ACI open最新文献

{"title":"Understanding the Acceptability of Health Apps among Adolescents: A Qualitative Study","authors":"Elizabeth Chen, K. Muessig, K. Moracco","doi":"10.1055/s-0042-1758461","DOIUrl":"https://doi.org/10.1055/s-0042-1758461","url":null,"abstract":"Abstract Background  Almost all adolescents aged 13 to 17 in the United States have access to a smartphone. While studies have commonly assessed the feasibility or usability of mobile health applications (“apps”), few have examined the acceptability of apps—whether individuals would actually use these health apps in their everyday lives—among adolescent populations. Objectives  This qualitative study aims to understand how adolescents assess the acceptability of health apps in the context of their everyday lives. Methods  Nineteen adolescents in grades 7 through 9 were asked to download a health app before participating in two semi-structured interviews 2 weeks apart. Seven domains from the Theoretical Framework of Acceptability were assessed: affective attitude, burden, ethicality, intervention coherence, opportunity costs, perceived effectiveness, and self-efficacy. A Grounded Theory approach was used to analyze data. Results  The seven acceptability domains plus two additional themes, intervention expectations (what adolescents anticipated given their experiences with other apps) and peer norms (friends' beliefs and attitudes toward the intervention's health topic), were salient. Conclusion  These nine domains of acceptability are relevant to adolescents and should be assessed during health app development by app developers and health researchers to improve adolescents' acceptability perceptions and potentially increase app usage.","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"06 1","pages":"e103 - e113"},"PeriodicalIF":0.0,"publicationDate":"2022-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47961286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IT Department Demand Governance in Health Care: Reflections on a Case Series","authors":"M. Leu, Diego Ize-Ludlow, A. Landman, Hamed Abbaszadegan, Craig B. Monsen","doi":"10.1055/s-0042-1749194","DOIUrl":"https://doi.org/10.1055/s-0042-1749194","url":null,"abstract":"\u0000 Background Little is written on how best to structure IT governance in health care organizations. Governance is challenging because these groups may contain administrators, clinicians, and staff in addition to IT employees; projects may be complex and have significant impact on the teams that provide patient care.\u0000 Methods Peer organizations in health care were purposefully selected and C-suite executives were interviewed about their IT governance. Notes taken from these conversations were analyzed for guiding principles.\u0000 Results We interviewed leaders from five peer organizations. Consensus principles included: (1) minimize unwarranted variation; (2) evolve governance with the organization but independently of projects; (3) govern all clinical applications; (4) be flexible with intake, yet clear on decision-making; (5) have a tiered approach to governance; and (6) be multidisciplinary. Emerging principles included: (1) assign an IT business relationship manager to each high priority initiative, (2) have a clear escalation path to a small number of decision-makers, (3) include analytics to inform governance, (4) leverage Informatics expertise, and (5) use structured tools to streamline the process.\u0000 Conclusion While IT governance is very different across distinct health care organizations, there are some general principles that many share.","PeriodicalId":72041,"journal":{"name":"ACI open","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49208148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lessons Learned from Creating Alert Governance during an Electronic Health Record Transition","authors":"Michelle Stoffel, Sundeep Desai, Megan Laine, M. Leu, Zachary C. Liao, Jeehoon Jang, Angad P. Singh, N. Pozdeyev, P. Sutton, Adam Wright, A. A. White","doi":"10.1055/s-0042-1749196","DOIUrl":"https://doi.org/10.1055/s-0042-1749196","url":null,"abstract":"\u0000 Background Our multihospital transition to a single electronic health record (EHR) provided an opportunity to transform alert governance. Our case provides insights into the unique challenges and opportunities of creating governance during a transition to meet both implementation and future alert management needs.\u0000 ObjectivesThis case report describes the efforts of UW Medicine Information Technology Services to advance alert governance during EHR transition and highlights the opportunities to improve care quality and provider experience within a changing environment.\u0000 Methods We used a multidisciplinary approach and external evidence to define governance for provider-facing interruptive alerts. We established the context for our governance efforts with a systemic environmental scan. We used literature review and expert consultation to determine alert design and performance best practices, sought to design postimplementation evaluation tools, and engaged clinical stakeholders to help with decision-making.\u0000 Results We created alert design and implementation tools and an alert approval process, eliminating 21 unnecessary alerts prior to implementation. We developed prototype evaluation metrics and enlisted clinical owners for postimplementation optimization of 221 alerts.