Enhancing Value:
Using WHIO Data for
Evaluating Radiology Services
Data Mart Version 8 ©2014 Wisconsin Medical Society
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The Wisconsin Health Information Organization (WHIO) has created a data mart of health insurance claims information from 16 health insurance companies. The data mart is a tremendous asset for evaluating utilization of health services in Wisconsin. This report considers outpatient radiology services included in the WHIO Data Mart Version 8 (DMV8) between April 1, 2010, and March 31, 2012. These services account for more than $6.5 billion in billed charges or about 9.7% of overall billed charges in DMV8.
In order to evaluate health care value, it is necessary to focus on measures of both health care utilization and quality of care. Related to utilization, the top 25 radiology CPT codes—based on total standard costs and total billed charges—were identified in the WHIO data mart. Content experts reviewed those codes and eliminated some because a variety of physicians other than radiologists report them. They added other codes for a total of 161 candidate radiology CPT codes. This report focuses on one of the 161 candidate codes—computerized tomography (CT) scan of the abdomen and pelvis with contrast (CPT code 74177)—because it was included on the content expert list and because it topped both the total billed charges and total standard cost lists.
Key Findings
In our comparison of population utilization and average billed charges for CPT code 74177 for Wisconsin’s five public health regions, we found the following:
• 129,051 claims accounted for $202,292,676 in total billed charges for CT scan of the abdomen and pelvis with contrast. Claims with the 74177 global code represent the majority of billed charges.
• Average billed charges and claims per 1,000 beneficiaries vary across Wisconsin’s five public health regions for CPT code 74177.
• The Southern Region had the lowest number of claims per 1,000 beneficiaries with 11.4.
• The Northeastern Region had the highest number of claims per 1,000 beneficiaries at 17.6.
• Average billed charges per claim were highest in the Southern Region ($3,208) and lowest in the Northeastern Region ($2,369).
• The Northern Region had both low utilization per 1,000 beneficiaries (11.9 claims) and low average billed charges ($2,385).
Comparative analyses similar to the one in this report are available for the other 160 radiology CPT codes on the Wisconsin Medical Society (Society) website.* Turning to health care quality—the other component of value—10 candidate quality measures pertaining to radiology services were identified in the WHIO data. Two of the 10 were commonly accepted Healthcare Effectiveness Data and Information Set
(HEDIS®) measures at the time of DMV8 and are
presented in this report:
• Patients with uncomplicated low back pain that did not have imaging studies.
• Patients 42 to 69 years of age that had a screening mammogram in the last 24 reported months.
We compared quality measure results for internists and family physicians in each of the public health regions and found that:
• Internists scored higher than family physicians statewide (79.7% vs 73.8%, respectively) on screening mammograms for patients aged 42 to 60 years. The Northern Region had the lowest score for family physicians (71.4%), while the
Using WHIO Data for Evaluating Radiology Services
Southeastern Region had the lowest score for internists (76.9%).
• Family physicians performed better than internists in terms of not ordering imaging studies for patients with uncomplicated low back pain. The statewide average was 77.9% for family physicians and 73.6% for internists. Family physicians and internists in the Southeastern Region had the best performance scores (78.9% and 75.2%, respectively).
Results for the eight other WHIO radiology care quality measures are available on the Society website.*
Conclusion
Health care reform models focus on payment for value that rewards physicians for good stewardship of health services in delivering high quality health care. The WHIO data mart is a unique asset for capturing variation in measures of both health care utilization and quality of care. This report presents an example of how radiology claims contributed by multiple payers can be used to compare a commonly performed radiology procedure and two national standard quality measures pertaining to radiology care.
Disclaimer
The Wisconsin Medical Society has created this report to provide health care cost and utilization information for local, regional and statewide areas. The data source for this report is the WHIO Data Mart Version 8 (DMV8) database, which the Society relied upon without audit in the creation of this report. The collection and aggregation of all underlying data was undertaken by WHIO. The Society is not responsible for the accuracy or content of the underlying data contained in this report or for the concepts or methodologies contained in the software used in the analysis. Be advised of the possibility of errors in data collection or aggregation or in software concepts or methodology, which may affect the report results. Use of the data or conclusions contained in this report for anything other than informational purposes is at the recipient’s own risk.
With more than 12,000 members dedicated to the best interests of their patients, the Wisconsin Medical Society (Society) is the largest association of medical doctors in the state and a trusted source for health policy leadership since 1841. The Society – together with the Wisconsin Medical Society Foundation (a nonprofit organization founded in 1955) and Wisconsin Medical Society Insurance & Financial Services, Inc. – works to improve the health of all Wisconsin citizens. To learn more, visit www. wisconsinmedicalsociety.org.
