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Practice and Outcomes of the Perioperative Surgical Home in a California Integrated Delivery System

Qiu, Chunyuan MD, MS; Cannesson, Maxime MD, PhD; Morkos, Atef MD; Nguyen, Vu T. MD; LaPlace, Diana MD; Trivedi, Narendra S. MD; Khachatourians, Armond MD; Rinehart, Joseph MD; Kain, Zeev N. MD, MBA

doi: 10.1213/ANE.0000000000001370
Ambulatory Anesthesiology and Perioperative Management: Original Clinical Research Report

BACKGROUND: In this article, we report on the implementation and impact of a Perioperative Surgical Home (PSH) model for the total knee arthroplasty at an integrated delivery system (Kaiser Permanente).

METHODS: A multidisciplinary committee developed and implemented a series of PSH protocols that included the entire continuum of care from the decision for surgery until 30 days after surgery. Five hundred forty-six subjects were included in the preimplementation phase (Fast Track [T-fast]), and 518 patients were included in the postimplementation phase (PSH). The primary end points of this report are hospital length of stay (LOS), postoperative skilled nursing facility (SNF) bypass rate, and 30-day readmission rate. We used a generalized linear model to assess the effect on LOS while adjusting for potential confounding variables.

RESULTS: We found that patients assigned to the PSH pathway had a significantly shorter mean LOS compared with patients in the T-fast group (2.4 ± 2.1 days [confidence interval {CI}, 2.2–2.8] vs 3.4 ± 2.9 days [CI, 2.9–3.9]). The SNF bypass rate was significantly higher in the PSH group compared with the T-fast group (94% vs 80%, P = 0.00002, CI, −0.102 to −0.036). There was no difference in the 30 readmission rates between patients managed in the PSH track and the T-fast track (1.2% vs 0.98%).

CONCLUSIONS: Introduction of the PSH into an integrated delivery system resulted in a simultaneous reduction of LOS and SNF admission for total knee arthroplasty patients.

From the *Department of Anesthesiology, Kaiser Permanente Baldwin Park Medical Center, Baldwin Park, California; Department of Anesthesiology and Perioperative Care, University of California Irvine, Irvine, California; Department of Orthopedic Surgery, Kaiser Permanente Baldwin Park Medical Center, Baldwin Park, California; and §Department of Anesthesiology and Perioperative Care, American College of Perioperative Medicine, Irvine, California.

Chunyuan Qiu, MD, MS, is currently affiliated with the Department of Anesthesiology and Perioperative Care, UCI Medical Center, Irvine, California.

Accepted for publication March 14, 2016.

Funding: None.

Conflict of Interest: See Disclosures at the end of the article.

This report was previously presented, in part, at the ASA Annual meeting 2014, which was the subject of an article in Anesthesiology News.

Reprints will not be available from the authors.

Address correspondence to Chunyuan Qiu, MD, MS, Department of Anesthesiology, Kaiser Permanente Baldwin Park Medical Center, 1011 Baldwin Park Blvd, Baldwin Park, CA 91706. Address e-mail to chunyuan.x.qiu@kp.org.

Changes in the American health care system and continuing implementation of the 2010 Affordable Care Act are currently reshaping the landscape of the health care industry.1 The new direction of this industry is clearly captured in Berwick and Hackbarth’s triple aims of improving experience of care, improving health of populations, and reducing per capita costs of health care.2 Concurrently, the current primary push by the Center for Medicare & Medicaid Services and commercial payers is from volume to value.3 This approach advocates compensating hospitals and health care providers based on the value they deliver to a particular patient rather than simply based on the provision of the care. Indeed, the recently introduced concepts of Medicare Access and CHIP Reauthorization Act of 2015, merit-based incentive payment system and alternative payment models, underscore this recent trend.a Because value within the health care settings is defined as “outcomes relative to costs,”4 it is important to examine not only health care outcomes but also its cost. Typically, perioperative patient care accounts for >50% of hospital budget and preventable complications such as pneumonia, delirium, and urinary tract infection, continue to be common in this setting.5–7 Thus, it is important to explore new perioperative delivery care models that simultaneously improve outcomes while decreasing cost.

