Protecting, maintaining and improving the health of all Minnesotans Date:
June 1, 2011
To:
Provider Peer Grouping Rapid Response Team members
From:
Katie Burns, Health Economics Program
Subject:
Tools for Clinic-Level Peer Grouping
Thank you for participating in the Rapid Response Team. In preparation for our next
meeting, I wanted to distribute the attached memo. The memo describes tools we are
using to conduct the PPG physician clinic analysis at a clinic level. Specifically, it
describes a measure called the Primary Care Service Index (PCSI) and outlines how
MDH will use the PCSI and its components to facilitate a clinic level of analysis. We are
also proposing to use the PCSI to perform a service mix adjustment and are soliciting
RRT input on whether a need exists for a separate adjustment to account for variations in
service mix or whether the ACG risk adjustment tool can adequately account for this type
of variation to the extent such adjustment is warranted.
We will review the memo during our meeting to ensure you have an opportunity to
clarify your understanding of the issues and to ask questions.
Response deadline: We will need your feedback on these issues by Tuesday, June 14
at 4:00 pm. Responses may be provided via email to [email protected].
Memo
Date:
May 31, 2011
To:
Provider Peer Grouping Rapid Response Team
From:
Kevan Edwards
Katie Burns
Subject:
Tools for Peer Grouping at a Clinic Level
Introduction
Provider peer grouping (PPG) compares providers on a combined measure of risk-adjusted cost
and quality for a provider’s total patient population as well as for select specific health
conditions. Consistent with the Provider Peer Grouping Advisory Group’s recommendations,
clinics that offer primary care will be included in total care PPG while both primary care and
relevant specialty-only clinics will be included in the condition-specific analysis. Based on our
work to date, MDH intends to peer group at the clinic level, rather than at the medical group
level, in the first iteration of PPG.
The purpose of this memo is to describe several key aspects of the total care physician clinic
analysis, particularly in the context of clinic-level peer grouping. First, this memo describes our
method for linking individual providers to clinic locations and allocating their time across
multiple clinics when necessary. Second, this memo describes our method for assessing the
extent to which primary care is practiced at an individual clinic and how this information could
be used to perform a service mix adjustment. MDH is soliciting RRT input on whether a need
exists for a separate adjustment to account for variations in service mix or whether the ACG risk
adjustment tool can adequately account for this type of variation to the extent such adjustment is
warranted.
Specifically, MDH has developed a measure – the Primary Care Service Index or PCSI – as a
useful tool for assessing the extent to which clinical staff at particular physician clinics practice
primary care. MDH will use the PCSI score and the availability of sufficient quality measures for
the quality composite as described in a previous memo for determining whether a clinic should
be included in total care PPG. MDH will also use a component of the PCSI -- information from
the state licensing file about clinic priority locations – to allocate costs for a single provider
across the various clinics at which s/he is registered for those providers registered at multiple
clinics. MDH is also considering using the PCSI measure to adjust costs as a final step in the
physician clinic analysis in order to more fairly compare clinics offering different types of
services.
Division of Health Policy/ Health Economics Program • 85 East Seventh Place • Suite 220 • St. Paul, MN 55101
www.health.state.mn.us
Linking Physicians and Clinical Staff to Clinic Locations
Claims data links patients with individual providers; it does not associate patients with specific
clinic locations. To associate individual providers with specific clinics, providers have been
linked to clinics through information in the Minnesota Statewide Quality Reporting and
Measurement System physician clinic registry. Patient costs have been attributed to individual
providers consistent with the multiple proportional rule we discussed in a previous memo and the
linkage between providers and clinics has been used to attribute patient costs to clinics.
Approximately 24% of providers are linked with multiple sites in the physician clinic registry.
Patient costs attributed to providers registered with multiple physician clinics will be allocated
across the multiple clinics using weights based on the best information available as described
later in this memo.
Physician clinics are required to annually register all clinical staff at a clinic site level, providing
the clinic’s name and clinic-level National Provider Identification (NPI) number as well as
names and individual-level NPIs for each clinical staff (physicians, physician assistants, and
advanced practice registered nurses). The registry that will be used in the first iteration of PPG
was populated in early 2010 based on data related to 2009 dates of service, the same service
dates that will be used in the physician clinic analysis.
Physician clinics completed the registry with varying levels of care. MDH has invested a
significant amount of time in verifying and cleaning fields in the registry. MDH used the data
sources described below to assist in this process.
