Faculty Bibliography

Insurers and policy makers have created health care price transparency websites to facilitate price shopping and reduce spending. However, price transparency tools to date have been plagued by low use. It is unclear whether this low use reflects a lack of interest or a lack of awareness. We launched a large online advertising campaign to increase consumers' awareness about insurer-specific negotiated price information available on New Hampshire's public price transparency website. Our campaign led to a more than 600 percent increase in visits to the website. However, in our analysis of health plan claims, this increased use of the website did not translate to increased use of lower-price providers. Our findings imply that the limited success to date of price transparency tools in reducing health care spending is driven by structural factors that limit consumers' ability to use health care price information as opposed to only a lack of awareness about price transparency tools.

BACKGROUND:The 340B Drug Pricing Program entitles qualifying hospitals to discounts on outpatient drugs, increasing the profitability of drug administration. By tying the program eligibility of hospitals to their Disproportionate Share Hospital (DSH) adjustment percentage, which reflects the proportion of hospitalized patients who are low-income, the program is intended to expand resources for underserved populations but provides no direct incentives for hospitals to use financial gains to enhance care for low-income patients. METHODS:We used Medicare claims and a regression-discontinuity design, taking advantage of the threshold for program eligibility among general acute care hospitals (DSH percentage, >11.75%), to isolate the effects of the program on hospital-physician consolidation (i.e., acquisition of physician practices or employment of physicians by hospitals) and on the outpatient administration of parenteral drugs by hospital-owned facilities in three specialties in which parenteral drugs are frequently used. For low-income patients, we also assessed the effects of the program on the provision of care by hospitals and on mortality. RESULTS:Hospital eligibility for the 340B Program was associated with 2.3 more hematologist-oncologists practicing in facilities owned by the hospital, or 230% more hematologist-oncologists than expected in the absence of the program (P=0.02), and with 0.9 (or 900%) more ophthalmologists per hospital (P=0.08) and 0.1 (or 33%) more rheumatologists per hospital (P=0.84). Program eligibility was associated with significantly higher numbers of parenteral drug claims billed by hospitals for Medicare patients in hematology-oncology (90% higher, P=0.001) and ophthalmology (177% higher, P=0.03) but not rheumatology (77% higher, P=0.12). Program eligibility was associated with lower proportions of low-income patients in hematology-oncology and ophthalmology and with no significant differences in hospital provision of safety-net or inpatient care for low-income groups or in mortality among low-income residents of the hospitals' local service areas. CONCLUSIONS:The 340B Program has been associated with hospital-physician consolidation in hematology-oncology and with more hospital-based administration of parenteral drugs in hematology-oncology and ophthalmology. Financial gains for hospitals have not been associated with clear evidence of expanded care or lower mortality among low-income patients. (Funded by the Agency for Healthcare Research and Quality and others.).

OBJECTIVE: To examine the effect on BRCA testing and mastectomy rates of a widely viewed 2013 New York Times editorial by public figure Angelina Jolie that endorsed BRCA testing and announced Jolie's decision to undergo preventive mastectomy. DESIGN: Observational study with difference-in-difference analysis. SETTING: Commercially insured US population. PARTICIPANTS: Women aged 18-64 years with claims in the Truven MarketScan commercial claims database (n=9 532 836). MAIN OUTCOME MEASURES: Changes in BRCA testing rates in the 15 business days before versus after 14 May 2013 (editorial date) compared with the change in the same period in 2012; mastectomy rates in the months before and after publication, both overall and within 60 days of BRCA testing among women who were tested; national estimates of incremental tests and expenditures associated with Jolie's article in the 15 days after publication. RESULTS: Daily BRCA test rates increased immediately after the 2013 editorial, from 0.71 tests/100 000 women in the 15 business days before to 1.13 tests/100 000 women in the 15 business days after publication. In comparison, daily test rates were similar in the same period in 2012 (0.58/100 000 women in the 15 business days before 14 May versus 0.55/100 000 women in the 15 business days after), implying a difference-in-difference absolute daily increase of 0.45 tests/100 000 women or a 64% relative increase (P<0.001). The editorial was associated with an estimated increase of 4500 BRCA tests and $13.5m ( pound10.8m; euro12.8) expenditure nationally among commercially insured adult women in those 15 days. Increased BRCA testing rates were sustained throughout 2013. Overall mastectomy rates remained unchanged in the months after publication, but 60 day mastectomy rates among women who had a BRCA test fell from 10% in the months before publication to 7% in the months after publication, suggesting that women who underwent tests as a result of to the editorial had a lower pre-test probability of having the BRCA mutation than women tested before the editorial. CONCLUSIONS: Celebrity endorsements can have a large and immediate effect on use of health services. Such announcements can be a low cost means of reaching a broad audience quickly, but they may not effectively target the subpopulations that are most at risk for the relevant underlying condition.

