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A Perioperative Medicine Model for Population Health: An Integrated Approach for an Evolving Clinical Science

Aronson, Solomon MD, MBA, FASA, FACC, FCCP, FAHA, FASE*; Westover, Julie BS*; Guinn, Nicole MD*; Setji, Tracy MD, MHS; Wischmeyer, Paul MD*; Gulur, Padma MD*; Hopkins, Thomas MD*; Seyler, Thorsten M. MD, PhD; Lagoo-Deendayalan, Sandhya MD, PhD§; Heflin, Mitchell T. MD, MHS; Thompson, Annemarie MD*; Swaminathan, Madhav MD*; Flanagan, Ellen MD*

Author Information
doi: 10.1213/ANE.0000000000002606

Table 1.
Table 1.:
Population Cohorts, Examples, and Potential for Value Creation

Value enhancement in health care is characterized as enhancing quality and/or decreasing cost for a “unit of care,”1 with the latter achieved by reducing or eliminating operational inefficiencies, redundancy, and/or unnecessary utilization. Operational inefficiencies such as overpriced drugs or contracted support account for only about 5% of total value destruction and are best managed with attention to negotiation, supply chain management, and similar business principals. More important, value in health care is lost when unnecessary use of resources during an episode of care or when unadvisable, unnecessary use of care occurs. The opportunity for greatest value enhancement therefore may indeed lie within the management of the most complex episodes of care for the sickest patients2,3 with early adoption of a best practice care design (Table 1). By 2020, it is predicted that 55 million adults in the United States will be ≥65 years of age,4 with half of the adult population having at least 1 chronic disease, and 25% having 2 or more chronic diseases. Surgical patients with multiple chronic conditions have a high risk of postoperative complications. The continued growth of the complex chronic disease and senior populations will inevitably make effective and safe perioperative care a major priority for health professionals, health systems, payers, and patients. With the present average cost of a surgical complication reported to be approximately $12,000 per episode,5 this trend no doubt, if left unchecked, will result in further increased growth in health care costs, with an estimated 19% of the US gross domestic product devoted to health care.6


The practice of perioperative medicine has been described as “the practice of patient-centered, multidisciplinary, and integrated medical care of patients from the moment of contemplation of surgery until full recovery.”7 After early institutional success with enhanced recovery after surgery (ERAS) protocols,8 the Perioperative Enhancement Team (POET) was formed at Duke University School of Medicine, in Durham, North Carolina, to enhance perioperative care reengineering processes. This publication describes the processes developed to address specific preoperative comorbidities as well as rationalization and implementation of other perioperative care programs, including a perioperative senior health clinic.

The POET is multidisciplinary and serves as a foundational function in perioperative care redesign that bridges strategy, operations, tactics, finance, workflow planning, project management, electronic medical record integration, implementation science, education and training, patient tracking, data tracking, continuous quality improvement, and reporting. The core group of POET includes physicians from anesthesiology, surgery, and internal medicine, and a team of nurses, managers, administrators, advanced practice providers, and support staff. Individual patient-centered services are managed in newly created independent clinics and/or coordinated into existing clinics that are staffed by physicians and extenders as needed. The decision to create an optimization program known as a Preoperative Risk Evaluation and Optimization (PREOp) clinic is the result of a collective and exhaustive decision process within the POET model (Table 2). This process includes generative discussion, gathering of content expertise, best practice research, and business case modeling. After a clinical outcome improvement and financial analysis is completed and judged to be compelling, key stakeholders are engaged to help redesign work streams, while clinical metrics are developed and informatics resources leveraged to enable continuous data tracking and facilitate continuous performance improvement. Early alignment with project management enables workflow to be effectively tied to the electronic health record. The process leverages existing data stores and builds new discrete data elements when necessary to build the architecture that is required to support longitudinal analyses. In its initial launch, direct and indirect costs for standing up POET were supported by the department of anesthesiology. Subsequently, institutional support has contributed to its sustainability and growth. The next derivative model for preoperative optimization known as the Preanesthesia Surgical Screening (PASS) clinic will be largely institutionally supported. Extensive financial modeling for the program has demonstrated a positive contribution margin to the institution.

