People: Principal Investigator

Associate Professor (Research) of Medicine (Biomedical Informatics Research Center), of Biomedical Data Science and of Surgery
(650) 725-5507

Bio

Dr Hernandez-Boussard is an Associate Professor in Medicine (Biomedical Informatics), Biomedical Data Science, and Surgery at the Stanford University School of Medicine. Dr. Hernandez-Boussard's background and expertise is in the field of computational biology, with concentration on accountability measures, population health, and health policy. A key focus of her research is the application of novel methods and tools to large clinical datasets for hypothesis generation, comparative effectiveness research, and the evaluation of quality healthcare delivery.

Publications

  • Drug-Free Interventions to Reduce Pain or Opioid Consumption After Total Knee Arthroplasty: A Systematic Review and Meta-analysis. JAMA surgery Tedesco, D., Gori, D., Desai, K. R., Asch, S., Carroll, I. R., Curtin, C., McDonald, K. M., Fantini, M. P., Hernandez-Boussard, T. 2017: e172872

    Abstract

    There is increased interest in nonpharmacological treatments to reduce pain after total knee arthroplasty. Yet, little consensus supports the effectiveness of these interventions.To systematically review and meta-analyze evidence of nonpharmacological interventions for postoperative pain management after total knee arthroplasty.Database searches of MEDLINE (PubMed), EMBASE (OVID), Cochrane Central Register of Controlled Trials (CENTRAL), Cochrane Database of Systematic Reviews, Web of Science (ISI database), Physiotherapy Evidence (PEDRO) database, and ClinicalTrials.gov for the period between January 1946 and April 2016.Randomized clinical trials comparing nonpharmacological interventions with other interventions in combination with standard care were included.Two reviewers independently extracted the data from selected articles using a standardized form and assessed the risk of bias. A random-effects model was used for the analyses.Postoperative pain and consumption of opioids and analgesics.Of 5509 studies, 39 randomized clinical trials were included in the meta-analysis (2391 patients). The most commonly performed interventions included continuous passive motion, preoperative exercise, cryotherapy, electrotherapy, and acupuncture. Moderate-certainty evidence showed that electrotherapy reduced the use of opioids (mean difference, -3.50; 95% CI, -5.90 to -1.10 morphine equivalents in milligrams per kilogram per 48 hours; P = .004; I2 = 17%) and that acupuncture delayed opioid use (mean difference, 46.17; 95% CI, 20.84 to 71.50 minutes to the first patient-controlled analgesia; P < .001; I2 = 19%). There was low-certainty evidence that acupuncture improved pain (mean difference, -1.14; 95% CI, -1.90 to -0.38 on a visual analog scale at 2 days; P = .003; I2 = 0%). Very low-certainty evidence showed that cryotherapy was associated with a reduction in opioid consumption (mean difference, -0.13; 95% CI, -0.26 to -0.01 morphine equivalents in milligrams per kilogram per 48 hours; P = .03; I2 = 86%) and in pain improvement (mean difference, -0.51; 95% CI, -1.00 to -0.02 on the visual analog scale; P < .05; I2 = 62%). Low-certainty or very low-certainty evidence showed that continuous passive motion and preoperative exercise had no pain improvement and reduction in opioid consumption: for continuous passive motion, the mean differences were -0.05 (95% CI, -0.35 to 0.25) on the visual analog scale (P = .74; I2 = 52%) and 6.58 (95% CI, -6.33 to 19.49) opioid consumption at 1 and 2 weeks (P = .32, I2 = 87%), and for preoperative exercise, the mean difference was -0.14 (95% CI, -1.11 to 0.84) on the Western Ontario and McMaster Universities Arthritis Index Scale (P = .78, I2 = 65%).In this meta-analysis, electrotherapy and acupuncture after total knee arthroplasty were associated with reduced and delayed opioid consumption.

    View details for DOI 10.1001/jamasurg.2017.2872

    View details for PubMedID 28813550

  • Opioid Abuse And Poisoning: Trends In Inpatient And Emergency Department Discharges. Health affairs (Project Hope) Tedesco, D., Asch, S. M., Curtin, C., Hah, J., McDonald, K. M., Fantini, M. P., Hernandez-Boussard, T. 2017; 36 (10): 1748–53

    Abstract

    Addressing the opioid epidemic is a national priority. We analyzed national trends in inpatient and emergency department (ED) discharges for opioid abuse, dependence, and poisoning using Healthcare Cost and Utilization Project data. Inpatient and ED discharge rates increased overall across the study period, but a decline was observed for prescription opioid-related discharges beginning in 2010, while a sharp increase in heroin-related discharges began in 2008.