IMPORTANCE: There is increasing interest in using price transparency tools to decrease health care spending. OBJECTIVE: To measure the association between offering a health care price transparency tool and outpatient spending. DESIGN, SETTING, AND PARTICIPANTS: Two large employers represented in multiple market areas across the United States offered an online health care price transparency tool to their employees. One introduced it on April 1, 2011, and the other on January 1, 2012. The tool provided users information about what they would pay out of pocket for services from different physicians, hospitals, or other clinical sites. Using a matched difference-in-differences design, outpatient spending among employees offered the tool (n=148,655) was compared with that among employees from other companies not offered the tool (n=295,983) in the year before and after it was introduced. EXPOSURE: Availability of a price transparency tool. MAIN OUTCOMES AND MEASURES: Annual outpatient spending, outpatient out-of-pocket spending, use rates of the tool. RESULTS: Mean outpatient spending among employees offered the tool was $2021 in the year before the tool was introduced and $2233 in the year after. In comparison, among controls, mean outpatient spending changed from $1985 to $2138. After adjusting for demographic and health characteristics, being offered the tool was associated with a mean $59 (95% CI, $25-$93) increase in outpatient spending. Mean outpatient out-of-pocket spending among those offered the tool was $507 in the year before introduction of the tool and $555 in the year after. Among the comparison group, mean outpatient out-of-pocket spending changed from $490 to $520. Being offered the price transparency tool was associated with a mean $18 (95% CI, $12-$25) increase in out-of-pocket spending after adjusting for relevant factors. In the first 12 months, 10% of employees who were offered the tool used it at least once. CONCLUSIONS AND RELEVANCE: Among employees at 2 large companies, offering a price transparency tool was not associated with lower health care spending. The tool was used by only a small percentage of eligible employees.

OBJECTIVE:To assess the effects of hospital 340B eligibility on quality of inpatient care provided to Medicaid and uninsured patients and for all patients. DATA/METHODS:Agency for Health Care Research and Quality's Healthcare Cost and Utilization Project State Inpatient Data, Hospital Cost Reporting Information System Data, Office of Pharmacy Affairs Information System Data, and American Hospital Association Annual Survey. DESIGN/METHODS:Regression discontinuity design comparing hospitals just above the DSH percentage program eligibility threshold to those just below. Quality measures include all-cause mortality and 30-day readmission rates as well as condition-specific measures. DATA EXTRACTION/METHODS:Inpatient data from general acute care hospitals from 2008 to 2014 in 15 states. Data linked on hospital 340B eligibility and participation. PRINCIPAL FINDINGS/RESULTS:We did not find discontinuities in inpatient care quality across the Program eligibility threshold for Medicaid and uninsured patients; specifically, on all-cause mortality (beta = -0.04 percentage points, 95% CI: -0.16, 0.08), 30-day readmission rates (beta = -0.16 percentage points, 95% CI: -0.81, 0.5), or other measures. Among insured and non-Medicaid patients, we found discontinuities for acute myocardial infarction (beta = -0.87 percentage points, 95% CI: -1.55, -0.2) and postoperative sepsis (beta = -0.15 percentage points, 95% CI: -0.23, -0.07) mortality. CONCLUSIONS:340B Program participation has not demonstrated improved quality of inpatient care among Medicaid or uninsured patients.

While a large body of evidence has examined hospital concentration, its effects on health care for low-income populations are less explored. We use comprehensive discharge data from New York State to measure the effects of changes in market concentration on hospital-level inpatient Medicaid volumes. Holding fixed hospital factors constant, a one percent increase in HHI leads to a 0.6% (s.e. = 0.28%) decrease in the number of Medicaid admissions for the average hospital. The strongest effects are on admissions for birth (-1.3%, s.e. = 0.58%). These average hospital-level decreases largely reflect redistribution of Medicaid patients across hospitals, rather than overall reductions in hospitalizations for Medicaid patients. In particular, hospital concentration leads to a redistribution of admissions from non-profit hospitals to public hospitals. We find evidence that for births, physicians serving high shares of Medicaid beneficiaries in particular experience reduced admissions as concentration increased. These reductions may reflect preferences among these physicians or reduced admitting privileges by hospitals as a means to screen out Medicaid patients.

