Anesthesiologists' Role in Value-based Perioperative Care and Healthcare Transformation

Closing the Chasm: Understanding and Addressing the Anesthesia Workforce Supply and Demand Imbalance

The imbalance in anesthesia workforce supply and demand has been exacerbated post-COVID due to a surge in demand for anesthesia care, especially in non-operating room anesthetizing sites, at a faster rate than the increase in anesthesia clinicians. The consequences of this imbalance or labor shortage compromise healthcare facilities, adversely affect the cost of care, worsen anesthesia workforce burnout, disrupt procedural and surgical schedules, and threaten academic missions and the ability to educate future anesthesiologists. In developing possible solutions, one must examine emerging trends that are affecting the anesthesia workforce, new technologies that will transform anesthesia care and the workforce, and financial considerations, including governmental payment policies. Possible practice solutions to this imbalance will require both short- and long-term multifactorial approaches that include increasing training positions and retention policies, improving capacity through innovations, leveraging technology, and addressing financial constraints.

Value-based preoperative assessment in a large academic hospital

BACKGROUND

Value-based healthcare (VBHC) is an approach that focuses on delivering the highest possible value for patients while driving cost efficiency in health services. It emphasizes improving patient outcomes and experiences while optimizing the use of resources, shifting the healthcare system's focus from the volume of services to the value delivered. Our study assessed the effectiveness of implementing a VBHC-principled, tailored preoperative evaluation in enhancing patient care and outcomes, as well as reducing healthcare costs.

METHODS

We employed a quality improvement, before-and-after approach to assessing the effects of implementing VBHC strategies on the restructuring of the preoperative evaluation clinics at Humanitas Research Hospital. The intervention introduced a VBHC-tailored risk matrix during the postintervention phase (year 2021), and the results were compared with those of the preintervention phase (2019). The primary study outcome was the difference in the number of preoperative tests and visits at baseline and after the VBHC approach. Secondary outcomes were patient outcomes and costs.

RESULTS

A total of 9722 patients were included: 5242 during 2019 (baseline) and 4,480 during 2021 (VBHC approach). The median age of the population was 63 (IQR 51-72), 23% of patients were classified as ASA 3 and 4, and 26.8% (2,955 cases) were day surgery cases. We found a considerable decrease in the number of preoperative tests ordered for each patient [6.2 (2.5) vs 5.3 (2.6) tests, p < 0.001]. The number of preoperative chest X-ray, electrocardiogram, and cardiac exams decreased significantly with VBHC. The length of the preoperative evaluation was significantly shorter with VBHC [373 (136) vs 290 (157) min, p < 0.001]. Cost analysis demonstrated a significant reduction in costs, while there was no difference in clinical outcomes.

CONCLUSIONS

We demonstrated the feasibility, safety, and cost-effectiveness of a tailored approach for preoperative evaluation. The implementation of VBHC enhanced value, as evidenced by decreased patient time in preoperative evaluation and by a reduction in unnecessary preoperative tests.

A Novel Digital Health Platform With Health Coaches to Optimize Surgical Patients: Feasibility Study at a Large Academic Health System

BACKGROUND

Pip is a novel digital health platform (DHP) that combines human health coaches (HCs) and technology with patient-facing content. This combination has not been studied in perioperative surgical optimization.

OBJECTIVE

This study's aim was to test the feasibility of the Pip platform for deploying perioperative, digital, patient-facing optimization guidelines to elective surgical patients, assisted by an HC, at predefined intervals in the perioperative journey.

METHODS

We conducted an institutional review board-approved, descriptive, prospective feasibility study of patients scheduled for elective surgery and invited to enroll in Pip from 2.5 to 4 weeks preoperatively through 4 weeks postoperatively at an academic medical center between November 22, 2022, and March 27, 2023. Descriptive primary end points were patient-reported outcomes, including patient satisfaction and engagement, and Pip HC evaluations. Secondary end points included mean or median length of stay (LOS), readmission at 7 and 30 days, and emergency department use within 30 days. Secondary end points were compared between patients who received Pip versus patients who did not receive Pip using stabilized inverse probability of treatment weighting.

