The segregation of physician networks providing care to black and white patients with heart disease: Concepts, measures, and empirical evaluation

Black-White disparities in cardiac care may be related to physician referral network segregation. We developed and tested new geographic physician network segregation measures. We used Medicare claims to identify Black and White Medicare heart disease patients and map physician networks for 169 hospital referral regions (HRRs) with over 1000 Black patients. We constructed two network segregation indexes ranging from 0 (integration) to 100 (total segregation): Dissimilarity (the unevenness of Black and White patient distribution across physicians [Dn]) and Absolute Clustering (the propensity of Black patients' physicians to have closer ties with each other than with other physicians [ACLn]). We employed conditional logit models to estimate the probability of using the best (lowest mortality) geographically available hospital for Black and White patients undergoing coronary artery bypass grafting (CABG) surgery in 126 markets with sufficient sample size at increasing levels of network segregation and for low vs. high HRR Black patient population. Physician network segregation was lower than residential segregation (Dissimilarity 21.9 vs. 48.7, and Absolute Clustering 4.8 vs. 32.4) and positively correlated with residential segregation (p < .001). Network segregation effects differed by race and HRR Black patient population. For White patients, higher network segregation was associated with a higher probability of using the best available hospitals in HRRs with few black patients but unchanged (ACLn) or lower (Dn) probability of best hospital use in HRRs with many Black patients. For Black patients, higher network segregation was not associated with a substantial change in the probability of best hospital use regardless of the HRR Black patient population size. Measuring physician network segregation is feasible and associated with nuanced effects on Black-White differences in high-quality hospital use for heart disease. Further work is needed to understand underlying mechanisms and potential uses in health equity policy.

Understanding the social risk factor adjustment's effect on Star Ratings

OBJECTIVES

CMS implemented the Categorical Adjustment Index (CAI) to address measurement bias in the Medicare Advantage (MA) Star Ratings, as unadjusted scores may disadvantage MA contracts serving more enrollees at greater social risk. CAI values are added to a contract's Star Ratings to adjust for the mean within-contract performance disparity associated with its percentage of enrollees with low socioeconomic status (ie, receipt of a Part D low-income subsidy or dual eligibility for Medicare and Medicaid [LIS/DE]) and who are disabled. We examined the CAI's effect on Star Ratings and the type of contracts affected.

STUDY DESIGN

Observational study of MA contracts with health and prescription drug coverage.

METHODS

We compared adjusted and unadjusted 2017-2020 Star Ratings overall and by contracts' proportion of LIS/DE and disabled enrollees. We assessed the CAI's effect on qualifying for quality bonus payments (QBPs), eligibility for rebate payments, and high-performing and low-performing designations.

RESULTS

The CAI's impact was modest overall (3.2%-14.9% of contracts experienced one-half Star Rating changes). Upward changes were concentrated among contracts with high percentages of LIS/DE or disabled enrollees (7.7%-32.3% of these contracts saw increased Star Ratings). In 2020, 26.0% of contracts with a high proportion of LIS/DE or disabled enrollees that qualified for a QBP did so because of the CAI.

CONCLUSIONS

The CAI primarily affected contracts with high LIS/DE or disabled enrollment, which received higher Star Ratings because of the CAI. The adjustment helps ensure that such contracts' performance is not understated and reduces incentives for MA contracts to avoid patients at greater social risk.

Within-Physician Differences in Patient Sharing Between Primary Care Physicians and Cardiologists Who Treat White and Black Patients With Heart Disease

BACKGROUND

Black-White disparities in heart disease treatment may be attributable to differences in physician referral networks. We mapped physician networks for Medicare patients and examined within-physician Black-White differences in patient sharing between primary care physicians and cardiologists.

METHODS AND RESULTS

Using Medicare fee-for-service files for 2016 to 2017, we identified a cohort of Black and White patients with heart disease and the primary care physicians and cardiologists treating them. To ensure the robustness of within-physician comparisons, we restricted the sample to regional health care markets (ie, hospital referral regions) with at least 10 physicians sharing ≥3 Black and White patients. We used claims to construct 2 race-specific physician network measures: degree (number of cardiologists with whom a primary care physician shares patients) and transitivity (network tightness). Measures were adjusted for Black-White differences in physician panel size and calculated for all settings (hospital and office) and for office settings only. Of 306 US hospital referral regions, 226 and 145 met study criteria for all settings and office setting analyses, respectively. Black patients had more cardiology encounters overall (6.9 versus 6.6; P<0.001) and with unique cardiologists (3.0 versus 2.6; P<0.001), but fewer office encounters (31.7% versus 41.1%; P<0.001). Primary care physicians shared Black patients with more cardiologists than White patients (mean differential degree 23.4 for all settings and 3.6 for office analyses; P<0.001 for both). Black patient-sharing networks were less tightly connected in all but office settings (mean differential transitivity -0.2 for all settings [P<0.001] and near 0 for office analyses [P=0.74]).

CONCLUSIONS

Within-physician Black-White differences in patient sharing exist and may contribute to disparities in cardiac care.

A Formal Framework For Incorporating Equity Into Health Care Quality Measurement

Quality measurement is an important tool for incentivizing improvement in the quality of health care. Most quality measurement efforts do not explicitly target health equity. Although some measurement approaches may intend to realign incentives to focus quality improvement efforts on underserved groups, the extent to which they accomplish this goal is understudied. We posit that tying incentives to approaches on the basis of stratification or disparities may have unintended consequences or limited effects. Such approaches might not reduce existing disparities because addressing one aspect of equity may be in competition with addressing others. We propose equity weighting, a new measurement framework to advance equity on multiple fronts that addresses the shortcomings of existing approaches and explicitly calibrates incentives to align with equity goals. We use colorectal cancer screening data derived from 2017 Medicare claims to illustrate how equity weighting fixes unintended consequences in other methods and how it can be adapted to policy goals.

Estimated Annual Spending on Lecanemab and Its Ancillary Costs in the US Medicare Program

This cross-sectional cost analysis uses data from the 2018 Health and Retirement Study to estimate the potential future Medicare spending and beneficiary costs for lecanemab.

Changes in US Hospital Financial Performance During the COVID-19 Public Health Emergency

Importance

The COVID-19 public health emergency (PHE) caused substantial changes in hospital operations. The net effect of these changes on hospital financial performance is unclear.

Objective

To evaluate changes in hospital financial performance before and during the COVID-19 PHE.

Design, Setting, and Participants

This longitudinal within-hospital cohort analysis from 2017 to 2021 used national RAND hospital data merged with American Community Survey data. A total of 4223 short-term acute care or critical access hospitals in the US with financial data spanning 2017 to 2021 were evaluated.

Exposure

Financial performance during the first 2 years of the PHE.

Main Outcomes and Measures

The main outcome was PHE financial distress calculated based on net operating income (operating revenue minus operating expenses). Within-hospital changes in net operating income over time were evaluated with and without COVID-19 relief funding. From henceforth, 2020/2021 means the weighted average financial performance for both calendar year 2020 and 2021. Hospitals were characterized as having new financial distress if (1) their average 2020/2021 net operating income was negative and (2) the average 2020/2021 net operating income was less than that hospital's pre-2020 net operating income. Predictors of new financial distress were evaluated using logistic regression and predictors of COVID-19 relief using 2-part models.

Results

In this sample of 4423 hospitals, 3529 (80.0%) received PHE funds during 2020/2021. A total of 846 (19.1%) were located in a census tract with more than 20% Hispanic residents. Of the total number of hospitals, 720 (16.3%) of hospitals had PHE financial distress, whereas 2047 (46.3%) had PHE financial distress after excluding COVID-19 relief funding from net operating income. The majority of hospitals (n = 3337; 74.8%) had a positive net operating income across 2020/2021, with 785 (17.8%) hospitals moving from a negative pre-2020 to a positive 2020/2021 net operating income. In adjusted analyses, hospitals treating a higher proportion of Hispanic populations were more likely to have PHE distress (adjusted odds ratio, 1.3; 95% CI, 1.1-1.6; P = .02). Median (IQR) operating margins from 2020/2021 were at an all-time high of 6.5% (0.2%-13.3%) compared with pre-2020 operating margins of 2.8% (-2.8% to 9.3%).

Conclusions and Relevance

In this cohort study of US hospitals, the large majority had positive financial performance during 2020/2021, partly due to COVID-19 relief funds. However, hospitals serving Hispanic populations had substantially worsened financial performance during 2020/2021, even after accounting for COVID-19 relief. That COVID-19 relief funding aided in operating margins reaching all-time highs indicates funding amounts may have been larger than was necessary for many hospitals. With COVID-19 relief funding ending yet COVID-19 related continuing to affect hospital expenses, ongoing monitoring of hospital financial performance is vital to ensure patients retain access to care.

