Impact of adding therapeutic recommendations to risk assessments from a prediction model for postoperative nausea and vomiting

Comparison of prophylaxis strategy for postoperative nausea and vomiting and its incidence before and after the implementation of 5-hydroxytryptamine 3 in surgical setting: a single-center, retrospective study

PURPOSE

To investigate the association between adherence to guideline-recommended risk-based postoperative nausea and vomiting (PONV) prophylaxis, the antiemetics used for PONV prophylaxis, and the incidence of PONV in patients who were underwent general anesthesia before and after 5-HT3 receptor antagonists became available.

METHODS

Patients (≥ 20 years old) who were extubated after scheduled surgery and returned to general wards between January 2021 and February 2022 and between June 2022 and July 2023 were included. Risk factors included age < 50, female, motion sickness, nonsmoker, surgical factors, and postoperative opioid use. Two and three or more prophylaxis were recommended for patients with one or two and three or more risk factors, respectively. The primary outcome was the number of patients who received adequate prophylaxis, and the secondary outcomes were antiemetic agents used during anesthesia and the incidence of PONV on postoperative days 0 and 1. PONV was defined as documented PONV or rescue antiemetic administration.

RESULTS

From January 2021 to February 2022 and from June 2022 to July 2023, 2342 and 2682 patients were included, respectively. Before ondansetron became available, more D2 receptor antagonists were used (p < 0.001), and after ondansetron became available, both ondansetron (p < 0.001) and propofol (p < 0.001) were given more frequently. Before and after ondansetron became available, the number of patients with adequate prophylaxis was 3.7% and 9.2%, respectively (p < 0.001), and the incidence of PONV on postoperative days 0 and 1 was 44.6% and 44.0%, respectively (p = 0.67).

CONCLUSION

The availability of ondansetron increased the number of patients with adequate PONV prophylaxis, but did not decrease the incidence of PONV.

[Comparison of different prediction models for the occurrence of nausea and vomiting in the postoperative phase : A systematic qualitative comparison based on prospectively defined quality indicators]

BACKGROUND

Various prognostic prediction models exist for evaluating the risk of nausea and vomiting in the postoperative period (PONV). So far, no systematic comparison of these prognostic scores is available.

METHOD

A systematic literature search was carried out in seven medical databases to find publications on prognostic PONV models. Identified scores were assessed against prospectively defined quality criteria, including generalizability, validation and clinical relevance of the models.

RESULTS

The literature search revealed 62 relevant publications with a total of 81,834 patients which could be assigned to 8 prognostic models. The simplified Apfel score performed best, primarily because it was extensively validated. The Van den Bosch score and Sinclair score tied for second place. The simplified Koivuranta score was in third place.

CONCLUSION

The qualitative analysis highlights the strengths and weaknesses of each prediction system based on predetermined standardized quality criteria.

Anesthesia decision analysis using a cloud-based big data platform

Big data technologies have proliferated since the dawn of the cloud-computing era. Traditional data storage, extraction, transformation, and analysis technologies have thus become unsuitable for the large volume, diversity, high processing speed, and low value density of big data in medical strategies, which require the development of novel big data application technologies. In this regard, we investigated the most recent big data platform breakthroughs in anesthesiology and designed an anesthesia decision model based on a cloud system for storing and analyzing massive amounts of data from anesthetic records. The presented Anesthesia Decision Analysis Platform performs distributed computing on medical records via several programming tools, and provides services such as keyword search, data filtering, and basic statistics to reduce inaccurate and subjective judgments by decision-makers. Importantly, it can potentially to improve anesthetic strategy and create individualized anesthesia decisions, lowering the likelihood of perioperative complications.

Impact of goal-directed hemodynamic therapy on perioperative outcomes in head and neck free flap surgery: A before-and-after pilot study

Background

Free flap reconstruction for head and neck cancer is associated with a high risk of perioperative complications. One of the modifiable risk factors associated with perioperative morbidity is intraoperative hypotension (IOH). The main aim of this pilot study is to determine if the intraoperative use of goal-directed hemodynamic therapy (GDHT) is associated with a reduction in the number of IOH events in this population.

Methods

A before-and-after study design. The patients who had intraoperative GDHT were compared to patients from a previous period before the implementation of GDHT. The primary outcome was the number of IOH episodes defined as five or more successive minutes with a mean arterial pressure <65 mmHg. The secondary outcomes included major postoperative morbidity and 30-day mortality.

