APPENDIX 2: DETAILED METHODOLOGY
March 31st, 2014
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Detailed Methodology
Introduction
This methodology report is intended to provide more detailed information about the analysis
underlying the Minnesota Provider Peer Grouping (PPG) Hospital Total Care Report. It provides
information about the data sources used for the analysis, as well as methods developed and employed
for the calculation of risk-adjusted costs and assignment of quality scores.
The methodology in the current report has evolved considerably from the initial rounds of confidential
reporting based on a number of inputs including:

Recommendations from Minnesota Department of Health’s (MDH’s) 2013 Advisory Group;

Feedback from MDH’s Reliability Workgroup and Rapid Response Team;

Stakeholder feedback, including that from hospitals and health systems in response to MDH’s
release of reports in the Fall of 2011 and Spring 2013; and

MDH and Mathematica’s analytic and research work.
While the current methodology represents a comprehensive well-vetted and thoroughly tested
approach, for future versions of this report we will continue to consider feedback from MDH’s current
advisory bodies and stakeholder groups.
Calculation of Hospital Total Care Quality Score
Quality Measures
Consistent with the PPG Advisory Group’s recommendation, quality measures used in this report were
the most recently available measures at the time of the analysis. The available quality measures for the
total care quality composite vary by hospital peer group. For hospitals designated as Prospective
Payment System (PPS) hospitals, a maximum of 55 measures were scored for inclusion in the Total
Care Quality Score (Appendix Table 1). The measures are grouped into categories, or “domains,”
which are scored separately. The Processes of Care (20 measures) and Outcomes of Care (25
measures) domains account for 45 measures. The Outcomes of Care domain comprises three
subdomains: Readmissions (3 measures), Mortality (8 measures), and Inpatient Complications and
Infections (14 measures). For PPS hospitals, the Patient Experience domain (10 measures) is also
included in the Total Care Quality Score.
For Critical Access Hospitals (CAHs), the Total Care Quality Score is based on a maximum of 28
quality measures because some of the PPS measures address types of health care services that are not
as regularly provided at CAHs. The quality measures are grouped into domains for Processes of Care
(15 measures) and Outcomes of Care (13 measures). The Outcomes of Care domain includes the
following subdomains: Readmissions (2 measures), Mortality (3 measures), and Inpatient
Complications and Infections (8 measures). For CAHs that have collected Patient Experience survey
data, those measures are reported here for informational purposes; these measures were not included in
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the computation of the Total Care Quality Score.
Data Sources
The data for all quality measures in the total care composite come from a variety of publicly reported
sources. Most measures are incorporated in the Minnesota Statewide Quality Reporting and
Measurement System (SQRMS)1 publicly reported by MDH.

The Processes of Care measures for acute myocardial infarction (AMI), heart failure,
pneumonia, surgical care infection prevention (SCIP), and influenza immunization are from the
Centers for Medicare & Medicaid Services’ (CMS’s) hospital inpatient quality reporting
program, reported on Hospital Compare (http://www.medicare.gov/hospitalcompare/).
Hospitals directly report process of care measures to CMS as part of the Hospital Inpatient
Quality Reporting program, based on medical records of care provided to all patients.

The 30-day readmission and mortality measures for AMI, heart failure, and pneumonia—all in
the Outcomes of Care domain—are also from CMS Hospital Compare. CMS calculates 30-day
mortality and readmission measures using claims/billing data for Medicare fee-for-service
patients ages 65 and older only.

Two Processes of Care measures for infection control for intensive care unit (ICU) patients
(central line infection bundle compliance and ventilator-associated pneumonia bundle) and two
Outcomes of Care inpatient complications and infections measures (surgical site infections
[SSI] following vaginal hysterectomy and total knee arthroplasty) are obtained from the
Minnesota Hospital Association (MHA). See http://www.mnhospitalquality.org/measures.aspx
for more information.

Eight of the inpatient complications and infections measures in the Outcomes of Care domain
are from the Agency for Healthcare Research and Quality (AHRQ) patient safety indicators
(PSI) module (http://www.qualityindicators.ahrq.gov/Modules/psi_overview.aspx). Five of the
mortality measures in the Outcomes of Care domain are from the AHRQ inpatient quality
indicators (IQIs) module (http://www.qualityindicators.ahrq.gov/Modules/iqi_overview.aspx).
Data for these measures are calculated by MDH, and are reported on
http://www.mnhealthscores.org, as well as on MDH’s health reform web site.

Four additional inpatient complications and infections measures for hospital acquired infection
(HAI)—central-line associated blood stream infection (CLABSI), catheter-associated urinary
tract infection (CAUTI), SSI following abdominal hysterectomy, and SSI following colon
surgery—come from Hospital Compare, from data collected by the Centers for Disease Control
and Prevention. National Healthcare Safety Network (NHSN) (http://www.cdc.gov/nhsn/).
1
The Statewide Quality Reporting and Measurement System (SQRMS) is Minnesota’s standardized set of quality measures
collected under Minnesota Statutes, Section 62U.02. This system was developed in response to bi-partisan health care
reform legislation in Minnesota that, among other initiatives, focused on improving the transparency in cost and quality of
health care in Minnesota.
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Peer Groups
An important characteristic of peer grouping is to compare hospitals with other hospitals that offer
similar services to a broadly similar case mix of patients. For this analysis, a hospital’s peer group is
comprised of all hospitals of the same type—either hospitals paid under Medicare’s Inpatient
Prospective Payment System (PPS hospitals) or hospitals designated as Critical Access Hospitals
(CAHs). Certain facilities were excluded from peer grouping analysis and reporting, including the
Veterans Health Administration hospitals and other government-owned hospitals, community health
centers, a facility that recently stopped providing hospital care, and a few specialty hospitals. In
addition, three Children's hospitals and 30 CAHs were excluded from analysis and reporting because
they did not meet the standards for quality reporting. Appendix Table 3 lists both of these groups of
excluded hospitals. Of the remaining 50 potential PPS hospitals in Minnesota, data from two pairs of
hospitals, each of which is operated by a single care system, were combined to create a single report
for both facilities. These exclusions resulted in 48 PPS hospitals and 48 CAHs eligible for inclusion in
these reports.
Assignment of Quality Points
In this report, hospitals could earn up to ten points on each quality measure for which they had
reported data. Before scoring, rates for negative outcomes (inpatient complications and infections,
mortality, and readmissions) were first subtracted from 100 percent, so that the measurement direction
of good performance could be assessed consistently across all measures. (For example, a mortality rate
of one percent would first be subtracted from 100 percent, yielding a “survival” rate of 99 percent, for
purposes of scoring.)
Points were assigned by comparing a hospital’s performance rate to each measure’s upper and lower
performance thresholds. The lower threshold for earning any points is fixed at 50 percent. The
benchmark for top (10) points depends upon the distribution of performance rates among those
hospitals in the same peer group that also report that quality measure. The benchmark was determined
according to the following rules:
A. If the median rate was  90 percent, the benchmark was the median performance rate of
hospitals in the peer group.
B. If the highest rate was  90 percent but the median was < 90 percent, the benchmark was 90
percent (absolute rate).
C. If the median and the highest rates were both < 90 percent, the benchmark was the best rate
among hospitals reporting the measure (maximum score).
For example, measures with very high scoring distributions might have a benchmark at or just below
100 percent (Rule A), while measures with much lower performance distribution might have a
benchmark of 85 percent (Rule C).
Points for each measure were then assigned as follows:
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
10 points if the hospital’s rate was at or above the benchmark

