
The CDC describes three types of surgical site infections:
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Superficial incisional SSI. This infection occurs just in the area of the skin where the surgical incision was made.
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Deep incisional SSI. This infection occurs beneath the incision area in muscle tissue and in fascia, the tissue surrounding the muscles.
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Organ or space SSI. This type of infection can be in any area of the body other than skin, muscle, and fascia that was involved in the surgery, such as a body organ or a space between organs.
IDPH monitors and reports inpatient KPRO and CABG Deep Incisional Primary and Organ/Space SSIs that were identified during admission or readmission to Illinois facilities as defined in the NHSN Manual.
SSI Risk Adjustment factors
The predicted number of infections is calculated based on 2015 national HAI aggregate data and patient risk at each health facility type. The logistic regression models are used to calculate the number of predicted SSI events under the 2015 baseline.
For acute care hospitals, the number of predicted events calculated under the 2015 baseline for SSI (CABG and KPRO) is risk adjusted based on the following factors found to be statistically significant predictors of SSI incidence:
CABG: gender, diabetes, trauma, ASA, wound class, medical school affiliation, facility bed size, age, duration, BMI, and age-gender interaction.
KPRO: gender, trauma, anesthesia, ASA, wound class, medical school affiliation, facility bed size, age, duration, BMI, and procedure type.
Methicillin-Resistant Staphylococcus aureus (MRSA) and Clostridium difficile Infections in Illinois Hospitals
As of January 1, 2012 all acute care hospitals in Illinois began reporting MRSA bloodstream infections and CDI using the National Healthcare Safety Network's (see above) Multidrug-Resistant Organism (MDRO) Laboratory-Identified (LabID) Event module. The LabID Event method enables facilities to report proxy measures for healthcare-associated infections based on data obtained from the laboratory without clinical evaluation of the patient. Positive lab results (LabID Events) are categorized as healthcare facility-onset (HO) or community-onset (CO) based on when an individual is admitted to a hospital as a patient and when the lab specimen was obtained. LabID Events are categorized as HO if the specimen was collected on or after the fourth day of an inpatient hospital stay. Events are categorized as CO if the specimen was collected during the first 3 days of an inpatient stay.
MRSA bloodstream infections - NHSN LabID Event Reporting
The MRSA LabID standardized infection ratio (SIR) is a measure that compares a facility’s burden of MRSA bloodstream infections to a predicted number based on a national referent population. A facility’s MRSA LabID SIR is calculated as follows:
SIR = Number of observed HO MRSA LabID events
Number of predicted HO MRSA LabID events
Numerator: Only HO, non-duplicate MRSA blood LabID events are included in the numerator.
Denominator: NHSN uses risk models and facility patient days to calculate the number of predicted HO MRSA bacteremia events at a facility. In 2015, CDC modified the risk adjustment factors used in the models and updated national baseline data that are used as a basis for comparison in SIR calculations. Under the 2015 baseline, NHSN started using four separate models based on facility type: acute care hospital, critical access hospital, inpatient rehabilitation facility, and long-term acute care hospital. The risk adjustment factors (e.g., medical school affiliation, number of ICU beds, and CO MRSA prevalence rate) included in the MRSA model depend on the facility type. The facility patient days used to calculate the number of predicted MRSA events includes the total number of facility-wide patient days minus inpatient rehabilitation facility and inpatient psychiatric facility locations with a separate CMS Certification Number (CCN).
Note: SIRs are calculated only if the number of predicted events is greater than or equal to 1.
Clostridium difficile infections - NHSN LabID Event Reporting
The CDI LabID SIR is a measure that compares a facility’s burden of CDI to a predicted number based on a national referent population. A facility’s CDI LabID SIR is calculated as follows:
SIR = Number of observed HO CDI LabID events
Number of predicted HO CDI LabID events
Numerator: Only incident, HO, non-duplicate CDI LabID events are included in the numerator.
Denominator: NHSN uses risk models and facility patient days to calculate the number of predicted HO CDI events at a facility. Under the 2015 baseline, NHSN started using four separate CDI models based on facility type: acute care hospital, critical access hospital, inpatient rehabilitation facility, and long-term acute care hospital. The risk adjustment factors (e.g., CDI test type and CO CDI prevalence rate) included in the model depend on the facility type. The facility patient days used to calculate the number of predicted CDI events includes the total number of facility-wide patient days minus inpatient rehabilitation facility and inpatient psychiatric facility locations with a separate CCN minus baby-based locations (e.g., neonatal intensive care units, special care nurseries, well-baby nurseries, and newborns in labor and delivery units).
Notes: SIRs are calculated only if the number of predicted events is greater than or equal to 1. Additionally, NHSN will not calculate a CDI SIR for any quarter that has an extreme outlier inpatient CO prevalence rate, defined as greater than 2.6 CO events per 100 admissions.