Table 2.
Table 2.:
Perioperative Risk Evaluation and Optimization Programs at Duke

POET identifies and addresses process gaps for the unmet needs of patients for surgery by focusing on developing PREOp clinics for identifying, optimizing, and managing modifiable comorbidities. The Perioperative Optimization for Senior Health (POSH) clinic directly provides perioperative care for frail, older adults at high risk for adverse outcomes, including identifying and mitigating certain medical factors, as well as general goal setting and discharge care planning. The POSH clinic is supported by grants and by patient revenue streams for clinic visits. These initiatives have received recent attention9–12 as an innovative approach to deal with existing preoperative system challenges that result in suboptimal care, inefficiencies, and wasted resources. Before these initiatives, patients with a surgical need were simply identified and scheduled for surgery. Patients were screened by anesthesia before surgery typically at short notice before the day of surgery. After the operation, patients were typically managed by their surgeons and their teams, with input from consulting subspecialties when appropriate, up until the time of discharge. Since launching POET, a core group of dedicated providers (physicians, nurses, nurse managers, advanced practice providers, social workers, therapists, dieticians, and support staff) with a common interest in advancing the science of perioperative medicine now work together, share goals, improve quality, reduce redundancies, and improve transitions of care.

POET recognized that a traditional preoperative anesthesia clinic or preanesthesia testing (PAT) clinic, despite best efforts to accommodate patients’ evaluations before scheduled surgeries, often confronts time-limited constraints to assure that ideal recommendations for preoperative management of chronic comorbid conditions are fulfilled (Figure 1). Most often, risk assessment is accomplished and passed forward to others in the perioperative care delivery team so that any precautionary steps (if needed) are taken during surgery. It is less common that proactive management and responsibility of the chronic medical condition are undertaken before surgery. On few occasions, at the time of a PAT clinic visit typically days before surgery, an assessment of risk will be sufficiently high as to trigger an action to recommend surgery be postponed or cancelled.

Figure 1.
Figure 1.:
Old paradigm of pathway to surgery after declaration of surgery is made. ICU indicates intensive care unit; PACU, postoperative care unit; PAT, preanesthesia testing; SNF, skilled nursing facility.

However, the above-described process is fundamentally different for our POET–PREOp process, which involves earliest assessment of a patient at the time of surgical contemplation. The referral to any of the PREOp programs is primarily by the surgical team and the patient after a contemplation of a surgery treatment option threshold is crossed. The referral is done according to a predetermined protocol in accordance with agreed-upon threshold criteria of risk and within-care redesign pathways developed by POET. A “hub and spoke” organization between the surgical clinic and PREOp and PAT underscores the screening, which may involve point-of-care testing to enable early identification of modifiable high-risk conditions (Supplemental Digital Content 1, Figure 1, When a high-risk condition is identified, the patient is then referred to a PREOp program for management. The high-risk medical condition is then proactively managed. After a determination that optimization has occurred, the patient is then referred for routine preanesthesia and presurgery evaluation and teaching. Patients within each PREOp clinic are tracked by POET. Communication between the PREOp programs and surgery teams is monitored by POET.

Figure 2.
Figure 2.:
POET process from surgery contemplation to PREOp. POET indicates perioperative enhancement team; PREOp, perioperative risk evaluation and optimization.

POET recognized that a preoperative evaluation process should ideally acquire information, risk stratify, communicate, and coordinate risk reduction management, and that a team with a focus on preoperative screening and subsequent care optimization for modifiable risk factors should also provide patient education and patient (and family) engagement, with aligned expectations to the transition of care process. The process at Duke entails communication between providers and patients, as well as communication between primary care and specialty care clinics for scheduling coordination and patient tracking. These essential components were made possible by an advanced clinical informatics support structure that features discrete order entry, patient tracking, clinical decision support, and comprehensive data management. This core informatics infrastructure is leveraged as soon as the patient is enrolled in the POET care model. In addition to facilitating alignment with best practice for ordering appropriate preoperative laboratory studies, utilization of the order set and associated consult orders automatically notifies the subspecialty clinic that a “POET” patient has been identified and adds the patient to a list of similar patients that can be accessed by interdisciplinary care team members across the continuum of care. A functional clinical dashboard is then used to track patient progress in real time while they are enrolled in the optimization program and as they proceed from the preoperative to the intraoperative and postoperative experience. The system also facilitates communication of patient enrollment and provider alignment with best clinical practices on use of proprietary electronic order sets the day of the procedure by notifying the perioperative team when the patient arrives in the preoperative holding area (Figure 2).


