Abstract
Background
The effectiveness of the CMS nonpayment policy for certain hospital-acquired conditions (HAC) is debated, since their preventability is questionable in several groups of patients. This study aimed to determine the rate of the three most common HAC in major surgical resections for cancer: surgical site infection (SSI), urinary tract infection (UTI), and venous thromboembolism (VTE). Additionally, the association of HAC with patients’ characteristics and their effect on post-operative outcomes were investigated.
Methods
Patients who underwent surgical resection for esophageal, gastric, hepato-biliary, pancreatic, colorectal, and lung cancer were identified using the ACS-NSQIP database (2005–2012). Early surgical outcomes were compared between HAC and non-HAC patients. Modified Poisson regression was used to identify risk factors for developing HAC.
Results
Seventy-four thousand three hundred eighty-one patients were identified, of whom 9,479 (12.74 %) developed one or more HAC. HAC patients had significantly higher rates of 30-day mortality, return to operating room, 30-day readmission, had longer LOS, and were less likely to be discharged home. Several peri-operative patients’ factors were significantly associated with HAC.
Conclusion
Our data show that the development of HAC is strongly associated to pre-operative patients’ characteristics and not only to sub-optimal peri-operative care, therefore suggesting that the nonpayment policy might be excessively penalizing.
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Acknowledgments
Mr. Edwin Lewis and Mrs. Jane Blaustein provided generous support of Dr. Lidor’s Department.
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Discussant
Dr. Pierre F. Saldinger (Flushing, NY):
It is quite evident that CMS’ policy of punishment rather than positive reinforcement does not constitute an environment conducive to real sustainable performance improvement. The desire to improve patient outcomes should indeed be driven by our deepest commitment to patients rather than by our hospital administrator’s worry about payment withhold.
This study presents important and compelling data. It solidifies the notion that complications in surgical patients are, to a certain degree, predictable. While this information could be important to policy makers, it is critical to us surgeons so as to devise risk-mitigating processes for hospital-acquired conditions.
The authors conclude that the occurrence of hospital-acquired conditions is, in large parts, related to intrinsic patient factors, an emerging paradigm which the American College of Surgeons has included in its risk calculator. They deduce that our ability to reduce the incidence may be minimal and therefore we should not be penalized by CMS for such occurrences.
I would like to challenge the authors to provide us with a more optimistic outlook.
Here are my questions.
1. You show that the incidence of HAC decreased from 15 to 11 % during a 6-year period. Have you looked at hospital characteristics within NSQIP where there was the most significant decrease?
2. Did you see the same trend in your institution’s NSQIP data?
3. There are several studies showing that the incidence of HAC can be decreased by pre-operative interventions. You describe the profile of a risk-prone patient that includes dyspnea, weight loss ASA, BMI, etc. Have you thought of devising a pre-operative risk assessment for cancer patients that would include the application of such risk-mitigating processes?
Closing Discussant
Dr. Molena:
1. It is certainly encouraging to see a decrease in the incidence of HAC over the years considered in our study. Moreover, our study showed that the improvement started before the implementation of the CMS policy, indicating that quality improvement in health care has been a priority for clinicians over the last decade independent of the reimbursement issue. NSQIP data are completely de-identified and therefore, it is not possible to conduct sub-analysis in regards to the type of hospital or hospital volumes. Previous studies using different databases have shown a direct correlation between hospital volume and outcomes in general. However, in one study looking specifically at HAC after head and neck cancer surgery, there was no association found between HAC and hospital size, location, or volume status.
2. We did not have access to the Johns Hopkins Hospital-specific NSQIP data so were unable to investigate the incidence of HAC in our institution over the study period.
3. This is a very interesting point. Although NSQIP offers a surgical risk calculator, a risk assessment tool specific for cancer patients is not yet available. It would be indeed very helpful to have such a tool since there are issues specific to cancer patients that should be considered, such as nutritional status, pre-operative induction treatment, cancer type, and stage. The window for treatment is also a constraint in patients with cancer and therefore correcting some of the risk factors for HAC is not always possible. However, it would be helpful for the clinician to understand how specific risk factors influence the development of HAC to decide when to apply such mitigating or prevention processes. We have not thought about developing such processes but it is a very good idea that we should consider in the future.
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Molena, D., Mungo, B., Stem, M. et al. Prevalence, Impact, and Risk Factors for Hospital-Acquired Conditions after Major Surgical Resection for Cancer: A NSQIP Analysis. J Gastrointest Surg 19, 142–151 (2015). https://doi.org/10.1007/s11605-014-2642-x
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DOI: https://doi.org/10.1007/s11605-014-2642-x