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Putzier M, Khakzad T, Dreischarf M, Thun S, Trautwein F, Taheri N. Implementation of cloud computing in the German healthcare system. NPJ Digit Med 2024; 7:12. [PMID: 38218892 PMCID: PMC10787755 DOI: 10.1038/s41746-024-01000-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 01/03/2024] [Indexed: 01/15/2024] Open
Abstract
With the advent of artificial intelligence and Big Data - projects, the necessity for a transition from analog medicine to modern-day solutions such as cloud computing becomes unavoidable. Even though this need is now common knowledge, the process is not always easy to start. Legislative changes, for example at the level of the European Union, are helping the respective healthcare systems to take the necessary steps. This article provides an overview of how a German university hospital is dealing with European data protection laws on the integration of cloud computing into everyday clinical practice. By describing our model approach, we aim to identify opportunities and possible pitfalls to sustainably influence digitization in Germany.
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Affiliation(s)
- M Putzier
- Center for Musculoskeletal Surgery, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - T Khakzad
- Center for Musculoskeletal Surgery, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - M Dreischarf
- RAYLYTIC GmBH, Petersstraße 32 - 34, 04109, Leipzig, Germany
| | - S Thun
- Core Facility Digital Medicine and Interoperability, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - F Trautwein
- RAYLYTIC GmBH, Petersstraße 32 - 34, 04109, Leipzig, Germany
| | - N Taheri
- Center for Musculoskeletal Surgery, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.
- Berlin Institute of Health, Julius Wolff Institute for Biomechanics and Musculoskeletal Regeneration, Charité-Universitätsmedizin Berlin, Augustenburger Pl. 1, 13353, Berlin, Germany.
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Sung M, He J, Zhou Q, Chen Y, Ji JS, Chen H, Li Z. Using an Integrated Framework to Investigate the Facilitators and Barriers of Health Information Technology Implementation in Noncommunicable Disease Management: Systematic Review. J Med Internet Res 2022; 24:e37338. [PMID: 35857364 PMCID: PMC9350822 DOI: 10.2196/37338] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 05/25/2022] [Accepted: 06/27/2022] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND Noncommunicable disease (NCD) management is critical for reducing attributable health burdens. Although health information technology (HIT) is a crucial strategy to improve chronic disease management, many health care systems have failed in implementing HIT. There has been a lack of research on the implementation process of HIT for chronic disease management. OBJECTIVE We aimed to identify the barriers and facilitators of HIT implementation, analyze how these factors influence the implementation process, and identify key areas for future action. We will develop a framework for understanding implementation determinants to synthesize available evidence. METHODS We conducted a systematic review to understand the barriers and facilitators of the implementation process. We searched MEDLINE, Cochrane, Embase, Scopus, and CINAHL for studies published between database inception and May 5, 2022. Original studies involving HIT-related interventions for NCD management published in peer-reviewed journals were included. Studies that did not discuss relevant outcome measures or did not have direct contact with or observation of stakeholders were excluded. The analysis was conducted in 2 parts. In part 1, we analyzed how the intrinsic attributes of HIT interventions affect the successfulness of implementation by using the intervention domain of the Consolidated Framework for Implementation Research (CFIR). In part 2, we focused on the extrinsic factors of HIT using an integrated framework, which was developed based on the CFIR and the levels of change framework by Ferlie and Shortell. RESULTS We identified 51 papers with qualitative, mixed-method, and cross-sectional methodologies. Included studies were heterogeneous regarding disease populations and HIT interventions. In part 1, having a relative advantage over existing health care systems was the most prominent intrinsic facilitator (eg, convenience, improvement in quality of care, and increase in access). Poor usability was the most noted intrinsic barrier of HIT. In part 2, we mapped the various factors of implementation to the integrated framework (the coordinates are shown as level of change-CFIR). The key barriers to the extrinsic factors of HIT included health literacy and lack of digital skills (individual-characteristics of individuals). The key facilitators included physicians' suggestions, cooperation (interpersonal-process), integration into a workflow, and adequate management of data (organizational-inner setting). The importance of health data security was identified. Self-efficacy issues of patients and organizational readiness for implementation were highlighted. CONCLUSIONS Internal factors of HIT and external human factors of implementation interplay in HIT implementation for chronic disease management. Strategies for improvement include ensuring HIT has a relative advantage over existing health care; tackling usability issues; and addressing underlying socioeconomic, interpersonal, and organizational conditions. Further research should focus on studying various stakeholders, such as service providers and administrative workforces; various disease populations, such as those with obesity and mental diseases; and various countries, including low- and middle-income countries.
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Affiliation(s)
- Meekang Sung
- College of Pharmacy, Seoul National University, Seoul, Republic of Korea
| | - Jinyu He
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Qi Zhou
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Yaolong Chen
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - John S Ji
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Haotian Chen
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Zhihui Li
- Vanke School of Public Health, Tsinghua University, Beijing, China.,Institute for Healthy China, Tsinghua Universtiy, Beijing, China
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Distributed application of guideline-based decision support through mobile devices: Implementation and evaluation. Artif Intell Med 2022; 129:102324. [DOI: 10.1016/j.artmed.2022.102324] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 05/11/2022] [Accepted: 05/13/2022] [Indexed: 11/18/2022]
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Vest JR, Freedman S, Unruh MA, Bako AT, Simon K. Strategic use of health information exchange and market share, payer mix, and operating margins. Health Care Manage Rev 2022; 47:28-36. [PMID: 33298801 PMCID: PMC10445427 DOI: 10.1097/hmr.0000000000000293] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND Health information exchange (HIE) capabilities are tied to health care organizations' strategic and business goals. As a technology that connects information from different organizations, HIE may be a source of competitive advantage and a path to improvements in performance. PURPOSE The aim of the study was to identify the impact of hospitals' use of HIE capabilities on outcomes that may be sensitive to changes in various contracting arrangements and referral patterns arising from improved connectivity. METHODOLOGY Using a panel of community hospitals in nine states, we examined the association between the number of different data types the hospital could exchange via HIE and changes in market share, payer mix, and operating margin (2010-2014). Regression models that controlled for the number of different data types shared intraorganizationally and other time-varying factors and included both hospital and time fixed effects were used for adjusted estimates of the relationships between changes in HIE capabilities and outcomes. RESULTS Increasing HIE capability was associated with a 13 percentage point increase in a hospital's discharges that were covered by commercial insurers or Medicare (i.e., payer mix). Conversely, increasing intraorganizational information sharing was associated with a 9.6 percentage point decrease in the percentage of discharges covered by commercial insurers or Medicare. Increasing HIE capability or intraorganizational information sharing was not associated with increased market share nor with operating margin. CONCLUSIONS Improving information sharing with external organizations may be an approach to support strategic business goals. PRACTICE IMPLICATIONS Organizations may be served by identifying ways to leverage HIE instead of focusing on intraorganizational exchange capabilities.
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Affiliation(s)
- Joshua R Vest
- Department of Health Policy & Management, Indiana University Richard M Fairbanks School of Public Health – Indianapolis, Scientist, Regenstrief Institute
| | - Seth Freedman
- Indiana University O′Neill School of Public & Environmental Affairs
| | | | - Abdulaziz T Bako
- Department of Health Policy & Management, Indiana University Richard M Fairbanks School of Public Health - Indianapolis
| | - Kosali Simon
- Indiana University O′Neill School of Public & Environmental Affairs
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Arzt NH, Chertcoff D, Nicolary S, Suralik M, Berry M. Immunization calculation engine: An open source immunization evaluation and forecasting system. Learn Health Syst 2022; 6:e10285. [PMID: 35036556 PMCID: PMC8753301 DOI: 10.1002/lrh2.10285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 06/08/2021] [Accepted: 06/23/2021] [Indexed: 11/10/2022] Open
Abstract
INTRODUCTION The immunization calculation engine (ICE) is a free, open-source immunization forecasting evaluation and software system whose default immunization schedule supports all routine childhood, adolescent, and adult immunizations based on the recommendations of the Advisory Committee on Immunization Practices (ACIP). ICE utilizes its immunization rules and patient data to evaluate and return the validity of each immunization in the patient's history along with one or more evaluation reasons. It also returns a recommendation for each vaccine group along with one or more recommendation reasons. METHODS In January 2020, ICE was first released as a Docker image along with the traditional zip archive file which had been used up to that point. Docker enables software providers to easily distribute their software so that it can be run "out of the box" in the user's local environment. Software running in Docker containers drastically reduces the complexity of software distribution and set up. RESULTS Clinical systems of many types use ICE. The project began within the public health arena as a feature of Immunization Information Systems (IIS), but electronic health records (EHR) and personal health records (PHR) have also deployed ICE. While it is not possible to identify the specific impact of ICE on clinical care without additional research, it should be pointed out that once deployed within an IIS, EHR, or PHR the display of ICE results is performed for every patient viewed by a user and often for every patient appearing on a report. In a typical month, thousands if not millions of evaluations and forecasts are performed by ICE and displayed to the users. CONCLUSIONS The ICE Project believes in minimizing the barriers to installing and using ICE anywhere. To that end, there is no registration required to download the source code or runtime code for the ICE service and its default rule. Similarly, the Project created a Docker image of ICE to facilitate easy and seamless implementation.
