Landscape of Health Systems in the United States

Impact of Hospital Affiliation With a Flagship Hospital System on Surgical Outcomes

OBJECTIVE

To compare general surgery outcomes at flagship systems, flagship hospitals, and flagship hospital affiliates versus matched controls.

SUMMARY BACKGROUND DATA

It is unknown whether flagship hospitals perform better than flagship hospital affiliates for surgical patients.

METHODS

Using Medicare claims for 2018 to 2019, we matched patients undergoing inpatient general surgery in flagship system hospitals to controls who underwent the same procedure at hospitals outside the system but within the same region. We defined a "flagship hospital" within each region as the major teaching hospital with the highest patient volume that is also part of a hospital system; its system was labeled a "flagship system." We performed 4 main comparisons: patients treated at any flagship system hospital versus hospitals outside the flagship system; flagship hospitals versus hospitals outside the flagship system; flagship hospital affiliates versus hospitals outside the flagship system; and flagship hospitals versus affiliate hospitals. Our primary outcome was 30-day mortality.

RESULTS

We formed 32,228 closely matched pairs across 35 regions. Patients at flagship system hospitals (32,228 pairs) had lower 30-day mortality than matched control patients [3.79% vs. 4.36%, difference=-0.57% (-0.86%, -0.28%), P<0.001]. Similarly, patients at flagship hospitals (15,571/32,228 pairs) had lower mortality than control patients. However, patients at flagship hospital affiliates (16,657/32,228 pairs) had similar mortality to matched controls. Flagship hospitals had lower mortality than affiliate hospitals [difference-in-differences=-1.05% (-1.62%, -0.47%), P<0.001].

CONCLUSIONS

Patients treated at flagship hospitals had significantly lower mortality rates than those treated at flagship hospital affiliates. Hence, flagship system affiliation does not alone imply better surgical outcomes.

Hub and spoke framework for study of surgical centralization within United States health systems

BACKGROUND

Hospital consolidation into health systems has mixed effects on surgical quality, potentially related to degree of surgical centralization at high-volume (hub) sites. We developed a novel measure of centralization and evaluated a hub and spoke framework.

METHODS

Surgical centralization within health systems was measured using hospital surgical volumes (American Hospital Association) and health system data (Agency for Healthcare Research and Quality). Hub and spoke hospitals were compared using mixed effects logistic regression and system characteristics associated with surgical centralization were identified using a linear model.

RESULTS

Within 382 health systems containing 3022 hospitals, system hubs perform 63% of cases (IQR 40-84%). Hubs are larger, in metropolitan and urban areas, and more often academically affiliated. Degree of surgical centralization varies ten-fold. Larger, multistate, and investor-owned systems are less centralized. Adjusting for these factors, there is less centralization among teaching systems (p ​< ​0.001).

CONCLUSIONS

A hub-spoke framework applies to most health systems but centralization varies significantly. Future studies of health system surgical care should assess the contributions of surgical centralization and teaching status on differential quality.

Impact of performance-based budgeting on quality outcomes in U.S. military health care facilities

BACKGROUND

Performance-based budgeting (PBB) is a variation of pay for performance that has been used in government hospitals but could be applicable to any integrated system. It works by increasing or decreasing funding based on preestablished performance thresholds, which incentivizes organizations to improve performance. In late 2006, the U.S. Army implemented a PBB program that tied hospital-level funding decisions to performance on key cost and quality-related metrics.

PURPOSE

The aim of this study was to estimate the impact of PBB on quality improvement in U.S. Army health care facilities.

APPROACH

This study used a retrospective difference-in-differences analysis of data from two Defense Health Agency data repositories. The merged data set encompassed administrative, demographic, and performance information about 428 military health care facilities. Facility-level performance data on quality indicators were compared between 187 Army PBB facilities and a comparison group of 241 non-PBB Navy and Air Force facilities before and after program implementation.

RESULTS

The Army's PBB programs had a positive impact on quality performance. Relative to comparison facilities, facilities that participated in PBB programs increased performance for over half of the indicators under investigation. Furthermore, performance was either sustained or continued to improve over 5 years for five of the six performance indicators examined long term.

CONCLUSION

Study findings indicate that PBB may be an effective policy mechanism for improving facility-level performance on quality indicators.