\u0000 Conclusion We leveraged the fluid environment of our EHR implementation to rapidly build a provider-led governance infrastructure to meet immediate transitional needs and to facilitate future alert maintenance and improvement.","PeriodicalId":72041,"journal":{"name":"ACI open","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46752803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and Integration of Mobile Health Technology in the Treatment of Orthopaedic Surgery: A Qualitative Study","authors":"C. Bruce, P. Harrison, Thomas M. Vinh, Agnita G. Manoharan, Charlie Giammattei, Caitlin Bliven, Jamie Shallcross, Aroub Khleif, Nhan Tran, Joshua R Sol, Kayla Gutierrez, B. Kash, R. Saldana, Kwan-Jun Park, F. Zheng, S. Desai, Stephen L Jones, Barach P., Roberta Schwartz","doi":"10.1055/s-0042-1754011","DOIUrl":"https://doi.org/10.1055/s-0042-1754011","url":null,"abstract":"\u0000 Background The use of mobile health (mHealth) technologies has dramatically increased in the past year. A critical component in the discussion about telehealth and mHealth technologies is the importance of integrating the voices of patients, caregivers, and their clinicians.\u0000 Methods This study was performed at a tertiary center in Houston consisting of 7 hospitals (1 academic and 6 community hospitals). The clinically integrated mHealth technology consisted of a mHealth education and monitoring platform that used patient-centered emails and text messages over a 50-day period, from prior to the orthopaedic total joint replacement surgery to posthospital discharge to provide education and health monitoring at home. Study participants included patients who were scheduled for total joint replacement surgery between July 2018 and November 2019, and their caregivers. The study involved two components: (1) focus group study (n = 15); split into two groups of participants who had not used the mHealth technology (α-testing during the design phase, prior to implementation); and (2) a content analysis of 377 free-text comments from patients who used the mHealth technology, and who responded to questions about their use of the mHealth platform (β-testing; after implementation, during the execution phase). Thematic analyses methods were used.\u0000 Results Three key themes emerged during the design phase including: (1) monitoring, bidirectional questions asking patients to respond to a question can feel invasive and/or annoying unless framed in a reciprocal, contextual-based way; (2) text messages should be used selectively for time-sensitive, critical information; and (3) information should be contained within the body of the message. Three themes emerged during the execution phase include: (1) the content should be divided into small, digestible chunks at the times that patients need that information; (2) the tone of the messages should be approachable and friendly, as opposed to detached and professional; and (3) mHealth technologies make patients calmer and more confident and less inclined to draw on hospital personnel, enabling patients to be managed by the automated program without escalating to human care. Limited, bidirectional engagement can foster interactivity and patient monitoring without becoming excessive or burdensome to health care professionals.\u0000 Conclusion The use of mHealth for patient care is likely to be more effective and used in this multihospital mHealth technology study of patients undergoing orthopaedic surgery, if they are clinically integrated with staff who can respond to escalated problems as needed, to enable better adoption, uptake, and sustainability of technology.","PeriodicalId":72041,"journal":{"name":"ACI open","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45061084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Clinical Decision Support System Design Framework for Nursing Practice","authors":"Sheng-Chieh Lu, Rebecca J L Brown, Martin Michalowski","doi":"10.1055/s-0041-1736470","DOIUrl":"https://doi.org/10.1055/s-0041-1736470","url":null,"abstract":"Abstract Background As nurses increasingly engage in decision-making for patients, a unique opportunity exists to translate research into practice using clinical decision support systems (CDSSs). While research has shown that CDSS has led to improvements in patient outcomes and nursing workflow, the success rate of CDSS implementation in nursing is low. Further, the majority of CDSS for nursing are not designed to support the care of patients with comorbidity. Objectives The aim of the study is to conceptualize an evidence-based CDSS supporting complex patient care for nursing. Methods We conceptualized the CDSS through extracting scientific findings of CDSS design and development. To describe the CDSS, we developed a conceptual framework comprising the key components of the CDSS and the relationships between the components. We instantiated the framework in the context of a hypothetical clinical case. Results We present the conceptualized CDSS with a framework comprising six interrelated components and demonstrate how each component is implemented via a hypothetical clinical case. Conclusion The proposed framework provides a common architecture for CDSS development and bridges CDSS research findings and development. Next research steps include (1) working with clinical nurses to identify their knowledge resources for a particular disease to better articulate the knowledge base needed by a CDSS, (2) develop and deploy a CDSS in practice using the framework, and (3) evaluate the CDSS in the context of nursing care.","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"05 1","pages":"e84 - e93"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41536216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Facilitating Genetics Aware Clinical Decision Support: Putting the eMERGE