Letters

Drafting of the manuscript: Waits, Reames, Sheetz, Englesbe. Critical revision of the manuscript for important intellectual content: Waits, Reames, Englesbe, Campbell. Statistical analysis: Waits, Reames, Sheetz. Administrative, technical, or material support: Reames. Study supervision: Waits, Englesbe, Campbell. Conflict of Interest Disclosures: None reported. Additional Information: Dr Campbell is program director of the Michigan Surgical Quality Collaborative. Additional Contributions: We thank John Z. Ayanian, MD, MPP, the director of the Institute for Health Policy and Innovation and Professor of Medicine at the Department of Internal Medicine, University of Michigan, Ann Arbor, for his helpful comments. He was not compensated financially for his contributions. 1. Ayanian JZ. Michigan’s approach to Medicaid expansion and reform. N Engl J Med. 2013;369(19):1773-1775. 2. LaPar DJ, Bhamidipati CM, Mery CM, et al. Primary payer status affects mortality for major surgical operations. Ann Surg. 2010;252(3):544-550; discussion 550-541. 3. Bradley CJ, Dahman B, Bear HD. Insurance and inpatient care: differences in length of stay and costs between surgically treated cancer patients. Cancer. 2012;118(20):5084-5091. 4. Centers for Medicare & Medicaid Services (CMS), HHS. Medicaid program; state disproportionate share hospital allotment reductions. Final rule. Fed Regist. 2013;78(181):57293-57313.

educational interventions such as ward-based simulation training can be empirically tested.5 This strategy would also provide measures of implementation in the field, across health systems. Focusing on process-related measures may also allow greater ease of implementation of improvement measures. Although structural factors such as nurse staffing levels or a hospital’s diagnostic resources are important, these can be prohibitively expensive, or politically difficult, to change. Measures such as checklists or educational tools to improve care processes can be, by comparison, a bargain and can engage health care professionals to directly influence the care of their patients. Certainly, such measures are no miracle cure. Overcoming the inertia of established practice and of an established culture requires dedication and perseverance to ensure that measures can be adapted and to ensure that staff members can accept them. However, by beginning to focus on more granular data and by considering process-based interventions, we can begin to start addressing the underlying issues to improve patient care and surgical outcomes, and respond to Dr Kao’s timely call to arms.

5. Waits SA, Sheetz KH, Campbell DA, et al. Failure to rescue and mortality following repair of abdominal aortic aneurysm. J Vasc Surg. 2014;59(4):909, e1. 6. Share DA, Campbell DA, Birkmeyer N, et al. How a regional collaborative of hospitals and physicians in Michigan cut costs and improved the quality of care. Health Aff (Millwood). 2011;30(4):636-645.

Philip H. Pucher, MD, MRCS Rajesh Aggarwal, MD, PhD, MA, FRCS Author Affiliations: Department of Surgery and Cancer, Imperial College London, St Mary’s Hospital, London, England (Pucher); Department of Surgery, Hospital of the University of Pennsylvania, Perelman School of Medicine, Philadelphia (Aggarwal).

COMMENT & RESPONSE

Failure to Rescue To the Editor A growing body of evidence implicates failure to rescue after surgery (ie, patient death following postoperative complication) in a significant proportion of the variability seen in surgical outcomes.1,2 Whereas research to date has demonstrated associations between a range of factors and failure to rescue, conclusive causal factors underlying such failures in postoperative care have yet to be identified. In a recent commentary in JAMA Surgery, Kao3 identifies a need to focus on processes or structures at the hospital or patient level. In addition, she highlights the need to consider aspects of care not typically subject to documentation, such as nontechnical and team performance. Observational studies allow the capture of processrelated data that may not otherwise be documented and can contribute to a more detailed understanding of what actually happens during patient care delivery on a daily basis. We recently undertook an observational study of surgical ward rounds, considering the thoroughness of patient management, assessment, and clinicians’ nontechnical performance. Our findings demonstrated not only wide variations in care but a significant association between ward round quality and preventable complications in the postoperative phase. 4 Combining such observational process data with larger outcome-related data sets should provide new insights into the mechanisms underlying failure to rescue. Furthermore, the means to reduce failure-to-rescue rates through

