Association of Measured Quality and Future Financial Performance Among Hospitals Performing Cardiac Surgery.

GOAL: For decades, hospitals performing cardiac surgery have carried the cost of implementing quality improvement activities and reporting quality outcomes. However, the financial return of such investments is unclear, which weakens the incentive for hospitals to invest in quality improvement activities. This study explored the relationship between a hospital's measured quality and its financial performance. METHODS: Using data from the American Hospital Association and Hospital Compare from 2014 to 2018, we performed an observational study of hospitals performing cardiac surgery. We used mixed-effects regression models with fixed-year effects and random intercepts to explore associations between measured quality and hospital financial performance. Our dependent variables were margins (profit divided by revenue) and financial distress; our independent variables included Patient Safety Indicator 90 (PSI-90) and hospital characteristics. PRINCIPAL FINDINGS: Our sample included 4,927 hospital-years from 1,209 unique hospitals. Hospitals in the worst-performing PSI-90 score quartile experienced a lower operating margin (-1.26%, 95% CI [-2.10 to -0.41], p = .004), a lower total margin (-0.92%, 95% CI [-1.66 to -0.17], p = .016), and an increased odds of financial distress in the next year (OR: 2.12, 95% CI [1.36-3.30], p = .001) when compared with the best-performing hospitals. PRACTICAL APPLICATIONS: Our exploration into financial distress provides managers with a better understanding of the relationship between a hospital's measured quality and its financial position. In reflecting on our findings, hospital leaders may consider viewing patient safety as a modifiable factor that can improve their organization's overall financial health. Our findings suggest that excellent safety performance may be both financially and clinically beneficial to hospitals.

Orthopaedic surgery after COVID-19 - A blueprint for resuming elective surgery after a pandemic.

BACKGROUND: The COVID-19 outbreak was fraught with danger and despair as many medically necessary surgeries were cancelled to preserve precious healthcare resources and mitigate disease transmission. As the rate of infection starts to slow, healthcare facilities and economies attempt to return to normalcy in a graduated manner and the massive pent-up demand for surgeries needs to eventually be addressed in a systematic and equitable manner. MATERIALS AND METHODS: Guidelines from the Alliance of International Organizations of Orthopaedics and Traumatology, Orthopaedic Trauma Association, American College of Surgeons, American Society of Anaesthesiologists, Association of perioperative Registered Nurses, American Hospital Association, Centers for Medicare and Medicaid Services, World Health Organization and Centers for Disease Control and Prevention were evaluated and summarized into a working framework, relevant to orthopaedic surgeons. RESULTS: The guiding principles for restarting elective surgeries in a safe and acceptable manner include up-to-date disease awareness, projection and judicious management of equipment and facilities, effective human resource management, a fair and transparent system to prioritize cases, optimization of peri-operative workflows and continuous data gathering and clinical governance. CONCLUSION: The world was ill prepared for the initial COVID-19 outbreak. However, with effective forward planning, institutions can ramp-up elective surgical caseload in a safe and equitable manner.

Comparison of Risk-Standardized Readmission Rates of Surgical Patients at Safety-Net and Non-Safety-Net Hospitals Using Agency for Healthcare Research and Quality and American Hospital Association Data.