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Churi P, Pawar AV, Abdulmuhsin AA. Perception of privacy issues and awareness in health-care knowledge management systems: empirical study in Indian health-care context. INTERNATIONAL JOURNAL OF ORGANIZATIONAL ANALYSIS 2021. [DOI: 10.1108/ijoa-11-2020-2486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Purpose
Focusing on the Indian context, with the increase in the amount of data and its analysis in health-care knowledge management (KM), the privacy concerns rise which results in loss of trust of an individual in e-health-care systems. Privacy issues in health care, specific to India, are caused by prevalent complacency, culture, politics, budget limitations, large population and infrastructures. Because of these factors, data security requires a backseat that allows easy access to confidential information. Furthermore, the prevalent culture affects health-care disclosure in India. In many cultures, disclosing sensitive personal health-care data is considered ill mannered. This leads to discrepancies in the recorded health-care data and a decrease in the level of treatment meted out. The results and statistics of treatments given do not match the records because of inaccurate data reporting. With the significant rise in the analysis and use of technology in health-care KM systems, it is important to understand the perception of KM in terms of its use and awareness about data sharing in the KM system. The purpose of the paper is to measure the perception of privacy issues in the context of Indian healthcare management systems.
Design/methodology/approach
To measure the perception of the use of the KM system, a set of 20 questions was circulated with a sample size of 337 which includes health-care researchers, doctors, practitioners and patients. The questions focused upon the use, share the sensitive health data in the KM platform. All the demographic information such as age, sex, religion, occupation is recorded. The privacy of the individual is maintained while circulating the questionnaire. The usage of health KM system and its privacy is measured through means and t-test.
Findings
The results of the t-test were found positive. This research study finds that the privacy factor is important among the Indians to share the information with the KM repository. It is also found that medical practitioners or data custodians are not much serious about sensitive data is being stored for analysis. From the statistical perception of usage of KM and its privacy, new architecture and privacy guidelines were suggested which can be considered in future research.
Research limitations/implications
From the literature review, the questionnaire has developed which can help policymakers and hospital administrators collect information about KM processes in health-care organizations, and this can result in higher performance of health organizations. The privacy factor can also be included in typical health KM architecture ensure that while knowledge acquisition process, privacy of individual or organization can be maintained.
Social implications
KM enhances the value of corporations and business industries through knowledge production, distribution and provides reliable access to the knowledge resources. KM in health care can comprise a confluence of formal methodologies and techniques to facilitate the creation, identification, acquisition, development, preservation, dissemination and finally the utilization of the various facets of a health-care enterprise’s knowledge assets. According to IBM Global executive report in the year 2012, the entire health-care system has changed from diseases-centric to patient-centric. India is emerging in terms of revenue and employment in the health-care field. The advances of information and communication technology help the health-care sector streamline for data structure and access and health analytics.
Originality/value
In India, the KM is frequently used in health-care industries majorly by health-care practitioners and professionals. As health-care data and knowledge are considered to be sensitive, the privacy of an individual while using the data cannot be compromised. The proposed empirical work will provide a solution in determining the main barriers of implementing privacy policies that need to be solved first and to ensure effective implementation of KM in the health care of India.
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Orenstein EW, Yun K, Warden C, Westerhaus MJ, Mirth MG, Karavite D, Mamo B, Sundar K, Michel JJ. Development and dissemination of clinical decision support across institutions: standardization and sharing of refugee health screening modules. J Am Med Inform Assoc 2021; 26:1515-1524. [PMID: 31373356 DOI: 10.1093/jamia/ocz124] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2019] [Revised: 06/17/2019] [Accepted: 06/25/2019] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVES We developed and piloted a process for sharing guideline-based clinical decision support (CDS) across institutions, using health screening of newly arrived refugees as a case example. MATERIALS AND METHODS We developed CDS to support care of newly arrived refugees through a systematic process including a needs assessment, a 2-phase cognitive task analysis, structured preimplementation testing, local implementation, and staged dissemination. We sought consensus from prospective users on CDS scope, applicable content, basic supported workflows, and final structure. We documented processes and developed sharable artifacts from each phase of development. We publically shared CDS artifacts through online dissemination platforms. We collected feedback and implementation data from implementation sites. RESULTS Responses from 19 organizations demonstrated a need for improved CDS for newly arrived refugee patients. A guided multicenter workflow analysis identified 2 main workflows used by organizations that would need to be supported by shared CDS. We developed CDS through an iterative design process, which was successfully disseminated to other sites using online dissemination repositories. Implementation sites had a small-to-modest analyst time commitment but reported a good match between CDS and workflow. CONCLUSION Sharing of CDS requires overcoming technical and workflow barriers. We used a guided multicenter workflow analysis and online dissemination repositories to create flexible CDS that has been adapted at 3 sites. Organizations looking to develop sharable CDS should consider evaluating the workflows of multiple institutions and collecting feedback on scope, design, and content in order to make a more generalizable product.
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Affiliation(s)
- Evan W Orenstein
- Department of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, USA.,Division of Hospital Medicine, Children's Healthcare of Atlanta, Atlanta, Georgia, USA
| | - Katherine Yun
- PolicyLab, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Clara Warden
- PolicyLab, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Michael J Westerhaus
- Department of Medicine, HealthPartners Center for International Health, Minneapolis, Minnesota, USA
| | - Morgan G Mirth
- PolicyLab, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Division of Emergency Medicine, Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Dean Karavite
- Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Blain Mamo
- Minnesota Department of Public Health, Minneapolis, Minnesota, USA
| | - Kavya Sundar
- PolicyLab, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Jeremy J Michel
- Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
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Hoffman JM, Flynn AJ, Juskewitch JE, Freimuth RR. Biomedical Data Science and Informatics Challenges to Implementing Pharmacogenomics with Electronic Health Records. Annu Rev Biomed Data Sci 2020. [DOI: 10.1146/annurev-biodatasci-020320-093614] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Pharmacogenomic information must be incorporated into electronic health records (EHRs) with clinical decision support in order to fully realize its potential to improve drug therapy. Supported by various clinical knowledge resources, pharmacogenomic workflows have been implemented in several healthcare systems. Little standardization exists across these efforts, however, which limits scalability both within and across clinical sites. Limitations in information standards, knowledge management, and the capabilities of modern EHRs remain challenges for the widespread use of pharmacogenomics in the clinic, but ongoing efforts are addressing these challenges. Although much work remains to use pharmacogenomic information more effectively within clinical systems, the experiences of pioneering sites and lessons learned from those programs may be instructive for other clinical areas beyond genomics. We present a vision of what can be achieved as informatics and data science converge to enable further adoption of pharmacogenomics in the clinic.
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Affiliation(s)
- James M. Hoffman
- Department of Pharmaceutical Sciences and the Office of Quality and Patient Care, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - Allen J. Flynn
- Department of Learning Health Sciences, Medical School, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Justin E. Juskewitch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota 55905, USA
| | - Robert R. Freimuth
- Division of Digital Health Sciences, Department of Health Sciences Research, Center for Individualized Medicine, and Information and Knowledge Management, Mayo Clinic, Rochester, Minnesota 55905, USA
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Michel JJ, Erinoff E, Tsou AY. More Guidelines than states: variations in U.S. lead screening and management guidance and impacts on shareable CDS development. BMC Public Health 2020; 20:127. [PMID: 31996264 PMCID: PMC6990572 DOI: 10.1186/s12889-020-8225-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Accepted: 01/15/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Pediatric lead exposure in the United States (U.S.) remains a preventable public health crisis. Shareable electronic clinical decision support (CDS) could improve lead screening and management. However, discrepancies between federal, state and local recommendations could present significant challenges for implementation. METHODS We identified publically available guidance on lead screening and management. We extracted definitions for elevated lead and recommendations for screening, follow-up, reporting, and management. We compared thresholds and level of obligation for management actions. Finally, we assessed the feasibility of development of shareable CDS. RESULTS We identified 54 guidance sources. States offered different definitions of elevated lead, and recommendations for screening, reporting, follow-up and management. Only 37 of 48 states providing guidance used the Center for Disease Control (CDC) definition for elevated lead. There were 17 distinct management actions. Guidance sources indicated an average of 5.5 management actions, but offered different criteria and levels of obligation for these actions. Despite differences, the recommendations were well-structured, actionable, and encodable, indicating shareable CDS is feasible. CONCLUSION Current variability across guidance poses challenges for clinicians. Developing shareable CDS is feasible and could improve pediatric lead screening and management. Shareable CDS would need to account for local variability in guidance.