Statewide Trends in Methicillin-Resistant Staphylococcus aureus (MRSA) and Clostridium difficile based on Hospital Discharge Data
Methicillin-Resistant Staphylococcus aureus (MRSA) Trends in Illinois
Analysis in these sections was conducted using hospital discharge data, which are routinely collected and provided to the Illinois Department of Public Health for all acute care hospitals in Illinois. The unit of analysis is the hospital discharge, not the person or patient. If a person is admitted to the hospital multiple times during the course of a year, that person will be counted each time as a separate "discharge" from the hospital.
Up to 25 diagnosis codes for each discharge can be included in the analysis.
C. difficile Trends in Illinois
Analysis in these sections was conducted using hospital discharge data, which are routinely collected and provided to the Illinois Department of Public Health for hospitals in Illinois. The unit of analysis is the hospital discharge, not the person or patient. A person admitted to the hospital multiple times during the course of a year will be counted each time as a separate "discharge" from the hospital.
Up to 25 diagnosis codes for each discharge can be included in the analysis.
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Patient safety
The patient safety indicators (PSIs) are a set of measures that screen for adverse events that patients experience as a result of exposure to the health care system. These events are likely amenable to prevention by changes at the system or provider level.
Discharge data submitted by the hospitals, are entered by IDPH into software provided by the Agency for Healthcare Research and Quality (AHRQ). The measures of care listed are authored by AHRQ.
AHRQ Version 5.0.3 software is utilized with risk adjustment as appropriate. For additional information about AHRQ measures and risk adjustment, read about the Patient Safety Indicators at http://www.qualityindicators.ahrq.gov/.
Breast Feeding
The breast feeding measures are calculated from birth certificate data submitted by birthing hospitals to the Vital Records program of the Illinois Department of Public Health. Questions about breast feeding were incorporated as part of the US Standard Certificate Revisions recommended by the National Center for Health Statistics (NCHS). In January 2013, the question for breast feeding was revised. The question asks:
How is the infant being fed? (breast milk only, formula only, both breast milk and formula, neither breast milk nor formula, unknown)
Breastfeeding is reported by hospital as the percentage of infants who are exclusively breastfed, exclusively formula fed, and infants who received any breastfeeding (those who are exclusively breastfed or who received both breast milk and formula). The denominator for all measures is the number of total births in the hospital.
These counts are based on self-reporting of the mothers and hospital staff. The rates are preliminary estimates and subject to ongoing and annual data revision. As such, these counts may vary for the same period based on final counts produced annually.
Satisfaction
The HCAHPS (Hospital Consumer Assessment of Healthcare Providers and Systems) survey is the first national, standardized, publicly reported survey of patients' perspectives of hospital care. HCAHPS (pronounced “H-caps”), also known as the CAHPS® Hospital Survey, is a standardized survey instrument and data collection methodology for measuring patients’ perceptions of their hospital experience.
The HCAHPS survey asks discharged patients 27 questions about their recent hospital stay. The survey contains 18 questions about critical aspects of patients’ hospital experiences (communication with nurses and doctors, the responsiveness of hospital staff, the cleanliness and quietness of the hospital environment, pain management, communication about medicines, discharge information, overall rating of hospital, and would they recommend the hospital). The survey also includes four items to direct patients to relevant questions, three to adjust for the mix of patients across hospitals, and two items that support Congressionally-mandated reports.
The HCAHPS survey is administered to a random sample of adult patients across medical conditions between 48 hours and six weeks following discharge; the survey is not restricted to Medicare beneficiaries. Participating hospitals may either use an approved survey vendor, or collect their own HCAHPS data (if approved by CMS to do so). To accommodate the needs of hospitals, HCAHPS can be implemented in four different survey modes: mail, telephone, mail with telephone follow-up, or active interactive voice recognition (IVR). Hospitals may either integrate HCAHPS with their own patient surveys, or use HCAHPS by itself. Hospitals must survey patients throughout each month of the year. The survey is available in official English, Spanish, Chinese, Russian and Vietnamese versions.
The survey itself, as well as detailed information on sampling, data collection and coding, and file submission, are contained in the HCAHPS Quality Assurance Guidelines, Version 4.0, found at the official HCAHPS Web site, https://www.medicare.gov/hospitalcompare/search.html.
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Services
Discharge data from the Illinois Department of Public Health is utilized to calculate information on utilization of services. Data on the number of inpatients, their length of stay and median charges includes the use of DRG grouping software from 3M to combine these discharge data records into the various listed conditions. The median stay and charges are then calculated by listed service for each facility. A patient’s length of stay for any listed condition will vary. Data on outpatient procedure volume and charges includes the use of clinical classification software (CCS) for clustering patient diagnoses and procedures into a manageable number of clinically meaningful categories. The CCS was developed by the Healthcare Cost and Utilization Project https://www.hcup-us.ahrq.gov/datainnovations/icd10_resources.jsp. Data on diagnostic procedure visit volume and charges includes the use of revenue codes from the discharge data set. Median charges shown for all displayed services are list prices that may be discounted and paid by health insurance companies.
