Efficiency and profitability in US not-for-profit hospitals.

This article examines the relationship between hospital profitability and efficiency. A cross-section of 1317 U.S. metropolitan, acute care, not-for-profit hospitals for the year 2015 was employed. We use a frontier method, stochastic frontier analysis, to estimate hospital efficiency. Total margin and operating margin were used as profit variables in OLS regressions that were corrected for heteroskedacity. In addition to estimated efficiency, control variables for internal and external correlates of profitability were included in the regression models. We found that more efficient hospitals were also more profitable. The results show a positive relationship between profitability and size, concentration of output, occupancy rate and membership in a multi-hospital system. An inverse relationship was found between profits and academic medical centers, average length of stay, location in a Medicaid expansion state, Medicaid and Medicare share of admissions, and unemployment rate. The results of a Hausman test indicates that efficiency is exogenous in the profit equations. The findings suggest that not-for-profit hospitals will be responsive to incentives for increasing efficiency and use market power to increase surplus to pursue their objectives.

Strategic Differentiation of High-Tech Services in Local Hospital Markets.

This study assesses organizational and market factors related to high-tech service differentiation in local hospital markets. The sample includes 1704 nonfederal, general acute hospitals in urban counties in the United States. We relate organizational and market factors in 2011 to service differentiation in 2013, using ordinary least squares regression. Data are compiled from the American Hospital Association Annual Survey of Hospitals, Area Resource File, and Centers for Medicare and Medicaid Services. Results show that hospitals differentiate more services relative to market rivals if they are larger than the rival and if the hospitals are further apart geographically. Hospitals differentiate more services if they are large, teaching, and nonprofit or public and if they face more market competition. Hospitals differentiate fewer services from rivals if they belong to multihospital systems. The findings underscore the pressures that urban hospitals face to offer high-tech services despite the potential of high-tech services to drive hospital costs upward.

"Precision health" for high-need, high-cost patients.

It is increasingly clear that high-need, high-cost patients are not a homogenous group, but rather a diverse set of patients with varied circumstances and needs. Acting on this insight requires comprehensive data networks we have not traditionally had, and most analyses to date have focused primarily on claims data. We argue that making clinical and financial gains will require data-sharing networks that integrate clinical factors, genomic information, and social determinants from multiple health systems. Investing in these networks may allow us to better anticipate the unique needs of patients, conceptualize care models to meet those needs, and put targeted interventions into action.

Expanding Palliative Medicine across Care Settings: One Health System Experience.

BACKGROUND: The success of our hospital-based Palliative Care program stimulated requests to duplicate the program across the health system continuum of care. OBJECTIVE: To develop a model of care focused on a high-need, high-cost population that could be implemented across all care settings, including hospitals and patients' homes. METHODS: To fiscally support program expansion from hospital to home, we conducted a retrospective cost analysis for home-based Palliative Care (HBPC)-enrolled patients with continuous claims months before program enrollment through date of death. The HBPC enrollees were evaluated against a cohort group of CMS (Centers for Medicare & Medicaid Service) and Medicare Advantage patients who did not participate in the HBPC program (n = 3135). Twenty-one months of claims leading up to the date of death were evaluated for both populations. The analysis was designed to test whether Palliative Care patients demonstrated less overall claims expense and service utilization in the same periods as patients without Palliative Care. Claim months were grouped into three-month clusters for evaluation and statistical testing of per member per month utilization and cost. RESULTS: Overall, HBPC patients demonstrated significantly less service utilization and cost in the months leading up to death. Cost differences were primarily driven by clear cost divergence in the last three months of life [$9,843 (PC) vs. $27,530 (C)]. Our program grew from a hospital-based program to include the establishment of a home-based program. CONCLUSION: Palliative Care programs can successfully expand outside hospital walls to serve a high need/high-cost patient population.

Code Conversion Impact Factor and Cash Flow Impact of International Classification of Diseases, 10th Revision, on a Large Multihospital Radiology Practice.