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Affiliation(s)
- Jeremy J Michel
- Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia, 2716 South Street, Philadelphia, PA, 19146, USA.
- Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, 19146, USA.
- ECRI Institute Center for Clinical Evidence and Guidelines, Plymouth Meeting, PA, 19462, USA.
| | - Eileen Erinoff
- ECRI Institute Center for Clinical Evidence and Guidelines, Plymouth Meeting, PA, 19462, USA
| | - Amy Y Tsou
- ECRI Institute Center for Clinical Evidence and Guidelines, Plymouth Meeting, PA, 19462, USA
- Michael J Crescenz Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA
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Gao F, Sunyaev A. Context matters: A review of the determinant factors in the decision to adopt cloud computing in healthcare. INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT 2019. [DOI: 10.1016/j.ijinfomgt.2019.02.002] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Abstract
Sepsis is an inflammatory response triggered by infection, with a high in-hospital mortality rate. Early recognition and treatment can reverse the inflammatory response, with evidence of improved patient outcomes. One challenge clinicians face is identifying the inflammatory syndrome against the background of the patient's infectious illness and comorbidities. An approach to this problem is implementation of computerized early warning tools for sepsis. This multicenter retrospective study sought to determine clinimetric performance of a cloud-based computerized sepsis clinical decision support system (CDS), understand the epidemiology of sepsis, and identify opportunities for quality improvement. Data encompassed 6200 adult hospitalizations from 2012 through 2013. Of 13% patients screened-in, 51% were already suspected to have an infection when the system activated. This study focused on a patient cohort screened-in before infection was suspected; median time from arrival to CDS activation was 3.5 hours, and system activation to diagnostic collect was another 8.6 hours.
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12
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Patients Decision Aid System Based on FHIR Profiles. J Med Syst 2018; 42:166. [PMID: 30066031 DOI: 10.1007/s10916-018-1016-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Accepted: 07/11/2018] [Indexed: 10/28/2022]
Abstract
Patients are becoming more and more involved in clinical decision-making process. Several factors support this process. Advances in omics allows individualization of diagnosis and treatment. Patient awareness and easy availability of data on the Internet allows patients to become informed decision makers when it comes even to disease management. Mass media emphasize the issue of medical errors, making patients demanding for quality in medical care. In some healthcare settings, patents face a problem of interpreting medical data and making decisions on treatment tactics without having a doctor, who could potentially support them. Delegating this task to a Patient Decision Aide system can add automatically generated recommendations to result reports without adding significant workload on the doctors, increase patients' motivation and support their decisions. We have implemented a patient decision aid system based on the productions rules, which: Collects data from available sources; Automatically analyses and interprets laboratory test results; Recommends running additional tests for a more precise diagnostic; Delivers automatically generated reports to doctors and patients in a natural language. To achieve semantic interoperability with other systems we have implemented a FHIR engine. The knowledge base has been organized as a graph structure. The application is structured as a set of lightly coupled services, which implement the logic of the decision support system. In total, we have modelled 365 nodes of test components, 5084 nodes of inference rules, 49932 connections and 3072 blocks of text for medical certificates. The findings of the research provide a deep understanding of how the semantically interoperable clinical decision support systems are implemented. Advances in notification the patients with the elements of patient decision aid is important for clinical data management, and for patients' empowerment and protection. We suppose that the system empowering patients in such way can play a meaningful role in helping patients to make informed decisions during the process of diagnostics and treatment.
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Granja C, Janssen W, Johansen MA. Factors Determining the Success and Failure of eHealth Interventions: Systematic Review of the Literature. J Med Internet Res 2018; 20:e10235. [PMID: 29716883 PMCID: PMC5954232 DOI: 10.2196/10235] [Citation(s) in RCA: 276] [Impact Index Per Article: 46.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Accepted: 04/09/2018] [Indexed: 01/18/2023] Open
Abstract
Background eHealth has an enormous potential to improve healthcare cost, effectiveness, and quality of care. However, there seems to be a gap between the foreseen benefits of research and clinical reality. Objective Our objective was to systematically review the factors influencing the outcome of eHealth interventions in terms of success and failure. Methods We searched the PubMed database for original peer-reviewed studies on implemented eHealth tools that reported on the factors for the success or failure, or both, of the intervention. We conducted the systematic review by following the patient, intervention, comparison, and outcome framework, with 2 of the authors independently reviewing the abstract and full text of the articles. We collected data using standardized forms that reflected the categorization model used in the qualitative analysis of the outcomes reported in the included articles. Results Among the 903 identified articles, a total of 221 studies complied with the inclusion criteria. The studies were heterogeneous by country, type of eHealth intervention, method of implementation, and reporting perspectives. The article frequency analysis did not show a significant discrepancy between the number of reports on failure (392/844, 46.5%) and on success (452/844, 53.6%). The qualitative analysis identified 27 categories that represented the factors for success or failure of eHealth interventions. A quantitative analysis of the results revealed the category quality of healthcare (n=55) as the most mentioned as contributing to the success of eHealth interventions, and the category costs (n=42) as the most mentioned as contributing to failure. For the category with the highest unique article frequency, workflow (n=51), we conducted a full-text review. The analysis of the 23 articles that met the inclusion criteria identified 6 barriers related to workflow: workload (n=12), role definition (n=7), undermining of face-to-face communication (n=6), workflow disruption (n=6), alignment with clinical processes (n=2), and staff turnover (n=1). Conclusions The reviewed literature suggested that, to increase the likelihood of success of eHealth interventions, future research must ensure a positive impact in the quality of care, with particular attention given to improved diagnosis, clinical management, and patient-centered care. There is a critical need to perform in-depth studies of the workflow(s) that the intervention will support and to perceive the clinical processes involved.
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Affiliation(s)
- Conceição Granja
- Future Journal, Norwegian Centre for E-health Research, Tromsø, Norway
| | - Wouter Janssen
- Telemedicine and E-health Research Group, University of Tromsø-The Artic University of Norway, Tromsø, Norway
| | - Monika Alise Johansen
- Future Journal, Norwegian Centre for E-health Research, Tromsø, Norway.,Telemedicine and E-health Research Group, University of Tromsø-The Artic University of Norway, Tromsø, Norway
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Wright A, Ai A, Ash J, Wiesen JF, Hickman TTT, Aaron S, McEvoy D, Borkowsky S, Dissanayake PI, Embi P, Galanter W, Harper J, Kassakian SZ, Ramoni R, Schreiber R, Sirajuddin A, Bates DW, Sittig DF. Clinical decision support alert malfunctions: analysis and empirically derived taxonomy. J Am Med Inform Assoc 2018; 25:496-506. [PMID: 29045651 PMCID: PMC6019061 DOI: 10.1093/jamia/ocx106] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2017] [Accepted: 09/02/2017] [Indexed: 02/05/2023] Open
Abstract
Objective To develop an empirically derived taxonomy of clinical decision support (CDS) alert malfunctions. Materials and Methods We identified CDS alert malfunctions using a mix of qualitative and quantitative methods: (1) site visits with interviews of chief medical informatics officers, CDS developers, clinical leaders, and CDS end users; (2) surveys of chief medical informatics officers; (3) analysis of CDS firing rates; and (4) analysis of CDS overrides. We used a multi-round, manual, iterative card sort to develop a multi-axial, empirically derived taxonomy of CDS malfunctions. Results We analyzed 68 CDS alert malfunction cases from 14 sites across the United States with diverse electronic health record systems. Four primary axes emerged: the cause of the malfunction, its mode of discovery, when it began, and how it affected rule firing. Build errors, conceptualization errors, and the introduction of new concepts or terms were the most frequent causes. User reports were the predominant mode of discovery. Many malfunctions within our database caused rules to fire for patients for whom they should not have (false positives), but the reverse (false negatives) was also common. Discussion Across organizations and electronic health record systems, similar malfunction patterns recurred. Challenges included updates to code sets and values, software issues at the time of system upgrades, difficulties with migration of CDS content between computing environments, and the challenge of correctly conceptualizing and building CDS. Conclusion CDS alert malfunctions are frequent. The empirically derived taxonomy formalizes the common recurring issues that cause these malfunctions, helping CDS developers anticipate and prevent CDS malfunctions before they occur or detect and resolve them expediently.