Physician organizations' use of behavioral nudges to influence physician behavior

OBJECTIVES

Because physicians' decisions drive health care costs and quality, there is growing interest in applying behavioral economics approaches, including behavioral nudges, to influence physicians' decisions. This paper investigates adoption of behavioral nudges by health system-affiliated physician organizations (POs), types of nudges being used, PO leader perceptions of nudge effectiveness, and implementation challenges.

STUDY DESIGN

Mixed-methods study design (PO leader survey followed by in-depth qualitative interviews). Purposive sample of 30 health system-affiliated POs in 4 states; POs varied in size and quality performance.

METHODS

We collected data between October 2017 and June 2019. The survey asked PO leaders to report their organization's use of 5 categories of nudges to influence primary and specialty physicians' actions. We conducted semistructured phone interviews to confirm survey responses, elicit examples of the nudges that POs reported using, understand how nudges were structured, and identify implementation challenges. We present descriptive tabulations of nudge use and effectiveness ratings. We applied thematic analysis to the interview data.

RESULTS

Almost all POs in this study reported nudge use. Clinical templates, patient action lists, and altered order entry were most commonly used. However, PO leaders reported that nudge use was limited to a narrow range of clinical applications, not widespread across the organization, and mostly structured as suggestions rather than default actions or hard stops.

CONCLUSIONS

Nudge use remains limited in practice. Opportunities exist to expand use of nudges to influence physician behavior; however, expanding use of behavioral nudges will require PO investment of resources to support their construction and maintenance.

Predicting Race And Ethnicity To Ensure Equitable Algorithms For Health Care Decision Making

Algorithms are currently used to assist in a wide array of health care decisions. Despite the general utility of these health care algorithms, there is growing recognition that they may lead to unintended racially discriminatory practices, raising concerns about the potential for algorithmic bias. An intuitive precaution against such bias is to remove race and ethnicity information as an input to health care algorithms, mimicking the idea of "race-blind" decisions. However, we argue that this approach is misguided. Knowledge, not ignorance, of race and ethnicity is necessary to combat algorithmic bias. When race and ethnicity are observed, many methodological approaches can be used to enforce equitable algorithmic performance. When race and ethnicity information is unavailable, which is often the case, imputing them can expand opportunities to not only identify and assess algorithmic bias but also combat it in both clinical and nonclinical settings. A valid imputation method, such as Bayesian Improved Surname Geocoding, can be applied to standard data collected by public and private payers and provider entities. We describe two applications in which imputation of race and ethnicity can help mitigate potential algorithmic biases: equitable disease screening algorithms using machine learning and equitable pay-for-performance incentives.

Is Bigger Better?: A Closer Look at Small Health Systems in the United States

BACKGROUND

Research on US health systems has focused on large systems with at least 50 physicians. Little is known about small systems.

OBJECTIVES

Compare the characteristics, quality, and costs of care between small and large health systems.

RESEARCH DESIGN

Retrospective, repeated cross-sectional analysis.

SUBJECTS

Between 468 and 479 large health systems, and between 608 and 641 small systems serving fee-for-service Medicare beneficiaries, yearly between 2013 and 2017.

MEASURES

We compared organizational, provider and beneficiary characteristics of large and small systems, and their geographic distribution, using multiple Medicare and Internal Revenue Service administrative data sources. We used mixed-effects regression models to estimate differences between small and large systems in claims-based Healthcare Effectiveness Data and Information Set (HEDIS) quality measures and HealthPartners' Total Cost of Care measure using a 100% sample of Medicare fee-for-service claims. We fit linear spline models to examine the relationship between the number of a system's affiliated physicians and its quality and costs.

RESULTS

The number of both small and large systems increased from 2013 to 2017. Small systems had a larger share of practice sites (43.1% vs. 11.7% for large systems in 2017) and beneficiaries (51.4% vs. 15.5% for large systems in 2017) in rural areas or small towns. Quality performance was lower among small systems than large systems (-0.52 SDs of a composite quality measure) and increased with system size up to ∼75 physicians. There was no difference in total costs of care.

CONCLUSIONS

Small systems are a growing source of care for rural Medicare populations, but their quality performance lags behind large systems. Future studies should examine the mechanisms responsible for quality differences.

Physician Compensation Arrangements and Financial Performance Incentives in US Health Systems

Question

Do health system physician compensation arrangements primarily incentivize volume or value?

Findings

This cross-sectional mixed-methods study of 31 physician organizations affiliated with 22 US health systems found that volume was a component of primary care and specialist compensation for most POs (83.9% and 93.3%, respectively), representing a substantial portion of compensation when included (mean, 68.2% and 73.7%, respectively). While most primary care and specialist compensation arrangements included performance-based incentives, they averaged less than 10% of compensation.

Meaning

The study results suggest that despite growth in value-based payment arrangements from payers, health systems currently incentivize physicians to maximize volume, thereby maximizing health system revenues.

Importance

Public and private payers continue to expand use of alternative payment models, aiming to use value-based payment to affect the care delivery of their contracted health system partners. In parallel, health systems and their employment of physicians continue to grow. However, the degree to which health system physician compensation reflects an orientation toward value, rather than volume, is unknown.

Objective

To characterize primary care physician (PCP) and specialist compensation arrangements among US health system–affiliated physician organizations (POs) and measure the portion of total physician compensation based on quality and cost performance.

Design, Setting, and Participants

This study was a cross-sectional mixed-methods analysis of in-depth multimodal data (compensation document review, interviews with 40 PO leaders, and surveys conducted between November 2017 and July 2019) from 31 POs affiliated with 22 purposefully selected health systems in 4 states. Data were analyzed from June 2019 to September 2020.

Main Outcomes and Measures

The frequency of PCP and specialist compensation types and the percentage of compensation when included, including base compensation incentives, quality and cost performance incentives, and other financial incentives. The top 3 actions physicians could take to increase their compensation. The association between POs’ percentage of revenue from fee-for-service and their physicians’ volume-based compensation percentage.

Results

Volume-based compensation was the most common base compensation incentive component for PCPs (26 POs [83.9%]; mean, 68.2% of compensation; median, 81.4%; range, 5.0%-100.0% when included) and specialists (29 POs [93.3%]; mean, 73.7% of compensation; median, 90.5%; range, 2.5%-100.0% when included). While quality and cost performance incentives were common (included by 83.9%-56.7% of POs for PCPs and specialists, respectively), the percentage of compensation based on quality and cost performance was modest (mean, 9.0% [median, 8.3%; range, 1.0%-25.0%] for PCPs and 5.3% [median, 4.5%; range, 0.5%-16.0%] for specialists when included). Increasing the volume of services was the most commonly cited action for physicians to increase compensation, reported as the top action by 22 POs (70.0%) for PCPs and specialists. We observed a very weak, nonsignificant association between the percentage of revenue of POs from fee for service and the PCP and specialist volume-based compensation percentage (r = 0.08; P = .78 and r = −0.04; P = .89, respectively).

Conclusions and Relevance

The results of this cross-sectional study suggest that PCPs and specialists despite receiving value-based reimbursement incentives from payers, the compensation of health system PCPs and specialists was dominated by volume-based incentives designed to maximize health systems revenue.

Trends in US Ambulatory Care Patterns During the COVID-19 Pandemic, 2019-2021

Importance

Following reductions in US ambulatory care early in the pandemic, it remains unclear whether care consistently returned to expected rates across insurance types and services.

Objective

To assess whether patients with Medicaid or Medicare-Medicaid dual eligibility had significantly lower than expected return to use of ambulatory care rates than patients with commercial, Medicare Advantage, or Medicare fee-for-service insurance.

Design, Setting, and Participants

In this retrospective cohort study examining ambulatory care service patterns from January 1, 2019, through February 28, 2021, claims data from multiple US payers were combined using the Milliman MedInsight research database. Using a difference-in-differences design, the extent to which utilization during the pandemic differed from expected rates had the pandemic not occurred was estimated. Changes in utilization rates between January and February 2020 and each subsequent 2-month time frame during the pandemic were compared with the changes in the corresponding months from the year prior. Age- and sex-adjusted Poisson regression models of monthly utilization counts were used, offsetting for total patient-months and stratifying by service and insurance type.

Exposures

Patients with Medicaid or Medicare-Medicaid dual eligibility compared with patients with commercial, Medicare Advantage, or Medicare fee-for-service insurance, respectively.

Main Outcomes and Measures

Utilization rates per 100 people for 6 services: emergency department, office and urgent care, behavioral health, screening colonoscopies, screening mammograms, and contraception counseling or HIV screening.

