Building Capacity for Supply-Side Modeling, Simulation, and Research:

On September 21, 2011, Claudia Steiner made this presentation at the 2011 Annual Conference. Select to access the PowerPoint® presentation (4.8 MB). Plugin Software Help.

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Building Capacity for Supply-Side Modeling, Simulation, and Research: An Example Using Healthcare Cost & Utilization Project (HCUP) Data to Improve Timeliness of Estimates

September 21, 2011

Claudia Steiner, M.D, M.P.H.

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What is HCUP?

• HCUP is:
  • Longitudinal Multi-Year and All-Payer, Inpatient, Emergency Department, and Ambulatory Surgery Databases based on Hospital Billing Data.

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The Foundation of HCUP Data is Hospital Billing Data

Image: Two documents are shown with sections for Demographic Data; and Diagnoses, Procedures, and Charges indicated by brackets and captions.

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The HCUP Partnership

Image: A map of the United States, the Capitol Building, and a hospital are shown to represent the following partners, respectively:

• State.
• Federal.
• Industry.

Double headed arrows point between these three partners to indicate that the relationship is cyclical and mutual.

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Partnership: HCUP Database Participation By State

Image: A map of the United States is shown. States that are Non-participating, Partners Providing Inpatient Data Only, Partners Providing Inpatient & Ambulatory Surgery Data, Partners Providing Inpatient & Emergency Department Data, and Partners Providing Inpatient, Ambulatory Surgery, & Emergency Department Data are highlighted in different colors.

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HCUP Has Six Types of Databases

• Three state-level databases:
  • State Inpatient Databases (SID).
  • State Emergency Department Databases (SEDD).
  • State Ambulatory Surgery Databases (SASD).

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HCUP Has Six Types of Databases

• Three nationwide databases:
  • Nationwide Inpatient Sample (NIS).
  • Kids' Inpatient Database (KID).
  • Nationwide Emergency Department Sample (NEDS).

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What Types of Care Are and Are Not Captured by HCUP?

Included in HCUP
Inpatient care	State Inpatient Databases (SID) Nationwide Inpatient Sample (NIS) Kids' Inpatient Database (KID)
Emergency Department	State Emergency Department Databases (SEDD) Nationwide Emergency Department Sample (NEDS)
Ambulatory Surgery	State Ambulatory Surgery Databases (SASD)

 

Not Included in HCUP
Physician office visits
Pharmacy
Labs/Radiology

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Where Do We Get HCUP Data?

Image: A pie chart shows the following data:

Typically not included in HCUP data: 14% (N=805):

• Federal.
• Other/Long-Term Care.

Included in HCUP data: 86% (N=5,010):

• Community.

HCUP data is mostly from community hospitals.

Source: American Hospital Association (AHA), 2008.

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What Are Community Hospitals?

American Hospital Association Definition: Non-Federal, short-term, general, and other specialty hospitals, excluding hospital units of other institutions (e.g., prisons).

Included	Excluded
Multi-specialty general hospitals	Long-term care
OB-GYN	Psychiatric
ENT	Alcoholism/Chemical dependency
Orthopedic	Rehabilitation
Pediatric	DoD / VA / IHS
Public
Academic medical centers

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Accelerating HCUP Data and Information

• Need for timely projections on trends:
  • Provide analysts and policy makers timely information that can be used to evaluate the impact of quality improvement efforts.
  • HCUP Nationwide Inpatient Sample (NIS) typically lags the current calendar year by 17 months:
    • 2009 NIS available in June 2011.
• Demonstrate feasibility of producing gap-year national estimates.
• Demonstrate feasibility of collecting and processing quarterly data.

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Which HCUP Partners Collect Quarterly Data?

• A total of 40 of 44 States (91%) reported that they collect data at more frequent intervals than annually:
  • 23 States collect quarterly data (AR, CT, FL, GA, HI, IA, IL, IN, KY, MA, ME, MD, MI, MN, MO, MT, NC, NE, NM, NY, OH, OR, PA, RI, TN, TX, UT, VA, VT, WI & WY).
  • 4 States collect monthly data (NJ, SC, WA & WV).
  • 3 States collect both quarterly and monthly data (CO, NH & NV).
  • 2 State collects semi-annual data (AZ, CA).
• Four of the 44 States do not collect data more frequently than annually: Kansas, Louisiana, Oklahoma, and South Dakota.