Corresponding Author: Philip H. Pucher, MD, MRCS, Department of Surgery and Cancer, Imperial College London, St Mary’s Hospital, 10th Floor, Queen Elizabeth the Queen Mother Wing, Praed Street, London W2 1NY, England ([email protected]). Conflict of Interest Disclosures: None reported. 1. Ghaferi AA, Birkmeyer JD, Dimick JB. Variation in hospital mortality associated with inpatient surgery. N Engl J Med. 2009;361(14):1368-1375. 2. Gonzalez AA, Dimick JB, Birkmeyer JD, Ghaferi AA. Understanding the volume-outcome effect in cardiovascular surgery: the role of failure to rescue. JAMA Surg. 2014;149(2):119-123. 3. Kao LS. Rescuing failures: can large data sets provide the answer? JAMA Surg. 2014;149(2):124. 4. Pucher PH, Aggarwal R, Darzi A. Surgical ward round quality and impact on variable patient outcomes. Ann Surg. 2014;259(2):222-226. 5. Pucher PH, Aggarwal R, Singh P, Srisatkunam T, Twaij A, Darzi A. Ward simulation to improve surgical ward round performance: a randomized controlled trial of a simulation-based curriculum [published online March 18, 2014]. Ann Surg. doi:10.1097/SLA.0000000000000557.

To the Editor Gonzalez et al 1 report that failure-to-rescue (FTR) rates in cardiovascular surgery were lower (better) in high-volume hospitals than in low-volume hospitals. This is an important finding consistent with a large body of literature on FTR rates that has already shown its association with numerous hospital and staffing characteristics.2-5 However, unlike the traditional measure of FTR rates,2,4 Gonzalez et al1 did not count every death of a patient undergoing coronary artery bypass grafting (CABG). As reported, 75 391 of 119 434 patients (63%) in their study 1 were admitted for CABG, and among these patients, those who experienced an

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acute myocardial infarction (AMI) (before or after surgery) and subsequently died were not counted as a death, and therefore excluded from their FTR analysis. Apparently, Gonzalez et al1 have chosen not to count deaths (and their associated failures) because they did not consider an AMI a reliable complication—they had difficulty using Medicare Provider Analysis and Review data to determine whether the AMI occurred before or after surgery. Nowhere in their article or eTable is the total number of CABG patients with AMI reported, nor is the number of deaths ultimately excluded from the FTR analysis reported. From the perspective of any clinical trial reporting survival, the exclusion of a death because of measurement problems related to a complication prior to that death would be highly suspect. This exclusion should also be considered suspect when evaluating the FTR rate. To confirm the stability of their findings, Gonzalez et al1 should have provided a full account of (1) all deaths (not just patients who died without an AMI complication); (2) all patients with complications (including those who had an AMI); and (3) the FTR rate based on all patients. Such an analysis would be consistent with the original FTR theory2-4 that includes all deaths; a complete description of the construction of the FTR measure is available in the literature.4 It is difficult to imagine any theory, in any medical or surgical context, that would advocate the exclusion of known deaths based on a perceived difficulty in the measurement of complications. If the exclusion of deaths is due to the inadequacy of the available data set for a CABG analysis, then possibly a different data set should have been used (as was done in a previous analysis of death, complication, and FTR among CABG patients published in JAMA3).

1. Gonzalez AA, Dimick JB, Birkmeyer JD, Ghaferi AA. Understanding the volume-outcome effect in cardiovascular surgery: the role of failure to rescue. JAMA Surg. 2014;149(2):119-123.

In Reply We appreciate Dr Silber’s thoughtful letter. His insights and efforts have laid the foundation for failure to rescue (FTR) as an important measure of surgical quality.1 First, we understand Dr Silber’s concern regarding not counting known deaths. However, we would like to clarify that these patients were included in our overall calculation of postoperative mortality but excluded from our calculation of complication and FTR rates. Second, he asked whether the inclusion of patients with an acute myocardial infarction would alter our findings. As noted in our Table 2 reporting complication and FTR rates, we excluded patients with an International Classification of Diseases, Ninth Revision, Clinical Modification code for myocardial infarction who underwent coronary artery bypass grafting.2 Conversely, inclusion of these patients did not qualitatively change the findings presented therein. Comparing complications after coronary artery bypass grafting at low- and high-volume hospitals, we found that the inclusion of patients with a myocardial infarction resulted in rates of 43.6% and 42.4%, respectively (odds ratio, 1.06 [95% CI, 1.02-1.09]). Similarly, including these patients did not result in clinically meaningful differences in the relationship between volume and FTR rate (8.6% in lowvolume hospitals vs 7.4% in high-volume hospitals; odds ratio, 1.17 [95% CI, 1.08-1.27]). We unconditionally agree with Dr Kao’s call to arms for hospital- and patient-level studies to better understand the mechanisms of failure and the best practices for preventing poor outcomes. 3 We thank Drs Pucher and Aggarwal for highlighting their important work on the development of ward-based simulation and methods for optimizing rounding performance. Improving surgical outcomes will no doubt require a multifaceted approach, including observational analyses to identify important associations between patient outcomes and key macrosystem and microsystem characteristics, focused clinical or qualitative studies to delineate underlying mechanisms, and implementation studies to test interventions designed to empower health care providers to assume responsibility for safety in their real-world environment.4 We are in fact making some progress in this area. Our group is in the midst of a large, multiinstitutional study examining the specific relationship between FTR rate and hospital unit resources, safety attitudes, and safety practices. We are confident that this work will provide vital information to guide targeted interventions aimed at improving aspects of care that may be key components of effective rescue, such as teamwork, communication, and respect.

