Browsing by Subject "Decision support systems"
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Item A user-centered evaluation of medication therapy management alerts for community pharmacists: Recommendations to improve usability and usefulness(Elsevier, 2021) Snyder, Margie E.; Adeoye-Olatunde, Omolola A.; Gernant, Stephanie A.; DiIulio, Julie; Jaynes, Heather A.; Doucette, William R.; Russ-Jara, Alissa L.; Medicine, School of MedicineBackground: Community pharmacists provide comprehensive medication reviews (CMRs) through pharmacy contracts with medication therapy management (MTM) vendors. These CMRs are documented in the vendors' web-based MTM software platforms, which often integrate alerts to assist pharmacists in the detection of medication therapy problems. Understanding pharmacists' experiences with MTM alerts is critical to optimizing alert design for patient care. Objectives: The objectives of this study were to 1) assess the usability and usefulness of MTM alerts for MTM vendor-contracted community pharmacists and 2) generate recommendations for improving MTM alerts for use by community pharmacists. Methods: This was a convergent, parallel mixed-methods evaluation of data collected from 3 sources, with individual pharmacists contributing data to one or more sources: 1) community pharmacists' submissions of observational data about MTM alerts encountered during routine MTM provision, 2) videos of naturalistic usability testing of MTM alerts, and 3) semi-structured interviews to elicit pharmacists' perspectives on MTM alert usefulness and usability. MTM alert data submitted by pharmacists were summarized with descriptive statistics. Usability testing videos were analyzed to determine pharmacists' time spent on MTM alerts and to identify negative usability incidents. Interview transcripts were analyzed using a hybrid approach of deductive and inductive codes to identify emergent themes. Triangulation of data (i.e., determination of convergence/divergence in findings across all data sources) occurred through investigator discussion and identified overarching findings pertaining to key MTM alert challenges. These resulted in actionable recommendations to improve MTM alerts for use by community pharmacists. Results: Collectively, two and four overarching key challenges pertaining to MTM alert usability and usefulness, respectively, were identified, resulting in 15 actionable recommendations for improving the design of MTM alerts from a user-centered perspective. Conclusions: Recommendations are expected to inform enhanced MTM alert designs that can improve pharmacist efficiency, patient and prescriber satisfaction with MTM, and patient outcomes.Item Clinician Responses to a Clinical Decision Support Advisory for High Risk of Torsades de Pointes(American Heart Association, 2022) Gallo, Tyler; Heise, C. William; Woosley, Raymond L.; Tisdale, James E.; Tan, Malinda S.; Gephart, Sheila M.; Antonescu, Corneliu C.; Malone, Daniel C.; Medicine, School of MedicineBackground: Torsade de pointes (TdP) is a potentially fatal cardiac arrhythmia that is often drug induced. Clinical decision support (CDS) may help minimize TdP risk by guiding decision making in patients at risk. CDS has been shown to decrease prescribing of high‐risk medications in patients at risk of TdP, but alerts are often ignored. Other risk‐management options can potentially be incorporated in TdP risk CDS. Our goal was to evaluate actions clinicians take in response to a CDS advisory that uses a modified Tisdale QT risk score and presents management options that are easily selected (eg, single click). Methods and Results: We implemented an inpatient TdP risk advisory systemwide across a large health care system comprising 30 hospitals. This CDS was programmed to appear when prescribers attempted ordering medications with a known risk of TdP in a patient with a QT risk score ≥12. The CDS displayed patient‐specific information and offered relevant management options including canceling offending medications and ordering electrolyte replacement protocols or ECGs. We retrospectively studied the actions clinicians took within the advisory and separated by drug class. During an 8‐month period, 7794 TdP risk advisories were issued. Antibiotics were the most frequent trigger of the advisory (n=2578, 33.1%). At least 1 action was taken within the advisory window for 2700 (34.6%) of the advisories. The most frequent action taken was ordering an ECG (n=1584, 20.3%). Incoming medication orders were canceled in 793 (10.2%) of the advisories. The frequency of each action taken varied by drug class (P<0.05 for all actions). Conclusions: A modified Tisdale QT risk score–based CDS that offered relevant single‐click management options yielded a high action/response rate. Actions taken by clinicians varied depending on the class of the medication that evoked the TdP risk advisory, but the most frequent was ordering an ECG.Item Data visualization for truth maintenance in clinical decision support systems(2015-06-19) Liu, Gilbert C.; Odell, Jere D.; Whipple, Elizabeth C.; Ralston, Rick K.; Carroll, Aaron E.; Downs, Stephen M.Background and objectives The goal is to inform proactive initiatives to expand the knowledge base of clinical decision support systems. Design and setting We describe an initiative in which research informationists and health services researchers employ visualization tools to map logic models for clinical decision support within an electronic health record. Materials and methods We mapped