Nurse Staffing
Hospitals gather internal data related to the type and number of monthly nurse hours worked. They also gather data on the number of days patients spend within specific categories of service. This information is submitted quarterly to IDPH where the data is combined. In addition, hospitals submit annual data on the number of nurse staffing position vacancies and turnover rates.
Infection Prevention Staffing
The number of infection prevention and control staff, both total and those certified in infection control, is gathered from data submitted by hospitals to the Illinois Department of Public Health through the Annual Hospital Profile survey. The number of beds used in per 100 beds calculation reflects the total number of authorized beds established by certificate of need at the Illinois Department of Public Health.
Lactation Consultant Staffing
The number of specially trained lactation consultants and the number of International Board Certified lactation consultants is gathered from data submitted by hospitals to the Illinois Department of Public Health through the Annual Hospital Profile survey. The number of live births for each hospital is calculated from hospital discharge data submitted by hospitals to the Illinois Department of Public Health.
Authorized Beds
The bed numbers refer to the number of authorized beds approved by the Health Facilities and Services Review Board. These bed numbers may change frequently as a result of the regular Board meetings, and will be updated regularly as other data is added to the site.
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Emergency Department Services and Utilization
Timely and effective emergency department care is important because delays in receiving care in the emergency department and/or in being admitted as an inpatient can reduce the quality of care and increase risks and discomfort for patients with serious illnesses or injuries.
Data for Emergency Department waiting times come from Hospital Compare (
hospitalcompare.hhs.gov). Hospitals abstract the data for these measures from the medical records of their patients and submit the information to the Center for Medicare and Medicare Services (CMS).
Emergency room bypass hours are calculated from data submitted by hospitals to the Illinois Department of Public Health through its Web-based Illinois Hospital Bypass System. Hospitals fulfill reporting requirements by accessing the system at the start of the bypass period, indicating that it is on bypass. They then access the system at the end of the bypass period to indicate that the period has ended. Not all hospitals experience the need to place their emergency room on "bypass".
The number of patients seen in the emergency room, both those admitted and those treated and released as outpatients, is calculated from discharge data provided by the Illinois Department of Public Health.
The percent of patients who left the emergency room either before being seen or against medical advice is also calculated from discharge data provided by the Illinois Department of Public Health.
Patient Insurance Mix
Hospitals gather data on the type and volume of insurance providers of the patients seen in their facility. This information is submitted to the Illinois Department of Public Health annually, as part of the Annual Hospital Questionnaire (AHQ). Data on patient volume by insurance type was extracted as submitted to provide the percentage of hospital visits by major categories of insurance provider, with private pay and charity included where no insurance coverage exists.
Air Pollution Measure
Daily Fine Particulate Matter
The fine particulate matter measure comes from the U.S. County Health Rankings website (http://www.countyhealthrankings.org/app/illinois/2019/downloads) and is made available from the CDC WONDER program. CDC WONDER provides geographically aggregated daily measures of fine particulate matter in the outdoor air. Fine particulate matter, or PM 2.5 particles, are air pollutants with an aerodynamic diameter less than 2.5 micrometers. Data are available by place (combined 48 contiguous states plus the District of Columbia, region, division, state, county), time (year, month, day) and specified fine particulate matter (µg/m³) value. County-level and higher data are aggregated from 10 kilometer square spatial resolution grids. Further information about methodology is available on https://www.cdc.gov/air/default.htm.
Disease Prevalence and Health Behavior Measures
Asthma Prevalence
Data from the Illinois Behavioral Risk Factor Surveillance System (Illinois BRFSS) was used to present prevalence of asthma. Asthma prevalence is defined as adults 18 years of age or older having "Current Asthma". "Current Asthma" means respondents to the BRFSS telephone survey indicated that asthma was current and active at the time of telephone interview. (See Behavioral Risk Factor Surveillance System).
Diabetes Prevalence
Data from the Illinois Behavioral Risk Factor Surveillance System (Illinois BRFSS) was used to present prevalence of diabetes in Illinois counties. Diabetes prevalence is defined as adults, 18 years of age or older, who responded to the BRFSS telephone interview that they had been told they had diabetes (see Behavioral Risk Factor Surveillance System).