Results

More than 14.5 million US adults were included (mean age, 52.7 years; 54.9% women). In the March-April 2020 time frame, the combined use of 6 ambulatory services declined to 67.0% (95% CI, 66.9%-67.1%) of expected rates, but returned to 96.7% (95% CI, 96.6%-96.8%) of expected rates by the November-December 2020 time frame. During the second COVID-19 wave in the January-February 2021 time frame, overall utilization again declined to 86.2% (95% CI, 86.1%-86.3%) of expected rates, with colonoscopy remaining at 65.0% (95% CI, 64.1%-65.9%) and mammography at 79.2% (95% CI, 78.5%-79.8%) of expected rates. By the January-February 2021 time frame, overall utilization returned to expected rates as follows: patients with Medicaid at 78.4% (95% CI, 78.2%-78.7%), Medicare-Medicaid dual eligibility at 73.3% (95% CI, 72.8%-73.8%), commercial at 90.7% (95% CI, 90.5%-90.9%), Medicare Advantage at 83.2% (95% CI, 81.7%-82.2%), and Medicare fee-for-service at 82.0% (95% CI, 81.7%-82.2%; P < .001; comparing return to expected utilization rates among patients with Medicaid and Medicare-Medicaid dual eligibility, respectively, with each of the other insurance types).

Conclusions and Relevance

Between March 2020 and February 2021, aggregate use of 6 ambulatory care services increased after the preceding decrease in utilization that followed the onset of the COVID-19 pandemic. However, the rate of increase in use of these ambulatory care services was significantly lower for participants with Medicaid or Medicare-Medicaid dual eligibility than for those insured by commercial, Medicare Advantage, or Medicare fee-for-service.

Estimated Annual Spending on Aducanumab in the US Medicare Program

This cross-sectional study examines upper bound and lower bound annualized Medicare costs for administering aducanumab to beneficiaries with the approved indications of mild cognitive impairment or mild dementia.

Actions to improve quality: results from a national hospital survey

OBJECTIVES

CMS measures and reports hospital performance to drive quality improvement (QI), but information on actions that hospitals have taken in response to quality measurement is lacking. We aimed to develop national estimates of QI actions undertaken by hospitals and to explore their relationship to performance on CMS quality measures.

STUDY DESIGN

Nationally representative cross-sectional survey of acute care hospitals in 2016 (n = 1313 respondents; 64% response rate).

METHODS

We assessed 23 possible QI changes. Using multivariate linear regression, we estimated the relationship between reported QI changes and performance on composite measures derived from 26 Hospital Inpatient Quality Reporting Program measures (scaled 0-100), controlling for case mix and facility characteristics.

RESULTS

Hospitals reported implementing a mean of 17 QI changes (median [interquartile range], 17 [15-20]). Large hospitals reported significantly higher adoption rates than small hospitals for 18 QI changes. Most hospitals that reported making QI changes (63%-96% for the 23 changes) responded that the specific change made helped improve performance. In multivariate regression analyses, adoption of 92% of QI changes (90th percentile among hospitals), compared with adoption of 50% of QI changes (10th percentile), was associated with a 2.3-point higher overall performance score (95% CI, 0.7-4.0) and higher process (8.7 points; 95% CI, 5.7-11.7) and patient experience (3.0 points; 95% CI, 0.1-5.9) composite scores.

CONCLUSIONS

Hospitals reported widespread adoption of QI changes in response to CMS quality measurement and reporting. Higher QI adoption rates were associated with modestly higher process, patient experience, and overall performance composite scores.

Alignment Between Objective and Subjective Assessments of Health System Performance: Findings From a Mixed-Methods Study

EXECUTIVE SUMMARY

The article examines whether subjective performance assessments from health system executives match objective performance assessments and qualitatively explores ways to achieve high performance. We interviewed 138 C-suite executives of 24 health systems in California, Minnesota, Washington, and Wisconsin between 2017 and 2019. We used maximum variation sampling to select health systems to achieve diversity in performance on objective measures of clinical performance. Our interviews focused on executives' perceptions of their own health system's performance and factors they thought generally contributed to high performance. In our analysis, we grouped health systems based on objective performance levels (high, medium, and low) used in sampling, compared objective performance ratings with executives' subjective performance assessments, and used thematic analysis to identify reasons for subjective assessment of health system performance and levers of high performance in general. There was poor agreement between objective and subjective performance assessments (kappa = 0.082). Subjective assessments were higher than objective assessments and captured more factors than are typically considered in performance accountability and value-based payment initiatives. Executives whose views were inconsistent with objective performance assessments did not cite clinical care quality per se as the basis for their assessment, focusing instead on market competition, financial performance, and high customer satisfaction and loyalty. Executives who cited clinical quality metrics as the basis of their assessment offered subjective ratings consistent with objective ratings. Executives identified organizational culture, organizational governance, and staff engagement as levers for achieving high performance. Future research should explore the benefits and drawbacks of considering subjective performance assessments in value-based payment initiatives.

Rates of Disenrollment From Medicare Advantage Plans Are Higher for Racial/Ethnic Minority Beneficiaries

BACKGROUND

Each year, about 10% of Medicare Advantage (MA) enrollees voluntarily switch to another MA contract, while another 2% voluntarily switch from MA to fee-for-service Medicare. Voluntary disenrollment from MA plans is related to beneficiaries' negative experiences with their plan, disrupts the continuity of care, and conflicts with goals to reduce Medicare costs. Little is known about racial/ethnic disparities in voluntary disenrollment from MA plans.

OBJECTIVE

The objective of this study was to investigate differences in rates of voluntary disenrollment from MA plans by race/ethnicity.

SUBJECTS

A total of 116,770,319 beneficiaries enrolled in 736 MA plans in 2015.

METHODS

Differences in rates of disenrollment across racial/ethnic groups [Asian or Pacific Islander (API), Black, Hispanic, and White] were summarized using 4 types of logistic regression models: adjusted and unadjusted models estimating overall differences and adjusted and unadjusted models estimating within-plan differences. Unadjusted overall models included only racial/ethnic group probabilities as predictors. Adjusted overall models added age, sex, dual eligibility, disability, and state of residence as control variables. Between-plan differences were estimated by subtracting within-plan differences from overall differences.

RESULTS

Adjusted rates of disenrollment were significantly (P<0.001) higher for Hispanic (+1.2 percentage points), Black (+1.2 percentage points), and API beneficiaries (+2.4 percentage points) than for Whites. Within states, all 3 racial/ethnic minority groups tended to be concentrated in higher disenrollment plans. Within plans, API beneficiaries voluntarily disenrolled considerably more often than otherwise similar White beneficiaries.

CONCLUSION

These findings suggest the need to address cost, information, and other factors that may create barriers to racial/ethnic minority beneficiaries' enrollment in plans with lower overall disenrollment rates.

Home health agency adoption of quality improvement activities and association with performance

BACKGROUND

The Centers for Medicare & Medicaid Services (CMS) Home Health Quality Reporting Program (HHQRP) uses performance measurement to spur improvements in home health agencies' (HHAs') quality of care. We examined quality improvement (QI) activities HHAs reported making to improve on HHQRP quality measures, and whether reported QI activities were associated with better measure performance.

METHODS

We used responses (N = 1052) from a Web- and mail-based survey of a stratified random sample of HHAs included in CMS Home Health Compare in October 2019. We estimated national adoption rates for 27 possible QI activities related to organizational culture, health information technology, care process redesign, provider incentives, provider training, changes to staffing responsibilities, performance monitoring, and measure-specific QI initiatives and technical assistance. We used multivariate linear regression to examine the associations between HHA characteristics and QI adoption, and between QI adoption and CMS Home Health Quality of Patient Care Star Rating.

RESULTS

HHAs reported implementing an average of 16 QI activities (interquartile range 11-19 activities). Larger HHA size was associated with adopting 1.6 additional QI activities (p < 0.001). HHAs with higher proportions of disabled, black, or Hispanic patients adopted QI activities at similar or higher rates as other HHAs. Of the 27 QI activities, 23 were considered helpful by more than 80% of adopting HHAs. Compared with adopting 44% of QI activities (10th percentile among HHAs), adopting 89% of QI activities (90th percentile) was associated with a 0.4-star higher Star Rating (95% confidence interval 0.2-0.6).

CONCLUSIONS

HHAs report implementing a significant number of QI activities in response to CMS measurement programs; implementation of a greater number of activities is associated with better performance on publicly reported measures. To guide future HHA QI investments, work is needed to identify the optimal combination of QI activities and the specific QI activities that yield the greatest performance improvements.

Higher Medicare Spending On Imaging And Lab Services After Primary Care Physician Group Vertical Integration

In recent years direct ownership of physician practices by hospitals and health systems (that is, vertical integration) has become a prominent feature of the US health care system. One unexplored impact of vertical integration is the impact on referral patterns for common diagnostic tests and procedures and the associated spending. Using a 100 percent sample of 2013-16 Medicare fee-for-service claims data, we examined whether hospital and health system ownership of physician practices was associated with changes in site of care and Medicare reimbursement rates for ten common diagnostic imaging and laboratory services. After vertical integration, the monthly number of diagnostic imaging tests per 1,000 attributed beneficiaries performed in a hospital setting increased by 26.3 per 1,000, and the number performed in a nonhospital setting decreased by 24.8 per 1,000. Hospital-based laboratory tests increased by 44.5 per 1,000 attributed beneficiaries, and non-hospital-based laboratory tests decreased by 36.0 per 1,000. Average Medicare reimbursement rose by $6.38 for imaging tests and $0.57 for laboratory tests, which translates to $40.2 million and $32.9 million increases in Medicare spending, respectively, for the entire study period. This study highlights how the growing trend of vertical integration, combined with differences in Medicare payment between hospitals and nonhospital providers, leads to higher Medicare spending.