PRACTICE IMPLICATIONS

This study adds to the extant literature on pay for performance by examining the specific case of PBB. It demonstrates that quality performance can be influenced internally through centralized budgeting processes. Though specific to military hospitals, the findings might have applicability to other public and private sector hospitals who wish to incentivize performance internally in their organizational subunits through centralized budgeting processes.

Organization and Performance of US Health Systems

IMPORTANCE

Health systems play a central role in the delivery of health care, but relatively little is known about these organizations and their performance.

OBJECTIVE

To (1) identify and describe health systems in the United States; (2) assess differences between physicians and hospitals in and outside of health systems; and (3) compare quality and cost of care delivered by physicians and hospitals in and outside of health systems.

EVIDENCE REVIEW

Health systems were defined as groups of commonly owned or managed entities that included at least 1 general acute care hospital, 10 primary care physicians, and 50 total physicians located within a single hospital referral region. They were identified using Centers for Medicare & Medicaid Services administrative data, Internal Revenue Service filings, Medicare and commercial claims, and other data. Health systems were categorized as academic, public, large for-profit, large nonprofit, or other private systems. Quality of preventive care, chronic disease management, patient experience, low-value care, mortality, hospital readmissions, and spending were assessed for Medicare beneficiaries attributed to system and nonsystem physicians. Prices for physician and hospital services and total spending were assessed in 2018 commercial claims data. Outcomes were adjusted for patient characteristics and geographic area.

FINDINGS

A total of 580 health systems were identified and varied greatly in size. Systems accounted for 40% of physicians and 84% of general acute care hospital beds and delivered primary care to 41% of traditional Medicare beneficiaries. Academic and large nonprofit systems accounted for a majority of system physicians (80%) and system hospital beds (64%). System hospitals were larger than nonsystem hospitals (67% vs 23% with >100 beds), as were system physician practices (74% vs 12% with >100 physicians). Performance on measures of preventive care, clinical quality, and patient experience was modestly higher for health system physicians and hospitals than for nonsystem physicians and hospitals. Prices paid to health system physicians and hospitals were significantly higher than prices paid to nonsystem physicians and hospitals (12%-26% higher for physician services, 31% for hospital services). Adjusting for practice size attenuated health systems differences on quality measures, but price differences for small and medium practices remained large.

CONCLUSIONS AND RELEVANCE

In 2018, health system physicians and hospitals delivered a large portion of medical services. Performance on clinical quality and patient experience measures was marginally better in systems but spending and prices were substantially higher. This was especially true for small practices. Small quality differentials combined with large price differentials suggests that health systems have not, on average, realized their potential for better care at equal or lower cost.

At the vanguard: Leaders' perspectives on establishing healthcare system infection prevention programs

Hospitals are increasingly consolidating into health systems. Some systems have appointed healthcare epidemiologists to lead system-level infection prevention programs. Ideal program infrastructure and support resources have not been described. We informally surveyed 7 healthcare epidemiologists with recent experience building and leading system-level infection prevention programs. Key facilitators and barriers for program structure and implementation are described.

Effect of health system on the association of rurality and level of disadvantage with receipt of diabetic eye screening

INTRODUCTION

Rural versus urban disparities have been observed in diabetic eye screening, but whether the level of disadvantage in rural versus urban areas is related to these disparities is unclear. Our goal was to determine the role of level of disadvantage in explaining the effect of health systems on rural and urban disparities in diabetic eye screening.

RESEARCH DESIGN AND METHODS

This is a retrospective cohort study using an all-payer, state-wide claims database covering over 75% of Wisconsin residents. We included adults with diabetes (18-75 years old) who had claims billed throughout the baseline (2012-2013) and measurement (2013-2014) years. We performed multivariable regressions to assess factors associated with receipt of diabetic eye screening. The primary exposure was the primary care clinic's combined level of rurality and disadvantage. We adjusted for the health system as well as patient-level variables related to demographics and comorbidities. Health system was defined as an associated group of physicians and/or clinics.

RESULTS

A total of 118 707 adults with diabetes from 698 primary care clinics in 143 health systems met the inclusion criteria. Patients from urban underserved clinics were less likely to receive screening than those from rural underserved clinics before adjusting for health system in the model. After adjusting for health system fixed effects, however, the directionality of the relationship between clinic rurality and screening reversed: patients from urban underserved clinics were more likely to receive screening than those from rural underserved clinics. Similar findings were observed for both Medicare and non-Medicare subgroups.

