Reconstructive Surgeons as Essential Operative Consultants: Quantifying the True Value of Plastic Surgeons to an Academic Medical Center.

BACKGROUND: The revenue generated by plastic surgeons assisting other surgical services is poorly captured by hospital accounting systems, which categorize solely by attending physician of record. The financial impact of reconstructive surgery is thus systematically underestimated. The authors sought to quantify the overlooked value of plastic surgeons as consultants who facilitate complex and profitable operations. METHODS: Hospital billing data were reviewed for inpatient operations over a 3-year fiscal period (2015 to 2017). Cases in which a plastic surgeon assisted were identified. Case mix index, a measure of complexity that correlates with profit, and contribution margin, defined as revenue minus cost, were obtained for each case. RESULTS: Five hundred fifty-four cases required a reconstructive surgeon; 18,904 nonconsultation cases were identified for comparison. Average net revenue per case involving a consultation was 1.79 times greater than for control cases (p < 0.0001). Average contribution margin was 1.73 times greater (p < 0.005). The highest contribution margins stemmed from joint cases with cardiothoracic surgery and neurosurgery. Case mix index was significantly higher for consultation cases than for controls (4.5 versus 3.9; p < 0.0001). In 434 cases (78 percent), plastic surgery assisted with an integral aspect of the operation, meaning the surgery could not have been technically performed without reconstructive assistance. CONCLUSIONS: The authors' findings demonstrate that cases involving plastic surgeons have a higher profit margin than those performed by any department alone. However, this revenue is not appropriately attributed because of oversimplified financial metrics. The skill set of reconstructive surgeons is an undervalued resource for both patient care and hospital economics.

The Effect of Socioeconomic Status on Treatment and Mortality in Non-Small Cell Lung Cancer Patients.

BACKGROUND: Treatment decisions for patients with non-small cell lung cancer (NSCLC) are based on patient and tumor characteristics, including socioeconomic status (SES) factors. The objective was to assess the contribution of SES factors to treatment and outcomes among patients with stage I NSCLC. METHODS: The National Cancer Database was queried for operable patients with stage I NSCLC. Patients were divided into three treatment groups: primary resection (ie, surgery only); nonstandard treatments consisting of chemotherapy with or without radiation; and no therapy. The SES of patients who made up the treatment groups was assessed, and the 5-year survival of all groups was analyzed. RESULTS: The cohort included 69,168 patients with stage I NSCLC. Each of these patients had between zero and five SES risk factors. The factors associated with no surgery were low income, nonwhite race, low high school graduation rate, Medicaid or no insurance, rural residence, and distance less than 12.5 miles from treatment facility. Patients with several SES risk factors have linearly increasing odds of undergoing nonstandard treatments and quadratically increasing odds of having no therapy (for patients with five factors, to odds ratio 4.7; 95% confidence interval, 3.44 to 6.30). Surgery alone was associated with significantly longer 5-year survival (71.8%) compared with nonstandard treatments (22.7%) and no therapy (21.8%; P < .001). CONCLUSIONS: Socioeconomic status factors increase the risk of undergoing guideline discordant therapy for stage I NSCLC. As the number of SES factors increases, the odds of no therapy rises quadratically whereas the odds of nonstandard treatments rises constantly. The surgery only group had significantly longer survival than the nonstandard treatment and no therapy groups.

Mortality in Puerto Rico after Hurricane Maria.

BACKGROUND: Quantifying the effect of natural disasters on society is critical for recovery of public health services and infrastructure. The death toll can be difficult to assess in the aftermath of a major disaster. In September 2017, Hurricane Maria caused massive infrastructural damage to Puerto Rico, but its effect on mortality remains contentious. The official death count is 64. METHODS: Using a representative, stratified sample, we surveyed 3299 randomly chosen households across Puerto Rico to produce an independent estimate of all-cause mortality after the hurricane. Respondents were asked about displacement, infrastructure loss, and causes of death. We calculated excess deaths by comparing our estimated post-hurricane mortality rate with official rates for the same period in 2016. RESULTS: From the survey data, we estimated a mortality rate of 14.3 deaths (95% confidence interval [CI], 9.8 to 18.9) per 1000 persons from September 20 through December 31, 2017. This rate yielded a total of 4645 excess deaths during this period (95% CI, 793 to 8498), equivalent to a 62% increase in the mortality rate as compared with the same period in 2016. However, this number is likely to be an underestimate because of survivor bias. The mortality rate remained high through the end of December 2017, and one third of the deaths were attributed to delayed or interrupted health care. Hurricane-related migration was substantial. CONCLUSIONS: This household-based survey suggests that the number of excess deaths related to Hurricane Maria in Puerto Rico is more than 70 times the official estimate. (Funded by the Harvard T.H. Chan School of Public Health and others.).