Barriers to using clinical decision support in ambulatory care: Do clinics in health systems fare better?

OBJECTIVE

We quantify the use of clinical decision support (CDS) and the specific barriers reported by ambulatory clinics and examine whether CDS utilization and barriers differed based on clinics' affiliation with health systems, providing a benchmark for future empirical research and policies related to this topic.

MATERIALS AND METHODS

Despite much discussion at the theoretic level, the existing literature provides little empirical understanding of barriers to using CDS in ambulatory care. We analyze data from 821 clinics in 117 medical groups, based on in Minnesota Community Measurement's annual Health Information Technology Survey (2014-2016). We examine clinics' use of 7 CDS tools, along with 7 barriers in 3 areas (resource, user acceptance, and technology). Employing linear probability models, we examine factors associated with CDS barriers.

RESULTS

Clinics in health systems used more CDS tools than did clinics not in systems (24 percentage points higher in automated reminders), but they also reported more barriers related to resources and user acceptance (26 percentage points higher in barriers to implementation and 33 points higher in disruptive alarms). Barriers related to workflow redesign increased in clinics affiliated with health systems (33 points higher). Rural clinics were more likely to report barriers to training.

CONCLUSIONS

CDS barriers related to resources and user acceptance remained substantial. Health systems, while being effective in promoting CDS tools, may need to provide further assistance to their affiliated ambulatory clinics to overcome barriers, especially the requirement to redesign workflow. Rural clinics may need more resources for training.

Assessment of Variation in Electronic Health Record Capabilities and Reported Clinical Quality Performance in Ambulatory Care Clinics, 2014-2017

IMPORTANCE

Electronic health records (EHRs) are widely promoted to improve the quality of health care, but information about the association of multifunctional EHRs with broad measures of quality in ambulatory settings is scarce.

OBJECTIVE

To assess the association between EHRs with different degrees of capabilities and publicly reported ambulatory quality measures in at least 3 clinical domains of care.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional and longitudinal study was conducted using survey responses from 1141 ambulatory clinics in Minnesota, Washington, and Wisconsin affiliated with a health system that responded to the Healthcare Information and Management Systems Society Annual Survey and reported performance measures in 2014 to 2017. Statistical analysis was performed from July 10, 2019, through February 26, 2021.

MAIN OUTCOMES AND MEASURES

A composite measure of EHR capability that considered 50 EHR capabilities in 7 functional domains, grouped into the following ordered categories: no functional EHR, EHR underuser, EHR, neither underuser or superuser, EHR superuser; as well as a standardized composite of ambulatory clinical performance measures that included 3 to 25 individual measures (median, 13 individual measures).

RESULTS

In 2014, 381 of 746 clinics (51%) were EHR superusers; this proportion increased in each subsequent year (457 of 846 clinics [54%] in 2015, 510 of 881 clinics [58%] in 2016, and 566 of 932 clinics [61%] in 2017). In each cross-sectional analysis year, EHR superusers had better clinical quality performance than other clinics (adjusted difference in score: 0.39 [95% CI, 0.12-0.65] in 2014; 0.29 [95% CI, -0.01 to 0.59] in 2015; 0.26 [95% CI, -0.05 to 0.56] in 2016; and 0.20 [95% CI, -0.04 to 0.45] in 2017). This difference in scores translates into an approximately 9% difference in a clinic's rank order in clinical quality. In longitudinal analyses, clinics that progressed to EHR superuser status had only slightly better gains in clinical quality between 2014 and 2017 compared with the gains in clinical quality of clinics that were static in terms of their EHR status (0.10 [95% CI, -0.13 to 0.32]). In an exploratory analysis, different types of EHR capability progressions had different degrees of associated improvements in ambulatory clinical quality (eg, progression from no functional EHR to a status short of superuser, 0.06 [95% CI, -0.40 to 0.52]; progression from EHR underuser to EHR superuser, 0.18 [95% CI, -0.14 to 0.50]).

CONCLUSIONS AND RELEVANCE

Between 2014 and 2017, ambulatory clinics in Minnesota, Washington, and Wisconsin with EHRs having greater capabilities had better composite measures of clinical quality than other clinics, but clinics that gained EHR capabilities during this time had smaller increases in clinical quality that were not statistically significant.

Trends in Low-Value Health Service Use and Spending in the US Medicare Fee-for-Service Program, 2014-2018

IMPORTANCE

Low-value care, defined as care offering no net benefit in specific clinical scenarios, is associated with harmful outcomes in patients and wasteful spending. Despite a national education campaign and increasing attention on reducing health care waste, recent trends in low-value care delivery remain unknown.

OBJECTIVE

To assess national trends in low-value care use and spending.

DESIGN, SETTING, AND PARTICIPANTS

In this cross-sectional study, analyses of low-value care use and spending from 2014 to 2018 were conducted using 100% Medicare fee-for-service enrollment and claims data. Included individuals were aged 65 years or older and continuously enrolled in Medicare parts A, B, and D during each measurement year and the previous year. Data were analyzed from September 2019 through December 2020.

EXPOSURE

Being enrolled in fee-for-service Medicare for a period of time, in years.

MAIN OUTCOMES AND MEASURES

The Milliman MedInsight Health Waste Calculator was used to assess 32 claims-based measures of low-value care associated with Choosing Wisely recommendations and other professional guidelines. The calculator designates services as wasteful, likely wasteful, or not wasteful based on an absence of indication of appropriate use in the claims history; calculator-designated wasteful services were defined as low-value care. Spending was calculated as claim-line level (ie, spending on the low-value service) and claim level (ie, spending on the low-value service plus associated services), adjusting for inflation.

RESULTS

Among 21 045 759 individuals with fee-for-service Medicare (mean [SD] age, 77.4 [7.9] years; 12 515 915 [59.5%] women), the percentage receiving any of 32 low-value services decreased from 36.3% (95% CI, 36.3%-36.4%) to 33.6% (95% CI, 33.6%-33.6%) from 2014 to 2018. Uses of low-value services per 1000 individuals decreased from 677.8 (95% CI, 676.2-679.5) to 632.7 (95% CI, 632.6-632.8) from 2014 to 2018. Three services comprised approximately two-thirds of uses among 32 low-value services per 1000 individuals: preoperative laboratory testing decreased from 213.8 (95% CI, 213.4-214.2) to 166.2 (95% CI, 166.2-166.2), while opioids for back pain increased from 154.4 (95% CI, 153.6-155.2) to 182.1 (95% CI, 182.1-182.1) and antibiotics for upper respiratory infections increased from 75.0 (95% CI, 75.0-75.1) to 82 (95% CI, 82.0-82.0). Spending per 1000 individuals on low-value care also decreased, from $52 765.5 (95% CI, $51 952.3-$53 578.6) to $46 921.7 (95% CI, $46 593.7-$47 249.7) at the claim-line level and from $160 070.4 (95% CI, $158 999.8-$161 141.0) to $144 741.1 (95% CI, $144 287.5-$145 194.7) at the claim level.

CONCLUSIONS AND RELEVANCE

This cross-sectional study found that among individuals with fee-for-service Medicare receiving any of 32 measured services, low-value care use and spending decreased marginally from 2014 to 2018, despite a national education campaign in collaboration with clinician specialty societies and increased attention on low-value care. While most use of low-value care came from 3 services, 1 of these was opioid prescriptions, which increased over time despite the harms associated with their use. These findings may represent several opportunities to prevent patient harm and lower spending.

Health information technology for ambulatory care in health systems

OBJECTIVES

The adoption and use of health information technology (IT) by health systems in ambulatory care can be an important driver of care quality. We examine recent trends in health IT adoption by health system-affiliated ambulatory clinics in the context of the federal government's Meaningful Use and Promoting Interoperability programs.

STUDY DESIGN

We analyzed a national sample of 17,861 ambulatory clinics affiliated with 1711 health systems, using longitudinal data (2014-2016) from the HIMSS Analytics annual surveys.

METHODS

We used descriptive analyses and linear probability models to examine the adoption of electronic health records (EHRs), as well as 16 specific functionalities, at the clinic level and the system level. We compared the differential trends of adoption by various characteristics of health systems.

