Employer-Led Efforts to Improve the Value of Health Spending

March 14, 2016
Megan McHugh, PhD

Claude R. Maechling, PhD

Dorothy D. Dunlop, PhD

Linda O’Dwyer, MSLIS, MA

Dustin D. French, PhD

Rahul K. Khare, MD, MS

Anna P. Nannicelli, MPH, MSW

Alexandra R. Brown, BA


The American Journal of Accountable Care, March 2016, Volume 4, Issue 1

Findings from a systematic review show that employer-led efforts to date have produced few promising strategies for improving the value of health spending.


Objectives: Employers have a major stake in improving the value of health spending. Our objective was to assess existing evidence on the impact of employer-led efforts to lower costs and improve or maintain quality.

Study Design: Systematic literature review.

Methods: We searched MEDLINE, Business Source Premier, PAIS, ABI Inform Global, and the Grey Literature Report for articles, published through June 2015, that evaluated the impact of employer-led strategies to lower costs and improve or maintain healthcare quality or health outcomes. We limited our focus to randomized controlled trials and longitudinal observational studies with concurrent control groups. Data on the employers, interventions, research designs, and outcomes were extracted.

Results: Twelve articles met our inclusion criteria. The most common interventions were medication therapy management (4 articles), reductions in prescription drug co-payments for certain chronic conditions (3 articles), and managed care for physical and/or mental health (2 articles). Four studies reported cost reductions for employers. Among those 4 studies, 2—both medication therapy management interventions—also showed improvement on quality measures.

Conclusions: There are few studies with rigorous designs that have evaluated employer-led efforts to improve the value of health spending. Despite employers’ interest in improving the value of health spending, their efforts to date have produced few promising strategies for use by purchasers in the public or private sectors.

There is ample evidence showing the United States spends nearly twice as much per capita on healthcare as other industrialized countries, yet health outcomes in the United States are no better.1-3 As a result, many researchers, policy makers, and healthcare leaders conclude that the value of health spending in the United States is low.4 In an effort to improve the value of health spending, the CMS has initiated a number of programs that base provider reimbursement, at least in part, on performance measures.5,6 However, early data suggest that these value-based purchasing programs in the public sector have shown little or no success.7-9

Private sector efforts to improve the value of healthcare have received less attention. As the largest purchasers of healthcare, employers have a major stake in improving the value of health spending.10,11 Their interest in supporting high-value healthcare stems from a desire to keep the costs of employee benefits low, as well as the need to cultivate a healthy workforce with limited absenteeism, high productivity, and longevity. As a result, employers—particularly, large self-insured employers—have a tremendous incentive to adopt policies and implement care models aimed at improving the value of healthcare.

A number of articles in the academic and lay press have described employers’ efforts to reduce costs, which range from simple workplace wellness programs to more complex efforts designed to alter local delivery systems.12-14 Previous reviews have examined the impact of wellness programs and reductions in co-payments for prescription drugs.15-17 However, to date, there has not been a comprehensive assessment of employers’ efforts to improve the value of health spending. As a result, employers may be making benefit decisions with relatively limited evidence, and lessons for improving the value of health spending from the private sector may not be reaching public purchasers. Our purpose was to systematically review the evidence of the impact of employer-led efforts to improve the value of health spending.


Inclusion and Exclusion Criteria

We limited our review to articles that empirically tested the impact of an employer-led intervention on the value of health spending—value of health spending refers to quality in relation to the cost of care.18,19 Value can increase by improving quality of services while keeping costs constant, or by lowering costs and achieving the same level of quality. Although there is currently no standard approach for measuring the value of health spending,20,21 there is general agreement that costs and quality should be assessed through separate outcome measures.19 Therefore, we limited our search to articles that contained both cost and quality outcome measures. Cost assessments could include measures related to financial outlays (eg, lower premiums), utilization (eg, hospital admissions), or productivity (eg, absenteeism). Quality assessments could include process measures (eg, receipt of recommended care), measures related to adherence (eg, prescriptions filled), measures related to health outcomes and health status (eg, health risk group), and measures of patient experience and satisfaction.

We excluded articles where the only employer-led intervention was a wellness initiative—defined as a program that supports employees in understanding their health risks and adopting healthy behaviors to decrease health risk.15 Examples of wellness interventions include health risk assessments and screenings, lifestyle management, and behavioral health programs. These articles were excluded because other systematic reviews have described the impact of employer-led wellness interventions.15,17 We excluded articles that did not have a control group, as well as articles that did not control for confounding variables, either by design (eg, randomized controlled trials, propensity score matching) or statistical methods (eg, inclusion of control variables for age, race, sex). Therefore, our articles were limited to randomized controlled trials and longitudinal observational studies with concurrent control groups. We also excluded editorials, meeting abstracts, studies not published as full reports, articles focused on interventions conducted outside the United States, and articles focused on interventions mandated by state or federal law (eg, mental health parity).