2. Silber JH, Williams SV, Krakauer H, Schwartz JS. Hospital and patient characteristics associated with death after surgery: a study of adverse occurrence and failure to rescue. Med Care. 1992;30(7):615-629.

Amir A. Ghaferi, MD, MS Andrew A. Gonzalez, MD, JD, MPH

Jeffrey H. Silber, MD, PhD Author Affiliations: Center for Outcomes Research, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; Departments of Pediatrics and of Anesthesiology and Critical Care, University of Pennsylvania School of Medicine, Philadelphia; Department of Health Care Management, The Wharton School, University of Pennsylvania, Philadelphia; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia. Corresponding Author: Jeffrey H. Silber, MD, PhD, Center for Outcomes Research, Children’s Hospital of Philadelphia, 3535 Market St, Ste 1029, Philadelphia, PA 19104 ([email protected]). Conflict of Interest Disclosures: None reported.

3. Silber JH, Rosenbaum PR, Schwartz JS, Ross RN, Williams SV. Evaluation of the complication rate as a measure of quality of care in coronary artery bypass graft surgery. JAMA. 1995;274(4):317-323. 4. Silber JH, Romano PS, Rosen AK, Wang Y, Even-Shoshan O, Volpp KG. Failure-to-rescue: comparing definitions to measure quality of care. Med Care. 2007;45(10):918-925. 5. Silber JH, Rosenbaum PR, Romano PS, et al. Hospital teaching intensity, patient race, and surgical outcomes. Arch Surg. 2009;144(2): 113-120, discussion 121.

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Author Affiliations: Center for Healthcare Outcomes and Policy, Department of Surgery, University of Michigan, Ann Arbor (Ghaferi, Gonzalez); Department of Surgery, University of Illinois Hospital and Health Sciences System, Chicago (Gonzalez). Corresponding Author: Amir A. Ghaferi, MD, MS, Center for Healthcare Outcomes and Policy, Department of Surgery, University of Michigan, Ann Arbor, North Campus Research Complex, 2800 Plymouth Rd, Bldg 16, Room 167C, Ann Arbor, MI 48109 ([email protected]).

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Conflict of Interest Disclosures: None reported.

CORRECTION

1. Silber JH, Williams SV, Krakauer H, Schwartz JS. Hospital and patient characteristics associated with death after surgery: a study of adverse occurrence and failure to rescue. Med Care. 1992;30(7):615-629.

Incorrect Information in Table and Text: In the Original Investigation entitled “The Use of Magnetic Resonance Imaging in the Diagnosis of Suspected Appendicitis in Pregnancy: Shortened Length of Stay Without Increase in Hospital Charges” published online May 28, 2014, in JAMA Surgery (doi:10.1001/jamasurg.2013.4658), incorrect information appeared. In Table 3, the number (percentage) of patients in the MR Imaging group who underwent operative exploration should have read 12 (39%). On page E4, the second sentence of the first full paragraph should have read: “Patients without MR imaging had a higher percentage of operative exploration (61% [27 of 44] vs 39% [12 of 31]), which approached statistical significance (odds ratio [OR], 0.45; 95% CI, 0.18-1.16; P = .07).” This article was corrected online.

2. Gonzalez AA, Dimick JB, Birkmeyer JD, Ghaferi AA. Understanding the volume-outcome effect in cardiovascular surgery: the role of failure to rescue. JAMA Surg. 2014;149(2):119-123. 3. Kao LS. Rescuing failures: can large data sets provide the answer? JAMA Surg. 2014;149(2):124. 4. Ghaferi AA, Dimick JB. Variation in mortality after high-risk cancer surgery: failure to rescue. Surg Oncol Clin N Am. 2012;21(3):389-395, vii.

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