RESULTS

We find that the adoption of an EHR certified by the Office of the National Coordinator for Health IT (ONC) increased from 73% to 91%. However, in 2016, only 38% of clinics reported having all 16 health IT functionalities included in this study. Small health systems lag behind large systems in ambulatory health IT adoption. Patient-facing functionalities were less likely to be adopted than those oriented toward physicians. Health information exchange capabilities are still low among ambulatory clinics, pointing to the importance of the ONC's recent Promoting Interoperability initiative.

CONCLUSIONS

The relatively low uptake of health IT functionalities important to care improvement suggests substantial opportunities for further improving adoption of ambulatory health IT even among the current EHR users.

Health system affiliation of physician organizations and quality of care for Medicare beneficiaries who have high needs

OBJECTIVE

To test the hypothesis that health systems provide better care to patients with high needs by comparing differences in quality between system-affiliated and nonaffiliated physician organizations (POs) and to examine variability in quality across health systems.

DATA SOURCES

2015 Medicare Data on Provider Practice and Specialty linked physicians to POs. Medicare Provider Enrollment, Chain, and Ownership System (PECOS) and IRS Form 990 data identified health system affiliations. Fee-for-service Medicare enrollment and claims data were used to examine quality.

STUDY DESIGN

This cross-sectional analysis of beneficiaries with high needs, defined as having more than twice the expected spending of an average beneficiary, examined six quality measures: continuity of care, follow-up visits after hospitalizations and emergency department (ED) visits, ED visits, all-cause readmissions, and ambulatory care-sensitive hospitalizations. Using a matched-pair design, we estimated beneficiary-level regression models with PO random effects to compare quality of care in system-affiliated and nonaffiliated POs. We then limited the sample to system-affiliated POs and estimated models with system random effects to examine variability in quality across systems.

PRINCIPAL FINDINGS

Among 2 323 301 beneficiaries with high needs, 52.3% received care from system-affiliated POs. Rates of ED visits were statistically significantly different in system-affiliated POs (117.5 per 100) and nonaffiliated POs (106.8 per 100, P < .0001). Small differences in the other five quality measures were observed across a range of sensitivity analyses. Among systems, substantial variation was observed for rates of continuity of care (90% of systems had rates between 70.8% and 89.4%) and follow-up after ED visits (90% of systems had rates between 56.9% and 73.5%).

CONCLUSIONS

Small differences in quality of care were observed among beneficiaries with high needs receiving care from system POs and nonsystem POs. Health systems may not confer hypothesized quality advantages to patients with high needs.

Understanding how health systems facilitate primary care redesign

OBJECTIVE

To understand how health systems are facilitating primary care redesign (PCR), examine the PCR initiatives taking place within systems, and identify barriers to this work.

STUDY SETTING

A purposive sample of 24 health systems in 4 states.

STUDY DESIGN

Data were systematically reviewed to identify how system leaders define and implement initiatives to redesign primary care delivery and identify challenges. Researchers applied codes which were based on the theoretical PCR literature and created new codes to capture emerging themes. Investigators analyzed coded data then produced and applied a thematic analysis to examine how health systems facilitate PCR.

DATA COLLECTION

Semi-structured telephone interviews with 162 system executives and physician organization leaders from 24 systems.

PRINCIPAL FINDINGS

Leaders at all 24 health systems described initiatives to redesign the delivery of primary care, but many were in the early stages. Respondents described the use of centralized health system resources to facilitate PCR initiatives, such as regionalized care coordinators, and integrated electronic health records. Team-based care, population management, and care coordination were the most commonly described initiatives to transform primary care delivery. Respondents most often cited improving efficiency and enhancing clinician job satisfaction, as motivating factors for team-based care. Changes in payment and risk assumption as well as community needs were commonly cited motivators for population health management and care coordination. Return on investment and the slower than anticipated rate in moving from fee-for-service to value-based payment were noted by multiple respondents as challenges health systems face in redesigning primary care.

CONCLUSIONS

Given their expanding role in health care and the potential to leverage resources, health systems are promising entities to promote the advancement of PCR. Systems demonstrate interest and engagement in this work but face significant challenges in getting to scale until payment models are in alignment with these efforts.

Are health systems redesigning how health care is delivered?

OBJECTIVE

To explore why and how health systems are engaging in care delivery redesign (CDR)-defined as the variety of tools and organizational change processes health systems use to pursue the Triple Aim.

STUDY SETTING

A purposive sample of 24 health systems across 4 states as part of the Agency for Healthcare Research and Quality's Comparative Health System Performance Initiative.

STUDY DESIGN

An exploratory qualitative study design to gain an "on the ground" understanding of health systems' motivations for, and approaches to, CDR, with the goals of identifying key dimensions of CDR, and gauging the depth of change that is possible based on the particular approaches to redesign care being adopted by the health systems.

DATA COLLECTION

Semi-structured telephone interviews with health system executives and physician organization leaders from 24 health systems (n = 162).

PRINCIPAL FINDINGS

We identify and define 13 CDR activities and find that the health systems' efforts are varied in terms of both the combination of activities they are engaging in and the depth of innovation within each activity. Health system executives who report strong internal motivation for their CDR efforts describe more confidence in their approach to CDR than those who report strong external motivation. Health system leaders face uncertainty when implementing CDR due to a limited evidence base and because of the slower than expected pace of payment change.

CONCLUSIONS

The ability to validly and reliably measure CDR activities-particularly across varying organizational contexts and markets-is currently limited but is key to better understanding CDR's impact on intended outcomes, which is important for guiding both health system decision making and policy making.

The importance of understanding and measuring health system structural, functional, and clinical integration

OBJECTIVE

We explore if there are ways to characterize health systems-not already revealed by secondary data-that could provide new insights into differences in health system performance. We sought to collect rich qualitative data to reveal whether and to what extent health systems vary in important ways across dimensions of structural, functional, and clinical integration.

DATA SOURCES

Interviews with 162 c-suite executives of 24 health systems in four states conducted through "virtual" site visits between 2017 and 2019.

STUDY DESIGN

Exploratory study using thematic comparative analysis to describe factors that may lead to high performance.

DATA COLLECTION

We used maximum variation sampling to achieve diversity in size and performance. We conducted, transcribed, coded, and analyzed in-depth, semi-structured interviews with system executives, covering such topics as market context, health system origin, organizational structure, governance features, and relationship of health system to affiliated hospitals and POs.

PRINCIPAL FINDINGS

Health systems vary widely in size and ownership type, complexity of organization and governance arrangements, and ability to take on risk. Structural, functional, and clinical integration vary across systems, with considerable activity around centralizing business functions, aligning financial incentives with physicians, establishing enterprise-wide EHR, and moving toward single signatory contracting. Executives describe clinical integration as more difficult to achieve, but essential. Studies that treat "health system" as a binary variable may be inappropriately aggregating for analysis health systems of very different types, at different degrees of maturity, and at different stages of structural, functional, and clinical integration. As a result, a "signal" indicating performance may be distorted by the "noise."

CONCLUSIONS

Developing ways to account for the complex structures of today's health systems can enhance future efforts to study systems as complex organizations, to assess their performance, and to better understand the effects of payment innovation, care redesign, and other reforms.

Distinguishing High-Performing Health Systems Using a Composite of Publicly Reported Measures of Ambulatory Care

BACKGROUND

Payers and policymakers are rewarding high-performing health care providers on the basis of summaries of overall quality performance, and the methods they use for measuring performance are increasingly important.

OBJECTIVE

To develop and evaluate a measure that ranks health care systems by ambulatory care quality.

DESIGN

Systems were ranked using a composite model that summarizes individual measures of quality, accounts for their correlation, and does not require health care systems to report every measure. The composite measure's suitability was evaluated by examining whether it captured the quality indicated by component measures (validity), whether differences in rank between health care systems were larger than statistical noise (reliability), and whether year-to-year changes in rank were small (stability).

SETTING

California and Minnesota, 2014 to 2016.

PARTICIPANTS

55 health care systems.

MEASUREMENTS

Publicly reported measures of ambulatory care quality.

RESULTS

The composite measure was valid in that it was broadly representative of the component measures and was not dominated by any single measure. The measure was reliable because the ranks for 93% of California systems and 80% of Minnesota systems were unlikely to be more than 2 places lower or higher. The measure was stable because fewer than half of systems changed ranks by more than 2 ranks from year to year.

LIMITATION

The analysis is limited to available measures of ambulatory care quality and includes only 2 states.

CONCLUSION

This composite measure uses publicly reported data to produce valid, reliable, and stable ranks of ambulatory care quality for health care systems in Minnesota and California, and this approach could be used in other applications.

PRIMARY FUNDING SOURCE

Agency for Healthcare Research and Quality.