1 to 9 points, depending on where the hospital’s rate fell in nine evenly-spaced intervals
between 50 percent and the benchmark

0 points if the hospital’s rate was less than 50 percent.
Minimum Case Sizes
Hospitals must meet the relevant minimum case size (or denominator) requirement to have points
assigned and used in the calculation of the domain and Total Care Quality scores (Appendix Table 1).
There is an exception: If a CAH reported at least four measures in a domain and at least one measure
met the minimum case size while the others did not, then the rate for measures not meeting the
minimum case size were adjusted to reflect a weighted average between the hospital’s rate and the
mean among other CAHs. This is referred to as “imputation,” and the weight assigned to the hospital’s
imputed rate is proportional to the actual case size. For example, if a hospital had eight cases for a
measure with a minimum case size of ten, the hospital’s actual rate received a weight of 0.8 while the
peer group mean for the measure received a weight of 0.2. Points were assigned to both imputed and
non-imputed rates as described above. If an outcome measure rate was imputed, no confidence
intervals were calculated, and no test of statistically significant difference from the peer group mean
was reported in Table 3 of the report (see Risk Adjustment of Quality Measures).
Imputation was only performed when there were at least thirty total cases reported in the CAH peer
group and when the measure was reported by the individual hospital in question and by other CAHs.
Currently, this level of detail is not available from data obtained from CMS’s Hospital Compare (see
Appendix Table 1), so there are no imputed rates for these measures in this report.
In some PPS hospital and CAH reports, certain quality measures are reported that either did not meet
minimum case size or (in the case of CAHs) could not be imputed. These measures were not included
in the composite scoring, but are reported for informational purposes only.
Calculation of Domain Scores
CAHs and PPS hospitals both received domain scores for Processes of Care measures and Outcomes
of Care measures; PPS hospitals also received domain scores for Patient Experience measures. To
receive a domain score, PPS hospitals must have had at least six quality measures scored from each
domain, and CAHs must have had at least four. All scored measures contributed to the domain score.
The domain score, ranging from 0 to 100, was calculated as follows:
For example, if a hospital was scored on eight measures in a given domain, it could earn 80 total
possible points (10 per measure) for that subdomain. If that hospital earned 60 points on those eight
measures combined, then the subdomain score was
. Using this approach, the
domain score of different facilities might be based on different subsets of measures, because hospitals
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reported different measures.
Calculation of Total Quality Score
To receive a Total Care Quality Score, CAHs and PPS hospitals must have had domain scores for both
the Processes of Care and Outcomes of Care domains. In addition, PPS hospitals must have had
domain scores for the Patient Experience domain. The Total Care Quality Score, ranging from 0 to
100, was calculated as a weighted average of the domain scores. As shown below, greater weight was
placed on the Outcomes of Care domain (70 and 60 percent, respectively, for CAHs and PPS hospitals)
to reflect the greater importance of outcomes in assessing quality of care. The weights were as follows:
Domain
PPS
Composite Weight
CAH
Composite Weight
Processes of Care
20%
30%
Outcomes of Care
60%
70%
Patient Experience
20%
0%
As a final step in the calculation, the Total Care Quality Score was rounded to the nearest whole
number. For comparative purposes, hospital scores with the same whole number value were considered
equivalent. For example, if a CAH had a score of 60.355 on the Processes of Care domain and 75.524
on the Outcomes of Care domain, its Total Care Quality Score was calculated as follows:
Risk Adjustment of Quality Measures
Risk adjustment is a statistical process that adjusts the analysis of quality measurement by accounting
for those patient population characteristics that may independently affect results of a given measure
and are not randomly distributed across all providers submitting quality measures. By attempting to
adjust for patient factors that are beyond the control of providers and that may differ among patient
populations, risk adjustment allows for a more fair and equitable comparison of patient outcomes
across providers.
Not all measures require risk adjustment. For instance, the measures in the Processes of Care quality
domain were not risk adjusted, because measures reflecting whether a certain recommended process
took place are typically not related to patient characteristics.
The measures within the Outcomes of Care quality domain (composed of three subdomains or
categories of outcome: mortality, inpatient complications and infections, and readmissions) were risk
adjusted to reflect differences in patient risk factors that affect outcomes across hospitals. Measures in
the Outcomes of Care domain were adjusted using methodologies specific to each measure set: 30-day
mortality and 30-day readmissions were adjusted based on CMS methodology; the inpatient mortality
and inpatient complications and infections were adjusted using methodology developed by AHRQ2;
2
Certain AHRQ QIs (such as PSI 18- Obstetric Trauma – Vaginal Delivery with Instrument and PSI 19- Obstetric Trauma
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MHA methods were used for the surgical site infection rate for the vaginal hysterectomy measure and
total knee arthroplasty measures; and CDC methods were used for the hospital-acquired infection
(HAI) measures.
The approach to risk adjustment in the CMS 30-day and AHRQ outcomes measures vary and are
described elsewhere.3 However, both use an “indirect standardization” approach to risk adjustment.
This approach, in general, uses statistical models that measure the effect of patient risk factors (such as
age, gender, and pre-existing health conditions) on an outcome, and uses the results from the model to
estimate what a hospital’s expected outcomes would be if it were to treat an “average” patient
caseload.4 Under the AHRQ approach, the ratio of observed-to-expected outcomes is computed and
multiplied by a population rate to create a risk-adjusted rate for the hospital. This rate is further
adjusted (through a technique known as “smoothing”) by calculating the weighted average of the riskadjusted rate and a national rate (where the weight is a measure of reliability). The CMS approach to
risk adjustment uses a broader perspective by also accounting for “hospital-specific effects” on quality.
In this approach, a predicted rate that reflects the estimated rate with the hospital’s own quality effect
and the hospital’s patients is compared to an expected rate that reflects the estimated outcome with the
average quality effect for all hospitals and the hospital’s patients.
The surgical site infection rates for vaginal hysterectomy and total knee arthroplasty are adjusted using
a form of direct standardization.5 The vaginal hysterectomy rate is a combination of two rates produced
for each hospital: one for patients with any of three risk factors and one for patients with none of the
three risk factors. The risk factors are: (1) duration of the surgery greater than the recommended
amount of time; (2) wound class of III or IV; and (3) an ASA score (an anesthesiology risk assessment)
greater than or equal to 3. The combined rate is then the weighted average of these two rates, weighted
by the statewide proportion of patients in each cohort. Total knee arthroplasty uses the same risk
factors, but separates them into three levels: patients with none of the risk factors, patients with one
risk factor, and patients with two or three risk factors.
The Hospital-Acquired Infection (HAI) measures adjust for differences in the characteristics of
patients at a hospital, such as the type of patient care location, procedure, number of patients admitted
with MRSA or C. difficile infections, laboratory methods, hospital affiliation with a medical school,
and bed size of the patient care location. The measures compare the actual number of HAIs in a facility
or state to a national benchmark based on previous years of reported data and adjusts the data based on
several factors.6 A standardized infection ratio (SIR) is calculated as predicted infections to actual
– Vaginal Delivery without Instrument) are not risk adjusted in AHRQ methods because important risk factors are not
available in health care claims data.
3
See Claims-based measures under Hospitals-Inpatient on http://www.qualitynet.org/ for detailed information on the 30day mortality and readmission measures; see http://www.qualityindicators.ahrq.gov/Default.aspx for basic information on
the AHRQ QIs, and http://www.qualityindicators.ahrq.gov/Resources/default.aspx for links to more detailed information on
risk adjustment. MDH used AHRQ software version 4.1 to compute the measures.
4
In the AHRQ measures approach, the effect of each risk factor has been estimated on a national reference population and
is applied to the Minnesota hospital discharge data; in the CMS measure approach, the effect of each risk factor is estimated
on the national fee-for-service Medicare data for July 2008-June 2011.
5
See http://www.mnhospitals.org/Portals/0/Documents/data-reporting/SSI_final.pdf and
http://www.cdc.gov/nhsn/PDFs/pscManual/9pscSSIcurrent.pdf for more information.
6
See http://www.cdc.gov/nhsn/ for more information.
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infections. A SIR with a lower limit that is greater than 1.0 means that there were more HAIs in a
facility or state than were predicted, and an SIR with an upper limit that is less than 1.0 means that
there were fewer HAIs than were predicted. For purposes of display and scoring in this report, SIRs are
normalized by multiplying by the peer group rate of infection.
Table 3 in the report presents the 95 percent confidence interval associated with each hospital’s
outcome measure. These interval estimates were compared to the weighted peer group mean; where the
weight is the number of cases at each hospital. If a hospital’s lower 95 percent confidence interval was
greater than the peer group mean, or the hospital’s upper 95 percent confidence interval was below the
