Healthcare Cost and Utilization Project (HCUP): Overview of the HCUP Databases and Resources

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Healthcare Cost and Utilization Project (HCUP): Overview of the HCUP Databases and Resources
 
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Presentation Objectives Part I
  • Project Overview
  • AHRQ and HCUP Partners
  • The Making of HCUP Data
  • HCUP State Databases
  • HCUP Nationwide Databases
  • How to Obtain HCUP Databases & Access HCUP Resources
 
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What is HCUP?
  • HCUP is a comprehensive set of publicly available all-payer healthcare data (including self-pay and those billed as 'no charge').
  • Includes multi-year inpatient and outpatient data based on hospital billing records.
  • Includes:
    • HCUP Databases
    • Online Tools
    • Analytics
    • User Support
 
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HCUP Answers Questions
  • Uniquely addresses variation in acute care
    • Use of inpatient, emergency department (ED), and ambulatory surgery and other outpatient services
    • Clinical detail
    • Age, race and area of residence of patients
    • Geographical estimates (county, region, State, national)
    • Expected payer of services (Medicare, Medicaid, private insurance, self-pay, or those billed as 'no charge')
    • Cost of care
    • Care for a patient across time* (availability varies by State)
    • Access, quality, patient safety
    • Trends over time in all of the above
 
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Research Using HCUP Data
  • Costs of care
    • In 2016, there were 35.7 million hospital stays in the United States, with a rate of 104.2 stays per 1,000 population. The cost of these stays totaled over $417 billion with a mean cost per stay of $11,700. (2016 NIS, Stat Brief #246)
  • Access to care
    • Rates of influenza-related stays and ED visits were highest for patients from low-income areas. This disparity was greatest for young children: for children aged 0-4 years, the rate of influenza-related ED visits in 2015-2016 was 220 percent higher in the lowest than in the highest income areas. (2006-2016 NIS & NEDS, Stat Brief #253)
  • Quality of care
    • From 2010 to 2014, the rate of stays involving an adverse drug event
    • (ADE) increased the most for ADEs caused by smooth muscle and respiratory drugs (up 24 percent) and decreased the most for ADEs caused by cardiovascular drugs (down 18 percent). (2010 and 2014 SID, Stat Brief #234)
  • Readmissions
    • In 2016, the highest readmission rates were among Medicare patients aged 21-64 years and nonmaternal Medicaid patients aged 45-64 years (21.2 and 20.4 per 100 index admissions, respectively). (2010-2016 NRD, Stat Brief #248)
 
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Research Using HCUP Data Continued
  • Patient safety
    • Hospital improvements in patient safety and adverse events were noted from 2011 to 2014 in 34 States—there was a decrease in the percentage of hospitals classified as worse than average (from 9.5 to 6.7 percent) and an increase in the percentage of hospitals classified as better than average (from 3.4 to 5.5 percent).(2011 & 2014 SID, Stat Brief #237)
  • Geographic variation
    • From 2013-2015, alcohol-related stays in Rhode Island and Massachusetts (80 and 71 percent of counties in the top quintile) cost an average of $98 and $95 per resident annually, respectively. (2013-2015 SID, Stat Brief #245)
  • Trends in practice
    • In 2016, Medicare was the primary expected payer for the vast majority of cardiac pacemaker or cardioverter/defibrillator procedures (75.1 percent); lens and cataract procedures (68.5 percent); and vascular stents and OR procedures, other than head or neck (67.2 percent) (2016 NASS, Stat Brief #252)
  • Opioid-related stays
  • In 2016, most opioid-related stays among women aged 15-44 years involved abuse/dependence (86 percent). Nearly half of opioid stays among women aged 65 years and older were due to adverse events. (2016 NIS, Stat Brief #247)
 
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Presentation Objectives Part I
  • Project Overview
  • AHRQ and HCUP Partners
  • The Making of HCUP Data
  • HCUP State Databases
  • HCUP Nationwide Databases
  • How to Obtain HCUP Databases & Access HCUP Resources
 
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What is the Agency for Healthcare Research and Quality (AHRQ)?
  • The Agency for Healthcare Research and Quality (AHRQ) is a federal agency under the Department of Health and Human Services.
 
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AHRQ's Mission
  • To produce evidence to make healthcare
    • Safer
    • Higher quality
    • More accessible
    • Equitable
    • Affordable
  • To work with HHS and other partners to make sure that the evidence is understood and used
 
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The HCUP Partnership
  • Three-way cooperation between States, Federal government, and Industry
 
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HCUP Data Partners
  • Alaska Department of Health and Social Services
  • Alaska State Hospital and Nursing Home Association
  • Arizona Department of Health Services
  • Arkansas Department of Health
  • California Office of Statewide Health Planning and Development
  • Colorado Hospital Association
  • Connecticut Hospital Association
  • Delaware Health Statistics Center & Office of Vital Statistics
  • District of Columbia Hospital Association
  • Florida Agency for Health Care Administration
  • Georgia Hospital Association
  • Hawaii Laulima Data Alliance
  • Illinois Department of Public Health
  • Indiana Hospital Association
  • Iowa Hospital Association
  • Kansas Hospital Association
  • Kentucky Cabinet for Health and Family Services
  • Louisiana Department of Health
  • Maine Health Data Organization
  • Maryland Health Services Cost Review Commission
  • Massachusetts Center for Health Information and Analysis
  • Michigan Health and Hospital Association
  • Minnesota Hospital Association (provides data for Minnesota and North Dakota)
  • Mississippi Department of Health
  • Missouri Hospital Industry Data Institute
  • Montana Hospital Association
  • Nebraska Hospital Association
  • Nevada Department of Health and Human Services
  • New Hampshire Department of Health & Human Services
  • New Jersey Department of Health
  • New Mexico Department of Health
  • New York State Department of Health
  • North Carolina Department of Health and Human Services
  • North Dakota (data provided by the Minnesota Hospital Association)
  • Ohio Hospital Association
  • Oklahoma State Department of Health
  • Oregon Health Authority
  • Oregon Association of Hospitals and Health Systems
  • Pennsylvania Health Care Cost Containment Council
  • Rhode Island Department of Health
  • South Carolina Revenue and Fiscal Affairs Office
  • South Dakota Association of Health Care Organizations
  • Tennessee Hospital Association
  • Texas Department of State Health Services
  • Utah Department of Health
  • Vermont Association of Hospitals and Health Systems
  • Virginia Health Information
  • Washington State Department of Health
  • West Virginia Health Care Authority
  • Wisconsin Department of Health and Family Services
  • Wyoming Hospital Association
 
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HCUP Partners Providing Inpatient Data
  • A map of the United States shows those Partners that participate in HCUP by providing inpatient data. All States are participating except Idaho and Alabama.
  • HCUP data are collected on the State-level. All States that participate in HCUP provide us with inpatient data. Currently, we collect data from 48 States and the District of Columbia, representing 97% of the U.S. population and more than 97% of all hospital discharges.
 
