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Wang W, Li M, Loban K, Zhang J, Wei X, Mitchel R. Electronic health record and primary care physician self-reported quality of care: a multilevel study in China. Glob Health Action 2024; 17:2301195. [PMID: 38205626 PMCID: PMC10786430 DOI: 10.1080/16549716.2023.2301195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Accepted: 12/29/2023] [Indexed: 01/12/2024] Open
Abstract
BACKGROUND Health information technology is one of the building blocks of a high-performing health system. However, the evidence regarding the influence of an electronic health record (EHR) on the quality of care remains mixed, especially in low- and middle-income countries. OBJECTIVE This study examines the association between greater EHR functionality and primary care physician self-reported quality of care. METHODS A total of 224 primary care physicians from 38 community health centres (CHCs) in four large Chinese cities participated in a cross-sectional survey to assess CHC care quality. Each CHC director scored their CHC's EHR functionality on the availability of ten typical features covering health information, data, results management, patient access, and clinical decision support. Data analysis utilised hierarchical linear modelling. RESULTS The availability of five EHR features was positively associated with physician self-reported clinical quality: share records online with providers outside the practice (β = 0.276, p = 0.04), access records online by the patient (β = 0.325, p = 0.04), alert provider of potential prescription problems (β = 0.353, p = 0.04), send the patient reminders for care (β = 0.419, p = 0.003), and list patients by diagnosis or health risk (β = 0.282, p = 0.04). However, no association was found between specific features availability or total features score and physician self-reported preventive quality. CONCLUSIONS This study provides evidence that the availability of EHR systems, and specific features of these systems, was positively associated with physician self-reported quality of care in these 38 CHCs. Future longitudinal studies focused on standardised quality metrics, and designed to control known confounding variables, will further inform quality improvement efforts in primary care.
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Affiliation(s)
- Wenhua Wang
- School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an, PR China
| | - Mengyao Li
- School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an, PR China
| | - Katya Loban
- Research Institute of the McGill University Health Centre, McGill University, Montreal, Canada
| | - Jinnan Zhang
- School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an, PR China
| | - Xiaolin Wei
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Rebecca Mitchel
- Health and Wellbeing Research Unit (HoWRU), Macquarie Business School, Macquarie University, Sydney, Australia
- Newcastle Business School, University of Newcastle, Newcastle, Australia
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2
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Till L, Leis J, McCombs-Thornton K, Lee H, Reinhart S, Valado T, Briggs R, Bushar J, Fritz L. Improving electronic health record documentation and use to promote evidence-based pediatric care. J Pediatr Psychol 2024:jsae067. [PMID: 39172648 DOI: 10.1093/jpepsy/jsae067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 07/31/2024] [Accepted: 08/05/2024] [Indexed: 08/24/2024] Open
Abstract
OBJECTIVE Electronic health records (EHRs) often lack the necessary functionalities to support the full implementation of national clinical guidelines for pediatric care outlined in the American Academy of Pediatrics Bright Futures Guidelines. Using HealthySteps (HS), an evidence-based pediatric primary care program, as an exemplar, this study aimed to enhance pediatric EHRs, identify facilitators and barriers to EHR enhancements, and improve data quality for delivering clinical care as part of HS implementation and evidence building. METHODS Three HS sites-each differing in location, setting, number of children served, and mix of child insurance coverage-participated in the study. Sites received technical assistance to support data collection and EHR updates. A comprehensive evaluation, including a process evaluation and outcomes monitoring, was conducted to gauge progress toward implementing study data requirements over time. Data sources included administrative records, surveys, and interviews. RESULTS All sites enhanced their EHRs yet relied on supplemental data systems to track care coordination. Sites improved documentation of required data, demonstrating reductions in missing data and increases in extractable data between baseline and follow-up assessments. For example, the percentage of missing social-emotional screening results ranged from 0% to 8.0% at study conclusion. Facilitators and barriers to EHR enhancements included organizational supports, leadership, and capacity building. CONCLUSIONS With significant investment of time and resources, practices modified their EHRs to better capture services aligned with HS and Bright Futures. However, more scalable digital solutions are necessary to support EHR updates to help drive improvements in clinical care and outcomes for children and families.
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Affiliation(s)
- Lance Till
- James Bell Associates (JBA), Arlington, VA, United States
| | - Julie Leis
- James Bell Associates (JBA), Arlington, VA, United States
| | | | | | - Shauna Reinhart
- HealthySteps National Office at ZERO TO THREE, Washington, DC, United States
| | | | - Rahil Briggs
- HealthySteps National Office at ZERO TO THREE, Washington, DC, United States
| | - Jessica Bushar
- HealthySteps National Office at ZERO TO THREE, Washington, DC, United States
| | - Laila Fritz
- HealthySteps National Office at ZERO TO THREE, Washington, DC, United States
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3
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Julian GS, Shau WY, Chou HW, Setia S. Bridging Real-World Data Gaps: Connecting Dots Across 10 Asian Countries. JMIR Med Inform 2024; 12:e58548. [PMID: 39026427 DOI: 10.2196/58548] [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: 03/18/2024] [Revised: 06/17/2024] [Accepted: 07/19/2024] [Indexed: 07/20/2024] Open
Abstract
The economic trend and the health care landscape are rapidly evolving across Asia. Effective real-world data (RWD) for regulatory and clinical decision-making is a crucial milestone associated with this evolution. This necessitates a critical evaluation of RWD generation within distinct nations for the use of various RWD warehouses in the generation of real-world evidence (RWE). In this article, we outline the RWD generation trends for 2 contrasting nation archetypes: "Solo Scholars"-nations with relatively self-sufficient RWD research systems-and "Global Collaborators"-countries largely reliant on international infrastructures for RWD generation. The key trends and patterns in RWD generation, country-specific insights into the predominant databases used in each country to produce RWE, and insights into the broader landscape of RWD database use across these countries are discussed. Conclusively, the data point out the heterogeneous nature of RWD generation practices across 10 different Asian nations and advocate for strategic enhancements in data harmonization. The evidence highlights the imperative for improved database integration and the establishment of standardized protocols and infrastructure for leveraging electronic medical records (EMR) in streamlining RWD acquisition. The clinical data analysis and reporting system of Hong Kong is an excellent example of a successful EMR system that showcases the capacity of integrated robust EMR platforms to consolidate and produce diverse RWE. This, in turn, can potentially reduce the necessity for reliance on numerous condition-specific local and global registries or limited and largely unavailable medical insurance or claims databases in most Asian nations. Linking health technology assessment processes with open data initiatives such as the Observational Medical Outcomes Partnership Common Data Model and the Observational Health Data Sciences and Informatics could enable the leveraging of global data resources to inform local decision-making. Advancing such initiatives is crucial for reinforcing health care frameworks in resource-limited settings and advancing toward cohesive, evidence-driven health care policy and improved patient outcomes in the region.
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Affiliation(s)
| | - Wen-Yi Shau
- Pfizer Corporation Hong Kong Limited, Hong Kong, China (Hong Kong)
| | | | - Sajita Setia
- Executive Office, Transform Medical Communications Limited, Wanganui, New Zealand
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4
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Achterberg JL, Haas MR, Spruit MR. On the evaluation of synthetic longitudinal electronic health records. BMC Med Res Methodol 2024; 24:181. [PMID: 39143466 PMCID: PMC11323671 DOI: 10.1186/s12874-024-02304-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Accepted: 08/07/2024] [Indexed: 08/16/2024] Open
Abstract
BACKGROUND Synthetic Electronic Health Records (EHRs) are becoming increasingly popular as a privacy enhancing technology. However, for longitudinal EHRs specifically, little research has been done into how to properly evaluate synthetically generated samples. In this article, we provide a discussion on existing methods and recommendations when evaluating the quality of synthetic longitudinal EHRs. METHODS We recommend to assess synthetic EHR quality through similarity to real EHRs in low-dimensional projections, accuracy of a classifier discriminating synthetic from real samples, performance of synthetic versus real trained algorithms in clinical tasks, and privacy risk through risk of attribute inference. For each metric we discuss strengths and weaknesses, next to showing how it can be applied on a longitudinal dataset. RESULTS To support the discussion on evaluation metrics, we apply discussed metrics on a dataset of synthetic EHRs generated from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) repository. CONCLUSIONS The discussion on evaluation metrics provide guidance for researchers on how to use and interpret different metrics when evaluating the quality of synthetic longitudinal EHRs.
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Affiliation(s)
- Jim L Achterberg
- Public Health and Primary Care, Health Campus The Hague, Leiden University Medical Center, Albinusdreef 2, Leiden, South-Holland, 2333ZA, Netherlands.
| | - Marcel R Haas
- Public Health and Primary Care, Health Campus The Hague, Leiden University Medical Center, Albinusdreef 2, Leiden, South-Holland, 2333ZA, Netherlands
| | - Marco R Spruit
- Public Health and Primary Care, Health Campus The Hague, Leiden University Medical Center, Albinusdreef 2, Leiden, South-Holland, 2333ZA, Netherlands
- Leiden Institute of Advanced Computer Science, Leiden University, Einsteinweg 55, Leiden, South-Holland, 2333CC, Netherlands
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5
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Bolcato V, Basile G, Bianco Prevot L, Fassina G, Rapuano S, Brizioli E, Tronconi LP. Telemedicine in Italy: Healthcare authorization profiles in the modern medico-legal reading. INTERNATIONAL JOURNAL OF RISK & SAFETY IN MEDICINE 2024:JRS240004. [PMID: 39150835 DOI: 10.3233/jrs-240004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/18/2024]
Abstract
BACKGROUND The ruling n. 38485, 20 June 2019, of the Italian Supreme Court, III criminal section, addressed by the perspective of the law the very sensitive and new issue of telemedicine. OBJECTIVE This commentary deals with the issue of authorization of telemedicine activities by the health authority, starting from the Italian Court of Criminal Cassation, III section, decision n. 38485/2019. The case law explored the authorization of a health point, which carries out telemedicine services. METHODS Starting from the perspective discussed by Italian health regulations, the paper examines how the health act could be defined, with the possibilities offered by telecommunications, and how it now relates legally to the physical place where it takes place. RESULTS Even if telemedicine opens the way to virtual spaces of health practice, the Ministry of Health Italian Guidelines pose functional and logistical issues to guarantee users' safety and health care system accountability. Then, functional requirements for health legitimate practice, and their continuous monitoring, together with the responsibilities of the service centers, health professionals and health facilities, are discussed. CONCLUSION The questioning of States' health law, in a broad health system such as that of the Europe, characterized by autonomous health regulations, is extremely important for cross-border health policy with telemedicine, as overall regulatory compliance in health care is the ground criterion for risk prevention and patient safety, to be properly verified.
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Affiliation(s)
| | - Giuseppe Basile
- Trauma Unit and Emergency Department, IRCCS Galeazzi Orthopaedics Institute, Milan, Italy
- Legal Medicine Unit, Clinical Institute San Siro, Milan, Italy
| | - Luca Bianco Prevot
- Trauma Unit and Emergency Department, IRCCS Galeazzi Orthopaedics Institute, Milan, Italy
| | - Giovanni Fassina
- Department of Public Health, Experimental and Forensic Medicine, Unit of Forensic Sciences, University of Pavia, Pavia, Italy
- Unit of Legal Medicine, IRCCS Fondazione Istituto Neurologico Nazionale C. Mondino, Pavia, Italy
| | - Silvia Rapuano
- GVM Care and Research, Maria Cecilia Hospital, Cotignola, Italy
| | - Enrico Brizioli
- GVM Care and Research, Maria Cecilia Hospital, Cotignola, Italy
| | - Livio P Tronconi
- GVM Care and Research, Maria Cecilia Hospital, Cotignola, Italy
- Department of Human Sciences, European University of Rome, Rome, Italy
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Berman L, Ostchega Y, Giannini J, Anandan LP, Clark E, Spotnitz M, Sulieman L, Volynski M, Ramirez A. Application of a Data Quality Framework to Ductal Carcinoma In Situ Using Electronic Health Record Data From the All of Us Research Program. JCO Clin Cancer Inform 2024; 8:e2400052. [PMID: 39178364 DOI: 10.1200/cci.24.00052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 06/27/2024] [Accepted: 07/17/2024] [Indexed: 08/25/2024] Open
Abstract
PURPOSE The specific aims of this paper are to (1) develop and operationalize an electronic health record (EHR) data quality framework, (2) apply the dimensions of the framework to the phenotype and treatment pathways of ductal carcinoma in situ (DCIS) using All of Us Research Program data, and (3) propose and apply a checklist to evaluate the application of the framework. METHODS We developed a framework of five data quality dimensions (DQD; completeness, concordance, conformance, plausibility, and temporality). Participants signed a consent and Health Insurance Portability and Accountability Act authorization to share EHR data and responded to demographic questions in the Basics questionnaire. We evaluated the internal characteristics of the data and compared data with external benchmarks with descriptive and inferential statistics. We developed a DQD checklist to evaluate concept selection, internal verification, and external validity for each DQD. The Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) concept ID codes for DCIS were used to select a cohort of 2,209 females 18 years and older. RESULTS Using the proposed DQD checklist criteria, (1) concepts were selected and internally verified for conformance; (2) concepts were selected and internally verified for completeness; (3) concepts were selected, internally verified, and externally validated for concordance; (4) concepts were selected, internally verified, and externally validated for plausibility; and (5) concepts were selected, internally verified, and externally validated for temporality. CONCLUSION This assessment and evaluation provided insights into data quality for the DCIS phenotype using EHR data from the All of Us Research Program. The review demonstrates that salient clinical measures can be selected, applied, and operationalized within a conceptual framework and evaluated for fitness for use by applying a proposed checklist.
