EDBT 2026 Demo / reviewers in the wild / expert
William Brown III 0001
dblp:138/2242
· DBLP profile ↗
19ranked-venue papers
8as first author
6since 2021 · last 2026
0000-0003-4322-4859ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 19 · 8 first-author · 6 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Bidirectional data harmonization across the multiple chronic disease disparities research consortium: A pipeline description of opportunities and challenges
Hyelee Kim, Kathy Lanier, Sarit Helman, Niloufar Ameli, Sepideh Banava, Nancy Fan Cheng, Jason Boyce, Yulin Hswen, Catherine E. Oldenburg, Kim F. Rhoads, Edwin D. Charlebois, Stuart A. Gansky, William Brown III 0001 |
J. Biomed. Informatics | 14 |
| 2025 | Examining housing insecurity and transportation barriers in pediatric hospital readmissions: insights from structured and unstructured dataabstractBACKGROUND: Pediatric hospital readmissions increase healthcare costs and highlight gaps in care. Social determinants of health (SDOH), such as housing and transportation insecurity, significantly impact outcomes but are underexplored in pediatric populations. OBJECTIVES: This study evaluates the impact of housing and transportation-related SDOH on pediatric readmissions, comparing structured ICD-10-CM Z-codes alone to a combination of structured and unstructured data extracted via natural language processing (NLP). MATERIALS AND METHODS: We conducted a retrospective cohort study of pediatric patients (ages 2-17) discharged from UCSF Benioff Children's Hospital between January 2018 and January 2023. SDOH exposure was identified using structured Z-codes and NLP-extracted data. The primary outcome was hospital readmission within 365 days. Cox proportional hazards models assessed associations between SDOH and readmission risk. RESULTS: Among 8928 patients, only 0.8% were identified as exposed using structured data, compared to 31.7% using combined data. Patients identified through combined data had a higher readmission risk (HR: 2.64, 95% CI: 2.34-2.98) compared to those identified with structured data alone (HR: 1.99, 95% CI: 1.27-3.13). ED utilization was also higher among exposed patients. In the structured-only analysis, exposed patients had a significantly higher hazard of ED readmission (HR: 2.26, 95% CI: 1.65-3.10), whereas the association was slightly attenuated in the combined analysis (HR: 1.49, 95% CI: 1.37-1.62). CONCLUSION: Leveraging unstructured data enhances SDOH identification and reveals stronger associations with hospital and ED readmissions. A hybrid approach enables improved risk stratification and targeted interventions to address pediatric health disparities. Shivani Mehta, William Brown III 0001, Urmimala Sarkar, Nathan Tran, Yulin Hswen, Matthew S. Pantell |
J. Am. Medical Informatics Assoc. | 2 |
| 2023 | The association between prescription drug monitoring programs and controlled substance prescribing: a cross-sectional study using data from 2019 National Electronic Health Records SurveyabstractOBJECTIVE: The use of controlled medications such as opioids, stimulants, anabolic steroids, depressants, and hallucinogens has led to an increase in addiction, overdose, and death. Given the high attributes of abuse and dependency, prescription drug monitoring programs (PDMPs) were introduced in the United States as a state-level intervention. MATERIALS AND METHODS: Using cross-sectional data from the 2019 National Electronic Health Records Survey, we assessed the association between PDMP usage and reduced or eliminated controlled substance prescribing as well as the association between PDMP usage and changing a controlled substance prescription to a nonopioid pharmacologic therapy or nonpharmacologic therapy. We applied survey weights to produce physician-level estimates from the survey sample. RESULTS: Adjusting for physician age, sex, type of medical degree, specialty, and ease of PDMP, we found that physicians who reported "often" PDMP usage had 2.34 times the odds of reducing or eliminating controlled substance prescriptions compared to physicians who reported never using the PDMP (95% confidence interval [CI] 1.12-4.90). Adjusting for physician age, sex, type of doctor, and specialty, we found that physicians who reported "often" use of the PDMP had 3.65 times the odd of changing controlled substance prescriptions to a nonopioid pharmacologic therapy or nonpharmacologic therapy (95% CI: 1.61-8.26). DISCUSSION: These results support the continued use, investment, and expansion of PDMPs as an effective intervention for reducing controlled substance prescription and changing to nonopioid/pharmacologic therapy. CONCLUSION: Overall, frequent usage of PDMPs was significantly associated with reducing, eliminating, or changing controlled substance prescription patterns. Shivani Mehta, William Brown III 0001, Erin Ferguson, James Najera, Matthew S. Pantell |