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HCUP Partners Providing Ambulatory Surgery & Services Data
  • A map of the United States shows those 35 Partners that participate in HCUP by providing ambulatory surgery and services data. States include CA, CO, CT, the District of Columbia (DC), FL, GA, HI, IA, IL, IN, KS, KY, ME, MD, MI, MN, MO, NC, ND, NE, NH, NJ, NV, NY, OH, OK, OR, PA, SC, SD, TN, TX, UT, VT, WI.
 
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HCUP Partners Providing Emergency Department Data
  • A map of the United States shows those 41 Partners that participate in HCUP by providing emergency department data. States include AR, AZ, CA, CO, CT, the District of Columbia (DC), FL, GA, HI, IA, IL, IN, KS, KY, MA, MD, ME, MI, MO, MN, MS, MT, NC, ND, NE, NH, NJ, NM, NV, NY, OH, OR, RI, SC, SD, TN, TX, UT, VT, WI, WY.
 
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HCUP Participation by Data Type
  • A map of the United States that shows HCUP participation by State and data type (inpatient, emergency department, and ambulatory surgery & services combined).
 
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Presentation Objectives Part 1
  • Project Overview
  • AHRQ and HCUP Partners
  • The Making of HCUP Data
  • HCUP State Databases
  • HCUP Nationwide Databases
  • How to Obtain HCUP Data and Access HCUP Resources
 
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The Foundation of HCUP Data is Hospital Billing Data
  • Uniform billing forms, such as the UB-04 and the CMS 1500, are used by many hospitals and are the basis of HCUP data. These forms contain information used in the billing process. Basic demographic data, such as patient age and gender, are collected. More detailed information about the patient's hospital stay, such as the patient's diagnosis and the medical procedures performed, are also included. In addition, facility charges for patient care are included.
  • So, when thinking about HCUP data, it's important to remember that a large portion of these data are produced for "billing" purposes and not specifically to support research or policy development. However, some States add data elements that are intended to support research and public health, not billing purposes. The addition of information on race is one example.
 
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From Patient Hospital Visit to Administrative Record
  • It is helpful to review an inpatient patient flow diagram—from the patient's perspective and from a data perspective. From a patient's perspective, a patient either makes an appointment for inpatient care, is admitted directly from a physician's office, or is transferred from another hospital or emergency department. The patient is then admitted, receives inpatient care, and is discharged.
  • For the purposes of this presentation, it is important to understand this process from a data perspective, as well. While this perspective varies by hospital, generally a patient record is created that contains demographic information about the patient, as well as medical/clinical information about his or her inpatient services. From that patient record, a discharge summary is generated and given to a medical coder. The medical coder classifies the inpatient care into ICD-10-CM/PCS diagnosis and procedure codes. The billing department then uses the medical codes assigned by the coder to generate a hospital bill, such as a UB-04 form. The foundation of HCUP data is based on this type of billing data, also known as administrative data.
 
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The Making of HCUP Data
  • Patient enters hospital
  • Billing record is created
  • Hospital sends billing data and any additional data elements to data organizations
  • States store data in varying formats
  • AHRQ standardizes data to create uniform HCUP databases
 
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The HCUP Data Process
  • State data are mapped to a standardized HCUP format which allows for consistent data elements and values for comparison across States
    • Value-added variables (supplemental variables for revisit analyses, injury indicators, indicators for observation and ED services)
    • Hospital characteristics (teaching status, ownership/control, bed size)
    • Diagnostic related groups and severity measures
      • 3M's All Patient Refined DRGs (APR-DRGs)
  • Quality checks are performed
 
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Hospitals in the U.S.
  • 88% of hospitals in the U.S. are Community Hospitals
    • 15% Non-Community Hospitals (Federal/DoD/VA/IHS), Nonfederal Psychiatric, Nonfederal Long-Term Care, etc.)
    • Source: American Hospital Association (AHA) Annual Survey, Fiscal Year 2018
    • Please visit www.aha.org/statistics/fast-facts-us-hospitals Exit Disclaimer for more information.
 
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What Are Community Hospitals?

American Hospital Association Definition: Nonfederal, short-term general, and other special hospitals, excluding hospitals not accessible by the general public (e.g., prison hospitals or college infirmaries)
  • Included: Multi-specialty general hospitals, OB-GYN, ENT, Orthopedic, Pediatric, Public, Academic medical centers
  • Excluded: Long-term care, Psychiatric, Alcoholism/Chemical dependency, Rehabilitation, DoD/VA/HIS, College infirmaries
 
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What are Community Hospitals?
  • HCUP generally does not receive data from non-community hospitals, such as Psychiatric facilities.
  • However, if a patient is treated for a mental health condition in a community hospital, their information is included.
  • Mental, Behavioral and Neurodevelopmental Disorders, Top 5 Principal Diagnosis per 2017 National Inpatient Sample (NIS)
    • Depressive disorders: 536,580 discharges
    • Schizophrenia spectrum and other psychotic disorders: 398,840 discharges
    • Alcohol-related disorders: 308,030 discharges
    • Bipolar and related disorders: 271,610 discharges
    • Suicidal ideation/attempt/intentional self-harm: 125,135 discharges
Source: Weighted national estimates from the 2017 National Inpatient Sample (NIS), Clinical Classifications Software Refined (CCSR) default for principal diagnosis assignment
 
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HCUP State-Specific Databases
  • Inpatient State-Specific databases
    • State Inpatient Databases (SID)
  • Outpatient State-Specific Databases
    • State Ambulatory Surgery and Services Databases (SASD)
    • State Emergency Department Databases (SEDD)
 
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HCUP Nationwide Databases

  • Inpatient Nationwide databases
    • National Inpatient Sample (NIS)
    • Kids' Inpatient Database (KID)
    • Nationwide Readmissions Database (NRD)
  • Outpatient Nationwide Databases
    • Nationwide Emergency Department Sample (NEDS)
    • Nationwide Ambulatory Surgery Sample (NASS)
 
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Presentation Objectives Part I

  • Project Overview
  • AHRQ and HCUP Partners
  • The Making of HCUP Data
  • HCUP State Databases
  • HCUP Nationwide Databases
  • How to Obtain HCUP Data and Access HCUP Resources
 
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HCUP State Databases
  • State Inpatient Databases (SID)
    • Inpatient discharge data (including those admissions that started in the ED) from participating HCUP States
  • State Ambulatory Surgery & Services Databases (SASD)
    • Ambulatory surgery data (hospital-owned and some nonhospital-owned facilities) and other outpatient services from participating HCUP States
  • State Emergency Department Databases (SEDD)
    • Emergency department data (treat-and-release) from participating HCUP States
 
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What Data Elements are Included in the HCUP Databases?
  • Data Elements:
    • Patient demographics (e.g., age, sex, and for some States, race)
    • Diagnoses & procedures
    • Expected payment source (including self-pay and those billed as 'no charge')
    • Length of stay
    • Admission and discharge status
    • Point of origin
    • Total charges
    • Value-added variables (e.g., supplemental variables for revisit analyses)
 
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Some Data Elements Vary by State
  • Race/Ethnicity
  • Patient county
  • Patient ZIP Code
  • Severity of illness
  • Birthweight
  • Procedure date (days from admission to procedure)
  • Health plan details
  • Additional and/or more detailed expected payer information
  • Detailed charges
  • Patient identifiers (encrypted); supplemental variables for revisit analyses
  • Physician identifiers (encrypted)
  • Physician specialty
  • Hospital identifier (unencrypted)
 
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Example: Payer Detail Varies by State
  • A screenshot shows the different values and descriptions for the variable PAY1_X and PAY1 (Standardized).
 