RESULTS

A total of 283 patients were invited, of whom 172 (60.8%) enrolled in Pip. Of these, 80.2% (138/172) patients had ≥1 HC session and proceeded to surgery, and 70.3% (97/138) of the enrolled patients engaged with Pip postoperatively. The mean engagement began 27 days before surgery. Pip demonstrated an 82% weekly engagement rate with HCs. Patients attended an average of 6.7 HC sessions. Of those patients that completed surveys (95/138, 68.8%), high satisfaction scores were recorded (mean 4.8/5; n=95). Patients strongly agreed that HCs helped them throughout the perioperative process (mean 4.97/5; n=33). The average net promoter score was 9.7 out of 10. A total of 268 patients in the non-Pip group and 128 patients in the Pip group had appropriate overlapping distributions of stabilized inverse probability of treatment weighting for the analytic sample. The Pip cohort was associated with LOS reduction when compared to the non-Pip cohort (mean 2.4 vs 3.1 days; median 1.9, IQR 1.0-3.1 vs median 3.0, IQR 1.1-3.9 days; mean ratio 0.76; 95% CI 0.62-0.93; P=.009). The Pip cohort experienced a 49% lower risk of 7-day readmission (relative risk [RR] 0.51, 95% CI 0.11-2.31; P=.38) and a 17% lower risk of 30-day readmission (RR 0.83, 95% CI 0.30-2.31; P=.73), though these did not reach statistical significance. Both cohorts had similar 30-day emergency department returns (RR 1.06, 95% CI 0.56-2.01, P=.85).

CONCLUSIONS

Pip is a novel mobile DHP combining human HCs and perioperative optimization content that is feasible to engage patients in their perioperative journey and is associated with reduced hospital LOS. Further studies assessing the impact on clinical and patient-reported outcomes from the use of Pip or similar DHPs HC combinations during the perioperative journey are required.

PRO: Implementation Science Has Value in Anesthesiology and Cardiothoracic Surgery

Implementation science is a nascent field that aims to study the factors that influence the effectiveness of a given clinical intervention, such as the characteristics of the individuals involved, the internal and external settings, the process of implementation, and other factors. Overall, implementation science aims to increase the extent to which an intervention is practiced, and the quality of its delivery to a patient. Although still in its infancy, the applications of implementation science in anesthesiology and cardiothoracic surgery abound. Whether used to adopt novel innovations, avoid the use of obsolete practices, or redeploy existing interventions to improve quality, implementation science holds promise in optimizing how we bring the latest in clinical science to produce tangible benefits to patients and create sustainable change.

Exploring the opportunities and challenges of implementing artificial intelligence in healthcare: A systematic literature review

Recent progress in the realm of artificial intelligence has shown effectiveness in various industries, particularly within the healthcare sector. However, there are limited insights on existing studies regarding ethical, social, privacy, and technological aspects of AI in the health sector, which is the gap our study aims to fill. This study aimed to synthesize empirical studies on the challenges and opportunities of using AI by conducting a systematic review. We reviewed 33 articles published between 2015 and 2022 in the PubMed, IEEE Xplore, and Science Direct databases. The results show that artificial intelligence has the promise of improving health care and faces obstacles when implemented. Most of the reviewed studies indicated that the use of AI provides several opportunities, including teamwork and decision-making, technological advancement, diagnosis and patient monitoring, drug development, and virtual health assistance. However, the findings show that the use of AI in the health sector hinders multifaceted challenges, including ethical and privacy-related issues, lack of awareness, unreliability of technology, and professional liability. The findings highlight that artificial intelligence has the potential to transform healthcare and that addressing these challenges is crucial to fully utilize its potential.

