Samson Tu - Academia.edu (original) (raw)

Papers by Samson Tu

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2017

Clinicians and clinical decision-support systems often follow pharmacotherapy recommendations for... more Clinicians and clinical decision-support systems often follow pharmacotherapy recommendations for patients based on clinical practice guidelines (CPGs). In multimorbid patients, these recommendations can potentially have clinically significant drug-drug interactions (DDIs). In this study, we describe and validate a method for programmatically detecting DDIs among CPG recommendations. The system extracts pharmacotherapy intervention recommendations from narrative CPGs, normalizes the terms, creates a mapping of drugs and drug classes, and then identifies occurrences of DDIs between CPG pairs. We used this system to analyze 75 CPGs written by authoring entities in the United States that discuss outpatient management of common chronic diseases. Using a reference list of high-risk DDIs, we identified 2198 of these DDIs in 638 CPG pairs (46 unique CPGs). Only 9 high-risk DDIs were discussed by both CPGs in a pairing. In 69 of the pairings, neither CPG had a pharmacologic reference or a w...

Journal of biomedical semantics, 2017

Structured data acquisition is a common task that is widely performed in biomedicine. However, cu... more Structured data acquisition is a common task that is widely performed in biomedicine. However, current solutions for this task are far from providing a means to structure data in such a way that it can be automatically employed in decision making (e.g., in our example application domain of clinical functional assessment, for determining eligibility for disability benefits) based on conclusions derived from acquired data (e.g., assessment of impaired motor function). To use data in these settings, we need it structured in a way that can be exploited by automated reasoning systems, for instance, in the Web Ontology Language (OWL); the de facto ontology language for the Web. We tackle the problem of generating Web-based assessment forms from OWL ontologies, and aggregating input gathered through these forms as an ontology of "semantically-enriched" form data that can be queried using an RDF query language, such as SPARQL. We developed an ontology-based structured data acquisi...

AMIA ... Annual Symposium proceedings. AMIA Symposium, 2016

As utilization of clinical decision support (CDS) increases, it is important to continue the deve... more As utilization of clinical decision support (CDS) increases, it is important to continue the development and refinement of methods to accurately translate the intention of clinical practice guidelines (CPG) into a computable form. In this study, we validate and extend the 13 steps that Shiffman et al.(5) identified for translating CPG knowledge for use in CDS. During an implementation project of ATHENA-CDS, we encoded complex CPG recommendations for five common chronic conditions for integration into an existing clinical dashboard. Major decisions made during the implementation process were recorded and categorized according to the 13 steps. During the implementation period, we categorized 119 decisions and identified 8 new categories required to complete the project. We provide details on an updated model that outlines all of the steps used to translate CPG knowledge into a CDS integrated with existing health information technology.

AMIA ... Annual Symposium proceedings. AMIA Symposium, 2016

Through close analysis of two pairs of systems that implement the automated evaluation of perform... more Through close analysis of two pairs of systems that implement the automated evaluation of performance measures (PMs) and guideline-based clinical decision support (CDS), we contrast differences in their knowledge encoding and necessary changes to a CDS system that provides management recommendations for patients failing performance measures. We trace the sources of differences to the implementation environments and goals of PMs and CDS.

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2016

Clinical decision support (CDS) systems with complex logic are being developed. Ensuring the qual... more Clinical decision support (CDS) systems with complex logic are being developed. Ensuring the quality of CDS is imperative, but there is no consensus on testing standards. We tested ATHENA-HTN CDS after encoding updated hypertension guidelines into the system. A logic flow and a complexity analysis of the encoding were performed to guide testing. 100 test cases were selected to test the major pathways in the CDS logic flow, and the effectiveness of the testing was analyzed. The encoding contained 26 decision points and 3120 possible output combinations. The 100 cases selected tested all of the major pathways in the logic, but only 1% of the possible output combinations. Test case selection is one of the most challenging aspects in CDS testing and has a major impact on testing coverage. A test selection strategy should take into account the complexity of the system, identification of major logic pathways, and available resources.