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Example: Race Detail Varies by State
  • A screenshot shows the different values and descriptions for the variable RACE_X and RACE (Standardized).
 
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Partner Files vs. HCUP Files
  • Partner-Provided Files:
    • All data elements
    • May not have some value-added elements available
    • Not uniformly coded across states
    • Variability in quality checks by State
    • More timely
  • HCUP Files:
    • Subset of data elements
    • Value-added data elements available
    • Uniformly coded across the States
    • Standard data quality checks
    • Lag time
 
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Presentation Objectives Part I

  • Project Overview
  • AHRQ and HCUP Partners
  • The Making of HCUP Data
  • HCUP State Databases
  • HCUP Nationwide Databases
  • How to Obtain HCUP Data and Access HCUP Resources
 
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HCUP Nationwide Databases

  • National (Nationwide) Inpatient Sample (NIS)
    • Generate national and regional estimates of inpatient, utilization, access, quality, patient safety, etc.
  • Kids' Inpatient Database (KID)
    • Generate national and regional estimates of pediatric inpatient utilization, access, quality, etc.
  • Nationwide Readmissions Database (NRD)
    • Generate national estimates of all-cause and condition-specific readmissions
  • Nationwide Emergency Department Sample (NEDS)
    • Generate national and regional estimates of emergency department utilization, access, quality, etc.
  • Nationwide Ambulatory Surgery Sample (NASS)
    • Generate national and regional estimates of major ambulatory surgery encounters in hospital-owned facilities
 
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All Nationwide Databases Are Derived from HCUP State Databases
  • State Inpatient Databases (SID)
    • NIS: Sample inpatient discharges of all ages from all SID and community hospitals*
    • KID: Sample inpatient discharges aged <= 20 years old from all SID and community hospitals*
    • NRD: All inpatient discharges for all ages and community hospitals* from SID with verified patient linkage numbers, with some exclusions
  • State Emergency Department Databases (SEDD)
    • NEDS: Sample of hospital-owned EDs* from all SEDD and includes all ED admissions from the SID for the sampled EDs
  • State Ambulatory Surgery and Services Databases (SASD)
    • NASS: All major ambulatory surgery encounters for all ages and hospital-owned facilities* from the SASD, with some exclusions
* NIS, NRD, and NASS exclude community hospitals that are rehabilitation or long-term, acute-care facilities; KID and NEDS exclude community hospitals that are rehabilitation facilities.
 
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NIS is a Stratified Sample of Discharges from the SID
  • State Inpatient Databases (SID)
    • Approximately 4,600 hospitals
    • Approximately 35 million records
    • Strata
      • Ownership/Control
      • Bed Size
      • Teaching Status
      • Urban/Rural Location
      • U.S. Census Division
  • Stratified Sample of Discharges
    • Within strata sort by hospital, DRG, and admission month and select 1 in 5 records
    • **State not included in the stratum
  • National Inpatient Sample (NIS)
    • Approximately 4,600 hospitals
    • Approximately 7 million records
Statistics listed from 2017 data year
 
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KID is a Stratified Sample of Discharges from the SID
  • State Inpatient Databases (SID)
    • Approximately 4,600 hospitals
    • Approximately 35 million records
    • Strata
      • Uncomplicated Births
      • Complicated Births
      • Pediatric Non-Births
  • Stratified Sample of Discharges
    • 10% uncomplicated births
    • 80% pediatric discharges
    • *State not included in the stratum
  • KIDs' Inpatient Database (KID)
    • Approximately 4,200 hospitals
    • Approximately 3 million records
  • Statistics listed from 2016 data year
 
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KID is a Stratified Sample of Discharges from the SID
  • State Inpatient Databases (SID) and State Emergency Department Databases (SEDD)
  • Strata
    • U.S. Region
    • Urban/Rural Location
    • Teaching Status
    • Ownership/Control
    • Trauma center
  • Stratified Sample of Hospitals
    • *State not included in the stratum
  • Nationwide Emergency Department Sample (NEDS)
    • Approximately 980 hospitals
    • Approximately 34 million ED visits
Statistics listed from 2017 data year
 
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HCUP NEDS Data
  • SEDD: Treat-and-Release ED Visits
    • Approximately 87% of ED visits are treat-and-release
  • SID: Admitted ED Visits
  • NEDS
    • Approximately 13% of ED visits result in a hospital stay
Statistics listed from 2017 data year
 
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Additional Variables Are Included in the NEDS
  • These additional variables are relevant for research on emergency department utilization. Examples include:
    • Type of ED event-treated and released, admitted to the same hospital, transferred, died
    • Disposition of patient from ED
    • Died during the visit: in the ED, in the hospital, or did not die
    • Diagnosis reported on record indicates self harm
    • Trauma center level I, II, or III
    • HCUP ED hospital identifier
 
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NRD is Constructed from SID with Verified Patient Linkage Numbers
  • State Inpatient Databases (SID)
    • Hospital and Patient Exclusions
    • Strata
      • U.S. Region
      • Urban/Rural Location
      • Teaching Status
      • Size
      • Ownership/Control
      • Patient Characteristics (age and sex)
  • All Discharges (after exclusions)
  • Nationwide Readmissions Database (NRD)
    • Approximately 2,000 hospitals
    • Approximately 18 million records
Statistics listed from 2017 data year
 
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NRD Discharge-Level Exclusions
  • Discharge-level exclusions
    • Discharges from patients with an age of 0
    • Discharges with missing or unverified patient linkage numbers
    • Questionable patient linkage numbers: same patient linkage number on 20 or more discharges
    • Questionable patient linkage numbers: patient is hospitalized after discharged dead
    • Questionable patient linkage numbers: overlapping stays
    • Discharges from hospitals with more than 50 percent of their total discharges excluded for any of the above causes
 
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NASS is Constructed from Major Ambulatory Surgery Encounters in the SASD
  • State Ambulatory Surgery and Services Databases (SASD)
    • Strata
      • U.S. Region
      • Bed Size
      • Urban/Rural Location and Teaching Status
      • Ownership/Control
  • All Major AS Encounters from Hospital-Owned Facilities* (after exclusions)
    • *State not included in the stratum
  • Nationwide Emergency Department Sample (NASS)
    • Approximately 7.5 million ambulatory surgery encounters
    • Approximately 2,700 hospital-owned facilities
Statistics listed from 2017 data year
 
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NASS Exclusions/Limitations
  • Facility-level exclusions
    • Hospitals with gross irregularities in quarterly reporting volume
    • Hospitals that do not submit data in all 4 quarters
    • Hospitals with an unusually low volume of encounters involving an in-scope major ambulatory surgery
  • Encounter-level limitations
    • Limited to encounters involving at least one in-scope major ambulatory surgery
    • Major ambulatory surgeries: selected invasive, therapeutic surgical CPT-coded procedures that typically require the use of an operating room and regional anesthesia, general anesthesia, or sedation.
    • In-scope surgeries include CCS for Services and Procedures categories with (1) relatively high major ambulatory surgery volume, (2) a substantial share of major ambulatory surgeries performed in hospital-owned facilities, and (3) evidence of reliable reporting from SASD hospitals.
Statistics listed from 2017 data year
 
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NIS, NRD, KID, NEDS, & NASS: Must be Weighted to Produce National and Regional Estimates

An illustration shows the five nationwide databases (NIS, NRD, KID, NEDS, and NASS) can be weighted using the data element DISCWT to produce national and regional estimates.