Scoping Review: Anesthesiologist Involvement in Alternative Payment Models, Value Measurement, and Nonclinical Capabilities for Success in the United States of America

The US healthcare sector is undergoing significant payment reforms, leading to the emergence of Alternative Payment Models (APMs) aimed at improving clinical outcomes and patient experiences while reducing costs. This scoping review provides an overview of the involvement of anesthesiologists in APMs as found in published literature. It specifically aims to categorize and understand the breadth and depth of their participation, revolving around 3 main axes or "Aims": (1) shaping APMs through design and implementation, (2) gauging the value and quality of care provided by anesthesiologists within these models, and (3) enhancing nonclinical abilities of anesthesiologists for promoting more value in care. To map out the existing literature, a comprehensive search of relevant electronic databases was conducted, yielding a total of 2173 articles, of which 24 met the inclusion criteria, comprising 21 prospective or retrospective cohort studies, 2 surveys, and 1 case-control cohort study. Eleven publications (45%) discussed value-based, bundled, or episode-based payments, whereas the rest discussed non-payment-based models, such as Enhanced Recovery After Surgery (7 articles, 29%), Perioperative Surgical Home (4 articles, 17%), or other models (3 articles, 13%).The review identified key themes related to each aim. The most prominent themes for aim 1 included protocol standardization (16 articles, 67%), design and implementation leadership (8 articles, 33%), multidisciplinary collaboration (7 articles, 29%), and role expansion (5 articles, 21%). For aim 2, the common themes were Process-Based & Patient-Centric Metrics (1 article, 4%), Shared Accountability (3 articles, 13%), and Time-Driven Activity-Based Costing (TDABC) (3 articles, 13%). Furthermore, we identified a wide range of quality metrics, spanning 8 domains that were used in these studies to evaluate anesthesiologists' performance. For aim 3, the main extracted themes included Education on Healthcare Transformation and Policies (3 articles, 13%), Exploring Collaborative Leadership Skills (5 articles, 21%), and Embracing Advanced Analytics and Data Transparency (4 articles, 17%).Findings revealed the pivotal role of anesthesiologists in the design, implementation, and refinement of these emerging delivery and payment models. Our results highlight that while payment models are shifting toward value, patient-centered metrics have yet to be widely accepted for use in measuring quality and affecting payment for anesthesiologists. Gaps remain in understanding how anesthesiologists assess their direct impact and strategies for enhancing the sustainability of anesthesia practices. This review underscores the need for future research contributing to the successful adaptation of clinical practices in this new era of healthcare delivery.

Severe Postoperative Pain in Total Knee Arthroplasty Patients: Risk Factors, Insights and Implications for Pain Management via a Digital Health Approach

Up to 25% of patients undergoing knee arthroplasty report chronic pain postoperatively. Early identification of high-risk individuals can enhance pain management strategies. This retrospective analysis investigates the incidence of severe postoperative pain and its associated risk factors among 740 patients who underwent total knee arthroplasty. Utilizing a digital application, patients provided comprehensive data encompassing pre- and postoperative pain levels, analgesic usage, and completed a chronic pain risk assessment. Participants were categorized into two distinct groups based on their pain status at three months post-op: Group D+ (14%), characterized by pain scores exceeding 40/100 and/or the utilization of level 2 or 3 analgesics, and Group D- (86%), who did not meet these criteria. An analysis of pain trajectories within these groups revealed a non-linear progression, with specific patterns emerging amongst those predisposed to chronic pain. Notably, patients with a trajectory towards chronic pain exhibited a plateau in pain intensity approximately three weeks post-surgery. Significant preoperative risk factors were identified, including elevated initial pain levels, the presence of comorbidities, pain in other body areas, heightened joint sensitivity and stiffness. This study highlights the utility of digital platforms in enhancing patient care, particularly through the continuous monitoring of pain. Such an approach facilitates the early identification of potential complications and enables timely interventions.

Quality indicators and outcomes in ambulatory surgery

PURPOSE OF REVIEW

Quality indicators are used to monitor the quality and safety of care in ambulatory surgery, a specialty in which major morbidity and mortality remain low. As the demand for safe and cost-effective ambulatory surgical care continues to increase, quality indicators and metrics are becoming critical tools used to provide optimal care for these patients.

