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The American Journal of Managed Care July 2015
Low-Value Care for Acute Sinusitis Encounters: Who's Choosing Wisely?
Adam L. Sharp, MD, MS; Marc H. Klau, MD, MBA; David Keschner, MD, JD; Eric Macy, MD, MS; Tania Tang, PhD, MPH; Ernest Shen, PhD; Corrine Munoz-Plaza, MPH; Michael Kanter, MD; Matthew A. Silver, MD; and Michael K. Gould, MD, MS
Usefulness of Pharmacy Claims for Medication Reconciliation in Primary Care
Dominique Comer, PharmD, MS; Joseph Couto, PharmD, MBA; Ruth Aguiar, BA; Pan Wu, PhD; and Daniel J. Elliott, MD, MSCE
No Longer a Unicorn: Improving Health Through Accountable Care Organizations
Risa Lavizzo-Mourey, MD, MBA, president and CEO, The Robert Wood Johnson Foundation
ACA-Mandated Elimination of Cost Sharing for Preventive Screening Has Had Limited Early Impact
Shivan J. Mehta, MD, MBA; Daniel Polsky, PhD; Jingsan Zhu, MBA; James D. Lewis, MD, MSCE; Jonathan T. Kolstad, PhD; George Loewenstein, PhD; and Kevin G. Volpp, MD, PhD
Determinants of Medicare Plan Choices: Are Beneficiaries More Influenced by Premiums or Benefits?
Paul D. Jacobs, PhD; and Melinda B. Buntin, PhD
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Charles Elder, MD, MPH; Lynn DeBar, PhD, MPH; Cheryl Ritenbaugh, PhD, MPH; William Vollmer, PhD; Richard A. Deyo, MD, MPH; John Dickerson, PhD; and Lindsay Kindler, PhD, RN
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Worksite Medical Home: Health Services Use and Claim Costs
Christopher Conover, PhD; Rebecca Namenek Brouwer, MS; Gale Adcock, MSN, RN, FNP-BC, FAANP; David Olaleye, PhD, MSCe; John Shipway, BS; and Truls Østbye, MD, PhD
The Value of Colonoscopic Colorectal Cancer Screening of Adults Aged 50 to 64
Kathryn Fitch, RN, MEd; Bruce Pyenson, FSA, MAAA; Helen Blumen, MD, MBA; Thomas Weisman, MD, MBA; and Art Small, MD
It's Time for CMS to Utilize Functional Assessment as a Key Quality Component
Wayne Matthews, MS, PA-C, DFAAPA
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Jennifer K. Maratt, MD; and Sameer D. Saini, MD, MS
Pilot of Decision Support to Individualize Colorectal Cancer Screening Recommendations
Amy R. Schwartz, MD; Forrest L. Levin, MS; Joseph A. O'Neil, Jr, BS; and R. Scott Braithwaite, MD, MSc

Worksite Medical Home: Health Services Use and Claim Costs

Christopher Conover, PhD; Rebecca Namenek Brouwer, MS; Gale Adcock, MSN, RN, FNP-BC, FAANP; David Olaleye, PhD, MSCe; John Shipway, BS; and Truls Østbye, MD, PhD
This study examined the relationship among availability of an on-site, employer-provided primary care medical home, and health services use and health plan costs.

Objectives: To examine the relationship among use of an on-site employer-provided primary care medical home, and health services use and health plan costs for inpatient and outpatient services and pharmaceuticals.

Study Design: The study was a retrospective observational analysis of health plan claims, human resources data, and Health Care Center (HCC) encounters. 

Methods: Three years of data for employees and dependents designating the HCC as their primary care provider (HCC major users) were compared with data from 2 comparison groups: “casual” HCC users and HCC nonusers. The outcomes of interest were: 1) health services utilization, and 2) monetized use of the health plan. Secondary data from an employer-provided Health Care Center (HCC). 

Results: After adjusting for several potential confounders, HCC major users had less use of external healthcare services than the comparison groups (employees had 2.7 fewer external encounters than HCC casual users [P <.001] and 1.2 fewer external encounters than nonusers [P <.001]; dependents had 3.5 fewer external encounters than HCC casual users [P <.001] and 1.9 fewer external encounters than non-users [P <.001]). Annual monetized use of the health plan for employees and dependents was highest for HCC casual users relative to HCC major users (employees: $482 greater, P <.01; dependents: $598 greater, P <.001).