peer group mean, then that hospital’s rate was identified as “significantly different from the peer group
mean.” For certain AHRQ measures, it is theoretically possible for the upper limit to be greater than
100 percent. For practical reasons however, this upper limit was capped at 100 percent in Table 3. In
addition, for the two AHRQ obstetric trauma measures that were not risk adjusted (PSI 18 and PSI 19),
the AHRQ software uses the observed rate rather than the expected rate to calculate the confidence
intervals. In certain cases, where a hospital had a measure performance rate of 0.00 percent, its
standard error was 0.00, and therefore both the upper and lower confidence interval limits would equal
0.00 percent as well.7
7
For additional information, see
http://www.qualityindicators.ahrq.gov/Downloads/Resources/Publications/2011/Calculating_Confidence_Intervals_for_the
_AHRQ_QI.pdf
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Calculation of Hospital Total Care Costs
Data Sources
In the reports, “costs” refer to the total payments received by hospitals from both insurers and patients
for an inpatient stay. The source of the cost data for calculation of hospital costs is Minnesota’s
all‐payer claims database (APCD). The APCD contains claims data submitted by health plans,
third‐party administrators, county‐based purchasers, Prescription Drug Benefit Managers, the
Minnesota Department of Human Services (DHS),8 as well as Medicare fee-for-service data submitted
by MDH.9 Care provided to uninsured patients, patients who self-pay, Medicare supplemental claims,
or patients not enrolled with a data submitter as a Minnesota resident are not captured in the APCD
(some submitters include non-Minnesota residents in error, whose records are then excluded).
This report includes acute care hospital claims data from fiscal year 2011 dates of service (October 1,
2010 to September 30, 2011) for commercial and Medicaid or state enrollees, and fiscal year 2010
dates of service (October 1, 2009 to September 30, 2010) for Medicare beneficiaries.10 Future analyses
will benefit from a substantially shortened time lag between data submission and reporting, particularly
as it pertains to Medicare fee-for-service beneficiaries. Copays and deductibles owed by insured
patients were included in costs. Claims at the same facility for the same patient, with dates of service
that fell within 48 hours of a claims-documented discharge, were aggregated and considered a single
hospital stay.
Data Exclusions
Prior to standardization, data exclusions were applied to avoid over-counting discharges and to
enhance the comparability of the data. These included the following characteristics of any discharge:
(1) Medicare, Medicaid or commercial claims with total payment equal to the Medicare Part A
deductible for 2009 ($1,068), 2010 ($1,100), or 2011 ($1,132);
(2) discharges resulting in less than $300 per day in payment11;
(3) discharges associated with Medicare Cost Plans;
(4) discharges without a valid all-patient refined diagnosis-related grouping (APR-DRG) or major
diagnostic category (MDC)12;
8
DHS submits fee-for-service state public health care program data (e.g., Medicaid)
9
MDH submits fee-for-service Medicare data under data use agreements with the Centers for Medicare and Medicaid
Services (CMS).
10
Due to incomplete neonate submissions by Minnesota Health Care Claims Reporting System (MHCCRS) participants,
greater discrepancies with your internal data may result.
11
Payments this low likely reflect a partial payment.
12
MDCs and APR-DRGs were calculated by MDH’s data aggregator Onpoint Health Data using 3M TM APR-DRG
Software, developed by 3M Health Information Systems. For federal fiscal year 2010: APR-DRG grouper version 0727
was used and for federal fiscal year 2011: APR-DRG grouper version 0728 was used. Averill, RF, et al. 2003. All Patient
Refined Diagnosis Related Groups (APR-DRGs), Methodology Overview (3M Health Information Systems) available at
http://www.hcup-us.ahrq.gov/db/nation/nis/APR-DRGsV20MethodologyOverviewandBibliography.pdf
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(5) discharges for patients classified as Qualified Medicare Beneficiaries (QMB), a Medicaid
beneficiary category in which Medicaid pays the beneficiary’s Medicare Part A and B
premium;
(6) certain rare high-cost cases as described in the section below;
(7) discharges with seemingly inaccurate lengths of stay (less than 0 or more than 730 days);
(8) discharges with extremely high or low ratios of total costs to standardized costs.13
Fifteen percent of the discharges representing three percent of payments were dropped for one of these
reasons. The top four reasons were payment exactly equal to the annual Medicare deductible, daily
payment for the discharge less than $300, discharge paid for by a Medicare cost plans, and discharge
without a valid APR-DRG or MDC.
For PPS hospital discharges, we excluded certain rare high-cost discharges (including certain organ
transplants and burns), because only a few hospitals statewide have the capacity to treat these
conditions. Also, costs for these discharges are difficult to predict accurately. Therefore, all discharges
from 7 APR-DRGs, discharges with severity levels of 3 or 4 from 6 APR-DRGs, and discharges with
severity level of 4 from 3 APR-DRGs were excluded (see below):
13
These extreme ratios are generally the result of two factors (1) partial payments, or (2) erroneous lengths of stay on the
submitted claim.
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Attribution of Readmissions
In most cases, the costs measured in this report were based on payments made for a single stay for a
specific medical condition and/or procedure. As previously noted, in some cases a patient’s claims
based on dates of service at the same hospital within a 48-hour period were aggregated to a single stay.
In such instances, all associated costs, procedures, and diagnoses were aggregated to that single stay.
For any number of reasons, patients might also be readmitted to the same or another hospital soon after
discharge from the index hospitalization. In this analysis, special attribution rules were applied to
readmission following discharge for any one of the following conditions: heart attack or AMI,
congestive heart failure (CHF), pneumonia, or total knee replacement (TKR). If a patient was admitted
for one of these four conditions and then was readmitted to any hospital for any reason within 30 days
of the original discharge, the costs associated with the first such readmission were attributed to the
hospital where the index admission took place and added to the costs of the index admission. Note that
we only combined the costs of the first readmission to those of the index admission; we did not
attribute subsequent readmissions even if they occurred within the 30-day window.
For these special cases of readmissions following an AMI, CHF, pneumonia or TKR discharge, the
attribution of hospitalizations to hospitals consisted of three key steps: (1) identifying the index
admission (2) identifying the first readmission for any cause within 30 days of discharge from an index
admission, and (3) combining the costs of the first readmission with costs of the index admission to
create a single admission episode that was attributed to the hospital where the index admission
occurred.
Admissions for AMI, CHF, or pneumonia were identified based on the principal diagnosis; those for
TKR were identified based on any one of eight relevant procedure codes (see Appendix Table 2).
Admissions for these diagnoses were classified as index admissions only if (1) the patient did not die,
(2) the patient was not transferred out of the hospital to another acute care hospital, and (3) the
admission was not preceded within 30 days by an index admission. A patient with an AMI who was
discharged on the same day as admission was not classified as an index admission, because these
same-day discharges were unlikely to be true AMIs. The period for identifying AMI, CHF, pneumonia,
and TKR index admissions was restricted to the same twelve months of the measurement periods
previously noted. Costs for readmissions as defined herein that occurred up to 30 days beyond the
measurement period were included in the total care cost measure, because such readmissions could be
attributed to index stays within the measurement period.
Removal of Add-on Payments
Medicare Disproportionate Share (DSH) and Indirect Medical Education (IME) payments as well as
Medicaid add-on payments were removed from hospital payments. These add-on payments are
intended to compensate hospitals for pursuing social goals (for example, medical education and
treatment of disadvantaged and uninsured populations) not directly related to the care of the specific
patient on whose claim the add-on payment is attached.
Medicare DSH and IME
DSH and IME payments on Medicare fee-for-service inpatient claims are typically percentage
increases to what the hospital would otherwise have been reimbursed for the stay. The percentages are
based on formulas updated annually by CMS. The percentage add-on amounts for Medicare DSH and
IME are published annually. We used this information to calculate the percentage add-on each PPS
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hospital would receive for care provided to Medicare patients.14 This allowed us to exclude the portion
of the allowed amount (total payment) that was attributable to DSH and IME add-on payments. Some
hospitals received no add-on payments, while others may have received substantial increases to their
reimbursements. DSH and IME payments were also excluded from Medicare Advantage claim
payment amounts. Although there is no explicit federal payment of DSH and IME to hospitals that
treat Medicare Advantage patients, the calculation of capitation amounts for Medicare Advantage
plans and other federal rules have the effect of creating hospital payments closely matching Medicare
fee-for-service rates and implicitly paying DSH and IME add-on amounts for the treatment of these
patients.
Medicaid Add-On Payments
Medicaid add-on payments, which also aim to compensate hospitals for treating disadvantaged
populations, were similarly removed from reimbursements before calculating cost measures. Like
Medicare add-on payments, Medicaid add-ons are paid as a percentage increase to the reimbursement
for the treatment of Medicaid FFS patients. The percentage add-on amount is the result of a complex
formula that includes adjustments for the following:

