German Veselovskiy, MPP

Recently, researchers and policy makers have demonstrated growing interest in differences in payments across sites of care for the same healthcare service, such as in a hospital outpatient department (HOPD) versus a physician office (PO). Our objective was to examine the price differential for individuals with employer-sponsored insurance by site of care for 7 commonly performed services at the national and regional level. 

We analyzed 2008 to 2013 claims data from Truven Health MarketScan Commercial Claims and Encounters Database, containing administrative data for 44 to 53 million individuals covered by employer-sponsored health insurance. 

We selected 7 services based on total payments from different clinical categories—categories in which differences in clinical quality and patient morbidity are less likely to be sources of the price differential. We calculated payment amounts at the visit level for each healthcare service by site of care, then calculated the price differential by site of care as a ratio of average HOPD price to the average PO price or average ambulatory surgery center price for the same service.

Across all 7 services, prices at a HOPD were statistically significantly higher than payments to a PO, ranging in 2013 from 21% more for an office visit to 258% more for chest radiography. The increase in the price differentials, combined with a shift in volume in favor of hospital outpatient departments, was associated with a 44% increase in total spending between 2008 and 2013.

Our study shows that price differentials by site of care exist at a national level, and that they are increasing over time.

	Our analysis showed that for individuals with employer-sponsored insurance, prices for services performed at hospital outpatient departments were higher than prices for the same services at other care settings (ie, physician offices and/or ambulatory surgical centers). 

		Across all 7 commonly performed services analyzed, prices at hospital outpatient departments were higher than prices at physician offices; they ranged from 21% more for an office visit to 258% more for chest radiography in 2013. 

		The magnitude of price differential increased over the study time period (2008-2013). 

		The increase in the price differential for the 7 services, combined with a shift in volume in favor of hospital outpatient departments, was associated with a 44% increase in total spending between 2008 and 2013.

The role of healthcare prices as a key factor in driving total health spending in the United States, compared with other developed countries, is well documented.

 Characterizing variability in prices for different healthcare services, and that variability’s impact on total spending, has been of interest to researchers and policy makers. However, most research to date has focused on geographic variation in prices for specific healthcare services within the United States. These studies have found wide hospital-level and regional variation in prices for specific healthcare services, such as vaginal births and knee and hip replacements.

More recently, the focus has turned to characterizing price variations for the same healthcare service by site of care, (eg, hospital outpatient department [HOPD] and physician office [PO]). The Medicare Payment Advisory Commission (MedPAC) recently analyzed payments for services rendered in HOPDs compared with payments for the same services performed in independent physician practices. For example, for patients with similar risks and characteristics, payments in HOPD exceeded payments in PO by 19% for level II cardiac imaging, and by 141% for a level II echocardiogram.

Evidence of price differences across sites of care in the commercially insured population is limited; previous analysis has focused on either a single year of data or specific subpopulations. Analysis of commercial claims data from 2005 for 16 groups of services found the average HOPD-to-PO price ratio was 3.5.

 Based on data from 4 health plans, a 34% price differential was found between HOPDs and POs for cancer episodes with the same set of services in an episode, after adjusting for patient severity.

A more recent analysis of prices for 9 healthcare services, based on insurance claims for a subpopulation of active and retired autoworkers and their dependents, found a 4-fold variation in prices by site of care, with HOPD prices being consistently higher than those of POs.

 Similarly, researchers assessing the impact of Medicare fee cuts on integration of cardiologists with hospitals found differences in prices by site of care for select cardiology-related services.

 We are unaware of studies to date that have focused on national estimates of price differences by site of care and the implications of these differences for total US healthcare spending.

The objectives of our study were to: a) develop national estimates of price differences by site of care for select services, b) examine temporal trends in such price differences, and c) analyze implications for price differences on total and consumer out-of-pocket (OOP) spending.

We identified the top 100 Current Procedural Terminology (CPT) codes—the code set of medical procedures and services maintained by the American Medical Association&mdash;for calendar year 2011, then classified them into broad clinical categories, such as office visits, imaging services, outpatient procedures, laboratory services, etc.

We used the following set of criteria to select 7 services for our study: a) representation from different clinical categories, b) services with the highest total payments within a clinical category, c) sufficient volume of visits for the service by site of care to enable reliable comparisons of price differential (at least 20,000 visits at each site of care), and d) services in which differences in clinical quality and patient morbidity are less likely to be the source of the price differential. Based on these criteria, we selected CPT codes from the clinical categories of office visits, imaging services, and outpatient procedures. Specifically, we chose CPT codes 99213 (office visit, established patient, 15 minutes) and 99215 (office visit, established patient, 40 minutes) for office visits; 70450 (computed tomography [CT] scan), 72148 (magnetic resonance imaging [MRI]), and 71020 (chest radiography) for imaging services; and, for procedures, 43239 (upper gastrointestinal endoscopy) and 45378 (colonoscopy).

We defined a healthcare service as synonymous with a CPT code. A visit is defined as a provision of a healthcare service on a specific date. We calculated payment amounts at the visit level for each healthcare service by site of care and included both the facility and professional payments where applicable (eg, imaging services). The total payment included the portion paid by the insurer and the consumer OOP payment (ie, the allowed amount for the visit at a particular site of care). This allowed amount was defined as the price per visit. We defined the price differential by site of care to be the ratio of average HOPD price for a service to the average price of that same service in a PO or an ambulatory surgery center (ASC), as applicable.