Proceedings Amia Annual Symposium Amia Symposium, Feb 1, 2002

ABSTRACT Purpose: Patients with complex chronic disease are often managed with a team approach; y... more ABSTRACT Purpose: Patients with complex chronic disease are often managed with a team approach; yet, clinical decision support (CDS) for teams is limited. We are developing a CDS system for primary care patient panel management with detailed patient-specific recommendations based on clinical practice guidelines. The CDS system will be delivered through an existing Clinical Dashboard used by staff working in Patient Aligned Care Teams (PACT), which is a patient-centered medical home (PCMH) model of care used in VHA Primary Care sites. We aim to design a system that meets both management and end-user requirements for functionality by including stakeholder input early in the design. Method: We conducted detailed semi-structured interviews with 5 stakeholders representing clinical managers, front line staff, and implementation experts; these included physicians, nurses, and pharmacists from 2 different medical centers. We ask about current practices of patient care, including team member roles; use of the Clinical Dashboard; types of CDS that would be useful for the PACTs; and how the system can best integrate into workflow. Result: All of the stakeholders in these preliminary interviews agreed that multimorbidity creating complexity in care of chronic disease is common among their patients. Front-line stakeholders reported that many PACT members use the Clinical Dashboard for panel management, with pharmacists and nurses using it more often than physicians. They enumerated examples of specific challenges, such as the prioritization of treatment goals. There was a high degree of variability in PACT team organizational structure (e.g. some with pharmacist integrated into PACT); in use of the Clinical Dashboard; and team workflow. There was also a lack of consensus on appropriate methods of prioritization among the many management choices for patients with multimorbidity. Conclusion: These interviews have emphasized the need to develop a CDS system that is capable of accommodating different staff roles found in PACT teams operating within varying workflows. The CDS system needs a task-assignment feature that assigns appropriate tasks to PACT members based on their roles and availability, with flexibility to customize to the organizational structure at that site. A CDS system providing prioritization of management choices would likely need to include options of different approaches to prioritization. Views expressed are those of the authors and not necessarily of the Department of Veterans Affairs.

International Journal of Medical Informatics, Feb 1, 2007

Proceedings Amia Annual Symposium Amia Symposium, Sep 11, 2000

Proceedings of the Amia Symposium, 2000

Proceedings Amia Annual Symposium Amia Symposium, Feb 1, 2001

AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium, 2015

We developed a method to evaluate the extent to which the International Classification of Functio... more We developed a method to evaluate the extent to which the International Classification of Function, Disability, and Health (ICF) and SNOMED CT cover concepts used in the disability listing criteria of the U.S. Social Security Administration's "Blue Book." First we decomposed the criteria into their constituent concepts and relationships. We defined different types of mappings and manually mapped the recognized concepts and relationships to either ICF or SNOMED CT. We defined various metrics for measuring the coverage of each terminology, taking into account the effects of inexact matches and frequency of occurrence. We validated our method by mapping the terms in the disability criteria of Adult Listings, Chapter 12 (Mental Disorders). SNOMED CT dominates ICF in almost all the metrics that we have computed. The method is applicable for determining any terminology's coverage of eligibility criteria.

AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium, 2015

Decision support tools increasingly integrate clinical knowledge such as medication indications a... more Decision support tools increasingly integrate clinical knowledge such as medication indications and contraindications with electronic health record (EHR) data to support clinical care and patient safety. The availability of this encoded information and patient data provides an opportunity to develop measures of clinical decision complexity that may be of value for quality improvement and research efforts. We investigated the feasibility of using encoded clinical knowledge and EHR data to develop a measure of comorbidity interrelatedness (the degree to which patients' co-occurring conditions interact to generate clinical complexity). Using a common clinical scenario-decisions about blood pressure medications in patients with hypertension-we quantified comorbidity interrelatedness by calculating the number of indications and contraindications to blood pressure medications that are generated by patients' comorbidities (e.g., diabetes, gout, depression). We examined properties o...

