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Browsing by Author "Doebbeling, Bradley N."
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Item Applying human factors principles to alert design increases efficiency and reduces prescribing errors in a scenario-based simulation(Oxford University Press, 2014-10) Russ, Alissa L.; Zillich, Alan J.; Melton, Brittany L.; Russell, Scott A.; Chen, Siying; Spina, Jeffrey R.; Weiner, Michael; Johnson, Elizabette G.; Daggy, Joanne K.; McAnas, M. Sue; Hawsey, Jason M.; Puleo, Anthony G.; Doebbeling, Bradley N.; Saleem, Jason J.; Medicine Faculty Volunteers, IU School of MedicineOBJECTIVE: To apply human factors engineering principles to improve alert interface design. We hypothesized that incorporating human factors principles into alerts would improve usability, reduce workload for prescribers, and reduce prescribing errors. MATERIALS AND METHODS: We performed a scenario-based simulation study using a counterbalanced, crossover design with 20 Veterans Affairs prescribers to compare original versus redesigned alerts. We redesigned drug-allergy, drug-drug interaction, and drug-disease alerts based upon human factors principles. We assessed usability (learnability of redesign, efficiency, satisfaction, and usability errors), perceived workload, and prescribing errors. RESULTS: Although prescribers received no training on the design changes, prescribers were able to resolve redesigned alerts more efficiently (median (IQR): 56 (47) s) compared to the original alerts (85 (71) s; p=0.015). In addition, prescribers rated redesigned alerts significantly higher than original alerts across several dimensions of satisfaction. Redesigned alerts led to a modest but significant reduction in workload (p=0.042) and significantly reduced the number of prescribing errors per prescriber (median (range): 2 (1-5) compared to original alerts: 4 (1-7); p=0.024). DISCUSSION: Aspects of the redesigned alerts that likely contributed to better prescribing include design modifications that reduced usability-related errors, providing clinical data closer to the point of decision, and displaying alert text in a tabular format. Displaying alert text in a tabular format may help prescribers extract information quickly and thereby increase responsiveness to alerts. CONCLUSIONS: This simulation study provides evidence that applying human factors design principles to medication alerts can improve usability and prescribing outcomes.Item Computerised Clinical Reminders Use in an Integrated Healthcare System(2009) Fung, Constance; Tsai, Jerry; Lulejian, Armine; Glassman, Peter; Patterson, Emily; Doebbeling, Bradley N.; Asch, StevenObjective: To examine levels of routine computerised clinical reminder use in a nationwide sample of primary care physicians and to identify factors influencing reminder use. Design: Cross-sectional using a self-administered questionnaire. Setting: The United States Veterans Health Administration. Methods: Survey responses from 461 VHA primary care physicians sampled from across the Veterans Health Administration were sampled and analysed. We asked physicians how many computerised clinical reminders they use per patient per visit and when they typically use computerised clinical reminders in their clinics. Measured physician characteristics included age, gender, year of medical degree, number of days in clinic per week, and attitudes towards computerised clinical reminders (measured on Likert-like scales). We used multivariable linear regression to determine factors associated with greater use of computerised clinical reminders per patient per visit. Results: Average computerised clinical reminder use per patient visit was 4.2 (SD = 2.5). Eightysix percent of physicians resolve reminders during the visit. In a multivariable regression model, a higher score on the team factors scale is associated with use of more reminders (increase of 0.24 reminders for each unit increase on the team factors scale, or one extra reminder for each four unit increase in the team factor scale). Working more days in clinic is associated with use of more reminders per patient visit (increase of 0.13 reminders for each extra half-day of clinic per week, or about one additional reminder for physicians working ten half-days per week versus physicians working two half-days per week). Academic facility affiliation is associated with one less reminder used per patient visit as compared with no affiliation. Conclusions: Most United States Veterans Health Administration primary care physicians use computerised clinical reminders, typically during the patient visit. Strategies to increase reminder use should focus on improving physicians’ understanding of their role in completing reminder-related tasks and improving usability for users such as physicians who work in clinic less frequently.Item Data Analytics and Modeling for Appointment No-show in Community Health Centers(SAGE, 2018) Mohammadi, Iman; Wu, Huanmei; Turkcan, Ayten; Toscos, Tammy; Doebbeling, Bradley N.; BioHealth Informatics, School of Informatics and ComputingObjectives: Using predictive modeling techniques, we developed and compared appointment no-show prediction models to better understand appointment adherence in underserved populations. Methods and Materials: We collected electronic health record (EHR) data and appointment data including patient, provider and clinical visit characteristics over a 3-year period. All patient data came from an urban system of community health centers (CHCs) with 10 facilities. We sought to identify critical variables through logistic regression, artificial neural network, and naïve Bayes classifier models to predict missed appointments. We used 10-fold cross-validation to assess the models’ ability to identify patients missing their appointments. Results: Following data preprocessing and cleaning, the final dataset included 73811 unique appointments with 12,392 missed appointments. Predictors of missed appointments versus attended appointments included lead time (time between scheduling and the appointment), patient prior missed appointments, cell phone ownership, tobacco use and the number of days since last appointment. Models had a relatively high area under the curve for all 3 models (e.g., 0.86 for naïve Bayes classifier). Discussion: