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Calls for transparency in health care prices are increasing, in an effort to encourage and enable patients to make value-based decisions. Yet there is very little evidence of whether and how patients use health care price transparency tools.

Overall, use of the tool increased during the study period but remained low.

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Nonetheless, for some procedures the of people searching for prices of services called searchers was high relative to the of people who received the service called patients. Among Aetna patients who had an imaging service, childbirth, or one of several outpatient procedures, searchers for price information were ificantly more likely to be younger and healthier and to have incurred higher annual deductible spending than patients who did not search for price information.

Slowing the growth of health care costs is critical to the long-term fiscal stability of the United States, and it is the focus, either directly or indirectly, of the majority of health policy initiatives today.

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One tactic for reducing spending is to increase price transparency in health care—that is, to publish the prices that providers charge or patients and insurers pay for medical care. studies have found wide variation in medical prices across US markets. The rising prevalence of high deductibles in health plans is creating large populations of patients who have financial incentives to choose a low-cost provider. Efforts to introduce price transparency to the US health care system are increasing. In the Centers for Medicare and Medicaid Services CMS publicly released data on physician payment amounts for the first time, and in CMS implemented regulations stemming from the Affordable Care Act that require hospitals to annually publish prices of all the services they provide.

However, the functionality, comprehensiveness, and usability of these price data vary considerably. Health care pricing is complicated. Certain unique aspects of health care inherently limit the usefulness of and demand for price information in important ways.

For example, not all health care services lend themselves to consumer shopping. In many cases, health care needs are acute, and patients do not have the time or—in cases of critically ill patients in ambulances—even the ability to shop for and choose a provider.

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A growing of sources are providing the type of meaningful price transparency information described above through online tools, but there is very little evidence as to whether and how consumers use the tools. Christopher Whaley and coauthors analyzed the use of Castlight, a customized price transparency tool, for three services by employees at eighteen large self-insured employers. Consumers who searched for price information on Castlight were ificantly more likely to be female We evaluated how nonelderly adult enrollees insured at Aetna, a major commercial carrier, used a customized price transparency tool developed by the carrier.

The services included on the tool were considered by Aetna to be those that offered the biggest opportunities to save on health care expenses and those for which consumers were most likely to comparison shop. Aetna enrollees who searched the Member Payment Estimator for price information about a medical care service are called searchers in this article. Typically, searchers log into the Member Payment Estimator and specify, through a series of screens and menus, the person in their family for whom they are seeking the estimated price that is, the searcher, a spouse, orthe ZIP code where they want to find a provider, and the service or type of physician they need.

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As of the Member Payment Estimator automatically generates cost estimates for up to ten providers in the specified geographical area up from three in Enrollees can also query the Member Payment Estimator to obtain an estimate for a specific physician or facility by name. Estimates are listed from lowest to highest cost, but they can also be sorted by provider name or distance from the chosen ZIP code. They could either do an online search or call a customer service representative, who would search on their behalf.

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studies looked at the use of transparency tools in more limited populations for example, employees at a collection of firms that elected to use Castlight, or residents of New Hampshire, a small state. Having such detailed evidence is critical both to determining whether injecting price transparency into health care via searchable and customized web-based tools has the potential to affect patient decision making, and to identifying areas where changes in the de and targeting of these tools could increase their potential impact on the value of health care spending.

Aetna is a national health insurance company with over sixteen million enrollees in a range of commercial medical insurance products sold to large employers, small groups, and individuals. We obtained deidentified administrative enrollment and medical claims data for all enrollees who had searched the Member Payment Estimator tool and for the following two samples of nonsearchers: a random sample of enrollees who had never used the tool and a stratified random sample of enrollees who received a service during or but never used the tool even though it included price estimates for their service.

The sample was limited to adults ages 19—64 and, to improve the precision with which we were able to observe health status and out-of-pocket spending, to people enrolled for at least seven months in a given year. The sample consisted ofenrollees, of whomsearched the Member Payment Estimator;were randomly selected nonsearchers; andwere enrollees who received a service in —12 for which price estimates were available on the Member Payment Estimator but who never used the tool.