The Society and physicians across the state have made a commitment to transparency by using credible, robust data to improve quality and efficiency and make health care more accessible for Wisconsin citizens. One way the Society is accomplishing this is by analyzing health insurance claims data from the Wisconsin Health Information Organization (WHIO) database to assess differences in health care quality and utilization. The Society is one of the 13 founding members of WHIO and serves in leadership roles on the Board of Directors and other WHIO committees. As a founding member of WHIO, the Society is interested in how claims data may be helpful in studying utilization patterns in relation to appropriate use criteria and cost-sensitive best practices. The goal of these efforts is to enhance value and to ensure that as many people as possible have access to high-quality, affordable health care.
About the Wisconsin
Medical Society
Using WHIO Data for Evaluating Radiology Services
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*To access additional analyses on radiology utilization and quality measures, visit our website www.wisconsinmedicalsociety.org/ professional/enhancing-value/ or scan this code.
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Table 1. Population and WHIO Beneficiary Comparison by Region
Region Region Population Total WHIO Beneficiaries Year 2 WHIO Beneficiaries % of Region Population Represented in WHIO DMV8 Northeastern 1,159,413 791,671 717,714 68.3% Northern 480,094 378,877 348,435 78.9% Southeastern 1,939,113 1,235,442 1,100,803 63.7% Southern 1,068,737 928,931 860,600 86.9% Western 659,038 400,816 357,297 60.8%
About the
Wisconsin Health
Information
Organization
The Wisconsin Health Information Organization (WHIO) is a not-for-profit collaboration of health care providers, insurance companies, employers and public entities created in 2005 to develop a statewide database of health insurance claims. WHIO’s goal is to use health care data to improve the quality, affordability, safety and efficiency of health care in the state. This report uses the eighth release of the WHIO data – Data Mart Version 8 (DMV8) – with claims having dates of service from April 1, 2010, through March 31, 2012. DMV8 includes data from almost all major health care payers in Wisconsin except fee-for-service (FFS) Medicare.
Table 1 provides a regional display of the number of WHIO beneficiaries compared to total population in each of Wisconsin’s five public health regions. Percentages represented in WHIO DMV8 range from 60.8% of the population in the Western Region to 86.9% in the Southern Region. Sixteen data contributors provide health insurance claims for the WHIO database. Each database update is continuously populated with 24 months of health insurance claims data, and an updated version is released approximately every six months. More information about WHIO is available online at www. wisconsinhealthinfo.org.
WHIO Data Mart Version 8 Key Statistics
Population • 3,955,836 distinct beneficiaries in DMV8 (April 1, 2010 – March 31, 2012) • 3,736,671 Wisconsin beneficiaries in DMV8 • 3,570,414 distinct beneficiaries in Time Period 2 (April 1, 2011 – March 31, 2012)Percent of Wisconsin Population (Estimated April 1, 2010 at 5,686,986): 65.7%
DMV8 Population by Age Bands (Wisconsin Residents, Time Period 2)
• Younger than 18 – 28% • 18 to 64 – 59%
• 65 and older – 13%
DMV8 Population by Insurance Type (Wisconsin Residents, Time Period 2) • Commercially insured – 55% • Medicaid – 37% Medicaid fee-for-service (FFS) – 9% Medicaid HMO – 22% Medicare/Medicaid Dual FFS – 6% Medicare/Medicaid Dual HMO – 0.2% • Medicare – 8%
Medicare Advantage – 5% Medicare Supplemental – 3% • Federal Employee Program – 0.1%
Using WHIO Data for Evaluating Radiology Services
Using WHIO Data for Evaluating Radiology Services This Enhancing Value Report considers outpatient
radiology services included in the WHIO DMV8 that account for more than $6.5 billion in billed charges or about 9.7% of overall billed charges. It also reflects a departure from the Wisconsin Medical Society’s previous approaches to understanding utilization of health care services based on the WHIO claims data.
The WHIO data mart is a tremendous resource for evaluating utilization of health care services in Wisconsin. Since the first WHIO data mart was released in December 2008, the Society has offered orientations to the WHIO concepts and methodologies for physicians and their staff. Standardized pricing—as a proxy for differences in utilization of health care services— and Episode Treatment Groups (ETGs) are core concepts underlying the WHIO data aggregation specifications. Many outputs available through the WHIO Impact Intelligence Reporting System focus on ETGs and standardized pricing.
