A case management report: a collaborative perioperative surgical home paradigm and the reduction of total joint arthroplasty readmissions
© The Author(s). 2016
Received: 22 January 2016
Accepted: 26 September 2016
Published: 18 October 2016
Efforts to mitigate costs while improving surgical care quality have received much scrutiny. This includes the challenging issue of readmission subsequent to hospital discharge. Initiatives attempting to preclude readmission after surgery require planned and unified efforts extending throughout the perioperative continuum. Patient optimization prior to discharge, enhanced disease monitoring, and seamless coordination of care between hospitals and community providers is integral to this process. The perioperative surgical home (PSH) has been proposed as a model to improve the delivery of perioperative healthcare via patient-centered risk stratification strategies that emphasize value and evidence-based processes.
This case report seeks to specifically describe implementation of readmission reduction strategies via a PSH paradigm during total joint arthroplasty (TJA) procedures at the University of California Irvine (UCI) Health. An orthopedic surgeon open to collaborate within a PSH paradigm for TJA procedures was recruited to UCI Health in October of 2012. Institution specific data was then prospectively collected for 2 years post implementation of the novel program. A total of 328 unilateral, elective primary TJA (120 hip, 208 knee) procedures were collectively performed. Demographic analysis reveals the following: mean age of 64 ± 12; BMI of 28.5 ± 6.2; ASA Score distribution of 0.3 % class 1, 23 % class 2, 72 % class 3, and 4.3 % class 4; and 62.5 % female patients. In all, a 30-day unplanned readmission rate of 2.1 % (95 % CI 0.4–3.8) was observed during the study period. As a limitation of this case report, this reported rate does not reflect readmissions that may have occurred at facilities outside UCI Health.
As healthcare evolves to emphasize value over volume, it is integral to invest efforts in longitudinal patient outcomes including patient disposition subsequent to hospital discharge. As outlined by this case management report, the PSH provides an institution-led means to implement a series of care initiatives that optimize the important metric of readmission following TJA, potentially adding further value to patients, surgical colleagues, and health systems.
KeywordsAnesthesia Perioperative surgical home (PSH) Surgical readmissions Perioperative medicine Readmission reduction Hospital discharge Total joint arthroplasty (TJA)
Repeat admission after hospital discharge remains a significant and complex problem (Joynt and Jha 2012; Lucas and Pawlik 2014; Allaudeen et al. 2011; Merkow et al. 2015; Garrison et al. 2013; Zmistowski et al. 2013; Saucedo et al. 2014). Nearly one in every five patients is readmitted within 30 days of hospital discharge, accounting for an estimated $15 billion in healthcare spending annually (Allaudeen et al. 2011). This alarmingly high rate of unplanned readmission and the associated costs are both unsustainable and unacceptable. As the Affordable Care Act and other efforts to reduce the cost of healthcare are assimilated into payer policies, there is urgency for the healthcare industry to implement collaborative care models that emphasize value over volume (Ho and Sandy 2014; Szokol and Stead 2014; Schroeder and Frist 2013; Hertzberg 2013). Accountable care organizations (ACOs) are rapidly proliferating and can be defined as an integrated group motivated to provide enhanced patient care at a reduced cost for a defined population of patients (Barnes et al. 2014; Decamp et al. 2014; Epstein et al. 2014).
The Centers for Medicare & Medicaid Services (CMS) established the Hospital Readmissions Reduction Program in 2013.1 Under this program, payments are now reduced for hospitals with 30-day readmission rates higher than a national benchmark for patients with the diagnoses of heart attack, heart failure, or pneumonia. Payment reduction is expanding and now includes readmission after surgical procedures (specifically elective total hip or total knee arthroplasty and coronary artery bypass graft surgery). CMS has also begun to associate 30-day readmission rates after elective total joint arthroplasty (TJA) procedures as an overall surrogate measure of hospital quality (Grosso et al. 2012). Payers, providers, and policymakers have much impetus to enhance the quality of patient care during TJA procedures while reducing expenditures (Bozic et al. 2014).