All analyses and presentation of were weighted to for oversampling of searchers. We constructed variables that measured patient age, sex, comorbidities, category of eligibility that is, single or family coverageannual deductible spending, and location of residence.

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Comorbidities were measured using the Elixhauser comorbidity index, which is commonly used in this type of analysis. These data were linked to claims for the searchers. We compared the characteristics of searchers to those of all nonsearchers. The ificance of differences between the two groups was examined using two-tailed t -tests for continuous variables and chi-square tests for dichotomous variables.

We focused several analyses on a set of twenty-four services for which price estimates were available on the Member Payment Estimator. These services were selected because they were among those most commonly searched by enrollees or because they were determined by our research team to be potentially good candidates for patient shopping since they were not emergency services.

The selected services fell into the following : preventive services colonoscopy, flu shot, and mammogramimaging services echocardiogram; magnetic resonance imaging [MRI] of brain with or without dye, neck without contrast, lower back without dye, and lower extremity t without dye; and computed tomography [CT] scan of abdomen and pelvis without dye and abdomen, pelvis, and chest with dyeprocedures carpal tunnel release, cataract or lens procedures, cesarean section, inguinal herniorrhaphy [hernia repair], sleep study, tonsillectomy with or without adenoidectomy, total hip replacement, total knee replacement, upper gastrointestinal endoscopy, and vaginal deliveryand physician office visits new patient primary care office visit, new patient gynecological visit, established patient primary care office visit, and established patient gynecological visit.

To identify the association between individual characteristics and searching the Member Payment Estimator, we estimated logistic regression models on a stratified sample of patientsdefined as all enrollees who had a claim for one of our twenty-four selected services.

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The dependent variable was a dichotomous indicator of whether the patient ever searched the Member Payment Estimator. The models also included procedure, quarterly, and state dummy variables. We report from two pooled models: one that included the five services received by women only mammogram, cesarean section, vaginal delivery, and gynecological office visits for new and established patients and one that included the remaining nineteen selected services.

As a sensitivity analysis, we estimated but do not show in this article models that controlled for geography using dummy variables for hospital referral regions instead of states. The from this sensitivity analysis were similar to our primary. We also conducted descriptive analyses of the search-level Member Payment Estimator data to identify patterns of use of the tool, including the medical services most frequently searched, rates of search, and characteristics of repeat searchers. For the twenty-four selected services, we analyzed the proportion of searches for price information relative to the overall patient volume for each service.

For twenty-two of these services all but established patient office visits we report rates of enrollees with no history of receiving a service who searched for price estimates and received the service within 90 days or within days of the date of their first search. We had data on medical care utilization from January 1,through December 31, Thus, for these analyses we examined Member Payment Estimator searches that were conducted from January 1,through September 30 or June 30,respectively. Our study had several limitations. First, the study data were from the period —12, so they covered only the first two years of price transparency for consumers.

Despite the age of the data, this analysis provides new evidence on individual use of an online price transparency tool and can inform policy makers and insurers about possible new efforts for increasing the use of such tools. Importantly, the lag in time since people searched the tool allowed us to observe whether searchers actually received the care for which they sought price information. Second, because of limitations in our data set, we could not link individuals within the same family to each other.

Thus, we were unable to observe patterns of searching within families. Finally, we report on the experience of enrollees with commercial coverage from a single health plan. Although this population was large and geographically diverse, the generalizability of our findings to other groups could not be determined.

The primary insured individual in a health plan that is, the subscriber could query the Member Payment Estimator for price estimates for him- or herself or for a dependent in the plan. In the first full year that the tool was available,subscribers 1.

Use increased by 43 percent in the second year, tosubscribers 2. The vast majority of subscribers who used the Member Payment Estimator in were first-time searchers: In absolute terms, 3. Exhibit 1 Selected characteristics of searchers and nonsearchers on the Aetna Member Payment Estimator price tool. NOTES The sample included all people ages 19—64 who were the primary subscriber on the plan, who were enrolled for at least seven months of the year, and who had access to the MPE. were weighted to adjust for the oversampling of searchers. ificance indicates that the difference between searchers and nonsearchers was statistically ificant in two-tailed t -tests for continuous variables and chi-square tests for dichotomous variables.