Results

A total of 414 patients were included. These were divided into two groups. The control group (n = 346; January 1, 2018, to December 31, 2019), and the monitored group (n = 68; January 1, 2020, to May 1, 2021). The median intraoperative administered fluid volume was similar between the control and monitored groups (2250 interquartile range [IQR] [1607-3050] vs. 2210 IQR [1700-2807] mL). The monitored group was found to have an increased use of norepinephrine and dobutamine (respectively, 1.2% vs. 5.9% and 2.4% vs. 30.9%; p < 0.05). When adjusting for confounders (comorbidities, estimated blood loss, and duration of anesthesia) the incidence rate ratio (95% confidence interval) of number of IOH events was 0.94 (0.86-1.03), p = 0.24. The rate of postoperative flap and medical complications did not differ between the two groups.

Conclusions

Even though the use of vasopressors/inotropes was higher in the monitored group, the number of IOH episodes and postoperative morbidity and mortality were similar between the two groups. Further change in hemodynamic management will require the use of specific blood pressure targets in the GDHT fluid algorithm.

Machine learning-based causal models for predicting the response of individual patients to dexamethasone treatment as prophylactic antiemetic

Risk-based strategies are widely used for decision making in the prophylaxis of postoperative nausea and vomiting (PONV), a major complication of general anesthesia. However, whether risk is associated with individual treatment effect remains uncertain. Here, we used machine learning-based algorithms for estimating the conditional average treatment effect (CATE) (double machine learning [DML], doubly robust [DR] learner, forest DML, and generalized random forest) to predict the treatment response heterogeneity of dexamethasone, the first choice for prophylactic antiemetics. Electronic health record data of 2026 adult patients who underwent general anesthesia from January to June 2020 were analyzed. The results indicated that only a small subset of patients respond to dexamethasone treatment, and many patients may be non-responders. Estimated CATE did not correlate with predicted risk, suggesting that risk may not be associated with individual treatment responses. The current study suggests that predicting treatment responders by CATE models may be more appropriate for clinical decision making than conventional risk-based strategy.

Clinical practice guidelines for enhanced recovery after colon and rectal surgery from the American Society of Colon and Rectal Surgeons and the Society of American Gastrointestinal and Endoscopic Surgeons

The American Society of Colon and Rectal Surgeons (ASCRS) and the Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) are dedicated to ensuring high-quality innovative patient care for surgical patients by advancing the science, prevention, and management of disorders and diseases of the colon, rectum, and anus as well as minimally invasive surgery. The ASCRS and SAGES society members involved in the creation of these guidelines were chosen because they have demonstrated expertise in the specialty of colon and rectal surgery and enhanced recovery. This consensus document was created to lead international efforts in defining quality care for conditions related to the colon, rectum, and anus and develop clinical practice guidelines based on the best available evidence. While not proscriptive, these guidelines provide information on which decisions can be made and do not dictate a specific form of treatment. These guidelines are intended for the use of all practitioners, healthcare workers, and patients who desire information about the management of the conditions addressed by the topics covered in these guidelines. These guidelines should not be deemed inclusive of all proper methods of care nor exclusive of methods of care reasonably directed toward obtaining the same results. The ultimate judgment regarding the propriety of any specific procedure must be made by the physician in light of all the circumstances presented by the individual patient. This clinical practice guideline represents a collaborative effort between the American Society of Colon and Rectal Surgeons (ASCRS) and the Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) and was approved by both societies.

Management of postoperative nausea and vomiting in adults: current controversies

PURPOSE OF REVIEW

Postoperative nausea and vomiting (PONV) continue to plague the surgical patient population with an adverse impact on postoperative outcomes. The aim of this review is to critically assess current evidence for PONV management, including studies evaluating baseline risk reduction and antiemetic prophylaxis, to provide a pragmatic approach to prevention and treatment of PONV in routine clinical practice.

RECENT FINDINGS

Multiple recent reviews and guidelines have been published on this topic with some limitations. In the current ERAS era, all patients irrespective of their PONV risk should receive two to three antiemetics for prophylaxis. Patients at a high risk of PONV [i.e. prior history of PONV, history of motion sickness, high opioid requirements after surgery (e.g. inability to use nonopioid analgesic techniques)] should receive three to four antiemetics for prophylaxis.

SUMMARY

This review provides a practical approach to PONV prevention based on recent literature.

An Electronic Medical Record-Derived Individualized Performance Metric to Measure Risk-Adjusted Adherence with Perioperative Prophylactic Bundles for Health Care Disparity Research and Implementation Science

BACKGROUND

Health care disparity persists despite vigorous countermeasures. Clinician performance is paramount for equitable care processes and outcomes. However, precise and valid individual performance measures remain elusive.