Disproportionate Population Adjustment (DPA) payments are federal funds that are
distributed to the state of Minnesota to (like Medicare‘s DSH) compensate hospitals for the
treatment of Medical Assistance patients. Eligibility for DPA payments and the size of the addon payment are determined by the state, using a complex formula. DPA add-on payments can
vary by type of hospital stay, type of patient Medicaid eligibility, hospital size and location, and
other factors.

The Small Rural Hospital Adjustment applies to small rural hospitals and is related to the
timing of the hospital stay, the number of beds, and the location of the hospital in a rural
setting.

The Greater Minnesota Payment Adjustment applies to Minnesota hospitals located outside
the seven-county metropolitan area. These hospitals are eligible to qualify for a payment
increase at 90 percent of the seven-county metropolitan average for a set of 16 DRGs related to
cesarean sections, newborn delivery, neonatal issues, psychoses, childhood mental disorders,
and appendectomies.

Finally, the Payment Rate for Certain Births is an add-on payment related to vaginal birth
and cesarean section deliveries with complications.
To remove these payments, we received data that detailed claim-specific add-on amounts from the
Department of Human Services, which were then linked to APCD Medicaid fee-for-service claims by
MDH, allowing us to subtract these amounts from the final FFS payments. These add-on payments are
not paid for the hospital care of patients in Medicaid managed care plans and there are no
corresponding state rules similar to federal rules that would warrant removing these amounts from
managed care claims. For more detail regarding these Medicaid add-on payments, refer to the
following link on the DHS website:
http://www.dhs.state.mn.us/main/idcplg?IdcService=GET_DYNAMIC_CONVERSION&dDocName=
14
Separate rates are applied to the capital and operating portions of Medicare reimbursements. We calculated weighted
DSH and IME rates.
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dhs16_146905&RevisionSelectionMethod=LatestReleased
Outlier Adjustment
We performed hospital cost outlier adjustment by top-coding or truncating payments; payments that
were higher than certain thresholds described below were reset to equal the value at the threshold. The
objective of truncation is to reduce the influence of anomalous payments that cannot be predicted from
case mix, while making profiles accurately reflect hospital payments. Truncation was performed on
payments after add-on amounts were removed. Standardized costs were truncated by truncating the
length of stay (LOS)-adjusted DRG weights that are multiplied by base payments to form standardized
costs. Truncation thresholds were chosen to obtain high predictability, as measured by R-squared from
discharge-level and hospital-level regressions, and included a high proportion of hospitals’ payments
in the analysis, as measured by the ratio of the sum of payments after truncation to the sum of
untruncated payments.
For each pair of hospital type (PPS hospitals and CAHs) and payer type (Medicare, Medicaid, and
commercial payers), we selected truncation thresholds based on the variation of payments within
groups of discharges defined by their APR-DRG and SOI. The truncation point was set at a level 2.5
standard deviations above the mean payment within each of these discharge groups. In addition to
payments, LOS-adjusted DRG weights were truncated using the same approach. The following steps
describe the process in detail:
1. Global truncation. First, payments and standardized costs were truncated at the 99.98th
percentile within each pair of hospital type and payer type. Length of stay was truncated at
a level such that LOS times APR-DRG weight per day is equal to its 99.98th percentile.
This LOS truncation results in truncation of LOS adjusted DRG weight and standardized
cost at the 99.98th percentile and ensures that LOS and standardized cost are consistent in
subsequent steps.
2. Constructing cells defined by APR-DRGs for truncation. For each pair of hospital type
and payer type, the following steps were taken to construct cells defined by APR-DRGs for
truncation:
2.1 First, APR-DRG-SOI cells containing at least 50 discharges were identified.
2.2 If an APR-DRG-SOI cell had fewer than 50 discharges, it was combined with one or
more APR-DRGs with a similar DRG weight per day within the same SOI and MDC.
2.3 If the criteria in Step 2.2 were not met and some discharges remained ungrouped, all
APR-DRGs within the same SOI and MDC were combined.
2.4 If the criteria in Step 2.3 were not met and some discharges remained ungrouped, all
APR-DRGs with the same SOI were combined.
3. Truncation within APR-DRG cells. Payments and LOS-adjusted DRG weights were
truncated at 2.5 SDs above the mean within the cells established in Step 2. An LOSadjusted DRG weight was truncated by truncating the LOS at the level where LOS-adjusted
DRG weight was equal to the mean plus 2.5 SD for that cell.
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Cost Standardization
We examine and report case mix adjusted payments and standardized costs in the Hospital Total Care
Reports. The payments for each stay include total payments made to hospitals for inpatient care by the
patient, government insurer(s), and private insurer(s). These payments reflect both the volume and
intensity of resource use as well as prices. Standardized costs associated with each stay reflect the
expected resource use for treating the patient, but not hospital to hospital variations in prices. Prices,
for instance, may vary because hospitals negotiate different rates across insurers and different rates for
different types of hospitalizations. As a result, within a detailed payer type category, standardized costs
reflect the type and intensity of care (quantity) delivered during the stay, independent of price.
Systematic differences in prices across payer class were accounted for during case mix adjustment,
described below. Standardized costs are based on national APR-DRG weights that are re-centered
with Minnesota hospital claims data. APR-DRG weights were adjusted for each stay’s LOS to better
capture resource use and adjust for variations in patient severity. Comparing a hospital’s actual and
standardized costs allows report users to determine whether the hospital’s prices were higher or lower
than a peer group average, given its patient mix.
To calculate standardized costs, we used weights associated with each APR-DRG and severity-ofillness (SOI) category. The APR-DRG weights are a measure of expected resource use for a stay, given
the reason for the stay (the APR-DRG category) and the frailty or relative health of the patient
compared with other patients receiving the same service. Within each DRG, there are four SOI
categories. These DRG-SOI weights were developed by 3M (developer of the APR-DRG) and are
based on national data. The use of weights allowed us to analyze whether the differences in average
payment per stay between hospitals were driven by the complexity of their cases or by the differences
in their prices.
The weights were re-centered to 1.0 using data from the APCD. This process involves dividing all
DRG national weights by the mean weight within the APCD dataset, such that the mean Minnesota
hospital stay had a weight of 1.0. Re-centering weights does not change the standardized costs
assigned to a stay, but does make comparisons of patient mix between hospitals more intuitive.
Because of considerable variation in lengths of stay observed within hospital stays assigned to APRDRG-SOI categories, APR-DRG-SOI weights were adjusted by each stay’s length. 3M also provides a
national average length of stay (ALOS) for each APR-DRG-SOI. Adjusted weights were constructed
as the average national weight per day times the observed length of stay (LOS):