Obesity Prevalence
Data from the Illinois Behavioral Risk Factor Surveillance System (Illinois BRFSS) was used to present prevalence of obesity in Illinois counties. Obesity prevalence is defined as the percentage of adults age 18 or older with a body mass index greater than or equal to 30. Data on height and weight is collected through BRFSS telephone interview and used to calculate body mass index (see Behavioral Risk Factor Surveillance System).
Current Smokers
Data from the Illinois Behavioral Risk Factor Surveillance System (Illinois BRFSS) was used to present information on the percentage of current smokers in Illinois counties. Respondents to the BRFSS telephone survey indicated their current smoking status (see Behavioral Risk Factor Surveillance System).
Physical Inactivity
Data from the Illinois Behavioral Risk Factor Surveillance System (Illinois BRFSS) was used to present information on physical activity behaviors of residents of Illinois counties. Respondents to the BRFSS telephone survey were categorized as physically inactive if they reported no leisure time physical activity within the last thirty days (see Behavioral Risk Factor Surveillance System).
Poor Mental Health Days
Data from the Illinois Behavioral Risk Factor Surveillance System (Illinois BRFSS) was used to present the percentage of the adult population (age 18 or older) who responded they had eight or more “poor mental health days” in the past 30 days. The data is collected through the BRFSS telephone interview and is based on responses to the question “Thinking about your mental health, which includes stress, depression, and problems with emotions, for how many days during the past 30 days was your mental health not good?”. Data is available at the Illinois county geographical level. For more information about the Illinois BRFSS see /contents/view/data_sources/#brfss.
Prevalence of Heart Attack
Data from the Illinois Behavioral Risk Factor Surveillance System (Illinois BRFSS) was used to present prevalence of diagnosis of heart attack in Illinois counties. Heart attack prevalence is defined as adults, 18 years of age or older, who responded to the BRFSS telephone interview that they had been told they had heart attack (see Behavioral Risk Factor Surveillance System).
Prevalence of Angina or Coronary Heart Disease
Data from the Illinois Behavioral Risk Factor Surveillance System (Illinois BRFSS) was used to present prevalence of diagnosis of angina (coronary heart disease) in Illinois counties. Angina prevalence is defined as adults, 18 years of age or older, who responded to the BRFSS telephone interview that they had been told they had angina (see Behavioral Risk Factor Surveillance System).
Prevalence of Stroke
Data from the Illinois Behavioral Risk Factor Surveillance System (Illinois BRFSS) was used to present prevalence of diagnosis of stroke in Illinois counties. Stroke prevalence is defined as adults, 18 years of age or older, who responded to the BRFSS telephone interview that they had been told they had a stroke (see Behavioral Risk Factor Surveillance System).
Behavioral Health Hospitalizations
The Clinical Classification Software (CCS) for ICD-10-CM was used to analyze the Behavioral Health hospitalization measures for Mood Disorders, Alcohol-related Disorders, Substance-related Disorders, and Anxiety in the adult population (18 years and older). The CCS was developed as part of the Healthcare Cost and Utilization Project sponsored by the Agency for Health Research and Quality. The software was developed for use with hospital discharge data. The CCS tool collapses the multitude of ICD-10-CM codes (over 68,000 diagnosis codes) into a number of smaller clinically meaningful categories. It is often used in descriptive analyses. The CCS includes Mental Health and Substance Use disorder categories.
In this case, the Illinois Hospital Discharge data was utilized as the data source and includes hospitalization discharges with a billing code falling within one of the four CCS categories outlined above (for mood, alcohol, substance related disorders, and anxiety). Data includes only non-federal, acute care and behavioral health hospitals in Illinois. All Illinois Veterans Affairs and state run behavioral health hospitals are excluded.
Data for geographic areas (county, zip code, Cook County sub-regions and Illinois regions) and race/ethnicity categories with less than 20 discharges for the reporting period were suppressed due to statistical imprecision and patient confidentiality. Rates reported are average annual rates per 10,000 area population. Rate calculation for a given geographic area (zip/county/state region) or race/ethnicity category was suppressed when the combined population estimate was less than 1000.
Further information about the Clinical Classification Software can be found at: https://www.hcup-us.ahrq.gov/toolssoftware/ccs/CCSUsersGuide.pdf.
Emergency Department Measures
Interest in the study of emergency department utilization is growing rapidly. Emergency department (ED) visit volume has surged in recent years, and many people are using these services as a primary means of obtaining medical care. Along with demographic components such as age, sex, race and ethnicity, payer and income level, it is useful to look at the type of visit associated with emergency department use (necessary or unnecessary) and ED use for ambulatory care-sensitive conditions such as asthma and diabetes.