Importance: Medical patients discharged from safety-net hospitals (SNHs) experience higher readmission rates compared with those discharged from non-SNHs. However, little is known about whether this association persists for surgical patients. Objectives: To examine differences in readmission rates between SNHs and non-SNHs among surgical patients after discharge and determine whether hospital characteristics might account for some of the variation. Design, Setting, and Participants: This observational retrospective study linked the Healthcare Cost and Utilization Project State Inpatient Databases of the Agency for Healthcare Research and Quality from January 1, 2011, through December 31, 2014, for 4 states (New York, Florida, Iowa, and Washington) with data from the 2014 American Hospital Association annual survey. After identifying surgical discharges, SNHs were defined as those with the top quartile of inpatient stays paid by Medicaid or self-paid. Hospital-level risk-standardized readmission rates (RSRRs) for surgical discharges were calculated. The association between hospital RSRRs and hospital characteristics was evaluated with bivariate analyses. An estimated multivariable hierarchical linear regression model was used to examine variation in hospital RSRRs, adjusting for hospital characteristics, state, year, and SNH status. Data were analyzed from June 1, 2017, through March 1, 2018. Exposures: Surgical care at an SNH. Main Outcomes and Measures: Readmission after an index surgical admission. Results: A total of 1 252 505 patients across all 4 years and states were included in the analysis (51.7% women; mean [SD] age, 52.7 [18.1] years). Bivariate analyses found that SNHs had higher mean (SD) surgical RSRRs compared with non-SNHs; significant differences were found for New York (9.6 [0.1] vs 10.9 [0.1]; P < .001) and Florida (11.6 [0.1] vs 12.1 [0.1]; P = .001). The SNHs also had higher RSRRs in these 2 states when stratified by hospital funding (nonfederal government SNHs in New York, 11.9 [0.2]; for-profit, private SNHs in Florida, 13.1 [0.2]; P < .001 for both); however, bed size was a significant factor for higher mean (SD) RSRRs only for New York (200 to 399 beds, 12.0 [0.4]; P = .006). Similar results were found for multivariable linear regression models; RSRRs were 1.02% higher for SNHs compared with non-SNHs (95% CI, 0.75%-1.29%; P < .001). Increased RSRRs were observed for hospitals in New York and Florida, teaching hospitals, and investor-owned hospitals. Factors associated with reduced RSRRs included presence of an ambulatory surgery center, cardiac catheterization capabilities, and high surgical volume. Conclusions and Relevance: According to results of this study, surgical patients treated at SNHs experienced slightly higher RSRRs compared with those treated at non-SNHs. This association persisted after adjusting for year, state, and hospital factors, including teaching status, hospital bed size, and hospital volume.

The seesaw of CVD: Deaths down, costs up.

Coronary heart disease deaths will decline by 30% between 2010 and 2020 because of improvement in "cardiovascular health metrics" (avoidance of smoking, more physical activity, and so on). But this less-deadly era of CVD is going to be a more costly one, with direct medical costs of CVD more than doubling by 2030 to $918 billion from $396 billion in 2012.

Measuring the Volume-Outcome Relation for Complex Hospital Surgery.

BACKGROUND: Prominent studies continue to measure the hospital volume-outcome relation using simple logistic or random-effects models. These regression models may not appropriately account for unobserved differences across hospitals (such as differences in organizational effectiveness) which could be mistaken for a volume outcome relation. OBJECTIVE: To explore alternative estimation methods for measuring the volume-outcome relation for six major cancer operations, and to determine which estimation method is most appropriate. METHODS: We analyzed patient-level hospital discharge data from three USA states and data from the American Hospital Association Annual Survey of Hospitals from 2000 to 2011. We studied six major cancer operations using three regression frameworks (logistic, fixed-effects, and random-effects) to determine the correlation between patient outcome (mortality) and hospital volume. RESULTS: For our data, logistic and random-effects models suggest a non-zero volume effect, whereas fixed-effects models do not. Model-specification tests support the fixed-effects or random-effects model, depending on the surgical procedure; the basic logistic model is always rejected. Esophagectomy and rectal resection do not exhibit significant volume effects, whereas colectomy, pancreatic resection, pneumonectomy, and pulmonary lobectomy do. CONCLUSIONS: The statistical significance of the hospital volume-outcome relation depends critically on the regression model. A simple logistic model cannot control for unobserved differences across hospitals that may be mistaken for a volume effect. Even when one applies panel-data methods, one must carefully choose between fixed- and random-effects models.

Communication that heals: mindful communication practices from palliative care leaders.

Though research has begun to highlight the centrality of communication in palliative care, studies have yet to focus on the use of mindful communication. Mindful communication is associated with increases in patient care and decreases in physician burnout. Through in-depth, semi-structured interviews the authors sought mindful communication practices from palliative care leaders in American Hospital Association Circle of Life® award-wining units. Four key mindful communication practices emerged: Know your audience, ask questions, discard scripts, and recognize your role. The discussion articulates how key mindful communication practices may be used as a stage model, where key practices may be used individually or in concert, by sole practitioners or within interdisciplinary teams and by new and seasoned clinicians. Theoretical contributions and areas for future inquiry are also discussed.

Hospital Characteristics Associated With Penalties in the Centers for Medicare & Medicaid Services Hospital-Acquired Condition Reduction Program.