RECENT FINDINGS

Quality indicators are tools used by both regulatory agencies and surgical centers to improve safety and quality of ambulatory surgical and anesthetic care. These metrics are also being used to develop value-based payment models that focus on efficient, safe, and effective patient care. Patient reported outcome measures are a growing method of collecting data on the satisfaction and postoperative recovery period for ambulatory surgical patients. Monitoring of perioperative efficiency and utilization using quality metrics are important to the financial health of ambulatory surgical centers.

SUMMARY

Quality indicators will continue to play a growing role in the monitoring of quality and safety in ambulatory surgery, especially with the trend towards value-based reimbursement models and efficient, cost-effective surgical care. Additionally, quality indicators are useful tools to monitor postoperative patient outcomes and recovery pathways and the efficiency of operating room utilization and scheduling.

Can we nudge to reduce the perioperative low value care? Decision making factors influencing safe practice implementation

PURPOSE OF THE REVIEW

Highlight sources of low-value care (LVC) during the perioperative period help understanding the decision making behind its persistence, the barriers for change, and the potential implementation strategies to reduce it.

RECENT FINDINGS

The behavioural economics science spread of use through aligned strategies or nudge units offer an opportunity to improve success in the LVC reduction.

SUMMARY

LVC, such as unneeded surgeries, or preanaesthesia tests for low-risk surgeries in low-risk patients, is a relevant source of waste and preventable harm, most especially in the perioperative period. Despite the international focus on it, initial efforts to reduce it in the last decade have not clearly shown a sustainable improvement. Understanding the shared decision-making process and the barriers to be expected when tackling LVC is the first step to build the change. Applying a structured strategy based on the behavioural science principles may be the path to increasing high value care in an effective an efficient way. It is time to foster nudge units at different healthcare system levels.

Value-Based Care and Anesthesiology in the USA

Value-based care, prioritizing patient outcomes over service volume, is steering a transformative course in anesthesiology in the United States. With the rise of this patient-centric approach, anesthesiologists are adopting dynamic roles to meet the demands of medical institutions, insurers, and patients for high-quality, cost-effective care. The urgency for this transition is accentuated by persistent challenges in reducing postoperative mortality rates and surgical complications, further spotlighted by the coronvirus disease 2019 (COVID-19) pandemic. Anesthesiologists engage in preoperative optimization, personalized care delivery, and evidence-based practices, bolstering their influence in the perioperative environment. Their collaboration with perioperative stakeholders propels the shift toward a value-driven healthcare landscape. This review analyzes the implementation of value-based care in American anesthesiology, assesses the significance of technology in enhancing its delivery, and outlines potential strategies for improving its application.

Development and Validation of a Machine Learning Model to Identify Patients Before Surgery at High Risk for Postoperative Adverse Events

Importance

Identifying patients at high risk of adverse outcomes prior to surgery may allow for interventions associated with improved postoperative outcomes; however, few tools exist for automated prediction.

Objective

To evaluate the accuracy of an automated machine-learning model in the identification of patients at high risk of adverse outcomes from surgery using only data in the electronic health record.

Design, Setting, and Participants

This prognostic study was conducted among 1 477 561 patients undergoing surgery at 20 community and tertiary care hospitals in the University of Pittsburgh Medical Center (UPMC) health network. The study included 3 phases: (1) building and validating a model on a retrospective population, (2) testing model accuracy on a retrospective population, and (3) validating the model prospectively in clinical care. A gradient-boosted decision tree machine learning method was used for developing a preoperative surgical risk prediction tool. The Shapley additive explanations method was used for model interpretability and further validation. Accuracy was compared between the UPMC model and National Surgical Quality Improvement Program (NSQIP) surgical risk calculator for predicting mortality. Data were analyzed from September through December 2021.

Exposure

Undergoing any type of surgical procedure.

Main Outcomes and Measures

Postoperative mortality and major adverse cardiac and cerebrovascular events (MACCEs) at 30 days were evaluated.