OBJECTIVES

We sought to develop a generalizable, rigorous, risk-adjusted metric for individual clinician performance (MIP) derived directly from the electronic medical record (EMR) to provide visual, personalized feedback.

METHODS

We conceptualized MIP as risk responsiveness, i.e., administering an increasing number of interventions contingent on patient risk. We embedded MIP in a hierarchical statistical model, reflecting contemporary nested health care delivery. We tested MIP by investigating the adherence with prophylactic bundles to reduce the risk of postoperative nausea and vomiting (PONV), retrieving PONV risk factors and prophylactic antiemetic interventions from the EMR. We explored the impact of social determinants of health on MIP.

RESULTS

We extracted data from the EMR on 25,980 elective anesthesia cases performed at Penn State Milton S. Hershey Medical Center between June 3, 2018 and March 31, 2019. Limiting the data by anesthesia Current Procedural Terminology code and to complete cases with PONV risk and antiemetic interventions, we evaluated the performance of 83 anesthesia clinicians on 2,211 anesthesia cases. Our metric demonstrated considerable variance between clinicians in the adherence to risk-adjusted utilization of antiemetic interventions. Risk seemed to drive utilization only in few clinicians. We demonstrated the impact of social determinants of health on MIP, illustrating its utility for health science and disparity research.

CONCLUSION

The strength of our novel measure of individual clinician performance is its generalizability, as well as its intuitive graphical representation of risk-adjusted individual performance. However, accuracy, precision and validity, stability over time, sensitivity to system perturbations, and acceptance among clinicians remain to be evaluated.

Pharmacist-driven multidisciplinary initiative continuously improves postoperative nausea and vomiting in female patients undergoing abdominal surgery

WHAT IS KNOWN AND OBJECTIVE

The incorrect or insufficient prophylaxis of postoperative nausea and vomiting (PONV) is common in practice. A clinical pharmacist-led guidance team (CPGT) was established and included in general surgery teams.

OBJECTIVE

This study aimed to evaluate the effects of the CPGT on the improvement of PONV and prophylaxis administration.

METHODS

A prospective before-after study was conducted on 156 female patients undergoing abdominal surgery at a Chinese tertiary teaching hospital from December 2016 to December 2017. A total of 82 patients were enrolled in the preintervention period, and 74 patients were included in the post-intervention period. The CPGT established the evidence-based criteria for prophylactic anti-emetic administration and conducted interventions, including a review of medical records, provision of feedback, educational outreach, and dedicated support. Primary outcomes included the incidence of PONV within 24 hours of surgery, administered number of prophylactic anti-emetics, and accuracy of the timing for prophylactic anti-emetics. Outcomes were analysed by logistic regression or multivariable linear regression.

RESULTS AND DISCUSSION

After intervention, patients reported significantly less PONV (33.78% vs 56.10%; odds ratio [OR]: 0.29; numbers needed to treat [NNT]: 3.47), vomiting (29.73% vs 45.12%; OR: 0.42; NNT: 5.16) and nausea (31.08% vs 56.10%; OR: 0.24; NNT: 3.19) within 24 hours of surgery. The accuracy of the timing for prophylactic anti-emetics significantly increased (OR: 3.66; P: .003). Anaesthesiologists administered increased numbers of prophylactic anti-emetics (OR: 5.82; P < .001). The improvement of PONV did not decrease during the four-month period after intervention (P: .639).

WHAT IS NEW AND CONCLUSION

The CPGT is a valuable service model to continuously improve PONV and optimize prophylaxis administration.

Effect of Electronic Prescribing Strategies on Medication Error and Harm in Hospital: a Systematic Review and Meta-analysis

BACKGROUND

Computerized physician order entry and clinical decision support systems are electronic prescribing strategies that are increasingly used to improve patient safety. Previous reviews show limited effect on patient outcomes. Our objective was to assess the impact of electronic prescribing strategies on medication errors and patient harm in hospitalized patients.

METHODS

MEDLINE, EMBASE, CENTRAL, and CINAHL were searched from January 2007 to January 2018. We included prospective studies that compared hospital-based electronic prescribing strategies with control, and reported on medication error or patient harm. Data were abstracted by two reviewers and pooled using random effects model. Study quality was assessed using the Effective Practice and Organisation of Care and evidence quality was assessed using Grading of Recommendations Assessment, Development, and Evaluation.