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Affiliation(s)
- Adam Wright
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.,Department of Medicine, Harvard Medical School, Boston, MA, USA.,Clinical and Quality Analysis, Partners Healthcare, Somerville, MA, USA
| | - Angela Ai
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Joan Ash
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR, USA
| | - Jane F Wiesen
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR, USA
| | | | - Skye Aaron
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Dustin McEvoy
- Clinical and Quality Analysis, Partners Healthcare, Somerville, MA, USA
| | - Shane Borkowsky
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | | | - Peter Embi
- Regenstrief Institute, Indianapolis, IN, USA
| | - William Galanter
- Department of Medicine, Pharmacy Practices, and Pharmacy Systems, Outcomes and Policy, University of Illinois at Chicago, Chicago, IL, USA
| | - Jeremy Harper
- Department of Biomedical Informatics, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Steve Z Kassakian
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR, USA
| | - Rachel Ramoni
- Department of Oral Health Policy and Epidemiology, Harvard School of Dental Medicine, Boston, MA, USA.,Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Richard Schreiber
- Department of Medicine and Information Technology, Holy Spirit Hospital - A Geisinger Affiliate, Camp Hill, PA, USA
| | - Anwar Sirajuddin
- Department of Medical Informatics, Memorial Hermann Health System, Houston, TX, USA
| | - David W Bates
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.,Department of Medicine, Harvard Medical School, Boston, MA, USA.,Clinical and Quality Analysis, Partners Healthcare, Somerville, MA, USA
| | - Dean F Sittig
- Department of Biomedical Informatics, University of Texas Health Science Center at Houston, TX, USA
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Quaglini S, Sacchi L, Lanzola G, Viani N. Personalization and Patient Involvement in Decision Support Systems: Current Trends. Yearb Med Inform 2017; 10:106-18. [PMID: 26293857 DOI: 10.15265/iy-2015-015] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
OBJECTIVES This survey aims at highlighting the latest trends (2012-2014) on the development, use, and evaluation of Information and Communication Technologies (ICT) based decision support systems (DSSs) in medicine, with a particular focus on patient-centered and personalized care. METHODS We considered papers published on scientific journals, by querying PubMed and Web of ScienceTM. Included studies focused on the implementation or evaluation of ICT-based tools used in clinical practice. A separate search was performed on computerized physician order entry systems (CPOEs), since they are increasingly embedding patient-tailored decision support. RESULTS We found 73 papers on DSSs (53 on specific ICT tools) and 72 papers on CPOEs. Although decision support through the delivery of recommendations is frequent (28/53 papers), our review highlighted also DSSs only based on efficient information presentation (25/53). Patient participation in making decisions is still limited (9/53), and mostly focused on risk communication. The most represented medical area is cancer (12%). Policy makers are beginning to be included among stakeholders (6/73), but integration with hospital information systems is still low. Concerning knowledge representation/management issues, we identified a trend towards building inference engines on top of standard data models. Most of the tools (57%) underwent a formal assessment study, even if half of them aimed at evaluating usability and not effectiveness. CONCLUSIONS Overall, we have noticed interesting evolutions of medical DSSs to improve communication with the patient, consider the economic and organizational impact, and use standard models for knowledge representation. However, systems focusing on patient-centered care still do not seem to be available at large.
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Affiliation(s)
- S Quaglini
- Silvana Quaglini, Department of Electrical, Computer, and Biomedical Engineering, University of Pavia, Via Ferrata 5, 27100 Pavia, Italy, Tel: +39 0382 985058, Fax: +39 0382 985060, E-mail:
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Zolhavarieh S, Parry D, Bai Q. Issues Associated With the Use of Semantic Web Technology in Knowledge Acquisition for Clinical Decision Support Systems: Systematic Review of the Literature. JMIR Med Inform 2017; 5:e18. [PMID: 28679487 PMCID: PMC5517823 DOI: 10.2196/medinform.6169] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2016] [Revised: 12/19/2016] [Accepted: 03/28/2017] [Indexed: 11/17/2022] Open
Abstract
Background Knowledge-based clinical decision support system (KB-CDSS) can be used to help practitioners make diagnostic decisions. KB-CDSS may use clinical knowledge obtained from a wide variety of sources to make decisions. However, knowledge acquisition is one of the well-known bottlenecks in KB-CDSSs, partly because of the enormous growth in health-related knowledge available and the difficulty in assessing the quality of this knowledge as well as identifying the “best” knowledge to use. This bottleneck not only means that lower-quality knowledge is being used, but also that KB-CDSSs are difficult to develop for areas where expert knowledge may be limited or unavailable. Recent methods have been developed by utilizing Semantic Web (SW) technologies in order to automatically discover relevant knowledge from knowledge sources. Objective The two main objectives of this study were to (1) identify and categorize knowledge acquisition issues that have been addressed through using SW technologies and (2) highlight the role of SW for acquiring knowledge used in the KB-CDSS. Methods We conducted a systematic review of the recent work related to knowledge acquisition MeM for clinical decision support systems published in scientific journals. In this regard, we used the keyword search technique to extract relevant papers. Results The retrieved papers were categorized based on two main issues: (1) format and data heterogeneity and (2) lack of semantic analysis. Most existing approaches will be discussed under these categories. A total of 27 papers were reviewed in this study. Conclusions The potential for using SW technology in KB-CDSS has only been considered to a minor extent so far despite its promise. This review identifies some questions and issues regarding use of SW technology for extracting relevant knowledge for a KB-CDSS.
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Affiliation(s)
- Seyedjamal Zolhavarieh
- Department of Computer Science, Auckland University of Technology, Auckland, New Zealand
| | - David Parry
- Department of Computer Science, Auckland University of Technology, Auckland, New Zealand
| | - Quan Bai
- Department of Computer Science, Auckland University of Technology, Auckland, New Zealand
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Amland RC, Haley JM, Lyons JJ. A Multidisciplinary Sepsis Program Enabled by a Two-Stage Clinical Decision Support System: Factors That Influence Patient Outcomes. Am J Med Qual 2016; 31:501-508. [PMID: 26491116 PMCID: PMC5098699 DOI: 10.1177/1062860615606801] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Sepsis is an inflammatory response triggered by infection, with risk of in-hospital mortality fueled by disease progression. Early recognition and intervention by multidisciplinary sepsis programs may reverse the inflammatory response among at-risk patient populations, potentially improving outcomes. This retrospective study of a sepsis program enabled by a 2-stage sepsis Clinical Decision Support (CDS) system sought to evaluate the program's impact, identify early indicators that may influence outcomes, and uncover opportunities for quality improvement. Data encompassed 16 527 adult hospitalizations from 2014 and 2015. Of 2108 non-intensive care unit patients screened-in by sepsis CDS, 97% patients were stratified by 177 providers. Risk of adverse outcome improved 30% from baseline to year end, with gains materializing and stabilizing at month 7 after sepsis program go-live. Early indicators likely to influence outcomes include patient age, recent hospitalization, electrolyte abnormalities, hypovolemic shock, hypoxemia, patient location when sepsis CDS activated, and specific alert patterns.
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Arzt NH. Clinical Decision Support for Immunizations (CDSi): A Comprehensive, Collaborative Strategy. BIOMEDICAL INFORMATICS INSIGHTS 2016; 8:1-13. [PMID: 27789956 PMCID: PMC5072461 DOI: 10.4137/bii.s40204] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/10/2016] [Revised: 07/26/2016] [Accepted: 08/04/2016] [Indexed: 11/20/2022]
Abstract
This article focuses on the requirements and current developments in clinical decision support technologies for immunizations (CDSi) in both the public health and clinical communities, with an emphasis on shareable solutions. The requirements of the Electronic Health Record Incentive Programs have raised some unique challenges for the clinical community, including vocabulary mapping, update of changing guidelines, single immunization schedule, and scalability. This article discusses new, collaborative approaches whose long-term goal is to make CDSi more sustainable for both the public and private sectors.
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Affiliation(s)
- Noam H Arzt
- President, HLN Consulting, LLC, Palm Desert, CA, USA
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Middleton B, Sittig DF, Wright A. Clinical Decision Support: a 25 Year Retrospective and a 25 Year Vision. Yearb Med Inform 2016; Suppl 1:S103-16. [PMID: 27488402 DOI: 10.15265/iys-2016-s034] [Citation(s) in RCA: 92] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
OBJECTIVE The objective of this review is to summarize the state of the art of clinical decision support (CDS) circa 1990, review progress in the 25 year interval from that time, and provide a vision of what CDS might look like 25 years hence, or circa 2040. METHOD Informal review of the medical literature with iterative review and discussion among the authors to arrive at six axes (data, knowledge, inference, architecture and technology, implementation and integration, and users) to frame the review and discussion of selected barriers and facilitators to the effective use of CDS. RESULT In each of the six axes, significant progress has been made. Key advances in structuring and encoding standardized data with an increased availability of data, development of knowledge bases for CDS, and improvement of capabilities to share knowledge artifacts, explosion of methods analyzing and inferring from clinical data, evolution of information technologies and architectures to facilitate the broad application of CDS, improvement of methods to implement CDS and integrate CDS into the clinical workflow, and increasing sophistication of the end-user, all have played a role in improving the effective use of CDS in healthcare delivery. CONCLUSION CDS has evolved dramatically over the past 25 years and will likely evolve just as dramatically or more so over the next 25 years. Increasingly, the clinical encounter between a clinician and a patient will be supported by a wide variety of cognitive aides to support diagnosis, treatment, care-coordination, surveillance and prevention, and health maintenance or wellness.
