HOSPITAL STRENGTH INDEX™
METHODOLOGY 2015
February 2015
HOSPITAL STRENGTH INDEX - 2015
The Hospital Strength INDEX™ is the industry’s most comprehensive and straightforward
method for comparing hospital performance in the new healthcare.
iVantage aggregates hospital-specific data for 62 performance indicator variables, and calculates each hospital’s
percentile rankings compared to all hospitals in the study group. Aggregate scores across the nine pillars serve as the
basis for a single overall rating – the Hospital Strength INDEX.
Data Summary
Unless otherwise noted, data used to produce the INDEX are available from public sources, primarily the federal
government. All available data are included. Statistical sampling and data projection methodologies are employed only
when necessary.
Each INDEX release is based on the most recently available data for each indicator source. All information included
in this release (version 3.0) represents the most recently available data as of December 2014.
Figure 1
PILLAR
DATA SOURCE
HOSPITAL STRENGTH INDEX 2015
Inpatient Share
Outpatient Share
Population Risk
CMS
Service Area File 2011 - 2013
CMS
Standard Analytical File O/P 2011 - 2013
CMS, Robert Wood Johnson
Service Area File 2013, ACO Service Area Table 2012, 2014
County Health Rankings
Cost
CMS
Charge
CMS
MedPAR 2013 Final Standard Analytical File, O/P 2013,
HCRIS Q3 2014
MedPAR 2013 Final, Standard Analytical File O/P 2013
Quality
Outcomes
CMS
12/18/2014 Hospital Compare Download Date
CMS
12/18/2014 Hospital Compare Download Date – Mortality and
Readmissions, MedPAR 2011-2013 Final
Patient Perspectives
CMS
12/18/2014 Hospital Compare Download Date – HCAHPS
Financial Strength
CMS, iVantage Health Analytics
CMS Hospital Cost Report Information Systems (HCRIS Q3
2014) Proprietary Hospital Master Table for Hospital Chain
(note: Hospital Master is the only non-public dataset)
Note: see Appendix 1 for details on time periods covered in each dataset.
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HOSPITAL STRENGTH INDEX - 2015
Methodology Summary
The INDEX is based on a composite measure of nine pillars of hospital strength: Inpatient Share Ranking, Outpatient
Share Ranking, Population Risk, Cost, Charge, Quality, Outcomes, Patient Perspectives, and Financial Strength.
Pillars are made up of individual indicator variables that comprise the “indicator level”. Indicators are also grouped into
three categories (the “index level”, used for reporting purposes): Risk, Value, and Performance. The following notes
apply to the INDEX calculation methodology:
1. Source information comprised of “raw” indicator variables is compiled; in some instances, as in the
case of Medicare market share calculations, weighting and/or standardization are performed.
2. For pillars with multiple composite percentile scores, averages are calculated across all percentile
scores to derive a pillar average.
3. Calculated indicator-level scores are derived from raw values.
4. National percentile rankings are calculated for each composite (pillar) score to obtain a percentile ranking.
5. Indicators that cannot be ranked due to missing or excluded data are discarded in pillarlevel calculations.
6. When calculating the overall INDEX score, missing pillars are imputed based on the mean of all
the other non-missing pillars.
7. When calculating INDEX values (Risk, Value, and Performance), missing pillars are imputed
based on the mean of the other non-missing pillars within their category.
Hospitals in the Study Group
The INDEX strives to include all eligible U.S. active, short-term, acute care, non-specialty, non-federal hospitals in the
study group (includes Critical Access Hospitals). The most recently available CMS Hospital Provider of Services (POS)
file is used to determine the initial population of eligible hospitals. The file contains an individual record for each
Medicare-approved provider and is updated quarterly. This dataset is cross-checked against other available sources of
record, including the AHA Hospital Directory, to confirm hospital identity and status, and to further determine
appropriateness for inclusion.
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HOSPITAL STRENGTH INDEX - 2015
Exclusions are based on the following criteria:
1. Specialty Hospitals:
a. Hospitals designated as specialty hospitals in the CMS Hospital Provider of Services file
are excluded; these include psychiatric, rehab, long-term care, surgical specialty and
other specialty facilities;
b. Governmental facilities including Veterans Administration, Indian Health Service hospitals
and related federal facilities are excluded;
c. Acute hospitals with 80 percent of their MS-DRG inpatient case mix concentrated in three or fewer
Major Diagnostic Categories (MDCs) are excluded; and
d. Hospitals designated as cancer centers and children’s or pediatric hospitals are also excluded.
2. Geography:
Hospitals in outlying U.S. Territories are excluded, e.g., Samoa, Virgin Island, P.R.
