Rationale and Design of an Evidence Based Tool to Guide Preoperative Evaluation and Management

Article Citation:

Alex Campbell, David Ingham, Joshua Mueller, Timothy Henry, Scott Sharkey, and Michael Cummings (2018) Rationale and Design of an Evidence Based Tool to Guide Preoperative Evaluation and Management. Journal of the Minneapolis Heart Institute Foundation: Fall/Winter 2018, Vol. 2, No. 2, pp. 16-21.

Review Paper

Alex Campbell, MD

David Ingham, DO

Joshua Mueller, MD

Timothy Henry, MD

Scott Sharkey, MD

Michael Cummings, MS, MD

Minneapolis Heart Institute, Abbott Northwestern Hospital, Minneapolis, MN; Abbott Northwestern Hospital, Minneapolis, MN; Abbott Northwestern Internal Medicine Residency Program, Minneapolis, MN; Abbott Northwestern General Medicine Associates, Edina, MN

Address for Correspondence: Alex Campbell, MD, Minneapolis Heart Institute, 920 E 28th Street #300, Minneapolis, Minnesota 55407, Tel: 612-863-3900 E-mail: Alex.Campbell@allina.com

ABSTRACT

In the United States, over testing and over treatment are recognized as the cause of both excess cost and patient harm. Healthcare value (defined as “health outcomes achieved relative to the costs of care”) has become a focus to improve the quality and affordability of healthcare. Perioperative evaluation and management of the surgical patient represents a clear opportunity to improve healthcare value. Herein, we describe the rationale for and the development of a standardized clinical decision support tool that has been distributed to over 600 clinicians performing preoperative evaluations. All patients undergoing this evaluation will be tracked, with the intent to publish both healthcare cost and safety outcomes. The use of a perioperative decision support tool is a unique approach to value in healthcare.

Keywords: perioperative, standardization, value, safety

INTRODUCTION

Perioperative evaluation and management of the surgical patient represents a clear opportunity to improve healthcare value.1,2 Annual spending on preoperative testing in the United States exceeds 18 billion dollars, the majority of which is low value and does not improve patient outcomes.1 Furthermore, mismanagement of high-risk perioperative medications—in particular, antiplatelet and anticoagulation agents—exposes patients to the risk of both bleeding and thrombotic complications. Unfortunately, recommendations regarding antiplatelet and anticoagulant management are often vague and frequently not followed.3–6

Preoperative testing should be selective, based on medical morbidities and surgical risk.7–9 Despite society guidelines recommending the elimination of routine testing, there has been little change in this practice over the past two decades.10,11

While guidelines and best practice recommendations have largely failed to reduce preoperative testing, there is preliminary evidence that unnecessary testing is reduced by utilizing trained preoperative teams in designated clinics using standardized testing protocols.12,13 This divergence between effective perioperative management and real-world practice provides an opportunity to standardize perioperative management with the goal of reducing costs and improving patient outcomes. Therefore, we developed a cloud-based decision tool to guide clinician preoperative testing, standardize high risk medication management, and facilitate clinician communication across a large health system.

EVIDENCE REVIEW

The evidence for preoperative testing is largely based on expert opinion. Current guidelines recommend that preoperative testing should be guided by the history and physical examination, medical record review, and consideration of procedure complexity and potential for blood loss.9,14,15Laboratory TestingHemoglobin and coagulation studies

A history of anemia is an indication for obtaining a hemoglobin prior to low-risk procedures. In intermediate and high-risk procedures, with potential for significant blood loss, obtaining a baseline hemoglobin is recommended.9,16 Routine coagulation studies or platelet counts are not predictive of perioperative bleeding. A history of increased bleeding or clinical conditions that predispose to bleeding (eg, liver disease) are indications for coagulation studies.9,17Electrolytes

For routine preoperative testing, the incidence of unexpected electrolyte derangement is very low. Preoperative measurement of electrolytes should be based on specific clinical indications such as diuretic use. History of kidney disease is an indication for renal function testing.9,17Urinalysis

High-quality evidence does not support preoperative screening for asymptomatic bacteriuria in asymptomatic patients.9,18Timing

In those with an indication for laboratory testing, it is reasonable to use results obtained within the past 30 days.19Cardiovascular Evaluation

In general, preoperative cardiovascular testing (eg, stress testing, EKG, echocardiography) should be driven by standard clinical indications. A planned surgical procedure is not an indication for preoperative testing.20

Abnormalities on preoperative EKGs are common but of limited value in predicting perioperative complications.21,22 The ACC/AHA recommends against obtaining routine EKGs in patients undergoing low-risk surgeries. Furthermore, obtaining EKGs in asymptomatic patients undergoing low-risk surgeries may lead to further unnecessary testing. In patients undergoing intermediate and high-risk surgeries, however, a baseline EKG may be useful in the event of postoperative status changes.20

Patients with good functional capacity of ≥4 METS (brisk walk, climbing one flight of stairs without stopping) have very low perioperative risk and generally require no preoperative stress testing irrespective of surgical risk. However, current guidelines are inconclusive regarding stress testing in patients with poor functional capacity.6,20Importantly, in the only randomized trial evaluating high-risk patients undergoing high-risk major vascular surgery, prophylactic revascularization was not beneficial.23 In fact, most perioperative myocardial infarctions are not caused by hemodynamically significant epicardial artery stenoses.24 Consequently, the strategy of stress testing with subsequent prophylactic revascularization is unlikely to be effective in prevention of perioperative myocardial infarction.25,26High-risk Medication ManagementAntiplatelet Therapy in Patients With Coronary Artery Disease, Including Prior PCI