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Affiliation(s)
- Lew Berman
- National Institutes of Health, All of Us Research Program, Bethesda, MD
| | - Yechiam Ostchega
- National Institutes of Health, All of Us Research Program, Bethesda, MD
| | - John Giannini
- National Institutes of Health, All of Us Research Program, Bethesda, MD
| | | | | | - Matthew Spotnitz
- National Institutes of Health, All of Us Research Program, Bethesda, MD
| | | | | | - Andrea Ramirez
- National Institutes of Health, All of Us Research Program, Bethesda, MD
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7
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Goldstein ND, Jones J, Kahal D, Burstyn I. Inferring Population HIV Viral Load From a Single HIV Clinic's Electronic Health Record: Simulation Study With a Real-World Example. Online J Public Health Inform 2024; 16:e58058. [PMID: 38959056 PMCID: PMC11255534 DOI: 10.2196/58058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 04/24/2024] [Accepted: 05/23/2024] [Indexed: 07/04/2024] Open
Abstract
BACKGROUND Population viral load (VL), the most comprehensive measure of the HIV transmission potential, cannot be directly measured due to lack of complete sampling of all people with HIV. OBJECTIVE A given HIV clinic's electronic health record (EHR), a biased sample of this population, may be used to attempt to impute this measure. METHODS We simulated a population of 10,000 individuals with VL calibrated to surveillance data with a geometric mean of 4449 copies/mL. We sampled 3 hypothetical EHRs from (A) the source population, (B) those diagnosed, and (C) those retained in care. Our analysis imputed population VL from each EHR using sampling weights followed by Bayesian adjustment. These methods were then tested using EHR data from an HIV clinic in Delaware. RESULTS Following weighting, the estimates moved in the direction of the population value with correspondingly wider 95% intervals as follows: clinic A: 4364 (95% interval 1963-11,132) copies/mL; clinic B: 4420 (95% interval 1913-10,199) copies/mL; and clinic C: 242 (95% interval 113-563) copies/mL. Bayesian-adjusted weighting further improved the estimate. CONCLUSIONS These findings suggest that methodological adjustments are ineffective for estimating population VL from a single clinic's EHR without the resource-intensive elucidation of an informative prior.
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Affiliation(s)
- Neal D Goldstein
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, United States
| | - Justin Jones
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, United States
| | | | - Igor Burstyn
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, United States
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8
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Goldstein ND. A Qualitative Study of Physicians' Views on the Reuse of Electronic Health Record Data for Secondary Analysis. QUALITATIVE HEALTH RESEARCH 2024:10497323241245644. [PMID: 38830368 DOI: 10.1177/10497323241245644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2024]
Abstract
Electronic health records (EHRs) have become ubiquitous in clinical practice. Given the rich biomedical data captured for a large panel of patients, secondary analysis of these data for health research is also commonplace. Yet, there are many caveats to EHR data that the researchers must be aware of, such as the accuracy of and motive for documentation, and the reason for patients' visits to the clinic. The clinician-the author of the documentation-is thus central to the correct interpretation of EHR data for research purposes. In this study, I interviewed 11 physicians in various clinical specialties to bring attention to their view on the validity of research using EHR data. Qualitative, in-depth, one-on-one interviews were conducted with practicing physicians in inpatient and outpatient medicine. Content analysis using a data-driven, inductive approach to identify themes related to challenges and opportunities in the reuse of EHR data for secondary analysis generated seven themes. Themes that reflected challenges of EHRs for research included (1) audience, (2) accuracy of data, (3) availability of data, (4) documentation practices, and (5) representativeness. Themes that reflected opportunities of EHRs for research included (6) endorsement and (7) enablers. The greatest perceived barriers reflected the intended audience of the EHR, the interpretation and meaning of the data, and the quality of the data for research purposes. Physicians generally expressed more perceived challenges than opportunities in the reuse of EHR data for research purposes; however, they remained optimistic.
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Affiliation(s)
- Neal D Goldstein
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA, USA
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Oo M, Anderson-Badbade S, Grzejszczak L, Rogers P, Tavernier RLE. A Preliminary Study of Prescription for Play on Developmental Concerns. Clin Pediatr (Phila) 2024:99228241258846. [PMID: 38828996 DOI: 10.1177/00099228241258846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/05/2024]
Affiliation(s)
- May Oo
- Weitzman Institute, Moses/Weitzman Health System, Washington, DC, USA
| | | | | | - Peyton Rogers
- Weitzman Institute, Moses/Weitzman Health System, Washington, DC, USA
| | - Rebecca L Emery Tavernier
- Weitzman Institute, Moses/Weitzman Health System, Washington, DC, USA
- University of Minnesota Medical School, Duluth, MN, USA
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10
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National Association Of School Nurses. National Association of School Nurses Position Statement: Electronic Health Records: An Essential School Nursing Tool for Supporting Student Health. J Sch Nurs 2024; 40:352-354. [PMID: 38706166 DOI: 10.1177/10598405241241804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/07/2024] Open
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11
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Claggett J, Petter S, Joshi A, Ponzio T, Kirkendall E. An Infrastructure Framework for Remote Patient Monitoring Interventions and Research. J Med Internet Res 2024; 26:e51234. [PMID: 38815263 PMCID: PMC11176884 DOI: 10.2196/51234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 10/12/2023] [Accepted: 04/09/2024] [Indexed: 06/01/2024] Open
Abstract
Remote patient monitoring (RPM) enables clinicians to maintain and adjust their patients' plan of care by using remotely gathered data, such as vital signs, to proactively make medical decisions about a patient's care. RPM interventions have been touted as a means to improve patient care and well-being while reducing costs and resource needs within the health care ecosystem. However, multiple interworking components must be successfully implemented for an RPM intervention to yield the desired outcomes, and the design and key driver of each component can vary depending on the medical context. This viewpoint and perspective paper presents a 4-component RPM infrastructure framework based on a synthesis of existing literature and practice related to RPM. Specifically, these components are identified and considered: (1) data collection, (2) data transmission and storage, (3) data analysis, and (4) information presentation. Interaction points to consider between components include transmission, interoperability, accessibility, workflow integration, and transparency. Within each of the 4 components, questions affecting research and practice emerge that can affect the outcomes of RPM interventions. This framework provides a holistic perspective of the technologies involved in RPM interventions and how these core elements interact to provide an appropriate infrastructure for deploying RPM in health systems. Further, it provides a common vocabulary to compare and contrast RPM solutions across health contexts and may stimulate new research and intervention opportunities.
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Affiliation(s)
- Jennifer Claggett
- School of Business, Wake Forest University, Winston-Salem, NC, United States
- Center for Healthcare Innovation, School of Medicine, Wake Forest University, Winston-Salem, NC, United States
| | - Stacie Petter
- School of Business, Wake Forest University, Winston-Salem, NC, United States
| | - Amol Joshi
- School of Business, Wake Forest University, Winston-Salem, NC, United States
- Center for Healthcare Innovation, School of Medicine, Wake Forest University, Winston-Salem, NC, United States
| | - Todd Ponzio
- Health Science Center, University of Tennessee, Memphis, TN, United States
| | - Eric Kirkendall
- Center for Healthcare Innovation, School of Medicine, Wake Forest University, Winston-Salem, NC, United States
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Sheikhtaheri A, Tabatabaee Jabali SM, Bitaraf E, TehraniYazdi A, Kabir A. A near real-time electronic health record-based COVID-19 surveillance system: An experience from a developing country. HEALTH INF MANAG J 2024; 53:145-154. [PMID: 35838165 PMCID: PMC9289498 DOI: 10.1177/18333583221104213] [Citation(s) in RCA: 7] [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] [Accepted: 05/15/2022] [Indexed: 11/24/2022]
Abstract
CONTEXT Access to real-time data that provide accurate and timely information about the status and extent of disease spread could assist management of the COVID-19 pandemic and inform decision-making. AIM To demonstrate our experience with regard to implementation of technical and architectural infrastructure for a near real-time electronic health record-based surveillance system for COVID-19 in Iran. METHOD This COVID-19 surveillance system was developed from hospital information and electronic health record (EHR) systems available in the study hospitals in conjunction with a set of open-source solutions; and designed to integrate data from multiple resources to provide near real-time access to COVID-19 patients' data, as well as a pool of health data for analytical and decision-making purposes. OUTCOMES Using this surveillance system, we were able to monitor confirmed and suspected cases of COVID-19 in our population and to automatically notify stakeholders. Based on aggregated data collected, this surveillance system was able to facilitate many activities, such as resource allocation for hospitals, including managing bed allocations, providing and distributing equipment and funding, and setting up isolation centres. CONCLUSION Electronic health record systems and an integrated data analytics infrastructure are effective tools to enable policymakers to make better decisions, and for epidemiologists to conduct improved analyses regarding COVID-19. IMPLICATIONS Improved quality of clinical coding for better case finding, improved quality of health information in data sources, data-sharing agreements, and increased EHR coverage in the population can empower EHR-based COVID-19 surveillance systems.
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Affiliation(s)
- Abbas Sheikhtaheri
- Department of Health Information
Management, School of Health Management and Information Sciences, Iran University of Medical
Sciences, Tehran, Iran
| | | | - Ehsan Bitaraf
- Center for Statistics and
Information Technology, Iran University of Medical
Sciences, Tehran, Iran
| | - Alireza TehraniYazdi
- Center for Statistics and
Information Technology, Iran University of Medical
Sciences, Tehran, Iran
| | - Ali Kabir
- Minimally Invasive Surgery Research
Center, Iran University of Medical
Sciences, Tehran, Iran
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Kookal KK, Walji MF, Brandon R, Kivanc F, Mertz E, Kottek A, Mullins J, Liang S, Jenson LE, White JM. Systematically assessing the quality of dental electronic health record data for an investigation into oral health care disparities. J Public Health Dent 2024. [PMID: 38659337 DOI: 10.1111/jphd.12618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Revised: 03/27/2024] [Accepted: 04/11/2024] [Indexed: 04/26/2024]
Abstract
OBJECTIVES This work describes the process by which the quality of electronic health care data for a public health study was determined. The objectives were to adapt, develop, and implement data quality assessments (DQAs) based on the National Institutes of Health Pragmatic Trials Collaboratory (NIHPTC) data quality framework within the three domains of completeness, accuracy, and consistency, for an investigation into oral health care disparities of a preventive care program. METHODS Electronic health record data for eligible children in a dental accountable care organization of 30 offices, in Oregon, were extracted iteratively from January 1, 2014, through March 31, 2022. Baseline eligibility criteria included: children ages 0-18 with a baseline examination, Oregon home address, and either Medicaid or commercial dental benefits at least once between 2014 and 2108. Using the NIHPTC framework as a guide, DQAs were conducted throughout data element identification, extraction, staging, profiling, review, and documentation. RESULTS The data set included 91,487 subjects, 11 data tables comprising 75 data variables (columns), with a total of 6,861,525 data elements. Data completeness was 97.2%, the accuracy of EHR data elements in extracts was 100%, and consistency between offices was strong; 29 of 30 offices within 2 standard deviations of the mean (s = 94%). CONCLUSIONS The NIHPTC framework proved to be a useful approach, to identify, document, and characterize the dataset. The concepts of completeness, accuracy, and consistency were adapted by the multidisciplinary research team and the overall quality of the data are demonstrated to be of high quality.