3. Data Exclusions:
a. Hospitals with missing or implausible critical financial indicators, including revenue and balance
sheet data, in their Medicare Hospital Cost Report Information System (HCRIS) filings are excluded;
b. Hospitals missing scores due to lack of supporting data in two or more risk pillars, or three or
more value pillars are excluded; and
c. Hospitals missing the outcomes pillar are excluded.
4. New or Changed Hospitals:
a. New hospitals and facilities that began participating in the Medicare program in 2013,
including facilities that changed classification (such as conversion to a Critical Access
Hospital), are excluded;
b. This process identified a total of 4,334 hospitals that were included in the final study. Of that total,
1,291 facilities are designated as Critical Access hospitals.
5. General Note:
If a hospital does not appear in Hospital Compare, they receive a score of zero. If the hospital
appears but the data are suppressed by CMS, then those data are counted as missing and no
penalization occurs.
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HOSPITAL STRENGTH INDEX - 2015
Risk Index Components
The following service area definitions are used for all Risk category calculations:
1. The list of zip codes is taken from three years’ worth of data that contain 75% of the total Medicare
case count
2. Zips that have less than an average of one (1) case per year are removed
3. Zips that have a center point more than 150 miles from the facility are removed
4. Home zip code is added
Figure 2
PILLAR
Category
Indicator
Data
Methodology
Scoring
Inpatient Share Ranking
Risk
Target HHI - Target Hospital’s Herfindahl-Hirschman Index (HHI) score
Service Area File
The above service area is used to compute a Herfindahl-Hirschman Index (HHI) score. The target hospital’s
Herfindahl-Hirschman Index (HHI) score is then derived as the square of the market share percentage expressed
on a scale from zero to 10,000.
Percentile rankings are calculated based on the market share scores. Higher scores receive higher rankings. Pillar
scores are then calculated as outlined in the methodology detailed above.
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HOSPITAL STRENGTH INDEX - 2015
Figure 3
PILLAR
Category
Indicator
Data
Methodology
Scoring
Notes
Outpatient Share Ranking
Risk
Target Facility’s Outpatient Market Share – Cardiac Surgery
Target Facility’s Outpatient Market Share – Other Surgery
Target Facility’s Outpatient Market Share – Emergency
Target Facility’s Outpatient Market Share – Diagnostic and Therapeutic Services
Outpatient (OP) Standard Analytical File
Each hospital’s category specific market share is first calculated based on the three year, 75% county outpatient
service area (each category will have separate market definitions). Market share values are then computed based
on the most recent year of data for each category. National percentile scores are then calculated and rolled up to
get the overall OP Share ranking score. (In order to better focus competition at the market level and reduce the
data “noise” influenced by factors like extremely low case counts or cases from relatively distant Federal
Information Processing Standard (FIPS) codes).
Percentile rankings are calculated based on the market share scores. Higher scores receive higher rankings. Pillar
scores are then calculated as outlined in the methodology detailed above.
The OP procedures are rolled up to the highest ranking category by case. The hierarchy goes in the following
order: cardiac surgery, other surgery, emergency, and diagnostic and therapeutic services. Any cases that do not
fall into those categories are excluded from analysis.
Figure 4
PILLAR
Category
Indicators
Data
Scoring
Notes
POPULATION RISK
Risk
Weighted Average of Ambulatory care-sensitive conditions rate per 1000 Medicare enrollees (based on county
level information)
Weighted Average of ACO Medicare spend per beneficiary grand rate (based on county level information)
Weighted Average of % of population receiving HbA1c screening (based on county level information)
Weighted Average of years of potential life lost below age 75 per 100k Pop (based on county level information)
Weighted Average population to mental health provider ratio (based on county level information)
Service Area File, ACO Spend File, County Health Rankings
An aggregate score for each facility is calculated by multiplying Years of Potential Life Lost (YPLL), Ambulatory
Care Sensitive Conditions (ACSC), Population to Behavioral Health Provider Ratio, and HbA1c screen rankings by
a weight factor based on the county level market share for each FIPS code in a hospital’s service area. An
aggregate Medicare per Beneficiary Grand Rate value is calculated for the hospital’s market service area. The
Grand Rate value consists of total annual Medicare payments for Inpatient, Outpatient and Physician services.
Percentile rankings are calculated based on the indicators above. Lower scores for Grand Rate, Behavioral
Health, YPLL and ACSC are better, while higher scores are better for HbA1c. Pillar scores are then calculated as
outlined in the methodology above.
FIPS codes missing data for any of the four health factor measures are excluded and FIPS codes missing data for
ACO Grand Rate are excluded.