where d refers to the specific APR-DRG-SOI and i refers to the specific hospital stay in question.
In addition to the APR-DRG weights, calculation of standardized costs requires that a base payment
rate for each payer type be estimated using observed payment rates in the APCD. Five base payment
rates were calculated for each payer type (Medicare FFS, Medicare Advantage, Medicaid FFS,
Medicaid managed care, and commercial payers). Each base payment rate was calculated by taking the
sum of the allowed amounts (that is, total payments) on all stays paid by a payer type (across all APRDRG and SOI categories) and dividing it by the sum of the adjusted weights for those stays. Therefore,
the base payment rate can be interpreted as what the payer type pays on average for a stay with an
B-14
APR-DRG-SOI weight of 1.0. The base payment rate specific to the payer type for the stay was then
multiplied by the stay’s LOS-adjusted weight to arrive at the standardized cost for hospital stay.
Case-Mix (Risk) & Payer-Mix Adjustment
Truncated payments and standardized costs were case-mix adjusted using indirect standardization,
based on linear regression models of cost. Clinical risk factors were identified using the APR-DRG
grouper, which assigns hospital stays to clinically related groups using diagnosis information contained
on the claim for each stay.15 The grouper also classifies each stay in one of four SOI categories. In
addition to APR-DRG and SOI, regression models included the additional risk factors of patient age
and sex. Specification of age differed by hospital type and payer type.16 In addition, in Medicaid
models, all variables were interacted with an indicator of whether the payer was managed care. We
estimated 12 separate regression models for payments and standardized costs, two types of hospital
peer groups (PPS hospitals and CAHs), and discharges covered by three types of payers—(1) Medicare
(including Medicare Advantage), (2) Medicaid (including Medicaid managed care), and (3)
commercial payers. Expected payments (or standardized costs) were calculated for each discharge
using the regression estimate that applied to that discharge’s hospital and payer type. Case-mix
adjusted payments for a hospital for a given payer type were calculated as:
Casemix adjusted payments = mean payment *
 observed payments
 expected payments
where the mean payment is calculated over all discharges covered by that payer type, and observed and
expected payments are summed over all discharges covered by that payer type at the hospital. Payermix adjusted payments for a hospital are calculated similarly with the mean payment, and observed
and expected payments being calculated across all payer types instead of a particular payer type. Casemix adjusted standardized costs were calculated similarly.
We evaluated alternative specifications of the risk adjustment model based on the APR-DRG grouper
using criteria such as goodness-of-fit and predictive ratios for high and low cost discharges and
diagnostic cohorts. We selected models based on national DRG weights over models based on APRDRG categories because of their parsimony and superior fit for the majority of models estimated.
Payer-specific case mix-adjusted costs were calculated by constructing a ratio of the sum of the
observed costs to the sum of the expected costs. The expected cost of each discharge was the predicted
value from the regression model. This ratio was multiplied by the peer group specific/payer type
specific average cost of discharges. This approach produces a risk-adjusted value that represents the
cost of treating the average patient for that payer type within a peer group, controlling for differences
15
When a hospital stay is assigned the costs of a readmission (see Attribution of Readmissions), the clinical risk factors for
the stay are limited to the diagnoses observed for the index stay and do not include the diagnoses observed for the
readmission or those in the patient’s clinical history.
16
For PPS hospitals, age categories were interacted with DRG weight, while for CAHs, fixed effects were estimated for
each age category. Specification of age also differed by payer type. For instance, Medicare models excluded the lower age
ranges but separate categories were established for 10 year increments up to age 94 and a single category was used for ages
95 and up. For commercial models, ages 65 and up were included as a single category, while for CAH Medicaid models,
ages 85 and up were included as a single category.
B-15
in patient risk.
Total risk-adjusted costs were calculated similarly, except that the hospital’s ratio of observed-toexpected costs included the discharges of all payer types in the peer group. This ratio was multiplied
by the peer group’s overall mean cost per stay. This adjusted value represents the cost of treating the
average patient based on each hospital’s actual payer mix.
Reliability
Reliability is the consistency with which cost comparisons of hospitals can be measured. Reliability
depends on the number of discharges attributed to a hospital and the intraclass correlation (ICC) for
hospital costs. The larger the number of discharges at each hospital and the higher the ICC, the more
reliably an analysis can distinguish actual differences in performance between hospitals.
Because a higher reliability level would result in excluding more hospitals from receiving a report, we
sought to balance the desire for high reliability in public reporting with consideration of the number of
hospitals that would be included in peer group and eligible to receive a report. Based on an impact
analysis of four reliability levels on report inclusion, and subsequent input from the Reliability
Workgroup, we decided to 1) include a PPS hospital or CAH in provider peer grouping only if it met
the minimum number of discharges to satisfy a reliability standard in one payer type of 0.8, and 2)
report that hospital’s costs by service category (MDCs or aggregate MDCs) if the number of
discharges in that category meet a reliability standard of 0.4.
Categories of Health Care Services (and Aggregations)
Cost-of-service categories were represented by major diagnostic categories (MDCs) or aggregated
MDCs which were further specified into one of three clinical areas—Medical, Surgical, and Newborn.
We used individual MDCs or aggregated MDCs to report cost breakdowns, because MDCs are the
only summary-level clinical service categories consistently available in claims data for all three payer
types (Medicare, Medicaid, and commercial). MDCs are formed by classifying all possible principal
diagnoses (from ICD-9-CM) into 25 mutually exclusive diagnosis areas. The diagnoses in each MDC
correspond to a single organ system or etiology, and, in general, are associated with a particular
medical specialty. MDCs can be viewed as a roll-up of the APR-DRGs, which can be assigned to most,
but not all, hospital claims.
In the inpatient claims for this analysis, there were some ungroupable cases that had no assigned
MDCs and DRGs, because the principal diagnosis was invalid or missing for these claims. These
ungroupable cases were excluded from final cost analysis, consistent with the data exclusions process
described earlier.
As noted previously (see “Reliability”), Total Care Costs are reported only for those hospitals with the
minimum number of discharges required to achieve the global reliability standard of 0.8 for at least
one payer type.
However, additional reliability standards and discharge thresholds were applied when reporting costs
by diagnostic category and/or payer type:

To report costs at the MDC level for any hospital, at least ten hospitals in a peer group (either
PPS hospitals or CAHs) had to have a sufficient number of discharges to achieve a moderate
B-16
reliability standard of 0.4 for that MDC. MDCs with fewer than ten hospitals meeting this
threshold were rolled up to an “other” category, for the purposes of reporting.