To ensure comparability of visits across the different sites of care, we used the following criteria for inclusion based on claims for these visits: a) visits paid in-network and on a fee-for-service basis; b) for imaging services and outpatient procedures, only visits with both technical and professional claims; and c) visits for endoscopy and colonoscopy in which these were the only procedures performed during the visit. To minimize the effect of outlier payments on price differential, we excluded visits using the interquartile range method for outliers.

The data source is the Truven Health MarketScan Commercial Claims and Encounters Database, 2008 to 2013. The Market Scan data contain administrative data for 44 to 53 million individuals (depending on the study year) covered by employer-sponsored health insurance. We used the annual enrollment file and outpatient services file, which include information on coverage dates, service dates, age, sex,  total dollars paid to providers, procedure codes, procedure modifier codes, and the place of service where the procedure was performed.

We calculated the average price at the visit level for each of the 7 services by site of care and by year, and we used weights derived from the Household Component of the Medical Expenditure Panel Survey and provided by Truven Health Analytics to generate national estimates of price differentials. For procedures, we calculated Charlson comorbidity index (CCI) scores to assess morbidity of patients by site of care.

 Specifically, we compared average CCI scores for patients, as well as percent of patients with CCI scores of 0, 1, and >1, by site of care. Similar to researchers at MedPAC, we did not risk adjust payments for office visits and imaging services, because patient morbidity is less likely to be an issue for these services.

We also conducted statistical tests of significance using the 2-sample 

 test to assess the probability that differences in the average price by site of care are random. To examine trends in price differentials, we calculated an index of the price differential for each clinical category: office visits, imaging services, and outpatient procedures. The index was derived using as weights the proportion of visits for each service by site of care.

Finally, to calculate additional spending due to price differential for each service, we multiplied the number of visits occurring in an HOPD by the difference between the average price paid for this service in an HOPD and the average price paid for the same service in a PO. We then summed these amounts across all 7 services to arrive at the total national additional spending due to price differential by site of care.

Comparisons of Price Differential at the Service Level

 shows the ratio of average HOPD price to average PO price for office visits and imaging services, and additionally, for the colonoscopies and endoscopies, the ratio of average HOPD price to average ASC price. Between 2008 and 2013, and across all services, HOPD prices were statistically significantly different (

 <.001) and higher than prices at PO or ASC (where applicable).

The site-of-care price differential for imaging and procedures was substantially higher when compared with office visits. Average HOPD prices were 2 to 3 times more than average prices at PO for the same service. For procedures, these observed differences do not appear to be caused by differences in patient morbidity by site of care. Patient morbidity rates, as measured by the CCI, were similar across sites of care across all years in our study sample, and higher HOPD to PO and ASC pricing was observed among patients with similar CCI scores (see 

 for CCI data for 2013 [eAppendices available at 

]). Distribution of patients’ gender and age were also similar for the analyzed services across different sites of care (see eAppendix 2 for the 2013 data).

Trends in Price Differential and Volume of Services by Site of Care (2008-2013)

We found that price differential by site of care increased over time. The 

 shows temporal trends in the index of price differential by clinical category. Between 2008 and 2013, the price differential index increased by 10% for office visits, 15% for procedures, and 17% for imaging services. Within each clinical category, the price differential for some services increased at a faster rate than others. For example, the price differential of chest radiography increased by 20% from 2008 to 2013, while the price differential for CT scan of head remained largely unchanged (decrease of less than 1%).

In addition to examining temporal trends in the price differential by site of care, we also analyzed changes in the proportion of visits occurring at each site of care between the years 2008 and 2013. In all years, the vast majority of office visits occurred in a PO. We did, however, observe a shift in the volume of services for CPT code 99215 (office visit, established patient, 40 minutes) in favor of hospital outpatient departments, from 5% of visits in 2008 to 8% in 2013 (

). All imaging services also showed a volume shift from a PO to an HOPD between 2008 and 2013. This shift was most pronounced for MRI, where the proportion of visits in HOPDs increased from 32% in 2008 to 37% in 2013.

Price Differential and Out-of-Pocket Spending

 shows the differential in 2013 average individual OOP spending for a service received at an HOPD versus a PO. Across product types, such as health maintenance organization, preferred provider organization, or consumer-directed health plan, on average, an individual receiving care in an HOPD paid between 1.06 and 2.94 times what they would have paid in a PO for that same service.

National Estimates of Additional Spending Due to Price Differential

We found that the price differential between HOPD and PO was associated with $1.3 billion more in healthcare spending for all 7 services in 2008 (adjusted to 2013 dollars using the healthcare consumer price index) and $1.9 billion in 2013—a 44% increase in total spending.

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Between 2009 and 2013, for individuals with employer-sponsored insurance, prices for services performed at hospital outpatient departments were higher than in physician offices, and the magnitude of price differential increased over time.

National Estimates of Price Variation by Site of Care

Policy makers have growing interest in price transparency and in the kinds of tools available to consumers. Health plans have implemented price estimator tools that make provider pricing information available to members; however, systematic data on prevalence and characteristics of such tools are limited. The purpose of this study was to describe the characteristics of price estimator tools offered by health plans to their members and to identify potential trends, challenges, and opportunities for advancing the utility of these tools.

Between 2014 and 2015, we conducted a national Web-based survey of health plans with commercial enrollment (100 plans, 43% response rate). Descriptive analyses were conducted using survey data. 