Yet many health care opinion leaders have
questioned why the WHIO data are not used more
widely. The answer may, in part, have to do with the core WHIO methodologies (e.g., standardized pricing and ETGs), which mask the basic building blocks of utilization—billed charges, ICD-9 diagnosis and CPT procedure codes—that may be more recognizable to physicians. Presenting physicians with comparative utilization information based on data aggregated in unfamiliar ways has introduced barriers to understanding health care costs and practice pattern variations that may be associated with over- or under-utilization of health care services.
Working with Wisconsin radiology leaders, the Society initiated introductory discussions to better understand how physicians view the CPT codes. Building on these insights, this report is divided into four sections. The first presents key statistics about WHIO Data Mart Version 8 (DMV8). Subsequent sections provide demographic characteristics about the people whose claims are captured in the WHIO data mart, utilization of radiology services CPT code 74177—CT abdomen and pelvis with contrast— and quality of care measures related to radiology utilization.
Using WHIO Data for Evaluating Radiology
Services
Disclosure
This report is based on the last year of the WHIO DMV8 data mart, including the three-month lag period, full claims and service records with coverage for all beneficiaries and all payers. Billed charges (Cost2) were attributed to a public health region based on the ZIP code of all physician practice locations for all specialties (peer groups) and all regions that were mapped to counties. Counties were attributed to one of five public health regions as defined by the Wisconsin Department of Health Services. Total billed charges, average billed charges and claims per 1,000 were calculated directly from the claims without consideration of the episode grouping methodology. There was no minimum number of observations required for each public health region. Utilization statistics are unadjusted, although demographic data and payer mix are presented for each public health region. The top and bottom 3% of the data series were removed. Data for beneficiaries in border areas of the state may be under-represented since health insurance companies from neighboring states currently do not contribute data to the WHIO data mart.
The quality of care measures were attributed to internal medicine and family medicine peer groups based on the Optum-defined peer groups. Patient quality opportunities and the quality opportunities with compliance were attributed to the physicians in the family medicine and internal medicine peer groups by Optum.
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Adams Ashland Barron Bayfield Brown Buffalo Burnett Calumet Chippewa Clark Columbia Crawford Dane Dodge Door Douglas Dunn Eau Claire Florence Fond du Lac Forest Grant Green Green Lake Iowa Iron Jackson Jefferson Juneau Kenosha Kewaunee La Crosse Lafayette Langlade Lincoln Manitowoc Marathon Marinette Marquette Menominee Milwaukee Monroe Oconto Oneida Outagamie Ozaukee Pepin Pierce Polk Portage Racine Richland Rock Rusk St Croix Sauk Sawyer Shawano Sheboygan Taylor Trempealeau Vernon Vilas Walworth Washburn Washington Waukesha Waupaca Waushara Winnebago Wood Northern Region Southern Region Southeastern Region Northeastern Region Western Region Price Male Female 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Below 18 18 to 64 Above 64Medicare Medicaid Commercial
54.1% 45.9% 34.5% 57.4% 6.0% 65.5% 41.2% 43.8% 0.0% 1.3% 50.2% (n=106,721) (n=200,082) (n=50,494) Male Female 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Below 18 18 to 64 Above 64
Medicare Medicaid Commercial
58.0% 79.2% 19.3% 42.0% 20.1% 36.2% 0.0% 0.7% 44.5% (n=231,853) (n=539,566) (n=89,181) 52.7% 47.3% Western Region (n = 357,297) Southern Region (n = 860,600)
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Adams Ashland Barron Bayfield Brown Buffalo Burnett Calumet Chippewa Clark Columbia Crawford Dane Dodge Door Douglas Dunn Eau Claire Florence Fond du Lac Forest Grant Green Green Lake Iowa Iron Jackson Jefferson Juneau Kenosha Kewaunee La Crosse Lafayette Langlade Lincoln Manitowoc Marathon Marinette Marquette Menominee Milwaukee Monroe Oconto Oneida Outagamie Ozaukee Pepin Pierce Polk Portage Racine Richland Rock Rusk St Croix Sauk Sawyer Shawano Sheboygan Taylor Trempealeau Vernon Vilas Walworth Washburn Washington Waukesha Waupaca Waushara Winnebago Wood Northern Region Southern Region Southeastern Region Northeastern Region Western Region Price 53.1% 46.9% Male Female 40.6% 64.8% 5.5% 59.4% 33.4% 32.2% 0.0% 1.8% 62.3% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Below 18 (n=92,868) (n=201,137)18 to 64 (n=54,430)Above 64Medicare Medicaid Commercial
Male Female 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Below 18 18 to 64 Above 64
Medicare Medicaid Commercial
52.9% 47.1% 47.2% 69.9% 5.4% 52.8% 27.6% 24.6% 0.0% 2.5% 69.9% (n=200,799) (n=411,205) (n=105,710) Male Female 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Below 18 18 to 64 Above 64
Medicare Medicaid Commercial
54.3% 45.7% 32.6% 59.5% 18.6% 67.4% 39.0% 31.3% 0.0% 1.5% 50.1% (n=354,319) (n=621,219) (n=125,265) Northern Region (n = 348,435) Northeastern Region (n = 717,714) Southeastern Region (n = 1,100,803)
This figure displays the distribution of beneficiaries in Year 2 of the WHIO data mart by state public health region. The WHIO data capture different percentages of the five public health region
populations with 60.8% of the Western Region population and 86.9% of the Southern Region population represented in the WHIO DMV8 database. This may be due to beneficiaries in border areas of the state receiving health insurance from a neighboring state that does not contribute data to WHIO.
