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Policy PointsConcerns have been raised about risk selection in the Medicare Shared Savings Program (MSSP). Specifically, turnover in accountable care organization (ACO) physicians and patient panels has led to concerns that ACOs may be earning shared‐savings bonuses by selecting lower‐risk patients or providers with lower‐risk panels.We find no evidence that changes in ACO patient populations explain savings estimates from previous evaluations through 2015. We also find no evidence that ACOs systematically manipulated provider composition or billing to earn bonuses.The modest savings and lack of risk selection in the original MSSP design suggest opportunities to build on early progress.Recent program changes provide ACOs with more opportunity to select providers with lower‐risk patients. Understanding the effect of these changes will be important for guiding future payment policy. Context: The Medicare Shared Savings Program (MSSP) establishes incentives for participating accountable care organizations (ACOs) to lower spending for their attributed fee‐for‐service Medicare patients. Turnover in ACO physicians and patient panels has raised concerns that ACOs may be earning shared‐savings bonuses by selecting lower‐risk patients or providers with lower‐risk panels. Methods: We conducted three sets of analyses of Medicare claims data. First, we estimated overall MSSP savings through 2015 using a difference‐in‐differences approach and methods that eliminated selection bias from ACO program exit or changes in the practices or physicians included in ACO contracts. We then checked for residual risk selection at the patient level. Second, we reestimated savings with methods that address undetected risk selection but could introduce bias from other sources. These included patient fixed effects, baseline or prospective assignment, and area‐level MSSP exposure to hold patient populations constant. Third, we tested for changes in provider composition or provider billing that may have contributed to bonuses, even if they were eliminated as sources of bias in the evaluation analyses. Findings: MSSP participation was associated with modest and increasing annual gross savings in the 2012‐2013 entry cohorts of ACOs that reached $139 to $302 per patient by 2015. Savings in the 2014 entry cohort were small and not statistically significant. Robustness checks revealed no evidence of residual risk selection. Alternative methods to address risk selection produced results that were substantively consistent with our primary analysis but varied somewhat and were more sensitive to adjustment for patient characteristics, suggesting the introduction of bias from within‐patient changes in time‐varying characteristics. We found no evidence of ACO manipulation of provider composition or billing to inflate savings. Finally, larger savings for physician group ACOs were robust to consideration of differential changes in organizational structure among non‐ACO providers (eg, from consolidation). Conclusions: Participation in the original MSSP program was associated with modest savings and not with favorable risk selection. These findings suggest an opportunity to build on early progress. Understanding the effect of new opportunities and incentives for risk selection in the revamped MSSP will be important for guiding future program reforms. [ABSTRACT FROM AUTHOR]

Context: Structural features of health care environments are associated with patient health outcomes, but these relationships are not well understood in sports medicine. Objective: To evaluate the association between athlete injury outcomes and structural measures of health care at universities: (1) clinicians per athlete, (2) financial model of the sports medicine department, and (3) administrative reporting structure of the sports medicine department. Design: Descriptive epidemiology study. Setting: Collegiate sports medicine programs. Patients or Other Participants: Colleges that contribute data to the National Collegiate Athletic Association (NCAA) Injury Surveillance Program. Main Outcome Measure(s): We combined injury data from the NCAA Injury Surveillance Program, sports medicine staffing data from NCAA Research, athletic department characteristics from the United States Department of Education, and financial and administrative oversight model data from a previous survey. Rates of injury, reinjury, concussion, and time loss (days) in NCAA athletes. Results: Compared with schools that had an average number of clinicians per athlete, schools 1 standard deviation above average had a 9.5% lower injury incidence (103.6 versus 93.7 per 10000 athlete-exposures [AEs]; incidence rate ratio [IRR] = 0.905, P, .001), 2.7% lower incidence of reinjury (10.6 versus 10.3 per 10000 AEs; IRR = 0.973, P = .004), and 6.7% lower incidence of concussion (6.1 versus 5.7 per 10000 AEs; IRR = 0.933, P, .001). Compared with the average, schools that had 1 standard deviation more clinicians per athlete had 16% greater injury time loss (5.0 days versus 4.2 days; IRR = 1.16, P, .001). At schools with sports medicine departments financed by or reporting to the athletics department (or both), athletes had higher injury incidences (31% and 9%, respectively). Conclusions: The financial and reporting structures of collegiate sports medicine departments as well as the number of clinicians per athlete were associated with injury risk. Increasing the number of sports medicine clinicians on staff and structuring sports medicine departments such that they are financed by and report to a medical institution may reduce athlete injury incidence. [ABSTRACT FROM AUTHOR]