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Affiliation(s)
- Krishna Kumar Kookal
- Technology Services and Informatics, School of Dentistry, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Muhammad F Walji
- Department of Clinical and Health Informatics, D. Bradley McWIlliams School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Ryan Brandon
- Willamette Dental Group and Skourtes Institute, Hillsboro, Oregon, USA
| | - Ferit Kivanc
- Willamette Dental Group and Skourtes Institute, Hillsboro, Oregon, USA
| | - Elizabeth Mertz
- Department of Preventive and Restorative Dental Sciences, University of California, San Francisco, California, USA
| | - Aubri Kottek
- Department of Preventive and Restorative Dental Sciences, University of California, San Francisco, California, USA
| | - Joanna Mullins
- Willamette Dental Group and Skourtes Institute, Hillsboro, Oregon, USA
| | - Shuang Liang
- Department of Preventive and Restorative Dental Sciences, University of California, San Francisco, California, USA
| | - Larry E Jenson
- Department of Preventive and Restorative Dental Sciences, University of California, San Francisco, California, USA
| | - Joel M White
- Department of Preventive and Restorative Dental Sciences, University of California, San Francisco, California, USA
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Lemas DJ, Du X, Rouhizadeh M, Lewis B, Frank S, Wright L, Spirache A, Gonzalez L, Cheves R, Magalhães M, Zapata R, Reddy R, Xu K, Parker L, Harle C, Young B, Louis-Jaques A, Zhang B, Thompson L, Hogan WR, Modave F. Classifying early infant feeding status from clinical notes using natural language processing and machine learning. Sci Rep 2024; 14:7831. [PMID: 38570569 PMCID: PMC10991582 DOI: 10.1038/s41598-024-58299-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 03/27/2024] [Indexed: 04/05/2024] Open
Abstract
The objective of this study is to develop and evaluate natural language processing (NLP) and machine learning models to predict infant feeding status from clinical notes in the Epic electronic health records system. The primary outcome was the classification of infant feeding status from clinical notes using Medical Subject Headings (MeSH) terms. Annotation of notes was completed using TeamTat to uniquely classify clinical notes according to infant feeding status. We trained 6 machine learning models to classify infant feeding status: logistic regression, random forest, XGBoost gradient descent, k-nearest neighbors, and support-vector classifier. Model comparison was evaluated based on overall accuracy, precision, recall, and F1 score. Our modeling corpus included an even number of clinical notes that was a balanced sample across each class. We manually reviewed 999 notes that represented 746 mother-infant dyads with a mean gestational age of 38.9 weeks and a mean maternal age of 26.6 years. The most frequent feeding status classification present for this study was exclusive breastfeeding [n = 183 (18.3%)], followed by exclusive formula bottle feeding [n = 146 (14.6%)], and exclusive feeding of expressed mother's milk [n = 102 (10.2%)], with mixed feeding being the least frequent [n = 23 (2.3%)]. Our final analysis evaluated the classification of clinical notes as breast, formula/bottle, and missing. The machine learning models were trained on these three classes after performing balancing and down sampling. The XGBoost model outperformed all others by achieving an accuracy of 90.1%, a macro-averaged precision of 90.3%, a macro-averaged recall of 90.1%, and a macro-averaged F1 score of 90.1%. Our results demonstrate that natural language processing can be applied to clinical notes stored in the electronic health records to classify infant feeding status. Early identification of breastfeeding status using NLP on unstructured electronic health records data can be used to inform precision public health interventions focused on improving lactation support for postpartum patients.
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Affiliation(s)
- Dominick J Lemas
- Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, 2004 Mowry Road, Clinical and Translational Research Building, Gainesville, FL, 32610, USA.
- Department of Obstetrics and Gynecology, University of Florida College of Medicine, Gainesville, FL, 32610, USA.
| | - Xinsong Du
- Division of General Internal Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
| | - Masoud Rouhizadeh
- Department of Pharmaceutical Outcomes and Policy, University of Florida College of Medicine, Gainesville, FL, 32610, USA
- Biomedical Informatics and Data Science Section, Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Braeden Lewis
- Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, 2004 Mowry Road, Clinical and Translational Research Building, Gainesville, FL, 32610, USA
| | - Simon Frank
- Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, 2004 Mowry Road, Clinical and Translational Research Building, Gainesville, FL, 32610, USA
| | - Lauren Wright
- Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, 2004 Mowry Road, Clinical and Translational Research Building, Gainesville, FL, 32610, USA
| | - Alex Spirache
- Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, 2004 Mowry Road, Clinical and Translational Research Building, Gainesville, FL, 32610, USA
| | - Lisa Gonzalez
- Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, 2004 Mowry Road, Clinical and Translational Research Building, Gainesville, FL, 32610, USA
| | - Ryan Cheves
- Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, 2004 Mowry Road, Clinical and Translational Research Building, Gainesville, FL, 32610, USA
| | - Marina Magalhães
- Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, 94305, USA
| | - Ruben Zapata
- Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, 2004 Mowry Road, Clinical and Translational Research Building, Gainesville, FL, 32610, USA
| | - Rahul Reddy
- Department of Computer and Information Science, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL, 32611, USA
| | - Ke Xu
- Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, 2004 Mowry Road, Clinical and Translational Research Building, Gainesville, FL, 32610, USA
| | - Leslie Parker
- Department of Biobehavioral Nursing Science, University of Florida College of Nursing, Gainesville, FL, 32603, USA
| | - Chris Harle
- Health Policy and Management Department, Richard M. Fairbanks School of Public Health, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202, USA
| | - Bridget Young
- Division of Breastfeeding and Lactation Medicine, University of Rochester Medical Center, Rochester, NY, 14642, USA
| | - Adetola Louis-Jaques
- Department of Obstetrics and Gynecology, University of Florida College of Medicine, Gainesville, FL, 32610, USA
| | - Bouri Zhang
- Health Science Center Libraries, University of Florida, Gainesville, FL, 32610, USA
| | - Lindsay Thompson
- Department of Pediatrics, Wake Forest School of Medicine, Winston-Salem, NC, 27101, USA
| | - William R Hogan
- Data Science Institute, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - François Modave
- Department of Anesthesiology, University of Florida College of Medicine, Gainesville, FL, 32610, USA
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Kumari R, Chander S. Improving healthcare quality by unifying the American electronic medical report system: time for change. Egypt Heart J 2024; 76:32. [PMID: 38489094 PMCID: PMC10942963 DOI: 10.1186/s43044-024-00463-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2023] [Accepted: 03/03/2024] [Indexed: 03/17/2024] Open
Abstract
BACKGROUND In recent years, innovation in healthcare technology has significantly improved the efficiency of the healthcare system. Advancements have led to better patient care and more cost-effective services. The electronic medical record (EMR) system, in particular, has enhanced interoperability and collaboration across healthcare departments by facilitating the exchange and utilization of patient data. The COVID-19 pandemic further accelerated this trend, leading to a surge in telemedicine services, which rely on electronic communication to deliver healthcare remotely. MAIN BODY Integrating artificial intelligence (AI) and machine learning (ML) in healthcare have been instrumental in analyzing vast data sets, allowing for identifying patterns and trends that can improve care delivery and pinpoint potential issues. The proposal of a unified EMR system in the USA aims to capitalize on these technological advancements. Such a system would streamline the sharing of patient information among healthcare providers, improve the quality and efficiency of care, and minimize the likelihood of errors in patient treatment. CONCLUSION A unified electronic medical record system represents a promising avenue for enhancing interoperability within the US healthcare sector. By creating a more connected and accessible network of patient information, it sets the stage for a transformation in healthcare delivery. This change is imperative for maintaining the momentum of progress in healthcare technology and realizing the full potential of recent advancements in patient care and system efficiency.
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Affiliation(s)
- Roopa Kumari
- Department of Pathology, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy PI, New York, NY, 10029, USA
| | - Subhash Chander
- Department of Pathology, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy PI, New York, NY, 10029, USA.
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16
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Secor AM, Célestin K, Jasmin M, Honoré JG, Wagner AD, Beima-Sofie K, Pintye J, Puttkammer N. Electronic Medical Record Data Missingness and Interruption in Antiretroviral Therapy Among Adults and Children Living With HIV in Haiti: Retrospective Longitudinal Study. JMIR Pediatr Parent 2024; 7:e51574. [PMID: 38488632 PMCID: PMC10986334 DOI: 10.2196/51574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 01/18/2024] [Accepted: 01/19/2024] [Indexed: 04/04/2024] Open
Abstract
Background Children (aged 0-14 years) living with HIV often experience lower rates of HIV diagnosis, treatment, and viral load suppression. In Haiti, only 63% of children living with HIV know their HIV status (compared to 85% overall), 63% are on treatment (compared to 85% overall), and 48% are virally suppressed (compared to 73% overall). Electronic medical records (EMRs) can improve HIV care and patient outcomes, but these benefits are largely dependent on providers having access to quality and nonmissing data. Objective We sought to understand the associations between EMR data missingness and interruption in antiretroviral therapy treatment by age group (pediatric vs adult). Methods We assessed associations between patient intake record data missingness and interruption in treatment (IIT) status at 6 and 12 months post antiretroviral therapy initiation using patient-level data drawn from iSanté, the most widely used EMR in Haiti. Missingness was assessed for tuberculosis diagnosis, World Health Organization HIV stage, and weight using a composite score indicator (ie, the number of indicators of interest missing). Risk ratios were estimated using marginal parameters from multilevel modified Poisson models with robust error variances and random intercepts for the facility to account for clustering. Results Data were drawn from 50 facilities and comprised 31,457 patient records from people living with HIV, of which 1306 (4.2%) were pediatric cases. Pediatric patients were more likely than adult patients to experience IIT (n=431, 33% vs n=7477, 23.4% at 6 months; P<.001). Additionally, pediatric patient records had higher data missingness, with 581 (44.5%) pediatric records missing at least 1 indicator of interest, compared to 7812 (25.9%) adult records (P<.001). Among pediatric patients, each additional indicator missing was associated with a 1.34 times greater likelihood of experiencing IIT at 6 months (95% CI 1.08-1.66; P=.008) and 1.24 times greater likelihood of experiencing IIT at 12 months (95% CI 1.05-1.46; P=.01). These relationships were not statistically significant for adult patients. Compared to pediatric patients with 0 missing indicators, pediatric patients with 1, 2, or 3 missing indicators were 1.59 (95% CI 1.26-2.01; P<.001), 1.74 (95% CI 1.02-2.97; P=.04), and 2.25 (95% CI 1.43-3.56; P=.001) times more likely to experience IIT at 6 months, respectively. Among adult patients, compared to patients with 0 indicators missing, having all 3 indicators missing was associated with being 1.32 times more likely to experience IIT at 6 months (95% CI 1.03-1.70; P=.03), while there was no association with IIT status for other levels of missingness. Conclusions These findings suggest that both EMR data quality and quality of care are lower for children living with HIV in Haiti. This underscores the need for further research into the mechanisms by which EMR data quality impacts the quality of care and patient outcomes among this population. Efforts to improve both EMR data quality and quality of care should consider prioritizing pediatric patients.
