A six-year repeated evaluation of computerized clinical decision support system user acceptability

OBJECTIVE: Long-term acceptability among computerized clinical decision support system (CDSS) users in pediatrics is unknown. We examine user acceptance patterns over six years of our continuous computerized CDSS integration and updates. MATERIALS AND METHODS: Users of Child Health Improvement through Computer Automation (CHICA), a CDSS integrated into clinical workflows and used in several urban pediatric community clinics, completed annual surveys including 11 questions covering user acceptability. We compared responses across years within a single healthcare system and between two healthcare systems. We used logistic regression to assess the odds of a favorable response to each question by survey year, clinic role, part-time status, and frequency of CHICA use. RESULTS: Data came from 380 completed surveys between 2011 and 2016. Responses were significantly more favorable for all but one measure by 2016 (OR range 2.90-12.17, all p < 0.01). Increasing system maturity was associated with improved perceived function of CHICA (OR range 4.24-7.58, p < 0.03). User familiarity was positively associated with perceived CDSS function (OR range 3.44-8.17, p < 0.05) and usability (OR range 9.71-15.89, p < 0.01) opinions. CONCLUSION: We present a long-term, repeated follow-up of user acceptability of a CDSS. Favorable opinions of the CDSS were more likely in frequent users, physicians and advanced practitioners, and full-time workers. CHICA acceptability increased as it matured and users become more familiar with it. System quality improvement, user support, and patience are important in achieving wide-ranging, sustainable acceptance of CDSS

Effect of a Computer-Based Decision Support Intervention on Autism Spectrum Disorder Screening in Pediatric Primary Care Clinics: A Cluster Randomized Clinical Trial

Importance: Universal early screening for autism spectrum disorder (ASD) is recommended but not routinely performed. Objective: To determine whether computer-automated screening and clinical decision support can improve ASD screening rates in pediatric primary care practices. Design, Setting, and Participants: This cluster randomized clinical trial, conducted between November 16, 2010, and November 21, 2012, compared ASD screening rates among a random sample of 274 children aged 18 to 24 months in urban pediatric clinics of an inner-city county hospital system with or without an ASD screening module built into an existing decision support software system. Statistical analyses were conducted from February 6, 2017, to June 1, 2018. Interventions: Four clinics were matched in pairs based on patient volume and race/ethnicity, then randomized within pairs. Decision support with the Child Health Improvement Through Computer Automation system (CHICA) was integrated with workflow and with the electronic health record in intervention clinics. Main Outcomes and Measures: The main outcome was screening rates among children aged 18 to 24 months. Because the intervention was discontinued among children aged 18 months at the request of the participating clinics, only results for those aged 24 months were collected and analyzed. Rates of positive screening results, clinicians' response rates to screening results in the computer system, and new cases of ASD identified were also measured. Main results were controlled for race/ethnicity and intracluster correlation. Results: Two clinics were randomized to receive the intervention, and 2 served as controls. Records from 274 children (101 girls, 162 boys, and 11 missing information on sex; age range, 23-30 months) were reviewed (138 in the intervention clinics and 136 in the control clinics). Of 263 children, 242 (92.0%) were enrolled in Medicaid, 138 (52.5%) were African American, and 96 (36.5%) were Hispanic. Screening rates in the intervention clinics increased from 0% (95% CI, 0%-5.5%) at baseline to 68.4% (13 of 19) (95% CI, 43.4%-87.4%) in 6 months and to 100% (18 of 18) (95% CI, 81.5%-100%) in 24 months. Control clinics had no significant increase in screening rates (baseline, 7 of 64 children [10.9%]; 6-24 months after the intervention, 11 of 72 children [15.3%]; P = .46). Screening results were positive for 265 of 980 children (27.0%) screened by CHICA during the study period. Among the 265 patients with positive screening results, physicians indicated any response in CHICA in 151 (57.0%). Two children in the intervention group received a new diagnosis of ASD within the time frame of the study. Conclusions and Relevance: The findings suggest that computer automation, when integrated with clinical workflow and the electronic health record, increases screening of children for ASD, but follow-up by physicians is still flawed. Automation of the subsequent workup is still needed