Health plan members have access to a variety of price estimator tool capabilities for commonly used procedures. These tools take into account member characteristics, including member zip code and benefit design. Despite outreach to members, however, challenges remain with respect to member uptake of such tools. 

Our study found that health plans share price and provider performance data with their members. 

	We conducted a national survey of health plans to examine characteristics of provider price estimator tools available to the commercially insured population. Health plans offer these tools to their enrollees and take into account member characteristics such as zip code and benefit design. 

		Price estimates are available for commonly used services, including outpatient surgery and radiology. 

		Plans use various approaches, including digital and social marketing, to increase member use of tools. 

		Early evidence shows the positive impact of such tools on cost savings. Additional research is needed to increase the use of these tools and broaden their impact.

In an effort to slow the rising costs of healthcare, consumer groups, state governments, and health plans have called for greater price transparency in the healthcare market.

 Policy makers and researchers have posited that increasing price transparency will afford consumers the opportunity to comparison-shop among providers, which could result in higher-cost providers lowering their prices to improve value.

 As enrollment in high-deductible health plans has grown, consumers in these plans have a greater financial incentive to compare prices across providers because they have higher out-of-pocket obligations.

 Even consumers not in high-deductible health plans may now participate in benefit designs offering incentives and opportunities to select higher quality and lower cost (ie, high-value) providers.

 Consumers want to understand their out-of-pocket expenses for specific services for a given provider, as well as the costs for a complete episode of care.

 To help meet consumer needs, health plans have implemented tools that allow consumers to compare and select providers based on providers’ quality performance and prices for specific healthcare services. Using such tools can benefit consumers in terms of lowering their out-of-pocket costs and selecting higher-quality providers.

Recent evidence shows that availability of price information can impact consumer behavior and promote informed decision making. In a study of 1421 employees, researchers found that presenting easy-to-understand, high-quality information alongside pricing estimates increased the likelihood of an individual choosing a high-value provider.

 Increased likelihood of visiting a new provider, as well as lower payments for clinical care, have also been attributed to accessibility of price estimates.

 Much attention has been given to the topic of price transparency; however, studies to date have primarily focused on price information made available through state requirements for mandatory reporting.

 Meanwhile, in the private sector, health plans have begun to offer provider-level pricing information to their members using Web-based price estimator tools.

 Although some information is available, we are unaware of any studies that have systematically collected data on the characteristics of health plan price estimators.

 The purpose of this exploratory study was to describe the characteristics of price estimator tools offered by health plans to their members and to identify potential trends, challenges, and opportunities for advancing the utility of these tools.

For the purposes of this study, “price estimator tools” refer to tools that allow consumers to obtain estimates of prices associated with specific healthcare services that could be either specific to a provider or based on geography.

Data for this study were collected using a Web-based survey instrument. To develop the survey instrument, we conducted a targeted literature review of health plan price estimator tools, reviewed health plan price estimator tools that were publicly available, and conducted preliminary interviews with representatives of 4 plans to get a broad understanding of these tools. We pilot-tested the survey with these same 4 health plans and conducted telephone interviews with these plans to get additional feedback on the survey.

Final survey questions focused on the following 7 aspects of health plan price estimator tools: 1) core capabilities and characteristics taken into account, 2) data used in price estimator tools, 3) display of price estimates, 4) services for which estimates may be obtained, 5) provider information, 6) member engagement, and 7) outcomes and challenges. The questions were a mixture of open-ended and binary yes or no responses. For open-ended questions, we asked plan representatives to elaborate on characteristics pertaining to their price estimator tool that were not included as a response option on binary yes or no questions. Twenty-two binary questions had corresponding open-ended questions to which the plan representatives could respond.

We invited 106 health plans that met the following criteria: a) listed as a member of America's Health Insurance Plans in 2014, and b) offered products in the commercial insurance market. Of the 106 plans, 4 plans were not eligible to participate because they no longer offered commercial products at the time of the survey, and 2 had recently been acquired by another health plan. Using a key informant approach, we e-mailed invitations to the chief medical officers of the remaining 100 health plans, who then shared the survey with their teams, as appropriate. Data from this survey were collected in 2 phases between April 2014 and July 2015.

To be included in our analyses, plans had to have a price estimator tool available to their members. For the analyses, we characterized health plans by total size of enrollment (using quintiles), time since their price estimator tool became available (<1 year, 1-3 years, >3 years), and vendor type for their tool (health plan, third-party, or a combination of both). We examined the overall frequencies and Fisher’s exact tests for each price estimator tool characteristic, stratified by health plan characteristics (not all results are reported). Following the calculation of frequencies, we compiled and summarized all open-ended responses. Any plans that did not provide a price estimator tool were excluded from analyses.

A total of 43 plans responded to the survey, resulting in a 43% response rate. The characteristics of the responding plans can be found in the 

). Of the 43 plans that responded during both phases of data collection, 11 did not provide a price estimator tool to their members, although 4 of these 11 intended to provide a tool within 12 to 24 months. One plan of the 43 had made a tool available during our second phase of data collection in 2015, but did not provide updated responses to the survey. Our final analytic sample is thus composed of the remaining 31 plans that provided price estimator tools to their members.

The 31 plans included in the analyses account for 140.8 million commercial enrollees, corresponding to 75.9% of the total national commercial enrollment for 2014.

