Anita M. Preininger

dblp:288/9258 · DBLP profile ↗
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9ranked-venue papers
2as first author
5since 2021 · last 2021
0000-0001-8011-9391ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 9 · 2 first-author · 5 since 2021
YearPublicationVenuePosition
2021 Understanding the use of pharmacological knowledge bases in clinical care
Shilo Anders, Laurie L. Novak, Nawshin Kutub, Carrie Reale, Daniel J. France, Christopher L. Simpson, Courtney A. Vanhouten, Karlis Draulis, Rubina F. Rizvi, Tiffani J. Bright, Gretchen Purcell Jackson, Anita M. Preininger
AMIA12
2021 A Return to Workplace Health Advisor Implementing Public Health Guidance for Safe Re-Opening During a Pandemic
Anita M. Preininger, Fernando J. Suarez Saiz, Jaimie Gorman, Brian Gibbemeyer, Gretchen Purcell Jackson
AMIA1
2021 Deploying Conversational Agents to Facilitate Housing Assistance Needs Resulting from COVID-19
Brett R. South, Anita M. Preininger, Piyush Parmar, Rubina F. Rizvi, David Brotman, Shira Alevy, Mollie McKillop, Gretchen Purcell Jackson, William Kassler
AMIA2
2021 Leveraging conversational technology to answer common COVID-19 questions
abstract
The rapidly evolving science about the Coronavirus Disease 2019 (COVID-19) pandemic created unprecedented health information needs and dramatic changes in policies globally. We describe a platform, Watson Assistant (WA), which has been used to develop conversational agents to deliver COVID-19 related information. We characterized the diverse use cases and implementations during the early pandemic and measured adoption through a number of users, messages sent, and conversational turns (ie, pairs of interactions between users and agents). Thirty-seven institutions in 9 countries deployed COVID-19 conversational agents with WA between March 30 and August 10, 2020, including 24 governmental agencies, 7 employers, 5 provider organizations, and 1 health plan. Over 6.8 million messages were delivered through the platform. The mean number of conversational turns per session ranged between 1.9 and 3.5. Our experience demonstrates that conversational technologies can be rapidly deployed for pandemic response and are adopted globally by a wide range of users.
Mollie McKillop, Brett R. South, Anita M. Preininger, Mitch Mason, Gretchen Purcell Jackson
J. Am. Medical Informatics Assoc.3
2021 Comparison of an oncology clinical decision-support system's recommendations with actual treatment decisions
abstract
OBJECTIVE: IBM(R) Watson for Oncology (WfO) is a clinical decision-support system (CDSS) that provides evidence-informed therapeutic options to cancer-treating clinicians. A panel of experienced oncologists compared CDSS treatment options to treatment decisions made by clinicians to characterize the quality of CDSS therapeutic options and decisions made in practice. METHODS: This study included patients treated between 1/2017 and 7/2018 for breast, colon, lung, and rectal cancers at Bumrungrad International Hospital (BIH), Thailand. Treatments selected by clinicians were paired with therapeutic options presented by the CDSS and coded to mask the origin of options presented. The panel rated the acceptability of each treatment in the pair by consensus, with acceptability defined as compliant with BIH's institutional practices. Descriptive statistics characterized the study population and treatment-decision evaluations by cancer type and stage. RESULTS: Nearly 60% (187) of 313 treatment pairs for breast, lung, colon, and rectal cancers were identical or equally acceptable, with 70% (219) of WfO therapeutic options identical to, or acceptable alternatives to, BIH therapy. In 30% of cases (94), 1 or both treatment options were rated as unacceptable. Of 32 cases where both WfO and BIH options were acceptable, WfO was preferred in 18 cases and BIH in 14 cases. Colorectal cancers exhibited the highest proportion of identical or equally acceptable treatments; stage IV cancers demonstrated the lowest. CONCLUSION: This study demonstrates that a system designed in the US to support, rather than replace, cancer-treating clinicians provides therapeutic options which are generally consistent with recommendations from oncologists outside the US.
Suthida Suwanvecho, Harit Suwanrusme, Tanawat Jirakulaporn, Surasit Issarachai, Nimit Taechakraichana, Palita Lungchukiet, Wimolrat Decha, Wisanu Boonpakdee, Nittaya Thanakarn, Pattanawadee Wongrattananon, Anita M. Preininger, Metasebya Solomon, Suwei Wang, Rezzan Hekmat, Irene Dankwa-Mullan, Edward H. Shortliffe, Vimla L. Patel, Yull Arriaga, Gretchen Purcell Jackson, Narongsak Kiatikajornthada
J. Am. Medical Informatics Assoc.11
2020 Identifying and Leveraging Public Data Sources with Structured Social Determinants of Health Information for Observational Health Research
Irene Dankwa-Mullan, Mollie McKillop, Metasebya Solomon, Anita M. Preininger, Mark C. Roebuck, Yull Arriaga, Judy George, Gretchen Purcell Jackson, Brett R. South
AMIA4
2020 Adoption and Impact of a Personalized and Data-Driven Health Benefits Decision-Support Tool
Mollie McKillop, Anita M. Preininger, Tyler Steben, Karlis Draulis, Nawshin Kutub, Gretchen Purcell Jackson
AMIA2
2020 An Operational Performance-Improvement Tool to Enable Value-based Healthcare
Anita M. Preininger, Bedda L. Rosario, Nawshin Kutub, Karlis Draulis, Stacey Duke, Wesley Rikkers, Gretchen Purcell Jackson
AMIA1
2020 Concordance with Oncology Clinical Decision Support and Clinical Outcomes in Breast and Colorectal Cancer Patients
Suthida Suwanvecho, Harit Suwanrusme, Tanawat Jirakulaporn, Palita Lungchukiet, Nimit Taechakraichana, Nittaya Thanakarn, Wimolrat Decha, Wisanu Boonpakdee, Pattanawadee Wongrattananon, Anita M. Preininger, Suwei Wang, Metasebya Solomon, Rezzan Hekmat, Jaime Esquivel, Irene Dankwa-Mullan, Vimla L. Patel, Edward H. Shortliffe, Yull Arriaga, Gretchen Purcell Jackson, Narongsak Kiatikajornthada
AMIA10