Emergency Department Visit Acuity Measures
The Illinois Department of Public Health used an algorithm to help classify ED utilization developed by the New York University Center for Health and Public Service Research. Data used as input to this classification system comes from the Illinois discharge data collection system and includes outpatient discharges with an emergency department billing code. These data currently exclude those cases known to have resulted in admission to a hospital as an inpatient; however they do include cases where an outpatient surgery and/or observation care may have been given. The algorithm classifies ED cases into four major categories of visit necessity after isolating injury, drug, alcohol and mental illness cases for separate study. Any cases not meeting any of these criteria are labeled "unclassified".
The four major groups of ED care are as follows:
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non-emergent
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emergent but primary care treatable
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emergent but primary care avoidable
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emergent and unavoidable
The first three groups are often combined, resulting in two final groupings labeled 1) all primary care sensitive; and 2) emergent. Complete documentation on the development and use of the ED utilization algorithm is detailed by the New York University research team. Due to small numbers, data for drug, alcohol and mental illness cases were combined for analysis into the separate Behavioral Health ED visit category. Injury data is also shown separately.
Data for geographic areas (county, zip code, Cook County sub-regions and Illinois regions) with less than 20 visits in a given emergency room category were suppressed due to statistical imprecision and patient confidentiality.
Data by visit category is expressed as a percentage of all Emergency Department visits and crude rate per 10,000 population within a geographic locale. Charges shown are gross charges established by hospitals each year, not actual dollar amounts received in payment. All patients are charged the same gross charge (or list price) for the same services before applying any discounts.
Emergency Department Asthma and Diabetes Measures
Asthma
The first-listed (or primary diagnosis) was used to identify the ED discharges for asthma. The data source was the Illinois discharge data collection system. and includes outpatient discharges with an emergency department billing code.These data currently exclude those cases known to have resulted in admission to a hospital as an inpatient; however they do include cases where an outpatient surgery and/or observation care may have been given.
Asthma ED discharges were defined as follows:
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pediatric, if patient age was less than 18 years; and
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adult for patients 18 years or older
Data for geographic areas (county, zip code, Cook County sub-regions and Illinois regions) and race/ethnicity categories with less than 20 discharges in for the reporting period was suppressed due to statistical imprecision and patient confidentiality. Rates reported for pediatric and adult populations are three-year average rates per 10,000 area population. Rate calculation for a given geographic area (zip/county/state region) or race/ethnicity category was suppressed when the data reporting period combined population estimate was less than 1000.
Type II Diabetes
The data source was the Illinois discharge data collection system which includes outpatient discharges with emergency department billing codes. These data currently exclude those cases known to have resulted in admission to a hospital as an inpatient; however they do include cases where an outpatient surgery and/or observation care may have been given. Only patients aged 18 years or older were included in the analysis. Data for geographic areas (county, zip code, Cook County sub-regions and Illinois regions) and race/ethnicity categories with less than 20 discharges in for the data reporting period was suppressed due to statistical imprecision and patient confidentiality. Data range period average rates are reported per 10,000 area population. Rate calculation for a given geographic area (zip/county/state region) or race/ethnicity category was suppressed when the data reporting period combined population estimate was less than 1000.
Emergency Department Behavioral Health Measures
The Clinical Classification Software (CCS) for ICD-10-CM was used to analyze the Behavioral Health measures for Mood Disorders, Alcohol-related Disorders, Substance-related Disorders, and Anxiety in the adult population (18 years and older). The CCS was developed as part of the Healthcare Cost and Utilization Project sponsored by the Agency for Health Research and Quality. The software was developed for use with hospital discharge data. The CCS tool collapses the multitude of ICD-10-CM codes into clinically meaningful categories. It is often used in descriptive analyses. The CCS includes Mental Health and Substance Use disorder categories.
In this case, the Illinois Hospital Discharge data was utilized as the data source and includes all outpatient discharges with an emergency department billing code. These data currently exclude those cases known to have resulted in admission to a hospital as an inpatient.
Data for geographic areas (county, zip code, Cook County sub-regions and Illinois regions) and race/ethnicity categories with less than 20 discharges within the data reporting period were suppressed due to statistical imprecision and patient confidentiality. Rates reported are average annual rates over the data range reporting period per 10,000 area population. Rate calculation for a given geographic area (zip/county/state region) or race/ethnicity category was suppressed when the combined population estimate was less than 1000 for the data reporting period.
Emergency Department Hypertension
Emergency Department visits for hypertension were defined as visits with a primary diagnosis of hypertension and are based on the Agency for Health Research and Quality prevention quality indicator PQI 7 (for hypertension). Specifications exclude all obstetric-related visits, visits associated with cardiac procedures, Stage IV kidney disease, or transfers from other health care facilities. The data source was the Illinois discharge data collection system and includes all 2012, 2013, and 2014 outpatient discharges with an emergency department billing code. These data currently exclude those cases known to have resulted in admission to a hospital as an inpatient; however they do include cases where an outpatient surgery and/or observation care may have been given. Only patients aged 18 years or older were included in the analysis. Data for geographic areas (county, zip code, Cook County sub-regions and Illinois regions) and race/ethnicity categories with less than 20 discharges in 2012-2014 were suppressed due to statistical imprecision and patient confidentiality. Three-year average crude rates are reported per 10,000 area population. Rate calculation for a given geographic area (zip/county/state region) or race/ethnicity category was suppressed when the 2012-2014 combined population estimate was less than 1000.