Data Sources
Three sources of data were used to link providers to specific physician clinics, to determine how
to allocate costs across clinics for providers affiliated with multiple clinics, and to develop the
measure that assesses the extent to which primary care is practiced at a particular physician
clinic. These include the National Plan and Provider Enumeration System (NPPES) registration
file, the Minnesota Statewide Quality Reporting and Measurement System physician clinic
registry, and the Minnesota Board of Medical Practice licensure file. In combination, these three
sources of data provide the following key pieces of information:
1. An individual provider’s practice location(s),
2. An individual provider’s NPI number and self-selected taxonomy codes (up to four)
which indicate the types of care the provider practices,
3. An individual provider’s priority rating for each type of care (i.e., the principal form of
care provided or a secondary form of care), and
4. A physician’s priority rating of the clinic practice location (i.e., principal place of practice
or a secondary place of practice).
Together, these data elements allow MDH to link individual clinic staff (including physicians,
advanced practice registered nurses, and physician assistants) to particular clinic locations, and
approximate how physicians allocate their time across each physician clinic at which they are
registered. These data are also used to assess the combination of verified physician specialties at
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each physician clinic to create a measure of the extent to which individual physicians and other
clinical staff practice primary care as well as the extent to which a clinic location provides
primary care. Prior to demonstrating the calculation of the primary care service index, it is
useful to pause and explain the role of each data element in the overall measure.
Practice Location:
In the Minnesota Statewide Quality Reporting and Measurement System physician clinic
registry, physicians may be registered at up to three clinic locations. Of the 15,312 clinical staff
included in the 2010 physician clinic registry, 3,650 (24 percent) of providers are registered at
multiple locations. In order to properly gauge the primary care capacity of each clinic, it is
necessary to calculate a unique primary care capacity measure for each clinical staff at each
clinic location at which he/she is registered in order to account for how a particular provider
contributes to an overall measure of primary care capacity at a specific clinic.
Taxonomy Codes:
Taxonomy codes are a classification system which describes specializations and sub-specialties
of medical care. For purposes of PPG, MDH consulted with medical organizations and
designated the following specialties as primary care providers (a more detailed list of which
specialties are considered primary care is presented in Attachment A):
1.
2.
3.
4.
5.
Family Health and Primary Care specialties
Selected Internal Medicine specialties
All Gerontologists
Selected OB/GYN specialties
Selected Pediatrician specialties
Taxonomy code values which fall into these categories of “primary care” are assigned a primary
care value of one. All other taxonomy codes values outside the range of primary care are
assigned a primary care value of zero.
Medical Specialty and Taxonomy Priority Rating (TPR):
Each reported taxonomy code is rated by priority in the taxonomy history of the provider. The
assigned weight depends on the number of taxonomy codes reported and the provider’s rating of
each taxonomy code as either their principal or secondary medical specialty. For example:
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Table 1: Examples of Weighting Associated with Taxonomy Priority Weighting
Number of
Taxonomy
Codes
One
Two
Two
Three
Three
Priority Assigned
to Taxonomy
Codes?
Not necessary
Yes
No
Yes
No
TPR of second
TPR of first
1
Taxonomy Code Taxonomy Code
TPR of third
Taxonomy Code
1
.7
.5
.6
.333
N/A
N/A
N/A
.2
.333
N/A
.3
.5
.2
.333
Clinic Location and Clinic Priority Rating (CPR):
In the physician clinic registry, clinical staff may be registered at up to three clinic locations. For
some of the 24% of clinical staff who practice at multiple locations, the state licensure file
provides information about how physicians allocate their time across various practice locations.
In such cases, one clinic is designated as the principal practice location while the other clinic(s)
are deemed as secondary practice locations. Based on the number of clinics at which the
physician practices, and the priority ranking of each clinic, weights can be assigned to that clinic
to approximate the involvement of that physician in the care of the clinic’s patients. The
essential concept behind the weights is that they sum to 1.0 to approximate the distribution of a
full time employee over all clinics at which they are registered. While these weights are
approximations, they have the benefit of allowing us to approximate the extent to which a
physician or other clinical staff practice at particular clinic locations. These weights will be used
to allocate costs among clinics for providers who are registered at multiple clinics.
The weights are described in Table 2 below:
Table 2: Weighting Associated with Clinic “Priority Ratings” 2
Number of
Clinics at
Which a
Physician is
Registered
One
Two
Two
Three
Three
Is One Clinic
Noted as the
Priority
Location?
CPR for
physician’s
first clinic
location
CPR for
physician’s
second clinic
location
CPR for
physician’s
third clinic
location
Sum of
Physician’s
CPR
scores
Not necessary
Yes
No
Yes
No
1.0
.7
.5
.6
.333
N/A
.3
.5
.2
.333
N/A
N/A
N/A
.2
.333
1.0
1.0
1.0
1.0
1.0
1
Considered the primary taxonomy code when a priority among multiple taxonomy codes is indicated.