Among the first preoperative care optimization clinics at Duke developed were the preoperative anemia clinic,13 the preoperative diabetes clinic,14 the preoperative nutrition optimization clinic, the perioperative pain clinic, and the POSH clinic.15 The typical process for transitional care redesign from “surgery declaration” to “surgery ready” involves a comprehensive approach that includes data review (eg, transfusion rate by procedure), risk determination (eg, hemoglobin [Hgb] associated with transfusion), workflow analysis, workflow design, staff planning, space planning, training, financial modeling, development of diagnostic and treatment plan(s), electronic medical record integration (order sets, scheduling, and communication), addressing patient education needs, and communication. A brief summary on rationalization and description for each preoperative care optimization clinic is provided.


Anemia is common in patients presenting for elective surgery, and is associated with increased risk of perioperative blood transfusion and consequential morbidity and mortality.16–18 Blood transfusion, in addition to its direct contribution to morbidity, also burdens a health system financially in terms of both direct (acquisition, inventory, and verification) and indirect (increased length of stay [LOS] and transfusion-related events) costs.19 When preoperative anemia is treated, reduced cost of care with improved quality of outcomes has been demonstrated.20 The incidence of anemia increases with age; therefore, the incidence of anemia in surgical populations is also likely to increase due to an increase in the demographic of elderly patients who will undergo surgical procedures.

POET developed and implemented a preoperative anemia clinic to diagnose and treat anemia in patients presenting for elective surgery with an aim to decrease transfusion rates, improve patient outcomes, improve patient satisfaction, and decrease costs to the institution.21,22 To date, more than 850 patients have been referred to the preoperative anemia clinic from orthopedics, high-risk obstetrics, and other surgical clinics (Supplemental Digital Content 2, Table 1, An institutional preoperative anemia treatment algorithm was developed by consensus and triggered when a patient is identified as high risk for transfusion (Supplemental Digital Content 1, Figure 2, A Hemocue point-of-care test (Quest Diagnostics, Madison, NJ) or an Hgb direct measurement from a complete blood count is incorporated into the algorithm for screening.

Although the prevalence of preoperative anemia according to the World Health Organization definition was approximately 18% overall for lower extremity total joint replacement patients at Duke, compared to 35% nationally,13 it was decided that an institution-specific definition of anemia to designate high risk would be used. It was determined after a chart review that the preoperative Hgb trigger associated with intraoperative transfusion practice was case specific and significantly less than the World Health Organization definition. For example, among orthopedic patients to date at Duke who were referred to the preoperative anemia clinic, the average presenting Hgb has been 10.4 mg/dL, whereas the average discharge Hgb was 12.5 mg/dL after 4–6 weeks of treatment (ie, erythropoietin or iron infusion), representing a substantial improvement in red cell mass. Preliminary observations indicate significant decrease in the transfusion rates among our highest risk for transfusion patient populations who were enrolled in the anemia clinic program.


The incidence of diabetes in the general US population and the surgical population is increasingly common: 29 million people in the United States (9% of the population) are affected by diabetes, and approximately 25% of these patients will require surgery. In addition, 5%–10% of patients presenting for surgery are found to have previously unrecognized diabetes, which is associated with higher preoperative blood glucose levels and a higher risk of perioperative mortality compared to patients who are aware of their diabetes.23–28 Poorly controlled diabetic patients before surgery impose a significant financial health resource burden, including prolonged ventilator dependence, postoperative infection, acute renal failure, increased hospital LOS, and postoperative loss of productivity. Moreover, poor preoperative glycemic control has been shown to portend poor intraoperative glycemic control, which is an established risk factor for perioperative morbidity.29–31