Importance/UNASSIGNED:Rising drug costs contribute to medication nonadherence and adverse health outcomes. Real-time prescription benefit (RTPB) systems present prescribers with patient-specific out-of-pocket cost estimates and recommend lower-cost, clinically appropriate alternatives at the point of prescribing. Objective/UNASSIGNED:To investigate whether RTPB recommendations lead to reduced patient out-of-pocket costs for medications. Design, Setting, and Participants/UNASSIGNED:In this cluster randomized trial, medical practices in a large, urban academic health system were randomly assigned to RTPB recommendations from January 13 to July 31, 2021. Participants were adult patients receiving outpatient prescriptions during the study period. The analysis was limited to prescriptions for which RTPB could recommend an available alternative. Electronic health record data were used to analyze the intervention's effects on prescribing. Data analyses were performed from August 20, 2021, to June 8, 2022. Interventions/UNASSIGNED:When a prescription was initiated in the electronic health record, the RTPB system recommended available lower-cost, clinically appropriate alternatives for a different medication, length of prescription, and/or choice of pharmacy. The prescriber could select either the initiated order or one of the recommended options. Main Outcomes and Measures/UNASSIGNED:Patient out-of-pocket cost for a prescription. Secondary outcomes were whether a mail-order prescription and a 90-day supply were ordered. Results/UNASSIGNED:Of 867 757 outpatient prescriptions at randomized practices, 36 419 (4.2%) met the inclusion criteria of having an available alternative. Out-of-pocket costs were $39.90 for a 30-day supply in the intervention group and $67.80 for a 30-day supply in the control group. The intervention led to an adjusted 11.2%; (95% CI, -15.7% to -6.4%) reduction in out-of-pocket costs. Mail-order pharmacy use was 9.6% and 7.6% in the intervention and control groups, respectively (adjusted 1.9 percentage point increase; 95% CI, 0.9 to 3.0). Rates of 90-day supply were not different. In high-cost drug classes, the intervention reduced out-of-pocket costs by 38.9%; 95% CI, -47.6% to -28.7%. Conclusions and Relevance/UNASSIGNED:This cluster randomized clinical trial showed that RTPB recommendations led to lower patient out-of-pocket costs, with the largest savings occurring for high-cost medications. However, RTPB recommendations were made for only a small percentage of prescriptions. Trial Registration/UNASSIGNED:ClinicalTrials.gov Identifier: NCT04940988; American Economic Association Registry: AEARCTR-0006909.

Importance:Given higher reimbursement rates, hospitals primarily serving privately insured patients may invest more in intensive coding than hospitals serving publicly insured patients. This may lead these hospitals to code more diagnoses for all patients. Objective:To estimate whether, for the same Medicaid enrollee with multiple hospitalizations, a hospital's share of privately insured patients is associated with the number of diagnoses on claims. Design, Setting, and Participants:This cross-sectional study used patient-level fixed effects regression models on inpatient Medicaid claims from Medicaid enrollees with at least 2 admissions in at least 2 different hospitals in New York State between 2010 and 2017. Analyses were conducted from 2019 to 2021. Exposures:The annual share of privately insured patients at the admitting hospital. Main Outcomes and Measures:Number of diagnostic codes per admission. Probability of diagnoses being from a list of conditions shown to be intensely coded in response to payment incentives. Results:This analysis included 1 614 630 hospitalizations for Medicaid-insured patients (mean [SD] age, 48.2 [20.1] years; 829 684 [51.4%] women and 784 946 [48.6%] men). Overall, 74 998 were Asian (4.6%), 462 259 Black (28.6%), 375 591 Hispanic (23.3%), 486 313 White (30.1%), 128 896 unknown (8.0%), and 86 573 other (5.4%). When the same patient was seen in a hospital with a higher share of privately insured patients, more diagnoses were recorded (0.03 diagnoses per percentage point [pp] increase in share of privately insured; 95% CI, 0.02-0.05; P < .001). Patients discharged from hospitals in the bottom quartile of privately insured patient share received 1.37 more diagnoses when they were subsequently discharged from hospitals in the top quartile, relative to patients whose admissions were both in the bottom quartile (95% CI, 1.21-1.53; P < .001). Those going from hospitals in the top quartile to the bottom had 1.67 fewer diagnoses (95% CI, -1.84 to -1.50; P < .001). Diagnoses in hospitals with a higher private payer share were more likely to be for conditions sensitive to payment incentives (0.08 pp increase for each pp increase in private share; 95% CI, 0.06-0.10; P < .001). These findings were replicated in 2016 to 2017 data. Conclusions and Relevance:In this cross-sectional study of Medicaid enrollees, admission to a hospital with a higher private payer share was associated with more diagnoses on Medicaid claims. This suggests payment policy may drive differential investments in infrastructure to document diagnoses. This may create a feedback loop that exacerbates resource inequity.