J. Am. Medical Informatics Assoc. | 2 |
| 2022 | Comparative Analysis of Social Connections/Isolation and Stress Documentation in Structured and Unstructured Machine De-Identified Data using PatientExploreR and EMERSE
Shivani Mehta, Anna Rubinsky, Courtney R. Lyles, Kathryn Kemper, Laura M. Gottlieb, Urmimala Sarkar, William Brown III 0001 |
AMIA | 8 |
| 2021 | Descriptive examination of secure messaging in a longitudinal cohort of diabetes patients in the ECLIPPSE studyabstractThe substantial expansion of secure messaging (SM) via the patient portal in the last decade suggests that it is becoming a standard of care, but few have examined SM use longitudinally. We examined SM patterns among a diverse cohort of patients with diabetes (N = 19 921) and the providers they exchanged messages with within a large, integrated health system over 10 years (2006-2015), linking patient demographics to SM use. We found a 10-fold increase in messaging volume. There were dramatic increases overall and for patient subgroups, with a majority of patients (including patients with lower income or with self-reported limited health literacy) messaging by 2015. Although more physicians than nurses and other providers messaged throughout the study, the distribution of health professions using SM changed over time. Given this rapid increase in SM, deeper understanding of optimizing the value of patient and provider engagement, while managing workflow and training challenges, is crucial. Anupama G. Cemballi, Andrew J. Karter, Dean Schillinger, Jennifer Y. Liu, Danielle S. McNamara, William Brown III 0001, Scott A. Crossley, Wagahta Semere, Mary Reed, Jill Y. Allen, Courtney R. Lyles |
J. Am. Medical Informatics Assoc. | 6 |
| 2021 | Challenges and solutions to employing natural language processing and machine learning to measure patients' health literacy and physician writing complexity: The ECLIPPSE study
William Brown III 0001, Renu Balyan, Andrew J. Karter, Scott A. Crossley, Wagahta Semere, Nicholas D. Duran, Courtney R. Lyles, Jennifer Y. Liu, Howard H. Moffet, Ryane Daniels, Danielle S. McNamara, Dean Schillinger |
J. Biomed. Informatics | 1 |
| 2020 | Developing a digital user-centered community resource mapping tool for safety-net patients in San Francisco
Anupama G. Cemballi, Kim Hanh Nguyen, Jose Miramontes, Jessica Fields, Anjali Gopalan, Tessa Cruz, Aekta Shah, Antwi Akom, William Brown III 0001, Urmimala Sarkar, Courtney R. Lyles |
AMIA | 9 |
| 2018 | Are participants concerned about privacy and security when using short message service to report product adherence in a rectal microbicide trial?abstractObjective: During a Phase 2 rectal microbicide trial, men who have sex with men and transgender women (n = 187) in 4 countries (Peru, South Africa, Thailand, United States) reported product use daily via short message service (SMS). To prevent disclosure of study participation, the SMS system program included privacy and security features. We evaluated participants' perceptions of privacy while using the system and acceptability of privacy/security features. Materials and Methods: To protect privacy, the SMS system: (1) confirmed participant availability before sending the study questions, (2) required a password, and (3) did not reveal product name or study participation. To ensure security, the system reminded participants to lock phone/delete messages. A computer-assisted self-interview (CASI), administered at the final visit, measured burden of privacy and security features and SMS privacy concerns. A subsample of 33 participants underwent an in-depth interview (IDI). Results: Based on CASI, 85% had no privacy concerns; only 5% were very concerned. Most were not bothered by the need for a password (73%) or instructions to delete messages (82%). Based on IDI, reasons for low privacy concerns included sending SMS in private or feeling that texting would not draw attention. A few IDI participants found the password unnecessary and more than half did not delete messages. Discussion: Most participants were not concerned that the SMS system would compromise their confidentiality. SMS privacy and security features were effective and not burdensome. Conclusion: Short ID-related passwords, ambiguous language, and reminders to implement privacy and security-enhancing behaviors are recommended for SMS systems. Rebecca Giguere, William Brown III 0001, Ivan C. Balán, Curtis Dolezal, Titcha Ho, Alan Sheinfil, Mobolaji Ibitoye, Javier R. Lama, Ian McGowan, Ross D. Cranston, Alex Carballo-Dieguez |
J. Am. Medical Informatics Assoc. | 2 |