The 2014 POISE-2 trial demonstrated no benefit with low-dose perioperative aspirin therapy, even in patients with established vascular disease. However, a subsequent sub-study has suggested lower major adverse event rates in those patients with prior coronary stenting. Therefore, low-dose aspirin should be continued for patients with prior stents and held in most other circumstances.26–28

Approximately 10% of all patients who undergo coronary stenting require non-cardiac surgery within 1 year. Dual antiplatelet therapy (DAPT)—ie, aspirin and a P2Y12 inhibitor—significantly increases the risk of major surgical bleeding. The decision to interrupt P2Y12 (often while continuing low-dose aspirin therapy) depends on the timing of, indication for, and type of stent implanted in context of risk of surgical bleeding.4,5,29

The risk of stent thrombosis decreases with time. In general, the risk of stent thrombosis is low (<1%) when DAPT is discontinued ≥1 month post bare metal stent (BMS) and ≥6 months post drug eluting stent (DES) implant. Current US guidelines continue to recommend delaying elective surgery for at least 6 months post DES and at least 4 weeks post BMS.4,5,30Bridging of Anticoagulation for Atrial Fibrillation

Although bridging for atrial fibrillation is frequently used, there is insufficient direct evidence to support this practice.3,6 The 2015 BRIDGE trial showed no reduction in thromboembolic events while tripling the risk of major bleeding. However, only 3% of the studied population had a CHADS2 score of 5 to 6; therefore, the benefit of bridging in high risk patients is unknown.31

Surprisingly, 30% of physicians bridge patients who are at low risk for thromboembolism. Furthermore, the observational trial, ORBITA-AF, showed no difference in risk scores between patients bridged and not bridged, suggesting indiscriminate bridging. In aggregate, these data suggest net harm to bridging of many patients in contemporary practice.3

The CHA2DS2-VASC and the CHADS2 score are validated risk models for estimating annual stroke rates for stable outpatient atrial fibrillation patients. However, these risk models were never intended to stratify perioperative risk of thromboembolism, nor have either been validated in the perioperative setting. In attempting to estimate periprocedural thrombotic risk, we use the CHADS2 score, as this was the model used in the lone randomized trial of bridging to date.31

TOOL DEVELOPMENT

Following an extensive review of the primary literature and all major society perioperative guidelines, we developed an algorithm to guide preoperative testing and medication management. Numerous studies have demonstrated the uptake of computerized decision support (CDS) tools by physicians to be suboptimal.32 Based on our own experience, we believe this is due to the overly complicated design of many such tools. Thus, we developed a CDS tool with a simple, user-friendly front-end interface for data entry and coupled it with a complex back-end design that seamlessly generates recommendations. Three attributes—procedure risk, patient specific characteristics, and procedural bleeding risk—are the basis for the tool’s recommendations. The number of possible combinations and permutations addressed by the tool are vast. When the evidence is clear (eg, testing prior to cataract surgery),33 the recommendation is prescriptive. When the evidence is less clear (eg, bridging for atrial fibrillation with a high CHA2DS2-VASC score), the recommendation is contextual. In these situations, we have recommended a shared decision involving the clinician and the patient.

USER INTERFACE

Procedural Risk (Figure 1)

Consensus does not exist on the optimal determination of the risk inherent to a specific procedure. Procedural risk categories are based on the modified Johns Hopkins surgical criteria, ACC/AHA joint surgical classifications, and expert opinion.33


FIGURE 1
Procedure risk categories.

Patient Characteristics (Figure 2)

Age, gender, renal function (Cockcroft-Gault equation), morbidities, medications, and functional capacity are some of the features considered under the patient characteristic category.

FIGURE 2
Patient-specific characteristics.

Bleeding Risk (Figure 3)

Bleeding risk is determined by the specific procedure and the anesthetic modality most commonly utilized for that procedure.


FIGURE 3
Surgery-specific bleeding risk.

TOOL OUTPUT

As shown in Figure 4, the Summary and Recommendations page assists the clinician in the preoperative evaluation while subsequently improving communication to anesthesiology and the surgeon. A focused summary of recommendations are provided to the ordering physician, anesthesiologist, and surgeon. A patient handout is then printed with clear instructions directing medication management.


FIGURE 4
Final output to communicate patient risk, recommend testing, and guide medication management.

STUDY GOALS

In January 2018, the tool was made available to approximately 600 clinicians performing preoperative evaluations at 63 clinics across Allina Health Systems, Minneapolis, MN. Tool utilization, cost of testing, rates of bleeding and thrombotic complications, length of stay, and readmission rates will be compared before and after tool implementation. Furthermore, given the large number of patients undergoing surgeries across the system, we hope to fill particular evidence gaps such as the impact of bridging decisions in high-risk atrial fibrillation patients

CONCLUSIONS

We developed a value-based preoperative clinical decision tool to guide appropriate testing and standardize management of high risk medications. Despite the complexity of the underlying algorithms, every effort was made to ensure simplicity of the user interface. The tool has been distributed to over 600 clinicians throughout Allina, and data are being tracked to assess both financial and quality outcomes.

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