Within each hospital’s report, the symbol † is used to flag numbers of discharges in a particular
diagnostic and/or payer type category too small to meet the 0.4 reliability threshold. This
applies to breakdowns by payer type or aggregate diagnostic categories (Medical/Surgical
/Newborn) shown in Table 5; to MDC-level breakdowns for all payers shown in Table 6; and to
aggregate diagnostic categories by payer type shown in Table 7. However, total numbers of
discharges and costs and utilization data in these categories are still reported.

To comply with CMS’s data release guidelines for Medicare-covered discharges, the number of
discharges can only be reported if there were at least 11 discharges of that type at the facility.
For hospitals with fewer than 11 discharges in any displayed category, the number of
discharges is not shown in the report itself and is denoted by the symbol #. However, total costs
and utilization data in these categories are reported. For patient confidentiality reasons
consistent with those required by CMS, we applied this rule to discharges covered by any payer
type. Additionally, when the number of discharges is suppressed in only a single category, it
may still be possible to determine the suppressed number by using counts, row, or column
totals in other categories. To avoid this possibility, we suppressed the number of discharges in
the category that had the next highest number of discharges, even though it would be greater
than or equal to 11. In this case the number of discharges is replaced with the symbol ##.
Benchmarking
To facilitate peer group comparisons across hospitals, we report a number of cost statistics. The
benchmark statistics are weighted means calculated across a hospital’s peer group. Using this design,
each PPS hospital is compared to the benchmark based on all PPS hospitals and each CAH is
compared to the benchmark based on all CAHs.
In the summary cost tables included in each hospital’s report, the following benchmark statistics are
included:

Risk-adjusted total costs per discharge, calculated as the weighted mean of risk-adjusted total
costs per discharge across all hospitals in the peer group, with weights equal to the number of
discharges at each hospital. Means were calculated by payer type and across all payer types for
all discharges and for categories of discharges.

Case mix-adjusted standardized costs per discharge, calculated similarly to total costs, as a
weighted average across all hospitals in the peer group, but using standardized costs per
discharge instead of actual costs. Case mix-adjusted standardized costs for each payer type
(based on the length of stay and statewide average daily payment for clinically similar hospital
stays) adjusts for differences in hospitals’ payments due to contractual agreements with thirdparty payers and other factors, and permits comparisons of resource use among hospitals with
different rates of reimbursement.

Ratio of case mix-adjusted total costs to case mix-adjusted standardized costs per discharge,
calculated as the ratio of the benchmark total costs per discharge to the benchmark standardized
costs per discharge. This ratio gives a baseline for the average price, in terms of payments per
resource unit, for a particular category of discharges when resources are measured using prices
B-17
standardized for patient and payer mix. It indicates, across all hospitals in the peer group,
whether the price per resource unit measured for that category of discharges is greater (if
greater than 1.0), the same (if equal to 1.0) or less (if less than 1.0) than the average price
across all discharges.
Additionally, for each hospital, we report the 95 percent confidence interval for total costs per
discharge. The confidence interval is compared with the benchmark mean weighted by the number of
discharges at each hospital, to determine whether the hospital’s costs were significantly different; that
is, whether the benchmark falls outside the hospital’s confidence interval around its total cost per
discharge. The confidence interval is calculated assuming a T-distribution, for which the standard error
is estimated as the standard deviation of residuals from the risk adjustment regression for all
observations in the benchmark mean, divided by the square root of the number of discharges at a
hospital. While it is theoretically possible for the lower value of the confidence interval to be negative,
for practical reasons this lower limit has been truncated to zero so negative values are not displayed in
Table 5 of this report17.
In the detailed cost tables for each hospital, we also present a set of benchmark statistics for each
hospital, calculated separately for each MDC (Table 6) and the three clinical areas (Medical, Surgical,
and Newborn) by payer type (Table 7), and across all hospitals in that hospital’s peer group. The
following benchmark statistics are included in the detailed cost tables:

Average length of stay in days, calculated by payer type, as the weighted mean of length of stay
across hospitals in the peer group and for a specific MDC/aggregated MDC, with weights equal
to the number of discharges at each hospital.

Case- and payer-mix adjusted total costs per discharge, calculated as the weighted average of
risk-adjusted total costs for that MDC or group of MDCs across hospitals in the peer group,
weighted by the number of observations per hospital (this is consistent with the metric of the
same name in Table 5).

Standardized costs per discharge for that MDC or clinical area, calculated as the weighted
average across all hospitals in the peer group, but using standardized costs per discharge
instead of total costs (this is consistent with the metric of the same name in Table 5).

Ratio of total costs to standardized costs per discharge, calculated as the ratio of the benchmark
total costs per discharge to the benchmark standardized costs per discharge.