Preparation and Use of Preconstructed Orders, Order Sets, and Order Menus in a Computerized Provider Order Entry System

Objective: To describe the configuration and use of the computerized provider order entry (CPOE) system used for inpatient and outpatient care at the authors' facility. Design: Description of order configuration entities, use patterns, and configuration changes in a production CPOE system. Measurements: The authors extracted and analyzed the content of order configuration entities (order dialogs, preconfigured [quick] orders, order sets, and order menus) and determined the number of orders entered in their production order entry system over the previous three years. The authors measured use of these order configuration entities over a six-month period. They repeated the extract two years later to measure changes in these entities. Results: CPOE system configuration, conducted before and after first production use, consisted of preparing 667 order dialogs, 5,982 preconfigured (quick) orders, and 513 order sets organized in 703 order menus for particular contexts, such as admission for a particular diagnosis. Fifty percent of the order dialogs, 57% of the quick orders, and 13% of the order sets were used within a six-month period. Over the subsequent two years, the volume of order configuration entities increased by 26%. Conclusions: These order configuration steps were time-consuming, but the authors believe they were important to increase the ordering speed and acceptability of the order entry software. Lessons learned in the process of configuring the CPOE ordering system are given. Better understanding of ordering patterns may make order configuration more efficient because many of the order configuration entities that were created were not used by clinician

Decision Support in Medicine: Examples from the HELP System

journal articleBiomedical Informatic

Hospital-Based Decision Support

book chapterBiomedical Informatic

Clinical Decision Support at Intermountain Healthcare

book chapterBiomedical Informatic

Addressing Health Literacy in Patient Decision Aids:An Update from the International Patient Decision Aid Standards

BACKGROUND: There is increasing recognition of the importance of addressing health literacy in patient decision aid (PtDA) development. PURPOSE: An updated review as part of IPDAS 2.0 examined the extent to which PtDAs are designed to meet the needs of low health literacy/disadvantaged populations. DATA SOURCES: Reference list of Cochrane review of randomised controlled trials (RCTs) of PtDAs (2014, 2017 and upcoming 2021 versions). STUDY SELECTION: RCTs that assessed the impact of PtDAs on low health literacy or other disadvantaged groups (i.e. ≥50% participants from disadvantaged groups and/or subgroup analysis in disadvantaged group/s). DATA EXTRACTION: Two researchers independently extracted data into a standardized form including PtDA development and evaluation details. We searched online repositories and emailed authors to access PtDAs to verify reading level, understandability and actionability. DATA SYNTHESIS: Twenty-five out of 213 RCTs met inclusion criteria illustrating that only 12% of studies addressed the needs of low health literacy or other disadvantaged groups. Reading age was calculated in 8/25 studies (33%), which is recommended in previous IPDAS guidelines. We accessed and independently assessed 11 PtDAs. None were written at 6(th) grade level or below. Ten PtDAs met the recommended threshold for understandability, but only 5 met the recommended threshold for actionability. We also conducted a post-hoc subgroup meta-analysis and found that knowledge improvements after receiving a PtDA were greater in studies that reported using strategies to reduce cognitive demand in PtDA development compared to studies that did not (Chi(2)=14.11, p=0.0002, I(2)=92.9%). LIMITATIONS: We were unable to access 13 out of 24 PtDAs. CONCLUSIONS: Greater attention to health literacy and disadvantaged populations is needed in the field of PtDAs to ensure equity in decision support

Understanding the acceptability of a computer decision support system in pediatric primary care