Results

Among 1 477 561 patients included in model development (806 148 females [54.5%; mean [SD] age, 56.8 [17.9] years), 1 016 966 patient encounters were used for training and 254 242 separate encounters were used for testing the model. After deployment in clinical use, another 206 353 patients were prospectively evaluated; an additional 902 patients were selected for comparing the accuracy of the UPMC model and NSQIP tool for predicting mortality. The area under the receiver operating characteristic curve (AUROC) for mortality was 0.972 (95% CI, 0.971-0.973) for the training set and 0.946 (95% CI, 0.943-0.948) for the test set. The AUROC for MACCE and mortality was 0.923 (95% CI, 0.922-0.924) on the training and 0.899 (95% CI, 0.896-0.902) on the test set. In prospective evaluation, the AUROC for mortality was 0.956 (95% CI, 0.953-0.959), sensitivity was 2148 of 2517 patients (85.3%), specificity was 186 286 of 203 836 patients (91.4%), and negative predictive value was 186 286 of 186 655 patients (99.8%). The model outperformed the NSQIP tool as measured by AUROC (0.945 [95% CI, 0.914-0.977] vs 0.897 [95% CI, 0.854-0.941], for a difference of 0.048), specificity (0.87 [95% CI, 0.83-0.89] vs 0.68 [95% CI, 0.65-0.69]), and accuracy (0.85 [95% CI, 0.82-0.87] vs 0.69 [95% CI, 0.66, 0.72]).

Conclusions and Relevance

This study found that an automated machine learning model was accurate in identifying patients undergoing surgery who were at high risk of adverse outcomes using only preoperative variables within the electronic health record, with superior performance compared with the NSQIP calculator. These findings suggest that using this model to identify patients at increased risk of adverse outcomes prior to surgery may allow for individualized perioperative care, which may be associated with improved outcomes.

Collaboration for Evidence-based Practice and Research in Anaesthesia (CEPRA): A consortium initiative for perioperative research

Evidence in perioperative care is insufficient. There is an urgent need for large perioperative research programmes, including pragmatic randomised trials, testing daily clinical treatments and unanswered question, thereby providing solid evidence for effects of interventions given to a large and growing number of patients undergoing surgery and anaesthesia. This may be achieved through large collaborations. Collaboration for Evidence-based Practice and Research in Anaesthesia (CEPRA) is a novel collaborative research network founded to pursue evidence-based answers to major clinical questions in perioperative medicine. The aims of CEPRA are to (1) improve clinical treatment and outcomes and optimise the use of resources for patients undergoing anaesthesia and perioperative care, and (2) disseminate results and inform caretakers, patients and relatives, and policymakers of evidence-based treatments in anaesthesia and perioperative medicine. CEPRA is inclusive in its concept. We aim to extend our collaboration with all relevant clinical collaborators and patient associations and representatives. Although initiated in Denmark, CEPRA seeks to develop an international network infrastructure, for example, with other Nordic countries. The work of CEPRA will follow the highest methodological standards. The organisation aims to structure and optimise any element of the research collaboration to reduce economic costs and harness benefits from well-functioning research infrastructure. This includes successive continuation of trials, harmonisation of outcomes, and alignment of data management systems. This paper presents the initiation and visions of the CEPRA network. CEPRA aims to be inclusive, patient-focused, methodologically sound, and to optimise all aspects of research logistics. This will translate into faster research conduct, reliable results, and accelerated clinical implementation of results, thereby benefiting millions of patients whilst being cost and labour-saving.

Economic Evaluation of Anesthesiology-Led Cardiac Implantable Electronic Device Service

BACKGROUND

Implementation of an anesthesiology-led cardiac implantable electronic device (CIED) service can be viewed to have economic and efficiency challenges. This study evaluates the cost savings of an anesthesiology-led CIED service.

METHODS

A total of 830 patients presented in the pre-implementation period from 1 March 2016 to 31 December 2017, and 1981 patients presented in the post-implementation period from 1 January 2018 to 31 October 2021. Interrupted time-series analysis for single-group comparisons was used to evaluate the cost savings resulting from reduction in operating room (OR) start delays for patients with CIEDs.