CONCLUSIONS

The effect of health system on receipt of diabetic eye screening in rural versus urban areas is most pronounced in underserved areas. Health systems, particularly those providing care to urban underserved populations, have an opportunity to increase screening rates by leveraging health system-level interventions to support patients in overcoming barriers from social determinants of health.

Diabetes Care Network: A Novel Model to Disseminate Team-Based Diabetes Specialty Care in a Rural Population

PURPOSE

The purpose of the study was to examine the impact of a novel approach to provide diabetes specialty team care to rural patients with type 2 diabetes (T2DM) on clinical outcomes and processes of care.

METHODS

Diabetes Care Network (DCN) provides Veterans with T2DM and elevated A1C an initial 6-week period of remote self-management education and support and medication management by a centrally located team of diabetes specialists. Participants are then comanaged by remote liaisons embedded in rural primary care facilities for the remainder of the 12-month intervention. In this pre-post intervention study, 87 Veterans enrolled in DCN from 2 different clinical sites had baseline and 12-month postenrollment A1C, systolic blood pressure, weight, and LDL cholesterol levels collected and compared using paired t tests.

RESULTS

Participants were mostly male and White with elevated baseline A1C. Participants from both sites had significant improvement in A1C over the 12-month intervention period compared to an increase in the 12 months prior to enrollment. There were also significant improvements in LDL and systolic blood pressure at 1 site, with no significant change in weight at either site.

CONCLUSIONS

DCN participants had significant improvement in A1C after not meeting similar goals previously in a robust primary care setting. A technology-enabled collaborative partnership between centrally located diabetes care teams and local liaisons is a feasible approach to enhance access to diabetes specialty care for rural populations.

Job market in head and neck surgery: A survey and analysis of recent fellowship graduates

OBJECTIVE

Recent years have seen increase in individuals pursuing postgraduate fellowships in head and neck (HN) surgery. This has presented concerns about insufficient jobs where graduates can apply their scope of specialized training.

METHODS

Data was collected in two manners- a survey and a manual online search of American Head and Neck Society (AHNS) fellowship graduates. A 25-question survey was sent in 2021 to approximately 400 HN fellows who graduated between 2010 and 2020. The AHNS list of graduates from the same years were searched online to collect information including gender, graduation year, fellowship training, and current job practice.

RESULTS

Of the 78 survey responses, 64.1 % were male and 34.6 % female. 96.2 % reported ablative, 84.6 % microvascular, and 82.1 % TORS training. Mean number of interviews was 4 with most interviewing during the 3rd quarter (January to March). Majority reported being in academic and university-based practices (79.6 %). Online search was done on 393 graduates. Since 2010 the number of graduates almost doubled. There was a statistically significant increase in females by year (p = 0.022). There was a significant decrease (p = 0.022) in graduates with additional fellowship training from that of their AHNS fellowship. There was also a statistically significant increase in graduates being in academic practices (p = 0.022).

CONCLUSION

Despite growing numbers, there appears to be more graduates entering an academic practice, although the definition of an academic HN practice may be evolving. These results provide guidance on how to approach the job search in a select market.

LEVEL OF EVIDENCE

II.

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.

Harnessing the Power of Health Systems and Networks for Antimicrobial Stewardship

Twenty of 21 health systems and network-based antimicrobial stewardship programs (ASPs) who were invited participated in a questionnaire, a webinar, and focus groups to understand implementation strategies for system-wide antimicrobial stewardship. Four centralized ASPs structures emerged. Of participating organizations, 3 (15%) confirmed classification as collaborative, 3 (15%) as centrally coordinated, 3 (15%) as in between or in transition between centrally coordinated and centrally led, 8 (40%) as centrally led, 2 (10%) as collaborative, consultative network. One (5%) organization considered themselves to be a hybrid. System-level stewardship responsibilities varied across sites and generally fell into 6 major categories: building and leading a stewardship community, strategic planning and goal setting, development of validated data streams, leveraging tools and technology for stewardship interventions, provision of subject-matter expertise, and communication/education. Centralized ASPs included in this study most commonly took a centrally led approach and engaged in activities tailored to system-wide goals.