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HOSPITAL STRENGTH INDEX - 2015
Figure 5
PILLAR
Category
Indicators
Data
Methodology
COST
Value
Medicare Case-Mix Adjusted Average Costs – Inpatient
Medicare Case-Mix Adjusted Average Costs – Outpatient
MedPAR, Outpatient Standard Analytical File, HCRIS
An overall average cost-to-charge ratio is computed for each hospital based on total charges and costs as
reported in the Medicare Hospital Cost Report Information System. To calculate inpatient average costs, a
hospital’s cost-to-charge ratio is applied to MedPAR inpatient charge data at the claim/patient level and adjusted
based on the CMS-assigned case weight for that claim’s MS-DRG code. A hospital’s costs are aggregated for all
inpatients to derive overall averages.
To calculate outpatient average costs, a hospital’s cost-to-charge ratio is applied to Medicare Outpatient Standard
Analytical File charge data at the claim/HCPCS level and adjusted based on the CMS-assigned case weight for
that claim’s APC (Ambulatory Payment Classification) code. A hospital’s costs are aggregated for all outpatients to
derive overall averages.
Percentile rankings are calculated based on the each cost indicator. Lower scores receive higher rankings. Pillar
scores are then calculated as outlined in the methodology detailed above.
Scoring
Figure 6
PILLAR
Category
Indicator
Data
Methodology
Scoring
CHARGE
Value
•Medicare Case-Mix Adjusted Average Charges – Inpatient
•Medicare Case-Mix Adjusted Average Charges – Outpatient
MedPAR, Outpatient Standard Analytical File
To calculate a hospital’s average inpatient charge score, claims data from MedPAR are adjusted for case mix and
wage index to derive an average charge per Inpatient admission. A hospital’s charges are aggregated for all
inpatients to derive overall averages.
To calculate a hospital’s average outpatient charge score, claims data from the Medicare Outpatient Standard
Analytical File are adjusted for case mix and wage index to derive an average charge per outpatient visit or
procedure. A hospital’s charges are aggregated for all Outpatients to derive overall averages.
Percentile rankings are calculated based on the each charge indicator. Lower scores receive higher rankings.
Pillar scores are then calculated as applicable per the methodology detailed above.
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HOSPITAL STRENGTH INDEX - 2015
Figure 7
PILLAR
Category
Indicator
Data
Methodology
Scoring
Notes
QUALITY
Value
Hospital Compare Process of Care Measures
Hospital Compare Process of Care Measures (# of Measures):
• Heart Attack (four)
• Heart Failure (three)
• Pneumonia (one)
• Surgical Care Improvement Program (SCIP) (eight)
• Outpatient (seven)
Averages of indicator measures (percentages) are calculated to produce pillar composite scores. All available
data are used in the calculation of averages. Missing data within measure sets are ignored unless a footnote in
the data denotes that a hospital chose not to submit data for all measures used in the pillar.
Percentile rankings are calculated based on each CMS Process of Care indicator. Higher scores receive higher
rankings. Pillar scores are then calculated as outlined in the methodology detailed above.
The initial quality indicators incorporated in the HOSPITAL STRENGTH INDEX represent the most generally
established and accepted public measure sets in the industry. Newer, more controversial measures and measures
that are not broadly representative have been purposefully omitted. The incorporation of additional measures in
future methodology will be considered based on industry consensus and acceptance.
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HOSPITAL STRENGTH INDEX - 2015
Figure 8
PILLAR
Category
Value
Indicators
Data
Notes
Hospital Compare 30-Day All-Cause Mortality Rates for AMI, HF and PN
Hospital Compare 30-Day Hospital Readmission Rates for AMI, HF and PN
Proprietary Risk Adjusted in Hospital All Condition Mortality – Lives Saved/Standard Deviation
AHRQ Patient Safety Indicators (PSI) – Composite Score
Hospital Compare Mortality and Readmission, MedPAR
Methodology
Scoring
OUTCOMES
For the Hospital Compare Mortality and Readmission indicators, mean averages are calculated to produce
composite scores. For the proprietary calculation of in-hospital mortality from any cause, data were first stratified by
DRG cluster. In clusters with lower mortality rates, contingency tables were used to stratify according to age category
and number of comorbidities. National per-stratum rates were used to calculate expected rates for each hospital. In
clusters with higher mortality rates, logistic regression models were fit, adjusting for age, gender, cluster-specific
comorbidities, and admission source. Expected rates from the contingency table and logistic models were applied to
each hospital’s patient base by running patient characteristics through the contingency tables/ models (risk
adjustment). An overall expected mortality rate was derived for each hospital and compared to the actual number of
deaths reported for that hospital in the MedPAR dataset. Finally, the number of positive or negative standard
deviations from the expected rate was calculated for each hospital. The AHRQ QI SAS® v4.5 software is applied to
2013 MedPAR data to generate the PSI Composite Score for each hospital.
For Hospital Compare Mortality and Readmission, lower scores receive higher rankings. For the proprietary mortality
indicator, percentile rankings are calculated based on the number of standard deviations from the expected rate, and
a higher number of positive standard deviations receives a higher ranking; a higher number of negative standard
deviations receives a lower ranking. Percentile rankings are calculated based on the PSI Composite scores. Lower
scores receive higher rankings. Index scores are then calculated as outlined in the methodology detailed above.