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HCUP Data for Timely National Projections

• Factors that contribute to success of the initiative:
  • Longitudinal nature of the HCUP databases:
    • 1988 forward.
  • Breadth of data across 44 states:
    • 295 million inpatient discharges from the 2001 to 2009.
  • Capacity of states to produce early quarterly data.
  • Modeling expertise at AHRQ and contract staff.
  • Availability of SAS Econometric Time Series Software.
  • Leveraging of report technology developed under the National Healthcare Quality Report (NHQR).

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Selected Healthcare-associated Infections (HAIs) and Outcomes

• Eight HAIs selected; six reported separately for adults and pediatrics.
• The HAIs reported in this study may have originated from either inpatient or outpatient health care services.
• HAIs are identified by a principal or secondary diagnosis on an inpatient stay.
• Indication that the diagnosis was present on admission (POA) could not be considered because POA is not available in historical SID.
• Approach provides nationwide, population-based�prevalence instead of the hospital-based performance or accountability measures.

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Five Outcomes of Interest

• Projections focus on hospital utilization and outcomes:
  • Number of inpatient discharges.
  • Rate per 1,000 discharges.
  • Average total charge (includes hospital services, no professional fees, not inflation-adjusted).
  • Average length of stay.
  • In-hospital mortality rate.

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Postoperative Sepsis (Adult)

Image: Line graph shows the observed and projected postoperative sepsis rate rising from 2001 to 2010.

• Population at risk: Elective, non-maternal, adult, surgical discharges with a length of stay ≥ four days, excluding discharges with any diagnosis of immunocompromised state, discharges with any diagnosis of cancer, and discharges with a principal diagnosis of infection.

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Postoperative Sepsis (Pediatric)

Image: Line graph shows the observed and projected postoperative sepsis rate rising slightly from 2001 to 2010.

• Population at risk: Non-neonatal, pediatric, surgical discharges with a length of stay ≥ four days, excluding discharges with a principal diagnosis of infection or a DRG indicating surgery for likely infection.

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Clostridium Difficile Infections (Adult)

Image: Line graph shows the observed and projected C. difficile infection rate rising from 2001 to 2010.

Population at risk: Non-maternal, adult discharges.

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Clostridium Difficile Infections (Pediatric)

Image: Line graph shows the observed and projected C. difficile infection rate rising from 2001 to 2010.

Population at risk: Pediatric discharges.

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HCUP Data for Timely National Projections

• HCUP projections in newest report are based on:
  • 295 million inpatient discharges from the 2001 to 2009 HCUP SID.
• "Early" 2010 data from 14 selected HCUP States that submitted data by July 2011.
• Ten cardiovascular / cerebrovascular conditions and procedures selected:
  • Each stratified by adult age (18-44, 45-64, 65+) and gender.

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Five Outcomes of Interest

• Projections focus on hospital utilization and outcomes:
  • Number of inpatient discharges.
  • Average total cost (includes hospital services, no professional fees, not inflation-adjusted).
  • Average length of stay.
  • In-hospital mortality rate.

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Acute Myocardial Infarction (Adult Age Group)

Image: Line graph shows the observed and projected acute myocardial infarction rates from 2001 to 2011 for adults aged 18-44, aged 45-64, and over 65.

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Acute Myocardial Infarction (Gender)

Image: Line graph shows the observed and projected acute myocardial infarction rates from 2001 to 2011 for males and females.

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HCUP Data Mining

• Purpose: Use early 2010 State Inpatient Data to identify diagnoses and procedures for which observed outcomes in 2010 digressed substantially from those outcomes predicted for 2010 using historical data from 2001-2009.
• Method: Analyze normalized residuals to identify the 2010 residuals that were statistical outliers compared with residuals observed during the 2001-2009 baseline period. These outlier residuals indicate potentially radical changes to the established trend for the outcome under consideration.

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Procedure Categories with Substantial Deviations Between Actual vs. Expected

Image: A chart lists Procedure Categories with Substantial Deviations Between Actual vs. Expected.

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Questions?

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Healthcare Cost and Utilization Project (HCUP)

Image: The HCUP logo is shown.