Physician versus Practice-Level Primary Care Continuity and Association with Outcomes in Medicare Beneficiaries

OBJECTIVE

To compare physician versus practice-level primary care continuity and their association with expenditure and acute care utilization among Medicare beneficiaries and evaluate if continuity of outpatient primary care at either/both physician or/and practice level could be useful quality measures.

DATA SOURCE

Medicare Fee-For-Service claims data for community dwelling beneficiaries without End-Stage Renal Disease who were attributed to a national random sample of primary care practices billing Medicare (2011-2017).

STUDY DESIGN

Retrospective secondary data analysis at per Medicare beneficiary per year level. We used multivariable linear regression with practice-level fixed effects to estimate continuity of care score at physician vs. practice level and their associations with outcomes.

DATA COLLECTION/EXTRACTION METHOD

We calculated clinician and practice level Bice-Boxerman continuity of care index scores, ranging from 0 to 1, using primary care outpatient claims. Medicare expenditures, hospital admissions, emergency department visits, and readmissions were obtained from the Medicare Beneficiary Summary File: Cost and Utilization Segment. Ambulatory care sensitive conditions (ACSC) were defined using diagnosis codes on inpatient claims.

PRINCIPAL FINDINGS

We studied 2,359,400 beneficiaries who sought care from 13,926 physicians. Every 0.1 increase in physician continuity score was associated with a $151 reduction in expenditures per beneficiary per year (P<0.01), and every 0.1 increase in practice continuity score was associated with $282 decrease (P<0.01) per beneficiary per year. Both physician- and practice-level continuity were associated with lower Medicare expenditures among small, medium, and large practices. Both physician- and practice-level continuity were associated with lower probabilities of hospitalization, emergency department visit, admissions for ACSC, and readmission.

CONCLUSIONS

Primary care continuity of care could serve as a potent value-based care quality metric. Physician-level continuity is a unique value center that cannot be supplanted by practice level continuity.

Survey of Information Exchange and Advanced Use of Other Health Information Technology in Primary Care Settings: Capabilities In and Outside of the Safety Net

BACKGROUND

Advanced use of health information technology (IT) functionalities can support more comprehensive, coordinated, and patient-centered primary care services. Safety net practices may benefit disproportionately from these investments, but it is unclear whether IT use in these settings has kept pace and what organizational factors are associated with varying use of these features.

OBJECTIVE

The aim was to estimate advanced use of health IT use in safety net versus nonsafety net primary care practices. We explore domains of patient engagement, population health management (decision support and registries), and electronic information exchange. We examine organizational characteristics that may differentially predict advanced use of IT across these settings, with a focus on health system ownership and/or membership in an independent practice network as key factors that may indicate available incentives and resources to support these efforts.

RESEARCH DESIGN

We conduct cross-sectional analysis of a national survey of physician practices (n=1776). We use logistic regression to predict advanced IT use in each of our domains based on safety net status and other organizational characteristics. We then use interaction models to assess whether ownership or network membership moderate the relationship between safety net status and advanced use of health IT.

RESULTS

Health IT use was common across primary care practices, but advanced use of health IT functionalities ranged only from 30% to 50% use. Safety net settings have kept pace with adoption of features for patient engagement and population management, yet lag in information exchange capabilities compared with nonsafety net practices (odds ratio=0.52 for federally qualified health centers, P<0.001; odds ratio=0.66 for other safety net, P=0.03). However, when safety net practices are members of a health system or practice network, health IT capabilities are comparable to nonsafety net sites.

CONCLUSIONS

All outpatient settings would benefit from improved electronic health record usability and implementation support that facilitates advanced use of health IT. Safety net practices, particularly those without other sources of centralized support, need targeted resources to maintain equitable access to information exchange capabilities.

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.

Examining the Relationship Between the Lean Management System and Quality Improvement Care Management Processes

BACKGROUND AND OBJECTIVES

The United States has an underperforming health care system on both cost and quality criteria in comparison with other developed countries. One approach to improving system performance on both cost and quality is to use the Lean Management System based on the Shingo principles originally developed by Toyota in Japan. Our objective was to examine the association between hospital use of the Lean Management System and evidence-based or recommended quality improvement care management processes.

METHODS

A cross-sectional analysis of data from 223 hospitals that responded to both the 2017 National Survey of Healthcare Organizations and Systems and the 2017 National Survey of Lean/Transformational Performance Improvement in Hospitals was conducted.