 Thirty-nine percent of these plans launched their price estimator tools more than 3 years ago, and just under half of the 31 plans (45%) offered multiple tools to their members—both provided by the plan directly and through arrangements with third-party vendors.

Capabilities of health plan price estimator tools. 

Our results indicated that health plan members have access to a variety of price estimator tool capabilities (

). Ninety-four percent of plans allowed for provider comparison shopping and about 58% displayed estimates for prescription drug costs. In generating price estimates, plans account for various member characteristics depending on the type of service being estimated. For instance, a member’s zip code (94%), product type (77%), and benefit design (77%) are commonly used characteristics for provider comparison shopping. In contrast, about one-third of plans account for member zip code (35%), product type (29%), and benefit design (29%) for cost estimates of prescription drugs (Table 1).

Services for which estimates may be obtained. 

Eighty percent of health plans choose which services to provide estimates for based on the most commonly used procedures and services. Of the most commonly used procedures, we found that nearly all of the plans provided estimates for elective outpatient surgery (97%), radiology services (eg, x-rays, computed tomography scans) (97%), and inpatient surgical services (97%) (

A majority of health plans also provided estimates for physician services (71%) and services associated with select chronic conditions (61%), such as glycated hemoglobin testing for patients with diabetes. Open-ended responses revealed that many members might also obtain estimates for preventive services, including wellness visits, preventive screenings, and behavioral health services. Less common, are estimates for services at retail/convenience clinics (32%), services provided in the emergency department (26%), and telemedicine (6%).

Data used to generate price estimates for the services primarily consisted of a health plan’s historical paid claims for a specific geographic area (55%), the health plan’s historical allowed rates (the maximum a health plan will pay an in-network provider for a service) for specific providers (52%), and a plan’s current negotiated rates (ie, the price negotiated between the health plan and the provider for a service) for specific providers (45%). These data are generally updated quarterly or semiannually (65%).

Health plans price estimator tools display a number of specific elements primarily for in-network providers, and members have the ability to compare prices for specific healthcare services across individual providers (68%). Seventy-one percent of plans also included price estimates for treatments at the individual provider level. Potential out-of-pocket costs that a member may incur are displayed by 90% of plans; such potential out-of-pocket costs could include co-pays, coinsurance, and the deductible for which the member is responsible. Fewer plans display information on reference-based pricing for services (13%), health savings account (HSA) balances (29%), and links to an outside HSA administrator (10%).

Alongside price estimates, plans share other information on providers, such as geographic location, performance data, designation as a Center of Excellence, etc (

). As shown in Table 2, the extent to which these additional pieces of provider information are fully integrated into the price estimator tool varies across plans.

The most common ways to direct members to use a price estimator tool are through messaging on a health plan portal (97%), outreach through employers (71%), digital communication—which includes e-mail, social media, and text messaging&mdash;(68%), and postal mail (58%) (

). Open-ended responses yielded additional details on innovative methods that plans are using to engage members; such methods include technological platforms like e-mail and text messaging, in which plans use alerts to prompt members’ awareness of “ways to save” on healthcare. Also technologically based are gamified programs like “Healthcare University,” in which members receive information through interactive videos and quizzes. Person-to-person communication, including the work of schedulers and financial counselors, is another way in which health plans engage members. On a larger scale, plans cite the implementation of social marketing campaigns to connect with members on price transparency.

Plans were also asked to identify features of their price estimator tool that members have found most useful. Estimates for out-of-pocket costs based on member benefits are recognized as one of the most useful features by the majority of plans (77%). Equally useful were the ability to compare prices for services across providers (77%) and having access to estimates for a wide range of services (68%) (Table 3).

Nearly half of the responding plans (45%) (

) had yet to formally evaluate outcomes from member use of price estimator tools, but they intended to in the near future. Those that had evaluated their price estimator tool reported increased use of lower-cost providers (19%), member out-of-pocket savings (16%), and employer cost savings (16%) (Table 4). The most common challenges reported were limited member uptake (58%) and lack of member awareness about the tool (58%) (Table 4).

Potential Relationship Between Key Features and Time Since the Tool Became Available

As part of our analysis, we wanted to understand if there were differences in tool characteristics given a health plan’s enrollment size, how long their tool has been available, and the type of tool vendor. Our results indicated a possible relationship between the length of time a tool has been available and the presence of specific tool features and challenges. An examination of this relationship can help to identify areas for additional research with a focus on understanding the complex implementation process of price estimator tools. To further examine this potential relationship, we calculated Fisher’s exact tests for tool features and challenges by time since the tool became available. Due to the exploratory nature of our study, we reported tool features and challenges, yielding a Fisher’s exact test significant at 

We observed the strongest relationships between time since the tool became available and estimation of physician services (

 <.03), displaying patient-related costs (

 <.05), and availability of delivery and postpartum service estimates (

 <.05), which indicated a significant difference in the likelihood of these elements being present in a tool given how long the tool has been available. Closely following in significance were limited member uptake (

 <.09), assistance provided by a nurse care manager (

 <.10), and displaying episode-of-care costs (

 <.14). Of the remaining features, we saw significance among availability of provider performance data (

 <.17), displaying estimates for prescription drugs (

 <.21), phone outreach by nurse care managers (

 <.18), availability of provider-level metrics (

As price estimator tools continue to evolve to meet the needs of consumers, the data that are displayed may affect the overall utility of these tools. Our results indicated that health plans are responding to consumer needs by providing price estimator tools that include information on out-of-pocket costs, with many of these price estimates taking into account individual benefit design.

