Assessing Trends in Hospital System Structures From 2008 to 2015.

BACKGROUND: The Affordable Care Act introduced a major systematic change aimed to promote coordination across the care continuum. Yet, it remains unknown the extent to which hospital system structures have changed following the Affordable Care Act. The structure of hospital systems has important implications for the cost, quality, and accessibility of health services. OBJECTIVES: To assess trends in the structures of hospital systems. RESEARCH DESIGN: We aggregated data from the American Hospital Association (AHA) Annual Survey to the system level. Using a panel of hospital systems from 2008 to 2015, we assessed trends in the number of hospital systems, their size, ownership characteristics, geospatial arrangements, and integration with outpatient services. RESULTS: In the period 2008-2015, there was an increasing percentage of hospitals that were system affiliated as well as growth in the number of hospital systems. A greater percentage of hospital systems that were organized as moderately centralized systems transitioned to centralized systems than to decentralized systems (19.8% vs. 4.7%; P<0.001). In terms of geospatial arrangement, a greater percentage of hub-and-spoke systems moved to a regional design than to national systems (20.0% vs. 8.2%; P<0.05). An increasing trend over time toward greater integration with outpatient services was found in a measure of total system level integration with outpatient services. CONCLUSIONS: Our findings suggest that hospital systems may be moving toward more regional designs. In addition, the trend of increasing integration offered across hospital systems overall, and as portion of total integration, suggests that systems may be increasing their services along the continuum of care.

Factors related to health information exchange participation and use.

This study examines factors facilitating and delaying participation and use of the Health Information Exchange (HIE) in Louisiana. Semi-structured qualitative interviews were conducted with health care representatives throughout the state. Findings suggest that Meaningful Use requirements are a critical factor influencing the decision to participate in the HIE, specifically the mandate that hospitals be able to electronically transfer summary of care documents. Creating buy-in within a few large hospital networks legitimized the HIE and hastened interest in those markets. Fees charged by electronic health record (EHR) vendors to develop HIE interfaces have been prohibitive. Funding from the federal incentive program is intended to offset the costs associated with EHR implementation and increase the likelihood that HIEs can provide value to the population; however, costs and time delays of EHR interface development may be key barriers to fully integrated HIEs. State HIEs may benefit from targeted involvement of state health care leaders who can champion the potential value of the HIE.

Quality Improvement Strategies in Accountable Care Organization Hospitals.

BACKGROUND: Accountable Care Organizations (ACOs) are hoped to lower costs and improve health care quality. However, hospitals remain unsure how to bring about the quality improvement (QI) required to increase financial viability. This success may hinge on the use of sophisticated measurement tracking and the use of multiple QI tools. This study aims to assess the current approaches that ACO hospitals are using to improve quality and to compare their strategies with non-ACO hospitals. METHODS: The 2013 American Hospital Association's Annual Survey and the Survey of Care Systems and Payment data were merged to identify ACO and non-ACO hospitals. ACO and non-ACO hospital rates of reported use of multiple QI tools and the ability to detect and track readmissions across organizational boundaries were compared. RESULTS: ACO hospitals were significantly less likely to use only 1 QI tool (43.5% vs 65.2%; P < .001) and more likely to use 2 (36.4% vs 28.1%; P < .05), 3 (12.1% vs 6.5%; P < .001), or 4 (8.0% vs 0.2%; P < .001) QI tools. ACO hospitals were significantly more likely to have the capability to detect readmissions (34.1% vs 22.8%; P < .001) and track readmissions (90.5% vs 85.7%; P < .05). CONCLUSIONS: Results suggest that ACO hospitals are incorporating more sophisticated measurements and combinations of QI tools than non-ACO hospitals. It remains to be seen whether this leads to accelerated changes across the quality domains in ACO hospitals.

Accountable care organization hospitals differ in health IT capabilities.

OBJECTIVES: The aim of this study was to evaluate health information technology (IT) adoption in hospitals participating in accountable care organizations (ACOs) and compare this adoption to non-ACO hospitals. STUDY DESIGN: A cross-sectional sample of US nonfederal, acute care hospitals with data from 3 matched sources: the 2013 American Hospital Association (AHA) Annual Survey, the 2013 AHA Survey of Care Systems and Payments (CSP), and the 2014 AHA Information Technology Supplement. METHODS: To compare health IT adoption in ACO- and non-ACO hospitals, we created measures of Meaningful Use (MU) Stage 1 and Stage 2 core and menu criteria, patient engagement-oriented health IT, and health information exchange (HIE) participation. Adoption was compared using both naïve and multivariate logit models. RESULTS: Of the 393 ACO hospitals and 810 non-ACO hospitals, a greater percentage of ACO hospitals were capable of meeting MU Stage 1 (50.9% vs 41.6%; P < .01) and Stage 2 (7.6% vs 4.8%; P < .05), having patient engagement health IT (39.8% vs 15.2%; P < .001), and participating in HIE (49.0% vs 30.1%; P < .001). In adjusted models, no difference was found between ACO and non-ACO hospital ability to meet MU Stage 1 or Stage 2, but ACO hospitals were more likely to have patient engagement health IT (odds ratio (OR), 2.20; 95% CI, 1.59-3.04) and be HIE participants (OR, 1.41; 95% CI, 1.03-1.92). CONCLUSIONS: ACO-participating hospitals appear to be focused more on adopting health IT that aligns with broader strategic goals rather than those that achieve MU. Aligning adoption with quality and payment reform may be a productive path forward to encourage hospital health IT adoption behavior.

Does Insurance Status Affect the Management of Acute Clavicle Fractures?

OBJECTIVES: To evaluate whether insurance is an unrecognized factor that plays a role in determining whether a patient receives surgery. METHODS: A retrospective cross-sectional analysis was performed using the Healthcare Cost and Utilization Project data for Florida in the year 2010. Discharge level data from emergency departments and ambulatory surgery settings were used to identify clavicle fractures by International Classification of Diseases 9 codes 81,000, 81,002, and 81,003. Internal fixation was identified using the Current Procedural Terminology code 23,515. Clavicle fractures that did not result in a Current Procedural Terminology code of 23,515 were assumed to have been managed nonoperatively. Multivariate logistic regression, allowing for intragroup correlation among surgeons, was used to determine the influence of payer source on treatment modality adjusting for race, age, number of chronic conditions, and sex. RESULTS: In total, there were 7858 clavicle fractures that met criteria for inclusion. Observations were removed from the analysis if there was missing personal demographic data or if the ability to track patients from the emergency department to follow-up care was not possible. Therefore, the final sample consisted of 5185 clavicle fractures of which 233 received internal fixation (4.5%). The odds of a patient with private insurance receiving internal fixation was 7.58 times [95% confidence interval (CI) = (4.04 to -14.21), P < 0.001] greater than a self-pay patient, all else being held constant. Patients defined by "other" sources of coverage, a group that includes worker's compensation, CHAMPUS (military), CHAMPVA (veterans), or other government insurance other than Medicare and Medicaid were also associated with an increased likelihood of receiving internal fixation by a factor of 6.80 (95% CI = 3.15, 14.64, P < 0.001) relative to self-pay patients, all else being held constant. The likelihood of patients with Medicare or Medicaid receiving internal fixation did not differ statistically from self-pay patients. CONCLUSIONS: Patients with any form of insurance, when compared with the self-pay, Medicare, and Medicaid populations, had a higher likelihood of operative intervention in Florida in 2010. This may represent an unintended trend in treatment. LEVEL OF EVIDENCE: Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.