The NRD is not designed to support regional analyses.
 
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NEDS: Must be Weighted to Produce National and Regional Estimates

An illustration shows that the NEDS can be weighted using the data element HOSPWT to produce national and regional estimates of emergency departments.
 
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Comparison of the HCUP Inpatient Databases
  State Inpatient Databases National Inpatient Sample Kids' Inpatient Database Nationwide Readmissions Database
HCUP Database SID (2017) NIS (2017) KID (2016) NRD (2017)
States 48 States + DC 47 States + DC 46 States + DC 28
Hospitals 4,584 4,584 4,200 2,454
Inpatient Discharges 35 million 7 million 3 million 18 million
Derived From - SID SID SID
Uses Examine State and local market area statistics on healthcare utilization, access, quality, patient safety, etc. Readmission analyses possible in some States. Generate national and regional estimates of healthcare utilization, access, quality, patient safety, etc. Generate national and regional pediatric estimates of healthcare statistics. Generate national estimates of all-cause and condition-specific readmissions.
 
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Comparison of the HCUP Outpatient Databases
  State Emergency Department Data Ambulatory Surgery and Services Data
HCUP Database SEDD (2017) NEDS (2017) SASD (2017) NASS (2017)
States 40 States + DC 36 States + DC 34 States + DC 32 States + DC
Hospitals 3,896 984 3,100 2,700
Outpatient Records 99 million ED visits 34 million ED visits 16 million surgeries 18 million major ambulatory surgeries
Derived From - SID & SEDD - SASD
Uses Examine ED visits at hospital-affiliated EDs that do not result in an admission for a give State. Generate national and regional estimates for hospital-based EDs. Study encounter-level data for ambulatory surgeries and other outpatient services from hospital-owned facilities. Generate national and regional estimates of major ambulatory surgery encounters performed in hospital-owned facilities.
 
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What Types of Care Are and Are Not Captured by HCUP?
  • Included in HCUP:
    • Inpatient Care
      • State Inpatient Databases (SID)
      • National (Nationwide) Inpatient Sample (NIS)
      • Kids' Inpatient Database (KID)
      • Nationwide Readmissions Database (NRD)
    • Emergency Department
      • State Emergency Department Databases (SEDD)
      • Nationwide Emergency Department Sample (NEDS)
    • Ambulatory Surgery and Services
      • State Ambulatory Surgery and Services Databases (SASD)
      • Nationwide Ambulatory Surgery Sample (NASS)
    • Other Non-Emergent Outpatient Services
      • State Ambulatory Surgery and Services Databases (SASD)
    • Not Included in HCUP
      • Physician office visits
      • Pharmacy
      • Labs/Radiology
 
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Benefits and Limitations of HCUP Databases
  • Benefits
    • Large number of records
    • Uniformity in coding
    • Regular, routine collection
    • Ease of access
    • All payers, including self-pay or those billed as 'no charge'
    • Available at local, State, regional, and national level
    • Supplemental variables available to facilitate research
  • Limitations
    • Limited clinical details
    • Lack reimbursed claims information
    • Does not include all hospital types (e.g., VA and DoD)
    • Does not show complete episode of care
    • State databases lack hospital characteristic information
    • Cannot link national databases to external sources
    • Differences in coding across hospitals
 
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Some Limitations of HCUP State Databases Can be Addressed by Linking to Other Databases
  • HCUP State databases can be linked to other databases, including:
    • American Hospital Association (AHA) Annual Survey
    • The Health Resources and Services Administration (HRSA) Area Health Resource File (AHRF)
    • Zip Code Files from Census or Vendor
    • Medicare Cost Reports
    • Trauma Information Exchange Program (TIEP)
 
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Summary
  • Eight types of HCUP databases
  • Databases are based on administrative hospital data: inpatient, emergency department, and ambulatory surgery and services
  • Available for multiple years
    • Nationwide
      • NIS (1988-2017)
      • KID (1997, 2000, 2003, 2006, 2009, 2012, 2016)
      • NRD (2010-2017)
      • NEDS (2006-2017)
      • NASS (2016-2017
    • State
      • SID (1990-2017)
      • SASD (1997-2017)
      • SEDD (1999-2017)
    • Can look at breadth of healthcare issues
  • Find out more on HCUP-US!
 
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Presentation Objectives Part I
  • Project Overview
  • AHRQ and HCUP Partners
  • The Making of HCUP Data
  • HCUP State Databases
  • HCUP Nationwide Databases
  • How to Obtain HCUP Databases & Access HCUP Resources
 
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The HCUP Database Process
  • Processed data sent to HCUP Partners
  • State Databases become available to the public through the HCUP Central Distributor
  • Nationwide Databases become available for download through the HCUP Central Distributor
 
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How to Purchase HCUP Data
  • HCUP Central Distributor: www.hcup-us.ahrq.gov/tech_assist/centdist.jsp
  • Visit the HCUP Central Distributor website.
  • The Central Distributor provides one stop shopping for purchasing many of the State Databases, as well as the Nationwide Databases.
  • Not all data elements are available from every Partner Organization, and not all Partner Organizations make their data available through the Central Distributor.
  • Some Partner Organizations may place additional restrictions on the sale of their data.
 
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Purchase Data Online Through the HCUP Central Distributor
  • Step 1: Take Data Use Agreement (DUA) online training
  • Step 2: Login or register for an account
  • Step 3: Create your profile under "My Account"
  • Step 4: Submit online order and complete further instructions listed on the "Thank You" page
  • Step 5: Download Nationwide databases online or receive delivery of State databases through the mail.
  • For assistance, contact the HCUP Central Distributor:
 
Slide 57

Slide 57 is described below.

Additional Requirement: Electronic Data Use Agreement (DUA) Course
  • Purpose of the Course:
  • Emphasize the importance of data protection
  • Reduce the risk of inadvertent violations
  • Describe your individual responsibility when using HCUP data
  • Takes 15 minutes to complete
  • www.hcup-us.ahrq.gov/tech_assist/dua.jsp
 
Slide 58

Slide 58 is described below.

Pricing Information per Data Year
  • Nationwide Databases (NIS, KID, NRD, NEDS, NASS)
    • NIS: $750 beginning 2017, student price $150
    • KID: $500 beginning 2016, student price $100
    • NRD: $1,000 beginning 2015, student price $200
    • NEDS: $1,000 beginning 2016, student price $200
    • NASS: $1,000 beginning 2016, student price $200
  • State Databases (SID, SASD, SEDD)
    • Varies by state, database, year, and type of applicant
    • $50 - $3,200
Funds for State data sales returned to HCUP Partners
 
Slide 59

Slide 59 is described below.