The percentage of beneficiaries in each age category was similar across the five public health regions. For the age group Below 18, the highest percentage of Medicaid beneficiaries was in the Southeastern Region (67.4%) whereas the Western Region had the highest percentage of Medicaid beneficiaries (41.2%) for the 18- to 64-year-old age group. The Southern Region had the highest percentage of Commercial beneficiaries for both the Below 18 (58.0%) and 18- to 64-year-old (79.2%) age groups. There was little variation in the percentage of female beneficiaries in each region.
Figure 1.
WHIO Beneficiary
Demographics in Year 2
by Public Health Region
Figure 1. WHIO Beneficiary Demographics by Public Health Region (WHIO DMV8
Year 2, all payers, full and partial claims, all beneficiaries)
Data Mart Version 8 ©2014 Wisconsin Medical Society
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In order to evaluate health care value, it is necessary to focus on measures of both health care utilization and quality of care. Related to utilization, the top
25 radiology CPT1 codes, based upon total standard
costs and total billed charges, were identified in DMV8. Content experts reviewed those codes and eliminated some because a variety of physicians other than radiologists report them. They added other codes for a total of 161 candidate radiology CPT codes. This report focuses on one of the 161 candidate codes—CT scan of the abdomen and pelvis with contrast (CPT code 74177)—because it was included on the content expert list and because it topped both the total billed charges and total standard cost lists.
Table 2 displays the number of claims and total billed charges in DMV8 for CPT code 74177 broken down by claims with the 26 modifier and claims without a modifier (global code). There were 129,051 claims with either of these codes that accounted for $202,292,676 in total billed charges. Claims with the 74177 global code represent the majority of billed charges for CT scan of the abdomen and pelvis with contrast.
Radiology Procedure Utilization
In addition to looking at radiology services at a macro level, it can be informative to study the variation in utilization of radiology procedures at a regional level. Thus, we compared population utilization and average billed charges for CT scan of the abdomen and pelvis with contrast across Wisconsin’s five public health regions.
Table 3 displays the number of 74177 claims for unique patients by public health region. Average billed charges and claims per 1,000 beneficiaries vary across Wisconsin’s five public health regions for CT
for abdomen and pelvis with contrast. The Southern Region had the lowest number of claims per 1,000 beneficiaries with 11.4. The Northeastern Region had the highest number of claims at 17.6 per 1,000 beneficiaries. Average billed charges per claim were highest in the Southern Region ($3,208 ) and lowest in the Northeastern Region ($2,369). The Northern Region had both low population utilization (11.9) and low average billed charges ($2,385).
Discussion
To provide appropriate care, physicians must have access to meaningful utilization and clinical information for medical decision making (See Sidebar). Presenting radiology utilization data to physicians in familiar ways will help them understand variations in the use of radiology procedures not associated with improved quality of care. Introducing new constructs (e.g., standardized pricing rather than billed charges or payments, and ETGs that mask the underlying CPT and ICD-9 diagnosis codes), leads to confusion. While WHIO’s aggregate measures may be directionally useful in the future, at this time, they create barriers for physicians seeking to understand overall utilization patterns and best practices. The observed differences in utilization may represent a crossroads in terms of the signals insurers are sending about payment. In March 2013, Kaiser Health News reported that insurance data show only 10.9% of spending for health care services in 2012 was based on value, while 89.1% of payments were
Using WHIO Data for Evaluating Radiology
Utilization Variation
Table 2. WHIO DMV8 Claims for CPT code 74177 CT Abdomen and Pelvis with Contrast
Number of Claims Total Billed Charges
74177 53,646 $152,364,830
74177_26 75,405 $49,927,846
Using WHIO Data for Evaluating Radiology Services
9
Reference
1. CPT copyright 2012 American Medical Association. All rights reserved. CPT is a registered trademark of the American Medical Association.