The perioperative surgical home (PSH) has been proposed as a model to improve the delivery of perioperative healthcare via patient-centered optimization strategies that involve risk stratification and standardization of care (Kash et al. 2014; Cyriac et al. 2016; Raphael et al. 2014; Garson et al. 2014; Cannesson et al. 2014; Schweitzer et al. 2013; Mackey and Schweitzer 2014; Vetter et al. 2013, 2014; Desebbe et al. 2016). The PSH also introduces clinical opportunities for varied providers to collectively enhance care of the surgical patient (Kash et al. 2014). A prime example is the reduction of surgical readmissions, as in theory this would yield improved longitudinal care at reduced costs (Joynt and Jha 2012). As such, this case report will outline one model of a collaborative perioperative team operating within a PSH practice-model to reduce surgical readmissions after TJA procedures.
Implementation of a perioperative surgical home for total joint arthroplasty (TJA) procedures
With unique and cumulative insights, a multitude of disciplines including anesthesiology, orthopedic surgery, nursing, pharmacy, case management, social work, nutrition, physical therapy, and information technology closely collaborated to institute a PSH for primary TJA (hip and knee) procedures at UCI Health in October of 2012 (Cyriac et al. 2016; Raphael et al. 2014; Garson et al. 2014). Weekly meetings were coordinated and LEAN Six Sigma methodology (De Koning et al. 2006) was used to ultimately manifest clinical pathways that paralleled “patient-centered, multidisciplinary, and integrated care (Grocott and Mythen 2015)” as opposed to fragmented, variable, and inefficient care (Mackey 2012; Berwick and Hackbarth 2012). As an integral component of the implemented TJA PSH paradigm, concerted strategies designed to avert post-surgical readmissions were employed at all phases encountered during the perioperative continuum.
Preoperative measures to optimize readmission risk
Postoperative measures to optimize readmission risk
Most common risk factors and causes that contribute to readmission risk after a surgical intervention
Post-discharge measures to optimize readmission risk
Point of care (POC) assessment and intervention prospects to avert hospital readmissions
Opportunities to avert a readmission in the emergency room
1. Point of care (POC) ultrasonography (Ramsingh et al. 2015) for bedside assessment of cardiopulmonary function, volume status, vascular access, gastric volume, bladder volume
2. Advanced pain management intervention including multimodal therapy with regional techniques ± indwelling catheters
3. Liaisons to surgical services that may be confined to the operating room and delayed in patient assessment
4. Patient education, medication reconciliation, expectation management, multimodal anxiolysis
5. Postoperative nausea and emesis management
6. Assessment and management of perioperative medical complications
7. Assistance with transitions in care with community primary care providers (PCPs) or other specialists to provide rapid and appropriate disposition planning
Results and Discussion
This report describes our findings for unplanned 30-day readmissions in the first 2 years of the novel PSH program (October 1 2012 until September 30 2014). Institutional Review Board (IRB) approval was obtained for prospective data collection, analysis, and reporting (IRB HS # 2012-9273). Data was corroborated using hospital-based decision support, electronic medical record (Allscripts, Chicago, IL), and AIMS (SIS, Alpharetta, GA). A total of 328 unilateral, primary, and elective TJA (120 hip, 208 knee) procedures were collectively performed in year 1 and year 2. Demographic analysis reveals the following: mean age of 64 ± 12; BMI of 28.5 ± 6.2; ASA Score distribution of 0.3 % class 1, 23 % class 2, 72 % class 3, and 4.3 % class 4; and 62.5 % female patients.
Post PSH implementation TJA and readmission data year 1 and year 2
Year 1 post PSH implementation
Year 2 post PSH implementation
Total number of total joint arthroplasty
Total number of unplanned 30-day readmissions
• Disruption of external wound
• Dislocation of prosthetic joint
• Stress fracture of femoral neck
• Peri-prosthetic fracture
• Contracture of tendon
• Acute renal failure
30-day readmission ratea
Preventable readmissions remain a common target for the improvement of healthcare (Joynt and Jha 2012; Lucas and Pawlik 2014; Allaudeen et al. 2011; Merkow et al. 2015; Garrison et al. 2013; Zmistowski et al. 2013; Saucedo et al. 2014; Jencks et al. 2009; Tsai et al. 2013; Joynt et al. 2011). Although surgical readmissions account for less than a quarter of all hospital readmissions (Jencks et al. 2009), analysis has revealed significant disparities in re-hospitalization rates after surgery between institutions (Lucas and Pawlik 2014; Tsai et al. 2013). It can be debated as to whether this appropriately parallels the quality of care rendered by a particular hospital or rather is a reflection of greater readmission risk for hospitals providing care to patient populations with greater disease burden or lower socioeconomic status and support (Tsai et al. 2013; Joynt et al. 2011). Regardless, a large review demonstrated that the majority of surgical readmissions are attributable to new complications that can be predicted and are characteristic of a particular procedure (Merkow et al. 2015). These findings suggest that appropriate risk stratification and thoroughly preparing patients for post-hospital care present significant potential for healthcare systems endeavoring to reduce surgical readmissions.