Partners Releasing Databases Through HCUP Central Distributor

  • Alaska
  • Arizona
  • Arkansas
  • California
  • Colorado
  • Delaware
  • District of Columbia
  • Florida
  • Georgia
  • Hawaii
  • Iowa
  • Kansas
  • Kentucky
  • Maine
  • Maryland
  • Massachusetts
  • Michigan
  • Mississippi
  • Nebraska
  • Nevada
  • New Jersey
  • New Mexico
  • New York
  • North Carolina
  • Oregon
  • Rhode Island
  • South Carolina
  • South Dakota
  • Utah
  • Vermont
  • Washington
  • West Virginia
  • Wisconsin
Remember, not all States participate in all years and for all databases.
 
Slide 60

Slide 60 is described below.

Software Requirements of Working with the Full HCUP Files
  • Software Package:
    • SAS
      • Load programs
      • Format programs
      • Example Statistical Coding
      • HCUP Tools and Programs
    • STATA
      • Load programs
      • Example Statistical Coding
      • HCUP Tools and Programs
    • SPSS
      • Load programs
      • HCUP Tools and Programs
    • SUDAAN
      • Example Statistical Coding
    • R
      • Example Statistical Coding
Microsoft Excel and Access are NOT GOOD Options!
 
Slide 61

Slide 61 is described below.

HCUP User Support Website
  • Find detailed information on HCUP databases, tools, and products
  • Access HCUPnet, HCUP Fast Stats, the Central Distributor, Online Tutorials, and more
  • Find comprehensive list of HCUP-related publications and database reports
  • Access technical assistance
  • Visit us at: www.hcup-us.ahrq.gov
 
Slide 62

Slide 62 is described below.

Presentation Objectives Part II
  • HCUPnet Overview
  • HCUP Fast Stats
  • Add Value to Your Databases with HCUP Tools & Software
  • Publications and Publication Search
  • How to Access HCUP Resources
 
Slide 63

Slide 63 is described below.

HCUPnet: Quick, Free Access to HCUP Statistics
  • Free online query system
  • Users generate tables and figures of outcomes by diagnoses and procedures
  • Statistics can be cross-classified by patient and hospital characteristics
  • Can produce county-level statistical maps
www.hcupnet.ahrq.gov
 
Slide 64

Slide 64 is described below.

HCUPnet Can Answer a Variety of Questions
  • What percentage of hospitalizations for children report Medicaid as expected payer, by State?
  • What are the most expensive conditions treated in U.S. hospitals?
  • What is the trend in hospitalizations for depression?
  • Will there be a sufficient number of cases to do my analysis?
  • How do my estimates and calculations compare with HCUPnet (validation)?
 
Slide 65

Slide 65 is described below.

Examples of What HCUPnet Provides...
  • Step-by-step queries from:
    • Hospital inpatient data (SID, NIS, KID, NRD)
    • Emergency department (ED) setting (SID, SEDD, NEDS)
    • Ambulatory surgery (AS) setting (SASD)
    • Community-level statistics
  • Specialized queries by:
    • Overall inpatient stays
      • Select conditions or procedures
    • Overall ED visits
      • Select conditions or procedures
    • Overall AS encounters
      • Select conditions or procedures
    • County-level, regional, or U.S.-Mexico border State statistics
  • Ready-to-use statistics:
    • Trends in inpatient stays
    • Related conditions and procedures
    • Readmissions (NRD)
    • Trends in ED visits
    • Percent of patients admitted versus discharged from the ED (i.e., treat-and-release)
    • Percent of cases treated in the inpatient versus AS settings
    • Inpatient stays for alcohol and other drugs
 
Slide 66

Slide 66 is described below.

How Does HCUPnet Work?
  • Step 1: What kind of statistics are you looking for?
  • Step 2: Choose how you would like to analyze the data?
  • Step 3: Create your analysis
  • Step 4: View and update your results in real time
  • Step 5: View your results in detailed graphs and maps
  • Step 6: Export your results for future use
 
Slide 67

Slide 67 is described below.

How Does HCUPnet Work? Analysis Setup (Steps 1 and 2)
  • The slide shows a screen shot of the analysis setup window on HCUPnet. In this example query, statistics will be specific to the inpatient setting, specifically for data year 2016. Individual ICD-10-CM diagnosis codes will be ranked to show the most common diagnoses for that setting and year.
 
Slide 68

Slide 68 is described below.

How Does HCUPnet Work? Modifying Results
  • Once results are displayed, you can use the navigation bar on the left to make changes to your analysis. Select outcomes and measures; see results by patient or hospital characteristics; change your setting of care, the geographic setting, or the year of your analysis; show results for subgroups; or change the diagnosis or procedures being shown.
 
Slide 69

Slide 69 is described below.

How Does HCUPnet Work? Options for Result Output
  • In addition to statistics being displayed in the table, users can select the option to graph their results. Excel and CSV options are available for exporting tabular results. The chart must be downloaded separately.
 
Slide 70

Slide 70 is described below.

Additional Examples of Output from HCUPnet
  • For users interested in obtaining community-level statistics, information can also be provided in a State-specific map, as shown on the slide.
 
 
Slide 71

Slide 71 is described below.

HCUPnet Versus Full HCUP Databases

Capability
  • HCUPnet Can Produce...
    • Simple statistics
    • Simple size calculations
    • Trends analyses
    • Rank order of diagnoses and procedures
    • Z-test calculator for significance testing
    • Validation of results obtained from the HCUP databases
  • HCUP Databases Can Produce...
    • Simple statistics
    • More complicated queries
    • Sample size calculations
    • Trends Analyses
    • Multivariate analyses
    • Rank order of diagnoses and procedures
    • Z-test calculator for significance testing
    • Validation of results obtained from the HCUP databases
 
 
Slide 72

Slide 72 is described below.

Presentation Objectives Part II
  • HCUPnet Overview
  • HCUP Fast Stats
  • Add Value to Your Databases with HCUP Tools & Software
  • Publications and Publication Search
  • How to Access HCUP Resources
 
 
Slide 73

Slide 73 is described below.

HCUP Fast Stats
  • Screenshot from HCUP Fast Stats homepage.
  • HCUP Fast Stats provides easy access to the latest HCUP-based statistics for healthcare information topics.
  • Uses visual statistical displays in stand-alone graphs, trend figures, or simple tables to convey complex information at a glance.
  • Information will be updated regularly (quarterly or annually, as newer data become available).
www.hcup-us.ahrq.gov/faststats/landing.jsp
 
 
Slide 74

Slide 74 is described below.

HCUP Fast Stats— State Trends in Hospital Use by Payer
  • Screenshot of HCUP Fast Stats homepage for the State Trends in Hospital Use by Payer topic.
  • The State Trends in Hospital Use by Payer topic includes statistics on the number of inpatient stays and emergency department visits by expected payer. For inpatient, trends by expected payer for categories of conditions (surgical, mental health, injury, maternal, and medical) and for emergency department, trends are provided for select conditions that are prevalent in the emergency department, such as abdominal pain, back or neck pain, and injury. Trends are currently provided through quarter 1 of 2019 for inpatient and quarter 4 of 2018 for the emergency department.
 