Infrastructure into Practice.","authors":"Casey Overby Taylor, Luke V Rasmussen, Laura J Rasmussen-Torvik, Cynthia A Prows, David A Dorr, Lipika Samal, Samuel Aronson","doi":"10.1055/s-0041-1729981","DOIUrl":"10.1055/s-0041-1729981","url":null,"abstract":"<p><p>This editorial provides context for a series of published case reports in ACI Open by summarizing activities and outputs of joint electronic health record integration and pharmacogenomics workgroups in the NIH-funded electronic Medical Records and Genomics (eMERGE) Network. A case report is a useful tool to describe the range of capabilities that an IT infrastructure or a particular technology must support. The activities we describe have informed infrastructure requirements used during eMERGE phase III, provided a venue to share experiences and ask questions among other eMERGE sites, summarized potential hazards that might be encountered for specific clinical decision support (CDS) implementation scenarios, and provided a simple framework that captured progress toward implementing CDS at eMERGE sites in a consistent format.</p>","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"05 1","pages":"e54-e58"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10621326/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49020665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Systematic Approach to Reconciling Data Quality Failures: Investigation Using Spinal Cord Injury Data","authors":"Nandini Anantharama, Wray L. Buntine, Andrew Nunn","doi":"10.1055/s-0041-1735975","DOIUrl":"https://doi.org/10.1055/s-0041-1735975","url":null,"abstract":"Abstract Background Secondary use of electronic health record's (EHR) data requires evaluation of data quality (DQ) for fitness of use. While multiple frameworks exist for quantifying DQ, there are no guidelines for the evaluation of DQ failures identified through such frameworks. Objectives This study proposes a systematic approach to evaluate DQ failures through the understanding of data provenance to support exploratory modeling in machine learning. Methods Our study is based on the EHR of spinal cord injury inpatients in a state spinal care center in Australia, admitted between 2011 and 2018 (inclusive), and aged over 17 years. DQ was measured in our prerequisite step of applying a DQ framework on the EHR data through rules that quantified DQ dimensions. DQ was measured as the percentage of values per field that meet the criteria or Krippendorff's α for agreement between variables. These failures were then assessed using semistructured interviews with purposively sampled domain experts. Results The DQ of the fields in our dataset was measured to be from 0% adherent up to 100%. Understanding the data provenance of fields with DQ failures enabled us to ascertain if each DQ failure was fatal, recoverable, or not relevant to the field's inclusion in our study. We also identify the themes of data provenance from a DQ perspective as systems, processes, and actors. Conclusion A systematic approach to understanding data provenance through the context of data generation helps in the reconciliation or repair of DQ failures and is a necessary step in the preparation of data for secondary use.","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"05 1","pages":"e94 - e103"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44532703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Policy Framework to Support Shared Decision-Making through the Use of Person-Generated Health Data","authors":"C. Petersen, M. Edmunds, D. McGraw, E. Priest, Jeffery R. L. Smith, E. Kemp, H. Campos","doi":"10.1055/s-0041-1736632","DOIUrl":"https://doi.org/10.1055/s-0041-1736632","url":null,"abstract":"Abstract Background Individuals increasingly want to access, contribute to, and share their personal health information to improve outcomes, such as through shared decision-making (SDM) with their care teams. Health systems' growing capacity to use person-generated health data (PGHD) expands the opportunities for SDM. However, SDM not only lacks organizational and information infrastructure support but also is actively undermined, despite public interest in it. Objectives This work sought to identify challenges to individual–clinician SDM and policy changes needed to mitigate barriers to SDM. Methods Two multi-stakeholder group of consumers, patients, caregivers; health services researchers; and experts in health policy, informatics, social media, and user experience used a consensus process based on Bardach's policy analysis framework to identify barriers to SDM and develop recommendations to reduce these barriers. Results Technical, legal, organizational, cultural, and logistical obstacles make data sharing difficult, thereby undermining use of PGHD and realization of SDM. Stronger privacy, security, and ethical protections, including informed consent; promoting better consumer access to their data; and easier donation of personal data for research are the most crucial policy changes needed to facilitate an environment that supports SDM. Conclusion Data protection policy lags far behind the technical capacity for third parties to share and reuse electronic information without appropriate permissions, while individuals' right to access their own health information is often restricted unnecessarily, poorly understood, and poorly communicated. Sharing of personal information in a private, secure environment in which data are shared only with individuals' knowledge and consent can be achieved through policy changes.","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"05 1","pages":"e104 - e115"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43377061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perspective: Data Governance—Making Data Great","authors":"K. Woeltje","doi":"10.1055/s-0041-1730383","DOIUrl":"https://doi.org/10.1055/s-0041-1730383","url":null,"abstract":"Health caredelivery in theUnitedStates is undergoingmassive changes. Although the pace at the local level can often be imperceptible, the overall momentum is relentless. Multiple factors are driving these changes—the rate of cost increases for care in theU.S. isunsustainable, theoutcomesofcareareworse than other countries that spend less, and a large portion of the populationdoesnothave real access toongoing care, leading to enormous societal costs. On thehealth caredelivery side, there has been a shift from stand-alone care delivery through stages of collaborative and value-driven health care toward a more accountable care/populationmanagementapproach (►Fig. 1). Politicians, policy experts, and health care administrators long recognized that changing models of health care would require significant amounts of data. This was a major factor in the founding of theOffice of theNational Coordinator forHealth InformationTechnology (ONC), and later theHealth Information Technology for Economic and Clinical Health (HITECH) Act which brought about the Meaningful Use program.1 With the increaseduseofelectronichealthrecords (EHRs), theavailability of electronic data in health care has risen dramatically. Organizations increasingly see their data as a strategic asset. Tomost effectively leverage this asset, data from diverse sources (e.g., revenue cycle, supply chain, quality measures) must be combined for analysis. The use of data from diverse sources has always occurred, but in many organizations, this was often accomplished through establishment of locally curated data collections. Unsurprisingly, organizational leaders found they could get different answers for the same question depending on which group they asked. Because data definitions can be quite nuanced, a team can become reluctant to share datawith the rest of the enterprise. There is a concern that otherswouldnot understand “mydata.” This can then lead to users on other teams to be creative in finding sources for the data they need. By acquiring data sets from diverse acquaintances across the organization, analysts may be using data with somewhat unclear provenance (often many steps away from the original sources) for important organizational reports that drive executive decision making. This can exacerbate the issue of getting different answers from different groups. Technical approaches to improving the situation include establishing a “single source of truth” for enterprise data, for example, via anenterprise datawarehouseor adata federation approach. This can helpwith some of the notions of “my data” versus “our data” in an organization, but does not in and of itself ensure that the data are well characterized and of high quality. As health care organizations struggle to use their data effectively, they realize they need an approach to addressing these issues. Whether they formally label it as such, what the organizations are grappling with is data governance.2,3","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"05 1","pages":"e80 - e83"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42466381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Researcher Perceptions of a Self-Service Online Portal to Facilitate Volunteer Recruitment into Clinical Trials","authors":"S. Emani, Y. G. Hsieh, G. Estey, H. Parker, Xiaofeng Zhang, K. Donelan, Jeanhee Chung","doi":"10.1055/s-0041-1732406","DOIUrl":"https://doi.org/10.1055/s-0041-1732406","url":null,"abstract":"Abstract Background Recruitment of volunteers is a major challenge for clinical trials. There has been increasing development and use of Internet-based portals in recruitment for clinical research. There has been little research on researcher use and perceptions of these portals. Objectives This study evaluated researcher perceptions of use of Rally, an Internet-based portal for clinical trial volunteer recruitment. Methods A cross-sectional survey was developed and implemented to understand researcher perceptions. From theoretical models of information technology use, the survey adopted items in four domains: ease of use, usefulness, facilitating conditions, and self-efficacy. The dependent variable was researchers' behavioral intention to use Rally. The survey captured characteristics of researchers such as gender, age, and role. It was implemented using the REDCap survey tool. An email invitation followed by three reminders was sent to researchers. A hierarchical regression model was applied to assess predictors of behavioral intention. Results The survey response rate was 35.6% (152 surveys received from 427 contacted researchers). In the hierarchical regression model, facilitating conditions and self-efficacy predicted behavioral intention (F (4,94) = 6.478; p <0.001). The model explained 21.6% of the variance in behavioral intention (R-square change = 21.3%, p <0.001). Conclusion Facilitating conditions and self-efficacy predicted researchers' behavioral intention to use Rally for volunteer recruitment into clinical trials. Future research should document best practices and strategies for enhancing researcher use of online portals for volunteer recruitment.","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"05 1","pages":"e59 - e66"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47552171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}