In this case management report, we outline the use of the PSH as a model to reduce the incidence of readmission after TJA surgery. Our model resulted in lower readmission rates than those reported nationally in a statistically significant manner. There are several limitations that should be noted, including a limited sample size and duration, lack of control group of patients not enrolled in the program, and the ability to only capture institution-specific readmissions. Nevertheless, we submit that understanding general risk factors and causes (Table 1) for readmission in surgical patient populations will facilitate the development of evidence-based models aimed at both optimizing patients for early discharge as well as decreasing preventable readmission. While there are certainly recurring factors that must be accounted for, efforts aimed at decreasing unplanned readmissions are ultimately much more complex and dynamic. Corrective efforts must be holistic and tailored to the patient, surgery, and the facility, as each readmission ultimately reflects multifactorial underpinnings. For instance, we learned that at our institution post-surgical joint dislocations and fractures were the primary culprits for unplanned readmissions (Table 3), and future pathway revisions will evolve to optimize patient education and physical therapy for fall prevention. A delicate balance must also be achieved for proper “discharge optimization,” as the inherent investment of time and resources required may be significant. Frank divergence exists between reducing readmission and other important hospital goals, such as a fast-track discharge (Kehlet and Wilmore 2005) and decreased length of stay (Pearson et al. 2001).
Pathways and systems that are integrated into discharge processes need thorough vetting and contribution from practitioners with diversified perspectives. The PSH provides an institution-led means to optimize patient care by unifying resources available throughout the perioperative continuum (Kash et al. 2014; Cyriac et al. 2016; Raphael et al. 2014; Garson et al. 2014; Cannesson et al. 2014; Schweitzer et al. 2013; Mackey and Schweitzer 2014; Vetter et al. 2013, 2014). Beginning with an indication for surgery and extending to the post-discharge transfer of care back to a PCP, there are an abundance of opportunities to incorporate the evidence-based initiatives of the PSH. By means of interdisciplinary discharge planning and oversight of process outcomes that re-compose variable practices into uniformly implemented evidence-based models, potential gaps in care that expose patients to harm or potential readmission can be minimized. As outlined by the Institute for Healthcare Improvement’s “Triple Aim,” much of healthcare reform has revolved around the multifaceted goals of improving patient satisfaction, while decreasing morbidity and costs of care (Vetter et al. 2014). With this in mind, it is important to continually search for ways to improve longitudinal patient outcomes as illustrated by this case report describing the potential impact of the PSH care model on the important metric of readmission following elective TJA surgery.
Centers for Medicare & Medicaid Services. Readmission Reductions Program, 2014. Available from URL: https://www.cms.gov/medicare/medicare-fee-for-service-payment/acuteinpatientpps/readmissions-reduction-program.html, (Last Viewed June 2016)
Medicare.gov. 30-day unplanned readmission and death measures: complication rate for hip/knee replacement patients. 2016. Available from URL: https://www.medicare.gov/hospitalcompare/Data/30-day-measures.html, (Last Viewed August 2016)
Centers for Medicare & Medicaid Services
Center for Perioperative Care
Institutional Review Board
Primary care provider
Point of care
Perioperative surgical home
Total joint arthroplasty
University of California, Irvine
We thank Dr. Patrick Hu for his assistance with figure preparation.
This work was received from the School of Medicine and Department of Anesthesiology & Perioperative Care, University of California Irvine
Availability of data and materials
Authors will not share data because of potential future publications.
NA participated in the case-study design, figure design, contributed to the statistical analysis, and authored the manuscript; JR performed statistical analysis and co-authored the manuscript; BL participated in case-study design and figure design and co-authored the manuscript; DM participated in case-study design and co-authored the manuscript; SS participated in figure design and co-authored the manuscript; KA participated in case-study design and co-authored the manuscript; RS participated in case-study design and co-authored the manuscript; MC participated in case-study design and co-authored the manuscript; ZK participated in case-study design, contributed to figure design, contributed to statistical analysis, and co-authored the manuscript. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
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