Three-quarters of the searches returned a price estimate for the subscriber that is, the person doing the searching him- or herself, and the remaining 25 percent of searches were on behalf of a dependent data not shown. Price estimates were more likely to be for women.

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Collectively, the top twenty services queried in each year represented about half of all searches. Preventive screening services colonoscopy and mammogram were the two most common services searched in and the first and third most common intogether ing for 15 percent of searches in and 14 percent in Exhibit 2. Several imaging services were also well represented in the top twenty services. Other common searches were for obstetrical care, physician office visits, and selected outpatient procedures.

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Exhibit 2 Most frequently searched health care services on the Aetna Member Payment Estimator price tool. NOTES Multiple searches by the same person for the same service on the same day were treated as a single search. Primary care is family practice, general practice, and internal medicine. MRI is magnetic resonance imaging. CT is computed tomography. One measure of the demand for price information on the Member Payment Estimator is to compare the of searchers with the volume for that service in the population.

Searchers do not all receive the medical service they search: They are simply individuals who get price information. There was wide variation in the of searchers relative to volume across the services. The of searchers represented 5 percent or less of the volume for physician office visits, imaging services, flu shots, and mammograms data not shown.

In contrast, the of searchers for tonsillectomy with or without adenoidectomy was 54 percent of the volume for those services among the population. Other services with a comparatively high volume of searchers relative to use were total knee replacement searchers represented 48 percent of the volumeinguinal herniorrhaphy 27 percentcataract or lens procedures 18 percentvaginal delivery or cesarean section 16 percentand carpal tunnel release 12 percent.

A second measure of the demand for price information is the share of patients enrollees who had a medical service who searched for price information for that service. Among the twenty-four selected services, those with the highest share of patients searching for price information were vaginal delivery or cesarean section 4. We sorted the twenty-four selected services into whether they were exclusively for women or for both men and women. Patients who searched for price information on procedures for both sexes were less likely to have a comorbidity. NOTES The presented are odds ratios from logistic regression models that also included service, state, quarter, and year fixed effects.

The services for women only were childbirth, gynecological office visits, and mammograms 71, of these services were provided in — Services for men and women were colonoscopy; magnetic resonance imaging of brain with or without dye, neck without contrast, lower back without dye or lower extremity t without dye; computed tomography scan of abdomen and pelvis without dye or abdomen, pelvis, and chest with dye; primary care office visits for new or established patients; total knee or hip replacement; sleep study; flu shot; carpal tunnel release; cataract or lens procedures; inguinal herniorrhaphy; echocardiogram; upper gastrointestinal endoscopy; and tonsillectomy with or without adenoidectomyof these services were provided in — Ninety-four percent of Member Payment Estimator searchers for twenty-two of our selected services all except established patient office visits had no history of receiving the service for which they searched the tool Exhibit 4.

Among searchers with no history of receiving the service, for whom prices were most likely new information, the proportions who received the service within 90 days or within days of their first search varied considerably. The highest proportions of searchers who then received the service were those who searched for prices of mammograms Although tonsillectomy procedures had a high of searchers relative to volume of the procedures in the population as noted aboveonly 7.

Exhibit 4 Rates of service use by searchers on the Aetna Member Payment Estimator price tool, — NOTES Selected magnetic resonance imaging MRI and computed tomography CT scans were MRI of brain with or without dye, neck without contrast, lower back without dye, and lower extremity t without dye; and CT scan of abdomen and pelvis without dye and abdomen, pelvis, and chest with dye.

Finally, we examined the frequency and characteristics of searches on the Member Payment Estimator. On average, the search showed prices for six different providers data not shown. However, the distribution was highly skewed: 59 percent of searches returned a price estimate for only one provider.

Searches with only one price estimate were most commonly for an established patient office visit.

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