Development and Validation of an Electronic Health Record-based Score for Triage to Perioperative Medicine

Le, Sidney; Corbin, Dalton; Myers, Laura C.; Kipnis, Patricia; Cohn, Bradley; Liu, Vincent X

doi:10.1097/sla.0000000000005284

Cited by 12 publications

(8 citation statements)

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“…Mortality was identified using KPNC health system records, and 30-day major postoperative complications included cardiac arrest, myocardial infarction, pulmonary embolism, sepsis, septic shock, deep or organ space surgical site infections, unplanned intubation, deep vein thrombosis, progressive kidney insufficiency or kidney failure, or cerebrovascular accident. These complications were selected and outcome was constructed based on prior studies of major NSQIP complications . Secondary outcomes included 30-day mortality from the day of surgery and 30-day readmission from the day of discharge.…”

Section: Methodsmentioning

confidence: 98%

Comparison of Electronic Frailty Metrics for Prediction of Adverse Outcomes of Abdominal Surgery

Liu

Kipnis

et al. 2022

JAMA Surg

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IMPORTANCE Electronic frailty metrics have been developed for automated frailty assessment and include the Hospital Frailty Risk Score (HFRS), the Electronic Frailty Index (eFI), the 5-Factor Modified Frailty Index (mFI-5), and the Risk Analysis Index (RAI). Despite substantial differences in their construction, these 4 electronic frailty metrics have not been rigorously compared within a surgical population.OBJECTIVE To characterize the associations between 4 electronic frailty metrics and to measure their predictive value for adverse surgical outcomes. DESIGN, SETTING, AND PARTICIPANTSThis retrospective cohort study used electronic health record data from patients who underwent abdominal surgery from January 1, 2010, to December 31, 2020, at 20 medical centers within Kaiser Permanente Northern California (KPNC). Participants included adults older than 50 years who underwent abdominal surgical procedures at KPNC from 2010 to 2020 that were sampled for reporting to the National Surgical Quality Improvement Program. MAIN OUTCOMES AND MEASURESPearson correlation coefficients between electronic frailty metrics and area under the receiver operating characteristic curve (AUROC) of univariate models and multivariate preoperative risk models for 30-day mortality, readmission, and morbidity, which was defined as a composite of mortality and major postoperative complications. RESULTSWithin the cohort of 37 186 patients, mean (SD) age, 67.9 (female, 19 127 [51.4%]), correlations between pairs of metrics ranged from 0.19 (95% CI, 0.18-0.20) for mFI-5 and RAI 0.69 (95% CI, 0.68-0.70). Only 1085 of 37 186 (2.9%) were classified as frail based on all 4 metrics. In univariate models for morbidity, HFRS demonstrated higher predictive discrimination (AUROC, 0.71; 95% CI, 0.70-0.72) than eFI (AUROC, 0.64; 95% CI, 0.63-0.65), mFI-5 (AUROC, 0.58; 95% CI, 0.57-0.59), and RAI (AUROC, 0.57; 95% CI, 0.57-0.58). The predictive discrimination of multivariate models with age, sex, comorbidity burden, and procedure characteristics for all 3 adverse surgical outcomes improved by including HFRS into the models. CONCLUSIONS AND RELEVANCEIn this cohort study, the 4 electronic frailty metrics demonstrated heterogeneous correlation and classified distinct groups of surgical patients as frail. However, HFRS demonstrated the highest predictive value for adverse surgical outcomes.

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Section: Methodsmentioning

confidence: 98%

Comparison of Electronic Frailty Metrics for Prediction of Adverse Outcomes of Abdominal Surgery

Liu

Kipnis

et al. 2022

JAMA Surg

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“… 23 The abLAPS score was categorized into 4 groups: unavailable, low (0–4), medium (5–10), and high (>10). 24 The mode of anesthesia was determined by the anesthesia provider. Cases were categorized as “general anesthesia” if a general anesthetic was used, even if accompanied by other adjunctive modes of anesthesia or analgesia, including secondary regional or neuraxial techniques, or if a case was converted to general anesthesia during the procedure.…”

Section: Methodsmentioning

confidence: 99%

“…We quantified severity of illness with the abbreviated Laboratory-based Acute Physiology Score (abLAPS), which was based on the most physiologically deranged value of 14 laboratory tests over the month before the date surgery admission date 23. The abLAPS score was categorized into 4 groups: unavailable, low (0–4), medium (5–10), and high (>10) 24. The mode of anesthesia was determined by the anesthesia provider.…”