RESULTS

Thirty-eight studies were included; comprised of 11 randomized control trials and 27 non-randomized interventional studies. Electronic prescribing strategies reduced medication errors (RR 0.24 (95% CI 0.13, 0.46), I² 98%, n = 11) and dosing errors (RR 0.17 (95% CI 0.08, 0.38), I² 96%, n = 9), with both risk ratios significantly affected by advancing year of publication. There was a significant effect of electronic prescribing strategies on adverse drug events (ADEs) (RR 0.52 (95% CI 0.40, 0.68), I² 0%, n = 2), but not on preventable ADEs (RR 0.55 (95% CI 0.30, 1.01), I² 78%, n = 3), hypoglycemia (RR 1.03 (95% CI 0.62-1.70), I² 28%, n = 7), length of stay (MD - 0.18 (95% - 1.42, 1.05), I² 94%, n = 7), or mortality (RR 0.97 (95% CI 0.79, 1.19), I² 74%, n = 9). The quality of evidence was rated very low.

DISCUSSION

Electronic prescribing strategies decrease medication errors and adverse drug events, but had no effect on other patient outcomes. Conservative interpretations of these findings are supported by significant heterogeneity and the preponderance of low-quality studies.

Dynamic predictive model for postoperative nausea and vomiting for intravenous fentanyl patient-controlled analgesia

Postoperative nausea and vomiting is the most common side-effect of opioid-based intravenous patient-controlled analgesia. Apfel's simplified risk score is popular but it has some limitations. We developed and validated a dynamic predictive model for nausea or vomiting up to 48 postoperative hours, available as an online web application. Fentanyl was used by 22,144 adult patients for analgesia after non-cardiac surgery under general anaesthesia: we randomly divided them into development (80%) and validation (20%) cohorts, repeated 100 times. We used linear discriminant analysis to select variables for multivariate logistic regression. The incidences of postoperative nausea or vomiting were: 0-48 h, 5691/22,144 (26%); 0-6 h, 2749/22,144 (12%); 6-12 h, 2687/22,144 (12%); 12-18 h, 2624/22,144 (12%); 18-24 h, 1884/22,144 (9%); and 24-48 h, 1082/22,144 (5%). The median (95%CI) area under the receiver operating characteristic curve was 0.72 (0.71-0.73) up to 48 postoperative hours compared with 0.65 (0.64-0.66) for the Apfel model, p < 0.001. The equivalent areas for 0-6 h, 6-12 h, 12-18 h, 18-24 h and 24-48 h were: 0.70 (0.69-0.72); 0.71 (0.69-0.73); 0.69 (0.68-0.71); 0.70 (0.67-0.72); and 0.69 (0.66-0.71), respectively. Our web application allows clinicians to calculate incidences of nausea and vomiting in patients receiving intravenous fentanyl for patient-controlled analgesia.

Methodological standards for the development and evaluation of clinical prediction rules: a review of the literature

Clinical prediction rules (CPRs) that predict the absolute risk of a clinical condition or future outcome for individual patients are abundant in the medical literature; however, systematic reviews have demonstrated shortcomings in the methodological quality and reporting of prediction studies. To maximise the potential and clinical usefulness of CPRs, they must be rigorously developed and validated, and their impact on clinical practice and patient outcomes must be evaluated. This review aims to present a comprehensive overview of the stages involved in the development, validation and evaluation of CPRs, and to describe in detail the methodological standards required at each stage, illustrated with examples where appropriate. Important features of the study design, statistical analysis, modelling strategy, data collection, performance assessment, CPR presentation and reporting are discussed, in addition to other, often overlooked aspects such as the acceptability, cost-effectiveness and longer-term implementation of CPRs, and their comparison with clinical judgement. Although the development and evaluation of a robust, clinically useful CPR is anything but straightforward, adherence to the plethora of methodological standards, recommendations and frameworks at each stage will assist in the development of a rigorous CPR that has the potential to contribute usefully to clinical practice and decision-making and have a positive impact on patient care.

Guidelines for Perioperative Care in Elective Colorectal Surgery: Enhanced Recovery After Surgery (ERAS®) Society Recommendations: 2018

BACKGROUND

This is the fourth updated Enhanced Recovery After Surgery (ERAS®) Society guideline presenting a consensus for optimal perioperative care in colorectal surgery and providing graded recommendations for each ERAS item within the ERAS® protocol.

