Active steps to reduce administrative spending associated with financial transactions in US health care.

US health care administrative spending is approximately $1 trillion annually. A major operational area is the financial transactions ecosystem, which has approximately $200 billion in spending annually. Efficient financial transactions ecosystems from other industries and countries exhibit 2 features: immediate payment assurance and high use of automation throughout the process. The current system has an average transaction cost of $12 to $19 per claim across private payers and providers for more than 9 billion claims per year; each claim on average takes 4 to 6 weeks to process and pay. For simple claims, the transaction cost is $7 to $10 across private payers and providers; for complex claims, $35 to $40. Prior authorization on approximately 5000 codes has an average cost of $40 to $50 per submission for private payers and $20 to $30 for providers. Interventions aligned with a more efficient financial transactions ecosystem could reduce spending by $40 billion to $60 billion; approximately half is at the organizational level (scaling interventions being implemented by leading private payers and providers) and half at the industry level (adopting a centralized automated claims clearinghouse, standardizing medical policies for a subset of prior authorizations, and standardizing physician licensure for a national provider directory).

Surgeon specialization and operative mortality in United States: retrospective analysis.

OBJECTIVE:  To measure the association between a surgeon's degree of specialization in a specific procedure and patient mortality. DESIGN:  Retrospective analysis of Medicare data. SETTING:  US patients aged 66 or older enrolled in traditional fee for service Medicare. PARTICIPANTS:  25 152 US surgeons who performed one of eight procedures (carotid endarterectomy, coronary artery bypass grafting, valve replacement, abdominal aortic aneurysm repair, lung resection, cystectomy, pancreatic resection, or esophagectomy) on 695 987 patients in 2008-13. MAIN OUTCOME MEASURE:  Relative risk reduction in risk adjusted and volume adjusted 30 day operative mortality between surgeons in the bottom quarter and top quarter of surgeon specialization (defined as the number of times the surgeon performed the specific procedure divided by his/her total operative volume across all procedures). RESULTS:  For all four cardiovascular procedures and two out of four cancer resections, a surgeon's degree of specialization was a significant predictor of operative mortality independent of the number of times he or she performed that procedure: carotid endarterectomy (relative risk reduction between bottom and top quarter of surgeons 28%, 95% confidence interval 0% to 48%); coronary artery bypass grafting (15%, 4% to 25%); valve replacement (46%, 37% to 53%); abdominal aortic aneurysm repair (42%, 29% to 53%); lung resection (28%, 5% to 46%); and cystectomy (41%, 8% to 63%). In five procedures (carotid endarterectomy, valve replacement, lung resection, cystectomy, and esophagectomy), the relative risk reduction from surgeon specialization was greater than that from surgeon volume for that specific procedure. Furthermore, surgeon specialization accounted for 9% (coronary artery bypass grafting) to 100% (cystectomy) of the relative risk reduction otherwise attributable to volume in that specific procedure. CONCLUSION:  For several common procedures, surgeon specialization was an important predictor of operative mortality independent of volume in that specific procedure. When selecting a surgeon, patients, referring physicians, and administrators assigning operative workload may want to consider a surgeon's procedure specific volume as well as the degree to which a surgeon specializes in that procedure.

If slow rate of health care spending growth persists, projections may be off by $770 billion.

Despite earlier forecasts to the contrary, US health care spending growth has slowed in the past four years, continuing a trend that began in the early 2000s. In this article we attempt to identify why US health care spending growth has slowed, and we explore the spending implications if the trend continues for the next decade. We find that the 2007-09 recession, a one-time event, accounted for 37 percent of the slowdown between 2003 and 2012. A decline in private insurance coverage and cuts to some Medicare payment rates accounted for another 8 percent of the slowdown, leaving 55 percent of the spending slowdown unexplained. We conclude that a host of fundamental changes--including less rapid development of imaging technology and new pharmaceuticals, increased patient cost sharing, and greater provider efficiency--were responsible for the majority of the slowdown in spending growth. If these trends continue during 2013-22, public-sector health care spending will be as much as $770 billion less than predicted. Such lower levels of spending would have an enormous impact on the US economy and on government and household finances.