relationships using software for social network analysis: NodeXL and CMAP. We defined relationships by shared observations, such as two Arden rules within medical logic modules that consider the same clinical observation, or by the presence of common keywords that were used to label rules according to standardized vocabularies. Results We studied the Child Health Improvement through Computer Automation (CHICA) system, an electronic medical record that contains 170 unique variables representing discrete clinical observations. These variables were used in 300 medical logic modules (MLM's) that prompted health care providers to deliver preventive counseling or otherwise served as clinical decision support. Using data visualization tools, we generated maps that illustrate connections, or lack thereof, between clinical topics within CHICA's MLMs. Conclusions The development of such maps may allow multiple disciplines commonly interacting over EMR platforms, and various perspectives (clinicians, programmers, informationists) to work more effectively as teams to refine the EMR by programming logic routines to address co-morbidities or other instances where domains of medical knowledge should be connected.Item Enhancing research on a clinical decision support and geographic information system: getting involved as informationists(Midwest Chapter, Medical Library Association, 2013-10-07) Whipple, Elizabeth C.; Ralston, Rick K.; Odell, Jere D.; Zimmerman, Carly; Liu, Gilbert C.In 2012, the National Library of Medicine (NLM) funded its first ever administrative supplement for informationists. The purpose of these grants is to enhance multidisciplinary basic and clinical research by integrating information specialists (informationists) on research teams in order to improve the capture, organization, and management of biomedical research data. Three informationists at the Indiana University School of Medicine were awarded one of these supplements to work on the Child Health Improvement through Computer Automation (CHICA) system. CHICA is a computer decision support system that interfaces with existing electronic medical record systems (EMRS) and delivers "just in time" patient-relevant guidelines to physicians during the clinical encounter. CHICA-GIS integrates a geographic information system (GIS) with CHICA to refer pediatricians and parents to relevant health services (as needed, for physical activity, dental care, or tutoring) near the patient's neighborhood. The informationists are enhancing the CHICA-GIS system by: improving the accuracy and accessibility of information, managing and mapping the knowledge which undergirds the CHICA-GIS decision support tool, supporting community engagement and consumer health information outreach, and facilitating the dissemination of new CHICA-GIS research results and services. This paper describes the initial process for approaching and collaborating with researchers, writing the grant and getting funded, and progress on the project goals to date.Item From Dyadic Ties to Information Infrastructures: Care-Coordination between Patients, Providers, Students and Researchers(Thieme, 2015-08-13) Purkayastha, Saptarshi; Price, A.; Biswas, R.; Jai Ganesh, A.U.; Otero, P.; BioHealth Informatics, School of Informatics and ComputingObjective: To share how an effectual merging of local and online networks in low resource regions can supplement and strengthen the local practice of patient centered care through the use of an online digital infrastructure powered by all stakeholders in healthcare. User Driven Health Care offers the dynamic integration of patient values and evidence based solutions for improved medical communication in medical care. Introduction: This paper conceptualizes patient care-coordination through the lens of engaged stakeholders using digital infrastructures tools to integrate information technology. We distinguish this lens from the prevalent conceptualization of dyadic ties between clinician-patient, patient-nurse, clinician-nurse, and offer the holistic integration of all stakeholder inputs, in the clinic and augmented by online communication in a multi-national setting. Methods: We analyze an instance of the user-driven health care (UDHC), a network of providers, patients, students and researchers working together to help manage patient care. The network currently focuses on patients from LMICs, but the provider network is global in reach. We describe UDHC and its opportunities and challenges in care-coordination to reduce costs, bring equity, and improve care quality and share evidence. Conclusion: UDHC has resulted in coordinated global based local care, affecting multiple facets of medical practice. Shared information resources between providers with disparate knowledge, results in better understanding by patients, unique and challenging cases for students, innovative community based research and discovery learning for all.Item Getting off obesity island: how informationists can enhance clinical decision support(Medical Library Association, 2014-05-19) Odell, Jere D.; Ralston, Rick K.; Whipple, Elizabeth C.Clinical decision support (CDS) will play a key role in improving the health of patients; informationists can support the development of CDS systems by indexing rule libraries and mapping the system logic. This work can help rule developers make more informed choices and understand how rules are related conceptually and operationally. With a map, rules can be written to bridge isolated concepts (islands) and rules that