METHODS

A wide database search on English literature publications was performed. Studies on each item within the protocol were selected with particular attention paid to meta-analyses, randomised controlled trials and large prospective cohorts and examined, reviewed and graded according to Grading of Recommendations, Assessment, Development and Evaluation (GRADE) system.

RESULTS

All recommendations on ERAS® protocol items are based on best available evidence; good-quality trials; meta-analyses of good-quality trials; or large cohort studies. The level of evidence for the use of each item is presented accordingly.

CONCLUSIONS

The evidence base and recommendation for items within the multimodal perioperative care pathway are presented by the ERAS® Society in this comprehensive consensus review.

What we can learn from Big Data about factors influencing perioperative outcome

PURPOSE OF REVIEW

This narrative review will discuss what value Big Data has to offer anesthesiology and aims to highlight recently published articles of large databases exploring factors influencing perioperative outcome. Additionally, the future perspectives of Big Data and its major pitfalls will be discussed.

RECENT FINDINGS

The potential of Big Data has given an incentive to create nationwide and anesthesia-initiated registries like the MPOG and NACOR. These large databases have contributed in elucidating some of the rare perioperative complications, such as declined cognition after exposure to general anesthesia and epidural hematomas in parturients. Additionally, they are useful in finding patterns such as similar outcome in subtypes of beta-blockers and lower incidence of pneumonia in preoperative influenza vaccinations in the elderly.

SUMMARY

Big Data is becoming increasingly popular with the collaborative collection of registries offering anesthesia a way to explore rare perioperative complications and outcome to encourage further hypotheses testing. Although Big Data has its flaws in security, lack of expertise and methodological concerns, the future potential of analytics combined with genomics, machine learning and real-time decision support looks promising.

Preoperative Risk Assessment to Guide Prophylaxis and Reduce the Incidence of Postoperative Nausea and Vomiting

PURPOSE

This article describes the implementation of a postoperative nausea and vomiting (PONV) risk prediction and prophylaxis protocol.

DESIGN

This is a retrospective pre/post implementation quality improvement project.

METHODS

This project used chart reviews to assess the impact of the implemented PONV assessment and prophylaxis in a sample population of adult females undergoing gynecologic surgical procedures.

FINDINGS

The mean number of prophylactic antiemetics administered significantly increased during the postimplementation period from 3.64 (SD, 0.878) in the preimplementation period to 4.07 (SD, 1.021) in the postimplementation period (P < .001). The greatest increase in antiemetic administration occurred in the moderate-risk (risk score, 4) and the high-risk (risk score, 5 to 6) groups. The incidence of PONV decreased from 32.3% in the preimplementation period to 28.9% in the postimplementation period; however, this reduction did not meet statistical significance. Antiemetic administration compliance increased from 37% in the preimplementation group to 61% in the postimplementation group (P < .001).

CONCLUSIONS

The results of this project suggest that a risk-tailored approach to PONV prophylaxis using a risk assessment tool along with treatment recommendations is effective at reducing the incidence of PONV. The effectiveness of this approach is limited by the involvement of the anesthesia providers responsible for completing the assessments and administering PONV prophylaxis.

Evaluating the impact of prediction models: lessons learned, challenges, and recommendations

An important aim of clinical prediction models is to positively impact clinical decision making and subsequent patient outcomes. The impact on clinical decision making and patient outcome can be quantified in prospective comparative-ideally cluster-randomized-studies, known as 'impact studies'. However, such impact studies often require a lot of time and resources, especially when they are (cluster-)randomized studies. Before envisioning such large-scale randomized impact study, it is important to ensure a reasonable chance that the use of the prediction model by the targeted healthcare professionals and patients will indeed have a positive effect on both decision making and subsequent outcomes. We recently performed two differently designed, prospective impact studies on a clinical prediction model to be used in surgical patients. Both studies taught us new valuable lessons on several aspects of prediction model impact studies, and which considerations may guide researchers in their decision to conduct a prospective comparative impact study. We provide considerations on how to prepare a prediction model for implementation in practice, how to present the model predictions, and how to choose the proper design for a prediction model impact study.

Post-operative nausea and vomiting in bariatric surgery patients: an observational study

BACKGROUND

The risk of post-operative nausea and vomiting (PONV) in patients undergoing bariatric surgery is unclear. The aim of the study was to investigate the risk of PONV and the use and effectiveness of PONV prophylaxis.

METHODS

This prospective observational study included 74 patients undergoing bariatric surgery with total intravenous anaesthesia. Patients were given PONV prophylaxis based on published guidelines and a simplified PONV risk score. Perioperative data were collected and a questionnaire was used at 2, 4, 6, 24, 48 and 72 h after the operation to evaluate PONV. Data are presented as risk (%) with the 95% confidence interval.