The aim for developing and implementing a preoperative diabetes clinic is to diagnose and treat patients with poor glycemic control presenting for elective surgery and thereby decrease related adverse sequelae. In addition, it was felt that identifying poorly controlled diabetes before surgery would be a responsible way to proactively implement strategies for enhancing a population health management agenda. The preoperative diabetes treatment algorithm developed by POET is triggered when a patient is identified as high risk by an Hgb A1c point-of-care screening test with a threshold of >7.5 (Supplemental Digital Content 1, Figure 3, To date, more than 100 patients have been referred to the preoperative diabetes clinic from orthopedics, surgical oncology, vascular surgery, and other surgical clinics (Supplemental Digital Content 2, Table 2, The approximate average presenting A1c for patients referred to the preoperative diabetic clinic has been >9.1, which equates to an estimated blood glucose of 215 mg/dL (range, 8–13.5 mg/dL). Patients referred to the preoperative diabetes clinic have seen a decrease in their A1c of nearly 2% and a decrease median day of surgery preoperative blood glucose level from prereferral to the preoperative diabetic clinic of nearly 65 mg/dL. The referral involves 4–12 weeks of focused treatment modification and consultation with an endocrinologist. Among the patients who were referred to the preoperative diabetes program, 75% were seen by a Duke endocrinologist, with a median treatment time of 31 days. Among patients who were referred to the preoperative diabetes clinic but chose not to participate in the program, more than half actively pursued treatment by another provider such as their primary care physician or local endocrinologist. Another metric of program success has been rapid access to the preoperative endocrinology service. A median wait time of 5–6 days for an appointment to the endocrinology consult service is significantly shortened for POET-designated patients compared to >40 days for patients without a POET designation. The high level of participation also indicates that this program is addressing an unmet need, and serves an important factor in contributing to patient satisfaction. Perhaps most important, >90% of the patients referred to the POET diabetes program had not been previously seen at Duke endocrinology, and many were unaware of their diabetes. This latter accomplishment of the preoperative diabetes clinic is demonstrative of an opportunity to incorporate new patients into chronic disease management initiatives within the health system. As a part of this pathway, patients are subsequently followed by the inpatient endocrinology team during hospitalization and after discharge. Throughout the process, health, economics, and long-term outcomes are tracked by POET.


Poor nutritional status at the time of surgery is common, particularly before gastrointestinal and oncologic procedures, with up to 65% of patients reported to be malnourished preoperatively.32–34 Surgical patients with unaddressed preoperative malnutrition experience significantly higher postoperative morbidity, infection, ventilator dependence, LOS, readmission rate, and hospital costs.35,36 In addition, elderly patients are also more likely to be at risk for poor nutrition and related adverse sequelae. Malnutrition defined as a body mass index <18.5 and/or albumin <3.0 has been a consensus criterion for patient exclusion at our institution for patient enrollment into the Centers for Medicare & Medicaid Services Comprehensive Care for Joint Replacement program37 in which we participate.

The aim for developing and implementing a preoperative nutrition clinic is to diagnose and treat patients presenting for elective surgery at risk for poor recovery and postoperative infection related to malnutrition. To screen patients for malnutrition before surgery, we developed a modified Malnutrition Universal Screening Tool named the Preoperative Nutrition Screen (PONS) to characterize risk attributable to nutrition and guide nutrition status changes after therapy.38,39 This novel screening tool, the PONS (Supplemental Digital Content 1, Figure 4,, developed for perioperative malnutrition risk assessment, relies on a history of unplanned weight loss, changes in eating habits, presenting body mass index, as well as vitamin D and albumin before surgery. Prealbumin, albumin, and vitamin D levels are checked in all patients who are evaluated for malnutrition before surgery. The PONS evaluation tool guides a preoperative treatment algorithm developed by POET (Supplemental Digital Content 1, Figure 5,


Chronic opioid users have been shown to comprise 15% to >50% of patients presenting for surgery in the United States,40 and tend to have higher intensity and a longer duration of pain after surgery. They have poorer outcomes from spine and joint replacement surgeries, and require supplemental opioids longer than opioid-naive patients.41 At Duke, these high-risk patients currently have a higher rate of 30-day readmissions and 30-day emergency department (ED) visits compared to opioid-naive patients.