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Affiliation(s)
- B Middleton
- Blackford Middleton, Cell: +1 617 335 7098, E-Mail:
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20
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Marco-Ruiz L, Pedrinaci C, Maldonado J, Panziera L, Chen R, Bellika JG. Publication, discovery and interoperability of Clinical Decision Support Systems: A Linked Data approach. J Biomed Inform 2016; 62:243-64. [DOI: 10.1016/j.jbi.2016.07.011] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2016] [Revised: 07/05/2016] [Accepted: 07/07/2016] [Indexed: 11/28/2022]
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Knowledge-Based Personal Health System to empower outpatients of diabetes mellitus by means of P4 Medicine. Methods Mol Biol 2016; 1246:237-57. [PMID: 25417090 DOI: 10.1007/978-1-4939-1985-7_15] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
Abstract
Diabetes Mellitus (DM) affects hundreds of millions of people worldwide and it imposes a large economic burden on healthcare systems. We present a web patient empowering system (PHSP4) that ensures continuous monitoring and assessment of the health state of patients with DM (type I and II). PHSP4 is a Knowledge-Based Personal Health System (PHS) which follows the trend of P4 Medicine (Personalized, Predictive, Preventive, and Participative). It provides messages to outpatients and clinicians about the achievement of objectives, follow-up, and treatments adjusted to the patient condition. Additionally, it calculates a four-component risk vector of the associated pathologies with DM: Nephropathy, Diabetic retinopathy, Diabetic foot, and Cardiovascular event. The core of the system is a Rule-Based System which Knowledge Base is composed by a set of rules implementing the recommendations of the American Diabetes Association (ADA) (American Diabetes Association: http://www.diabetes.org/ ) clinical guideline. The PHSP4 is designed to be standardized and to facilitate its interoperability by means of terminologies (SNOMED-CT [The International Health Terminology Standards Development Organization: http://www.ihtsdo.org/snomed-ct/ ] and UCUM [The Unified Code for Units of Measure: http://unitsofmeasure.org/ ]), standardized clinical documents (HL7 CDA R2 [Health Level Seven International: http://www.hl7.org/index.cfm ]) for managing Electronic Health Record (EHR). We have evaluated the functionality of the system and its users' acceptance of the system using simulated and real data, and a questionnaire based in the Technology Acceptance Model methodology (TAM). Finally results show the reliability of the system and the high acceptance of clinicians.
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22
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Use of a remote clinical decision support service for a multicenter trial to implement prediction rules for children with minor blunt head trauma. Int J Med Inform 2016; 87:101-10. [DOI: 10.1016/j.ijmedinf.2015.12.002] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2015] [Revised: 11/25/2015] [Accepted: 12/02/2015] [Indexed: 11/21/2022]
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Amland RC, Lyons JJ, Greene TL, Haley JM. A two-stage clinical decision support system for early recognition and stratification of patients with sepsis: an observational cohort study. JRSM Open 2015; 6:2054270415609004. [PMID: 26688744 PMCID: PMC4601128 DOI: 10.1177/2054270415609004] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
OBJECTIVE To examine the diagnostic accuracy of a two-stage clinical decision support system for early recognition and stratification of patients with sepsis. DESIGN Observational cohort study employing a two-stage sepsis clinical decision support to recognise and stratify patients with sepsis. The stage one component was comprised of a cloud-based clinical decision support with 24/7 surveillance to detect patients at risk of sepsis. The cloud-based clinical decision support delivered notifications to the patients' designated nurse, who then electronically contacted a provider. The second stage component comprised a sepsis screening and stratification form integrated into the patient electronic health record, essentially an evidence-based decision aid, used by providers to assess patients at bedside. SETTING Urban, 284 acute bed community hospital in the USA; 16,000 hospitalisations annually. PARTICIPANTS Data on 2620 adult patients were collected retrospectively in 2014 after the clinical decision support was implemented. MAIN OUTCOME MEASURE 'Suspected infection' was the established gold standard to assess clinical decision support clinimetric performance. RESULTS A sepsis alert activated on 417 (16%) of 2620 adult patients hospitalised. Applying 'suspected infection' as standard, the patient population characteristics showed 72% sensitivity and 73% positive predictive value. A postalert screening conducted by providers at bedside of 417 patients achieved 81% sensitivity and 94% positive predictive value. Providers documented against 89% patients with an alert activated by clinical decision support and completed 75% of bedside screening and stratification of patients with sepsis within one hour from notification. CONCLUSION A clinical decision support binary alarm system with cross-checking functionality improves early recognition and facilitates stratification of patients with sepsis.
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Affiliation(s)
- Robert C Amland
- Population Health, Cerner Corporation, Kansas City, 64117 USA
| | - Jason J Lyons
- Pulmonary Division, Department of Medicine, Unity Hospital, Rochester, 14626 USA
| | - Tracy L Greene
- Business Intelligence and Long Term Care, Rochester Regional Health System; Rochester, 14626 USA
| | - James M Haley
- Department of Medicine, Unity Hospital, Rochester, 14626 USA
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Wright A, Sittig DF, Ash JS, Erickson JL, Hickman TT, Paterno M, Gebhardt E, McMullen C, Tsurikova R, Dixon BE, Fraser G, Simonaitis L, Sonnenberg FA, Middleton B. Lessons learned from implementing service-oriented clinical decision support at four sites: A qualitative study. Int J Med Inform 2015; 84:901-11. [PMID: 26343972 DOI: 10.1016/j.ijmedinf.2015.08.008] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2015] [Revised: 08/07/2015] [Accepted: 08/17/2015] [Indexed: 02/05/2023]
Abstract
OBJECTIVE To identify challenges, lessons learned and best practices for service-oriented clinical decision support, based on the results of the Clinical Decision Support Consortium, a multi-site study which developed, implemented and evaluated clinical decision support services in a diverse range of electronic health records. METHODS Ethnographic investigation using the rapid assessment process, a procedure for agile qualitative data collection and analysis, including clinical observation, system demonstrations and analysis and 91 interviews. RESULTS We identified challenges and lessons learned in eight dimensions: (1) hardware and software computing infrastructure, (2) clinical content, (3) human-computer interface, (4) people, (5) workflow and communication, (6) internal organizational policies, procedures, environment and culture, (7) external rules, regulations, and pressures and (8) system measurement and monitoring. Key challenges included performance issues (particularly related to data retrieval), differences in terminologies used across sites, workflow variability and the need for a legal framework. DISCUSSION Based on the challenges and lessons learned, we identified eight best practices for developers and implementers of service-oriented clinical decision support: (1) optimize performance, or make asynchronous calls, (2) be liberal in what you accept (particularly for terminology), (3) foster clinical transparency, (4) develop a legal framework, (5) support a flexible front-end, (6) dedicate human resources, (7) support peer-to-peer communication, (8) improve standards. CONCLUSION The Clinical Decision Support Consortium successfully developed a clinical decision support service and implemented it in four different electronic health records and four diverse clinical sites; however, the process was arduous. The lessons identified by the Consortium may be useful for other developers and implementers of clinical decision support services.
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Affiliation(s)
- Adam Wright
- Brigham & Women's Hospital, Boston, MA, United States; Harvard Medical School, Boston, MA, United States; Partners HealthCare, Boston, MA, United States
| | - Dean F Sittig
- The University of Texas Health Science School of Biomedical Informatics at Houston, Houston, TX, United States
| | - Joan S Ash
- Oregon Health & Science University, Portland, OR, United States
| | - Jessica L Erickson
- Brigham & Women's Hospital, Boston, MA, United States; Partners HealthCare, Boston, MA, United States
| | - Trang T Hickman
- Brigham & Women's Hospital, Boston, MA, United States; Partners HealthCare, Boston, MA, United States
| | - Marilyn Paterno
- Brigham & Women's Hospital, Boston, MA, United States; Harvard Medical School, Boston, MA, United States; Partners HealthCare, Boston, MA, United States
| | - Eric Gebhardt
- Oregon Health & Science University, Portland, OR, United States
| | - Carmit McMullen
- Kaiser Permanente Center for Health Research, Portland, OR, United States
| | - Ruslana Tsurikova
- Brigham & Women's Hospital, Boston, MA, United States; Partners HealthCare, Boston, MA, United States
| | - Brian E Dixon
- Regenstrief Institute, Inc., Indianapolis, IN, United States; Indiana University Fairbanks School of Public Health, Indianapolis, IN, United States; Department of Veterans Affairs, Veterans Health Administration, Health Services Research and Development Service CIN 13-416, Richard L. Roudebush VA Medical Center, Indianapolis, IN, United States
| | - Greg Fraser
- WVP Health Authority, Salem, OR, United States
| | - Linas Simonaitis
- Regenstrief Institute, Inc., Indianapolis, IN, United States; Department of Veterans Affairs, Veterans Health Administration, Health Services Research and Development Service CIN 13-416, Richard L. Roudebush VA Medical Center, Indianapolis, IN, United States
| | - Frank A Sonnenberg
- Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, United States
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Hosseini M, Meade J, Schnitzius J, Dixon BE. Consolidating CCDs from multiple data sources: a modular approach. J Am Med Inform Assoc 2015; 23:317-23. [DOI: 10.1093/jamia/ocv084] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2015] [Accepted: 05/26/2015] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background Healthcare providers sometimes receive multiple continuity of care documents (CCDs) for a single patient encompassing the patient’s various encounters and medical history recorded in different information systems. It is cumbersome for providers to explore different pages of CCDs to find specific data which can be duplicated or even conflicted. This study describes initial steps toward a modular system that integrates and de-duplicates multiple CCDs into one consolidated document for viewing or processing patient-level data.