Conclusions: Employees and their dependents who were “casual users” of the HCC had the highest claims costs and use of outside healthcare services. Additional research is needed to assess the extent to which employees’ utilization of services at on-site primary care medical homes affects employee health outcomes, resulting in potential effects on company healthcare plan expenditures, worker productivity, and return on investment. 
Am J Manag Care. 2015;21(7):e422-e429
Take-Away Points

“Casual users” of an on-site medical home had the highest claims costs and use of outside healthcare services. While “major users” of the on-site medical home had higher use of on-site services, they had lower claims costs than the other groups for outpatient claims.
  • Use of on-site medical homes is associated with decreased total use of outpatient care including preventive care services.
  • Whether on-site clinics save money is dependent on the cost of on-site care delivery in the context of avoided claims costs.
  • Analytics software can help employers monitor and evaluate on-site and external use of health services.
The United States spends more per capita on healthcare than any other nation,1 and employers pay more than a quarter of this total.2 Regular access to primary care can help curb healthcare costs through increased use of clinical preventive services, reduced hospitalizations, appropriate follow-up of chronic conditions, and greater continuity of care.3-6

The “medical home” may be a good model for improving the health of employees through high-quality and readily accessible healthcare at the workplace.7-10 First introduced in 1967,11 “medical home” has recently been described as a place where patients receive “acute, chronic, and preventive services” that are “accessible, accountable, comprehensive, integrated, patient-centered, safe, scientifically valid, and satisfying to both patients and their physicians.”12

While many employers offer health promotion programs of various intensity and scope, we use the term “workplace medical home” to denote a set of more comprehensive primary care services at the worksite, offering acute care and chronic disease management in addition to clinical preventive services provided by nurse practitioners and physicians. This idea has caught on: the number of companies creating in-house healthcare opportunities is increasing, with reports of 23% to 30% of mid-sized and large employers (500 or more employees) now providing on-site or near-site clinics for employee health.13-15 The creation of employer-based primary care clinics, sometimes even including pharmacies, may be a response to an otherwise unsatisfactory and sometimes failing primary care system, as a way to reduce direct healthcare costs assumed by the employer, and/or to attract and retain employees. Employers may increasingly recognize the connection between employee health and work performance.

While worksite medical homes appear to produce economic benefits in terms of lower health plan spending and higher worker productivity, the indirect benefits are of great importance: companies providing on-site healthcare are doing well for their employees. Gemignani reported that employees cite satisfaction with convenience of location, payment, and lack of claims to file.16 Turner found that 95% of employees from a midwestern manufacturing plant offering on-site primary care would recommend the worksite clinic to coworkers, and 96% would themselves return for care.7 Worksite medical homes may also benefit employers by reducing the number of emergency episodes, ambulatory care–sensitive hospital admissions, and/or total cost of healthcare for an employer-sponsored health plan. Berry et al concluded that successful employee health centers are those created for the right reasons, including encouraging an attitude of wellness, convenient access to a high-quality medical home, conveying a company’s commitment to employees, improving productivity, reducing turnover, and achieving better control of healthcare costs.17 

The objective of this study was to explore the relationship among the extent of use of an on-site, employer-provided primary care medical home at a large North Carolina employer and: 1) health services utilization both in the Health Care Center (HCC) and in the community, and 2) health plan claims costs monetized using standardized prices. Employees at this workplace included 3 subject cohorts with varying degrees of “exposure” to the primary care medical home. What is unique about our study is that we have separately tracked HCC use and health plan use so that we can examine the extent to which on-site HCC use might substitute for use of care in the community.



Setting. SAS Institute Inc (SAS) is the world’s largest privately held software company, with more than 13,700 employees worldwide, and approximately 5200 employees working at the company’s global headquarters in Cary, North Carolina. Since 1984, Cary has had an on-site HCC, which has served as a “workplace medical home” since 1996 for employees and their dependents covered by SAS health insurance. The HCC operates during company weekday business hours, offering after-hours care through an answering service and rotating on-call physicians and nurse practitioners, who along with other health professionals provide a full range of primary care services. The HCC provides diagnosis and treatment of acute episodic illnesses, triage and treatment of emergencies, chronic disease management, and specialist referrals as needed. During this study’s timeframe, employees could choose between a networked preferred provider organization (PPO) plan and an indemnity plan for theirs and their dependents’ company-sponsored health insurance coverage. In addition to their choice of health plan, all employees and their dependents could choose between the on-site HCC or a community provider for primary care.

Subjects. This was a retrospective cohort study comparing HCC utilization in a group of patients who designated the HCC as their primary care provider relative to 2 comparison groups. The study population was every benefits-eligible employee during the entire 3-year study period and their dependents. The 3 mutually exclusive groups were: 1) HCC “major users, who designated the HCC as their primary care provider; 2) HCC “casual users, who designated primary care providers outside of the HCC, but who used other HCC services at least once during the 3-year study period; and 3) HCC nonusers who neither designated HCC as their provider nor used the HCC at all during the study period. Any employee or dependent who changed groups in the 3-year period was excluded from the analysis. The proportion of cases in this category was small and had no appreciable effect on study results.