The POET preoperative pain care clinic was launched in March 2017 to aid in the functional recovery of surgical patients with complex chronic pain syndromes through personalized care plans that address both pain and biopsychosocial factors that may hinder recovery. Patients are evaluated by medical history and physical examination with an opioid medication requirement of ≥60 mg morphine equivalent dose trigger for high risk. Management is then focused preoperatively to minimize risk of persistent postsurgery pain, with aims to prevent the transition from acute to chronic pain (Supplemental Digital Content 1, Figure 6, It is believed that patients undergoing surgery for chronic pain will benefit from personalized care to actively manage their recovery. The multimodal approach of the clinic includes nutrition experts, pain psychologists, and physical therapists, along with the anesthesia pain service. This POET preoperative ambulatory initiative is staffed by the same faculty team that serves the inpatient pain service, allowing for continuity of care throughout the perioperative period, which spans pain control needs before, during, and up to 90 days after patient hospital stay.


One third of inpatient surgical procedures in the United States are performed on a population segment that experiences the highest rates of complications. The geriatric population presents special challenges, including longer hospitalizations and loss of independence, that impede effective and safe perioperative care.

The POSH Clinic at Duke provides an opportunity for enhanced preoperative evaluation for these high-risk patients by a special geriatric consult team, which includes anesthesia, surgery, and internal medicine faculty. In the POSH model, older patients at highest risk of postoperative complications based on several risk factors (eg, cognitive impairment, poor nutritional status, multiple chronic diseases, impaired vision or hearing, and >80 years of age) are referred for preoperative functional status, mobility, cognition, mood, medications, nutrition, and social support15,42 evaluation to determine an individualized optimization strategy. In this model, both the patient and family members have an opportunity to discuss issues and participate actively in the patient’s decision-making before surgery and in the perioperative period. Postoperatively, the geriatrics team participates in the daily care of these hospitalized patients and assists with management of medications and chronic medical conditions (such as diabetes and high blood pressure), as well as working with patients and families to plan for discharge and posthospital care. The POSH initiative also provides caregiver support regarding education about expected outcomes, postoperative disposition/placement and care algorithms for treatment in advanced malignancy, and palliative care. To date, nearly 800 referrals to the POSH clinic have been made. Observed positive changes in disposition planning and reduced readmission rates for this population are presumed to be a consequence of increased patient and family engagement, better shared decision-making, and medical optimization.


While each health care system will reflect a unique blend of roles among physicians, nurses, and advanced practice providers, it was our goal to define new standards for risk evaluation, preoperative care optimization, and resource stratification using evidence-based interventions to improve patient outcomes and enhance the value of care. The current standard of care in the United States employs a PAT clinic just before an established surgical date (typically between 1 and 30 days). In other words, after a patient is declared to be a “surgical candidate,” the PAT clinic is an accepted part of the presurgical preparatory process to serve the principal role of enabling mandated presurgical history and physical examination requirements to be met.43 However, in this traditional preanesthesia evaluation and testing model, it is common that there is minimal opportunity to effectively impact management of chronic comorbid medical conditions and thereby best ensure surgical readiness. Because surgery dates are set at this stage, any active management if it were to occur would likely portend a disruptive scheduling outcome. Ideally, a surgical care plan should begin when a patient is first identified for surgery and should include coordination between relevant specialties and support services so that essential medical data and information for the patient are appropriately shared and continue seamlessly until the patient is fully recovered from surgery. The surgical readiness processes should include an assessment, coordination, and triage process whereby a patient is directed to a PREOp program or a POSH clinic when appropriate after the contemplation of “surgical management” is considered. This comprehensive perioperative medicine presurgery to surgery-ready transformation processes occurs at our PASS clinic (Figure 3). Going forward, the PASS clinic will funnel all surgical candidates through a common screening corridor to enable greater central coordination and greater efficiency.

Figure 3.
Figure 3.:
PASS model. MAPS indicates multidiscipline acute postoperative service; PASS, preanesthesia surgical screening; PAT, preanesthesia testing; POSH, perioperative optimization for senior health.