RESULTS

Controlling for hospital organizational and market characteristics, the number of years using Lean was positively associated with use of electronic health record-based decision support, use of quality-focused information management, use of evidence-based guidelines, and support for care transitions at the P < .05 level. The degree of education and training in Lean methods and processes was also positively associated ( P < .05) with greater support for care transitions. The number of years using Lean was marginally associated with screening for clinical conditions at the P < .10 level. There was an unexpected negative association between education and training scores and screening for clinical conditions.

CONCLUSIONS

Greater experience in using the Lean Management System is positively associated with several evidence-based and/or recommended quality improvement care management processes.

Competition and Integration of Health Systems in the Post-COVID-19 New Normal: Results from a Cross-Sectional Survey in the United States (Preprint)

Background

How do health systems in the United States view the concept of merger and acquisition (M&A) in a post-COVID 19 “new normal”? How do new entrants to the market and incumbents influence horizontal and vertical integration of health systems? Traditionally, it has been argued that M&A activity is designed to reduce inequities in the market, shift toward value-based care, or enhance the number and quality of health care offerings in a given market. However, the recent history of M&A activity has yielded fewer noble results. As might be expected, the smaller the geographical region in which M&A activity is pursued, the higher the likelihood that monopolistic tendencies will result.

Objective

We focused on three types of competition perceptions, external environment uncertainty–related competition, technology disruption–driven competition, and customer service–driven competition, and two integration plans, vertical integration and horizontal integration. We examined (1) how health system characteristics help discern competition perceptions and integration decisions, and (2) how environment-, technology-, and service-driven competition aspects influence vertical and horizontal integration among US health systems in the post-COVID-19 new normal.

Methods

We used data for this study collected through a consultant from a robust group of health system chief executive officers (CEOs) across the United States from February to March 2021. Among the 625 CEOs, 135 (21.6%) responded to our survey. We considered competition and integration aspects from the literature and ratified them via expert consensus. We collected secondary data from the Agency for Healthcare Research and Quality (AHRQ) Compendium of the US Health Systems, leading to a matched data set for 124 health systems. We used inferential statistical comparisons to assess differences across health systems regarding competition and integration, and we used ordered logit estimations to relate competition and integration.

Results

Health systems generally have a high level of the four types of competition perceptions, with the greatest concern being technology disruption–driven competition rather than environment uncertainty–related competition and customer service–driven competition. The first set of estimation results showed that size, teaching status, revenue, and uncompensated care burden are the main contingent factors influencing the three competition perceptions. The second set of estimation results revealed the relationships between different competition perceptions and integration plans. For vertical integration, environment uncertainty–related competition had a significant positive influence (P<.001), while the influence of technology disruption–driven competition was significant but negative (P<.001). The influence of customer service–driven competition on vertical integration was not evident. For horizontal integration, the results were similar for environment uncertainty–related competition and technology disruption–driven competition; however, the significance of technology disruption–driven competition was weak (P=.05). The influence of customer service–driven competition in the combined model was significant and negative (P<.001).

Conclusions

Competition-driven integration has subtle influences across health systems. Environment uncertainty–related competition is a significant factor, with underlying contingent factors such as revenue concerns and leadership as the leading causes of integration plans. However, technology disruption may hinder integrations. Undoubtedly, small- and low-revenue health systems facing a high level of competition are likely to merge to navigate the health care business successfully. This trend should be a focus of policy to avoid monopolistic markets.

Practice and market factors associated with provider volume of health information exchange

OBJECTIVE

To assess the practice- and market-level factors associated with the amount of provider health information exchange (HIE) use.

MATERIALS AND METHODS

Provider and practice-level data was drawn from the Meaningful Use Stage 2 Public Use Files from the Centers for Medicare and Medicaid Services, the Physician Compare National Downloadable File, and the Compendium of US Health Systems, among other sources. We analyzed the relationship between provider HIE use and practice and market factors using multivariable linear regression and compared primary care providers (PCPs) to non-PCPs. Provider volume of HIE use is measured as the percentage of referrals sent with electronic summaries of care (eSCR) reported by eligible providers attesting to the Meaningful Use electronic health record (EHR) incentive program in 2016.