 When price information is displayed without accompanying quality information, consumers potentially perceive higher price as being equivalent to higher quality. If consumers associate high price with high value, this does not lead to selection of high-value providers and may even deter consumers from seeking care altogether.

 Our study found that two-thirds of responding plans shared provider performance data with their members, with half of these plans integrating such data into their price estimator tool.

Despite providing price estimator tools that also include access to provider performance data, health plans in our study encountered challenges related to lack of member uptake. This finding coincides with the Catalyst for Payment Reform’s 2013 National Scorecard, which reported that 86% of plans provide cost information to members relative to co-pays and cost sharing, but only 2% of their members use these resources.

 Our results support the need for additional research on the appropriateness of outreach methods and how to better understand reasons for lack of engagement, including low health literacy and language barriers.

 A better understanding of these reasons can facilitate consumer uptake and help the evolution of these tools.

We also know from previous research that simply having access to a tool with such information does not increase the likelihood of using the tool, nor does it necessarily lead to lower costs.

 The way in which cost and quality data are visually displayed merits further exploration, as it impacts how well consumers are able to comprehend and use the information.

 Research suggests that quality data be presented with a clear format and descriptive labeling, and in minimal volume to not overwhelm consumers reviewing information.

First, with a response rate of 43%, these findings may not be fully generalizable to all health plans. However, we are comfortable with our findings since the plans included in our analysis account for 75.9% of total national commercial enrollment and, therefore, capture tool availability to a large proportion of commercial enrollees.

 Secondly, this study was not designed to draw conclusions on how tool characteristics impact cost outcomes or consumer behavior, but rather to describe the current characteristics and capabilities of health plan price estimator tools. These limitations notwithstanding, we believe our study contributes several interesting findings on the characteristics and capabilities of health plan price estimator tools.

Our study found that health plans provide price and provider performance data to their members. Additional research is needed to inform further development of these tools so they can better engage consumers, who can then make more informed and cost-effective decisions regarding their healthcare. 

 America’s Health Insurance Plans (AH, NB, GV), Washington, DC.

 The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

 Concept and design (AH, NB, GV); acquisition of data (AH, NB, GV); analysis and interpretation of data (AH, NB); drafting of the manuscript (AH, NB); critical revision of the manuscript for important intellectual content (AH, NB, GV); statistical analysis (NB); administrative, technical, or logistic support (AH, NB); and supervision (AH).

A national survey of health plans shows that price estimator tools available to commercial plan enrollees provide price information for a variety of services at the provider level.

Characterizing Health Plan Price Estimator Tools: Findings From a National Survey

Health insurance plans serve a critical role in public health emergencies, yet little has been published about their collective emergency preparedness practices and policies. We evaluated, on a national scale, the state of health insurance plans’ emergency preparedness and policies.

We queried members of America’s Health Insurance Plans, the national trade association representing the health insurance industry, about issues related to emergency preparedness issues: infrastructure, adaptability, connectedness, and best practices.

Of 137 health insurance plans queried, 63% responded, representing 190.6 million members and 81% of US plan enrollment. All respondents had emergency plans for business continuity, and most (85%) had infrastructure for emergency teams. Some health plans also have established benchmarks for preparedness (eg, response time). Regarding adaptability, 85% had protocols to extend claim filing time and 71% could temporarily suspend prior medical authorization rules. Regarding connectedness, many plans shared their contingency plans with health officials, but often cited challenges in identifying regulatory agency contacts. Some health insurance plans had specific policies for assisting individuals dependent on durable medical equipment or home healthcare. Many plans (60%) expressed interest in sharing best practices.

Health insurance plans are prioritizing emergency preparedness. We identified 6 policy modifications that health insurance plans could undertake to potentially improve healthcare system preparedness: establishing metrics and benchmarks for emergency preparedness; identifying disaster-specific policy modifications, enhancing stakeholder connectedness, considering digital strategies to enhance communication, improving support and access for special-needs individuals, and developing regular forums for knowledge exchange about emergency preparedness.

Health insurance plans are important stakeholders in the healthcare system and serve a unique role in public health emergencies. Prior systematic evaluations of how health insurance plans prepare and respond to these emergencies have not been reported, so we evaluated the preparedness of these key stakeholders. Responding plans represented 81% of health plan enrollment. We identified 6 modifications that plans could make to enhance healthcare system preparedness:

		Establish metrics and benchmarks for emergency preparedness plans and policies.

		Identify disaster-specific policy modifications.

		Enhance state, local, and federal stakeholder connectedness.

		Consider digital strategies to enhance communication.

		Improve support and access for special-needs individuals.

		Create regular forums for knowledge exchange about emergency preparedness.

Over the past 15 years, Americans have experienced multiple public health emergencies, including devastating natural disasters (eg, hurricanes, tornados, floods), environmental disasters (eg, the Gulf oil spill in 2010), bioterror incidents involving anthrax, the H1N1 pandemic, and mass casualty events that killed or injured scores of individuals.

 Additionally, as of August 2014, the World Health Organization declared the Ebola outbreak to be a public health emergency of international concern.

 The health and healthcare implications of these disasters have been quite varied. They have included the need to seek care in alternate locations due to destruction of communities or healthcare facilities, the loss of medicine or medical equipment, requirements for vaccines or other medical countermeasures, advanced trauma care, and care for the mental health sequelae of the disaster.