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2017

Clinicians and clinical decision-support systems often follow pharmacotherapy recommendations for... more Clinicians and clinical decision-support systems often follow pharmacotherapy recommendations for patients based on clinical practice guidelines (CPGs). In multimorbid patients, these recommendations can potentially have clinically significant drug-drug interactions (DDIs). In this study, we describe and validate a method for programmatically detecting DDIs among CPG recommendations. The system extracts pharmacotherapy intervention recommendations from narrative CPGs, normalizes the terms, creates a mapping of drugs and drug classes, and then identifies occurrences of DDIs between CPG pairs. We used this system to analyze 75 CPGs written by authoring entities in the United States that discuss outpatient management of common chronic diseases. Using a reference list of high-risk DDIs, we identified 2198 of these DDIs in 638 CPG pairs (46 unique CPGs). Only 9 high-risk DDIs were discussed by both CPGs in a pairing. In 69 of the pairings, neither CPG had a pharmacologic reference or a w...

Journal of biomedical semantics, 2017

Structured data acquisition is a common task that is widely performed in biomedicine. However, cu... more Structured data acquisition is a common task that is widely performed in biomedicine. However, current solutions for this task are far from providing a means to structure data in such a way that it can be automatically employed in decision making (e.g., in our example application domain of clinical functional assessment, for determining eligibility for disability benefits) based on conclusions derived from acquired data (e.g., assessment of impaired motor function). To use data in these settings, we need it structured in a way that can be exploited by automated reasoning systems, for instance, in the Web Ontology Language (OWL); the de facto ontology language for the Web. We tackle the problem of generating Web-based assessment forms from OWL ontologies, and aggregating input gathered through these forms as an ontology of "semantically-enriched" form data that can be queried using an RDF query language, such as SPARQL. We developed an ontology-based structured data acquisi...

AMIA ... Annual Symposium proceedings. AMIA Symposium, 2016

As utilization of clinical decision support (CDS) increases, it is important to continue the deve... more As utilization of clinical decision support (CDS) increases, it is important to continue the development and refinement of methods to accurately translate the intention of clinical practice guidelines (CPG) into a computable form. In this study, we validate and extend the 13 steps that Shiffman et al.(5) identified for translating CPG knowledge for use in CDS. During an implementation project of ATHENA-CDS, we encoded complex CPG recommendations for five common chronic conditions for integration into an existing clinical dashboard. Major decisions made during the implementation process were recorded and categorized according to the 13 steps. During the implementation period, we categorized 119 decisions and identified 8 new categories required to complete the project. We provide details on an updated model that outlines all of the steps used to translate CPG knowledge into a CDS integrated with existing health information technology.

AMIA ... Annual Symposium proceedings. AMIA Symposium, 2016

Through close analysis of two pairs of systems that implement the automated evaluation of perform... more Through close analysis of two pairs of systems that implement the automated evaluation of performance measures (PMs) and guideline-based clinical decision support (CDS), we contrast differences in their knowledge encoding and necessary changes to a CDS system that provides management recommendations for patients failing performance measures. We trace the sources of differences to the implementation environments and goals of PMs and CDS.

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2016

Clinical decision support (CDS) systems with complex logic are being developed. Ensuring the qual... more Clinical decision support (CDS) systems with complex logic are being developed. Ensuring the quality of CDS is imperative, but there is no consensus on testing standards. We tested ATHENA-HTN CDS after encoding updated hypertension guidelines into the system. A logic flow and a complexity analysis of the encoding were performed to guide testing. 100 test cases were selected to test the major pathways in the CDS logic flow, and the effectiveness of the testing was analyzed. The encoding contained 26 decision points and 3120 possible output combinations. The 100 cases selected tested all of the major pathways in the logic, but only 1% of the possible output combinations. Test case selection is one of the most challenging aspects in CDS testing and has a major impact on testing coverage. A test selection strategy should take into account the complexity of the system, identification of major logic pathways, and available resources.