 
Slide 75

Slide 75 is described below.

HCUP Fast Stats— National Hospital Utilization and Costs
  • Screenshot of statistics generated from the HCUP Fast Stats National Hospital Utilization and Costs topic.
  • The National Hospital Utilization and Costs topic includes information on trends in inpatient stays, the most common diagnoses for inpatient stays, and the most common operations during inpatient stays.
 
 
Slide 76

Slide 76 is described below.

HCUP Fast Stats— Opioid-Related Hospital Use
  • Screenshots of statistics generated from the HCUP Fast Stats Opioid-Related Hospital Use topic.
  • The Opioid-Related Hospital Use topic provides information on opioid-related inpatient stays and ED visits overall and by age group, sex, community-level income, patient location, and expected payer. Trends are presented graphically as population-based rates for the U.S. and by State.
 
 
Slide 77

Slide 77 is described below.

HCUP Fast Stats— Neonatal Abstinence Syndrome Among Newborn Hospitalizations
  • Screenshot of statistics generated from the Neonatal Abstinence Syndrome Among Newborn Hospitalizations.
  • The Neonatal Abstinence Syndrome Among Newborn Hospitalizations topic provides trends in neonatal abstinence syndrome-related newborn hospitalizations overall and by sex, expected payer, community-level income, and patient location. Trends are presented graphically as rates per 1,000 newborn hospitalizations, median costs, and median length of stay for the U.S. and by State.
 
 
Slide 78

Slide 78 is described below.

HCUP Fast Stats— Interactive Maps
  • Screenshots of the interactive U.S. maps generated from the Opioid-Related Hospital Use and Neonatal Abstinence Syndrome Among Newborn Hospitalizations topics.
  • An additional feature of the Opioid-Related Hospital Use and NAS Among Newborn Hospitalizations topics is an interactive U.S. map. For opioids, this map provides annual rates of opioid-related inpatient stays or emergency department (ED) visits per 100,000 population. For NAS, this map provides annual rates of NAS per 1,000 newborn hospitalizations. States are color-coded to identify each State's rate relative to the distribution across all States providing data in 2015. A year-slider is available so that users can see trends have changed over time.
 
 
Slide 79

Slide 79 is described below.

HCUP Fast Stats— Hurricane Impact on Hospital Use
  • Screenshot of statistics generated from the Hurricane Impact on Hospital Use topic.
  • The latest topic, Hurricane Impact on Hospital Use, presents change in population-based inpatient and emergency department utilization rates pre- versus post-hurricane for 11 U.S. hurricanes between 2005-2017. Hospital utilization statistics are provided for all conditions and for injuries only, and for select age groups, based on county proximity to the hurricane.
 
 
Slide 80

Slide 80 is described below.

Presentation Objectives Part II
  • HCUPnet Overview
  • HCUP Fast Stats
  • Add Value to Your Databases with HCUP Tools & Software
  • Publications and Publication Search
  • How to Access HCUP Resources
 
 
Slide 81

Slide 81 is described below.

What are HCUP Software Tools?

  • Can be applied to HCUP databases, to systematically create new data elements from existing data, thereby enhancing a researcher's ability to conduct analyses
  • While designed to be used with HCUP databases, the analytic tools may be applied to other administrative databases
 
 
Slide 82

Slide 82 is described below.

Multiple Coding Systems
  • Consider which coding system is appropriate for your analysis
  • Diagnosis-Related
    • ICD-10-CM
    • DRGs*
    • MDCs*
    • ICD-9-CM
  • Procedure-Related
    • ICD-10-PCS
    • CPT
    • HCPCS
    • ICD-9-CM
*Grouped conditions/procedures on inpatient stays
 
 
Slide 83

Slide 83 is described below.

ICD-10-CM Diagnosis-Related HCUP Software Tools
  • We will begin by discussing ICD-10-CM diagnosis-related HCUP software tools.
 
 
Slide 84

Slide 84 is described below.

Clinical Classifications Software Refined (CCSR) for ICD-10-CM Diagnoses
  • The CCSR replaces the beta version of the CCS for ICD-10-CM diagnoses and applies to all ICD-10-CM diagnosis codes through fiscal year (FY) 2020.
  • Aggregates over 70,000 ICD-10-CM diagnosis codes into a manageable number of clinically meaningful categories.
    • Categories are organized across 21 body systems, which generally follow the structure of the ICD-10-CM diagnosis chapters.
 
 
Slide 85

Slide 85 is described below.

Key Differences Between CCSR for ICD-10-CM and CCS for ICD-10-CM (Beta Version)
  • Difference
    • Number of categories
    • Mutually exclusive category assignment
    • Category naming convention
    • Multi-level system
    • Multi-level system
  • CCSR for ICD-10-CM Diagnoses
    • Over 530 categories
    • Some codes cross-classified to more than one CCSR diagnosis category
    • Categories start with three-character body system abbreviation followed by three digits
    • No multi-system developed
    • Flexibility to choose between file output versions
  • CCS for ICD-10-CM (Beta Version)
    • 283 categories
    • Each diagnosis code maps to one and only one CCS category
    • Categories are numeric
    • Multi-level system with additional diagnostic information up to two levels
    • Array of CCS data elements with the CCS category as the value
 
 
Slide 86

Slide 86 is described below.

Example: CCSR Category Naming Convention and Assignment
  • This slide provides an example of both CCSR category assignment and the naming convention used for CCSR categories. This code is mapped to the three CCSR categories. Due to the specificity of this ICD-10-CM diagnosis code, particularly that three different conditions are encompassed in a single code, three CCSR categories are assigned.
  • Diagnosis Code I13.0: Hypertensive heart and chronic kidney disease with heart failure and stage 1 through stage 4 chronic kidney disease, or unspecified chronic kidney disease
    • CCSR CIR008: Hypertension with complications and secondary hypertension
    • CCSR CIR019: Heart failure
    • CCSR GENN003: Chronic kidney disease
  • All three CCSR categories are named using first a three character abbreviation for the body system. CIR in this example pertains to the circulatory system and GEN pertains to the genitourinary system. Following the three character abbreviation is a three digit number to differentiate condition categories within the associated body system.
 
 
Slide 87

Slide 87 is described below.

CCSR for ICD-10-CM Diagnoses Default Categorization Scheme
  • Added to v2020.2, released in February 2020
  • Purpose of default CCSR categorization:
    • Allow users to rank hospital encounters into mutually exclusive groups
      • Principal (or first-listed) diagnosis code is assigned to a single default CCSR category
      • Each hospital encounter can be counted just once
  • The default categorizations are based on a specific set of 12 guidelines
 
 
Slide 88

Slide 88 is described below.

CCSR for ICD-10-CM Diagnoses Resources
  • User Guide for ICD-10-CM Diagnoses (PDF)
    • Detailed description of the guidelines used to assign CCSR categories and default for principal diagnosis
    • How-to guide for using the SAS program and CSV mapping file with your administrative data
  • Diagnosis CCSR reference file (Excel)
    • Searchable list of CCSR categories
    • Searchable list of ICD-10-CM codes, CCSR assignment, and default CCSR for the principal diagnosis
  • Comparison of the CCSR with the beta version of the CCS for ICD-10-CM Diagnoses (both PDF and Excel)
  • Log of changes across versions (Excel)
www.hcup-us.ahrq.gov/toolssoftware/ccsr/ccs_refined.jsp
 
 
Slide 89

Slide 89 is described below.