HIV/AIDS
HIV Prevalence
The Illinois electronic HIV/AIDS registry (eHARS) maintains data on people ever diagnosed with HIV disease in Illinois. The Illinois eHARS contains >95% of the number of persons estimated by CDC to be newly diagnosed with HIV in Illinois annually.
The prevalence rate is determined using data reported to eHARS. To determine the prevalence rate, the number of persons living with diagnosed HIV disease whose last known address was in Illinois and who were last known to be alive as of 12/31/2018 and reported to eHARS by June 30th, 2019 was used as the numerator. The most recently reported address in eHARS was used to calculate county-level incidence rates; county HIV prevalence rates can be affected by the presence of correctional facilities in the county. Vintage 2018 U.S. Census county population estimates were used as the denominator to determine the HIV prevalence rate per 100,000 population..
HIV Incidence
The Illinois electronic HIV/AIDS registry (eHARS) maintains data on people ever diagnosed with HIV disease in Illinois. The Illinois eHARS contains >95% of the number of persons estimated by CDC to be newly diagnosed with HIV in Illinois annually.
The HIV disease incidence rate is the number of persons newly diagnosed with HIV disease per 100,000 population. Due to the low number of newly reported HIV cases by county, incidence data reported to eHARS during 2016–2018 were combined to calculate a three-year incidence rate. Cases of HIV disease reported to eHARS with a diagnosis date during 1/1/2016 to 12/31/2018 and reported to eHARS as of 6/30/2019 were used to determine the numerator. The address at diagnosis was utilized to calculate county incidence rates. Vintage 2018 U.S. Census county population estimates for 2016–2018 were used as the denominator to determine the incidence rate per 100,000 population.
Rates are not displayed for counties with <3 newly diagnosed cases of HIV disease during 2016–2018
Injury
Inpatient Hospitalizations
The data source was the Illinois discharge data collection system and includes inpatient discharges based on ICD 10 CM codes. Hospital admissions with the principal diagnosis code indicating injury as the reason for hospitalization are included in this measure. The codes for all Injuries include traumatic brain injury (TBI), unintentional falls, motor vehicle traffic (MVT), assault, fire and firearms as well as all other causes of injury included in the external cause codes of the ICD 10 CM coding scheme.
The first-listed (or primary diagnosis) was used to identify the inpatient discharges for injuries. Guidance from the Council of State and Territorial Epidemiologists (CSTE) was used to define the indicator and sub-indicators and can be found here: GeneralInjuryIndicators - Injury_Surveillance_Methods_Toolkit (cste.org).
Injury Inpatient discharges were defined as follows:
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pediatric, if patient age was less than 18 years;
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adult for patients 18 – 64 years old; and
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Senior 65+ years or older
Data for geographic areas (county, zip code, Cook County sub-regions and Illinois regions), age groups and race/ethnicity categories with less than 20 discharges in for the reporting period was suppressed due to statistical imprecision and patient confidentiality. Rates reported for pediatric, adult and senior populations are three-year average rates per 10,000 area population. Rate calculation for a given geographic area (zip/county/state region), age group or race/ethnicity category was suppressed when the data reporting period combined population estimate was less than 1000.
Outpatient Emergency Department Visits
The data source was the Illinois discharge data collection system and includes outpatient treat and release ED visits based on ICD 10 CM codes. The most inclusive method (all diagnosis codes and external cause codes) was used to pull the data. The codes for all Injuries include traumatic brain injury (TBI), unintentional falls, motor vehicle traffic (MVT), assault, fire and firearms as well as all other causes of injury included in the external cause codes of the ICD 10 CM coding scheme.
The presence of an ICD 10 CM Injury code in any listed diagnosis code or external cause code slot was used to identify the outpatient ED visits for injuries. Guidance from the Council of State and Territorial Epidemiologists (CSTE) was used to define the indicator and sub-indicators and can be found here:
GeneralInjuryIndicators - Injury_Surveillance_Methods_Toolkit (cste.org).
Injury outpatient discharges were defined as follows:
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pediatric, if patient age was less than 18 years;
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adult for patients 18 – 64 years old; and
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Senior 65+ years or older
Data for geographic areas (county, zip code, Cook County sub-regions and Illinois regions), age groups and race/ethnicity categories with less than 20 discharges in for the reporting period was suppressed due to statistical imprecision and patient confidentiality. Rates reported for pediatric, adult and senior populations are three-year average rates per 10,000 area population. Rate calculation for a given geographic area (zip/county/state region), age group or race/ethnicity category was suppressed when the data reporting period combined population estimate was less than 1000.