Patient appointment adherence varies across clinics within a healthcare system. Data analytics results demonstrate the value of existing clinical and operational data to address important operational and management issues. Conclusion: EHR data including patient and scheduling information predicted the missed appointments of underserved populations in urban CHCs. Our application of predictive modeling techniques helped prioritize the design and implementation of interventions that may improve efficiency in community health centers for more timely access to care. CHCs would benefit from investing in the technical resources needed to make these data readily available as a means to inform important operational and policy questions.Item Development of a Workflow Integration Survey (WIS) for Implementing Computerized Clinical Decision Support(2011-10) Flanagan, Mindy; Arbuckle, Nicole; Saleem, Jason J.; Militello, Laura G.; Haggstrom, David A.; Doebbeling, Bradley N.Interventions that focus on improving computerized clinical decision support (CDS) demonstrate that successful workflow integration can increase the adoption and use of CDS. However, metrics for assessing workflow integration in clinical settings are not well established. The goal of this study was to develop and validate a survey to assess the extent to which CDS is integrated into workflow. Qualitative data on CDS design, usability, and integration from four sites was collected by direct observation, interviews, and focus groups. Thematic analysis based on the sociotechnical systems theory revealed consistent themes across sites. Themes related to workflow integration included navigation, functionality, usability, and workload. Based on these themes, a brief 12-item scale to assess workflow integration was developed, refined, and validated with providers in a simulation study. To our knowledge, this is one of the first tools developed to specifically measure workflow integration of CDS.Item The effect of provider- and workflow-focused strategies for guideline implementation on provider acceptance(2009-10) Flanagan, Mindy E.; Ramanujam, Rangaraj; Doebbeling, Bradley N.Background The effective implementation of clinical practice guidelines (CPGs) depends critically on the extent to which the strategies that are deployed for implementing the guidelines promote provider acceptance of CPGs. Such implementation strategies can be classified into two types based on whether they primarily target providers (e.g., academic detailing, grand rounds presentations) or the work context (e.g., computer reminders, modifications to forms). This study investigated the independent and joint effects of these two types of implementation strategies on provider acceptance of CPGs. Methods Surveys were mailed to a national sample of providers (primary care physicians, physician assistants, nurses, and nurse practitioners) and quality managers selected from Veterans Affairs Medical Centers (VAMCs). A total of 2,438 providers and 242 quality managers from 123 VAMCs participated. Survey items measured implementation strategies and provider acceptance (e.g., guideline-related knowledge, attitudes, and adherence) for three sets of CPGs--chronic obstructive pulmonary disease, chronic heart failure, and major depressive disorder. The relationships between implementation strategy types and provider acceptance were tested using multi-level analytic models. Results For all three CPGs, provider acceptance increased with the number of implementation strategies of either type. Moreover, the number of workflow-focused strategies compensated (contributing more strongly to provider acceptance) when few provider-focused strategies were used. Conclusion Provider acceptance of CPGs depends on the type of implementation strategies used. Implementation effectiveness can be improved by using both workflow-focused as well as provider-focused strategies.Item Efficiency Strategies for Facilitating Computerized Clinical Documentation in Ambulatory Care(2013) Saleem, Jason J.; Adams, Stephanie; Frankel, Richard M.; Doebbeling, Bradley N.; Patterson, Emily S.Most providers have experienced increased documentation demands with the use of electronic health records (EHRs). We sought to identify efficiency strategies that providers use to complete clinical documentation tasks in ambulatory care. Two observers performed ethnographic observations and interviews with 22 ambulatory care providers in a U.S. Veterans Affairs Medical Center. Observation notes and interview transcripts were coded for recurrent strategies relating to completion of the EHR progress notes. Findings included: the use of paper artifacts for handwritten notations; electronic templates for automation of certain parts of the note; use of shorthand and phrases rather than narrative writing; copying and pasting from previous EHR notes; directly entering information into the EHR note during the patient encounter; reliance on memory; and pre-populating an EHR note prior to seeing the patient. We discuss the findings in the context of distributed cognition to understand how clinical information is propagated and represented toward completion of a progress note. The study findings have important implications for improving and streamlining clinical documentation related to human factors workload management strategies.Item Examining the Relationship between Clinical Decision Support and Performance Measurement(2009-11) Haggstrom, David A.; Militello, Laura G.; Arbuckle, Nicole; Flanagan, Mindy; Doebbeling, Bradley N.In concept and practice, clinical decision support (CDS) and performance measurement represent distinct approaches to organizational change, yet these two organizational processes are interrelated. We set out to better understand how the relationship between the two is perceived, as well as how they jointly influence clinical practice. To understand the use of CDS at benchmark institutions, we conducted semistructured interviews with key managers, information technology personnel, and clinical leaders during a qualitative field study. Improved performance was frequently cited as a rationale for the use of clinical reminders. Pay-for-performance efforts also appeared to provide motivation for the use of clinical reminders. Shared performance measures were