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Affiliation(s)
- Andrew M Secor
- Department of Global Health, University of Washington, Seattle, WA, United States
| | - Kemar Célestin
- Centre Haïtien pour le Renforcement du Système de Santé, Port-au-Prince, Haiti
| | - Margareth Jasmin
- Centre Haïtien pour le Renforcement du Système de Santé, Port-au-Prince, Haiti
| | - Jean Guy Honoré
- Centre Haïtien pour le Renforcement du Système de Santé, Port-au-Prince, Haiti
| | - Anjuli D Wagner
- Department of Global Health, University of Washington, Seattle, WA, United States
| | - Kristin Beima-Sofie
- Department of Global Health, University of Washington, Seattle, WA, United States
| | - Jillian Pintye
- Department of Global Health, University of Washington, Seattle, WA, United States
| | - Nancy Puttkammer
- International Training and Education Center for Health, Seattle, WA, United States
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17
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Zhang G, Liu X, Zeng Y. Advancements in oncology nursing: Embracing technology-driven innovations. Asia Pac J Oncol Nurs 2024; 11:100399. [PMID: 38465238 PMCID: PMC10920149 DOI: 10.1016/j.apjon.2024.100399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 01/31/2024] [Indexed: 03/12/2024] Open
Affiliation(s)
- Guolong Zhang
- Respiratory Intervention Center, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xuanhui Liu
- Department of Industrial Design, Hangzhou City University, Hangzhou, China
| | - Yingchun Zeng
- School of Medicine, Hangzhou City University, Hangzhou, China
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18
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Sushil M, Butte AJ, Schuit E, van Smeden M, Leeuwenberg AM. Cross-institution natural language processing for reliable clinical association studies: a methodological exploration. J Clin Epidemiol 2024; 167:111258. [PMID: 38219811 DOI: 10.1016/j.jclinepi.2024.111258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 12/21/2023] [Accepted: 01/08/2024] [Indexed: 01/16/2024]
Abstract
OBJECTIVES Natural language processing (NLP) of clinical notes in electronic medical records is increasingly used to extract otherwise sparsely available patient characteristics, to assess their association with relevant health outcomes. Manual data curation is resource intensive and NLP methods make these studies more feasible. However, the methodology of using NLP methods reliably in clinical research is understudied. The objective of this study is to investigate how NLP models could be used to extract study variables (specifically exposures) to reliably conduct exposure-outcome association studies. STUDY DESIGN AND SETTING In a convenience sample of patients admitted to the intensive care unit of a US academic health system, multiple association studies are conducted, comparing the association estimates based on NLP-extracted vs. manually extracted exposure variables. The association studies varied in NLP model architecture (Bidirectional Encoder Decoder from Transformers, Long Short-Term Memory), training paradigm (training a new model, fine-tuning an existing external model), extracted exposures (employment status, living status, and substance use), health outcomes (having a do-not-resuscitate/intubate code, length of stay, and in-hospital mortality), missing data handling (multiple imputation vs. complete case analysis), and the application of measurement error correction (via regression calibration). RESULTS The study was conducted on 1,174 participants (median [interquartile range] age, 61 [50, 73] years; 60.6% male). Additionally, up to 500 discharge reports of participants from the same health system and 2,528 reports of participants from an external health system were used to train the NLP models. Substantial differences were found between the associations based on NLP-extracted and manually extracted exposures under all settings. The error in association was only weakly correlated with the overall F1 score of the NLP models. CONCLUSION Associations estimated using NLP-extracted exposures should be interpreted with caution. Further research is needed to set conditions for reliable use of NLP in medical association studies.
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Affiliation(s)
- Madhumita Sushil
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, USA
| | - Atul J Butte
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, USA
| | - Ewoud Schuit
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Maarten van Smeden
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Artuur M Leeuwenberg
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
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19
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Moser K, Massag J, Frese T, Mikolajczyk R, Christoph J, Pushpa J, Straube J, Unverzagt S. German primary care data collection projects: a scoping review. BMJ Open 2024; 14:e074566. [PMID: 38382948 PMCID: PMC10882319 DOI: 10.1136/bmjopen-2023-074566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/23/2024] Open
Abstract
BACKGROUND The widespread use of electronic health records (EHRs) has led to a growing number of large routine primary care data collection projects globally, making these records a valuable resource for health services and epidemiological and clinical research. This scoping review aims to comprehensively assess and compare strengths and limitations of all German primary care data collection projects and relevant research publications that extract data directly from practice management systems (PMS). METHODS A literature search was conducted in the electronic databases in May 2021 and in June 2022. The search string included terms related to general practice, routine data, and Germany. The retrieved studies were classified as applied studies and methodological studies, and categorised by type of research, subject area, sample of publications, disease category, or main medication analysed. RESULTS A total of 962 references were identified, with 241 studies included from six German projects in which databases are populated by EHRs from PMS. The projects exhibited significant heterogeneity in terms of size, data collection methods, and variables collected. The majority of the applied studies (n = 205, 85%) originated from one database with a primary focus on pharmacoepidemiological topics (n = 127, 52%) including prescription patterns (n = 68, 28%) and studies about treatment outcomes, compliance, and treatment effectiveness (n = 34, 14%). Epidemiological studies (n = 77, 32%) mainly focused on incidence and prevalence studies (n = 41, 17%) and risk and comorbidity analysis studies (n = 31, 12%). Only 10% (n = 23) of studies were in the field of health services research, such as hospitalisation. CONCLUSION The development and durability of primary care data collection projects in Germany is hindered by insufficient public funding, technical issues of data extraction, and strict data protection regulations. There is a need for further research and collaboration to improve the usability of EHRs for health services and research.
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Affiliation(s)
- Konstantin Moser
- Medical Faculty of the Martin Luther University Halle-Wittenberg, Institute of General Practice and Family Medicine, Halle, Germany
- Medical Faculty of the Martin Luther University Halle-Wittenberg, Institute of Medical Epidemiology, Biometrics, and Informatics, Halle, Germany
| | - Janka Massag
- Medical Faculty of the Martin Luther University Halle-Wittenberg, Institute of Medical Epidemiology, Biometrics, and Informatics, Halle, Germany
| | - Thomas Frese
- Medical Faculty of the Martin Luther University Halle-Wittenberg, Institute of General Practice and Family Medicine, Halle, Germany
| | - Rafael Mikolajczyk
- Medical Faculty of the Martin Luther University Halle-Wittenberg, Institute of Medical Epidemiology, Biometrics, and Informatics, Halle, Germany
| | - Jan Christoph
- Medical Faculty of the Martin Luther University Halle-Wittenberg, Junior Research Group (Bio-)Medical Data Science, Halle, Germany
| | - Joshi Pushpa
- Medical Faculty of the Martin Luther University Halle-Wittenberg, Institute of General Practice and Family Medicine, Halle, Germany
| | - Johanna Straube
- Medical Faculty of the Martin Luther University Halle-Wittenberg, Institute of General Practice and Family Medicine, Halle, Germany
| | - Susanne Unverzagt
- Medical Faculty of the Martin Luther University Halle-Wittenberg, Institute of General Practice and Family Medicine, Halle, Germany
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Sadak KT, Aremu TO, Buttar S, Ly DV, Weigel B, Neglia JP. The Feasibility and Acceptability of a Data Capture Methodology in Pediatric Cancer Patients Treated with Targeted Agents and Immunotherapies. Curr Oncol 2024; 31:693-703. [PMID: 38392045 PMCID: PMC10887547 DOI: 10.3390/curroncol31020051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 01/07/2024] [Accepted: 01/23/2024] [Indexed: 02/24/2024] Open
Abstract
As childhood cancer treatments have improved to include new and innovative agents, the need for more advanced monitoring of their long-term effects and related research has increased. This has resulted in a need for evidence-based research methodologies for the longitudinal care of childhood cancer patients treated with targeted agents and immunotherapies. The rationale for this pilot study was to determine the feasibility and acceptability of a data capture methodology for pediatric, adolescent, and young adult cancer patients treated with targeted agents and immunotherapy as there is little research to inform this delivery of care. Data were collected from thirty-two patients and two providers for descriptive statistics and thematic analyses. Feasibility was characterized by expected participant attrition. Key drivers of acceptability were (1) providers' language and clarity of communication and (2) convenient participation requirements. Long-term follow-up research practices developed with input from key stakeholders, including patients, caregivers, and providers, can lead to acceptable and feasible research protocols that optimize successful participant recruitment. These evidence-based research practices can result in high participant satisfaction and can be implemented as program development initiatives across centers caring for childhood cancer survivors.
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Affiliation(s)
- Karim Thomas Sadak
- University of Minnesota Masonic Children’s Hospital, University of Minnesota Masonic Cancer Center, 420 Delaware St. SE—Mayo MMC 484, Minneapolis, MN 55455, USA; (T.O.A.); (S.B.); (D.V.L.); (B.W.); (J.P.N.)
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21
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Nivestam A, Haak M, Westergren A. Recommendations for healthy aging as documented by health professionals: a summative content analysis of health records. Prim Health Care Res Dev 2024; 24:e73. [PMID: 38193504 PMCID: PMC10790364 DOI: 10.1017/s1463423623000671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 09/11/2023] [Accepted: 11/19/2023] [Indexed: 01/10/2024] Open
Abstract
AIM To identify what type of recommendations were recorded in older adults' health records by health professionals during preventive home visits. BACKGROUND To promote health and prevent ill health, health professionals can give support and recommendations to older adults. The preventive home visit for older adults is one example of an intervention where health professionals such as nurses, social workers, and assistant nurses can give recommendations. By exploring what recommendations are recorded and within what areas, we can also gain knowledge about areas where provision of recommendations seems lacking. This knowledge would provide health professionals with guidance in their counseling with the older adult. METHODS Records from preventive home visits (n = 596; mean age 78.71) were qualitatively and quantitatively analyzed. FINDINGS The most frequently recorded recommendations were related to physical or mental illness, falls, and then nutrition. The results showed that recommendations could be sorted into ten sub-categories related to physical or mental illness, falls, nutrition, physical activity, preparation for the future, social participation, finances, getting help from others, municipal services, and security at home. These ten sub-categories were classified into the International Classification of Functioning, Disability, and Health categories body functions & structure (including one sub-category), activity (including four sub-categories), participation (including three sub-categories), and environmental factors (including two sub-categories). From the results, we could conclude that the major focus was on risk prevention and less focus was on health promotion. Thus, the visitor's recommendations most likely mirror the older adult's explicit needs 'here and now' to a great extent. However, health visitors also need to focus on intrinsic capacities to promote health. Besides recommendations relating to the person's intrinsic capacities, environmental aspects should be focused upon, to improve healthy aging.
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Affiliation(s)
- Anna Nivestam
- Faculty of Health Sciences, Kristianstad University, Kristianstad, Sweden
| | - Maria Haak
- Faculty of Health Sciences, Kristianstad University, Kristianstad, Sweden
| | - Albert Westergren
- Faculty of Health Sciences, Kristianstad University, Kristianstad, Sweden
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22
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Asiri S. Factors Influencing Electronic Health Record Workflow Integration Among Nurses in Saudi Arabia: Cross-Sectional Study. SAGE Open Nurs 2024; 10:23779608241260547. [PMID: 38836189 PMCID: PMC11149434 DOI: 10.1177/23779608241260547] [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: 12/11/2023] [Revised: 05/06/2024] [Accepted: 05/19/2024] [Indexed: 06/06/2024] Open
Abstract
Introduction Globally, healthcare organizations have transitioned from paper-based documentation to electronic health records (EHR), including in Saudi Arabia. However, the adoption of EHR at the national level in Saudi Arabia needs more attention. Thus, this study aimed to determine the workflow integration of EHR and associated factors. Objectives The specific aims were to examine the level of EHR use and workflow integration among nurses, to determine the differences in EHR use and workflow integration based on nurses' demographic characteristics, and to determine the association between the predictive factors and EHR workflow integration. Methods This is a cross-sectional, correlational descriptive study. The data were collected from 293 nurses using the convenience sampling method. The participating nurses completed a questionnaire that included two measures: the Information System Use Survey and the Workflow Integration Survey (WIS). The data were analyzed using descriptive and multivariate statistics with SPSS software. Results The nurses had a positive perception of EHR use and workflow. The EHR use scores differed based on workplace (P < .01), education level (P < .05), and area of practice (P < .001). Similarly, the EHR workflow integration scores varied according to workplace (P < .05), education level (P < .05), and area of practice (P < .001). Education level and workplace significantly predicted information system use. Furthermore, education level and information system use significantly predicted the EHR integration into nurses' workflow. Conclusion The nurses expressed a greater perceived use of EHR regarding the integrated health information system, which was a predictor of EHR integration into nurses' workflow.