Materials and Methods The authors developed a prototype system to consolidate and de-duplicate CCDs. The system is engineered to be scalable, extensible, and open source. Using a corpus of 150 de-identified CCDs synthetically generated from a single data source with a common vocabulary to represent 50 unique patients, the authors tested the system’s performance and output. Performance was measured based on document throughput and reduction in file size and volume of data. The authors further compared the output of the system with manual consolidation and de-duplication. Testing across multiple vendor systems or implementations was not performed.
Results All of the input CCDs was successfully consolidated, and no data were lost. De-duplication significantly reduced the number of entries in different sections (49% in Problems, 60.6% in Medications, and 79% in Allergies) and reduced the size of the documents (57.5%) as well as the number of lines in each document (58%). The system executed at a rate of approximately 0.009–0.03 s per rule depending on the complexity of the rule.
Discussion and Conclusion Given increasing adoption and use of health information exchange (HIE) to share data and information across the care continuum, duplication of information is inevitable. A novel system designed to support automated consolidation and de-duplication of information across clinical documents as they are exchanged shows promise. Future work is needed to expand the capabilities of the system and further test it using heterogeneous vocabularies across multiple HIE scenarios.
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Affiliation(s)
- Masoud Hosseini
- School of Informatics and Computing, Department of BioHealth Informatics, Indiana University
- Regenstrief Institute, Inc
| | | | | | - Brian E Dixon
- Regenstrief Institute, Inc
- Richard M. Fairbanks School of Public Health at IUPUI, Indiana University
- Center for Health Information and Communication, Department of Veterans Affairs, Veterans Health Administration, Health Services Research and Development Service CIN 13-416, Richard L. Roudebush VA Medical Center
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Oh S, Cha J, Ji M, Kang H, Kim S, Heo E, Han JS, Kang H, Chae H, Hwang H, Yoo S. Architecture Design of Healthcare Software-as-a-Service Platform for Cloud-Based Clinical Decision Support Service. Healthc Inform Res 2015; 21:102-10. [PMID: 25995962 PMCID: PMC4434058 DOI: 10.4258/hir.2015.21.2.102] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2015] [Revised: 04/14/2015] [Accepted: 04/25/2015] [Indexed: 11/25/2022] Open
Abstract
Objectives To design a cloud computing-based Healthcare Software-as-a-Service (SaaS) Platform (HSP) for delivering healthcare information services with low cost, high clinical value, and high usability. Methods We analyzed the architecture requirements of an HSP, including the interface, business services, cloud SaaS, quality attributes, privacy and security, and multi-lingual capacity. For cloud-based SaaS services, we focused on Clinical Decision Service (CDS) content services, basic functional services, and mobile services. Microsoft's Azure cloud computing for Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) was used. Results The functional and software views of an HSP were designed in a layered architecture. External systems can be interfaced with the HSP using SOAP and REST/JSON. The multi-tenancy model of the HSP was designed as a shared database, with a separate schema for each tenant through a single application, although healthcare data can be physically located on a cloud or in a hospital, depending on regulations. The CDS services were categorized into rule-based services for medications, alert registration services, and knowledge services. Conclusions We expect that cloud-based HSPs will allow small and mid-sized hospitals, in addition to large-sized hospitals, to adopt information infrastructures and health information technology with low system operation and maintenance costs.
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Affiliation(s)
- Sungyoung Oh
- R&D Institute, ezCaretech Co. Ltd., Seoul, Korea
| | - Jieun Cha
- R&D Institute, ezCaretech Co. Ltd., Seoul, Korea
| | - Myungkyu Ji
- R&D Institute, ezCaretech Co. Ltd., Seoul, Korea
| | | | - Seok Kim
- Center for Medical Informatics, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Eunyoung Heo
- Center for Medical Informatics, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Jong Soo Han
- Health Promotion Center & Department of Family Medicine, Seoul National University Bundang Hospital, Seongnam, Korea
| | | | - Hoseok Chae
- R&D Institute, ezCaretech Co. Ltd., Seoul, Korea
| | - Hee Hwang
- Center for Medical Informatics, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Sooyoung Yoo
- Center for Medical Informatics, Seoul National University Bundang Hospital, Seongnam, Korea
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Multiple perspectives on clinical decision support: a qualitative study of fifteen clinical and vendor organizations. BMC Med Inform Decis Mak 2015; 15:35. [PMID: 25903564 PMCID: PMC4447027 DOI: 10.1186/s12911-015-0156-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2014] [Accepted: 04/07/2015] [Indexed: 02/08/2023] Open
Abstract
Background Computerized clinical decision support (CDS) can help hospitals to improve healthcare. However, CDS can be problematic. The purpose of this study was to discover how the views of clinical stakeholders, CDS content vendors, and EHR vendors are alike or different with respect to challenges in the development, management, and use of CDS. Methods We conducted ethnographic fieldwork using a Rapid Assessment Process within ten clinical and five health information technology (HIT) vendor organizations. Using an inductive analytical approach, we generated themes from the clinical, content vendor, and electronic health record vendor perspectives and compared them. Results The groups share views on the importance of appropriate manpower, careful knowledge management, CDS that fits user workflow, the need for communication among the groups, and for mutual strategizing about the future of CDS. However, views of usability, training, metrics, interoperability, product use, and legal issues differed. Recommendations for improvement include increased collaboration to address legal, manpower, and CDS sharing issues. Conclusions The three groups share thinking about many aspects of CDS, but views differ in a number of important respects as well. Until these three groups can reach a mutual understanding of the views of the other stakeholders, and work together, CDS will not reach its potential.
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Griebel L, Prokosch HU, Köpcke F, Toddenroth D, Christoph J, Leb I, Engel I, Sedlmayr M. A scoping review of cloud computing in healthcare. BMC Med Inform Decis Mak 2015; 15:17. [PMID: 25888747 PMCID: PMC4372226 DOI: 10.1186/s12911-015-0145-7] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2014] [Accepted: 03/04/2015] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Cloud computing is a recent and fast growing area of development in healthcare. Ubiquitous, on-demand access to virtually endless resources in combination with a pay-per-use model allow for new ways of developing, delivering and using services. Cloud computing is often used in an "OMICS-context", e.g. for computing in genomics, proteomics and molecular medicine, while other field of application still seem to be underrepresented. Thus, the objective of this scoping review was to identify the current state and hot topics in research on cloud computing in healthcare beyond this traditional domain. METHODS MEDLINE was searched in July 2013 and in December 2014 for publications containing the terms "cloud computing" and "cloud-based". Each journal and conference article was categorized and summarized independently by two researchers who consolidated their findings. RESULTS 102 publications have been analyzed and 6 main topics have been found: telemedicine/teleconsultation, medical imaging, public health and patient self-management, hospital management and information systems, therapy, and secondary use of data. Commonly used features are broad network access for sharing and accessing data and rapid elasticity to dynamically adapt to computing demands. Eight articles favor the pay-for-use characteristics of cloud-based services avoiding upfront investments. Nevertheless, while 22 articles present very general potentials of cloud computing in the medical domain and 66 articles describe conceptual or prototypic projects, only 14 articles report from successful implementations. Further, in many articles cloud computing is seen as an analogy to internet-/web-based data sharing and the characteristics of the particular cloud computing approach are unfortunately not really illustrated. CONCLUSIONS Even though cloud computing in healthcare is of growing interest only few successful implementations yet exist and many papers just use the term "cloud" synonymously for "using virtual machines" or "web-based" with no described benefit of the cloud paradigm. The biggest threat to the adoption in the healthcare domain is caused by involving external cloud partners: many issues of data safety and security are still to be solved. Until then, cloud computing is favored more for singular, individual features such as elasticity, pay-per-use and broad network access, rather than as cloud paradigm on its own.