The Perioperative Surgical Home (PSH) was recently proposed as a new perioperative delivery care model that will address both quality of clinical care along with patient satisfaction and the cost of care. PSH is a patient-centered, physician-led collaborative model of care that is aimed at improving clinical outcomes, enhancing patient satisfaction and reducing overall cost.8–11 This model guides the patient throughout the entire perioperative period and beyond, facilitating effective collaboration among all health care workers and assuring high clinical quality through a series of clinical pathways.12,13 The PSH model was studied in a limited number of institutions that have reported improved clinical outcomes, increased patient satisfaction, and decreased hospital costs13,14 but there are still many barriers impeding its wider adoption.15 This report, to the best of our knowledge, is the first description of a PSH implementation within an integrated delivery system (IDS).

Kaiser Permanente (KP) is the largest IDS in the United States. This system consists of 3 distinct yet fully integrated entities: Kaiser Foundation Health Plan (insurance), Kaiser Foundation Hospitals (hospitals), and Permanente Medical Groups (physicians). Because these 3 entities are bound together financially and operationally, it is vital for each of them to align with others to provide the highest possible quality of care at an affordable cost. We submit that the unique structure of the KP model as an IDS model provides an ideal environment for the introduction of a PSH model for patients undergoing total knee arthroplasty (TKA). Indeed, typical barriers for the PSH model include lack of alignment among anesthesiologist (who would provide much of the services of the PSH) and the hospitals and the insurance companies (who would benefit from the outcomes of the PSH). In an IDS model, these barriers typically do not exist. Another major barrier for the PSH comes from potential conflicts among anesthesiologists, surgeons, and hospitalists about scope of work and possible loss of professional payment. Again, within the context of an IDS model, this is not a barrier for successful implementation. The purpose of this study is to report the design, implementation, and impact of a PSH model at an IDS model in Southern California (KP).

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METHODS

Data described in this report include 1064 consecutive patients who underwent primary TKA from June 2012 to May 2014. The KP Southern California IRB approved this study. Because the study was conducted as a quality improvement project, it is reported following the Standards for Quality Improvement Reporting Excellence (SQUIRE guidelines)16,17 and is presented as a retrospective cohort study.

KP Baldwin Park is a hospital that is part of a large IDS and is located in the greater Los Angeles, California area. This hospital manages approximately 75,000 emergency department visits per year, 13,000 hospital admissions per year, >35,00 inpatient surgeries per year, and 9000 outpatient surgeries per year. The department of anesthesiology in this facility is a physician-only group practice and is part of the multispecialty Southern California Permanente medical group of >6000 physicians.

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Team and the Clinical Pathways

Figure 1

Figure 1

In March 2013, we formed a planning committee that included stakeholders involved in the provision of perioperative care for patients undergoing TKA (Figure 1). The committee consisted of disciplines such as anesthesiologists, surgeons, physical therapists, discharge planners, operating room and ward nurses, quality improvement specialists, skilled nursing facility (SNF) representatives, pharmacy employees, and information technology experts. The planning committee created a focus group including 20 patients who had previously undergone TKA at our facility. Input from these patients was integrated into the final PSH-TKA pathway. Extensive training for providers was conducted through assigned champions, and a 1-day retreat was organized before launching the program. During this retreat, we simulated a patient undergoing the PSH process with the participation of stakeholders from scheduling the procedure to 30 days after discharge. To ensure compliance, champions were involved with the management of the first 60 patients enrolled in this initiative. We also identified 12 patients who previously underwent TKA in our facility and who now were presenting for TKA of the contralateral knee under the PSH program. For these patients, we conducted and videotaped extensive interviews that focused on comparing their perioperative care experiences under the 2 different conditions of care. The resulting feedback furthered our understanding and reinforced our conviction in the superiority of the PSH model.