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Affiliation(s)
- Saeed Asiri
- Nursing Administration and Education Department, College of Nursing, King Saud University, Riyadh, Saudi Arabia
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23
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Nickson D, Meyer C, Walasek L, Toro C. Prediction and diagnosis of depression using machine learning with electronic health records data: a systematic review. BMC Med Inform Decis Mak 2023; 23:271. [PMID: 38012655 PMCID: PMC10680172 DOI: 10.1186/s12911-023-02341-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 10/15/2023] [Indexed: 11/29/2023] Open
Abstract
BACKGROUND Depression is one of the most significant health conditions in personal, social, and economic impact. The aim of this review is to summarize existing literature in which machine learning methods have been used in combination with Electronic Health Records for prediction of depression. METHODS Systematic literature searches were conducted within arXiv, PubMed, PsycINFO, Science Direct, SCOPUS and Web of Science electronic databases. Searches were restricted to information published after 2010 (from 1st January 2011 onwards) and were updated prior to the final synthesis of data (27th January 2022). RESULTS Following the PRISMA process, the initial 744 studies were reduced to 19 eligible for detailed evaluation. Data extraction identified machine learning methods used, types of predictors used, the definition of depression, classification performance achieved, sample size, and benchmarks used. Area Under the Curve (AUC) values more than 0.9 were claimed, though the average was around 0.8. Regression methods proved as effective as more developed machine learning techniques. LIMITATIONS The categorization, definition, and identification of the numbers of predictors used within models was sometimes difficult to establish, Studies were largely Western Educated Industrialised, Rich, Democratic (WEIRD) in demography. CONCLUSION This review supports the potential use of machine learning techniques with Electronic Health Records for the prediction of depression. All the selected studies used clinically based, though sometimes broad, definitions of depression as their classification criteria. The reported performance of the studies was comparable to or even better than that found in primary care. There are concerns with generalizability and interpretability.
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Affiliation(s)
| | - Caroline Meyer
- Warwick Medical School, University of Warwick, Coventry, UK
| | - Lukasz Walasek
- Department of Psychology, University of Warwick, Coventry, UK
| | - Carla Toro
- Warwick Medical School, University of Warwick, Coventry, UK
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Vanderlaan J, Jefferson K. Evaluation of a method to identify midwives in national provider identifier data. BMC Pregnancy Childbirth 2023; 23:809. [PMID: 37993806 PMCID: PMC10664267 DOI: 10.1186/s12884-023-06122-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 11/11/2023] [Indexed: 11/24/2023] Open
Abstract
OBJECTIVES Comparison of national midwife workforce data from the National Provider Identifier file determined it undercounted midwives compared to national data available from the American Midwifery Certification Board. This undercount may be due to the existence of three taxonomy categories for midwives when registering for the National Provider Identifier. The objective of this study was to obtain an accurate count of advanced practice midwives using the National Provider Identifier Data. METHODS A recode strategy was created using the NPPES Data Dissemination File for November 7, 2021. The strategy identified advanced practice midwives using education and certification information provided in the "credentials" field. The strategy was validated using the NPPES Data Dissemination File for August 7, 2022 and the gold standard was the American Midwifery Certification Board count of midwives by state for August, 2022. Validation compared the accuracy and precision of the recode to the accuracy and precision of using the advanced practice midwife taxonomy category. RESULTS The recode strategy improved the accuracy and precision of the count of advanced practice midwives compared to the identification of advanced practice midwives using the advanced practice midwife taxonomy category. CONCLUSIONS FOR PRACTICE Recoding the NPPES Data Dissemination File provides a more accurate and precise count of advanced practice midwives than relying on the existing advanced practice midwife taxonomy classification. Researchers can use the NPPES Data Dissemination File when studying the midwifery workforce.
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Affiliation(s)
- Jennifer Vanderlaan
- University of Nevada Las Vegas School of Nursing, 4505 S. Maryland Parkway, Box 453018, Las Vegas, NV, 89154-3018, USA.
| | - Karen Jefferson
- American College of Nurse-Midwives, 409 12Th St SW, Suite 600, Washington, DC, 20024-2188, USA
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Obeid S, Mashiach-Eizenberg M, Gur A, Lavy I. Examining Ethnic Disparities in Digital Healthcare Services Utilization: Insights from Israel. J Multidiscip Healthc 2023; 16:3533-3544. [PMID: 38024120 PMCID: PMC10661913 DOI: 10.2147/jmdh.s429121] [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: 08/22/2023] [Accepted: 10/24/2023] [Indexed: 12/01/2023] Open
Abstract
Purpose The purpose of this study was to examine ethnic disparities in the utilization of digital healthcare services (DHS) in Israel and explore the characteristics and factors influencing DHS use among the Arab minority and Jewish majority populations. Methods A cross-sectional correlational design was employed to collect data from 606 Israeli participants, 445 Jews, and 161 Arabs. Participants completed a digital questionnaire that assessed DHS utilization, digital health literacy, attitudes towards DHS, and demographic variables. Results The findings reveal significant disparities in DHS utilization and attitudes between these ethnic groups, with Jewish participants demonstrating higher rates of utilization and positive attitudes toward DHS. The study also explores the predictive role of digital health literacy and attitudes in DHS use while considering ethnicity as a potential moderator. Significant predicting factors related to DHS utilization among Jews include positive attitudes and high health literacy. Among the Arabs, only attitudes towards DHS significantly predict the extent of DHS use. Digital health literacy affects the extent of use through attitudes at the two groups of the moderator significantly, but it is stronger among the Arab group. Conclusion To improve healthcare outcomes and reduce disparities, efforts should focus on ensuring equitable access to DHS for the Arab minority population. Targeted interventions, including digital literacy education, removing technology access barriers, offering services in Arabic, and collaborating with community organizations, can help bridge the gap and promote equal utilization of DHS.
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Affiliation(s)
- Samira Obeid
- Department of Nursing, The Max Stern Yezreel Valley College, Yezreel Valley, Israel
- Public Health Research Department, North District, the Ministry of Health, Nof Hagalil, Israel
| | - Michal Mashiach-Eizenberg
- Department of Health Systems Management, The Max Stern Yezreel Valley College, Yezreel Valley, Israel
| | - Amit Gur
- Department of Health Systems Management, The Max Stern Yezreel Valley College, Yezreel Valley, Israel
| | - Ilana Lavy
- Department of Information Systems, The Max Stern Yezreel Valley College, Yezreel Valley, Israel
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Sampaio VS, Lopes R, Ozahata MC, Nakaya HI, Sousa E, Araújo JD, Bragatte MA, Brito AF, Grespan RMZ, Capuani MLD, Domingues HH, Pellini ACG, Mateos SDOG, Conde MTRP, Eudes Leal F, Sabino E, Simão M, Kalil J. Thinking out of the box: revisiting health surveillance based on medical records. ANTIMICROBIAL STEWARDSHIP & HEALTHCARE EPIDEMIOLOGY : ASHE 2023; 3:e185. [PMID: 38028896 PMCID: PMC10654951 DOI: 10.1017/ash.2023.451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 08/12/2023] [Indexed: 12/01/2023]
Abstract
Despite the considerable advances in the last years, the health information systems for health surveillance still need to overcome some critical issues so that epidemic detection can be performed in real time. For instance, despite the efforts of the Brazilian Ministry of Health (MoH) to make COVID-19 data available during the pandemic, delays due to data entry and data availability posed an additional threat to disease monitoring. Here, we propose a complementary approach by using electronic medical records (EMRs) data collected in real time to generate a system to enable insights from the local health surveillance system personnel. As a proof of concept, we assessed data from São Caetano do Sul City (SCS), São Paulo, Brazil. We used the "fever" term as a sentinel event. Regular expression techniques were applied to detect febrile diseases. Other specific terms such as "malaria," "dengue," "Zika," or any infectious disease were included in the dictionary and mapped to "fever." Additionally, after "tokenizing," we assessed the frequencies of most mentioned terms when fever was also mentioned in the patient complaint. The findings allowed us to detect the overlapping outbreaks of both COVID-19 Omicron BA.1 subvariant and Influenza A virus, which were confirmed by our team by analyzing data from private laboratories and another COVID-19 public monitoring system. Timely information generated from EMRs will be a very important tool to the decision-making process as well as research in epidemiology. Quality and security on the data produced is of paramount importance to allow the use by health surveillance systems.
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Affiliation(s)
- Vanderson S. Sampaio
- Instituto Todos pela Saúde, São Paulo, Brazil
- Fundação de Medicina Tropical Dr. Heitor Vieira Dourado, Manaus, Brazil
- School of Health Sciences, Amazonas State University, Manaus, Brazil
| | | | | | - Helder I. Nakaya
- Instituto Todos pela Saúde, São Paulo, Brazil
- Hospital Israelita Albert Einstein, São Paulo, Brazil
| | - Erick Sousa
- Instituto Todos pela Saúde, São Paulo, Brazil
- Telehealth Group, School of Medicine, Federal University of Goiás, Goiás, Brazil
| | | | - Marcelo A.S. Bragatte
- Instituto Todos pela Saúde, São Paulo, Brazil
- Capixaba Institute for Teaching, Research and Innovation in Health (ICEPi), Espírito Santo, Brazil
| | | | - Regina Maura Zettoni Grespan
- Municipal University of São Caetano do Sul, São Caetano do Sul, São Paulo, Brazil
- Secretary of Health of The Municipality of São Caetano do Sul, São Paulo, Brazil
| | | | | | | | | | | | - Fabio Eudes Leal
- Municipal University of São Caetano do Sul, São Caetano do Sul, São Paulo, Brazil
| | - Ester Sabino
- Instituto Todos pela Saúde, São Paulo, Brazil
- Instituto de Medicina Tropical da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | | | - Jorge Kalil
- Instituto Todos pela Saúde, São Paulo, Brazil
- Hospital Israelita Albert Einstein, São Paulo, Brazil
- Laboratory of Clinical Immunology and Allergy-LIM60/University of Sao Paulo School of Medicine, São Paulo, Brazil
- Institute for Investigation in Immunology - iii-INCT, São Paulo, Brazil
- Laboratory of Immunology, Heart Institute, University of São Paulo School of Medicine, São Paulo, Brazil
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Anand G, Sadhna D. Electronic health record interoperability using FHIR and blockchain: A bibliometric analysis and future perspective. Perspect Clin Res 2023; 14:161-166. [PMID: 38025292 PMCID: PMC10679575 DOI: 10.4103/picr.picr_272_22] [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: 12/26/2022] [Revised: 03/13/2023] [Accepted: 03/15/2023] [Indexed: 12/01/2023] Open
Abstract
Electronic health records (EHRs) constitute vital statistics, current health condition, ongoing therapies, and patient data; hence, their interoperability could be useful for epidemiologic and clinical research. Fast Healthcare Interoperability Resources (FHIR) and blockchain are currently "in-use" and tested for exchange of such data. The annual scientific production of publications for both FHIR and blockchain shows steady growth. The data interoperability and electronic data interchange have been introduced in the field of EHR in 2020, hence inferring that data interoperability is relatively a new domain. The thematic mapping suggested "interoperability" of EHR is well-developed and important for the structure of the research field.