are no longer needed can be weeded. Here we explore the added value that informationists bring to projects by reporting on the role of informationists working on a pediatric CDS.Item Measuring agreement between decision support reminders: the cloud vs. the local expert(Springer Nature, 2014-04-10) Dixon, Brian Edward; Simonaitis, Linas; Perkins, Susan M.; Wright, Adam; Middleton, Blackford; Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and EngineeringBackground: A cloud-based clinical decision support system (CDSS) was implemented to remotely provide evidence-based guideline reminders in support of preventative health. Following implementation, we measured the agreement between preventive care reminders generated by an existing, local CDSS and the new, cloud-based CDSS operating on the same patient visit data. Methods: Electronic health record data for the same set of patients seen in primary care were sent to both the cloud-based web service and local CDSS. The clinical reminders returned by both services were captured for analysis. Cohen's Kappa coefficient was calculated to compare the two sets of reminders. Kappa statistics were further adjusted for prevalence and bias due to the potential effects of bias in the CDS logic and prevalence in the relative small sample of patients. Results: The cloud-based CDSS generated 965 clinical reminders for 405 patient visits over 3 months. The local CDSS returned 889 reminders for the same patient visit data. When adjusted for prevalence and bias, observed agreement varied by reminder from 0.33 (95% CI 0.24 - 0.42) to 0.99 (95% CI 0.97 - 1.00) and demonstrated almost perfect agreement for 7 of the 11 reminders. Conclusions: Preventive care reminders delivered by two disparate CDS systems show substantial agreement. Subtle differences in rule logic and terminology mapping appear to account for much of the discordance. Cloud-based CDSS therefore show promise, opening the door for future development and implementation in support of health care providers with limited resources for knowledge management of complex logic and rules.Item The role of informationists in delivering geospatial intelligence to health care professionals(National Network of Libraries of Medicine, 2013-10-11) Ralston, Rick K.; Whipple, Elizabeth C.; Odell, Jere D.; Liu, Gilbert C.Three informationists at the Indiana University School of Medicine were awarded NLM supplement to work on the Child Health Improvement through Computer Automation (CHICA) system. CHICA is a computer decision support system that interfaces with existing electronic medical record systems (EMRS) and delivers "just in time" patient-relevant guidelines to physicians during the clinical encounter. CHICA-GIS integrates a geographic information system (GIS) with CHICA to refer pediatricians and parents to relevant health services (as needed, for physical activity, dental care, or tutoring) near the patient's neighborhood. The informationists are enhancing the CHICA-GIS system by: improving the accuracy and accessibility of information, managing and mapping the knowledge which undergirds the CHICA-GIS decision support tool, supporting community engagement and consumer health information outreach, and facilitating the dissemination of new CHICA-GIS research results and services. This presentation describes the initial process for approaching and collaborating with researchers, writing the grant and getting funded, and progress on the project goals to date.Item A Trustworthy Human–Machine framework for collective decision making in Food–Energy–Water management: The role of trust sensitivity(Elsevier, 2021-02) Uslu, Suleyman; Kaur, Davinder; Rivera, Samuel J.; Durresi, Arjan; Babbar-Sebens, Meghna; Tilt, Jenna H.; Computer and Information Science, School of ScienceWe propose a hybrid Trustworthy Human–Machine collective decision-making framework to manage Food–Energy–Water (FEW) resources. Decisions for managing such resources impact not only the environment but also influence the economic productivity of FEW sectors and the well-being of society. Therefore, while algorithms can be used to develop optimal solutions under various criteria, it is essential to explain such solutions to the community. More importantly, the community should accept such solutions to be able realistically to apply them. In our collaborative computational framework for decision support, machines and humans interact to converge on the best solutions accepted by the community. In this framework, trust among human actors during decision making is measured and managed using a novel trust management framework. Furthermore, such trust is used to encourage human actors, depending on their trust sensitivity, to choose among the solutions generated by algorithms that satisfy the community’s preferred trade-offs among various objectives. In this paper, we show different scenarios of decision making with continuous and discrete solutions. Then, we propose a game-theory approach where actors maximize their payoff regarding their share and trust weighted by their trust sensitivity. We run simulations for decision-making scenarios with actors having different distributions of trust sensitivities. Results showed that when actors have high trust sensitivity, a consensus is reached 52% faster than scenarios with low trust sensitivity. The utilization of ratings of ratings increased the solution trustworthiness by 50%. Also, the same level of solution trustworthiness is reached 2.7 times faster when ratings of ratings included.