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Clinical Pathways

The PSH-TKA pathway distinguishes itself from our previous standard of care, Fast Track (T-fast) protocol,b by the following characteristics: (1) participation of the anesthesiologists during the entire perioperative process; (2) practice of comprehensive perioperative medicine by anesthesiologists; and (3) leadership of the anesthesiologists in both clinical care and resource management (Figure 2). For example, under the PSH model, anesthesiologists managed all necessary steps such as preoperative management (laboratory testing, consultation of medical specialists, primary care consults, surgical scheduling, Surgical Care Improvement Project compliance, medication reconciliation). Anesthesiologists also participated in the design of surgeons’ order set for this PSH-TKA pathway and were involved in the creation and implementation of comprehensive pain and rehabilitation protocols for SNF and home care. We modified our preoperative care to now provide a service that included both surgeon’s appointment and anesthesia preoperative clinic (APC). Many required preoperative tasks that were completed in the APC that is staffed by 1 anesthesiologist, 2 physician assistants (PAs), 4 technicians, and 2 clerks. We conducted preoperative evaluations and medical optimization 3 to 14 days before surgery for all patients undergoing TKA. In some cases, when an underlying medical condition such as anemia was identified in the preoperative period, surgery was rescheduled and the APC staff worked with our hospitalists to optimize hemoglobin levels before the procedure. This flexibility in scheduling may have been easier than in other institutions because KP is an IDS in which rescheduling of surgery and preoperative optimization is easier to achieve because all outpatient and inpatients systems are integrated and the emphasis is on value rather than volume. ASA physical status III or IV patients were automatically identified through our electronic medical record system by our internal medicine colleagues, who would concurrently evaluate selected patients alongside the anesthesiologist on the day of the APC visit. In addition, laboratory studies, radiographic studies, electrocardiograms, additional medical consultations, and routine preadmission paper work were all completed at the APC (Table 1).

Table 1

Table 1

Figure 2

Figure 2

Our PSH protocol recommended spinal anesthesia (bupivacaine, 12.5–15 mg) and postoperative femoral nerve or adductor canal blocks (0.35% ropivacaine, 20 mL) for all patients who did not have contraindications. Pain management was further enhanced by a multimodal pain protocol that was initiated preoperatively, continued intraoperatively, and extended postoperatively into the SNF and home environment (Table 2). We also replaced the traditional single 24-hour postanesthesia visit, which focused primarily on a narrow set of postoperative complications, with daily anesthesia postoperative rounds, which focused on comprehensive medical optimization and functional recovery. For example, the anesthesia team managed all patients with diabetes mellitus and abnormal glucose levels after surgery. When needed, the team consulted the hospitalist service. As indicated earlier, this might have been more feasible because KP is an IDS where multidisciplinary collaboration can be achieved effectively because the financial incentives of all providers are aligned. The anesthesia team also helped match pain management with the changing needs of physical rehabilitation. The latter proved to be of great value for functional recovery in the PSH-TKA pathway. The above additional PSH anesthesia services were provided by a 0.25 full-time equivalent (FTE) of anesthesia PA and a 0.25 FTE of an anesthesiologist. It is important to note that the personnel devoted to the APC was in place before the implantation of the PSH and that KP did not hire any additional personnel but rather changed workflows in an existing clinic.

Table 2

Table 2

Table 3

Table 3

Twenty-four consecutive months of TKA data were collected, including 12 months of data under the baseline model (T-fast, May 1, 2012, to April 30, 2013) and 12 months of data under the PSH protocol (June 1, 2013, to May 30, 2014) in a historical-prospective study design (Table 3).

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Outcome Variables and Measurement

The primary outcome measure of this study was length of stay (LOS) in the hospital after surgery, with postoperative day (POD) 0 defined as day of surgery (Figures 3 and 4). The secondary outcome measures included SNF admission, pain scores at rest and during physical therapy (PT), and 30-day readmission rate and complications (Table 4). We used a conventional 11-point (0–10) Numerical Rating Scale for postoperative pain intensity. POD0 PT pain scores were only collected in the PSH group because T-fast pathway did not undergo PT until at least POD1. Pain was monitored every 4 hours after postanesthesia care unit discharge and was considered unacceptable if the pain score was >4 at any time during the entire LOS. POD0 included the successful completion of PT in the postanesthesia care unit or on the ward. The transfusion rate was defined as the percentage of patients receiving allogeneic or autologous transfusion of packed red blood cells any time during their LOS regardless of their indication. Transfusion was recommended by the orthopedic PA or anesthesia PA after rounds and was approved by the surgeon. One hundred thirty post-TKA patients under the PSH protocol were randomly surveyed within 1 year after surgery. The survey was conducted through telephone interview by 1 PA and 1 registered nurse (Table 5).

