Patient Perspectives on Defining Textbook Outcomes Following Major Abdominal Surgery.

BACKGROUND: The composite metric textbook outcome (TO) has recently gained interest as a novel quality measure. However, the criteria for defining a TO have not been rigorously defined and patient perspectives on the characteristics of TO are unknown. METHODS: Patients who underwent major abdominal surgery at a single tertiary care center were administered a customized survey designed to ascertain their perspectives on defining TOs. The relationship between patient-reported and clinically defined TO rates was compared. RESULTS: Among 79 patients who underwent gastrointestinal (51%), pancreatic (29%), hepatic (18%), or other major abdominal (3%) operations, 57% were female and 86% had an ASA class ≥3. Most patients underwent surgery for malignancy (87%) with 60% undergoing an open operation. Patients most commonly valued no mortality following surgery (96%), no reoperation (75%), and having a margin negative resection (73%) as "extremely important." In contrast, those outcomes that were most commonly valued as "not important at all" or "minimally important" were receiving a blood transfusion (24%) and not having any complications (13%). Using previously published criteria for TOs, 47 (60%) patients were classified as having a clinically defined TO; in contrast, 68 patients (86%) self-reported their outcome was textbook. Self-reported responses were concordant with clinically defined TO criteria 63% of the time (McNemar's test: S=15.2, p<0.01, evidence of disagreement). CONCLUSION: There was significant discordance between patient-reported versus clinically defined measures of TOs, suggesting patients value other considerations beyond traditional factors when evaluating the success of their surgery. Future studies should delineate these relationships and incorporate these factors to refine TO definitions.

Community vulnerability and mobility: What matters most in spatio-temporal modeling of the COVID-19 pandemic?

Community vulnerability is widely viewed as an important aspect to consider when modeling disease. Although COVID-19 does disproportionately impact vulnerable populations, human behavior as measured by community mobility is equally influential in understanding disease spread. In this research, we seek to understand which of four composite measures perform best in explaining disease spread and mortality, and we explore the extent to which mobility account for variance in the outcomes of interest. We compare two community mobility measures, three composite measures of community vulnerability, and one composite measure that combines vulnerability and human behavior to assess their relative feasibility in modeling the US COVID-19 pandemic. Extensions - via temporally dependent fixed effect coefficients - of the commonly used Bayesian spatio-temporal Poisson disease mapping models are implemented and compared in terms of goodness of fit as well as estimate precision and viability. A comparison of goodness of fit measures nearly unanimously suggests the human behavior-based models are superior. The duration at residence mobility measure indicates two unique and seemingly inverse relationships between mobility and the COVID-19 pandemic: the findings indicate decreased COVID-19 presence with decreased mobility early in the pandemic and increased COVID-19 presence with decreased mobility later in the pandemic. The early indication is likely influenced by a large presence of state-issued stay at home orders and self-quarantine, while the later indication likely emerges as a consequence of holiday gatherings in a country under limited restrictions. This study implements innovative statistical methods and furnishes results that challenge the generally accepted notion that vulnerability and deprivation are key to understanding disparities in health outcomes. We show that human behavior is equally, if not more important to understanding disease spread. We encourage researchers to build upon the work we start here and continue to explore how other behaviors influence the spread of COVID-19.

Provider-patient communication and hospital ratings: perceived gaps and forward thinking about the effects of COVID-19.

OBJECTIVES: To highlight clinical and operational issues, identify factors that shape patient responses in Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) and test the correlations between composite measures and overall hospital ratings. DESIGN: Responses to HCAHPS surveys were used in a partial correlation analysis to ascertain those HCAHPS composite measures that most relate to overall hospital ratings. The linear mean scores for the composite measures and individual and global items were analyzed with descriptive analysis and correlation analysis via JMP and SPSS statistical software. SETTING: HCAHPS is a patient satisfaction survey required by the Centers for Medicare and Medicaid Services for hospitals in the USA. The survey is for adult inpatients, excluding psychiatric patients. PARTICIPANTS: 3382 US hospitals. INTERVENTION: None. MAIN OUTCOME MEASURE: Pearson correlation coefficients for the six composite measures and overall hospital rating. RESULTS: The partial correlations for overall hospital rating and three composite measures are positive and moderately strong for care transition (0.445) and nurse communication (0.369) and weak for doctor communication (0.066). CONCLUSIONS: From a health policy standpoint, it is imperative that hospital administrators stress open and clear communication between providers and patients to avoid problems ranging from misdiagnosis to incorrect treatment. Additional research is needed to determine how the coronavirus of 2019 pandemic influences patients' perceptions of quality and willingness to recommend hospitals at a time when nurses and physicians show symptoms of burnout due to heavy workloads and inadequate personal protective equipment.