Association of Primary and Specialty Care Integration on Physician Communication and Cancer Screening in Safety-Net Clinics

INTRODUCTION

Primary care providers who lack reliable referral relationships with specialists may be less likely than those who do have such relationships to conduct cancer screenings. Community health centers (CHCs), which provide primary care to disadvantaged populations, have historically reported difficulty accessing specialty care for their patients. This study aimed to describe strategies CHCs use to integrate care with specialists and examine whether more strongly integrated CHCs have higher rates of screening for colorectal and cervical cancers and report better communication with specialists.

METHODS

Using a 2017 survey of CHCs in 12 states and the District of Columbia and administrative data, we estimated the association between a composite measure of CHC/specialist integration and 1) colorectal and cervical cancer screening rates, and 2) 4 measures of CHC/specialist communication using multivariate regression models.

RESULTS

Integration strategies commonly reported by CHCs included having specialists deliver care on-site (80%) and establishing referral agreements with specialists (70%). CHCs that were most integrated with specialists had 5.6 and 6.8 percentage-point higher colorectal and cervical cancer screening rates, respectively, than the least integrated CHCs (P < .05). They also had significantly higher rates of knowing that specialist visits happened (67% vs 42%), knowing visit outcomes (65% vs 42%), receiving information after visits (47% vs 21%), and timely receipt of information (44% vs 27%).

CONCLUSION

CHCs use various strategies to integrate primary and specialty care. Efforts to promote CHC/specialist integration may help increase rates of cancer screening.

Racial and ethnic disparities in care for health system-affiliated physician organizations and non-affiliated physician organizations

OBJECTIVE

To assess racial and ethnic disparities in care for Medicare fee-for-service (FFS) beneficiaries and whether disparities differ between health system-affiliated physician organizations (POs) and nonaffiliated POs.

DATA SOURCES

We used Medicare Data on Provider Practice and Specialty (MD-PPAS), Medicare Provider Enrollment, Chain, and Ownership System (PECOS), IRS Form 990, 100% Medicare FFS claims, and race/ethnicity estimated using the Medicare Bayesian Improved Surname Geocoding 2.0 algorithm.

STUDY DESIGN

Using a sample of 16 007 POs providing primary care in 2015, we assessed racial/ethnic disparities on 12 measures derived from claims (2 cancer screenings; diabetic eye examinations; continuity of care; two medication adherence measures; three measures of follow-up visits after acute care; all-cause emergency department (ED) visits, all-cause readmissions, and ambulatory care-sensitive admissions). We decomposed these "total" disparities into within-PO and between-PO components using models with PO random effects. We then pair-matched 1853 of these POs that were affiliated with health systems to similar nonaffiliated POs. We examined differences in within-PO disparities by affiliation status by interacting each nonwhite race/ethnicity with an affiliation indicator.

DATA COLLECTION/EXTRACTION METHODS

Medicare Data on Provider Practice and Specialty identified POs billing Medicare; PECOS and IRS Form 990 identified health system affiliations. Beneficiaries age 18 and older were attributed to POs using a plurality visit rule.

PRINCIPAL FINDINGS

We observed total disparities in 12 of 36 comparisons between white and nonwhite beneficiaries; nonwhites received worse care in 10. Within-PO disparities exceeded between-PO disparities and were substantively important (>=5 percentage points or>=0.2 standardized differences) in nine of the 12 comparisons. Among these 12, nonaffiliated POs had smaller disparities than affiliated POs in two comparisons (P < .05): 1.6 percentage points smaller black-white disparities in follow-up after ED visits and 0.6 percentage points smaller Hispanic-white disparities in breast cancer screening.

CONCLUSIONS

We find no evidence that system-affiliated POs have smaller racial and ethnic disparities than nonaffiliated POs. Where differences existed, disparities were slightly larger in affiliated POs.

Optimizing health IT to improve health system performance: A work in progress

BACKGROUND

Despite significant investments in health information technology (IT), the technology has not yielded the intended performance effects or transformational change. We describe activities that health systems are pursuing to better leverage health IT to improve performance.

METHODS

We conducted semi-structured telephone interviews with C-suite executives from 24 U.S. health systems in four states during 2017-2019 and analyzed the data using a qualitative thematic approach.

RESULTS

Health systems reported two broad categories of activities: laying the foundation to improve performance with IT and using IT to improve performance. Within these categories, health systems were engaged in similar activities but varied greatly in their progress. The most substantial effort was devoted to the first category, which enabled rather than directly improved performance, and included consolidating to a single electronic health record (EHR) platform and common data across the health system, standardizing data elements, and standardizing care processes before using the EHR to implement them. Only after accomplishing such foundational activities were health systems able to focus on using the technology to improve performance through activities such as using data and analytics to monitor and provide feedback, improving uptake of evidence-based medicine, addressing variation and overuse, improving system-wide prevention and population health management, and making care more convenient.

CONCLUSIONS AND IMPLICATIONS

Leveraging IT to improve performance requires significant and sustained effort by health systems, in addition to significant investments in hardware and software. To accelerate change, better mechanisms for creating and disseminating best practices and providing advanced technical assistance are needed.

Access, Quality, And Financial Performance Of Rural Hospitals Following Health System Affiliation

More than 100 rural hospitals have closed since 2010. Some rural hospitals have affiliated with health systems to improve their financial performance and potentially avoid closure, but the effects of affiliation on rural hospitals and their patients are unclear. To examine the relationship between affiliation and performance, we compared rural hospitals that affiliated with a health system in the period 2008-17 and a propensity score-weighted set of nonaffiliating rural hospitals on twelve measures of structure, utilization, financial performance, and quality. Following health system affiliation, rural hospitals experienced a significant reduction in on-site diagnostic imaging technologies, the availability of obstetric and primary care services, and outpatient nonemergency visits, as well as a significant increase in operating margins (by 1.6-3.6 percentage points from a baseline of -1.6 percent). Changes in patient experience scores, readmissions, and emergency department visits were similar for affiliating and nonaffiliating hospitals. While joining health systems may improve rural hospitals' financial performance, affiliation may reduce access to services for patients in rural areas.

Trends in the use of computerized physician order entry by health-system affiliated ambulatory clinics in the United States, 2014-2016

BACKGROUND

Computerized provider order entry (CPOE) can help providers deliver better quality care. We aimed to understand recent trends in use of CPOE by health system-affiliated ambulatory clinics.

METHODS

We analyzed longitudinal data (2014-2016) for 19,109 ambulatory clinics that participated in all 3 years of the Healthcare Information and Management Systems Society Analytics survey to assess use of CPOE and identify characteristics of clinics associated with CPOE use. We calculated descriptive statistics to examine overall trends in use, location of order entry (bedside vs. clinical station), and system-level use CPOE across all clinics. We used linear probability models to explore the association between clinic characteristics (practice size, practice type, and health system type) and two outcomes of interest: CPOE use at any point between 2014 and 2016, and CPOE use beginning in 2015 or 2016.

RESULTS

Between 2014 and 2016, use of CPOE increased more than 9 percentage points from 58 to 67%. Larger clinics and those affiliated with multi-hospital health systems were more likely to have reported use of CPOE. We found no difference in CPOE use by primary care versus specialty care clinics. When used, most clinics reported using CPOE for most or all of their orders. Health systems that used CPOE usually did so for all system-affiliated clinics.

CONCLUSIONS

Small practice size or not being part of a multi-hospital system are associated with lower use of CPOE between 2014 and 2016. Less than optimal use in these environments may be harming patient outcomes.

Low-Value Proton Pump Inhibitor Prescriptions Among Older Adults at a Large Academic Health System

BACKGROUND

Older adults are particularly vulnerable to complications from proton pump inhibitor (PPI) drugs. We sought to characterize the prevalence of potentially low-value PPI prescriptions among older adults to inform a quality improvement (QI) intervention.

METHODS

We created a cohort of patients, aged 65 years or older, receiving primary care at a large academic health system in 2018. We identified patients currently prescribed any PPI using the electronic health record (EHR) medication list (current defined as September 1, 2018). A geriatrician, a gastroenterologist, a QI expert, and two primary care physicians (PCPs) created multidisciplinary PPI appropriateness criteria based on evidenced-based guidelines. Supervised by a gastroenterologist and PCP, two internal medicine residents conducted manual chart reviews in a random sample of 399 patients prescribed PPIs. We considered prescriptions potentially low value if they lacked a guideline-based (1) short-term indication (gastroesophageal reflux disease [GERD]/peptic ulcer disease/Helicobacter pylori gastritis/dyspepsia) or (2) long-term (>8 weeks) indication (severe/refractory GERD/erosive esophagitis/Barrett esophagus/esophageal adenocarcinoma/esophageal stricture/high gastrointestinal bleeding risk/Zollinger-Ellison syndrome). We used the Wilson score method to calculate 95% confidence intervals (CIs) on low-value PPI prescription prevalence.