RESULTS

Sixty five per cent (54-75) of the patients experienced PONV in the first 24 post-operative hours and the risk increased with the number of risk factors for PONV. PONV occurred in 78% (66-87) of women and 26% (12-49) of men during the first 24 h. In relation to the guidelines, one patient received suboptimal PONV prophylaxis, 23% received optimal prophylaxis and 76% supra-optimal prophylaxis. The risk of PONV was 82% (59-94) with optimal prophylaxis and 59% (46-71) with supra-optimal prophylaxis. Of all patients, 34% (24-45) experienced severe PONV in the first 24 h that limited their activity.

CONCLUSIONS

The incidence of PONV in bariatric surgery patients was high despite a PONV prophylaxis regime following current guidelines. These results cast doubt as to the effectiveness of the usual PONV prophylaxis in this patient group and point to the need for further investigation of PONV prophylaxis and treatment in bariatric surgery patients.

Prediction models: the right tool for the right problem

PURPOSE OF REVIEW

Perioperative prediction models can help to improve personalized patient care by providing individual risk predictions to both patients and providers. However, the scientific literature on prediction model development and validation can be quite technical and challenging to understand. This article aims to provide the necessary insight for clinicians to assess the value of a prediction model that they intend to use in their clinical practice.

RECENT FINDINGS

Recent developments in prediction model research include the continuous development of new performance characteristics for prediction models, increasing insight into the limitations of old characteristics, as well as an improved understanding of the generalizability of prediction models to new populations and practices.

SUMMARY

Clinicians can assess the value of a prediction model for their practice by first identifying what the usage of the model will be. Second, they can recognize which performance characteristics are relevant to their assessment of the model. Finally, they need to decide whether the available scientific evidence sufficiently matches their clinical practice to proceed with implementation.

A systematic review of near real-time and point-of-care clinical decision support in anesthesia information management systems

Anesthesia information management systems (AIMS) are sophisticated hardware and software technology solutions that can provide electronic feedback to anesthesia providers. This feedback can be tailored to provide clinical decision support (CDS) to aid clinicians with patient care processes, documentation compliance, and resource utilization. We conducted a systematic review of peer-reviewed articles on near real-time and point-of-care CDS within AIMS using the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols. Studies were identified by searches of the electronic databases Medline and EMBASE. Two reviewers screened studies based on title, abstract, and full text. Studies that were similar in intervention and desired outcome were grouped into CDS categories. Three reviewers graded the evidence within each category. The final analysis included 25 articles on CDS as implemented within AIMS. CDS categories included perioperative antibiotic prophylaxis, post-operative nausea and vomiting prophylaxis, vital sign monitors and alarms, glucose management, blood pressure management, ventilator management, clinical documentation, and resource utilization. Of these categories, the reviewers graded perioperative antibiotic prophylaxis and clinical documentation as having strong evidence per the peer reviewed literature. There is strong evidence for the inclusion of near real-time and point-of-care CDS in AIMS to enhance compliance with perioperative antibiotic prophylaxis and clinical documentation. Additional research is needed in many other areas of AIMS-based CDS.

Barriers and facilitators perceived by physicians when using prediction models in practice

OBJECTIVES

Prediction models may facilitate risk-based management of health care conditions. In a large cluster-randomized trial, presenting calculated risks of postoperative nausea and vomiting (PONV) to physicians (assistive approach) increased risk-based management of PONV. This increase did not improve patient outcome-that is, PONV incidence. This prompted us to explore how prediction tools guide the decision-making process of physicians.

STUDY DESIGN AND SETTING

Using mixed methods, we interviewed eight physicians to understand how predicted risks were perceived by the physicians and how they influenced decision making. Subsequently, all 57 physicians of the trial were surveyed for how the presented risks influenced their perceptions.

RESULTS

Although the prediction tool made physicians more aware of PONV prevention, the physicians reported three barriers to use predicted risks in their decision making. PONV was not considered an outcome of utmost importance; decision making on PONV prophylaxis was mostly intuitive rather than risk based; prediction models do not weigh benefits and risks of prophylactic drugs.

CONCLUSION

Combining probabilistic output of the model with their clinical experience may be difficult for physicians, especially when their decision-making process is mostly intuitive. Adding recommendations to predicted risks (directive approach) was considered an important step to facilitate the uptake of a prediction tool.