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Affiliation(s)
- Gaurav Anand
- Medical Writing, Tata Consultancy Services, Noida, Uttar Pradesh, India
| | - Divya Sadhna
- Medical Writing, Tata Consultancy Services, Noida, Uttar Pradesh, India
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Riihimies R, Kosunen E, Koskela TH. Segmenting Patients With Diabetes With the Navigator Service in Primary Care and a Description of the Self-Acting Patient Group: Cross-Sectional Study. J Med Internet Res 2023; 25:e40560. [PMID: 37682585 PMCID: PMC10517389 DOI: 10.2196/40560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 05/02/2023] [Accepted: 06/26/2023] [Indexed: 09/09/2023] Open
Abstract
BACKGROUND The aim of patient segmentation is to recognize patients with similar health care needs. The Finnish patient segmentation service Navigator segregates patients into 4 groups, including a self-acting group, who presumably manages their everyday life and coordinates their health care. Digital services could support their self-care. Knowledge on self-acting patients' characteristics is lacking. OBJECTIVE The study aims are to describe how Navigator assigns patients with diabetes to the 4 groups at nurses' appointments at a health center, the self-acting patient group's characteristics compared with other patient groups, and the concordance between the nurse's evaluation of the patient's group and the actual group assigned by Navigator (criterion validity). METHODS Patients with diabetes ≥18 years old visiting primary care were invited to participate in this cross-sectional study. Patients with disability preventing informed consent for participation were excluded. Nurses estimated the patients' upcoming group results before the appointment. We describe the concordance (%) between the evaluation and actual groups. Nurses used Navigator patients with diabetes (n=304) at their annual follow-up visits. The self-acting patients' diabetes care values (glycated hemoglobin [HbA1c], urine albumin to creatinine ratio, low-density lipoprotein cholesterol, blood pressure, BMI), chronic conditions, medication, smoking status, self-rated health, disability (World Health Organization Disability Assessment Schedule [WHODAS] 2.0), health-related quality of life (EQ-5D-5L), and well-being (Well-being Questionnaire [WBQ-12]) and the patients' responses to Navigator's question concerning their digital skills as outcome variables were compared with those of the other patients. We used descriptive statistics for the patients' distribution into the 4 groups and demographic data. We used the Mann-Whitney U test with nonnormally distributed variables, independent samples t test with normally distributed variables, and Pearson chi-square tests with categorized variables to compare the groups. RESULTS Most patients (259/304, 85.2%) were in the self-acting group. Hypertension, hyperlipidemia, and joint ailments were the most prevalent comorbidities among all patients. Self-acting patients had less ischemic cardiac disease (P=.001), depression or anxiety (P=.03), asthma or chronic obstructive pulmonary disease (P<.001), long-term pain (P<.001), and related medication. Self-acting patients had better self-rated health (P<.001), functional ability (P<.001), health-related quality of life (P<.001), and general well-being (P<.001). All patients considered their skills at using electronic services to be good. CONCLUSIONS The patients in the self-acting group had several comorbidities. However, their functional ability was not yet diminished compared with patients in the other groups. Therefore, to prevent diabetic complications and disabilities, support for patients' self-management should be emphasized in their integrated care services. Digital services could be involved in the care of patients willing to use them. The study was performed in 1 health center, the participants were volunteers, and most patients were assigned to self-acting patient group. These facts limit the generalizability of our results. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) RR2-10.2196/20570.
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Affiliation(s)
- Riikka Riihimies
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Elise Kosunen
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Tuomas H Koskela
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Center of General Practice, Tampere University Hospital, Tampere, Finland
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Marlow N, Eckert M, Sharplin G, Gwilt I, Carson-Chahhoud K. Graphical User Interface Development for a Hospital-Based Predictive Risk Tool: Protocol for a Co-Design Study. JMIR Res Protoc 2023; 12:e47717. [PMID: 37651166 PMCID: PMC10502603 DOI: 10.2196/47717] [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: 03/29/2023] [Revised: 06/21/2023] [Accepted: 06/27/2023] [Indexed: 09/01/2023] Open
Abstract
BACKGROUND This co-design research method details the iterative process developed to identify health professional recommendations for the graphical user interface (GUI) of an artificial intelligence (AI)-enabled risk prediction tool. Driving the decision to include a co-design process is the belief that choices regarding the aesthetic and functionality of an intervention are best made by its intended users and that engaging these users in its design will promote the tool's adoption and use. OBJECTIVE The aim of this research is to identify health professional design and uptake recommendations for the GUI of an AI-enabled predictive risk tool. METHODS We will hold 3 research phases, each consisting of 2 workshops with health professionals, between mid-2023 and mid-2024. A total of 6 health professionals will be sought per workshop, resulting in a total enrollment of 36 health professionals at the conclusion of the research. A total of 7 workshop activities have been scheduled across the 3 workshops; these include context of use, notifiers, format, AI survey-Likert, prototype, AI survey-written, and testing. The first 6 of these activities will be repeated in each workshop to enable the iterative development and refinement of GUI. The last activity (testing) will be performed in the final workshop to examine health professionals' thoughts on the final GUI iteration. Qualitative and quantitative results data will be produced from tasks in each research activity. Qualitative data will be examined through inductive thematic analysis or deductive thematic analysis in accordance with the Nonadoption, Abandonment, and Challenges to the Scale-up, Spread, and Sustainability (NASSS) framework; visual data will be examined in accordance with "framework of interactivity;" and quantitative data will be examined using descriptive statistics. RESULTS Project registration with the Australia and New Zealand Clinical Trial Registry has been requested (#384098). Finalized design recommendations are expected in early to mid-2024, with a results manuscript to be submitted in mid-2024. This research method has human research ethics approval from the South Australian Department of Health and Wellbeing (#2022/HRE00131) as well as from the Human Research Ethics Committee of the University of South Australia (application ID#204143). CONCLUSIONS Understanding whether an intervention is needed in a particular situation is just the start; designing an intervention so that it is used within that situation is paramount. This co-design process engages end users to create a GUI that includes the aesthetic and functional details they need in a manner that aligns with their existing work practices. Indeed, interventions that fail to do this may be disliked, and at worst, they may be dangerous. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) PRR1-10.2196/47717.
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Affiliation(s)
| | | | | | - Ian Gwilt
- University of South Australia, Adelaide, Australia
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Hosch R, Baldini G, Parmar V, Borys K, Koitka S, Engelke M, Arzideh K, Ulrich M, Nensa F. FHIR-PYrate: a data science friendly Python package to query FHIR servers. BMC Health Serv Res 2023; 23:734. [PMID: 37415138 DOI: 10.1186/s12913-023-09498-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 05/03/2023] [Indexed: 07/08/2023] Open
Abstract
BACKGROUND We present FHIR-PYrate, a Python package to handle the full clinical data collection and extraction process. The software is to be plugged into a modern hospital domain, where electronic patient records are used to handle the entire patient's history. Most research institutes follow the same procedures to build study cohorts, but mainly in a non-standardized and repetitive way. As a result, researchers spend time writing boilerplate code, which could be used for more challenging tasks. METHODS The package can improve and simplify existing processes in the clinical research environment. It collects all needed functionalities into a straightforward interface that can be used to query a FHIR server, download imaging studies and filter clinical documents. The full capacity of the search mechanism of the FHIR REST API is available to the user, leading to a uniform querying process for all resources, thus simplifying the customization of each use case. Additionally, valuable features like parallelization and filtering are included to make it more performant. RESULTS As an exemplary practical application, the package can be used to analyze the prognostic significance of routine CT imaging and clinical data in breast cancer with tumor metastases in the lungs. In this example, the initial patient cohort is first collected using ICD-10 codes. For these patients, the survival information is also gathered. Some additional clinical data is retrieved, and CT scans of the thorax are downloaded. Finally, the survival analysis can be computed using a deep learning model with the CT scans, the TNM staging and positivity of relevant markers as input. This process may vary depending on the FHIR server and available clinical data, and can be customized to cover even more use cases. CONCLUSIONS FHIR-PYrate opens up the possibility to quickly and easily retrieve FHIR data, download image data, and search medical documents for keywords within a Python package. With the demonstrated functionality, FHIR-PYrate opens an easy way to assemble research collectives automatically.
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Affiliation(s)
- René Hosch
- Institute of Interventional and Diagnostic Radiology and Neuroradiology, University Hospital Essen, Hufelandstraße 55, Essen, 45147, Germany
- Institute for Artificial Intelligence in Medicine, University Hospital Essen, Girardetstraße 2, Essen, 45131, Germany
| | - Giulia Baldini
- Institute of Interventional and Diagnostic Radiology and Neuroradiology, University Hospital Essen, Hufelandstraße 55, Essen, 45147, Germany.
- Institute for Artificial Intelligence in Medicine, University Hospital Essen, Girardetstraße 2, Essen, 45131, Germany.
| | - Vicky Parmar
- Institute of Interventional and Diagnostic Radiology and Neuroradiology, University Hospital Essen, Hufelandstraße 55, Essen, 45147, Germany
- Institute for Artificial Intelligence in Medicine, University Hospital Essen, Girardetstraße 2, Essen, 45131, Germany
| | - Katarzyna Borys
- Institute of Interventional and Diagnostic Radiology and Neuroradiology, University Hospital Essen, Hufelandstraße 55, Essen, 45147, Germany
- Institute for Artificial Intelligence in Medicine, University Hospital Essen, Girardetstraße 2, Essen, 45131, Germany
| | - Sven Koitka
- Institute of Interventional and Diagnostic Radiology and Neuroradiology, University Hospital Essen, Hufelandstraße 55, Essen, 45147, Germany
- Institute for Artificial Intelligence in Medicine, University Hospital Essen, Girardetstraße 2, Essen, 45131, Germany
| | - Merlin Engelke
- Institute of Interventional and Diagnostic Radiology and Neuroradiology, University Hospital Essen, Hufelandstraße 55, Essen, 45147, Germany
- Institute for Artificial Intelligence in Medicine, University Hospital Essen, Girardetstraße 2, Essen, 45131, Germany
| | - Kamyar Arzideh
- Institute for Artificial Intelligence in Medicine, University Hospital Essen, Girardetstraße 2, Essen, 45131, Germany
- Central IT Department, Data Integration Center, University Hospital Essen, Hufelandstraße 55, Essen, 45147, Germany
| | - Moritz Ulrich
- Institute for Artificial Intelligence in Medicine, University Hospital Essen, Girardetstraße 2, Essen, 45131, Germany
- Central IT Department, Data Integration Center, University Hospital Essen, Hufelandstraße 55, Essen, 45147, Germany
| | - Felix Nensa
- Institute of Interventional and Diagnostic Radiology and Neuroradiology, University Hospital Essen, Hufelandstraße 55, Essen, 45147, Germany
- Institute for Artificial Intelligence in Medicine, University Hospital Essen, Girardetstraße 2, Essen, 45131, Germany
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Kavya R, Kala A, Christopher J, Panda S, Lazarus B. DAAR: Drift Adaption and Alternatives Ranking approach for interpretable clinical decision support systems. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2023.104793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
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Zhao S, Li H, Jing X, Zhang X, Li R, Li Y, Liu C, Chen J, Li G, Zheng W, Li Q, Wang X, Wang L, Sun Y, Xu Y, Wang S. Identifying subgroups of patients with type 2 diabetes based on real-world traditional chinese medicine electronic medical records. Front Pharmacol 2023; 14:1210667. [PMID: 37456755 PMCID: PMC10339739 DOI: 10.3389/fphar.2023.1210667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Accepted: 06/15/2023] [Indexed: 07/18/2023] Open
Abstract
Introduction: Type 2 diabetes (T2D) is a multifactorial complex chronic disease with a high prevalence worldwide, and Type 2 diabetes patients with different comorbidities often present multiple phenotypes in the clinic. Thus, there is a pressing need to improve understanding of the complexity of the clinical Type 2 diabetes population to help identify more accurate disease subtypes for personalized treatment. Methods: Here, utilizing the traditional Chinese medicine (TCM) clinical electronic medical records (EMRs) of 2137 Type 2 diabetes inpatients, we followed a heterogeneous medical record network (HEMnet) framework to construct heterogeneous medical record networks by integrating the clinical features from the electronic medical records, molecular interaction networks and domain knowledge. Results: Of the 2137 Type 2 diabetes patients, 1347 were male (63.03%), and 790 were female (36.97%). Using the HEMnet method, we obtained eight non-overlapping patient subgroups. For example, in H3, Poria, Astragali Radix, Glycyrrhizae Radix et Rhizoma, Cinnamomi Ramulus, and Liriopes Radix were identified as significant botanical drugs. Cardiovascular diseases (CVDs) were found to be significant comorbidities. Furthermore, enrichment analysis showed that there were six overlapping pathways and eight overlapping Gene Ontology terms among the herbs, comorbidities, and Type 2 diabetes in H3. Discussion: Our results demonstrate that identification of the Type 2 diabetes subgroup based on the HEMnet method can provide important guidance for the clinical use of herbal prescriptions and that this method can be used for other complex diseases.