RESULTS

Providers used HIE in 49% of referrals; PCPs used HIE in fewer referrals (43%) than non-PCPs (57%). Provider use of products from EHR vendors was negatively related to HIE use, while use of Athenahealth and Greenway Health products were positively related to HIE use. Providers treating, on average, older patients and greater proportions of patients with diabetes used HIE for more referrals. Health system membership, market concentration, and state HIE consent policy were unrelated to provider HIE use.

DISCUSSION

HIE use during referrals is low among office-based providers with the capability for exchange, especially PCPs. Practice-level factors were more commonly associated with greater levels of HIE use than market-level factors.

CONCLUSION

This furthers the understanding that market forces, like competition, may be related to HIE adoption decisions but are less important for use once adoption has occurred.

Hospital-based health systems 20 years later: A taxonomy for policy research and analysis

OBJECTIVE

Building on the original taxonomy of hospital-based health systems from 20 years ago, we develop a new taxonomy to inform emerging public policy and practice developments.

DATA SOURCES

The 2016 American Hospital Association's (AHA) Annual Survey; the 2016 IQVIA Healthcare Organizations and Systems (HCOS) database; and the 2017-2018 National Survey of Healthcare Organizations and Systems (NSHOS).

STUDY DESIGN

Cluster analysis of the 2016 AHA Annual Survey data to derive measures of differentiation, centralization, and integration to create categories or types of hospital-based health systems.

DATA COLLECTION

Principal components factor analysis with varimax rotation generating the factors used in the cluster algorithms.

PRINCIPAL FINDINGS

Among the four cluster types, 54% (N = 202) of systems are decentralized (-0.35) and relatively less differentiated (-0.37); 23% of systems (N = 85) are highly differentiated (1.28) but relatively decentralized (-0.29); 15% (N = 57) are highly centralized (2.04) and highly differentiated (0.65); and approximately 9 percent (N = 33) are least differentiated (-1.35) and most decentralized (-0.64). Despite differences in calculation, the Highly Centralized, Highly Differentiated System Cluster and the Undifferentiated, Decentralized System Cluster were similar to those identified 20 years ago. The other two system clusters contained similarities as well as differences from those 20 years ago. Overall, 82 percent of the systems remain relatively decentralized suggesting they operate largely as holding companies allowing autonomy to individual hospitals operating within the system.

CONCLUSIONS

The new taxonomy of hospital-based health systems bears similarities as well as differences from 20 years ago. Important applications of the taxonomy for addressing current challenges facing the healthcare system, such as the transition to value-based payment models, continued consolidation, and the growing importance of the social determinants of health, are highlighted.

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.

Mind the clinical-analytic gap: Electronic health records and COVID-19 pandemic response

Data quality is essential to the success of the most simple and the most complex analysis. In the context of the COVID-19 pandemic, large-scale data sharing across the US and around the world has played an important role in public health responses to the pandemic and has been crucial to understanding and predicting its likely course. In California, hospitals have been required to report a large volume of daily data related to COVID-19. In order to meet this need, electronic health records (EHRs) have played an important role, but the challenges of reporting high-quality data in real-time from EHR data sources have not been explored.

We describe some of the challenges of utilizing EHR data for this purpose from the perspective of a large, integrated, mixed-payer health system in northern California, US. We emphasize some of the inadequacies inherent to EHR data using several specific examples, and explore the clinical-analytic gap that forms the basis for some of these inadequacies. We highlight the need for data and analytics to be incorporated into the early stages of clinical crisis planning in order to utilize EHR data to full advantage. We further propose that lessons learned from the COVID-19 pandemic can result in the formation of collaborative teams joining clinical operations, informatics, data analytics, and research, ultimately resulting in improved data quality to support effective crisis response.

Estimates of ACO savings in the presence of provider and beneficiary selection

BACKGROUND

Medicare's accountable care organizations (ACOs)-designed to improve quality and lower spending-were associated with growing savings in previous studies. However, savings estimates may be biased by beneficiary sorting among providers based on healthcare needs and by providers opting into the program based on anticipated gains.

METHODS

Using Medicare administrative claims (2009-2014), we compared annual spending changes after provider organizations joined ACOs to changes in non-ACOs (controls). To address provider selection, using novel data to identify non-ACO organizations, we restricted controls to comparably large provider organizations. To address beneficiary selection, we (a) estimated within-organization (including non-ACO comparison organizations) spending changes, (b) estimated within-beneficiary spending changes, (c) incorporated beneficiaries without qualifying healthcare expenses, and (d) used a fixed beneficiary ACO assignment using the pre-ACO period.