Objective Individual users' attitudes and opinions help predict successful adoption of health information technology (HIT) into practice; however, little is known about pediatric users' acceptance of HIT for medical decision-making at the point of care. Materials and methods We wished to examine the attitudes and opinions of pediatric users' toward the Child Health Improvement through Computer Automation (CHICA) system, a computer decision support system linked to an electronic health record in four community pediatric clinics. Surveys were administered in 2011 and 2012 to all users to measure CHICA's acceptability and users' satisfaction with it. Free text comments were analyzed for themes to understand areas of potential technical refinement. Results 70 participants completed the survey in 2011 (100% response rate) and 64 of 66 (97% response rate) in 2012. Initially, satisfaction with CHICA was mixed. In general, users felt the system held promise; however various critiques reflected difficulties understanding integrated technical aspects of how CHICA worked, as well as concern with the format and wording on generated forms for families and users. In the subsequent year, users' ratings reflected improved satisfaction and acceptance. Comments also reflected a deeper understanding of the system's logic, often accompanied by suggestions on potential refinements to make CHICA more useful at the point of care. Conclusions Pediatric users appreciate the system's automation and enhancements that allow relevant and meaningful clinical data to be accessible at point of care. Understanding users' acceptability and satisfaction is critical for ongoing refinement of HIT to ensure successful adoption into practice

A Computational Framework for Planning Therapeutical Sessions aimed to Support the Prevention and Treatment of Mental Health Disorders using Emotional Virtual Agents