 While much has been reported about the preparedness and response of healthcare providers, far less has been published about those of health insurers.

 Public health emergencies can impact health insurance plans in multiple ways because of business disruptions, technology interruptions, or requests from patients and providers to deviate from normal coverage or payment policies so individuals can receive care and, subsequently, communities can recover.

Health insurance plans clearly have an established responsibility in the direct financing of healthcare, yet less attention has been paid to the unique role that health insurance plans fulfill in public health emergencies.

 Notably, the ways in which health insurance plans structure policies for beneficiaries before, during, and after disasters can significantly impact how individuals access and use healthcare services during disruptive events and their aftermath. A surge in demand for medical care during disaster events, for example, can send communities in search of nontraditional healthcare providers or alternate care facilities.

 Maintaining continuity of operations and information about available resources is an important responsibility for health insurance plans. To achieve this, health insurance plans need to be able to rapidly inform beneficiaries of their level of coverage and, in some cases, relax benefit restrictions or create new emergency plans.

The speed at which a health insurance plan can fulfill these critical responsibilities is, in part, contingent upon their disaster-management infrastructure and resources. Following Hurricane Katrina in 2005, America’s Health Insurance Plans (AHIP), the national trade association for the industry, convened its Readiness Task Force to identify strategies that health insurance plans use in disasters. A resulting white paper outlined the definition of a disaster, providing sample disaster plans and best-practice case studies of business models and policies.

However, we are unaware of any systematic examination of how health insurance plans across the nation prepare for or respond to public health emergencies.

As significant emergency events with broad impacts on health are currently in progress (eg, the Ebola epidemic)

 and will inevitably occur on a continuing basis, the study’s aim was to better understand the current state of preparedness of health insurance plans and to identify health insurance industry best practices for public health emergencies.

We surveyed health insurance plans across the United States to learn more about their preparedness and response policies and practices.

We surveyed all health insurance plans that were members of AHIP, a national trade association whose members provide health and supplemental benefits through employer-sponsored coverage, the individual insurance market, and public programs (eg, Medicare and Medicaid) to more than 200 million Americans. We defined health insurance plans as companies providing a risk-based, primary care health insurance product based on a regional provider network.

We developed survey content from a published report of the AHIP Readiness Task Force,

 and input from emergency preparedness experts, representatives of health plans, and officials at various levels of government. The survey (eAppendix A, available at www.ajmc.com) focused on 4 areas

: infrastructure (eg, existing emergency plans, metrics to evaluate these plans), adaptability (eg, events and triggers which might lead to an alteration of services, approaches to tracking and monitoring data, members with special needs), connectedness (eg, communication of plans to members and employees, ability to maintain up-to-date contact lists of partners, participation in collaborative exercises), and best practices/lessons learned.

We used information from the 2012 Directory of Health Plans, published by Atlantic Information Services, to determine each health insurance plan’s size, type of product, and area of operation. We categorized health insurance plans by size as follows: national (5 million or more enrollees), large (1 million to <5 million enrollees), medium (250,000 to <1 million enrollees), and small (<250,000 enrollees).

We pilot-tested the survey with 5 health insurance plans to ensure that the questions appropriately addressed the topic areas and were consistently understood by health insurance plan representatives. We also used the pilot to assess terminology, comprehensiveness, and response options. The primary recommendations from the pilot were minor edits and did not involve the addition or deletion of any questions developed for the survey.

AHIP notified the CEO of each plan about the voluntary survey. The survey was then sent to the person identified at each plan by AHIP as most responsible for business continuity or emergency preparedness (eg, chief medical officer, chief information officer, or chief operating officer). As needed, CEOs were contacted to facilitate survey completion. Follow-up calls were also made to promote engagement and address any questions that health plans may have had regarding the study. We distributed the survey via e-mail, with weekly reminders, from February 28 to May 1, 2013. AHIP also precontacted plans with incomplete or unanswered surveys by phone throughout the study period.

We calculated summary statistics and conducted bivariate analyses for key questions. To evaluate differences in responses by plan size, we used the χ2 test for differences among more than 2 proportions with (the application of) the finite population correction factor and Yates’ correction for continuity, as appropriate (ie, when >20% of cells had <5 count). All analyses were conducted using SAS 9.2 (Cary, North Carolina).

Of the 137 health plan members of AHIP, we received responses from 86 (63%). These 86 plans represent 81% of national private health plan enrollment and provide coverage for 190.6 million members across the United States. The responding plans varied by size, with the highest response rates from national (100%) and large plans (86%) compared with small plans (46%). We describe our major findings in 

All responding health plans had business continuity plans in place. Nearly all plans, regardless of size, reported having plans for business interruptions due to loss of critical infrastructure (eg, emergency power generators) or technical infrastructure (eg, information technology software or communication networks). Although there was variability by health plan size, most plans reported having emergency teams (85%) and emergency personnel (emergency recovery teams, 81%; disaster/emergency manager, 72%). Additionally, 59% reported having physical spaces (eg, emergency operations centers) for managing emergencies, and 40% reported having an emergency call center.

More than half of the health plans (59%) had established preparedness metrics to evaluate their emergency response and planning operations (eg, state of readiness [36%] or percent of operations restored [28%]), but we did not define these further in the study. There were no differences identified with regard to these metrics by health plan size.