Maternal and Child Health
Low Birth Weight
Birth certificate data collected by the Illinois Department of Public Health, Division of Vital Records were used to calculate the percentage of live births that were low birth weight (less than 2,500 grams). Births with a birth weight less than 350g or a missing birth weight were excluded from analysis. Births occurring out-of-state to Illinois residents are included in the analysis.
Preterm Birth
Birth certificate data collected by the Illinois Department of Public Health, Division of Vital Records were used to calculate the percentage of live births that were premature/preterm at the time of delivery (born at less than 37 completed weeks of gestation). Births that had a gestational age less than 17 weeks or more than 47 weeks were excluded from analysis, in accordance with data quality standards set by the Center for Disease Control and Prevention’s National Center for Health Statistics. Births occurring out-of-state to Illinois residents are included in the analysis.
Due to statistical imprecision and confidentiality concerns, data were suppressed for geographic areas and race/ethnicity categories with fewer than 100 total live births or fewer than 10 preterm births during the reporting period. Percentages reported are three-year averages for the population.
Breastfed in Delivery Hospital
Birth certificate data collected by the Illinois Department of Public Health, Division of Vital Records were used to calculate the percentage of live births with any breastfeeding (either exclusively or mixed breast/formula feeding) during the delivery hospitalization. Births that were missing infant feeding status on the birth certificate were excluded. Births occurring out-of-state to Illinois residents are included in the analysis.
Due to statistical imprecision and confidentiality concerns, data were suppressed for geographic areas and race/ethnicity categories with fewer than 100 total live births or fewer than 10 breastfed births during the reporting period. Percentages reported are three-year averages for the population.
Prenatal Care
Birth certificate data collected by the Illinois Department of Public Health, Division of Vital Records were used to calculate percentage of live births where the mother entered prenatal care during the first trimester of pregnancy. Timing of prenatal care entry was calculated based on the date of the first prenatal care visit in comparison to the start of the pregnancy, based on the gestational age at delivery. Those entering prenatal care during week 13 or earlier in pregnancy were considered to have started prenatal care in the first trimester. Births with a missing or invalid prenatal care entry date or a missing gestational age at delivery on the birth certificate were excluded. Births occurring out-of-state to Illinois residents are included in the analysis.
Due to statistical imprecision and confidentiality concerns, data were suppressed for geographic areas and race/ethnicity categories with fewer than 100 total live births or fewer than 10 births that entered prenatal care during the first trimester during the reporting period. Percentages reported are three-year averages for the population.
Smoking During Pregnancy
Birth certificate data collected by the Illinois Department of Public Health, Division of Vital Records were used to calculate the percentage of live births where the mother smoked any cigarettes during pregnancy. The birth certificate asks about the number of cigarettes smoked during each trimester of pregnancy and any responses above “zero” were classified as any smoking during pregnancy. Births that were missing smoking status on the birth certificate were excluded. Births occurring out-of-state to Illinois residents are included in the analysis.
Due to statistical imprecision and confidentiality concerns, data were suppressed for geographic areas and race/ethnicity categories with fewer than 100 total live births or fewer than 10 where the mother smoking during pregnancy during the reporting period. Percentages reported are three-year averages for the population.
Teen Birth Rate
The teen birth rate is the number of births to Illinois resident females ages 15-19 divided by the total number of females ages 15-19 in the population, multiplied by 1,000. Birth certificate data collected by the Illinois Department of Public Health, Division of Vital Records were used to identify the numerator (number of live births where the mother was 15-19 years old at the time of delivery). Births occurring out- of-state to Illinois residents are included in the analysis. Bridged race post-censal estimates (
https://www.cdc.gov/nchs/nvss/bridged_race.htm) were used as population denominators in the calculation of teen birth rates.
Due to statistical imprecision and confidentiality concerns, data were suppressed for geographic areas and race/ethnicity categories with fewer than 100 total females 15-19 in the population or fewer than 10 teen births during the reporting period. Rates reported are three-year averages for the population.
Oral Health Measures
Emergency Department: Non-Traumatic Dental Conditions (NTDC)
The data source was the Illinois discharge data collection system and includes outpatient discharges with an emergency department billing code. The most inclusive method (all diagnosis codes and reason for visit) was used to pull the data. The codes for NTDC are a subset of all oral and facial related codes and include caries, periodontal disease, erosion, occlusal anomalies, cysts, impacted teeth, teething, and all other non-traumatic conditions associated with the oral cavity. Diagnoses that are deemed due to trauma are excluded from this definition.