Percentage of hospital total costs calculated as the share of total payments to hospitals from a
particular payer type that was accounted for by discharges under a given MDC or clinical area,
across all hospitals in the peer group.
Unlike the summary cost tables, the detailed tables do not include 95 percent confidence intervals for
the hospital-specific total costs per discharge; any statistically significant difference between a
hospital’s per discharge costs and the benchmark estimate is identified with an asterisk.
17
For more on t-tests, see McDonald, J.H. 2009. Handbook of Biological Statistics (2nd ed.). Sparky House Publishing,
Baltimore, Maryland.
B-18
Final Cost Analysis
The final cost analysis for production of the Hospital Total Care cost reports incorporates the
various analyses, adjustments, and decisions described throughout this document. Costs include
hospital payments from third-party payers, and patient responsibility (i.e., deductibles, coinsurance, and co-payments) from federal FY 2011 for commercially insured beneficiaries and
state program recipients and federal FY 2010 for Medicare beneficiaries.18 Further, as previously
described, the analysis is based on costs of admissions that occurred at each hospital, as well as
costs of certain readmissions attributed to the hospital following discharge for specific conditions
or procedures, with various adjustments—price standardization, outlier adjustment, exclusion of
costs from rare and high cost cases, application of reliability standards, removal of add-on
payments such as IME from all Medicare claims and DPA from fee-for-service Medicaid, as well
as adjustment for case-mix (risk) adjustment and payer-mix by indirect standardization. The final
hospital total care cost analysis is performed for 48 PPS hospitals and 48 CAHs that meet the
criteria to receive hospital cost and quality reports.19
18
As described previously, costs also include payments for certain readmissions occurring up to 30 days after the end of the
measurement period for these beneficiaries.
19
Hospitals that do not meet the criteria for inclusion in the reporting system will still receive summarized data tables for
internal review.
B-19
Measure
Process of Care
AMI-2
Heart attack patients given aspirin at
discharge
AMI-8a
Heart attack patients given PCI w/in 90 min
of arrival
AMI-10
Heart attack patients given a statin Rx at
discharge
OP4
Outpatients with chest pain or possible
heart attack who got aspirin within 24 hours
of arrival
HF-1
Heart failure patients given discharge
instructions
HF-2
Heart failure patients given an evaluation of
left ventricular systolic function
HF-3
Heart failure patients given ACE inhibitor or
ARB for left ventricular systolic dysfunction
PN-3b
Pneumonia patients whose initial ER blood
culture was performed prior to the
administration of the first hospital dose of
antibiotics
PN-6
Pneumonia patients given the most
appropriate initial antibiotic(s)
SCIP-Inf- Surgery patients who received prophylactic
1a
antibiotic 1 hour prior to incision
SCIP-Inf- Surgery patients with appropriate
2a
prophylactic antibiotic selected
SCIP-Inf- Surgery patients with prophylactic
3a
antibiotics discontinued within 24 hours
after surgery
SCIP-Inf- Cardiac surgery patients with controlled
4
post-operative blood glucose
SCIP-Inf- Surgery patients whose urinary catheters
9
were removed on the first or second day
after surgery
SCIP-Inf- Surgery patients who were actively
10
warmed in the operating room or whose
body temperature was near normal
SCIPSurgery patients who received appropriate
VTE-2
VTE prophylaxis within 24 hours prior and
24 hours after surgery
SCIPSurgery patients who were taking beta
Card-2
blockers who were kept on them
VAP
Ventilator associated pneumonia bundle
compliance for ICU patients
CLI
Central line bundle compliance for ICU
patients
IMM2
Immunization rate for influenza
Steward/
Source
CMS/CMS
Data
Collection Risk
Period
Adjusted?
Minimum
Cases
Included
for CAHs?
07/201106/2012
07/201106/2012
07/201106/2012
07/201106/2012
No
10
No
No
10
No
No
10
No
No
10
Yes
10/201109/2012
10/201109/2012
10/201109/2012
10/201109/2012
No
10
Yes
No
10
Yes
No
10
No
No
10
Yes
10/201109/2012
07/201106/2012
07/201106/2012
07/201106/2012
No
10
Yes
No
10
Yes
No
10
Yes
No
10
Yes
07/201106/2012
07/201106/2012
No
10
No
No
10
Yes
CMS/CMS
07/201106/2012
No
10
Yes
CMS/CMS
07/201106/2012
No
10
Yes
CMS/CMS
07/201106/2012
10/201009/2011
10/201009/2011
10/201203/2013
No
10
Yes
No
10
Yes
No
10
Yes
No
10
Yes
CMS/CMS
CMS/CMS
CMS/CMS
CMS/CMS
CMS/CMS
CMS/CMS
CMS/CMS
CMS/CMS
CMS/CMS
CMS/CMS
CMS/CMS
CMS/CMS
CMS/CMS
IHI*/MHA
IHI/MHA
CMS/CMS
B-20
Data
Steward/
Collection Risk
Measure
Source
Period
Adjusted?
Outcomes of Care: Inpatient Complications and Infections
PSI 3
Decubitus Ulcer (pressure ulcer)
AHRQ/AHRQ 01/2011- Yes
12/2011
PSI 4
Death among surgical inpatients with
AHRQ/AHRQ 01/2011- Yes
serious treatable complications
12/2011
PSI 6
Iatrogenic pneumothorax
AHRQ/AHRQ 01/2011- Yes
12/2011
PSI 11
Post op respiratory failure
AHRQ/AHRQ 01/2011- Yes
12/2011
PSI 12
Postoperative pulmonary embolism or deep AHRQ/AHRQ 01/2011- Yes
vein thrombosis
12/2011
PSI 15
Accidental puncture or laceration
AHRQ/AHRQ 01/2011- Yes
12/2011
PSI 18
Obstetric trauma – vaginal delivery with
AHRQ/AHRQ 01/2011- No
instrument
12/2011
PSI 19
Obstetric trauma – vaginal delivery without AHRQ/AHRQ 01/2011- No
instrument
12/2011
SSI:Vag- HAI: SSI rate for vaginal hysterectomy
CDC/MHA
10/2010- Yes
Hyst
09/2011
SSI:TKA HAI: SSI rate for total knee arthroplasty
CDC/MHA
10/2009- Yes
09/2010
HAI-1
HAI: Central line-associated blood stream
CDC/CMS
10/2011- Yes
infection (CLABSI)
09/2012
HAI-2
HAI: Catheter-associated urinary tract
CDC/CMS
10/2011- Yes
infection (CAUTI)
09/2012
HAI-3
HAI: SSI from abdominal hysterectomy
CDC/CMS
10/2011- Yes
09/2012
HAI-4
HAI: SSI from colon surgery
CDC/CMS
10/2011- Yes
09/2012
Outcomes of Care: Mortality
MORT- 30-day mortality after hospital admission for CMS/CMS
07/2009- No
30-AMI heart attack
06/2012
MORT- 30-day mortality after hospital admission for CMS/CMS
07/2009- Yes
30-HF
heart failure
06/2012
MORT- 30-day mortality after hospital admission for CMS/CMS
07/2009- Yes
30-PN
pneumonia
06/2012
IQI 11
Abdominal aortic aneurism (AAA) repair
AHRQ/AHRQ 01/2011- Yes
inpatient mortality rate
12/2011
IQI 12
Coronary artery bypass graft (CABG)
AHRQ/AHRQ 01/2011- Yes
inpatient mortality rate
12/2011
IQI 17
Acute stroke inpatient mortality rate
AHRQ/AHRQ 01/2011- Yes
12/2011
IQI 19
Hip fracture inpatient mortality rate
AHRQ/AHRQ 01/2011- Yes
12/2011
IQI 30
Percutaneous transluminal coronary
AHRQ/AHRQ 01/2011- Yes
angioplasty (PTCA) inpatient mortality rate
12/2011
Outcomes of Care: Readmissions
READM- 30-day readmission rate following hospital CMS/CMS
07/2008- Yes
30-AMI discharge for heart attack
06/2011
READM- 30-day readmission rate following hospital CMS/CMS
07/2008- Yes
30-HF
discharge for heart failure
06/2011
READM- 30-day readmission rate following hospital CMS/CMS
07/2008- Yes
30-PN
discharge for pneumonia
06/2011
B-21
Minimum
Cases
Included
for CAHs?
25
Yes
25
No
25
Yes
25
Yes
25
Yes
25
Yes
25
Yes
25
Yes
25
No
25
Yes
25
No
25
No
25
No
25
No
25
No
25
Yes
25
Yes
25
No
25
No
25
No
25
Yes
25