Responding health insurance plans provided several concrete ways that they could further enhance their emergency preparedness efforts for both internal operations and member-related activities. These included use of social media outlets for communicating with members, customers, and providers; emergency preparedness webinars; construction of early alerts, checklists, lists of emergency contacts, and situational updates; and exercises for the industry to prevent and counter cyber attacks.

More than 95% of the plans indicated that a federal or state emergency declaration would trigger an internal review of their benefits (policy liberation). Most plans indicated that the changes they would most likely consider during an emergency period would include extending the time period for filing claims, revising or relaxating of out-of-network restrictions, and temporarily suspending business rules for prior medical authorization. Other changes they might consider include suspending business rules for precertification (61%), accepting incomplete claims due to record or data loss (51%), and ensuring the availability of electronic medical records to facilitate continuity of care (40%).

Some respondents reported having specific policies for assisting individuals with certain healthcare needs. Although more common in national plans, more than onethird of health insurance plans overall had capabilities to monitor and assist special populations: those dependent on durable medical equipment (34%), prescription drugs such as insulin or methadone (46%), and home healthcare (35%). Almost all the surveyed health insurance plans reported having the capability to use their claims data to monitor patient care needs, prescription medications, and provider/service utilization.

Although variability by plan size was identified, most health insurance plans indicated that they were able to communicate with stakeholders—such as members, employer groups, and providers&mdash;within 24 hours of a disaster. Prompt communication with public health officials occurred less often, and several plans indicated challenges in knowing who to contact within federal (61%), state (82%), and local (66%) regulatory agencies in the event of a disaster or public health emergency.

The vast majority (82%) of health insurance plans participated in internal preparedness drills. Fewer (30%) participated in preparedness drills with external stakeholders. Most expressed interest in engaging in these activities.

Many health plans shared specific lessons learned and best practices (

). Identified themes include using preparedness planning software, conducting regular emergency preparedness exercises, creating and maintaining spare storage capacity before backing up data, and using text messaging to keep staff informed in the event of emergency. Notably, 60% of health plans expressed interest in participating in a forum to further share and communicate about their specific experiences related to emergency preparedness.

To our knowledge, these data represent the first national view of health insurance plans’ emergency preparedness. Responding health insurance plans represented more than 190 million members, accounting for 81% of total health insurance plan enrollment in the United States. While differences were observed across plans relative to size, many small and medium health insurance plans reported preparedness resources and infrastructure similar to large and national plans.

We identified numerous areas in which health insurance plans have made significant efforts to prepare and respond to emergencies affecting the health and healthcare of their employees and members. We also identified 6 ways that health insurance plans can modify or supplement their existing policies and practices to further the preparedness efforts of the collective healthcare system:

1. Establish metrics for evaluating emergency preparedness plans and policies, and use them for benchmarking.

 Most respondents had basic emergency preparedness tools and policies in place, and 59% reported using specific metrics for evaluating tools and policies. While metrics specifically listed in the survey were not exhaustive, less than half reported using readiness, percent of operations restored, or percent of critical systems tested for benchmarking. While intermittent surveys may provide a snapshot of health insurance plan preparedness, industry-developed metrics could be helpful for real-time and ongoing benchmarking of preparedness. Additional metrics could be adapted from the best practices of other businesses and tailored for the unique challenges that health insurance plans face.

2. Identify policy modifications specific to health insurance plans for disasters.

 More than 80% of health insurance plans indicated they would make policy changes (eg, extending the time period for filing claims or relaxing out-of-network restrictions) in the event of a disaster, while some (40% to 50%) identified other modifications (eg, ensuring availability of electronic medical records to facilitate continuity of care or implementing a process to accept incomplete claims due to record or data loss). A need for specific service modifications has already been identified after prior disasters such as Hurricane Katrina,

when patients with chronic illnesses were transported to offsite locations and needed access to medications. Similar challenges arose after the 2011 catastrophic tornado in Joplin, Missouri, when patients were displaced and needed assistance with medical record access

 and input from health insurance plans about relaxation of restrictions for out-of-network care.

3. Enhance health insurance plan connectedness with state, local, and federal stakeholders. 

While the network of organizations in a healthcare system is vast, it is possible to enhance emergency communications between health insurance plans and other healthcare organizations such as hospitals and health departments. Improvements could be made regarding the specification of contact individuals in various organizations, routine maintenance of contact lists and what information to share with public health officials, and participation in local and national drills. Health plans indicated that while coping with a disaster, they sometimes struggled with finding accurate, up-to-date information about available physical resources (eg, whether a particular hospital clinic or long-term care facility was open) and vaccines (eg, indications for use or availability). Related challenges—such as determining reimbursement policies for care in nontraditional environments or service areas with voluntary evacuations, rather than government-mandated evacuations&mdash;weren’t directly evaluated in this survey, but they have been identified by healthcare providers and healthcare organization leaders in informal post-emergency debriefings and meetings.

Improving healthcare system connectedness (eg, contact lists, drills) and information exchange is consistent with the National Health Security Strategy Implementation Plan (2012) and guidance from the Hospital Preparedness Program. Both promote healthcare coalitions (HCCs) as models for fostering engagement of organizations across various sectors.

 In this context, HCCs bring together healthcare stakeholders for leveraging resources, drills and exercises, engagement, integration across groups, enhancing situational awareness, and other activities. This coordination of healthcare organizations and resources has improved some aspects of response in many events, including the Boston Marathon bombing and Hurricane Sandy.