RESULTS

Among 69 352 older adults, 8729 (12.6%) were prescribed a PPI. In the sample of 399 patients prescribed PPIs, 63.9% were female; their mean age was 76.2 years, and they were seen by 169 PCPs. Of the 399 prescriptions, 143 (35.8%; 95% CI = 31.3%-40.7%) were potentially low value-of which 82% began appropriately (eg, GERD) but then continued long term without a guideline-based indication. Among 169 PCPs, 32 (18.9%) contributed to 59.2% of potentially low-value prescriptions.

CONCLUSION

One in eight older adults were prescribed a PPI, and over one-third of prescriptions were potentially low-value. Most often, appropriate short-term prescriptions became potentially low value because they lacked long-term indications. With most potentially low-value prescribing concentrated among a small subset of PCPs, interventions targeting them and/or applying EHR-based automatic stopping rules may protect older adults from harm. J Am Geriatr Soc 67:2600-2604, 2019.

Federally Qualified Health Center Strategies for Integrating Care with Hospitals and Their Association with Measures of Communication

BACKGROUND

Federally qualified health centers have aligned clinical services and systems with local hospitals, but little is known about the specific care integration strategies health centers use or their impact on care. A research team examined the use of strategies by health centers to integrate care with hospitals and emergency departments (EDs) and their association with performance on measures of health center-hospital communication.

METHODS

A Web-based survey was administered to health center medical directors in 12 states and Washington, DC, in 2017. The survey collected 10 self-reported measures of communication between health centers and hospitals/EDs and the extent to which health centers used different strategies to improve care integration. Health center and market characteristics that predict higher vs. lower integration activity were examined, and logistic regression was used to assess the relationship between integration activity and communication.

RESULTS

Between 56% and 81% of health centers participated in quality improvement projects, health promotion initiatives, guideline alignment, or executive meetings with hospitals; far fewer established notification agreements regarding hospital/ED utilization. Health centers that were larger, were located in rural areas or states with Accountable Care Organization programs, reported fewer staff shortages, and had fewer minority patients were associated with greater integration activity. Higher levels of integration activity were associated with better performance on most communication measures in both inpatient and ED settings (p < 0.05). Integration activity was not associated with health centers' receipt of notifications after patients' ED visits.

CONCLUSION

Health centers differ in the use of strategies to integrate care with hospitals. Overall, integration activity is associated with better communication.

How are medical groups identified as high-performing? The effect of different approaches to classification of performance

BACKGROUND

Payers and policy makers across the international healthcare market are increasingly using publicly available summary measures to designate providers as "high-performing", but no consistently-applied approach exists to identifying high performers. This paper uses publicly available data to examine how different classification approaches influence which providers are designated as "high-performers".

METHODS

We conducted a quantitative analysis of cross-sectional publicly-available performance data in the U.S. We used 2014 Minnesota Community Measurement data from 58 medical groups to classify performance across 4 domains: quality (two process measures of cancer screening and 2 composite measures of chronic disease management), total cost of care, access (a composite CAHPS measure), and patient experience (3 CAHPS measures). We classified medical groups based on performance using either relative thresholds or absolute values of performance on all included measures.

RESULTS

Using relative thresholds, none of the 58 medical groups achieved performance in the top 25% or 35% in all 4 performance domains. A relative threshold of 40% was needed before one group was classified as high-performing in all 4 domains. Using absolute threshold values, two medical groups were classified as high-performing across all 4 domains. In both approaches, designating "high performance" using fewer domains led to more groups designated as high-performers, though there was little to moderate concordance across identified "high-performing" groups.

CONCLUSIONS

Classification of medical groups as high performing is sensitive to the domains of performance included, the classification approach, and choice of threshold. With increasing focus on achieving high performance in healthcare delivery, the absence of a consistently-applied approach to identify high performers impedes efforts to reliably compare, select and reward high-performing providers.

Evaluation of an Intervention to Reduce Low-Value Preoperative Care for Patients Undergoing Cataract Surgery at a Safety-Net Health System

IMPORTANCE

Preoperative testing for cataract surgery epitomizes low-value care and still occurs frequently, even at one of the nation's largest safety-net health systems.

OBJECTIVE

To evaluate a multipronged intervention to reduce low-value preoperative care for patients undergoing cataract surgery and analyze costs from various fiscal perspectives.

DESIGN, SETTING, AND PARTICIPANTS

This study took place at 2 academic safety-net medical centers, Los Angeles County and University of Southern California (LAC-USC) (intervention, n = 469) and Harbor-UCLA (University of California, Los Angeles) (control, n = 585), from April 13, 2015, through April 12, 2016, with 12 additional months (April 13, 2016, through April 13, 2017) to assess sustainability (intervention, n = 1002; control, n = 511). To compare pre- and postintervention vs control group utilization and cost changes, logistic regression assessing time-by-group interactions was used.

INTERVENTIONS

Using plan-do-study-act cycles, a quality improvement nurse reviewed medical records and engaged the anesthesiology and ophthalmology chiefs with data on overuse; all 3 educated staff and trainees on reducing routine preoperative care.

MAIN OUTCOMES AND MEASURES

Percentage of patients undergoing cataract surgery with preoperative medical visits, chest x-rays, laboratory tests, and electrocardiograms. Costs were estimated from LAC-USC's financially capitated perspective, and costs were simulated from fee-for-service (FFS) health system and societal perspectives.

RESULTS

Of 1054 patients, 546 (51.8%) were female (mean [SD] age, 60.6 [11.1] years). Preoperative visits decreased from 93% to 24% in the intervention group and increased from 89% to 91% in the control group (between-group difference, -71%; 95% CI, -80% to -62%). Chest x-rays decreased from 90% to 24% in the intervention group and increased from 75% to 83% in the control group (between-group difference, -75%; 95% CI, -86% to -65%). Laboratory tests decreased from 92% to 37% in the intervention group and decreased from 98% to 97% in the control group (between-group difference, -56%; 95% CI, -64% to -48%). Electrocardiograms decreased from 95% to 29% in the intervention group and increased from 86% to 94% in the control group (between-group difference, -74%; 95% CI, -83% to -65%). During 12-month follow-up, visits increased in the intervention group to 67%, but chest x-rays (12%), laboratory tests (28%), and electrocardiograms (11%) remained low (P < .001 for all time-group interactions in both periods). At LAC-USC, losses of $42 241 in year 1 were attributable to intervention costs, and 3-year projections estimated $67 241 in savings. In a simulation of a FFS health system at 3 years, $88 151 in losses were estimated, and for societal 3-year perspectives, $217 322 in savings were estimated.

CONCLUSIONS AND RELEVANCE

This intervention was associated with sustained reductions in low-value preoperative testing among patients undergoing cataract surgery and modest cost savings for the health system. The findings suggest that reducing low-value care may be associated with cost savings for financially capitated health systems and society but also with losses for FFS health systems, highlighting a potential barrier to eliminating low-value care.

Psychometric evaluation of the Medicare Advantage and prescription drug plan disenrollment reasons survey

OBJECTIVES

To develop and assess the reliability and validity of composite measures of reasons for disenrollment from Medicare Advantage (MA) and prescription drug plans (PDPs).

DATA SOURCE

Medicare beneficiaries who responded to the Medicare Advantage and Prescription Drug Plan Disenrollment Reasons Survey.

STUDY DESIGN

Separate multilevel factor analyses of MA and PDP data suggested groupings of survey items to form composite measures, for which internal consistency and interunit reliability were estimated. The association of each composite with an overall plan rating was examined to evaluate criterion validity.

PRINCIPAL FINDINGS

Five composites were identified: financial reasons for disenrollment; problems with prescription drug benefits and coverage; problems getting information and help from the plan; problems getting needed care, coverage, and cost information; and problems with coverage of doctors and hospitals. Beneficiary-level internal consistency reliability exceeded 0.70 for all but one composite (financial reasons); plan-level internal consistency reliability exceeded 0.80 for all composites; average interunit reliability for plans with ≥ 30 survey completes exceeded 0.75 for 3 of 5 composites. As expected, greater endorsement of reasons for disenrollment was associated with lower overall plan ratings.

CONCLUSIONS

The Disenrollment Reasons Survey provides a reliable and valid assessment of beneficiaries' reasons for leaving their plans. Multiple reasons for disenrollment may indicate especially poor experiences.

Level of agreement on health information technology adoption and use in survey data: a mixed-methods analysis of ambulatory clinics in 1 US state

Objective

Adoption of health information technology (HIT) is often assessed in surveys of organizations. The validity of data from such surveys for ambulatory clinics has not been evaluated. We compared level of agreement between 1 ambulatory statewide survey and 2 other data sources: a second survey and interviews with survey respondents.

Materials and methods

We used 2016 data from 2 surveys of ambulatory providers in Minnesota-the Healthcare Information and Management Systems Society (HIMSS) survey and the Minnesota HIT Ambulatory Clinic Survey-and primary data collected through qualitative interviews with survey respondents. We conducted a concurrent triangulation mixed-methods assessment of the Minnesota HIT survey by assessing level of agreement between it and HIMSS, and a thematic analysis of interview data to assess the respondent's understanding of what was being asked and their approach to responding.