Section: Methodsmentioning

confidence: 99%

COVID-19 Vaccination and the Timing of Surgery Following COVID-19 Infection

Kipnis

Cohn

et al. 2022

Annals of Surgery

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Objective: To evaluate whether COVID-19 vaccination status or mode of anesthesia modified the temporal harms associated with surgery following coronavirus disease-2019 (COVID-19) infection. Background: Surgery shortly after COVID-19 infection is associated with higher rates of complications, leading to recommendations to delay surgery following COVID-19 infection when possible. However, prior studies were based on populations with low or no prevalence of vaccination. Methods: A retrospective cohort study of patients who underwent scheduled surgery in a health system from January 1, 2018 to February 28, 2022 (N = 228,913) was performed. Patients were grouped by time of surgery relative to COVID-19 test positivity: 0 to 4 weeks after COVID-19 ("early post-COVID-19"), 4 to 8 weeks after COVID-19 ("mid post-COVID-19"), > 8 weeks after COVID-19 ("late post-COVID-19"), surgery at least 30 days before subsequent COVID-19 ("pre-COVID-19"), and surgery with no prior or subsequent test positivity for COVID-19. Results: Among patients who were not fully vaccinated at the time of COVID-19 infection, the adjusted rate of perioperative complications for the early post-COVID-19 group was significantly higher than for the pre-COVID-19 group (relative risk: 1.55; P = 0.05). No significantly higher risk was identified between these groups for patients who were fully vaccinated (0.66; P = 1.00), or for patients who were not fully vaccinated and underwent surgery without general anesthesia (0.52; P = 0.83). Conclusions: Surgery shortly following COVID-19 infection was not associated with higher risks among fully vaccinated patients or among patients who underwent surgery without general anesthesia. Further research will be valuable to understand additional factors that modify perioperative risks associated with prior COVID-19 infection.

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“…The tools he contributed to have been rapidly implemented into clinical practice resulting in substantial improvements in the approach to perioperative clinical evaluation and to surgical scheduling during the COVID pandemic. 19,43 In addition, he gained firsthand experience with Artificial Intelligence and Machine Learning tools, including computer vision, applied to pre-surgical EHR and imaging data. After program completion, he returned to complete his General Surgery residency with a long-term goal to use complex, multimodal data to improve surgical processes and outcomes.…”

Section: Introductionmentioning

confidence: 99%

Training the next generation of delivery science researchers: 10‐year experience of a post‐doctoral research fellowship program within an integrated care system

Grant

Schmittdiel

Liu

et al. 2023

Learning Health Systems

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IntroductionLearning health systems require a workforce of researchers trained in the methods of identifying and overcoming barriers to effective, evidence‐based care. Most existing postdoctoral training programs, such as NIH‐funded postdoctoral T32 awards, support basic and epidemiological science with very limited focus on rigorous delivery science methods for improving care. In this report, we present the 10‐year experience of developing and implementing a Delivery Science postdoctoral fellowship embedded within an integrated health care delivery system.MethodsIn 2012, the Kaiser Permanente Northern California Division of Research designed and implemented a 2‐year postdoctoral Delivery Science Fellowship research training program to foster research expertise in identifying and addressing barriers to evidence‐based care within health care delivery systems.ResultsSince 2014, 20 fellows have completed the program. Ten fellows had PhD‐level scientific training, and 10 fellows had clinical doctorates (eg, MD, RN/PhD, PharmD). Fellowship alumni have graduated to faculty research positions at academic institutions (9), and research or clinical organizations (4). Seven alumni now hold positions in Kaiser Permanente's clinical operations or medical group (7).ConclusionsThis delivery science fellowship program has succeeded in training graduates to address delivery science problems from both research and operational perspectives. In the next 10 years, additional goals of the program will be to expand its reach (eg, by developing joint research training models in collaboration with clinical fellowships) and strengthen mechanisms to support transition from fellowship to the workforce, especially for researchers from underrepresented groups.

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Development and Validation of an Electronic Health Record-based Score for Triage to Perioperative Medicine

Cited by 12 publications

References 50 publications

Comparison of Electronic Frailty Metrics for Prediction of Adverse Outcomes of Abdominal Surgery

Comparison of Electronic Frailty Metrics for Prediction of Adverse Outcomes of Abdominal Surgery

COVID-19 Vaccination and the Timing of Surgery Following COVID-19 Infection

Training the next generation of delivery science researchers: 10‐year experience of a post‐doctoral research fellowship program within an integrated care system

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