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Affiliation(s)
- Lena Griebel
- Department of Medical Informatics, Friedrich-Alexander-University Erlangen-Nürnberg, Wetterkreuz 13, Erlangen, D-91058 Germany
| | - Hans-Ulrich Prokosch
- Department of Medical Informatics, Friedrich-Alexander-University Erlangen-Nürnberg, Wetterkreuz 13, Erlangen, D-91058 Germany
| | - Felix Köpcke
- Department of Medical Informatics, Friedrich-Alexander-University Erlangen-Nürnberg, Wetterkreuz 13, Erlangen, D-91058 Germany
| | - Dennis Toddenroth
- Department of Medical Informatics, Friedrich-Alexander-University Erlangen-Nürnberg, Wetterkreuz 13, Erlangen, D-91058 Germany
| | - Jan Christoph
- Department of Medical Informatics, Friedrich-Alexander-University Erlangen-Nürnberg, Wetterkreuz 13, Erlangen, D-91058 Germany
| | - Ines Leb
- Department of Medical Informatics, Friedrich-Alexander-University Erlangen-Nürnberg, Wetterkreuz 13, Erlangen, D-91058 Germany
| | - Igor Engel
- Department of Medical Informatics, Friedrich-Alexander-University Erlangen-Nürnberg, Wetterkreuz 13, Erlangen, D-91058 Germany
| | - Martin Sedlmayr
- Department of Medical Informatics, Friedrich-Alexander-University Erlangen-Nürnberg, Wetterkreuz 13, Erlangen, D-91058 Germany
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Zheng YL, Ding XR, Poon CCY, Lo BPL, Zhang H, Zhou XL, Yang GZ, Zhao N, Zhang YT. Unobtrusive sensing and wearable devices for health informatics. IEEE Trans Biomed Eng 2015; 61:1538-54. [PMID: 24759283 PMCID: PMC7176476 DOI: 10.1109/tbme.2014.2309951] [Citation(s) in RCA: 247] [Impact Index Per Article: 27.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
The aging population, prevalence of chronic diseases, and outbreaks of infectious diseases are some of the major challenges of our present-day society. To address these unmet healthcare needs, especially for the early prediction and treatment of major diseases, health informatics, which deals with the acquisition, transmission, processing, storage, retrieval, and use of health information, has emerged as an active area of interdisciplinary research. In particular, acquisition of health-related information by unobtrusive sensing and wearable technologies is considered as a cornerstone in health informatics. Sensors can be weaved or integrated into clothing, accessories, and the living environment, such that health information can be acquired seamlessly and pervasively in daily living. Sensors can even be designed as stick-on electronic tattoos or directly printed onto human skin to enable long-term health monitoring. This paper aims to provide an overview of four emerging unobtrusive and wearable technologies, which are essential to the realization of pervasive health information acquisition, including: 1) unobtrusive sensing methods, 2) smart textile technology, 3) flexible-stretchable-printable electronics, and 4) sensor fusion, and then to identify some future directions of research.
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Frasch MG. Editorial: Perinatology in the Era of Big Data and Nanoparticles. Front Pediatr 2015; 3:95. [PMID: 26594641 PMCID: PMC4633508 DOI: 10.3389/fped.2015.00095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2015] [Accepted: 10/22/2015] [Indexed: 11/13/2022] Open
Affiliation(s)
- Martin G Frasch
- Department of Obstetrics and Gynecology, CHU Sainte-Justine Centre de Recherche, Université de Montréal , Montreal, QC , Canada ; Department of Neurosciences, CHU Sainte-Justine Centre de Recherche, Université de Montréal , Montreal, QC , Canada
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de la Torre-Díez I, Martínez-Pérez B, López-Coronado M, Díaz JR, López MM. Decision support systems and applications in ophthalmology: literature and commercial review focused on mobile apps. J Med Syst 2014; 39:174. [PMID: 25472731 DOI: 10.1007/s10916-014-0174-2] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2014] [Accepted: 11/25/2014] [Indexed: 11/29/2022]
Abstract
The growing importance that mobile devices have in daily life has also reached health care and medicine. This is making the paradigm of health care change and the concept of mHealth or mobile health more relevant, whose main essence is the apps. This new reality makes it possible for doctors who are not specialist to have easy access to all the information generated in different corners of the world, making them potential keepers of that knowledge. However, the new daily information exceeds the limits of the human intellect, making Decision Support Systems (DSS) necessary for helping doctors to diagnose diseases and also help them to decide the attitude that has to be taken towards these diagnoses. These could improve the health care in remote areas and developing countries. All of this is even more important in diseases that are more prevalent in primary care and that directly affect the people's quality of life, this is the case in ophthalmological problems where in first patient care a specialist in ophthalmology is not involved. The goal of this paper is to analyse the state of the art of DSS in Ophthalmology. Many of them focused on diseases affecting the eye's posterior pole. For achieving the main purpose of this research work, a literature review and commercial apps analysis will be done. The used databases and systems will be IEEE Xplore, Web of Science (WoS), Scopus, and PubMed. The search is limited to articles published from 2000 until now. Later, different Mobile Decision Support System (MDSS) in Ophthalmology will be analyzed in the virtual stores for Android and iOS. 37 articles were selected according their thematic (posterior pole, anterior pole, Electronic Health Records (EHRs), cloud, data mining, algorithms and structures for DSS, and other) from a total of 600 found in the above cited databases. Very few mobile apps were found in the different stores. It can be concluded that almost all existing mobile apps are focused on the eye's posterior pole. Among them, the most intended are for diagnostic of diabetic retinopathy. The primary market niche of the commercial apps is the general physicians.
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Affiliation(s)
- Isabel de la Torre-Díez
- Department of Signal Theory and Communications, and Telematics Engineering, University of Valladolid, Paseo de Belén, 15, 47011, Valladolid, Spain,
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Einbinder J, Hebel E, Wright A, Panzenhagen M, Middleton B. The Number Needed to Remind: a Measure for Assessing CDS Effectiveness. AMIA ... ANNUAL SYMPOSIUM PROCEEDINGS. AMIA SYMPOSIUM 2014; 2014:506-515. [PMID: 25954355 PMCID: PMC4419960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
BACKGROUND Clinical decision support (CDS) is associated with improvement in quality and efficiency in healthcare delivery. The appropriate way to evaluate its effectiveness remains uncertain. METHODS We analyzed data from our electronic health record (EHR) measuring the display frequency of eight reminders for Coronary Artery disease and Type 2 Diabetes and their associated performance according to a predefined methodology. We propose two key performance indicators to measure their impact on a target population: the reminder performance (RP), and the number needed to remind (NNR), to evaluate the impact that Clinical decision support reminders have on the adherence to guideline derived CDS interventions on the entire patient population, and individual providers receiving the interventions. RESULTS Data were available for 116,027 patients and a total of 1,982,735 reminders were displayed to a subset of 65,516 patients during the study period from January 1 to December 31, 2010. The evaluation framework assessed provider acknowledgement of the CDS intervention, and the presence of the expected performance event while accounting for patients' exposure to the CDS reminders. The total RP was 2.7% while the average NNR was 3.1 for all the reminders under study. CONCLUSIONS The proposed framework to asses of CDS performance provides a novel approach to improve the design and evaluation of CDS interventions. The application of this methodology represents an indicator to understand the impact of CDS interventions and subsequent patient outcomes. Further research is required to evaluate the impact of these systems on the quality of care.
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Affiliation(s)
- Jonathan Einbinder
- Clinical Informatics Research and Development, Partners Healthcare Systems, Wellesley, MA ; Harvard Medical School, Boston, MA ; Massachusetts General Hospital, Boston, MA
| | - Esteban Hebel
- Clinical Informatics Research and Development, Partners Healthcare Systems, Wellesley, MA ; German Clinic, Santiago, Chile
| | - Adam Wright
- Clinical Informatics Research and Development, Partners Healthcare Systems, Wellesley, MA ; Harvard Medical School, Boston, MA ; Massachusetts General Hospital, Boston, MA
| | | | - Blackford Middleton
- Clinical Informatics Research and Development, Partners Healthcare Systems, Wellesley, MA ; Harvard Medical School, Boston, MA ; Massachusetts General Hospital, Boston, MA
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Abstract
Sepsis is an inflammatory response triggered by infection, with a high in-hospital mortality rate. Early recognition and treatment can reverse the inflammatory response, with evidence of improved patient outcomes. One challenge clinicians face is identifying the inflammatory syndrome against the background of the patient's infectious illness and comorbidities. An approach to this problem is implementation of computerized early warning tools for sepsis. This multicenter retrospective study sought to determine clinimetric performance of a cloud-based computerized sepsis clinical decision support system (CDS), understand the epidemiology of sepsis, and identify opportunities for quality improvement. Data encompassed 6200 adult hospitalizations from 2012 through 2013. Of 13% patients screened-in, 51% were already suspected to have an infection when the system activated. This study focused on a patient cohort screened-in before infection was suspected; median time from arrival to CDS activation was 3.5 hours, and system activation to diagnostic collect was another 8.6 hours.