RESULTS

Each year, 19% of Medicare beneficiaries switched provider organizations. Spending was higher for switchers than stayers ($3163, p < .001) and grew more the next year ($2004; p < .001). Starting from a baseline regression modeled on previous ACO evaluations, estimated savings varied widely as we sequentially introduced methods to address selection. Combining methods, however, generated more stable estimated ACO savings of $46 (p = .022), averaged across cohorts.

CONCLUSIONS

When implementing a comprehensive suite of methods to adjust for provider and beneficiary selection, we estimated ACO savings that grew over time. Our estimates are in line with, but smaller than, previous estimates in the literature. Implementing piecemeal adjustments produced misleading results.

IMPLICATIONS

Our results confirm the importance of selection for savings estimates and for provider organizations managing costs and quality. Attribution rules that consider multiple years may help mitigate the impact of beneficiary churn for providers and payers. Implementing payment reform by randomizing early participants, or implementing fully across selected markets, may better serve efforts to evaluate and improve payment models.

LEVEL OF EVIDENCE

Level 3.

Avoiding Medicaid: Characteristics Of Primary Care Practices With No Medicaid Revenue

Primary care access for Medicaid patients is an ongoing area of concern. Most studies of providers' participation in Medicaid have focused on factors associated with the Medicaid program, such as reimbursement rates. Few studies have examined the characteristics of primary care practices associated with Medicaid participation. We used a nationally representative survey of primary care practices to compare practices with no, low, and high Medicaid revenue. Seventeen percent of practices received no Medicaid revenue; 38 percent and 45 percent were categorized as receiving low and high Medicaid revenue, respectively. Practices with no Medicaid revenue were more often small, independent, and located in urban areas with higher household income. These practices also have lower population health capabilities.

Health system integration with physician specialties varies across markets and system types

OBJECTIVE

To examine system integration with physician specialties across markets and the association between local system characteristics and their patterns of physician integration.

DATA SOURCES

Data come from the AHRQ Compendium of US Health Systems and IQVIA OneKey database.

STUDY DESIGN

We examined the change from 2016 to 2018 in the percentage of physicians in systems, focusing on primary care and the 10 most numerous nonhospital-based specialties across the 382 metropolitan statistical areas (MSAs) in the US. We also categorized systems by ownership, mission, and payment program participation and examined how those characteristics were related to their patterns of physician integration in 2018.

DATA COLLECTION/EXTRACTION METHODS

We examined local healthcare markets (MSAs) and the hospitals and physicians that are part of integrated systems that operate in these markets. We characterized markets by hospital and insurer concentration and systems by type of ownership and by whether they have an academic medical center (AMC), a 340B hospital, or accountable care organization.

PRINCIPAL FINDINGS

Between 2016 and 2018, system participation increased for primary care and the 10 other physician specialties we examined. In 2018, physicians in specialties associated with lucrative hospital services were the most commonly integrated with systems including hematology-oncology (57%), cardiology (55%), and general surgery (44%); however, rates varied substantially across markets. For most specialties, high market concentration by insurers and hospital-systems was associated with lower rates of physician integration. In addition, systems with AMCs and publicly owned systems more commonly affiliated with specialties unrelated to the physicians' potential contribution to hospital revenue, and investor-owned systems demonstrated more limited physician integration.

CONCLUSIONS

Variation in physician integration across markets and system characteristics reflects physician and systems' motivations. These integration strategies are associated with the financial interests of systems and other strategic goals (eg, medical education, and serving low-income populations).

Organizational integration, practice capabilities, and outcomes in clinically complex medicare beneficiaries

OBJECTIVE

To assess the association between clinical integration and financial integration, quality-focused care delivery processes, and beneficiary utilization and outcomes.

DATA SOURCES

Multiphysician practices in the 2017-2018 National Survey of Healthcare Organizations and Systems (response rate 47%) and 2017 Medicare claims data.