[EN] Interaction is defined as the realization of a reciprocal action between two or more people or things. Particularly in computer science, the term interaction refers to the discipline that studies the exchange of information between people and computers, and is generally known by the term Human-Computer Interaction (HCI). Good design decisions and an adequate development of the software is required for efficient HCI to facilitate the acceptability of computer-based applications by the users. In clinical settings it is essential to eliminate any barrier and facilitate the interaction between patients and the system. A smooth communication between the user and the computer-based application is fundamental to maximise the advantages and functionalities offered by the system. The design of these applications must consider the personal and current needs of the user by applying a User-Centered Design methodology. The main purpose of this research work is to contribute in the improvement of HCI-based applications addressed to the clinical context, particularly to enhance computer-based interactive sessions to support people suffering from a mental disorder such as Major Depression (MD). Thanks to the advances in Artificial Intelligence techniques, it is now possible to partially automate complex tasks such as the continuous provision of Cognitive-Behavioural Therapies (CBTs) to patients. These CBTs require good levels of adaptability and variability during the interaction with the patient that facilitates the acceptability in the user, an optimal usability and good level of engagement for a successful mid/long term use of the application and treatment adherence. The modelling of complex deliberative and affective processes in artificial systems can be applied to support the prevention and treatment of mental health related issues, enhancing the continuous and remote assistance of patients, saving some economical and clinical resources and reducing the waiting lists in the health services. In this regard, the efforts of this Thesis have been concentrated on the research of two main lines: (1) the generation and planning of adequate contents in an interactive system to support the prevention and treatment of MD based on characteristics of the user; and (2) the modelling of relevant affective processes able to communicate the contents in an emotional effective way taking into account the importance of the affective conditions associated with the MD in the users. Rule Based Systems and the appraisal theory of emotions have been the roots used to develop the main two modules of the computational Framework presented: the Contents Management and the Emotional Modules. Finally, the obtained Framework was integrated into two interactive systems to evaluate the achievement of the research objectives. The first system has been developed in the context of the Help4Mood European research project and its main aim was to support the remote treatment of patients with MD. The second scenario was a system developed to prevent MD and suicidal thoughts in the University community, which was developed in the context of the local PrevenDep research project. These evaluations have indicated that the proposed Framework has reached good levels of usability and acceptability in the target users thanks to the personalizations and adaptation capabilities of the contents and in the way how these contents are communicated to the user. The research work and the obtained results in this Thesis has contributed to the state of the art in HCI-based systems used as support in therapeutic interventions for the prevention and treatment of MD. This was obtained by the combination of a personalized content management to the patient, and the management of the affective processes associated to these pathologies. The developed work also identifies some research lines that need to be addressed in future works to get better HCI systems used for therapeutic purposes.[ES] Interactuar se define como la realización de una acción recíproca entre dos o más personas o cosas. Particularmente en informática, el término interacción se refiere a la disciplina que estudia el intercambio de información entre las personas y computadoras, y suele conocerse por el término anglosajón Human-Computer Interaction (HCI). Un buen diseño y un adecuado desarrollo del software es necesario para lograr una HCI eficiente que facilite la aceptabilidad del sistema por el usuario. En entornos clínicos es fundamental eliminar cualquier tipo de barrera y facilitar la interacción entre los pacientes y el computador. Es de vital importancia que haya una buena comunicación entre usuario y computador, por este motivo el sistema debe de estar diseñado pensando en las necesidades actuales, cambiantes y personales del usuario, basándose en la metodología de diseño centrado en el usuario. El propósito principal de esta investigación es la identificación de mejoras en HCI aplicada en entornos clínicos, en concreto para dar soporte a personas con trastornos mentales como la Depresión Mayor (DM) y que precisan de terapias psicológicas adecuadas y continuas. Gracias a técnicas de Inteligencia Artificial, es posible automatizar eficientemente ciertas acciones asociadas a los procesos de las terapias cognitivo-conductuales (CBTs, del inglés Cognitive-Behavioural Therapies). Los sistemas de ayuda a la CBT, requieren de una adaptabilidad y variabilidad en la interacción para favorecer la usabilidad del sistema y asegurar la continuidad de la motivación del paciente. Una buena gestión de esta automatización influiría en la aceptabilidad de los pacientes y podría mejorar su adherencia a los tratamientos y por consiguiente mejorar su estado de salud. Adicionalmente, la unión de procesos deliberativos dinámicos pueden liberar recursos clínicos, mejorando el control de los pacientes, y reduciendo los tiempos de espera y los costes económicos. En este sentido, los esfuerzos de esta Tesis se han centrado en la investigación de dos