Costs will be allocated across physician clinics for those providers registered at multiple clinics based on these
weights.
2
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Calculation of the Individual Primary Care Service Index Value
An individual provider’s primary care service index value is calculated using the following
formula:
 ( PCVi  j *TPRi  j *CPR)
Where:
PCV= Primary Care Value
TPR= Taxonomy Priority Rating
CPR= Clinic Priority Rating
i = first taxonomy code
j = last taxonomy code
It is important to note that an individual provider receives an individual PCSI value for each
clinic at which they are registered. Our intention is to aggregate the individual PCSI scores at a
clinic to the clinic level.
Table 3 provides an example of the data inputs and resulting individual primary care scores for
three separate hypothetical physicians.
Table 3: Individual Primary Care Service Index Values for Three Physicians
Provider
Data Element
Taxonomy Code 1
Taxonomy Code 2
Taxonomy Code 3
Taxonomy Code 4
Taxonomy 1 Priority
Taxonomy 2 Priority
Taxonomy 3 Priority
Taxonomy 4 Priority
Clinic Priority
Individual Prim ary
Care Score
Dr. Davis
Description
Primary Care
NA
NA
NA
Principal
NA
NA
NA
Principal (1/1)
Dr. Rogers
Value /
Rating
1
1
1
Description
Primary Care
Specialty
NA
NA
Principal
Secondary
NA
NA
Principal (1/1)
1
0.7
Dr. Thompson
Value /
Rating
1
0
0.7
0.3
1
Description
Specialist
Primary Care
Primary Care
NA
Principal
Secondary
Secondary
NA
Principal (1/2)
Value /
Rating
0
1
1
0.6
0.2
0.2
0.7
0.28
To further illustrate the calculation, look at the individual primary care score for Dr. Thompson.
Dr. Thompson has three taxonomy codes, two of which are considered primary care. Dr.
Thompson’s principal practice involves a specialty outside of primary care and so the specialty
priority is assigned a priority weight of 0.6. The two primary care service categories share the
remaining 0.4 of the practice priority weight and are each assigned a value of 0.2. Finally, Dr.
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Thompson practices at two clinic locations. This clinic is his/her main location and thus the
clinic priority rating is assigned a value of 0.7.
Using Dr. Thompson as an example, to calculate his/her individual PCSI at this clinic using the
PCSI formula described previously, we do the following:
PCSI i = (0 * 0.6 * 07) + (1 * 0.2 * 0.7) + (1 * 0.2 * 0.7)
= (0) + (.14) + (.14)
= 0.28
Calculation of Clinic Level PCSI Values
The PCSI value for the clinic is easily calculated from knowing the staff clinic priority values
and the individual level provider PCSI scores. The formula is:
(PCSI i )
PCSI c  
 (CPRi )
Where:
PCSI c = Clinic level PCSI value
PCSI i = Individual provider PCSI value
CPR i = Individual provider Clinic Priority Rating
In the hypothetical three physician clinic used previously, the sum of the individual level PCSI
scores is:
 PCSI i = 1 + 0.7 +
0.28
= 1.98
The sum of the individual provider clinic priority ratings serves as a proxy measure of the FTEs
for the providers registered at that clinic. In the example the sum of the clinic priority ratings is:
 CPRi = 1 + 1 + 0.7
= 2.7
Using the formula for clinic level PCSI, the PCSI value for this clinic is:
PCSI c = 1.98 / 2.7
= 0.73
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Planned and Potential Uses of the PCSI Measure
The physician clinic total care analysis will only include clinics offering primary care. The PCSI
values can be used to help determine whether a particular clinic is likely to offer sufficient levels
of primary care to be comparable to other clinics in the PPG total care analysis.
By looking at the distribution of clinic level PCSI scores, there is a clear bi-modal distribution
pattern among Minnesota physician clinics.
Figure 1: Distribution of Clinic Level PCSI Values
Clinics with a PCSI value of zero are specialty-only clinics. These clinics have no registered
clinical staff who report taxonomy codes that fit the definition of primary care. In addition to the
clinics with PCSI values equal to zero, those clinics with PCSI scores less than 0.30 have
proportionally few clinical staff at that location who report having a primary care specialty.
MDH believes the PSCI measure is a reasonable approximation of the extent to which primary
care is practiced at specific clinics. MDH analyzed clinic PCSI scores and notes that as PCSI
scores increase from zero to one, an increasing amount of data is available on quality measures
applicable to primary care providers across a range of quality measures. More specifically, an
analysis of clinics with PCSI values of less than 0.30 showed that most of these clinics either did
not submit quality measures required of primary care provider specialties or have organizational
descriptors that indicate the clinic is a specific specialty care provider.