Using Clinical Decision
Support Tools for Health
Policy
The American College of Radiology (ACR) has developed the Appropriateness Criteria® to
assist referring physicians and other providers in making the most appropriate imaging or treatment decisions for a specific clinical condition. By embedding these evidence-based criteria in point-of-service decision-support technologies, physicians can enhance quality of care, reduce patient confusion and reduce wasted health care resources through the most efficacious use of radiology. Recently, a coalition of the Wisconsin Radiology Society and the Wisconsin Medical Society convinced the Wisconsin Department of Health Services (DHS) that preauthorization of CT and magnetic resonance imaging (MRI) was duplicative and unnecessary if clinical decision-support tools were utilized to ensure appropriate use of radiology procedures. By capitalizing on advanced decision-support imaging tools, patients benefit from the consistent application of the most comprehensive current evidence for selecting appropriate diagnostic imaging and interventional procedures for numerous clinical conditions. These are time and effort savings to patients, physicians and the state due to implementing a streamlined, cost-effective approach to choosing imaging services. Previously, the preauthorization requirement set up a triangulation between insurer, patient and doctor. Delays in approving imaging orders could lead to longer patient wait times or last-minute changes in care, including failure to complete recommended imaging procedures. Going forward, DHS saves money on both unnecessary radiology procedures that are not performed and on the radiology benefit management preauthorization process. To read a case study about this initiative, visit http://www.acr.org/Advocacy/ Economics-Health-Policy/Imaging-3/Case-Studies.
Table 3. Regional Utilization of Global CPT code 74177
Region Number of Claims Unique Patients Total Billed Charges Average Billed Charges Claims Per 1,000 Ben-eficiaries Northeastern 13,942 10,838 $33,032,403 $2,369 17.6 Northern 4,506 3,686 $10,745,902 $2,385 11.9 Southeastern 19,548 15,345 $60,206,110 $3,080 15.8 Southern 10,605 8,887 $34,019,190 $3,208 11.4 Western 5,045 4,259 $14,361,225 $2,847 12.6
Table 4. Regional Utilization of CPT code 74177_26
Region Number of Claims Unique Patients Total Billed Charges Average Billed Charges Claims Per 1,000 Ben-eficiaries Northeastern 17,769 14,537 $12,903,630 $726 22.4 Northern 8,441 6,958 $4,900,111 $581 22.3 Southeastern 27,611 21,768 $17,366,162 $629 22.3 Southern 14,136 11,603 $9,148,794 $647 15.2 Western 7,448 6,246 $5,609,149 $753 18.6
To learn more about Wisconsin’s utilization patterns for additional radiology procedures, please visit the Wisconsin Medical Society Website by scanning this code.
for traditional fee-for-service, according to a study by the Catalyst for Payment Reform, a consortium of 21 large U.S. employers. The group’s report, the National Scorecard on Payment Reform, is aimed at encouraging the health care industry to adopt value-based payment systems that focus on quality and efficiency more quickly. One explanation for the variation in utilization across regions may be related to differences in payment systems that support changes in patient care, recognizing that there must be a financially sustainable way to switch from volume to value-based payment.
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Performance Measures Involving Radiology
Procedures
77 .9 % 77 .8 % 72 .9 % 78 .9 % 77 .7 % 77 .6 % 73 .6 % 73 .7 % 65 .8 % 75.2% 72 .1 % 67 .9 % 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%Statewide Northeastern Northern Southeastern Southern Western Family Medicine Internal Medicine
73 .8 % 75 .8 % 71 .4 % 72 .3 % 73 .5 % 75 .3 % 79 .7 % 81 .1 % 81 .2 % 76 .9 % 82 .3 % 83 .0 % 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Statewide Northeastern Northern Southeastern Southern Western Family Medicine Internal Medicine
Figure 5. Beneficiaries with Uncomplicated Low Back Pain Who Did
Not Have Imaging Studies.