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Dixon BE, Simonaitis L, Perkins SM, Wright A, Middleton B. Measuring agreement between decision support reminders: the cloud vs. the local expert. BMC Med Inform Decis Mak 2014; 14:31. [PMID: 24720863 PMCID: PMC4004460 DOI: 10.1186/1472-6947-14-31] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2013] [Accepted: 03/19/2014] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND 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.
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Affiliation(s)
- Brian Edward Dixon
- Department of BioHealth Informatics, Indiana University School of Informatics and Computing, Indiana University-Purdue University Indianapolis, 410 W. St., Suite 2000, Indianapolis, IN 46202, USA
- Center for Biomedical Informatics, Regenstrief Institute, Inc, Indianapolis, IN USA
- Center for Health Information and Communication, Department of Veterans Affairs, Veterans Health Administration, Health Services Research and Development Service CIN 13–416, Indianapolis, IN USA
| | - Linas Simonaitis
- Center for Biomedical Informatics, Regenstrief Institute, Inc, Indianapolis, IN USA
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN USA
| | - Susan M Perkins
- Department of Biostatistics, Indiana University, School of Medicine, Indianapolis, IN USA
- Indiana University Cancer Center, Indianapolis, IN USA
- Indiana Clinical Translational Science Institute, Indianapolis, IN USA
| | - Adam Wright
- Harvard Medical School, Boston, MA USA
- Division of General Medicine, Brigham and Women’s Hospital, Boston, MA USA
- Partners HealthCare, Boston, MA USA
| | - Blackford Middleton
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN USA
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Kellermann AL, Saultz JW, Mehrotra A, Jones SS, Dalal S. Primary Care Technicians: A Solution To The Primary Care Workforce Gap. Health Aff (Millwood) 2013; 32:1893-8. [DOI: 10.1377/hlthaff.2013.0481] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- Arthur L. Kellermann
- Arthur L. Kellermann ( ) is dean of the F. Edward Hébert School of Medicine, Uniformed Services University of the Health Sciences, in Bethesda, Maryland
| | - John W. Saultz
- John W. Saultz is a professor in and chair of the Department of Family Medicine at the Oregon Health and Science University, in Portland
| | - Ateev Mehrotra
- Ateev Mehrotra is an associate professor at Harvard Medical School and affiliated adjunct staff at the RAND Corporation in Boston, Massachusetts
| | - Spencer S. Jones
- Spencer S. Jones is director of information science at Vanguard Health Systems, in Nashville, Tennessee; affiliated adjunct staff at the RAND Corporation; and an instructor in the Division of General Medicine at Brigham and Women’s Hospital and Harvard Medical School
| | - Siddartha Dalal
- Siddartha Dalal is vice president of advanced research and technology at American International Group Inc., in New York City
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Dixon BE, Jabour AM, Phillips EO, Marrero DG. An informatics approach to medication adherence assessment and improvement using clinical, billing, and patient-entered data. J Am Med Inform Assoc 2013; 21:517-21. [PMID: 24076751 DOI: 10.1136/amiajnl-2013-001959] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
The aim of this study was to describe an integrated informatics approach to aggregating and displaying clinically relevant data that can identify problems with medication adherence and facilitate patient-provider communication about strategies to improve medication use. We developed a clinical dashboard within an electronic health record (EHR) system that uses data from three sources: the medical record, pharmacy claims, and a personal health record. The data are integrated to inform clinician-patient discussions about medication adherence. Whereas prior research on assessing patterns of medication adherence focused on a single approach using the EHR, pharmacy data, or patient-entered data, we present an approach that integrates multiple electronic data sources increasingly found in practice. Medication adherence is a complex challenge that requires patient and provider team input, necessitating an integrated approach using advanced EHR, clinical decision support, and patient-controlled technologies. Future research should focus on integrated strategies to provide patients and providers with the right combination of informatics tools to help them adequately address the challenge of adherence to complex medication therapies.
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Affiliation(s)
- Brian E Dixon
- Department of BioHealth Informatics, Indiana University School of Informatics and Computing, Indiana University-Purdue University Indianapolis, Indianapolis, Indiana, USA
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Overby CL, Kohane I, Kannry JL, Williams MS, Starren J, Bottinger E, Gottesman O, Denny JC, Weng C, Tarczy-Hornoch P, Hripcsak G. Opportunities for genomic clinical decision support interventions. Genet Med 2013; 15:817-23. [PMID: 24051479 DOI: 10.1038/gim.2013.128] [Citation(s) in RCA: 56] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2013] [Accepted: 07/15/2013] [Indexed: 12/12/2022] Open
Affiliation(s)
- Casey Lynnette Overby
- 1] Department of Biomedical Informatics, Columbia University, New York, New York, USA [2] Program for Personalized & Genomic Medicine and Center for Health-Related Informatics and Bioimaging, University of Maryland School of Medicine, Baltimore, Maryland, USA
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Goldberg HS, Paterno MD, Rocha BH, Schaeffer M, Wright A, Erickson JL, Middleton B. A highly scalable, interoperable clinical decision support service. J Am Med Inform Assoc 2013; 21:e55-62. [PMID: 23828174 DOI: 10.1136/amiajnl-2013-001990] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
OBJECTIVE To create a clinical decision support (CDS) system that is shareable across healthcare delivery systems and settings over large geographic regions. MATERIALS AND METHODS The enterprise clinical rules service (ECRS) realizes nine design principles through a series of enterprise java beans and leverages off-the-shelf rules management systems in order to provide consistent, maintainable, and scalable decision support in a variety of settings. RESULTS The ECRS is deployed at Partners HealthCare System (PHS) and is in use for a series of trials by members of the CDS consortium, including internally developed systems at PHS, the Regenstrief Institute, and vendor-based systems deployed at locations in Oregon and New Jersey. Performance measures indicate that the ECRS provides sub-second response time when measured apart from services required to retrieve data and assemble the continuity of care document used as input. DISCUSSION We consider related work, design decisions, comparisons with emerging national standards, and discuss uses and limitations of the ECRS. CONCLUSIONS ECRS design, implementation, and use in CDS consortium trials indicate that it provides the flexibility and modularity needed for broad use and performs adequately. Future work will investigate additional CDS patterns, alternative methods of data passing, and further optimizations in ECRS performance.
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Affiliation(s)
- Howard S Goldberg
- Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts, USA
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Ammenwerth E, Nykänen P, Rigby M, de Keizer N. Clinical decision support systems: need for evidence, need for evaluation. Artif Intell Med 2013; 59:1-3. [PMID: 23810731 DOI: 10.1016/j.artmed.2013.05.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2013] [Accepted: 05/12/2013] [Indexed: 01/03/2023]
Affiliation(s)
- Elske Ammenwerth
- Institute of Health Informatics, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard Wallnöfer Zentrum 1, 6060 Hall in Tyrol, Austria.
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Dixon BE, Gamache RE, Grannis SJ. Towards public health decision support: a systematic review of bidirectional communication approaches. J Am Med Inform Assoc 2013; 20:577-83. [PMID: 23467470 PMCID: PMC3628068 DOI: 10.1136/amiajnl-2012-001514] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2012] [Revised: 02/01/2013] [Accepted: 02/09/2013] [Indexed: 11/03/2022] Open
Abstract
OBJECTIVE To summarize the literature describing computer-based interventions aimed at improving bidirectional communication between clinical and public health. MATERIALS AND METHODS A systematic review of English articles using MEDLINE and Google Scholar. Search terms included public health, epidemiology, electronic health records, decision support, expert systems, and decision-making. Only articles that described the communication of information regarding emerging health threats from public health agencies to clinicians or provider organizations were included. Each article was independently reviewed by two authors. RESULTS Ten peer-reviewed articles highlight a nascent but promising area of research and practice related to alerting clinicians about emerging threats. Current literature suggests that additional research and development in bidirectional communication infrastructure should focus on defining a coherent architecture, improving interoperability, establishing clear governance, and creating usable systems that will effectively deliver targeted, specific information to clinicians in support of patient and population decision-making. CONCLUSIONS Increasingly available clinical information systems make it possible to deliver timely, relevant knowledge to frontline clinicians in support of population health. Future work should focus on developing a flexible, interoperable infrastructure for bidirectional communications capable of integrating public health knowledge into clinical systems and workflows.
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Affiliation(s)
- Brian E Dixon
- School of Informatics and Computing, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USA.
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