We have implemented a proof-of-concept process for patients enrolled in our Comprehensive Care for Joint Replacement program, whereby stop criteria are applied for patients designated to this care bundle. The criteria include smoking and not actively engaged with a smoking cessation program, A1c > 7.5%, Hgb < 11 mg/dL, platelet count <50,000, end-stage renal disease on hemodialysis, coronary stenting with or without acute myocardial infarction within the past 9 months, stroke or transient ischemic attack within the previous 9 months, any active infections, any open wounds, uncontrolled hypothyroid or hyperthyroid or hyperparathyroidism, chronic obstructive pulmonary disease on oxygen, and chronic high-dose narcotic use (>60 mg MSO4 equivalent/day or addiction). It is noteworthy that many of the aforementioned stop criteria are modifiable comorbidities and triggers to defer the patient to a PREOp clinic for management before being considered “ready for surgery.” It is our goal to address these (and other) modifiable conditions for all elective surgical conditions in our PASS clinic model.

Also of note, we believe the contemplation of surgery rather than the declaration of surgery should ignite the evaluation process because it may be appropriate, and the responsibility of specialists, to steer patients away from surgery when the risks are determined to significantly outweigh the benefits. That said, the described new paradigm for preoperative optimization should enable better fulfillment of surgical readiness goals in any given patient. This, in turn, should help with decision-making for optimization before surgery and help predict resource allocation needs after surgery. Ideally, the paradigm incorporates a patient and family advisory council before surgery to enhance patient and family involvement in shared decision-making when considering surgery.

Centralization of preoperative optimization services depend on institutional needs and conditions. The hub and spoke model for transitional care clinics can be independent of or coexist with a single dedicated central space that houses all essential stakeholders (eg, a registered dietician, physical therapist, diabetic specialist, pain specialist, geriatrician, certified tobacco cessation behavior specialist, and social worker) along with the team responsible for general preoperative anesthesia readiness evaluation and training. PREOp programs ideally also perform counseling for diet modification and smoking cessation; screening for preventive health metrics, including flu and pneumococcal vaccination compliance; adherence to best practice perioperative laboratory testing standards; as well as candidacy for other perioperative optimization strategies such as need for POSH, alignment with and education for ERAS, candidacy for perioperative blood management protocols, need for perioperative device management, or evaluation by our Perioperative Chronic Pain Management Center. Finally, at an appropriate clinic-specific, surgical case-specific and patient-specific time (which is not necessarily immediately after surgery), management of the patient’s perioperative medical comorbidities is transferred to the appropriate PCP.


In addition to preoperative optimization, POET has formed a multidisciplinary team to focus on coagulation management. The Coagulation and Lysis Oversight Team has developed intraoperative and postoperative blood management and transfusion algorithms for trauma, cardiovascular and obstetric surgery, as well as perioperative management care pathways for patients with coagulation disorders. Other initiatives being developed include the Perioperative Anesthesia Cardiac Electrophysiology Devices team, trained to assist with perioperative device management needs during surgery, a perioperative smoking cessation program, a preoperative allergy testing clinic, an obstructive sleep apnea clinic, as well as postoperative care navigation and coordination. The Multidisciplinary Acute Postop Service (MAPS) is expected to compliment POSH postoperative management of high-risk elderly patients by ensuring adherences to ERAS care protocols,44 acute pain management, postoperative medical management, nutrition management, and rehabilitation to reduce postoperative adverse events and facilitate throughput and expedited hospital discharge. These teams require individuals with unique understanding, experience, and expertise in perioperative medicine, and are best served by a core group of invested physicians, nurses, and advanced practice providers.