Figure 6. Beneficiaries 42-69 Years of Age Who Had a Screening
Mammogram in the Last 24 Months.
had the best score (83.0%), while family physicians in the Northeastern Region had the best performance (75.8%).
Quality of care measures are another dimension of the value proposition around use of radiology procedures. The Healthcare Effectiveness Data and Information Set (HEDIS®)2 is a tool used by more than 90% of
America's health plans to measure performance on important dimensions of care and service.Altogether, HEDIS® consists of 75 measures across eight
domains of care3. Two commonly accepted national
standard HEDIS® performance measures related
to the use of radiology procedures at the time of DMV8 are presented in this report. Results on each of the following measures were compared within regions and across regions for family physicians and internists:
• Patients with uncomplicated low back pain that did not have imaging studies.
• Patients 42 to 69 years of age that had a screening mammogram in the last 24 reported months.
Figure 5 displays the results of the low back pain performance measure. Family physicians performed better than internists in terms of not ordering imaging studies for patients with uncomplicated low back pain. The statewide average was 77.9% for family physicians and 73.6% for internists. Family physicians and internists in the Southeastern Region had the best scores overall with performance at 78.9% and 75.2% respectively. Family physicians and internists in the Northern Region had the worst scores on this measure. Figure 6 contains results of the screening
mammography performance measure. Internists scored higher than family physicians (79.7% vs. 73.8%, respectively), both statewide and across all regions. Of family physicians, those in the Northern Region had the lowest score (71.4%), while the lowest scoring internists were in the Southeastern Region (76.9%). Internists in the Western Region
Reference
2. HEDIS® is a registered trademark of the National Committee for
Quality Assurance (NCQA)
3. NCQA Website. http://www.ncqa.org/HEDISQualityMeasurement/ WhatisHEDIS.aspx. Accessed November 5, 2013.
To learn about more quality measures pertaining to radiology procedures, please visit the Wisconsin Medical Society website www.wisconsinmedicalsociety. org/professional/enhancing-value/by scanning this code.
The Wisconsin Medical Society offers physicians, other health care professionals and health care organizations several opportunities to learn how they can use the WHIO database to improve the quality and efficiency of care they provide. These opportunities include the following:
Buck E. Badger Report—Available at the individual physician and clinic levels, the Buck E. Badger Report provides standard informa-tion about a physician’s practice in comparison to his/her specialty for 19 specialties (e.g., a family physician is compared to all family physicians in Wisconsin). The report provides information about the type of Episode Treatment Groups (ETGs) that make up a physi-cian’s practice, the case mix of a physitype of Episode Treatment Groups (ETGs) that make up a physi-cian’s attributed episodes of care and the case mix-adjusted overall quality and cost indices.
Episode Treatment Group (ETG) Analyzer Report—The Society’s ETG Analyzer Report provides a comparison of all of a clinic’s ETGs (with at least 30 episodes) to a regional group. The regional group may be one of Wisconsin’s eight economic development regions, a county or a combination of counties (up to 12 may be selected). For each ETG, the report provides the number of episodes, average standard costs and average billed costs for the selected clinic and its comparison region. This helps a clinic select ETGs for additional analysis.
ETG Drill-Down Report—The ETG Drill-Down Report provides detailed information about the average standard costs for one ETG for each physician in a medical group, for the medical group overall and in comparison to a regional group. Five service categories are used to present the cost analysis for each ETG: facility inpatient, facility outpatient, pharmacy, professional services and ancillary.
Custom Analytics—The Society’s Data Analytics team of WHIO experts is available to work with physicians and health care lead-ers to address specific areas of concern or interest. The WHIO data have been analyzed to understand claims-level variation in specific ETGs, for evaluating patient-centered medical home out-comes and for contracting purposes related to Accountable Care Organizations. To learn more, call 866.442.3751.
Next Steps
Wisconsin Medical
Society Staff involved in
creating this report
Cindy Helstad, PhD, RN, Senior Director of Research and Analytics Raju Vadapalli, MCA, Systems Architect
Laura Jacobs, Project Manager/ Business Analyst
Jaime Schleis, Service Specialist Mary Kay Adams-Edgette, Senior Graphic Designer
Kendi Parvin, Director of Communications
Tim Bartholow, MD, former Chief Medical Officer
We wish to thank Susan
Wiegmann, PhD, Lisa Hildebrand, Timothy A. Crummy, MD, and Gregg Bogost, MD, for their helpful comments on draft versions of this report.