RESULTS

OR start-time delay was reduced by 10.6 min (95%CI: -20.5 to -0.83), comparing pre- to post-implementation. For an OR cost of USD 45/min, we estimated the direct cost to the department to be USD 1.68/min. The intervention translated into a total cost reduction during the intervention period of USD 250,000 (USD 18,000 to USD 470,000) per year for the institution and USD 9800 (USD 730 to USD 17,000) per year for the department. The yearly cost of employing a full-time team of CIED specialists would have been USD 135,456. The service triggered electrophysiology consultation on 13 device malfunctions.

CONCLUSIONS

An anesthesiology-led CIED service resulted in substantial cost savings, increased OR efficiency and patient safety.

Patient safety and staff psychological safety: A mixed methods study on aspects of teamwork in the operating room

Objectives

To predict the amount of teamwork that takes place throughout a surgery, based on performing a preoperative safety standards (surgical safety checklist and surgical count) and to explore factors affecting patient safety and staff psychological safety during a surgery, based on interprofessional teamwork.

Methods

This mixed methods study included quantitative and qualitative analyses. Quantitative data included 2,184 direct observations of surgical cases with regard to the performance of safety standards during surgeries in 29 hospitals, analyzed using multivariate binary logistic regressions. Qualitative data were obtained from an analysis of 25 semi-structured interviews with operating room (OR) clinicians and risk managers, using an inductive thematic analysis approach.

Results

Analysis of the OR observations revealed that a lack of teamwork in the preoperative "sign-in" phase doubled the chances of there being a lack of teamwork during surgery [odds ratio = 1.972, 95% confidence interval (CI) 1.741, 2.233, p < 0.001] and during the "time-out" phase (odds ratio = 2.142, 95% CI 1.879, 2.441, p < 0.001). Consistent presence of staff during surgery significantly increased teamwork, by 21% for physicians and 24% for nurses (p < 0.05), but staff turnover significantly decreased teamwork, by 73% for physicians (p < 0.05). Interview data indicated that patient safety and staff psychological safety are related to a perception of a collaborative team role among OR staff, with mutual commitment and effective interprofessional communication.

Conclusions

Healthcare organizations should consider the key finding of this study when trying to identify factors that affect teamwork during a surgery. Effective preoperative teamwork positively affects intraoperative teamwork, as does the presence of more clinicians participating in a surgery, with no turnover. Other factors include working in a fixed, designated team, led by a surgeon, which functions with effective interprofessional communication that promotes patient safety and staff psychological safety.

Does multimodal perioperative pain management enhance immediate and short-term outcomes after living donor partial hepatectomy? A systematic review of the literature and expert panel recommendations

BACKGROUND

The optimal analgesic strategy for patients undergoing donor hepatectomy is not known and the potential short- and long-term physical and psychological consequences of complications are significant.

OBJECTIVES

To identify whether a multimodal approach to pain of the donor intraoperatively enhances immediate and short-term outcomes after living liver donation, and to provide international expert panel recommendations.

DATA SOURCES

Ovid MEDLINE, Embase, Scopus, Google Scholar, and Cochrane Central.

METHODS

Systematic review following PRISMA guidelines and recommendations using the GRADE approach derived from an international expert panel. PROSPERO 2021 CRD42021260699.

RESULTS

Nine studies assessing multi-modal analgesia strategies were included in a qualitative assessment. Interventions included local, regional, and neuro-axial anesthetic techniques, pharmacological intervention (NSAIDs, COX-2 inhibitors, ketamine, dexmedetomidine, and lidocaine), and acupuncture. Overall, there was a significant (40%) reduction in opioid requirement on day 1 and a significant reduction in pain scores in the intervention vs control groups. Significant reductions in either length of stay or post-operative complications were demonstrated in four of nine studies.

CONCLUSIONS

Opioid use for patients undergoing donor hepatectomy is likely to impact both their short- and long-term outcomes. To reduce post-operative pain scores, shorten length of hospital stay, and promote earlier post-operative return of bowel function, we recommend that multi-modal analgesia be offered to patients undergoing living donor hepatectomy. Further research is required to confirm which multi-modal techniques are most associated with enhanced recovery in living liver donors.