    View details for DOI 10.1377/hlthaff.2017.0260

    View details for PubMedID 28971919

  • The Fifth Vital Sign: Postoperative Pain Predicts 30-day Readmissions and Subsequent Emergency Department Visits. Annals of surgery Hernandez-Boussard, T., Graham, L. A., Desai, K., Wahl, T. S., Aucoin, E., Richman, J. S., Morris, M. S., Itani, K. M., Telford, G. L., Hawn, M. T. 2017

    Abstract

    We hypothesized that inpatient postoperative pain trajectories are associated with 30-day inpatient readmission and emergency department (ED) visits.Surgical readmissions have few known modifiable predictors. Pain experienced by patients may reflect surgical complications and/or inadequate or difficult symptom management.National Veterans Affairs Surgical Quality Improvement data on inpatient general, vascular, and orthopedic surgery from 2008 to 2014 were merged with laboratory, vital sign, health care utilization, and postoperative complications data. Six distinct postoperative inpatient patient-reported pain trajectories were identified: (1) persistently low, (2) mild, (3) moderate or (4) high trajectories, and (5) mild-to-low or (6) moderate-to-low trajectories based on postoperative pain scores. Regression models estimated the association between pain trajectories and postdischarge utilization while controlling for important patient and clinical variables.Our sample included 211,231 surgeries-45.4% orthopedics, 37.0% general, and 17.6% vascular. Overall, the 30-day unplanned readmission rate was 10.8%, and 30-day ED utilization rate was 14.2%. Patients in the high pain trajectories had the highest rates of postdischarge readmissions and ED visits (14.4% and 16.3%, respectively, P < 0.001). In multivariable models, compared with the persistently low pain trajectory, there was a dose-dependent increase in postdischarge ED visits and readmission for pain-related diagnoses, but not postdischarge complications (χ trend P < 0.001).Postoperative pain trajectories identify populations at risk for 30-day readmissions and ED visits, and do not seem to be mediated by postdischarge complications. Addressing pain control expectations before discharge may help reduce surgical readmissions in high pain categories.

    View details for DOI 10.1097/SLA.0000000000002372

    View details for PubMedID 28657940

  • New Paradigms for Patient-Centered Outcomes Research in Electronic Medical Records: An Example of Detecting Urinary Incontinence Following Prostatectomy. EGEMS (Washington, DC) Hernandez-Boussard, T., Tamang, S., Blayney, D., Brooks, J., Shah, N. 2016; 4 (3): 1231-?

    Abstract

    National initiatives to develop quality metrics emphasize the need to include patient-centered outcomes. Patient-centered outcomes are complex, require documentation of patient communications, and have not been routinely collected by healthcare providers. The widespread implementation of electronic medical records (EHR) offers opportunities to assess patient-centered outcomes within the routine healthcare delivery system. The objective of this study was to test the feasibility and accuracy of identifying patient centered outcomes within the EHR.Data from patients with localized prostate cancer undergoing prostatectomy were used to develop and test algorithms to accurately identify patient-centered outcomes in post-operative EHRs - we used urinary incontinence as the use case. Standard data mining techniques were used to extract and annotate free text and structured data to assess urinary incontinence recorded within the EHRs.A total 5,349 prostate cancer patients were identified in our EHR-system between 1998-2013. Among these EHRs, 30.3% had a text mention of urinary incontinence within 90 days post-operative compared to less than 1.0% with a structured data field for urinary incontinence (i.e. ICD-9 code). Our workflow had good precision and recall for urinary incontinence (positive predictive value: 0.73 and sensitivity: 0.84).Our data indicate that important patient-centered outcomes, such as urinary incontinence, are being captured in EHRs as free text and highlight the long-standing importance of accurate clinician documentation. Standard data mining algorithms can accurately and efficiently identify these outcomes in existing EHRs; the complete assessment of these outcomes is essential to move practice into the patient-centered realm of healthcare.

    View details for DOI 10.13063/2327-9214.1231

    View details for PubMedID 27347492

    View details for PubMedCentralID PMC4899050

Academic Appointments

Associate Professor, Medicine - Biomedical Informatics Research 

Associate Professor, Biomedical Data Science

Associate Professor, Surgery - General Surgery

Member, Stanford Cancer Institute

Professional Education

M.S., Stanford University, Health Services Research (2013)

Ph.D., University Claude Bernard, Lyon 1, Computational Biology (1999)

M.P.H., Yale University, Epidemiology (1993)

B.A., University California, Irvine, Psychology (1991)

B.S., University of California, Irvine, Biology (1991)