No
25
No
25
Yes
25
Yes
Steward/
Source
Measure
Patient Experience (CAHPS)
Nurses “always” communicated well
AHRQ/CMS
Doctors “always” communicated well
AHRQ/CMS
Patients “always” received help as soon as AHRQ/CMS
they wanted
Patients’ pain was “always” well controlled AHRQ/CMS
Staff always explained about medicine
before giving it to patients
Patients given information about what to do
during recovery at home
Area around patients’ room was always
quiet at night
Patients’ room and bathroom were always
clean
Patients would definitely recommend the
hospital
Patients gave hospital rating of 9 or 10 on
scale of 0 to 10
AHRQ/CMS
AHRQ/CMS
AHRQ/CMS
AHRQ/CMS
AHRQ/CMS
AHRQ/CMS
*IHI = Institute for Healthcare Improvement
B-22
Data
Collection Risk
Period
Adjusted?
10/2011 –
09/2012
10/2011 –
09/2012
10/2011 –
09/2012
10/2011 –
09/2012
10/2011 –
09/2012
10/2011 –
09/2012
10/2011 –
09/2012
10/2011 –
09/2012
10/2011 –
09/2012
10/2011 –
09/2012
Minimum
Cases
Included
for CAHs?
No
300
No
No
300
No
No
300
No
No
300
No
No
300
No
No
300
No
No
300
No
No
300
No
No
300
No
No
300
No
ICD-9-CM
Description
AMI Codes
410.00
AMI (anterolateral wall) – episode of care unspecified
410.01
AMI (anterolateral wall) – initial episode of care
410.10
AMI (other anterior wall) – episode of care unspecified
410.11
AMI (other anterior wall) – initial episode of care
410.20
AMI (inferolateral wall) – episode of care unspecified
410.21
AMI (inferolateral wall) – initial episode of care
410.30
AMI (inferoposterior wall) – episode of care unspecified
410.31
AMI (inferoposterior wall) – initial episode of care
410.40
AMI (other inferior wall) – episode of care unspecified
410.41
AMI (other inferior wall) – initial episode of care
410.50
AMI (other lateral wall) – episode of care unspecified
410.51
AMI (other lateral wall) – initial episode of care
410.60
AMI (true posterior wall) – episode of care unspecified
410.61
AMI (true posterior wall) – initial episode of care
410.70
AMI (subendocardial) – episode of care unspecified
410.71
AMI (subendocardial) – initial episode of care
410.80
AMI (other specified site) – episode of care unspecified
410.81
AMI (other specified site) – initial episode of care
410.90
AMI (unspecified site) – episode of care unspecified
410.91
AMI (unspecified site) – initial episode of care
CHF Codes
402.01
Malignant hypertensive heart disease with congestive heart failure (CHF)
402.11
Benign hypertensive heart disease with CHF
402.91
Hypertensive heart disease with CHF
404.01
Malignant hypertensive heart and renal disease with CHF
404.03
Malignant hypertensive heart and renal disease with CHF & renal failure (RF)
404.11
Benign hypertensive heart and renal disease with CHF
404.13
Benign hypertensive heart and renal disease with CHF & RF
404.91
Unspecified hypertensive heart and renal disease with CHF
404.93
Hypertension and non-specified heart and renal disease with CHF & RF
428.xx
Heart failure codes
Pneumonia Codes
480.0
Pneumonia due to adenovirus
480.1
Pneumonia due to respiratory syncytial virus
480.2
Pneumonia due to parainfluenza virus
480.3
Pneumonia due to SARS-associated coronavirus
480.8
Viral pneumonia: pneumonia due to other virus not elsewhere classified
480.9
Viral pneumonia unspecified
481
Pneumococcal pneumonia [streptococcus pneumoniae pneumonia]
482.0
Pneumonia due to klebsiella pneumoniae
482.1
Pneumonia due to pseudomonas
482.2
Pneumonia due to hemophilus influenzae (h. influenzae)
482.30
Pneumonia due to streptococcus unspecified
482.31
Pneumonia due to streptococcus group a
482.32
Pneumonia due to streptococcus group b
482.39
Pneumonia due to other streptococcus
482.40
Pneumonia due to staphylococcus unspecified
482.41
Pneumonia due to staphylococcus aureus
482.49
Other staphylococcus pneumonia
482.81
Pneumonia due to anaerobes
482.82
Pneumonia due to escherichia coli [e.coli]
B-23
ICD-9-CM
Description
Pneumonia Codes, continued
482.83
Pneumonia due to other gram-negative bacteria
482.84
Pneumonia due to legionnaires' disease
482.89
Pneumonia due to other specified bacteria
482.9
Bacterial pneumonia unspecified
483.0
Pneumonia due to mycoplasma pneumoniae
483.1
Pneumonia due to chlamydia
483.8
Pneumonia due to other specified organism
485
Bronchopneumonia organism unspecified
486
Pneumonia organism unspecified
487.0
Influenza with pneumonia
TKR Codes
81.54
Total Knee Replacement
81.55
Revision of Knee replacement, NOS
81.59
Revision of joint replacement of lower extremity, not elsewhere classified
00.80
Revision of knee replacement, total (all components)
Replacement of femoral, tibial, and patellar components (all components)
Excludes:
revision of only one or two components (tibial, femoral or patellar component) (00.81-00.84)
00.81
Revision of knee replacement, tibial component
Replacement of tibial baseplate and tibial insert (liner)
Excludes:
revision of knee replacement, total (all components) (00.80)
00.82
Revision of knee replacement, femoral component
That with replacement of tibial insert (liner)
Excludes:
revision of knee replacement, total (all components) (00.80)
00.83
Revision of knee replacement, patellar component
Excludes:
revision of knee replacement, total (all components) (00.80)
00.84
Revision of total knee replacement, tibial insert (liner)
B-24
Bethesda Rehabilitation Hospital
Regency Hospital of Minneapolis
Phillips Eye Institute
Anoka Metro Regional Treatment Center
Brainerd Regional Human Services Center
Mayo Psychiatry and Psychology Treatment
Willmar Regional Treatment Center
Shriners Hospitals for Children
Veterans Affairs Medical Center
Veterans Affairs Medical Center
US Public Health Service - Red Lake
US Public Health Service - Cass Lake
Community Behavioral Health Hospital – Alexandria
Community Behavioral Health Hospital – Annandale
Community Behavioral Health Hospital - Fergus Falls
Community Behavioral Health Hospital – Rochester
Community Behavioral Health Hospital - St. Peter
Community Behavioral Health Hospital – Wadena
Community Behavioral Health Hospital – Baxter
Community Behavioral Health Hospital - Cold Spring
Community Behavioral Health Hospital – Bemidji
Lakeside Medical Center
Hospitals not Receiving Reports due to not meeting standards for Quality Reporting
Children's Hospitals and Clinics, Minneapolis
Children's Hospitals and Clinics, St. Paul
Gillette Children’s Specialty Healthcare
Albany Area Hospital and Medical Center
Appleton Area Health Services
CentraCare Health System - Long Prairie
Clearwater Health Services
Cook County North Shore Hospital
Cook Hospital & C&NC
Ely-Bloomenson Community Hospital
Essentia Health Ada
Essentia Health Graceville
Essentia Health Northern Pines
Hendricks Community Hospital Association
Johnson Memorial Health Services
Kittson Memorial Healthcare Center
Lake View Memorial Hospital
LakeWood Health Center
Madelia Community Hospital
Madison Hospital
Mahnomen Health Center
Mayo Clinic Health System - St. James
Minnesota Valley Health Center
North Valley Health Center
Prairie Ridge Hospital and Health Services
RC Hospital & Clinics
Sanford Medical Center Jackson
Sanford Tracy Medical Center
Sanford Westbrook Medical Center
Sanford Wheaton Medical Center
Sibley Medical Center
B-25
Tyler Healthcare Center/Avera
Windom Area Hospital
B-26