associated with shared clinical reminders. The close link between clinical reminders and performance measurement causes these tools to have many of the same implementation challenges.Item Integrating Clinical Decision Support into Workflow(2011) Doebbeling, Bradley N.; Saleem, Jason; Haggstrom, David; Militello, Laura; Flanagan, Mindy; Arbuckle, Nicole; Kiess, Chris; Hoke, Shawn; Dexter, Paul; Linder, Jeff; Sarbah, Steedman; Burgo, LucillePurpose: The aims were to (1) identify barriers and facilitators related to integration of clinical decision support (CDS) into workflow and (2) develop and test CDS design alternatives. Scope: To better understand CDS integration, we studied its use in practice, focusing on CDS for colorectal cancer (CRC) screening and followup. Phase 1 involved outpatient clinics of four different systems—120 clinic staff and providers and 118 patients were observed. In Phase 2, prototyped design enhancements to the Veterans Administration’s CRC screening reminder were compared against its current reminder in a simulation experiment. Twelve providers participated. Methods: Phase 1 was a qualitative project, using key informant interviews, direct observation, opportunistic interviews, and focus groups. All data were analyzed using a coding template, based on the sociotechnical systems theory, which was modified as coding proceeded and themes emerged. Phase 2 consisted of rapid prototyping of CDS design alternatives based on Phase 1 findings and a simulation experiment to test these design changes in a within-subject comparison. Results: Very different CDS types existed across sites, yet there are common barriers: (1) lack of coordination of “outside” results and between primary and specialty care; (2) suboptimal data organization and presentation; (3) needed provider and patient education; (4) needed interface flexibility; (5) needed technological enhancements; (6) unclear role assignments; (7) organizational issues; and (8) disconnect with quality reporting. Design enhancements positively impacted usability and workflow integration but not workload. Conclusions: Effective CDS design and integration requires: (1) organizational and workflow integration; (2) integrating outside results; (3) improving data organization and presentation in a flexible interface; and (4) providing just-in time education, cognitive support, and quality reporting.Item Large-Scale Data Mining to Optimize Patient-Centered Scheduling at Health Centers(Springer, 2018-09-04) Kunjan, Kislaya; Wu, Huanmei; Toscos, Tammy R.; Doebbeling, Bradley N.; BioHealth Informatics, School of Informatics and ComputingPatient-centered appointment access is of critical importance at community health centers (CHCs) and its optimal implementation entails the use of advanced data analytics. This study seeks to optimize patient-centered appointment scheduling through data mining of Electronic Health Record/Practice Management (EHR/PM) systems. Data was collected from different EHR/PM systems in use at three CHCs across the state of Indiana and integrated into a multidimensional data warehouse. Data mining was performed using decision tree modeling, logistic regression, and visual analytics combined with n-gram modeling to derive critical influential factors that guide implementation of patient-centered open-access scheduling. The analysis showed that appointment adherence was significantly correlated with the time dimension of scheduling, with lead time for an appointment being the most significant predictor. Other variables in the time dimension such as time of the day and season were important predictors as were variables tied to patient demographic and clinical characteristics. Operationalizing the findings for selection of open-access hours led to a 16% drop in missed appointment rates at the interventional health center. The study uncovered the variability in factors affecting patient appointment adherence and associated open-access interventions in different health care settings. It also shed light on the reasons for same-day appointment through n-gram-based text mining. Optimizing open-access scheduling methods require ongoing monitoring and mining of large-scale appointment data to uncover significant appointment variables that impact schedule utilization. The study also highlights the need for greater "in-CHC" data analytic capabilities to re-design care delivery processes for improving access and efficiency.Item Missing links: challenges in engaging the underserved with health information and communication technology(ACM, 2016-05) Wright, Maria D.; Flanagan, Mindy E.; Kunjan, Kislaya; Doebbeling, Bradley N.; Toscos, Tammy; BioHealth Informatics, School of Informatics and ComputingWe sought to understand underserved patients' preferences for health information technology (HIT) and examine the current use of personal health records (PHRs) in Community Health Centers (CHCs) serving low-income, uninsured, and underinsured patients. Forty-three patients and 49 clinic staff, administrators, and providers from these CHC systems were interviewed using open-ended questions assessing patient experience, perceptions of the CHC, access barriers, strategies used to overcome access barriers, technology access and use, and clinic operations and workflow. All seven CHC systems were at some stage of implementing PHRs, with two clinics having already completed implementation. Indiana CHCs have experienced barriers to implementing and using PHRs in a way that provides value for patients or providers/staff There was a general lack of awareness among patients regarding the existence of PHRs, their benefits and a lack of effective promotion to patients. Most patients have access to the internet, primarily through mobile phones, and desire greater functionality in order to communicate with CHCs and manage their health conditions. Despite decades of research, there remain barriers to the adoption and use of PHRs. Novel approaches must be developed to achieve the desired impact of PHRs on patient engagement, communication and satisfaction. Our findings provide a roadmap to greater engagement of patients via PHRs by expanding functionality, training both patients and clinic providers/staff, and incorporating adult learning strategies.
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