Weighting of the Outcomes component is as follows: Hospital Compare Mortality and Readmission (each equally
weighted): 33%, Proprietary Inpatient Mortality: 33%, PSI: 33%. Pillar scores are then calculated as outlined in the
methodology detailed above.
For the proprietary mortality indicator, among inpatients age 65 or older at critical access and acute care hospitals,
specific reasons for the exclusion were as follows: stayed less than two days (unless died), left against medical
advice, transferred out, or assigned DRGs 981-999. For more information on AHRQ PSI, see
http://www.qualityindicators.ahrq.gov/Modules/psi_overview.aspx
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HOSPITAL STRENGTH INDEX - 2015
Figure 9
PILLAR
Category
Indicator
Data
Methodology
Scoring
PATIENT PERSPECTIVES
Value
Percent of Respondents Who Would Definitely Recommend the Hospital
HCAHPS Percent of Respondents Who Would Definitely Recommend the Hospital
Percentile rankings are calculated based on the percentage score of the respondents indicating they would
“definitely recommend” the hospital.
Percentile rankings are calculated based on the survey scores. Higher scores receive higher rankings. Pillar
scores are then calculated as outlined in the methodology detailed above.
Figure 10
PILLAR
Category
Indicators
Data
Methodology
Scoring
Notes
FINANCIAL STRENGTH
Performance
Total Liability/Total Assets, Net Working Capital/Total Liabilities, Net Income/Total Revenue, Total Assets/Total
Expenses
CMS Hospital Cost Report Information Systems (HCRIS), EDGAR Fillings, Merit Financial Press, LLC audited
financial statements.
The above ratios are calculated for each hospital based on the most recent available HCRIS Hospital Cost Report
data, except for large national hospital systems as noted below. The capital efficiency ratio is weighted at 40
percent of the Financial Stability Index. The other three indicators are equally weighted to calculate the remaining
60 percent. This weighting adjusts for a number of factors, most notably that the capital efficiency ratio is the
single best predictor of hospital solvency as indicated in the research study cited below. It also balances the use
of a single income statement to multiple balance sheet ratios.
For large national investor-owned and not-for-profit healthcare systems, the systems’ consolidated ratios for
leverage, liquidity, and resource availability are used for the facilities in a system in place of HCRIS data. These
data are sourced from SEC Edgar filings and audited cost reports from Merritt Research Services, LLC. The
capital efficiency indicator is based on HCRIS Hospital Cost Report data for all hospitals included in the study.
Percentile rankings are calculated based on each financial indicator. Higher scores receive higher rankings for all
indicators except leverage, where lower scores receive higher rankings. Index scores are then calculated as
outlined in the methodology detailed above.
The Financial Stability Index is adapted from academic research that identified the financial ratios most correlated
to long-term fiscal viability. See: Lynn, M., & Wetheim, P. (1993). Key Financial Ratios Can Foretell Hospital
Closures. HFMA Journal, 47(11), 66-70. The use of consolidated ratios for large systems is necessary in order to
produce comparable metrics across the broadest hospital sample, as the accounting and cash flow management
practices of these systems impacts HCRIS balance sheet reporting.
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HOSPITAL STRENGTH INDEX - 2015
Appendix 1:
Data Set Name
Data Source
Data Available
Dates Contained in the
File
Service Area File 2013
HCRIS Q3 2014
CMS
CMS
May 2014
October 18, 2014
MedPAR 2013 Final Rule
Demographics 2013-2018
Update
ACO Service Area Table 2012
2014 County Health Rankings
CMS
ESRI
September 2014
September 2013
January 2013-December 2013
Most recent cost report provided
as of 09/30/14
October 2012-September 2013
January 2013-December 2013
October 2013
March 2014
January 2012-December 2012
2008-2011
Hospital Compare
CMS
Robert Wood Johnson
Foundation
CMS
December 18, 2014
SAF – OP 2013
Hospital Master
CMS
iVantage Health Analytics
November 2014
December 2014
Mortality and Readmission –
7/1/2010-6/30/2013 Hospital
Measures and HCAHPS –
01/1/2013 – 03/31/2014
October 2012 – September 2013
The most current hospital
information as of December 2014
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HOSPITAL STRENGTH INDEX - 2015
About iVantage Health Analytics
iVantage is a leading advisory and business analytic services company applying AHT – Accelerated Healthcare
Transformation™ and the VantagePoints platform to drive sustained, evidence-based results. The company’s
unique combination of technology, content, and expert advisory services accelerates decision making for the
new healthcare. Visit www.iVantageHealth.com.
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