Prehabilitation of Cardiac Surgical Patients, Part 1: Anemia, Diabetes Mellitus, Obesity, Sleep Apnea, and Cardiac Rehabilitation

The concept of "prehabilitation" consists of screening for and identification of pre-existing disorders followed by medical optimization. This is performed for many types of surgery, but may have profound impacts on outcomes particularly in cardiac surgery given the multiple comorbidities typically carried by these patients. Components of prehabilitation include direct medical intervention by preoperative specialists as well as significant care coordination and shared decision making. In this two-part review, the authors describe existing evidence to support the optimization of various preoperative problems and present a few institutional protocols utilized by our center for cardiac presurgical care. This first installment will focus on the management of anemia, obesity, sleep apnea, diabetes, and cardiac rehabilitation prior to surgery. The second will focus on frailty, malnutrition, respiratory disease, alcohol and smoking cessation, and depression.

Perioperative Brain Health in the Older Adult: A Patient Safety Imperative

While people 65 years of age and older represent 16% of the population in the United States, they account for >40% of surgical procedures performed each year. Maintaining brain health after anesthesia and surgery is not only important to our patients, but it is also an increasingly important patient safety imperative for the specialty of anesthesiology. Aging is a complex process that diminishes the reserve of every organ system and often results in a patient who is vulnerable to the stress of surgery. The brain is no exception, and many older patients present with preoperative cognitive impairment that is undiagnosed. As we age, a number of changes occur in the human brain, resulting in a patient who is less resilient to perioperative stress, making older adults more susceptible to the phenotypic expression of perioperative neurocognitive disorders. This review summarizes the current scientific and clinical understanding of perioperative neurocognitive disorders and recommends patient-centered, age-focused interventions that can better mitigate risk, prevent harm, and improve outcomes for our patients. Finally, it discusses the emerging topic of sleep and cognitive health and other future frontiers of scientific inquiry that might inform clinical best practices.

Pro-Con Debate: Anesthesiologist- Versus Hospitalist- Run Preoperative Clinics and Perioperative Care

In this Pro-Con commentary article, we discuss the models, value propositions, and opportunities of preoperative clinics run by anesthesiologists versus hospitalists and their role in perioperative care. The medical and anesthesia evaluation before surgery has pivoted from the model of "clearance" to the model of risk assessment, preparation, and optimization of medical and psychosocial risk factors. Assessment of these risk factors, optimization, and care coordination in the preoperative period has expanded the roles of anesthesiologists and hospitalists as members of the perioperative care team. There is ongoing debate regarding which model of preoperative assessment provides the most optimal preparation for the patient undergoing surgery. This article hopes to shed light on this debate with the data and perspectives on these care models.

Dollars for Diagnosis: A Single-Institutional Analysis of Billing for Intraoperative Transesophageal Echocardiography Examinations

OBJECTIVES

The authors sought to identify correctable reasons for the failed completion of required billing elements necessary for the reimbursement of services for intraoperative transesophageal echocardiography (TEE).

DESIGN

This was a retrospective study.

SETTING

This study was completed at a single institution and large academic center.

PARTICIPANTS

The patient population included all adult patients who underwent cardiac surgery at a single academic center over one year.

INTERVENTIONS

This retrospective review of TEE documentation and billing data was performed for the all adults undergoing cardiac surgery over the course of one year.

METHODS AND MAIN RESULTS

Documentation characteristics were compared between examinations that were reimbursed and those that were not. Out of 504 TEE examinations, 30% were not reimbursed. For these examinations, there was a lower compliance in the completion of minimum billing requirements, compared with those that were reimbursed; designation as "diagnostic" (29% v 93%, respectively, p < 0.0001), procedure note (70% v 99%, p < 0.0001), and procedure order (67% v 98%, p = 0.0002). The total estimated annual loss in revenue was $36,000.

CONCLUSIONS

Understanding documentation requirements for TEE is an overlooked but important part of anesthesiology practice that may lead to substantial cost savings. Completion of a procedure note, procedure order, and documentation of an examination as "diagnostic" was associated with successful billing.