PURPOSE: The 2015 conversion of the International Classification of Diseases (ICD) system from the ninth revision (ICD-9) to the 10th revision (ICD-10) was widely projected to adversely impact physician practices. We aimed to assess code conversion impact factor (CCIF) projections and revenue delay impact to help radiology groups better prepare for eventual conversion to ICD, 11th revision (ICD-11). METHODS: Studying 673,600 claims for 179 radiologists for the first year after ICD-10's implementation, we identified primary ICD-10 codes for the top 90th percentile of all examinations for the entire enterprise and each subspecialty division. Using established methodology, we calculated CCIFs (actual ICD-10 codes ÷ prior ICD-9 codes). To assess ICD-10's impact on cash flow, average monthly days in accounts receivable status was compared for the 12 months before and after conversion. RESULTS: Of all 69,823 ICD-10 codes, only 7,075 were used to report primary diagnoses across the entire practice, and just 562 were used to report 90% of all claims, compared with 348 under ICD-9. This translates to an overall CCIF of 1.6 for the department (far less than the literature-predicted 6). By subspecialty division, CCIFs ranged from 0.7 (breast) to 3.5 (musculoskeletal). Monthly average days in accounts receivable for the 12 months before and after ICD-10 conversion did not increase. CONCLUSION: The operational impact of the ICD-10 transition on radiology practices appears far less than anticipated with respect to both CCIF and delays in cash flow. Predictive models should be refined to help practices better prepare for ICD-11.

Corporate Investors Increased Common Ownership In Hospitals And The Postacute Care And Hospice Sectors.

The sharing of investors across firms is a new antitrust focus because of its potential negative effects on competition. Historically, the ability to track common investors across the continuum of health care providers has been limited. Thus, little is known about common investor ownership structures that might exist across health care delivery systems and how these linkages have evolved over time. We used data from the Provider Enrollment, Chain, and Ownership System of the Centers for Medicare and Medicaid Services to identify common investor ownership linkages across the acute care, postacute care, and hospice sectors within the same geographic markets. To our knowledge, this study provides the first description of common investor ownership trends in these sectors. We found that the percentage of acute care hospitals having common investor ties to the postacute or hospice sectors increased from 24.6 percent in 2005 to 48.9 percent in 2015. These changes have important implications for antitrust, payment, and regulatory policies.

As for-profits stumble, regional systems pick up the pieces.

Some regional not-for-profit systems see acquiring the hospital assets of struggling for-profit operators as a way to gain referrals, expand their provider networks and consolidate their regions.

'We asked what services ... could be better performed at centers of excellence throughout the system'.

After becoming CEO of the near bankrupt Mount Sinai Medical Center in New York City in 2003, Dr. Kenneth Davis led a notable financial turnaround with the help of a board filled with some of New York City's wealthiest businessmen. Now, as head of a financially robust system that includes seven hospitals, 7,100 employed physicians and a sprawling network of practices and ambulatory centers that stretches from Westchester County to Florida, he is attempting to lead Mount Sinai into the new era of population health management and affordable care. Modern Healthcare Editor Merrill Goozner asked him about key elements in that transition. This is an edited transcript.

Capital Investment by Independent and System-Affiliated Hospitals.

Capital expenditures are a critical part of hospitals' efforts to maintain quality of patient care and financial stability. Over the past 20 years, finding capital to fund these expenditures has become increasingly challenging for hospitals, particularly independent hospitals. Independent hospitals struggling to find ways to fund necessary capital investment are often advised that their best strategy is to join a multi-hospital system. There is scant empirical evidence to support the idea that system membership improves independent hospitals' ability to make capital expenditures. Using data from the American Hospital Association and Medicare Cost Reports, we use difference-in-difference methods to examine changes in capital expenditures for independent hospitals that joined multi-hospital systems between 1997 and 2008. We find that in the first 5 years after acquisition, capital expenditures increase by an average of almost $16,000 per bed annually, as compared with non-acquired hospitals. In later years, the difference in capital expenditure is smaller and not statistically significant. Our results do not suggest that increases in capital expenditures vary by asset age or the size of the acquiring system.

Is the system really the solution? Operating costs in hospital systems.

Hospital system formation has recently accelerated. Executives emphasize scale economies that lower operating costs, a claim unsupported in academic research. Do systems achieve lower costs than freestanding facilities, and, if so, which system types? We test hypotheses about the relationship of cost with membership in systems, larger systems, and centralized and local hub-and-spoke systems. We also test whether these relationships have changed over time. Examining 4,000 U.S. hospitals during 1998 to 2010, we find no evidence that system members exhibit lower costs. However, members of smaller systems are lower cost than larger systems, and hospitals in centralized systems are lower cost than everyone else. There is no evidence that the system's spatial configuration is associated with cost, although national system hospitals exhibit higher costs. Finally, these results hold over time. We conclude that while systems in general may not be the solution to lower costs, some types of systems are.