The first-listed (or primary diagnosis) was used to identify the ED discharges for NTDC. The data source was the Illinois discharge data collection system. and includes outpatient discharges with an emergency department billing code. These data include all NTCD diagnosis codes and reason for visit.
NTDC ED discharges were defined as follows:
Data for geographic areas (county, zip code, Cook County sub-regions and Illinois regions) and race/ethnicity categories with less than 20 discharges in for the reporting period was suppressed due to statistical imprecision and patient confidentiality. Rates reported for pediatric and adult populations are three-year average rates per 10,000 area population. Rate calculation for a given geographic area (zip/county/state region) or race/ethnicity category was suppressed when the data reporting period combined population estimate was less than 1000.
Self-Reported: Illinois County Behavioral Risk Factor Survey (ICBRFS)
The data source was the Illinois County Behavioral Risk Factor Survey (ICBRFS). ICBRFS is a statewide telephone survey that collects county level health data on health-related risk behaviors, chronic health conditions, health care access, and use of preventative services. The ICBRFS uses a standardized questionnaire and procedures established by the Centers for Disease Control and Prevention (CDC) and used for the nationwide program known as Behavioral Risk Factor Surveillance System (BRFSS).
The IL BRFSS statewide data is available at: http://www.idph.state.il.us/brfss/statedata.asp
The interviews are conducted over a period of years and are referred to as a round. Round 6 started in 2015 with counties at the southernmost portion of the state and progressed north to the top of the state, completing all counties of Illinois in 2019. Round 6 included approximately 37,000 surveys across the state.
Because the ICBRFS respondents are randomly selected, measures of prevalence are subject to random sample errors. Each measure listed in the data tables includes the number of respondents (unweighted count), the estimated percent (weighted percentage), the 95% confidence interval (upper and lower limits), and the estimated population (weighted count).
Calculations are intentionally suppressed to reduce the possibility of making statements about the findings when the data is not strong enough to support any statistical conclusions. To provide high quality health information, prevalence estimates are suppressed when any of the following criteria are met: fewer than 6 respondents in the numerator (i.e. the number of respondents associated with the response categories, e.g. “Yes-No”), there are fewer than 50 respondents in the denominator (i.e. the total number of respondents to a question), the half-width of the confidence interval for the prevalence estimate is greater than 10. Additionally, not all survey questions are able to be analyzed for each county.
Weighted data are used in all calculations, so percentages shown in tables cannot be derived exactly from the numbers presented. ICBRFS data are weighted for the probability of selection of a telephone number, the number of adults in a household, and the number of phones in a household. The data is adjusted to reflect the demographic distribution of the county’s adult population (ages 18 and older). It is advised not to compare county data to state rates from the BRFSS due to the difference in the methodology to weigh the data. Additionally, comparisons to other Illinois counties should be made with caution as ICBRFS completes counties on a rotating basis and counties will be surveyed during different timeframes within the survey rotation.
Preventable Hospitalization Indicators
Prevention Quality Indicators (PQIs), developed by the federal Agency of Healthcare Research and Quality (AHRQ), identify hospital admissions that evidence suggests could have been avoided, at least in part, through high-quality outpatient care. They represent hospital admission rates for ambulatory care sensitive conditions. Even though these indicators are based on hospital inpatient data, they provide insight into the community health care system or services outside the hospital setting. For Prevention Quality Indicators, lower rates usually represent better outpatient care.
PQIs used in this report consist of the following 13 ambulatory care sensitive conditions, which are measured as rates of admission to the hospital. They are presented as a rate among the adult population (>=18 years of age):
Both the observed and risk adjusted measures are reported. Risk adjustment is based on county specific age and sex distribution. Further details of the PQIs can be found at: http://www.qualityindicators.ahrq.gov/Modules/pqi_resources.aspx.
The PQIs are defined using AHRQ definitions and programs. The county level PQIs were created using AHRQ SAS QI 4.5a. As this software only defines the PQIs at the county level, the AHRQ SAS program was modified to allow for estimation of Illinois regions.
Race specific PQIs: The race specific PQI measures reflect crude, race-stratified rates. They are not risk adjusted. The rates are suppressed where case counts or populations are low.
Categorization of Race/Ethnicity Data
Race and ethnicity data are collected according to Office of Management and Budget standards. Race coding options are: American Indian/Alaska Native, Asian, Black, Hawaiian/Pacific Islander, White, Unknown/Not Provided. Ethnicity was coded as Hispanic/Latin or Non-Hispanic/Latin. For the purposes of the current analyses, race was categorized using the following method: Ethnicity was assessed first and if "Hisp/Latin" was selected, race was assigned as Hisp/Latin. If ethnicity was classified as "Non-Hispanic/Latin", race was assigned according to the race coding option selected:<