Table 4

Table 4

Table 5

Table 5

Figure 3

Figure 3

Data collection variables were decided based on SQUIRE guidelines and obtained using KP Total Joint Replacement Registry (TJRR) and the anesthesia information management system (Epic, Verona, WI). The KP TJRR consists of clinical data entered by various health care providers at the point of care and process and outcome data that were obtained from KP administrative databases and electronic health records in a health care IDS. The KP TJRR captures complications through International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis codes. It searches the whole organization’s integrated EHR, including inpatient hospital stays, outpatient, urgent care, emergency room, and ambulatory care visits. Data collection methodology of the TJRR has been documented elsewhere and used in Table 4.18 Because KP is a fully integrated health care system, the overwhelming majority of patients have their care delivered within the IDS. In the minority of cases where patients present for care outside of our own KP facilities, we have an active repatriation program to bring our patients back to our facilities as soon as they are medically stable, facilitating consistent treatment by KP standards and protocols and also capturing diagnosis codes for tracking of complications. A research assistant conducted a chart review of complications that had been identified and determined whether the identified complications fit the Agency for Healthcare Research and Quality guidelines.18 Myocardial infarctions, respiratory distress, deep vein thrombosis with pulmonary embolus, surgical site infections, and neurologic events were considered “major complications.” Anemia, arrhythmias, deep vein thrombosis, postoperative nausea and vomiting, urinary retention, uncontrolled pain, and joint swelling were considered “minor complications.”

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Statistical Analysis

The primary goal of this analysis was to assess the impact of the PSH-TKA implementation on LOS in the hospital compared with the T-fast protocol, which were both based on the same discharge criteria. LOS data were first checked for normality using the Shapiro-Wilk test. Assuming the data were nonnormal, the effect of group on LOS was tested using a generalized linear model (GLM), which would (unlike standard linear regression) allow for nonnormal response variables and adjusting for potential confounding variables. We assumed that because the LOS was a form of count (no negative values possible) and would likely have a strong right skew that a γ distribution using a log-link would be an appropriate distribution for the model.19 Other factors and covariates included in the model were specific procedure type, surgeon, patient gender, patient age, patient body mass index, ASA physical status patient score, surgery duration in minutes, and estimated blood loss in milliliters. Categorical and ordinal variables were used as factors and scalar measures used as covariates, and an intercept was included in the model. Comparisons between groups for ordinal data (eg, complication rates as sum of yes/no fields within each patient) and proportions (eg, readmission rates) were performed with Pearson χ2 test.

All data are presented as mean ± SD, median and interquartile range (25th percentile–75th percentile), or count (percentage) as appropriate. Confidence intervals (CIs) are reported at the 95% level. By using the parameters estimated from the GLM, the power of detecting association between LOS and the implementation of the protocol was >90%. All comparisons were made at a significance level of 0.05, and all analyses were performed with R (www.r-project.org) and SPSS 21.0.0.0 (IBM, Armonk, NY).

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RESULTS

Five hundred forty-six subjects were included in the preimplementation phase, and 518 patients were included in the postimplementation phase. Baseline demographics of patients in the preimplementation and postimplementation periods are presented in Table 3.

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Primary Outcome

Figure 4

Figure 4

As anticipated, LOS data were found to be heavily right-skewed and nonnormal, using Shapiro-Wilk test (P < 0.00001), for both T-fast and PSH groups. Based on the GLM results, the implementation of the PSH pathway had a significant effect (P < 0.0005) on LOS, independent of the other variables included in the model. Patients assigned to the PSH pathway had a mean LOS of 2.4 ± 2.1 days (95% CI, 2.2–2.8) compared with the T-fast group, which had a mean LOS of 3.4 ± 2.9 days (95% CI, 2.9–3.9; Figure 3). Other significant variables in the model were procedure, knee replacement revision total cemented (resulted in an approximately 1-day increase in LOS compared with knee replacement total), gender (males had an average 0.2-day increase in LOS compared with females), and ASA physical status (0.4-day increase in LOS for each step increase in ASA physical status over ASA physical status I). Surgeon, case time, estimated blood loss, patient age, and patient body mass index were not statistically significant factors. The changes in LOS during the study period (time series) are shown in Figure 4.