Study Identification and Selection

In June 2015, a research librarian (LO) conducted systematic searches in PubMed MEDLINE (1940s-2015), Business Source Premier (1886-2015), Public Affairs Information Service — PAIS (1915-2015), and ABI Inform Global (1971-2015), with no date or language limits, using search terms for employers, costs, and quality. The searches combined permutations of the following terms using the Boolean operators AND and OR: health benefit plans, employer-sponsored, employer-based, self-insured, self-insurance, costs, utilization, absenteeism, sick days, hospitalization, admission, emergency, health status, health behavior, satisfaction, as well as a number of conditions of interest. The Grey Literature Report was also searched. See the eAppendix (available at www.ajmc.com) for a complete list of the search strategies for each database.

Two reviewers (MM and CRM) independently screened the titles and abstracts of each unique article for concordance with the inclusion and exclusion criteria. When both reviewers identified discordance, studies were discarded. The full text of the remaining articles were retrieved for further critical appraisal regarding eligibility by the 2 reviewers, and again, studies were discarded when both reviewers identified discordance with the inclusion and exclusion criteria.

Data Extraction

Each article selected for inclusion was independently reviewed by 2 reviewers who were responsible for extracting several data elements following a standardized extraction form. Data elements included the industry, size, and location of the employer; characteristics of the intervention; study design; and cost and quality outcomes. Many studies included multiple measures of cost and quality. Because we were most interested in the financial implications to the employers, we reported on the changes in costs to employers in our results; we only reported changes in utilization if no cost data were provided. All quality measures included in the studies are reported in our results. Finally, the reviewers identified additional candidate studies by reviewing the reference lists of the included articles.


The literature search produced 925 unique candidate articles, of which 58 were selected for full text review (Figure). After full text review, an additional 47 articles were excluded, with the most common reasons being weak study design (ie, no control group or no controls for confounding variables), absences of a cost or quality outcome measure, and the intervention was not employer-led. Eleven articles satisfied all criteria, and 1 additional article was added after reviewing the reference lists. In all, 12 articles were included in the review.

Characteristics of the Employers and Interventions

Of the 12 studies, 5 provided information on the number of employees or covered lives (employees and dependents). All 5 were large organizations, ranging from just over 13,000 total covered lives to just over 42,000, including dependents aged under 18 years. Seven studies reported the location of the organization’s headquarters or intervention site; there was considerable diversity across the United States. (Table 1). All but 2 studies reported information about the employer’s industry. Four employers were private, for-profit organizations, 3 were universities, and 3 were government or military.

The interventions varied substantially. Four employers introduced medication therapy management (MTM) programs where patients met one-on-one with a pharmacist and received individualized services focused on reconciling medication regimens, preventing adverse events, identifying significant medication interactions and missing essential therapies, and improving adherence.22-25 Three employers reduced prescription drug co-payments for certain chronic conditions with the goal of improving adherence and health, and reducing more costly health services and overall health spending.26-28 Conversely, another employer increased prescription drug co-payments for brand-name drugs as an incentive to steer patients toward less expensive drugs.29 Two employers introduced managed care, which encompassed a set of tools (eg, co-payments, utilization management) to improve coordination and efficiency of care.30,31 Another employer changed its reimbursement arrangements with primary care physicians, offering a capitated rate instead of fee-for-service, in an effort to get physicians to be more cost-conscious32; the savings generated from capitation were shared with participating physicians. Finally, one employer introduced a high-deductible health plan, with the idea that greater exposure to the direct cost of their care would make employees more cost- and health-conscious.33

Intervention Impacts

Table 2 provides a detailed description of the statistically significant (P <.05) outcomes from each study, organized by intervention type. Of the 4 studies reporting on MTM interventions, 2 reported lower medical costs and total healthcare costs for the employer.23,25 Of those 2 studies, one reported participants had higher medication possession ratios, a measure of adherence, and the other reported an increase in the percent of participants who achieved goals for blood pressure and body mass index, and clinical improvements in the stages of hypertension. One of the MTM studies showing no change in employer spending was the only randomized controlled trial in our sample.24

Both of the managed care interventions resulted in higher costs to the employers,30,31 though unlike many of the other studies, the intervention costs were included in the analyses. In both studies, participants reported high satisfaction and better access to care. None of the 3 studies evaluating the reduced pharmacy drug co-payments for certain chronic conditions reported savings to employers, and improvements in quality measures were observed in 2 of the studies.27,28 However, the increased brand-name drug co-payment intervention resulted in lower drug costs for the employer and no change in use of drugs.29

The study investigating capitation for primary care reported that the intervention resulted in lower charges and no change in blood pressure control.32 Finally, the study evaluating implementation of the high-deductible health plan showed mixed results regarding utilization, and although cancer screenings initially declined, there was no difference between the intervention and control groups after 4 years.33


The results of our systematic review show few efforts by employers to improve the value of health spending, evaluate the results, and publish their findings. This is not surprising, however, given that health benefit design and reimbursement is not central to the core business of most employers. Even if employers initiate interventions aimed at improving value, they may not have the desire nor the resources to conduct methodologically rigorous evaluations and document the findings.