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Affiliation(s)
- Shuai Zhao
- Department of Endocrinology, Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Hengfei Li
- Department of Infectious Diseases, Hubei Provincial Hospital of Traditional Chinese Medicine (Affiliated Hospital of Hubei University of Chinese Medicine, Hubei Province Academy of Traditional Chinese Medicine), Wuhan, China
| | - Xuan Jing
- Hebei Provincial Hospital of Traditional Chinese Medicine, Shijiazhuang, China
| | - Xuebin Zhang
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China
| | - Ronghua Li
- Department of Endocrinology, Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Yinghao Li
- Institute of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Chenguang Liu
- Department of Endocrinology, Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Jie Chen
- Department of Endocrinology, Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Guoxia Li
- Department of Endocrinology, Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Wenfei Zheng
- Department of Endocrinology, Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Qian Li
- Department of Nursing, Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Xue Wang
- Department of Endocrinology, Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Letian Wang
- Institute of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Yuanyuan Sun
- Department of Obstetrics and Gynecology, Weifang Fangzi District People’s Hospital, Weifang, China
| | - Yunsheng Xu
- Department of Endocrinology, Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Shihua Wang
- Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China
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Husain AN, Eiden E, Vesoulis ZA. Use of an electronic medical record to optimize a neonatal sepsis score for mortality prediction. J Perinatol 2023; 43:746-751. [PMID: 36450852 PMCID: PMC10580075 DOI: 10.1038/s41372-022-01573-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 11/17/2022] [Accepted: 11/24/2022] [Indexed: 12/03/2022]
Abstract
OBJECTIVE Late-onset sepsis (LOS) is a significant cause of mortality in preterm infants. The neonatal sequential organ failure assessment (nSOFA) provides an objective assessment of sepsis risk but requires manual calculation. We developed an EMR pipeline to automate nSOFA calculation for more granular analysis of score performance and to identify optimal alerting thresholds. METHODS Infants born <33 weeks of gestation with LOS were included. A SQL-based pipeline calculated hourly nSOFA scores 48 h before/after sepsis evaluation. Sensitivity analysis identified the optimal timing and threshold of nSOFA for LOS mortality. RESULTS Eighty episodes of LOS were identified (67 survivors, 13 non-survivor). Non-survivors had persistently elevated nSOFA scores, markedly increasing 12 h prior to culture. At sepsis evaluation, the AUC for nSOFA >2 was 0.744 (p = 0.0047); thresholds of >3 and >4 produced lower AUCs. CONCLUSIONS nSOFA is persistently elevated for infants with LOS mortality compared to survivors with an optimal alert threshold >2.
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Affiliation(s)
- Ameena N Husain
- Department of Pediatrics, Division of Newborn Medicine, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Elise Eiden
- Institute for Informatics, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Zachary A Vesoulis
- Department of Pediatrics, Division of Newborn Medicine, Washington University School of Medicine, St. Louis, MO, 63110, USA.
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Vasilica C, Wynn M, Davis D, Charnley K, Garwood-Cross L. The digital future of nursing: making sense of taxonomies and key concepts. BRITISH JOURNAL OF NURSING (MARK ALLEN PUBLISHING) 2023; 32:442-446. [PMID: 37173087 DOI: 10.12968/bjon.2023.32.9.442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Digital technology is becoming increasingly common in routine nursing practice. The adoption of digital technologies such as video calling, and other digital communication, has been hastened by the recent COVID-19 pandemic. Use of these technologies has the potential to revolutionise nursing practice, leading to potentially more accurate patient assessment, monitoring processes and improved safety in clinical areas. This article outlines key concepts related to the digitalisation of health care and the implications for nursing practice. The aim of this article is to encourage nurses to consider the implications, opportunities and challenges associated with the move towards digitalisation and advances in technology. Specifically, this means understanding key digital developments and innovations associated with healthcare provision and appreciating the implications of digitalisation for the future of nursing practice.
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Affiliation(s)
- Cristina Vasilica
- Reader, Digital Health, School of Health and Society, University of Salford, Salford
| | - Matthew Wynn
- Lecturer, Adult Nursing, School of Health and Society, University of Salford, Salford
| | - Dilla Davis
- Lecturer, Adult Nursing, School of Health and Society, University of Salford, Salford
| | - Kyle Charnley
- Lecturer, Mental Health Nursing, School of Health and Society, University of Salford, Salford
| | - Lisa Garwood-Cross
- Research Fellow, Digital Health, School of Health and Society, University of Salford, Salford
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Alhalabi MM. Mortality and risk factors associated with peptic ulcer bleeding among adult inpatients of Damascus Hospital, Syria: A cross-sectional study. Medicine (Baltimore) 2023; 102:e33699. [PMID: 37115046 PMCID: PMC10145724 DOI: 10.1097/md.0000000000033699] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 04/06/2023] [Accepted: 04/14/2023] [Indexed: 04/29/2023] Open
Abstract
Peptic ulcer bleeding is associated with significant morbidity and mortality, while monitoring mortality is extremely beneficial to public health, and the latest estimates date back to 2010 for the Syrian population. This study aims to estimate the in-hospital mortality rate and risk factors associated with peptic ulcer bleeding among adult inpatients at Damascus Hospital, Syria. A cross-sectional study with systematic random sampling. Sample size (n) was calculated using the proportional equation: [n = Z2P (1 - P)/d2], with the following hypothesis: Z = 1.96 for the 95% confidence level, P = .253 for mortality in patients hospitalized with complicated peptic ulcers, a margin of error (d) = 0.05, 290 charts were reviewed, and the Chi-square test (χ2 test) was used for categorical variables, and the t test for continuous data. We reported the odds ratio in addition to mean and standard deviation with a 95% confidence. A P value less than .05 was considered statistically significant. Data were analyzed using a statistical package for the social sciences (SPSS). The mortality rate was 3.4%, and the mean age was 61.76 ± 16.02 years. The most frequent comorbidities were hypertension, diabetes mellitus, and ischemic heart disease. The most commonly used medications were NSAIDs, aspirin, and clopidogrel. 74 patients (25.52%) were using aspirin with no documented indication P < .01, odds ratio = 6.541, 95% CI [2.612-11.844]. There were 162 (56%) Smokers. Six patients (2.1%) suffered from recurrent bleeding, and 13 (4.5%) needed surgery. Raising awareness about the risks of using non-steroidal anti-inflammatory drugs may reduce the occurrence of peptic ulcers and, as a result, peptic ulcer complications. Larger, nationwide studies are needed to estimate the real mortality rate in complicated peptic ulcer patients in Syria. There is a lack of some critical data in the patients' charts, which necessitates action to correct.
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Tang G, Izumi K, Izumisawa M, Koyama S. Japanese Consumers' Attitudes towards Obtaining and Sharing Health Information Regarding Over-the-Counter Medication: Designing an Over-the-Counter Electronic Health Record. Healthcare (Basel) 2023; 11:healthcare11081166. [PMID: 37108000 PMCID: PMC10138617 DOI: 10.3390/healthcare11081166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 04/11/2023] [Accepted: 04/17/2023] [Indexed: 04/29/2023] Open
Abstract
Designing an over-the-counter medication electronic health record (OTC-EHR) may help improve OTC usage. An online survey for the conceptual OTC-EHR design examined participant characteristics, attitudes towards obtaining user-shared OTC medication information, health-related application usage, and the inclination to share anonymized health information. Descriptive statistics, tests to assess statistical significance, and text mining were used to analyze the results. The findings revealed that Japanese consumers, particularly those with high eHealth literacy and women, possess relatively positive attitudes towards obtaining user-shared OTC medication information than those with low eHealth literacy (t (280.71) = -4.11, p < 0.001) and men (t (262.26) = -2.78, p = 0.006), respectively. Most consumers own smartphones but do not use health-related applications. A minority held positive attitudes about sharing anonymized health information. The perceived helpfulness of OTC-EHR was positively associated with the usage of health-related applications (χ2 (4) = 18.35, p = 0.001) and attitude towards sharing anonymized health information (χ2 (3) = 19.78, p < 0.001). The study findings contribute towards OTC-EHR's design to enhance consumers' self-medication and reduce risks, while the psychological barriers to sharing anonymized health information should be improved by increasing the OTC-EHR's penetration rate and engaging in appropriate information design.
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Affiliation(s)
- Guyue Tang
- Graduate School of Comprehensive Human Sciences, University of Tsukuba, Ibaraki 305-8577, Japan
| | - Kairi Izumi
- Graduate School of Comprehensive Human Sciences, University of Tsukuba, Ibaraki 305-8577, Japan
| | | | - Shinichi Koyama
- Graduate School of Comprehensive Human Sciences, University of Tsukuba, Ibaraki 305-8577, Japan
- Faculty of Art and Design, University of Tsukuba, Ibaraki 305-8574, Japan
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Mahajan HB, Junnarkar AA. Smart healthcare system using integrated and lightweight ECC with private blockchain for multimedia medical data processing. MULTIMEDIA TOOLS AND APPLICATIONS 2023:1-24. [PMID: 37362704 PMCID: PMC10105161 DOI: 10.1007/s11042-023-15204-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 08/31/2022] [Accepted: 03/30/2023] [Indexed: 06/28/2023]
Abstract
Cloud-based Healthcare 4.0 systems have research challenges with secure medical data processing, especially biomedical image processing with privacy protection. Medical records are generally text/numerical or multimedia. Multimedia data includes X-ray scans, Computed Tomography (CT) scans, Magnetic Resonance Imaging (MRI) scans, etc. Transferring biomedical multimedia data to medical authorities raises various security concerns. This paper proposes a one-of-a-kind blockchain-based secure biomedical image processing system that maintains anonymity. The integrated Healthcare 4.0 assisted multimedia image processing architecture includes an edge layer, fog computing layer, cloud storage layer, and blockchain layer. The edge layer collects and sends periodic medical information from the patient to the higher layer. The multimedia data from the edge layer is securely preserved in blockchain-assisted cloud storage through fog nodes using lightweight cryptography. Medical users then safely search such data for medical treatment or monitoring. Lightweight cryptographic procedures are proposed by employing Elliptic Curve Cryptography (ECC) with Elliptic Curve Diffie-Hellman (ECDH) and Elliptic Curve Digital Signature (ECDS) algorithm to secure biomedical image processing while maintaining privacy (ECDSA). The proposed technique is experimented with using publically available chest X-ray and CT images. The experimental results revealed that the proposed model shows higher computational efficiency (encryption and decryption time), Peak to Signal Noise Ratio (PSNR), and Meas Square Error (MSE).
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Panigutti C, Beretta A, Fadda D, Giannotti F, Pedreschi D, Perotti A, Rinzivillo S. Co-design of human-centered, explainable AI for clinical decision support. ACM T INTERACT INTEL 2023. [DOI: 10.1145/3587271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
eXplainable AI (XAI) involves two intertwined but separate challenges: the development of techniques to extract explanations from black-box AI models, and the way such explanations are presented to users, i.e., the explanation user interface. Despite its importance, the second aspect has received limited attention so far in the literature. Effective AI explanation interfaces are fundamental for allowing human decision-makers to take advantage and oversee high-risk AI systems effectively. Following an iterative design approach, we present the first cycle of prototyping-testing-redesigning of an explainable AI technique, and its explanation user interface for clinical Decision Support Systems (DSS). We first present an XAI technique that meets the technical requirements of the healthcare domain: sequential, ontology-linked patient data, and multi-label classification tasks. We demonstrate its applicability to explain a clinical DSS, and we design a first prototype of an explanation user interface. Next, we test such a prototype with healthcare providers and collect their feedback, with a two-fold outcome: first, we obtain evidence that explanations increase users’ trust in the XAI system, and second, we obtain useful insights on the perceived deficiencies of their interaction with the system, so that we can re-design a better, more human-centered explanation interface.
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Affiliation(s)
- Cecilia Panigutti
- Università di Pisa, Italy and European Commission, Joint Research Centre (JRC), Italy
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Yip M, Ackery A, Jamieson T, Mehta S. The Priorities of End Users of Emergency Department Electronic Health Records: Modified Delphi Study. JMIR Hum Factors 2023; 10:e43103. [PMID: 36897633 DOI: 10.2196/43103] [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: 09/29/2022] [Revised: 01/16/2023] [Accepted: 02/11/2023] [Indexed: 03/11/2023] Open
Abstract
BACKGROUND The needs of the emergency department (ED) pose unique challenges to modern electronic health record (EHR) systems. A diverse case load of high-acuity, high-complexity presentations, and ambulatory patients, all requiring multiple transitions of care, creates a rich environment through which to critically examine EHRs. OBJECTIVE This investigation aims to capture and analyze the perspective of end users of EHR about the strengths, limitations, and future priorities for EHR in the setting of the ED. METHODS In the first phase of this investigation, a literature search was conducted to identify 5 key usage categories of ED EHRs. Using key usage categories in the first phase, a modified Delphi study was conducted with a group of 12 panelists with expertise in both emergency medicine and health informatics. Across 3 rounds of surveys, panelists generated and refined a list of strengths, limitations, and key priorities. RESULTS The findings from this investigation highlighted the preference of panelists for features maximizing functionality of basic clinical features relative to features of disruptive innovation. CONCLUSIONS By capturing the perspectives of end users in the ED, this investigation highlights areas for the improvement or development of future EHRs in acute care settings.