For the current study, data from SAS human resources databases (for demographics, type of position, etc); insurance claims databases (for external health encounters and claim costs); and the HCC database (for internal encounters) were linked by SAS personnel. During the study period, SAS offered enrollment in either an indemnity plan or a PPO plan, each administered by a different third-party administrator (TPA): a Blue Cross Blue Shield (BCBS) PPO or a United Medical Resources (UMR) indemnity plan using the same plan design. These TPAs paid health claims submitted directly to them with funds provided by SAS based on projected spending and claims handling/administrative costs. Because the proportion of individuals who had selected UMR varied greatly across the 3 groups, all utilization was standardized and monetized using 2009 payment rates from BCBS North Carolina. Thus, observed “simulated” spending differences across groups are due to utilization rather than to “price” differences.

Random identification numbers were assigned to each plan member, and the data set was de-identified prior to analysis. The study was approved by the Duke University Medical Center Institutional Review Board.

Statistical Analysis

Preliminary analysis revealed the nonnormal distribution of our primary outcome variables; we therefore used the logarithmic transformation of each variable in the regression model. The SAS/GLIMMIX procedure was used to fit separate models for each outcome (annual monetized use and specific healthcare services use), examining the differences in the outcome measure across the 3 groups adjusted for the effects of covariates. The procedure allows for fitting statistical models to data with nonconstant variability and when the response variable is not necessarily normally distributed (SAS Institute 2012). Covariates included in the model are demographic characteristics (ie, age, gender, race/ethnicity); employee characteristics (ie, duration of SAS employment, full-time worker status, job classification, earnings quintile, and number of dependents); the individual’s health status that measures the presence or absence of 5 chronic diseases (hypertension, heart disease, type 1 or 2 diabetes mellitus, asthma, and stroke, as well as total number of aforementioned chronic diseases); and study year. The 5 chronic diseases were selected because of their high public health impact in terms of frequent occurrence, severity, and chronicity. Differences in all outcome variables among groups were estimated using adjusted means, with P values adjusted for multiple comparisons using the Tukey-Kramer method.

The primary outcome of interest was annual monetized use, defined here as the sum of all utilization reported in actual health claims. Utilization was monetized using standardized pricing for each unit of service. Annual monetized use data are derived from actual health plan claims for employees and their dependents paid by SAS during the period from January 1, 2006, to December 31, 2008. We also investigated more specific health services use: 1) inpatient utilization (including hospital and post acute nursing home stays); 2) outpatient utilization (including preventive and acute/chronic encounters); 3) inpatient expenses; 4) labor and delivery expenses; 5) emergency department costs; 6) ambulatory care expenses; and 7) prescription drug use. Current Procedure Terminology-4 codes were used to divide ambulatory encounters into preventive and acute/chronic care.


Sample Characteristics

Characteristics of the 3 comparison groups are provided in Table 1. The average age of employees was about 45 in all 3 groups, whereas among dependents, there was a notable difference in age among HCC major users (27.6 years) and HCC casual users (19.8 years) or nonusers (21.3 years). There were substantial gender differences across the employee groups, ranging from 51% female among HCC major users, to only 28% among nonusers (P <.001), with much smaller gender differences in the dependent groups. Differences in race/ethnicity among the groups were relatively small, but there were sizeable differences in employment duration with SAS. The groups did not differ significantly in representation from various job classes (ie, managerial versus sales). The share of workers in the highest income quintile was more than twice as large for nonusers (38.9%) than HCC major users (18.9%; P <.001); this differential was less pronounced among dependents (34.3% vs 22.5%) but remained statistically significant (P <.001). Finally, employees in the nonuser group were somewhat sicker than employees in the other 2 groups, having both a higher number of chronic diseases and a higher likelihood of suffering from at least 1 of the chronic conditions examined. In contrast, dependents in the HCC major users were somewhat sicker than dependents in the other 2 groups using the same metrics.

Health Services Use by Employees

In both adjusted and unadjusted analyses, the number of annual external outpatient encounters was lower among the HCC major users than among the other 2 groups (P <.001)—a pattern repeated for acute care (P <.001) and preventive care encounters (P <.001). The vast majority of those HCC encounters for HCC major users (7.5 of the 7.9 per year) were acute/chronic encounters. The average number of annual hospital admissions was slightly lower for HCC casual users compared with HCC major and nonusers (Table 2a); however, there were no statistically significant differences across the 3 groups.

Standardized Claim Costs for Employees

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