líneas diferentes: (1) la selección y planificación adecuada de los contenidos presentados durante la interacción a través de una planificación dinámica y personalizada, y (2) la adecuación de la comunicación de los contenidos hacia el paciente tomando en cuenta la importancia de los procesos afectivos asociados a estas patologías. Los Sistemas Basados en Reglas (SBR) han sido la herramienta utilizada para dar soporte a los dos módulos principales que componen el Framework presentado en esta Tesis: el módulo de gestión de los contenidos y el módulo emocional. Concluida la fase de diseño, desarrollo y testeo, el Framework fue adaptado e integrado en sistemas reales, para validar la viabilidad y la adecuación del marco de trabajo de esta Tesis. En primer lugar, el sistema se aplicó durante tres años en el tratamiento de la DM en varios centros clínicos europeos en el contexto del Proyecto Europeo de investigación Help4Mood. Finalmente, el sistema fue evaluado en la tarea de prevención de la DM y del suicidio en el Proyecto Local de investigación PrevenDep, de un año de duración. El feedback de estas evaluaciones demostraron que el HCI del Framework tiene unos niveles altos de usabilidad y aceptación, gracias a la personalización, variabilidad y adaptación de los contenidos y de la comunicación de los mismos. Los experimentos computacionales llevados a cabo en esta Tesis han permitido avanzar el estado del arte de sistemas computacionales emocionales aplicados en entornos terapéuticos para la prevención y tratamiento de la DM. Principalmente, gracias a la combinación de una gestión personalizada de los contenidos hacia el paciente tomando en cuenta la importancia de los procesos afectivos asociados a estas patologías. Este trabajo abre nuevas líneas de investigación, como la aplicación de este sistema en otras patologías de salud mental en las qu[CA] Interactuar es defineix com la realització d'una acció recíproca entre dos o més persones o coses. Particularment en informàtica, el terme interacció es refereix a la disciplina que estudia l'intercanvi d'informació entre les persones i computadores, i es sol conèixer pel terme anglosaxó Human-Computer Interaction (HCI). Un bon disseny i un adequat desenvolupament del software és necessari per aconseguir una HCI eficient que faciliti l'acceptabilitat del sistema per l'usuari. En entorns clínics és fonamental eliminar qualsevol tipus de barrera i facilitar la interacció entre els pacients i el computador. És de vital importància que hi hagi una bona comunicació entre l'usuari (o pacient) i el computador, per aquest motiu el sistema ha d'estar dissenyat pensant en les necessitats actuals, cambiants i personals de l'usuari, basant-se en la metodologia de disseny centrat en l'usuari. El propòsit principal d'aquesta investigació és la identificació de millores en HCI aplicada en entorns clínics, en concret per donar suport a persones amb trastorns mentals com la Depressió Major (DM) i que precisen de teràpies psicològiques adequades i contínues. Gràcies a tècniques d'Intel·ligència Artificial, és possible automatitzar eficientment certes accions asociades al processos de les teràpies cognitiu-conductuals. Els sistemes computacionals de ajuda a la CBT, requereixen d'una adaptabilitat i variabilitat en la interacció per afavorir la usabilitat del sistema i assegurar la continuïtat de la motiviació del pacient. Una bona gestió d'aquesta automatització influiria en l'acceptabilitat dels pacients i podria millorar la seva adherència als tractaments i per tant millorar el seu estat de salut. Addicionalment, la unió de processos deliberatius dinàmics poden alliberar recursos clínics, millorant el control dels pacients, i reduint els temps d'espera i els costos econòmics. En aquest sentit, els esforços d'aquesta Tesi s'han centrat en la investigació de dues línies diferents: (1) la selecció i planificació adequada dels continguts presentats durant la interacció a través d'una planificació dinàmica i personalitzada, i (2) l'adequació de la comunicació dels continguts cap al pacient tenint en compte la importància dels processos afectius associats a aquestes patologies. Els Sistemes Basats en Regles (SBR) han estat la eina utilitzada per donar suport als dos mòduls principals que componen el Framework presentat en aquesta Tesi: el mòdul de gestió dels continguts oferits a l'usuari; i el mòdul emocional. Conclosa la fase de disseny, desenvolupament i testeig, el Framework va ser adaptat als dominis corresponents i integrat en sistemes madurs per ser avaluat en dos escenaris reals, per validar la viabilitat i l'adequació del Framework d'aquesta tesi. Primerament, el sistema es va aplicar durant tres anys en el tractament de la DM major en diversos centres clínics europeus en el context del Projecte Europeu d'investigació Help4Mood. Finalment, el sistema va ser avaluat en la tasca de prevenció de la DM i del suïcidi al Projecte Local d'investigació PrevenDep, d'un any de durada. El feedback de les avaluacions han demostrat que el HCI del Framework obté uns nivells alts d'usabilitat i acceptació, gràcies a la personalització, variabilitat i adaptació dels continguts i de la comunicació. Els experiments computacionals duts a terme en aquesta Tesi han permès avançar l'estat de l'art de sistemes computacionals emocionals aplicats en entorns terapèutics per a la prevenció i tractament de la DM. Principalment, gracies a la combinació d'una gestió personalitzada dels continguts cap al pacient tenint en compte la importància dels processos afectius associats a aquestes patologies. Aquest treball obre noves línies d'investigació, com l'aplicació d'aquest sistema en altres patologies de salut mental en què sigui recomanable l'aplicació de sessions terapèutiques.Bresó Guardado, A. (2016). A Computational Framework for Planning Therapeutical Sessions aimed to Support the Prevention and Treatment of Mental Health Disorders using Emotional Virtual Agents [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/64082TESI