4. Consider digital strategies to enhance communication.

 In the current information technology age, in which individuals and organizations are increasingly connected through networks and mobile phones, digital-based strategies for data collection and message dissemination could also help the emergency preparedness of healthcare systems and health insurance plans.

 Streamlined, readily available approaches for information surveillance and exchange (eg, websites, telephone hotlines, short message service text) could be very useful in this context.

5. Improve support and access to resources for individuals with special needs.

 Individuals reliant upon electricity-dependent medical equipment and life-sustaining healthcare services are particularly vulnerable in disasters that result in prolonged, widespread power outages since their access to care and other needed resources can be severely disrupted.

 Our survey revealed that most health plans have policies and the capability to use claims and other data systems to help monitor potential care interruptions, access to healthcare services and facilities, and reliance upon life-maintaining medical equipment. Broad adoption of such practices continues to improve health plans’ ability to anticipate community needs during a disaster and to promote emergency planning strategies for particularly vulnerable individuals.

6. Create regular forums for knowledge exchange about emergency preparedness.

 Many of the plans commented on lessons learned from specific events (eg, 9/11, Hurricane Sandy, the H1N1 outbreak), and indicated an interest in participating in forums to further share their experiences. Such venues could help insurers act on many of the study findings and advance the broader preparednessof health insurance plans and the healthcare system, including a focus on emergency plan development and the implementation of such plans across the health insurance community.

Because large plans were more likely than smaller ones to respond to the survey, we cannot readily assess the generalizability of findings across all health plans. However, because responding plans cover such a large percentage of the nation’s insured, the findings from our study do apply to most of the population. In addition, all data are based on self-reporting, so we cannot assess the degree to which the plans, policies, and capabilities could actually be used in an emergency. To date, standardized questions to assess the preparedness of health insurance plans have not been developed, so there may have been relevant content omitted from the survey that could be helpful for describing preparedness. This study represented a snapshot of health insurance plans’ preparedness, while future work could focus on tracking preparedness over time and evaluating the performance and improvement of emergency strategies in subsequent events.

Health insurance plans serve a critical role in public health emergencies. The authors queried plans about issues related to emergency preparedness: infrastructure, adaptability, connectedness, and best practices.

State of Emergency Preparedness for US Health Insurance Plans

 Key stakeholders agree better data on patients’ language are needed to effectively address language-related barriers to timely, highquality healthcare. Our objective was to describe health plan efforts to collect language data from its members, provide language services, and improve the provision of culturally and linguistically appropriate services (CLAS).

 National surveys in 2003, 2006, and 2008.

 Surveys were administered to health plans offering commercial, Medicaid, and/or Medicare Advantage products.

 123 health plans responded to the 2008 survey (50% response rate), including 65 commercial (50%), 46 Medicaid (53%), and 12 Medicare plans (44%), representing a total enrollment of 133.8 million Americans. In 2008, 74.0% of health plans collected language data (commercial 60.0%, Medicaid 89.1%, Medicare 91.7%), which is an increase for each plan type since 2003. Health plans used direct and indirect collection methods. Nearly all health plans reported offering language services, the most common being telephonic interpreting, multilingual member materials, and access to bilingual providers. A variety of strategies for improving CLAS were cited by health plans, including improving health plan communication materials, health literacy initiatives for members, and targeted training for providers and staff.

 Health plans have made substantial progress in the collection of language data and many are offering options for language services. With the rapid growth in Medicaid participation and newly insured individuals anticipated under the Affordable Care Act, health plans may be uniquely positioned to implement and test interventions that aim to improve appropriate utilization of language services by providers and patients.

	Key stakeholders agree that better data on patients’ language are needed to effectively address language-related barriers to timely, high-quality healthcare.

		In 2008, 74.0% of health plans collected language data (commercial 60.0%, Medicaid 89.1%, Medicare 91.7%); an increase since 2003.

		Health plans cited a variety of strategies for improving the provision of culturally and linguistically appropriate services and nearly all plans reported offering language services in 2008.

		Health plans may be uniquely positioned to implement and test interventions that aim to improve appropriate utilization of language services.

	Over the past several decades, the United States has experienced rapid growth in the racial and ethnic diversity of its population. By 2050, racial and ethnic minorities are estimated to comprise 54% of the nation’s population.

 Furthermore, in 2000, approximately 47 million Americans reported speaking a language other than English at home, and 21 million reported speaking English less than “very well.”

 Several studies have documented the negative impact of language barriers on patient-provider communication, patient safety, and the overall timeliness and quality of healthcare received.

	Although expanded insurance coverage is an important step in reducing gaps in care, it does not guarantee that patients, especially persons with limited English proficiency and low functional health literacy, can effectively navigate the healthcare system to access preventive services and obtain the care they need.

 Availability of a full range of culturally and linguistically appropriate healthcare services is essential for overcoming barriers and accessing timely care. To identify gaps in care for diverse populations, develop strategies to improve patient-provider communication, and allocate needed services and resources, key stakeholders agree that better data on patients’ language are needed.

	This article reports the results of 3 nationwide surveys of health plans regarding their efforts to improve the provision of culturally and linguistically appropriate services for their members.

 Specifically, we describe how health plans collect and use language data from their members, and what types of language access services are provided to members by plans. Our goal was to describe recent progress made by health plans and to identify areas needing further improvement.

Health plans have made substantial progress in the collection of language data and many are offering options for language services.

German Veselovskiy, MPP

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