STUDY DESIGN

Cross-sectional study of Medicare beneficiaries attributed to physician practices, focusing on two domains of integration: clinical (coordination of patient services, use of protocols, individual clinician measures, access to information) and financial (financial management and planning across operating units). We examined the association between integration domains, the adoption of quality-focused care delivery processes, beneficiary utilization and health-related outcomes, and price-adjusted spending using linear regression adjusting for practice and beneficiary characteristics, weighting to account for sampling and nonresponse.

DATA COLLECTION/EXTRACTION METHODS

1 604 580 fee-for-service Medicare beneficiaries aged 66 or older attributed to 2113 practices. Of these, 414 209 beneficiaries were considered clinically complex (frailty or 2 + chronic conditions).

PRINCIPAL FINDINGS

Financial integration and clinical integration were weakly correlated (correlation coefficient = 0.19). Clinical integration was associated with significantly greater adoption of quality-focused care delivery processes, while financial integration was associated with lower adoption of these processes. Integration was not generally associated with reduced utilization or better beneficiary-level health-related outcomes, but both clinical integration and financial integration were associated with lower spending in both the complex and noncomplex cohorts: (clinical complex cohort: -$2518, [95% CI: -3324, -1712]; clinical noncomplex cohort: -$255 [95% CI: -413, -97]; financial complex cohort: -$997 [95% CI: -$1320, -$679]; and financial noncomplex cohort: -$143 [95% CI: -210, -$76]).

CONCLUSIONS

Higher levels of financial integration were not associated with improved care delivery or with better health-related beneficiary outcomes. Nonfinancial forms of integration deserve greater attention, as practices scoring high in clinical integration are more likely to adopt quality-focused care delivery processes and have greater associated reductions in spending in complex patients.

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.

Can vertically integrated health systems provide greater value: The case of hospitals under the comprehensive care for joint replacement model?

OBJECTIVE

We aim to assess whether system providers perform better than nonsystem providers under an alternative payment model that incentivizes high-quality, cost-efficient care. We posit that the payment environment and the incentives it provides can affect the relative performance of vertically integrated health systems. To examine this potential influence, we compare system and nonsystem hospitals participating in Medicare's Comprehensive Care for Joint Replacement (CJR) model.

DATA SOURCES

We used hospital cost and quality data from the Centers for Medicare & Medicaid Services linked to data from the Agency for Healthcare Research and Quality's Compendium of US Health Systems and hospital characteristics from secondary sources. The data include 706 hospitals in 67 metropolitan areas.

STUDY DESIGN

We estimated regressions that compared system and nonsystem hospitals' 2017 cost and quality performance providing lower joint replacements among hospitals required to participate in CJR.

PRINCIPAL FINDINGS

Among CJR hospitals, system hospitals that provided comprehensive services in their local market had 5.8 percent ($1612) lower episode costs (P = .01) than nonsystem hospitals. System hospitals that did not provide such services had 3.5 percent ($967) lower episode costs (P = .14). Quality differences between system hospitals and nonsystem hospitals were mostly small and statistically insignificant.

CONCLUSIONS

When operating under alternative payment model incentives, vertical integration may enable hospitals to lower costs with similar quality scores.

Safely Practicing in a New Environment: A Qualitative Study to Inform Physician Onboarding Practices

BACKGROUND

Physicians are frequently asked to practice in hospitals different from their home institution, often under contracts called professional service agreements (PSAs). With highly variable onboarding processes, traveling physicians are often left to "figure out" the available resources, processes of care, crucial relationships, and culture of the new institution. This research aimed to understand the current practices of onboarding for the purpose of informing future improvements in practice.

METHODS

Two physicians conducted semistructured, in-depth interviews with physicians working at hospitals beyond their home institution. A thematic qualitative analysis was performed.

RESULTS

The sample included 20 physicians from six specialties. Key findings include (1) the basic logistics of providing care in a new environment are often not incorporated into physician onboarding and can limit physicians' ability to provide care efficiently and effectively; (2) the strength of interpersonal relationships greatly influences the ability of physicians to get help when working in new environments; and (3) managing clinical emergencies in unfamiliar settings can result in significant perceived risk to patient safety due to delays in providing care.

CONCLUSION

The onboarding process, for physicians working in new institutions, provides significant opportunity for improvement. In the future, more work is needed to ensure that the most notable differences between institutions are clarified, physicians have the necessary information and professional relationships to handle emergencies, and they know which patients they can safely care for in their new institution.