POET has also been involved with redesigning the care of patients outside the perioperative setting, specifically in the domain of patients with chronic pain syndromes who are not directly associated with a declaration of surgery. Chronic pain affects >30% of the US population, with increasing incidence in females, the elderly, and patients of low socioeconomic status, with attributable costs estimated at $250–$500 billion per year.45 Patients with poorly managed pain are common high utilizers of acute care services, and account for a disproportionate share of hospitalizations and emergency department (ED) visits. These patients are reported to have up to 4 times the number of annual inpatient admissions compared to matched controls.46–48 POET, with hospitalists, emergency medicine physicians, social workers, and pain physicians, developed a program that provides care options for “high utilizers” of the ED (ie, ≥5 ED visits in a 6-month period). The POET initiative known as Pain Assessment Risk Treatments for Novel Effective Recovery uses a screening tool to assess and capture high utilizers and initiates an ED diversion care pathway to decrease downstream emergency room congestion and reduce costs.49

Figure 4.
Figure 4.:
POET model encompasses the entire perioperative journey from declaration of surgery throughout after discharge through transition of care. CLOT indicates Coagulation and Lysis Oversight Team; ERAS, enhance recovery after surgery; ICU, intensive care unit; MAPS, multidiscipline acute postoperative service; PACED, perioperative cardiac electrophysiology devices; PACU, postanesthesia care unit; PASS, preanesthesia surgical screening; PAT, preanesthesia testing; POET, perioperative enhancement team; POSH, perioperative optimization for senior health; ReDUCE, Responsible Drug Use and Cost Effective initiative; RRT, rapid response team; SNF, skilled nursing facility.

POET focus is to meet the evolving needs of the perioperative medicine50 population (Figure 4) with continued development of clinical pathways for surgical patients. Eventually, optimization planning will be used to better direct bed, staff, and other logistic needs, and engagement with payers to incentivize and restructure payment based on risk management in the ecosystem of population health will follow. Finally, attention to continually acquire key data elements and build a data repository to ultimately develop large-scale perioperative medicine population health research initiatives will be essential.


Name: Solomon Aronson, MD, MBA, FASA, FACC, FCCP, FAHA, FASE.

Contribution: This author helped with the concept and hypothesis generation, and helped collect the data, analyze the data, and edit the manuscript.

Conflicts of Interest: None.

Name: Julie Westover, BS.

Contribution: This author helped collect the data, analyze the data, and edit the manuscript.

Conflicts of Interest: None.

Name: Nicole Guinn, MD.

Contribution: This author helped collect thedata, analyze the data, and edit the manuscript.

Conflicts of Interest: None.

Name: Tracy Setji, MD, MHS.

Contribution: This author helped collect thedata, analyze the data, and edit the manuscript.

Conflicts of Interest: None.

Name: Paul Wischmeyer, MD.

Contribution: This author helped collect thedata, analyze the data, and edit the manuscript.

Conflicts of Interest: P. Wischmeyer declares the following conflicts of interest: Abbott Nutrition—consulting, research grants, and continuous medical education (CME) speaker in areas of perioperative and critical care malnutrition; Baxter—research grants and consulting on hospital malnutrition; Nutricia—consulting on hospital and intensive care unit (ICU) malnutrition; Fresenius Kabi—research grants and consulting on hospital and ICU malnutrition; B. Braun—CME speaking on hospital malnutrition; Lyric Inc—research grant and consulting on ICU nutrition

Name: Padma Gulur, MD.

Contribution: This author helped collect thedata, analyze the data, and edit the manuscript.

Conflicts of Interest: None.

Name: Thomas Hopkins, MD.

Contribution: This author helped edit the manuscript.

Conflicts of Interest: None.

Name: Thorsten M. Seyler, MD, PhD.

Contribution: This author helped edit themanuscript.

Conflicts of Interest: None.

Name: Sandhya Lagoo-Deendayalan, MD, PhD.

Contribution: This author helped collect thedata, analyze the data, and edit the manuscript.

Conflicts of Interest: None.

Name: Mitchell T. Heflin, MD, MHS.

Contribution: This author helped collect thedata, analyze the data, and edit the manuscript.

Conflicts of Interest: None.

Name: Annemarie Thompson, MD.

Contribution: This author helped edit themanuscript.

Conflicts of Interest: None.

Name: Madhav Swaminathan, MD.

Contribution: This author helped edit themanuscript.

Conflicts of Interest: None.

Name: Ellen Flanagan, MD.

Contribution: This author helped edit themanuscript.

Conflicts of Interest: None.

This manuscript was handled by: Thomas R. Vetter, MD, MPH.

Acting EIC on final acceptance: Thomas R. Vetter, MD, MPH.


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