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Secondary Outcomes

There was no significant difference between groups in either major (P = 0.237) or minor (P = 0.992) complications (Table 4). The same-day cancellation rate was 1.2% in the T-fast pathway and 0.98% in the PSH pathway (P = 0.98). There were no intraoperative blood product transfusion episodes in either the T-fast pathway or PSH pathway. A significantly fewer patients in the PSH pathway received a postoperative transfusion compared with patients in the T-fast pathway (3.5% vs 7%, P = 0.0239, 95% CI, 0.004–0.036). No 90-day mortality was observed in either group. There were 436 patients discharged directly home from the T-fast group with an 80% SNF bypass rate, whereas 486 PSH patients were successfully discharged home with a 94% SNF bypass rate (P = 0.00002, 95% CI, −0.102 to −0.036). Overall, 78% of patients in the PSH group underwent PT on POD0 compared with none in the T-fast group. The average pain score of these patients on POD1 was 2.8 ± 0.4. There were 73 (15.1%) postoperative emergency department visits in the T-fast phase compared with 55 (10.8%) in the PSH phase (P = 0.07). There was no statistically significant difference in 30-day readmission rate, 0.9% for the T-fast group and 1.2% for the PSH group (P = 0.88).

Table 5 presents the satisfaction data collected from 130 patients 1 year after surgery. As displayed in this table, 98% of the patients thought the preoperative preparation was excellent or satisfactory. Interestingly, although 13% of the patients reported their LOS as too short, 98% still believed their home environment was satisfactory on discharge and 97% were pleased with their pain and rehabilitation programs. Although 36% of patients did not report improved activity level 30 days after surgery, 93% of the patients reported same or improved outlook on improving lifestyle after surgery (Table 5).

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DISCUSSION

Under the conditions of this study, we found that, within an IDS, introduction of a PSH model for knee replacement surgery resulted in a simultaneous reduction in LOS and SNF admission. Indeed, the SNF bypass rate was 94% among PSH patients, whereas the 30-day readmission rate remained very low in these patients (0.98%). This very high SNF bypass rate has significant public health implications because it is reported that postdischarge care accounts for more than one-third of total episode payments and varies substantially across patients undergoing joint surgery. We believe that the high SNF bypass rate observed among PSH patients in this study was because of the entire bundle of care rather than one specific element in the PSH model. That said, we believe that managing a patient’s expectations, evaluating home readiness preoperatively, early rehabilitation, better analgesia, better cognition function through regional anesthesia, and nerve-block centered multimodal analgesia therapy are a large part of SNF bypass.

A previous initiative in our facility had reduced LOS to 3.4 days and increased the SNF bypass rate to 80%.c Introduction of the PSH to our facility resulted in a further reduction of LOS to 2.4 days and a further increase in the SNF bypass rate to 94%. These 2 findings were independent of patients’ gender, ASA physical status scores, comorbidities, or surgeons. LOS for patients undergoing TKA has been a major interest for the past few years. Indeed, fast tracking in TKA patients has been effective in reducing LOS from 8 days merely a decade ago to 4 days or less.20 El Bitar et al.21 have recently used nationwide data to examine predictors for LOS for primary TKA. The investigators found that the majority of patients had a hospital LOS of about 3 days (74.8%). The most significant predictors the authors found for LOS in their nationwide sample were age ≥80 years, Hispanic race, Medicaid payer status, lower household income, weekend admission, rural nonteaching hospital, and discharge to a SNF. Because of the complexity of the LOS issue as outlined by El Bitar et al., it is difficult to compare our particular LOS findings with nationwide data without further analysis. Interestingly, the value of LOS reduction as observed in recent years is now being questioned because it often results in shifting cost and care from hospital to SNFs and increased postoperative readmission rates. Although SNFs are more cost-effective for transitioning certain TKA patients, their services are still a significant additional expense.22,23 Within this context, the results of this PSH report are of high significance because we observed decreased LOS, markedly increased SNF bypass rate, and no increase in the postoperative readmission rates. Indeed, we observed a 1.2% 30-day readmission rate, which is far lower than the average 4.6% reported in the literature.24

In our PSH model, pain management was based on peripheral nerve block and enhanced by a defined regimen of multimodal medications, all of which focused on preemptive rather than rescue pain therapy. From preoperative initiation of pain regimens to intraoperative spinal anesthesia to immediate postoperative peripheral nerve block to around-the-clock multimodal pain therapy, our pain protocol was designed to maximize pain control while minimizing side effects that may interfere with a patient’s early PT. It was created to avoid central sensitization from both primary surgical stimulation and subsequent inflammatory cascades. As a result, 78% of PSH patients were able to complete PT on POD0. This aggressive PT schedule required not only a greater degree of pain control but also rapid recovery of physical and cognitive capacity immediately after surgery on POD0.