The limited number of articles meeting our inclusion criteria may also reflect a lack of emphasis among employers or evaluators on both the cost and quality implications of employer-led interventions. A number of news reports, employer surveys, and research studies have shown that employers are experimenting with different health benefit designs34-38; however, many evaluations of these efforts were excluded from our review because they did not include both cost and quality outcomes in their analyses.26,35 Given employers’ long-standing and important role as healthcare purchasers, it is unfortunate that few lessons about improving value can be drawn from this sector. Further, employers experimenting with different ways to manage their health benefits are largely doing so without the benefit of strong evidence.

The most promising findings from our review relate to the MTM interventions. Two of the 4 studies reported cost savings and some indication of improved or maintained quality. MTM programs may be relatively easy for employers to implement since they do not require changes in contracts with providers (unlike initiating managed care or capitated payments) or changes to bargaining agreements with union employees (unlike changing co-payments). Although there is a cost associated with adding MTM services (eg, hiring a pharmacist),39 both studies reported a positive return on investment. Still, our findings should be viewed with some caution. The longest follow-up among the studies was 1 year, so it is unclear whether the savings and improvements were maintained in the medium or long term.

Implications for Future Research

Our results align with findings from a previous systematic review of studies evaluating the effects of co-payment reductions: improved quality but no cost savings to employers.16 The limited evidence about employer-led strategies to improve the value of health spending highlights 2 opportunities for future work. First, there is an opportunity for further employer-led experimentation with interventions to improve the value of their health spending. The emphasis on value-driven purchasing, to date, has largely stemmed from public purchasers, for example, the Centers for Medicare and Medicaid Innovation’s demonstration projects within the Medicare and Medicaid programs.40,41

Although many lessons from those demonstration projects may be applicable to the private sector, the Medicare and Medicaid programs support a different patient population than employers. Consequently, experimentation in both sectors is needed.

Second, there is potentially an opportunity for employer-researcher partnerships to help with evaluations of employer-led interventions. Researchers may help employers identify interventions, evaluate interventions, and bridge the gap between what is known and what is practiced. For example, previous reviews have shown that the impact of workplace wellness programs on cost and behavior changes is mixed at best,17,42 yet over half of large employers use them at a cost of almost $600 per employee per year.43 Researchers may help to bridge this divide between research evidence and decision making.


Our systematic review has some limitations. First, our search results may be subject to publication bias, as successful interventions are more likely to be published.44 Second, it is possible that employers are implementing and evaluating interventions to improve the value of their health spending, but their internal reports are not circulated in the public domain. Third, it is difficult to generalize our conclusions since the interventions were diverse, cost and quality outcomes were not uniformly operationalized, and effect sizes were not consistently reported.


Our systematic review found few rigorous evaluations of employer-led efforts to improve the value of healthcare spending. As a result, there are few evidence-based strategies for employers to consider to improve value of their spending. More employer-led experimentation, a greater focus on quality outcomes, and employer-researcher partnerships may help to expand the evidence base for interventions that improve the value of healthcare spending.

Author Affiliations: Branstad Family Foundation (CRM), Chicago, IL; Center for Healthcare Studies (MM, DDD, DDF, RKK, APN, ARB, JLH), Northwestern University, Feinberg School of Medicine (LO), Chicago, IL.

Source of Funding: The manuscript was developed with support from the Branstad Family Foundation.

Author Disclosures: Dr Khare, Ms Nannicelli, and Ms Brown were all affiliated with the Center for Healthcare Studies at Northwestern University, Feinberg School of Medicine, during completion of the study. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (MM, DDD, DDF, RKK, JLH); acquisition of data (MM, CRM, LO, RKK, ARB, APN, JLH); analysis and interpretation of data (MM, CRM, DDD, DDF); drafting of the manuscript (MM, DDF, JLH); critical revision of the manuscript for important intellectual content (MM, CRM, DDD, APN, JLH); provision of study materials or patients (ARB, APN); obtaining funding (JLH); administrative, technical, or logistic support (DDD, RKK, ARB, APN); and supervision (JLH).

Send correspondence to: Megan McHugh, PhD, Center for Healthcare Studies, 633 N. St. Clair, 20th Fl, Chicago IL 60657. E-mail: megan-mchugh@northwestern.edu.


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