Background: Prior studies have demonstrated how price transparency lowers the test-ordering rates of trainees in hospitals, and physician-targeted price transparency efforts have been viewed as a promising cost-controlling strategy.Objective: To examine the effect of displaying paid-price information on test-ordering rates for common imaging studies and procedures within an accountable care organization (ACO).Design: Block randomized controlled trial for 1 year.Subjects: A total of 1205 fully licensed clinicians (728 primary care, 477 specialists).Intervention: Starting January 2014, clinicians in the Control arm received no price display; those in the intervention arms received Single or Paired Internal/External Median Prices in the test-ordering screen of their electronic health record. Internal prices were the amounts paid by insurers for the ACO's services; external paid prices were the amounts paid by insurers for the same services when delivered by unaffiliated providers.Main Measures: Ordering rates (orders per 100 face-to-face encounters with adult patients): overall, designated to be completed internally within the ACO, considered "inappropriate" (e.g., MRI for simple headache), and thought to be "appropriate" (e.g., screening colonoscopy).Key Results: We found no significant difference in overall ordering rates across the Control, Single Median Price, or Paired Internal/External Median Prices study arms. For every 100 encounters, clinicians in the Control arm ordered 15.0 (SD 31.1) tests, those in the Single Median Price arm ordered 15.0 (SD 16.2) tests, and those in the Paired Prices arms ordered 15.7 (SD 20.5) tests (one-way ANOVA p-value 0.88). There was no difference in ordering rates for tests designated to be completed internally or considered to be inappropriate or appropriate.Conclusions: Displaying paid-price information did not alter how frequently primary care and specialist clinicians ordered imaging studies and procedures within an ACO. Those with a particular interest in removing waste from the health care system may want to consider a variety of contextual factors that can affect physician-targeted price transparency. [ABSTRACT FROM AUTHOR]

In 2011 CareFirst BlueCross BlueShield, a large mid-Atlantic health insurance plan, implemented a payment and delivery system reform program. The model, called the Total Care and Cost Improvement Program, includes enhanced payments for primary care, significant financial incentives for primary care physicians to control spending, and care coordination tools to support progress toward the goal of higher-quality and lower-cost patient care. We conducted a mixed-methods evaluation of the initiative's first three years. Our quantitative analyses used spending and utilization data for 2010-13 to compare enrollees who received care from participating physician groups to similar enrollees cared for by nonparticipating groups. Savings were small and fully shared with providers, which suggests no significant effect on total spending (including bonuses). Our qualitative analysis suggested that early in the program, many physicians were not fully engaged with the initiative and did not make full use of its tools. These findings imply that this and similar payment reforms may require greater time to realize significant savings than many stakeholders had expected. Patience may be necessary if payer-led reform is going to lead to system transformation. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Little is known about real-world facility-level preferences for cardiac resynchronization therapy devices with (CRT-D) and without (CRT-P) defibrillator backup. We quantify this variation at the facility level and exploit this variation to compare outcomes of patients receiving these 2 devices.Methods and Results: Claims data from fee-for-service Medicare beneficiaries were used to identify new CRT-P and CRT-D implants, 2006 to 2012. We modeled factors associated with receipt of each device, and compared mortality, hospitalizations, and reoperations for patients receiving each using both logistic regression and instrumental variable analysis to account for confounding. Among 71 459 device recipients (CRT-P, 11 925; CRT-D, 59 534; 31% women), CRT-P recipients were older, more likely to be women, and had more comorbidities. Variation in device selection among facilities was substantial: After adjustment for patient characteristics, the odds of receiving a CRT-P (versus CRT-D) device were 7.6× higher for a patient treated at a facility in the highest CRT-P use quartile versus a facility in the lowest CRT-P use quartile. Logistic modeling suggested a survival advantage for CRT-D devices but with falsification end points indicating residual confounding. By contrast, in the instrumental variable analysis using facility variability as the proposed instrument, clinical characteristics and falsification end points were well balanced, and 1-year mortality in patients who received CRT-P versus CRT-D implants did not differ, while CRT-P patients had a lower probability of hospitalizations and reoperations in the year following implant.Conclusions: CRT-P versus CRT-D selection varies substantially among facilities, adjusted for clinical factors. After instrumental variable adjustment for clinical covariates and facility preference, survival was no different between the devices. Therefore, CRT-P may be preferred for Medicare beneficiaries considering new CRT implantation. [ABSTRACT FROM AUTHOR]

Purpose The opioid epidemic continues to result in significant morbidity and mortality even within hospitals where opioids are the second most common cause of adverse events. Opioid stewardship represents one model for hospitals to promote safe and rational prescribing of opioids to mitigate preventable adverse events in alliance with new Joint Commission standards. The purpose of this study was to identify the prevalence of current hospital practices to improve opioid use. Methods A cross-sectional survey of hospital best practices for opioid use was electronically distributed via electronic listservs in March 2018 to examine the presence of an opioid stewardship program and related practices, including formulary restrictions, specialist involvement for high-risk patients, types of risk factors screened, and educational activities. Results Among 133 included hospitals, 23% reported a stewardship program and 14% reported a prospective screening process to identify patients at high risk of opioid-related adverse events (ORAEs). Among those with a prospective screening process, there was variability in ORAE risk factor screening. Formulary restrictions were dependent on specific opioids and formulations. Patient-controlled analgesia was restricted at 45% of hospitals. Most hospitals reported having a pain management service (90%) and a palliative care service providing pain management (67%). Conclusion The absence of opioid stewardship and prospectively screening ORAEs represents a gap in current practice at surveyed hospitals. Hospitals have an opportunity to implement and refine best practices such as access to pain management specialists, use of formulary restrictions, and retrospective and prospective monitoring of adverse events to improve opioid use. [ABSTRACT FROM AUTHOR]