As indicated by our survey data, up to 16% of the PSH-TKA group patients did not enjoy positive lifestyle changes 1 year after their surgery, suggesting that a functional knee after a successful and costly TKA may not always result in the desired improvements in quality of life. Also, although patients were very satisfied overall with the PSH care, some of them did not expect to be discharged so early. The perception of leaving the hospital sooner than expected was an opportunity to manage patients’ expectations, a task we continue to address in our improvement efforts, but was not within the timeframe of the presented data. However, readers should note that the survey data we collected for the PSH group are limited by the lack of standardization in the time duration between surgery and when patients were surveyed (up to 1 year after surgery) inducing a potential recall bias.

We would also like to comment on the much-needed change in our philosophy of patient care paradigms in the context of functional recovery and PSH. We believe that transitioning from purely symptom-based management strategies to strategies that incorporate patients’ ability to participate in functional activities that will enhance their functional recovery. For example, move away from only a static numeric-based value for pain management intervention (Visual Analog Scale > 4/10) to one that also incorporates patients’ need for additional intervention (analgesia) to participate in activities that will help them with their functional recovery.

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Methodologic Considerations

Quality improvement and historical prospective studies are inherently limited because they are not randomized or controlled and they reduce the ability to make a causal connection between the intervention and the change in outcome. However, when implementing a complex process (such as PSH), it is practically impossible to randomize and to control the implementation of the process under testing. For this reason, the historical prospective approach methodology is one of the methodologies available for testing the implementation of a quality improvement program in the setting of comparative effectiveness research. This approach has been used in several studies, including some with significant impact on health care and perioperative medicine.25 In addition, we have used a GLM to assess the effect of group on LOS while adjusting for potential confounding variables to strengthen our conclusion and increase the repeatability of our results. We did collect data retrospectively but used the same data collection methodology in both the historical and the prospective groups. In addition, the primary outcome was an objective measurement of the hospital LOS. Furthermore, we used the KP TJRR and the Anesthesia Information Management System to standardize the way postoperative complications were reported.

Although the implementation of PSH was achieved without hiring additional staff members, there were real costs associated with the project. This extra cost consisted in the reallocation of existing resources that could have arguably been used for other purposes. More specifically, the PSH anesthesia services were provided by a 0.25 FTE of anesthesia PA and a 0.25 FTE of an anesthesiologist.

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CONCLUSION

This article is a report of early adoption of PSH practice in the largest IDS system in the United States. This corroborates a recent study from University of California Irvine12,13 despite significant differences in practice environment, scope of involvement, and specific method. The results of this study not only demonstrate that the goals of Bundled Payments for Care Improvement and Berwick’s triple aims are achievable but also demonstrate that the scope of anesthesiology as a medical specialty can be far broader than what has been commonly practiced.

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DISCLOSURES

Name: Chunyuan Qiu, MD, MS.

Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript.

Conflicts of Interest: Chunyuan Qiu declares no conflicts of interest.

Name: Maxime Cannesson, MD, PhD.

Contribution: This author helped analyze the data and write the manuscript.

Conflicts of Interest: Maxime Cannesson consulted for Covidien, consulted for Edwards Lifesciences, consulted for Masimo Corp, and reported a conflict of interest with Sironis.

Name: Atef Morkos, MD.

Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript.

Conflicts of Interest: Atef Morkos declares no conflicts of interest.

Name: Vu T. Nguyen, MD.

Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript.

Conflicts of Interest: Vu T. Nguyen declares no conflicts of interest.

Name: Diana LaPlace, MD.

Contribution: This author helped design the study, conduct the study, and write the manuscript.

Conflicts of Interest: Diana LaPlace declares no conflicts of interest.

Name: Narendra S. Trivedi, MD.

Contribution: This author helped conduct the study and write the manuscript.