Presentation Objectives Part II
  • Currently a beta version; a fully refined version of the CCI for ICD-10-CM is expected to be released in late 2020.
  • Groups diagnosis codes into Chronic or Non-Chronic Categories
    • CCI for ICD-10-CM diagnosis codes (beta version)
      • By FY for years 2016-2020
  • Groups ICD-10-CM Diagnosis Codes to Condition Categories
    1. Chronic, e.g., Diabetes
    2. By FY for years 2016-2020
    3. Non-Chronic, e.g., Food Poisoning
 
 
Slide 90

Slide 90 is described below.

Elixhauser Comorbidity Software for ICD-10-CM (Beta Version)
  • Currently a beta version; a fully refined version of the Elixhauser Comorbidity for ICD-10-CM is expected to be released in late 2020.
  • Creates indicator flags for 29 major comorbidities
    • Elixhauser Comorbidity Software for ICD-10-CM (beta version) available by FY for years 2016-2020
  • ICD-10-CM and DRGs on Administrative Data can use the Elixhauser Comorbidity Software to create Comorbidity Variables, such as:
    • Obesity
    • Congestive heart failure
    • Hypertension
    • Paralysis
    • Liver disease...
 
 
Slide 91

Slide 91 is described below.

ICD-10-PCS Procedure-Related HCUP Software Tools
  • Now, we are going to discuss the HCUP software tools for ICD-10-PCS procedure codes.
 
 
Slide 92

Slide 92 is described below.

Clinical Classifications Software (CCS) for ICD-10-PCS (Beta Version
  • Currently a beta version; a fully refined version of the CCS for ICD-10-PCS is expected to be released in late 2020.
  • Clusters procedure codes into clinically meaningful categories
    • >77,000 ICD-10-PCS procedure codes → 231 categories
  • Useful for presenting descriptive statistics and understanding patterns
  • The CCS can be used to identify populations for procedure-specific studies
  • It can be a useful way to categorize procedures when exploring data and can serve as a tool for reporting statistical information on hospitalizations
 
 
Slide 93

Slide 93 is described below.

Procedure Classes for ICD-10-PCS (Beta Version)
  • Currently a beta version; a fully refined version of the Procedure Classes for ICD-10-PCS is expected to be released in late 2020.
  • Groups procedure codes into one of four categories
    • Versions available by FY for years 2016-2020
  • ICD-10-PCS Procedure Codes can be grouped into one of four categories using the Procedure Classes for ICD-10-PCS (Beta Version) software:
    1. Minor Diagnostic, e.g., Electrocardiogram
    2. Minor Therapeutic, e.g., Pacemaker
    3. Major Diagnostic, e.g., Pericardial Biopsy
    4. Major Therapeutic (ex: CABG)
 
 
Slide 94

Slide 94 is described below.

Utilization Flags for ICD-10-PCS (Beta Version)
  • Currently a beta version; a fully refined version of the Utilization Flags is expected to be released in 2021.
  • Reveals additional information about the use of healthcare services
  • Primarily uses UB-04 revenue codes, augmented with
  • ICD-10-PCS procedure codes
    • Versions available by FY for years 2017-2020
  • UB-04 codes + ICD-10-PCS procedure codes can use the Utilization Flags for ICD-10-PCS Software (beta version) to create 30 Utilization Flags, such as:
    • Emergency Room
    • Observation Services
    • Intensive Care Unit
    • Renal Dialysis
    • CT Scan...
 
 
Slide 95

Slide 95 is described below.

2016-2018 State and 2016-2017 Nationwide Databases: Revised Structure
  • 2016-2018 State and 2016-2017 Nationwide databases include full calendar years of data with diagnosis and procedure codes reported using the ICD-10-CM/PCS coding system
  • Data elements derived from HCUP software tools are not provided in these HCUP databases
  • For users interested in applying the HCUP software tools to the ICD-10-CM/PCS data in the 2016-2018 State and 2016-2017 Nationwide databases:
 
 
Slide 96

Slide 96 is described below.

CPT/HCPCS Procedure-Related HCUP Software Tools
  • Now, we are going to discuss the HCUP software tools for CPT/HCPCS procedure codes
 
 
Slide 97

Slide 97 is described below.

Clinical Classifications Software (CCS) for Services and Procedures
  • Clusters HCPCS Level I (or CPT procedure codes) and HCPCS Level II codes into clinically meaningful procedure categories
  • Procedure categories are identical to the CCS beta version for ICD-10-PCS and CCS for ICD-9-CM, with the addition of specific categories unique to professional service codes in CPT/HCPCS
  • Users must agree to a license to use the CCS-Services and Procedures before accessing the software
  • Updated to include procedure codes effective January 2019
 
 
Slide 98

Slide 98 is described below.

Surgery Flags for Services and Procedures
  • Provides a method for identifying surgical procedures and encounters using CPT-based data
  • Surgery Flags for Services and Procedures
    • Updated to include CPT codes released through January 2019
  • CPT procedures codes can be classified into the following categories with the Surgery Flags for Services and Procedures:
    1. Narrow
      • Invasive therapeutic surgical procedure
      • Typically requires use of an operating room
      • Requires regional /general anesthesia, or sedation to control pain
    2. Broad
      • Includes all narrowly defined surgical procedures as well as a broader group of diagnostic and less invasive therapeutic surgeries
    3. Neither Broad nor Narrow
      • Example: Use of endoscopies for diagnostic purposes only and for which nothing was removed
 
 
Slide 99

Slide 99 is described below.

ICD-9-CM Related HCUP Software Tools
  • To wrap up the HCUP Software tools, we will briefly mention the tools available for ICD-9-CM, both diagnoses and procedures.
 
 
Slide 100

Slide 100 is described below.

HCUP Software Tools for ICD-9-CM
  • Clinical Classifications Software (CCS) for ICD-9-CM Diagnosis and Procedures
  • Chronic Condition Indicator for ICD-9-CM
  • Elixhauser Comorbidity Software for ICD-9-CM
  • Procedure Classes for ICD-9-CM
  • Utilization Flags for ICD-9-CM
  • Surgery Flags for ICD-9-CM
www.hcup-us.ahrq.gov/tools_software.jsp"
 
 
Slide 101

Slide 101 is described below.

AHRQ Quality Indicators
  • Now, we are going to briefly discuss the AHRQ Quality Indicators.
 
 
Slide 102

Slide 102 is described below.

AHRQ Quality Indicators
  • Creates measures of healthcare quality using inpatient administrative data
  • Four Quality Indicator modules:
    1. Prevention Quality Indicators (PQIs)
    2. Inpatient Quality Indicators (IQIs)
    3. Patient Safety Indicators (PSIs)
    4. Pediatric Indicators (PDIs)
 
 
Slide 103

Slide 103 is described below.