Results

We find high agreement between the 2 surveys on questions related to common HIT functionalities-such as computerized provider order entry, medication-based decision support, and e-prescribing-which were widely adopted by respondents' organizations. Qualitative data suggest respondents found wording of items about these functionalities clear but encountered multiple challenges including interpreting items for less commonly adopted functionalities, estimating degree of HIT usage, and indicating relevant barriers. Respondents identified multiple errors in responses and likely reported greater within-group homogeneity than actually existed.

Conclusions

Survey items related to the presence or absence of widely adopted HIT functionalities may be more valid than items about less common functionalities, degree of usage, and barriers.

Specialty care access for Medicaid enrollees in expansion states

OBJECTIVES

Community health centers (CHCs) historically have reported challenges obtaining specialty care for their patients, but recent policy changes, including Medicaid eligibility expansions under the Affordable Care Act, may have improved access to specialty care. The objective of this study was to assess current levels of difficulty accessing specialty care for CHC patients, by insurance type, and to identify specific barriers and strategies that CHCs are using to overcome these barriers.

STUDY DESIGN

Cross-sectional survey, administered during summer 2017, of medical directors at CHCs in 9 states and the District of Columbia, all of which expanded Medicaid.

METHODS

Surveys were administered to medical directors at 361 CHCs (response rate, 55%) to assess the difficulty of accessing specialty care by insurance type and to identify the specialties for which it was most difficult to obtain new patient visits. The survey also elicited ratings of commonly reported barriers to obtaining specialty care and identified strategies used by CHCs to access specialty care for patients. Descriptive results are presented.

RESULTS

Nearly 60% of CHCs reported difficulty obtaining new patient specialty visits for their Medicaid patients, most often for orthopedists. Barriers to specialty care reported by CHCs included that few specialists in Medicaid managed care organization (MCO) networks were accepting new patients (69.4%) and MCO administrative requirements for obtaining specialist consults (49.0%). To enhance access to specialists, CHCs reported that they entered into referral agreements, developed appointment reminder systems, and participated in data exchange and other community-based initiatives.

CONCLUSIONS

Medicaid patients at CHCs face many barriers to accessing specialty care. Payment policies and network adequacy rules may need to be reexamined to address these challenges.

Are value-based incentives driving behavior change to improve value?

OBJECTIVES

To understand physician organization (PO) responses to financial incentives for quality and total cost of care among POs that were exposed to a statewide multipayer value-based payment (VBP) program, and to identify challenges that POs face in advancing the goals of VBP.

STUDY DESIGN

Semistructured qualitative interviews and survey.

METHODS

We drew a stratified random sample of 40 multispecialty California POs (25% of the POs that were eligible for incentives). In-person interviews were conducted with physician leaders and a survey was administered on actions being taken to reduce costs and redesign care and to discuss the challenges to improving value. We performed a thematic analysis of interview transcripts to identify common actions taken and challenges to reducing costs.

RESULTS

VBP helps to promote care delivery transformation among POs, although efforts varied across organizations. Investments are occurring primarily in strategies to control hospital costs and redesign primary care, particularly for chronically ill patients; specialty care redesign is largely absent. Physician payment incentives for value remain small relative to total compensation, with continued emphasis on productivity. Challenges cited include the lack of a single enterprisewide electronic health records platform for information exchange, limited ability to influence specialists who were not exclusive to the organization, lack of payer cost and utilization data to manage costs, inability to recoup care redesign investments given the small size of VBP incentives, and lack of physician cost awareness.

CONCLUSIONS

Transformation could be advanced by strengthening financial incentives for value; engaging specialists in care redesign and delivering value; enhancing partnerships among POs, hospitals, and payers to align quality and cost actions; strengthening information exchange across providers; and applying other strategies to influence physician behavior.

Sample selection in the face of design constraints: Use of clustering to define sample strata for qualitative research

OBJECTIVE

To sample 40 physician organizations stratified on the basis of longitudinal cost of care measures for qualitative interviews in order to describe the range of care delivery structures and processes that are being deployed to influence the total costs of caring for patients.

DATA SOURCES

Three years of physician organization-level total cost of care data (n = 156 in California) from the Integrated Healthcare Association's value-based pay-for-performance program.

STUDY DESIGN

We fit total cost of care data using mixture and K-means clustering algorithms to segment the population of physician organizations into sampling strata based on 3-year cost trajectories (ie, cost curves).

PRINCIPAL FINDINGS

A mixture of multivariate normal distributions can classify physician organization cost curves into clusters defined by total cost level, shape, and within-cluster variation. K-means clustering does not accommodate differing levels of within-cluster variation and resulted in more clusters being allocated to unstable cost curves. A mixture of regressions approach focuses overly on anomalous trajectories and is sensitive to model coding.

CONCLUSIONS

Statistical clustering can be used to form sampling strata when longitudinal measures are of primary interest. Many clustering algorithms are available; the choice of the clustering algorithm can strongly impact the resulting strata because various algorithms focus on different aspects of the observed data.

Reducing disparities requires multiple strategies

Disparities in care are a complex issue requiring multiple strategies to solve, including approaches to improve the measurement of quality and reporting stratified performance estimates.

Shifting From Passive Quality Reporting to Active Nudging to Influence Consumer Choice of Health Plan

Comparative quality information on health plan and provider performance is increasingly available in the form of quality report cards, but consumers rarely make use of these passively provided decision support tools. In 2012-2013, the Centers for Medicare & Medicaid Services (CMS) initiated quality-based nudges designed to encourage beneficiaries to move into higher quality Medicare Advantage (MA) plans. We assess the impacts of CMS' targeted quality-based nudges with longitudinal analysis of 2009-2014 MA plan enrollment trends. Nudges are associated with 17% reductions in enrollment in the lowest-performing plans and 3% increases in enrollment in the highest performing plans (annually, p < .01 for both), occurring at the time of nudge implementation and relative to trends for plans with moderate performance that were not targeted by nudges. These findings suggest that quality-based nudges can successfully steer consumers into higher quality plans and provide opportunities for purchasers and payers to increase consumers' use of quality information.

Adjusting Medicare Advantage star ratings for socioeconomic status and disability

OBJECTIVES

Studies have identified potential unintended effects of not adjusting clinical performance measures in value-based purchasing programs for socioeconomic status (SES) factors. We examine the impact of SES and disability adjustments on Medicare Advantage (MA) plans' and prescription drug plans' (PDPs') contract star ratings. These analyses informed the development of the Categorical Adjustment Index (CAI), which CMS implemented with the 2017 star ratings.

STUDY DESIGN

Retrospective analyses of MA and PDP performance using 2012 Medicare beneficiary-level characteristics and performance data from the Star Rating Program.

METHODS

We modeled within-contract associations of beneficiary SES (Medicaid and Medicare dual eligibility [DE] or receipt of a low-income subsidy [LIS]) and disability with performance on 16 clinical measures. We estimated variability in contract-level DE/LIS and disability disparities using mixed-effects regression models. We simulated the impact of applying the CAI to adjust star ratings for DE/LIS and disability to construct the 2017 star ratings.

RESULTS

DE/LIS was negatively associated with performance for 12 of 16 measures and positively associated for 2 of 16 measures. Disability was negatively associated with performance for 11 of 15 measures and positively associated for 3 of 15 measures. Adjusting star ratings using the CAI resulted in half-star rating increases for 8.5% of MA and 33.3% of PDP contracts that exceeded 50% DE/LIS beneficiaries.

CONCLUSIONS

Increases in star ratings following adjustment of clinical performance for SES and disability using the CAI focused on contracts with higher percentages of DE/LIS beneficiaries. Adjustment for enrollee characteristics may improve the accuracy of quality measurement and remove incentives for providers to avoid caring for more challenging patient populations.

Understanding The Role Played By Medicare's Patient Experience Points System In Hospital Reimbursement

In 2015 the Medicare Hospital Value-Based Purchasing (VBP) program paid hospitals $1.4 billion in performance-based incentives; 30 percent of a hospital's VBP Total Performance Score was based on performance on Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) measures of the patient experience of care. Hospitals receive patient experience points based on three components: achievement, improvement, and consistency. For 2015 we examined how the three components affected reimbursement for 3,152 hospitals, including their impact on low-performing and high-minority hospitals. Achievement accounted for 96 percent of the differences among hospitals in total HCAHPS points. Although achievement had the biggest influence on payments, payments related to improvement and consistency were more beneficial for low-performing hospitals that disproportionately served minority patients. The findings highlight the important inducement that paying for improvement provides to initially low-performing hospitals to improve care and the role this incentive structure plays in minimizing resource redistributions away from hospitals serving minority populations. Additional emphasis on improvement points could benefit hospitals serving disadvantaged patients.