Conflicts of Interest: Narendra S. Trivedi declares no conflicts of interest.

Name: Armond Khachatourians, MD.

Contribution: This author helped design the study, conduct the study, and analyze the data.

Conflicts of Interest: Armond Khachatourians declares no conflicts of interest.

Name: Joseph Rinehart, MD.

Contribution: This author helped analyze the data and write the manuscript.

Conflicts of Interest: Joseph Rinehart consulted for Edwards Lifesciences, consulted for Masimo, and reported a conflict of interest with Sironis.

Name: Zeev N. Kain, MD, MBA.

Contribution: This author helped analyze the data and write the manuscript.

Conflicts of Interest: Zeev N. Kain declares no conflicts of interest.

This manuscript was handled by: Tong J. Gan, MD.

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RECUSE NOTE

Dr. Maxime Cannesson is the Section Editor for Technology, Computing, and Simulation for Anesthesia & Analgesia. This manuscript was handled by Dr. Tong J. Gan, Section Editor of Ambulatory Anesthesiology and Perioperative Management, and Dr. Cannesson was not involved in any way with the editorial process or decision.

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FOOTNOTES

a https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Value-Based-Programs/MACRA-MIPS-and-APMs/MACRA-MIPS-and-APMs.html. Accessed on December 25, 2015.
Cited Here...

b Qiu C, Etrata R, LaPlace D, Nguyen V, Rodriguez D, Saldana K, Qiu J, Jo H, Heyman C. Femoral Nerve Block (FNB) for Total Knee Arthrosplasty: Impact on Length of Hospital Stay. ASA Annual Meeting 2012, A032; Qiu C, Nguyen V, Qiu J, Jo H, Etrata R, LaPlace D, Trivedi N, Rodriguez D, Saldana J, Markos J. Fast Tracking Total Knee Arthroplasty: The Impact of Femoral Nerve Block. ASA Annual Meeting 2012, A859.
Cited Here...

c Qiu C, Etrata R, LaPlace D, Nguyen V, Rodriguez D, Saldana K, Qiu J, Jo H, Heyman C. Femoral Nerve Block (FNB) for Total Knee Arthrosplasty: Impact on Length of Hospital Stay. ASA Annual Meeting 2012, A032; Qiu C, Nguyen V, Qiu J, Jo H, Etrata R, LaPlace D, Trivedi N, Rodriguez D, Saldana J, Markos J. Fast Tracking Total Knee Arthroplasty: The Impact of Femoral Nerve Block. ASA Annual Meeting 2012, A859.
Cited Here...