Proceedings Amia Annual Symposium Amia Symposium, Feb 1, 2002

ABSTRACT Purpose: Patients with complex chronic disease are often managed with a team approach; y... more ABSTRACT Purpose: Patients with complex chronic disease are often managed with a team approach; yet, clinical decision support (CDS) for teams is limited. We are developing a CDS system for primary care patient panel management with detailed patient-specific recommendations based on clinical practice guidelines. The CDS system will be delivered through an existing Clinical Dashboard used by staff working in Patient Aligned Care Teams (PACT), which is a patient-centered medical home (PCMH) model of care used in VHA Primary Care sites. We aim to design a system that meets both management and end-user requirements for functionality by including stakeholder input early in the design. Method: We conducted detailed semi-structured interviews with 5 stakeholders representing clinical managers, front line staff, and implementation experts; these included physicians, nurses, and pharmacists from 2 different medical centers. We ask about current practices of patient care, including team member roles; use of the Clinical Dashboard; types of CDS that would be useful for the PACTs; and how the system can best integrate into workflow. Result: All of the stakeholders in these preliminary interviews agreed that multimorbidity creating complexity in care of chronic disease is common among their patients. Front-line stakeholders reported that many PACT members use the Clinical Dashboard for panel management, with pharmacists and nurses using it more often than physicians. They enumerated examples of specific challenges, such as the prioritization of treatment goals. There was a high degree of variability in PACT team organizational structure (e.g. some with pharmacist integrated into PACT); in use of the Clinical Dashboard; and team workflow. There was also a lack of consensus on appropriate methods of prioritization among the many management choices for patients with multimorbidity. Conclusion: These interviews have emphasized the need to develop a CDS system that is capable of accommodating different staff roles found in PACT teams operating within varying workflows. The CDS system needs a task-assignment feature that assigns appropriate tasks to PACT members based on their roles and availability, with flexibility to customize to the organizational structure at that site. A CDS system providing prioritization of management choices would likely need to include options of different approaches to prioritization. Views expressed are those of the authors and not necessarily of the Department of Veterans Affairs.

International Journal of Medical Informatics, Feb 1, 2007

Proceedings Amia Annual Symposium Amia Symposium, Sep 11, 2000

Proceedings of the Amia Symposium, 2000

Proceedings Amia Annual Symposium Amia Symposium, Feb 1, 2001

AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium, 2015

We developed a method to evaluate the extent to which the International Classification of Functio... more We developed a method to evaluate the extent to which the International Classification of Function, Disability, and Health (ICF) and SNOMED CT cover concepts used in the disability listing criteria of the U.S. Social Security Administration's "Blue Book." First we decomposed the criteria into their constituent concepts and relationships. We defined different types of mappings and manually mapped the recognized concepts and relationships to either ICF or SNOMED CT. We defined various metrics for measuring the coverage of each terminology, taking into account the effects of inexact matches and frequency of occurrence. We validated our method by mapping the terms in the disability criteria of Adult Listings, Chapter 12 (Mental Disorders). SNOMED CT dominates ICF in almost all the metrics that we have computed. The method is applicable for determining any terminology's coverage of eligibility criteria.

AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium, 2015

Decision support tools increasingly integrate clinical knowledge such as medication indications a... more Decision support tools increasingly integrate clinical knowledge such as medication indications and contraindications with electronic health record (EHR) data to support clinical care and patient safety. The availability of this encoded information and patient data provides an opportunity to develop measures of clinical decision complexity that may be of value for quality improvement and research efforts. We investigated the feasibility of using encoded clinical knowledge and EHR data to develop a measure of comorbidity interrelatedness (the degree to which patients' co-occurring conditions interact to generate clinical complexity). Using a common clinical scenario-decisions about blood pressure medications in patients with hypertension-we quantified comorbidity interrelatedness by calculating the number of indications and contraindications to blood pressure medications that are generated by patients' comorbidities (e.g., diabetes, gout, depression). We examined properties o...