| 2018 | Challenges and solutions implementing an SMS text message-based survey CASI and adherence reminders in an international biomedical HIV PrEP study (MTN 017)abstractBACKGROUND: We implemented a text message-based Short Message Service computer-assisted self-interviewing (SMS-CASI) system to aid adherence and monitor behavior in MTN-017, a phase 2 safety and acceptability study of rectally-applied reduced-glycerin 1% tenofovir gel compared to oral emtricitabine/tenofovir disoproxil fumarate tablets. We sought to implement SMS-based daily reminders and product use reporting, in four countries and five languages, and centralize data management/automated-backup. METHODS: We assessed features of five SMS programs against study criteria. After identifying the optimal program, we systematically implemented it in South Africa, Thailand, Peru, and the United States. The system consisted of four windows-based computers, a GSM dongle and sim card to send SMS. The SMS-CASI was, designed for 160 character SMS. Reminders and reporting sessions were initiated by date/time triggered messages. System, questions, responses, and instructions were triggered by predetermined key words. RESULTS: There were 142,177 total messages: sent 86,349 (60.73%), received 55,573 (39.09%), failed 255 (0.18%). 6153 (4.33%) of the message were errors generated from either our SMS-CASI system or by participants. Implementation challenges included: high message costs; poor data access; slow data cleaning and analysis; difficulty reporting information to sites; a need for better participant privacy and data security; and mitigating variability in system performance across sites. We mitigated message costs and poor data access by federating the SMS-CASI system, and used secure email protocols to centralize data backup. We developed programming syntaxes to facilitate daily data cleaning and analysis, and a calendar template for reporting SMS behavior. Lastly, we ambiguated text message language to increase privacy, and standardized hardware and software across sites, minimizing operational variability. CONCLUSION: We identified factors that aid international implementation and operation of SMS-CASI for real-time adherence monitoring. The challenges and solutions we present can aid other researchers to develop and manage an international multilingual SMS-based adherence reminder and CASI system. William Brown III 0001, Rebecca Giguere, Alan Sheinfil, Mobolaji Ibitoye, Ivan C. Balán, Titcha Ho, Luis Quispe, Wichuda Sukwicha, Javier R. Lama, Alex Carballo-Dieguez, Ross D. Cranston |
J. Biomed. Informatics | 1 |
| 2016 | SMASH: A Data-driven Informatics Method to Assist Experts in Characterizing Semantic Heterogeneity among Data Elements
William Brown III 0001, Chunhua Weng, David K. Vawdrey, Alex Carballo-Dieguez, Suzanne Bakken |
AMIA | 1 |
| 2016 | A user-centered model for designing consumer mobile health (mHealth) applications (apps)
Rebecca Schnall, Marlene Rojas, Suzanne Bakken, William Brown III 0001, Alex Carballo-Dieguez, Monique Carry, Deborah Gelaude, Jocelyn Patterson Mosley, Jasmine Travers |
J. Biomed. Informatics | 4 |
| 2015 | Developing an Ontology from HIV-associated Elements in Research
William Brown III 0001, Chunhua Weng, David K. Vawdrey, Alex Carballo-Dieguez, Suzanne Bakken |
AMIA | 1 |
| 2014 | Developing an eBook-Integrated High-Fidelity Mobile App Prototype for Promoting Child Motor Skills and Taxonomically Assessing Children's Emotional Responses Using Face and Sound Topology
William Brown III 0001, Connie Liu, Rita M. John, Phoebe Ford |
AMIA | 1 |
| 2014 | Integrating Diverse HIV-associated Datasets via Semantic Harmonization
William Brown III 0001, Chunhua Weng, David K. Vawdrey, Suzanne Bakken |
AMIA | 1 |
| 2014 | Use of Design Science for Informing the Development of a Mobile App for Persons Living with HIV
Rebecca Schnall, Marlene Rojas, Jasmine Travers, William Brown III 0001, Suzanne Bakken |
AMIA | 4 |
| 2013 | Method for the Development of Data Visualizations for Community Members with Varying Levels of Health Literacy
Adriana Arcia, Michael E. Bales, William Brown III 0001, Manuel Co Jr., Melinda Gilmore, Young Ji Lee, Chin S. Park, Jennifer E. Prey, Mark Velez, Janet Woollen, Sunmoo Yoon, Rita Kukafka, Jacqueline Merrill, Suzanne Bakken |
AMIA | 3 |
| 2013 | Development of an HIV Biomedical Survey Ontology to Assist and Improve Survey and Computer Assisted Self-Interview (CASI) Instrumentation for HIV Clinical and Behavioral Research
William Brown III 0001, Alex Carballo-Dieguez |
AMIA | 1 |
| 2013 | Use of the Health-ITUEM for Evaluating Mobile Health Technology
Rebecca Schnall, Po-Yin Yen, Marlene Rojas, William Brown III 0001 |
AMIA | 4 |
| 2013 | Assessment of the Health IT Usability Evaluation Model (Health-ITUEM) for evaluating mobile health (mHealth) technology
William Brown III 0001, Po-Yin Yen, Marlene Rojas, Rebecca Schnall |
J. Biomed. Informatics | 1 |