Screenshot of AHRQ Quality Indicators Homepage
  • The AHRQ quality indicators and all of the tools we have presented are updated annually to take into account annual coding changes.
  • The v2019 software supports FY 2019 (October 2018 to September 2019) data.
  • To learn more about the AHRQ Quality Indicators, you can visit the AHRQ QI Website: www.qualityindicators.ahrq.gov
 
 
Slide 104

Slide 104 is described below.

AHRQ Value-Added Clinical and Quality Measurement Tools
HCUP Software Tool ICD-9-CM ICD-10-CM/PCS (Beta) ICD-10-CM Diagnoses CPT© Procedure Codes
Clinical Classifications Software (CCS) X* X
ICD-10-PCS only
  X*
Clinical Classifications Software Refined (CCSR) for ICD-10-CM diagnoses NEW     X
ICD-10-PCS only
 
Procedure Classes X* X    
Chronic Condition Indicator X* X    
Elixhauser Comorbidity Software X* X    
Utilization Flags X* X    
Surgery Flags X*     X*
AHRQ Quality Indicators
Prevention Quality Indicators X X    
Inpatient Quality Indicators X X    
Patient Safety Indicators X X    
Pediatric Quality Indicators X X    
*Included on the HCUP databases
 
 
Slide 105

Slide 105 is described below.

HCUP Supplemental Files
  • To conclude the section on HCUP Tools & Software, we will discuss the HCUP Supplemental Files.
 
 
Slide 106

Slide 106 is described below.

HCUP Supplemental Files Can Only be Applied to HCUP Databases
  • Cost-to-Charge Ratio (CCR) Files
  • Hospital Market Structure (HMS) Files
  • Trend Weights Files (NIS & KID)
  • NIS Hospital Ownership File
 
 
Slide 107

Slide 107 is described below.

Cost-to-Charge Ratio (CCR) Files
  • Enable conversion of charge data to cost data on the SID, NIS, KID, and NRD
    • Hospital-Level data
    • Apply Ratios
    • Convert Total Charges to Costs
 
 
Slide 108

Slide 108 is described below.

Hospital Market Structure (HMS) Files
  • Contain various measures of hospital market competition
  • Allow users to broadly characterize the intensity of competition that hospitals face
    • Using various definitions of market area
 
 
Slide 109

Slide 109 is described below.

Additional HCUP Supplemental Files
  • Trend Weights Files (NIS & KID)
    • Provide trend weights and data elements that are consistently defined across data years to address the NIS sample redesign in 2012 and the KID sample redesign in 2000
  • AHA Linkage Files
    • Enable researchers to link hospital identifiers in some State Databases to the AHA Annual Survey Databases
www.hcup-us.ahrq.gov/tools_software.jsp
 
 
Slide 110

Slide 110 is described below.

Screenshot of HCUP Tools & Software Homepage
 
 
Slide 111

Slide 111 is described below.

Presentation Objectives Part II
  • HCUPnet Overview
  • HCUP Fast Stats
  • Add Value to Your Databases with HCUP Tools & Software
  • Publications and Publication Search
  • How to Access HCUP Resources
 
 
Slide 112

Slide 112 is described below.

HCUP Publications
  • Statistical Briefs
  • Methods Series Reports
  • Screenshot of HCUP Statistical Brief and Methods Series Report
 
 
Slide 113

Slide 113 is described below.

Statistical Brief Topics
  • Screenshot of three HCUP statistical briefs.
  • HCUP Statistical Briefs are short, focused reports on topics related to specific conditions, procedures, or populations. Statistical Briefs are useful to a wide variety of audiences, including policy analysts, decision makers, media personnel, and others in need of summary facts and figures on current healthcare issues.
 
 
Slide 114

Slide 114 is described below.

HCUP Methods Reports
  • Screenshot of four HCUP Methods Reports
  • Methodological information on the HCUP databases and software tools
  • The HCUP Methods Series Reports feature a broad array of methodological information on the HCUP databases and software tools.
 
 
Slide 115

Slide 115 is described below.

HCUP Findings-At-A-Glance
  • Provide focused look at different topics across a broad range of health policy issues relate to hospital use and costs
  • Examples of current report topics:
    • Wildfires in California: Emergency Department Visits, 2018
    • Suicidal Ideation, Suicide Attempt, or Self-Inflicted Harm: Pediatric Emergency Department Visits, 2010-2014 and 2016
    • Neonatal Abstinence Syndrome Births: Trends in the United States, 2008-2019
 
 
Slide 116

Slide 116 is described below.

HCUP-US for HCUP Reports and Publications Search
  • Screenshot of the Reports page, showing where you can access Statistical Briefs, HCUP Methods Series reports, and HCUP Publications.
www.hcup-us.ahrq.gov/reports.jsp
 
 
Slide 117

Slide 117 is described below.

Publications Search Page on the HCUP-US Website
  • Simple or advanced search options
    • Data Year
    • Database, Tool, and Product
    • Author
    • Title
    • State
Over 8,500 peer-reviewed publications using HCUP data, products, or tools
 
 
Slide 118

Slide 118 is described below.

HCUP Supports High Impact Health Services, Policy, & Clinical Research
  • Pictures of logos from some of the government reports, e-journals, magazines, and newspapers that have used HCUP data, tools, and products.
 
 
Slide 119

Slide 119 is described below.

Presentation Objectives Part II
  • Tools & Software
  • Supplemental Files
  • HCUPnet Overview
  • HCUP Fast Stats
  • Publications and Publication Search
  • How to Access HCUP Resources
 
 
Slide 120

Slide 120 is described below.

HCUP User Support Website
  • Find detailed information on HCUP databases, tools, and products
  • Access HCUPnet, HCUP Fast Stats, the Central Distributor, Online Tutorials, and more
  • Find comprehensive list of HCUP-related publications, database reports, and fact books
  • Access technical assistance
  • Visit us at www.hcup-us.ahrq.gov
 
 
Slide 121

Slide 121 is described below.

Using HCUP Technical Assistance
  • Technical Assistance Team
    • Responds to inquiries about HCUP data, products, and tools
    • Collects user feedback and suggestions for improvement
Email: hcup@ahrq.gov
 
 
Slide 122

Slide 122 is described below.

Interactive Online HCUP Tutorials and Training Courses
  • HCUP Overview Course
  • Producing National HCUP Estimates
  • Load and Check HCUP Data
  • HCUP Tools Loading
  • Calculating Standard Errors
  • HCUP Sample Design
  • Multi-Year Analysis
  • Nationwide Readmissions Database (NRD)
 
 
Slide 123

Slide 123 is described below.

Join the HCUP E-mail List
  • HCUP Newsletter, published quarterly
    • User Tech Tips
    • Upcoming Events
  • New Data Releases
  • New Reports
https://subscriptions.ahrq.gov/accounts/USAHRQ/subscriber/new?topic_id=USAHRQ_65
 
 
Slide 124

Slide 124 is described below.

Questions/Comments?
 

Internet Citation: HCUP Overview Presentation. Healthcare Cost and Utilization Project (HCUP). April 2021. Agency for Healthcare Research and Quality, Rockville, MD. www.hcup-us.ahrq.gov/news/exhibit_booth/hcup_90_min_pres.jsp.
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