IMPORTANCE: In fiscal year (FY) 2015, the Centers for Medicare & Medicaid Services (CMS) instituted the Hospital-Acquired Condition (HAC) Reduction Program, which reduces payments to the lowest-performing hospitals. However, it is uncertain whether this program accurately measures quality and fairly penalizes hospitals. OBJECTIVE: To examine the characteristics of hospitals penalized by the HAC Reduction Program and to evaluate the association of a summary score of hospital characteristics related to quality with penalization in the HAC program. DESIGN, SETTING, AND PARTICIPANTS: Data for hospitals participating in the FY2015 HAC Reduction Program were obtained from CMS' Hospital Compare and merged with the 2014 American Hospital Association Annual Survey and FY2015 Medicare Impact File. Logistic regression models were developed to examine the association between hospital characteristics and HAC program penalization. An 8-point hospital quality summary score was created using hospital characteristics related to volume, accreditations, and offering of advanced care services. The relationship between the hospital quality summary score and HAC program penalization was examined. Publicly reported process-of-care and outcome measures were examined from 4 clinical areas (surgery, acute myocardial infarction, heart failure, pneumonia), and their association with the hospital quality summary score was evaluated. EXPOSURES: Penalization in the HAC Reduction Program. MAIN OUTCOMES AND MEASURES: Hospital characteristics associated with penalization. RESULTS: Of the 3284 hospitals participating in the HAC program, 721 (22.0%) were penalized. Hospitals were more likely to be penalized if they were accredited by the Joint Commission (24.0% accredited, 14.4% not accredited; odds ratio [OR], 1.33; 95% CI, 1.04-1.70); they were major teaching hospitals (42.3%; OR, 1.58; 95% CI, 1.09-2.29) or very major teaching hospitals (62.2%; OR, 2.61; 95% CI, 1.55-4.39; vs nonteaching hospitals, 17.0%); they cared for more complex patient populations based on case mix index (quartile 4 vs quartile 1: 32.8% vs 12.1%; OR, 1.98; 95% CI, 1.44-2.71); or they were safety-net hospitals vs non-safety-net hospitals (28.3% vs 19.9%; OR, 1.36; 95% CI, 1.11-1.68). Hospitals with higher hospital quality summary scores had significantly better performance on 9 of 10 publicly reported process and outcomes measures compared with hospitals that had lower quality scores (all P ≤ .01 for trend). However, hospitals with the highest quality score of 8 were penalized significantly more frequently than hospitals with the lowest quality score of 0 (67.3% [37/55] vs 12.6% [53/422]; P < .001 for trend). CONCLUSIONS AND RELEVANCE: Among hospitals participating in the HAC Reduction Program, hospitals that were penalized more frequently had more quality accreditations, offered advanced services, were major teaching institutions, and had better performance on other process and outcome measures. These paradoxical findings suggest that the approach for assessing hospital penalties in the HAC Reduction Program merits reconsideration to ensure it is achieving the intended goals.

Cardiac risk stratification for noncardiac surgery: update from the American College of Cardiology/American Heart Association 2007 guidelines.

The American College of Cardiology and American Heart Association updated their joint guidelines on perioperative cardiovascular evaluation and care for noncardiac surgery in 2007. The guidelines recommend preoperative cardiac testing only when the results may influence patient management. They specify four high-risk conditions for which evaluation and preoperative treatment are needed: unstable coronary syndromes, decompensated heart failure, significant cardiac arrhythmias, and severe valvular disease. Patient-specific factors and the risk of the surgery itself are considerations in the need for an evaluation and the treatment strategy before noncardiac surgery. In most instances, coronary revascularization before noncardiac surgery has not been shown to reduce morbidity and mortality, except in patients with left main disease. The timing of surgery following percutaneous coronary intervention (PCI) depends on whether a stent was used, the type of stent, and the antiplatelet regimen.

Does advanced medical technology encourage hospitalist use and their direct employment by hospitals?

In the United States, inpatient medical care increasingly encompasses the use of expensive medical technology and, at the same time, is coordinated and supervised more and more by a rapidly growing number of inpatient-dedicated physicians (hospitalists). In the production of inpatient care services, Hospitalist services can be viewed as complementary to sophisticated and expensive medical equipment in the provision of inpatient medical care. We investigate the causal relationship between a hospital's access to three types of sophisticated diagnostic and therapeutic medical equipment - intensity-modulated radiation therapy, gamma knife, and multi-slice computed tomography - and its likelihood of using hospitalists. To rule out omitted variables bias and reverse causality, we use technology-specific Certificate of Need regulation to predict technology use. We find a strong positive association, yet no causal link between access to medical technology and hospitalist use. We also study the choice of employment modality among hospitals that use hospitalists, and find that access to expensive medical technology reduces the hospital's propensity to employ hospitalists directly.

2008 AHA Circle of Life awards.

The three winners of this year's awards demonstrate that it takes a team effort to respond to whatever the patient--and the family--needs. They realize that reaching out to smaller providers--and even competitors--is the right thing to do.