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REFERENCES

1. Murray CJ, Frenk J. Ranking 37th—measuring the performance of the U.S. health care system. N Engl J Med 2010;362:98–9.
2. Berwick DM, Hackbarth AD. Eliminating waste in US health care. JAMA 2012;307:1513–6.
3. Burwell SM. Setting value-based payment goals—HHS efforts to improve U.S. health care. N Engl J Med 2015;372:897–9.
4. Porter MF. What is value in health care? N Engl J Med 2010;363:2477–81.
5. Pearse RM, Moreno RP, Bauer P, Pelosi P, Metnitz P, Spies C, Vallet B, Vincent JL, Hoeft A, Rhodes A; European Surgical Outcomes Study (EuSOS) Group for the Trials groups of the European Society of Intensive Care Medicine and the European Society of Anaesthesiology. Mortality after surgery in Europe: a 7 day cohort study. Lancet 2012;380:1059–65.
6. Zmistowski B, Restrepo C, Hess J, Adibi D, Cangoz S, Parvizi J. Unplanned readmission after total joint arthroplasty: rates, reasons, and risk factors. J Bone Joint Surg Am 2013;95:1869–76.
7. Tsai TC, Joynt KE, Orav EJ, Gawande AA, Jha AK. Variation in surgical-readmission rates and quality of hospital care. N Engl J Med 2013;369:1134–42.
8. Kain ZN, Vakharia S, Garson L, Engwall S, Schwarzkopf R, Gupta R, Cannesson M. The perioperative surgical home as a future perioperative practice model. Anesth Analg 2014;118:1126–30.
9. Vetter TR, Boudreaux AM, Jones KA, Hunter JM Jr, Pittet JF. The perioperative surgical home: how anesthesiology can collaboratively achieve and leverage the triple aim in health care. Anesth Analg 2014;118:1131–6.
10. Kain ZN, Vakharia S, Garson L, Engwall S, Schwarzkopf R, Gupta R, Cannesson M. The perioperative surgical home as a future perioperative practice model. Anesth Analg 2014;118:1126–30.
11. Vetter TR, Boudreaux AM, Jones KA, Hunter JM Jr, Pittet JF. The perioperative surgical home: how anesthesiology can collaboratively achieve and leverage the triple aim in health care. Anesth Analg 2014;118:1131–6.
12. Garson L, Schwarzkopf R, Vakharia S, Alexander B, Stead S, Cannesson M, Kain Z. Implementation of a total joint replacement-focused perioperative surgical home: a management case report. Anesth Analg 2014;118:1081–9.
13. Kash BA, Zhang Y, Cline KM, Menser T, Miller TR. The perioperative surgical home (PSH): a comprehensive review of US and non-US studies shows predominantly positive quality and cost outcomes. Milbank Q 2014;92:796–821.
14. Raphael DR, Cannesson M, Schwarzkopf R, Garson LM, Vakharia SB, Gupta R, Kain ZN. Total joint Perioperative Surgical Home: an observational financial review. Perioper Med (Lond) 2014;3:6.
15. Prielipp RC, Morell RC, Coursin DB, Brull SJ, Barker SJ, Rice MJ, Vender JS, Cohen NH. The future of anesthesiology: should the Perioperative Surgical Home redefine us? Anesth Analg 2015;120:1142–8.
16. Ogrinc G, Mooney SE, Estrada C, Foster T, Goldmann D, Hall LW, Huizinga MM, Liu SK, Mills P, Neily J, Nelson W, Pronovost PJ, Provost L, Rubenstein LV, Speroff T, Splaine M, Thomson R, Tomolo AM, Watts B. The SQUIRE (Standards for QUality Improvement Reporting Excellence) guidelines for quality improvement reporting: explanation and elaboration. Qual Saf Health Care 2008;17(suppl 1):i13–32.
17. Davidoff F, Batalden P, Stevens D, Ogrinc G, Mooney SE; SQUIRE development group. Publication guidelines for quality improvement studies in health care: evolution of the SQUIRE project. BMJ 2009;338:a3152.
18. Bini SA, Khatod M, Inacio MC, Paxton EW. Same-day versus staged bilateral total knee arthroplasty poses no increase in complications in 6672 primary procedures. J Arthroplasty 2014;29:694–7.
19. Basu A, Rathouz PJ. Estimating marginal and incremental effects on health outcomes using flexible link and variance function models. Biostatistics 2005;6:93–109.
20. Cram P, Lu X, Kates SL, Singh JA, Li Y, Wolf BR. Total knee arthroplasty volume, utilization, and outcomes among Medicare beneficiaries, 1991–2010. JAMA 2012;308:1227–36.
21. El Bitar YF, Illingworth KD, Scaife SL, Horberg JV, Saleh KJ. Hospital length of stay following primary total knee arthroplasty: data from the nationwide inpatient sample database. J Arthroplasty 2015;30:1710–5.
22. Bozic KJ, Ward L, Vail TP, Maze M. Bundled payments in total joint arthroplasty: targeting opportunities for quality improvement and cost reduction. Clin Orthop Relat Res 2014;472:188–93.
23. Lovald ST, Ong KL, Lau EC, Schmier JK, Bozic KJ, Kurtz SM. Mortality, cost, and health outcomes of total knee arthroplasty in Medicare patients. J Arthroplasty 2013;28:449–54.
24. Pugely AJ, Martin CT, Gao Y, Mendoza-Lattes S, Callaghan JJ. Differences in short-term complications between spinal and general anesthesia for primary total knee arthroplasty. J Bone Joint Surg Am 2013;95:193–9.
25. Pronovost P, Needham D, Berenholtz S, Sinopoli D, Chu H, Cosgrove S, Sexton B, Hyzy R, Welsh R, Roth G, Bander J, Kepros J, Goeschel C. An intervention to decrease catheter-related bloodstream infections in the ICU. N Engl J Med 2006;355:2725–32.
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