Based on this information and a policy goal of including only clinics that offer primary care, we
have decided to only include clinics with a PCSI score higher than 0.30 and who meet the criteria
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related to the construction of the composite quality measure (i.e. have sufficient data for at least
one measure in each subcomposite category). This will help ensure the clinics included in PPG
total care provide at least a minimal threshold of primary care. Once we have applied this
criteria, the average PCSI score of remaining clinics increases from a statewide average of .59 to
.83.
The accuracy of the PCSI relies on providers accurately reporting taxonomy codes and their
priority in national NPI registry files, accurate registration of providers at clinics, and accurate
information about clinic priority in the state licensure file. We encourage continued efforts to
maximize accurate data submissions and reporting in these data sources.
Potential Use of the PCSI to Adjust Costs At the Clinic Level
MDH is also proposing to use the clinic PCSI score to adjust costs between clinics with different
primary care capacity to account for cost variation attributable to differences in the services
provided. The proposed service mix adjustment uses a ratio approach, weighting the clinic’s
attributed risk adjusted cost of care by the ratio of the clinic specific PSCI to the state wide
average PCSI. Further, the proposed service mix adjuster would occur as the last step in the
adjustment process, taking place only after all other forms of risk adjustment (related to
clinical/diagnostic differences, payer mix, and outliers) have been performed
Table 4 provides an example of the proposed service mix adjuster using three separate
hypothetical clinics.
Table 4: Service Mix Adjustment Example
Clinic
Attributed Risk-Adjusted
Patients Attributed Costs
Clinic
PCSI
Score
Risk-Adjusted Per
Patient Per Year
Total Cost of Care
Dollars
Relative Cost
Weight
Service Mix Adjusted
Per Patient Per Year
Total Cost of Care
Dollars
Relative Cost
Weight
A
250
$230,560.00
0.7315
$922.24
0.79
$816.33
0.70
B
1,000
$654,540.00
0.9865
$654.54
0.56
$781.35
0.67
C
350
$545,690.00
0.6845
$1,559.11
1.33
$1,291.40
1.10
4,250,600
$4,973,202,000
0.8264
$1,170.00
1.00
$1,170.00
1.00
State Wide Values
Using Clinic A from Table 4 as an example, the annual per patient total cost of care is
determined by dividing the total attributed costs at the clinic by the total attributed patients at the
clinic. For Clinic A, this is equal to $230,560 / 250 or $922.24 per patient per year.
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Prior to adjustment for service mix, clinics can be compared to other clinics in the state by
dividing clinic specific risk-adjusted annual per patient costs by the statewide average annual per
patient cost. For Clinic A this is equal to $922.24 / $1170 or 0.79 (79% of the statewide average
per patient annual cost).
However, to improve the comparison for clinics with differing service mix, the annual per patient
total cost of care can be adjusted to reflect the clinic’s staff capacity for primary care relative to
the statewide average primary care capacity. Clinic A’s PCSI value is 0.7315, a little less than
the statewide benchmark for all clinics of 0.8264. To adjust costs to reflect the service mix
difference, multiply the unadjusted annual per patient costs by the Clinic PCSI to Statewide
PCSI ratio. For clinic A this is equal to $922.24 * (0.7315 / 0.8264) = $816.33.
Clinic A’s PCSI service mix adjusted costs can be compared to other clinic’s service mix
adjusted costs by dividing the clinic specific annual per patient cost by the statewide average
annual per patient cost (note the value is the same adjusted or unadjusted by service mix). The
adjusted comparison is equal to $816.33 / $1,170 or 0.70 (70% of the statewide average per
patient annual cost).
Conclusions:
MDH developed the PCSI as a unique measure of the extent to which primary care is practiced at
particular clinics. Because total care PPG is intended to include comparable clinics offering
primary care and because clinics differ in the extent to which they offer primary care, MDH will
use the PCSI as one criterion for determining whether clinics are included in the PPG total care
analysis. MDH will also use a component of the PCSI -- information from the state licensing file
about clinic priority locations – to allocate costs for a single provider across the various clinics at
which s/he is registered for those providers registered at multiple clinics.
MDH is proposing to use the PCSI measure to adjust costs between primary care only clinics and
multispecialty clinics that offer primary care as outlined above, used on the heels of
clinical/diagnostic, outlier, and payer mix risk adjustments. MDH is soliciting feedback on
whether an adjustment related to service mix is needed in the context of clinic-level peer
grouping. MDH appreciates that some aspects of differences in service mix will be accounted
for through the use of ACGs as more severely ill patients are likely to receive care from
specialists. MDH is seeking stakeholder feedback about whether the ACG-based risk adjustment
method sufficiently accounts for differences in service mix or whether additional adjustment
based on PCSI values is warranted.
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