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Affiliation(s)
- Matthew Yip
- Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- The Institute for Health Policy, Management, and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Alun Ackery
- Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Unity Health Toronto, Toronto, ON, Canada
| | - Trevor Jamieson
- Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Unity Health Toronto, Toronto, ON, Canada
| | - Shaun Mehta
- Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Unity Health Toronto, Toronto, ON, Canada
- Department of Emergency Medicine, North York General Hospital, North York, ON, Canada
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Forster AJ, Chute CG, Pincus HA, Ghali WA. ICD-11: A catalyst for advancing patient safety surveillance globally. BMC Med Inform Decis Mak 2023; 21:383. [PMID: 36894925 PMCID: PMC9999485 DOI: 10.1186/s12911-023-02134-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Accepted: 02/06/2023] [Indexed: 03/11/2023] Open
Abstract
The World Health Organization's (WHO) international classification of disease version 11 (ICD-11) contains several features which enable improved classification of patient safety events. We have identified three suggestions to facilitate adoption of ICD-11 from the patient safety perspective. One, health system leaders at national, regional, and local levels should incorporate ICD-11 into all approaches to monitor patient safety. This will allow them to take advantage of the innovative patient safety classification methods embedded in ICD-11 to overcome several limitations related to existing patient safety surveillance methods. Two, application developers should incorporate ICD-11 into software solutions. This will accelerate adoption and utility of software-enabled clinical and administrative workflows relevant to patient safety management. This is enabled as a result of the ICD-11 application programming interface (or API) developed by the WHO. Third, health system leaders should adopt the ICD-11 using a continuous improvement framework. This will help leaders at national, regional and local levels to take advantage of specific existing initiatives which will be strengthened by ICD-11, including peer review comparisons, clinician engagement, and alignment of front-line safety efforts with post marketing surveillance of medical technologies. While the investment to adopt ICD-11 will be considerable, these will be offset by reducing the ongoing costs related to a lack of accurate routine information.
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Affiliation(s)
- Alan J Forster
- The Ottawa Hospital Ottawa; Ottawa Hospital Research Institute, Clinical Epidemiology Program; and Faculty of Medicine, University of Ottawa, Ottawa, Canada.
| | - Christopher G Chute
- Schools of Medicine, Public Health, and Nursing, Johns Hopkins University, Baltimore, USA
| | - Harold Alan Pincus
- Irving Institute for Clinical and Translational Research and Department of Psychiatry, Columbia University and New York State Psychiatric Institute, New York, NY, USA
| | - William A Ghali
- The Ottawa Hospital Ottawa; Ottawa Hospital Research Institute, Clinical Epidemiology Program; and Faculty of Medicine, University of Ottawa, Ottawa, Canada
- Schools of Medicine, Public Health, and Nursing, Johns Hopkins University, Baltimore, USA
- Irving Institute for Clinical and Translational Research and Department of Psychiatry, Columbia University and New York State Psychiatric Institute, New York, NY, USA
- Office of the Vice President Research; and, The O'Brien Institute of Public Health, University of Calgary, Calgary, AB, Canada
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Antikainen E, Linnosmaa J, Umer A, Oksala N, Eskola M, van Gils M, Hernesniemi J, Gabbouj M. Transformers for cardiac patient mortality risk prediction from heterogeneous electronic health records. Sci Rep 2023; 13:3517. [PMID: 36864069 PMCID: PMC9978282 DOI: 10.1038/s41598-023-30657-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 02/27/2023] [Indexed: 03/04/2023] Open
Abstract
With over 17 million annual deaths, cardiovascular diseases (CVDs) dominate the cause of death statistics. CVDs can deteriorate the quality of life drastically and even cause sudden death, all the while inducing massive healthcare costs. This work studied state-of-the-art deep learning techniques to predict increased risk of death in CVD patients, building on the electronic health records (EHR) of over 23,000 cardiac patients. Taking into account the usefulness of the prediction for chronic disease patients, a prediction period of six months was selected. Two major transformer models that rely on learning bidirectional dependencies in sequential data, BERT and XLNet, were trained and compared. To our knowledge, the presented work is the first to apply XLNet on EHR data to predict mortality. The patient histories were formulated as time series consisting of varying types of clinical events, thus enabling the model to learn increasingly complex temporal dependencies. BERT and XLNet achieved an average area under the receiver operating characteristic curve (AUC) of 75.5% and 76.0%, respectively. XLNet surpassed BERT in recall by 9.8%, suggesting that it captures more positive cases than BERT, which is the main focus of recent research on EHRs and transformers.
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Affiliation(s)
- Emmi Antikainen
- VTT Technical Research Centre of Finland Ltd., 33101, Tampere, Finland.
| | - Joonas Linnosmaa
- grid.6324.30000 0004 0400 1852VTT Technical Research Centre of Finland Ltd., 33101 Tampere, Finland
| | - Adil Umer
- grid.6324.30000 0004 0400 1852VTT Technical Research Centre of Finland Ltd., 33101 Tampere, Finland
| | - Niku Oksala
- grid.502801.e0000 0001 2314 6254Faculty of Medicine and Health Technology, Tampere University, 33720 Tampere, Finland ,Finnish Cardiovascular Research Center Tampere, 33520 Tampere, Finland ,grid.412330.70000 0004 0628 2985Vascular Centre, Tampere University Hospital, 33520 Tampere, Finland
| | - Markku Eskola
- Finnish Cardiovascular Research Center Tampere, 33520 Tampere, Finland ,grid.412330.70000 0004 0628 2985Tays Heart Hospital, Tampere University Hospital, 33521 Tampere, Finland
| | - Mark van Gils
- grid.502801.e0000 0001 2314 6254Faculty of Medicine and Health Technology, Tampere University, 33720 Tampere, Finland
| | - Jussi Hernesniemi
- grid.502801.e0000 0001 2314 6254Faculty of Medicine and Health Technology, Tampere University, 33720 Tampere, Finland ,Finnish Cardiovascular Research Center Tampere, 33520 Tampere, Finland ,grid.412330.70000 0004 0628 2985Tays Heart Hospital, Tampere University Hospital, 33521 Tampere, Finland
| | - Moncef Gabbouj
- grid.502801.e0000 0001 2314 6254Faculty of Information Technology and Communication Sciences, Tampere University, 33720 Tampere, Finland
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Smits PD, Gratzl S, Simonov M, Nachimuthu SK, Goodwin Cartwright BM, Wang MD, Baker C, Rodriguez P, Bogiages M, Althouse BM, Stucky NL. Risk of COVID-19 breakthrough infection and hospitalization in individuals with comorbidities. Vaccine 2023; 41:2447-2455. [PMID: 36803895 PMCID: PMC9933320 DOI: 10.1016/j.vaccine.2023.02.038] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 02/06/2023] [Accepted: 02/11/2023] [Indexed: 02/18/2023]
Abstract
BACKGROUND The successful development of multiple COVID-19 vaccines has led to a global vaccination effort to reduce severe COVID-19 infection and mortality. However, the effectiveness of the COVID-19 vaccines wane over time leading to breakthrough infections where vaccinated individuals experience a COVID-19 infection. Here we estimate the risks of breakthrough infection and subsequent hospitalization in individuals with common comorbidities who had completed an initial vaccination series. METHODS Our study population included vaccinated patients between January 1, 2021 to March 31, 2022 who are present in the Truveta patient population. Models were developed to describe 1) time from completing primary vaccination series till breakthrough infection; and 2) if a patient was hospitalized within 14 days of breakthrough infection. We adjusted for age, race, ethnicity, sex, and year-month of vaccination. RESULTS Of 1,218,630 patients in the Truveta Platform who had completed an initial vaccination sequence between January 1, 2021 and March 31, 2022, 2.85, 3.42, 2.75, and 2.88 percent of patients with CKD, chronic lung disease, diabetes, or are in an immunocompromised state experienced breakthrough infection, respectively, compared to 1.46 percent of the population without any of these four comorbidities. We found an increased risk of breakthrough infection and subsequent hospitalization in individuals with any of the four comorbidities when compared to individuals without these four comorbidities. CONCLUSIONS Vaccinated individuals with any of the studied comorbidities experienced an increased risk of breakthrough COVID-19 infection and subsequent hospitalizations compared to the people without any of the studied comorbidities. Individuals with immunocompromising conditions and chronic lung disease were most at risk of breakthrough infection, while people with CKD were most at risk of hospitalization following breakthrough infection. Patients with multiple comorbidities have an even greater risk of breakthrough infection or hospitalization compared to patients with none of the studied comorbidities. Individuals with common comorbidities should remain vigilant against infection even if vaccinated.
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Affiliation(s)
| | | | - Michael Simonov
- Truveta, Inc, Bellevue, WA, United States; Yale School of Medicine, New Haven, CT, United States
| | | | | | | | | | | | | | - Benjamin M Althouse
- Truveta, Inc, Bellevue, WA, United States; University of Washington, Seattle, Washington, United States; New Mexico State University, Las Cruces, New Mexico, United States
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Park HA, Cho I. Use of the clinical care classification in South Korean nursing practice: Challenges and opportunities. Int J Med Inform 2023; 170:104968. [PMID: 36603388 DOI: 10.1016/j.ijmedinf.2022.104968] [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: 03/01/2022] [Revised: 06/29/2022] [Accepted: 12/13/2022] [Indexed: 12/29/2022]
Abstract
BACKGROUND AND OBJECTIVES A government-driven standardization of nursing terminology including the Clinical Care Classification (CCC) was endorsed in South Korea in 2015, but the number of hospitals who have adopted this standard terminology remains unknown. This study aimed to determine the CCC awareness, adoption, and utilization statuses and its association with patient experience in South Korea. DESIGN, SETTING, AND PARTICIPANTS A nationwide telephone survey was conducted from January 13 to February 12, 2022 among 217 tertiary and secondary hospitals participating in the health information exchange network. The survey questionnaire included 22 items in 3 categories: current status of electronic nursing records, awareness and adoption of standard terminology, and open-ended questions regarding standard usage and dissemination. General characteristics and experience scores of the patients of the surveyed hospitals were collected from the publicly available data sources. Data analysis was performed using descriptive statistics, t-test, and generalized linear regression. MAIN OUTCOMES AND MEASURES The rates of awareness and adoption in hospitals to the nursing terminology standard of the CCC were calculated, and the current status of electronic nursing records used in practice was examined. The relationships between CCC awareness and the characteristics of hospitals in their patient experiences of health services were also identified. RESULTS The survey response rate was 24.9 % (54/217). Two out of three hospitals (68.5 %) were aware of the CCC. These hospitals had 800 beds or more, and higher scores for patient experience. CCC awareness was significantly related to increases in the overall scores for patient experiences (t = 2.70, p =.0103), but no significance with sub-score for nursing service (t = 1.23, p =.1594). CONCLUSIONS With a high adoption rate of electronic medical record systems, two-third hospitals acknowledged their CCC awareness, but were still lagged in adoption and usage of it in practice with operational challenges. The CCC awareness has potential relationships with positive patient experience.
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Affiliation(s)
- Hyeoun-Ae Park
- College of Nursing, Seoul National University, Seoul, South Korea
| | - Insook Cho
- Department of Nursing, Inha University, Incheon, South Korea.
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Vercell A, Gasteiger N, Yorke J, Dowding D. Patient-facing cancer mobile apps that enable patient reported outcome data to be collected: A systematic review of content, functionality, quality, and ability to integrate with electronic health records. Int J Med Inform 2023; 170:104931. [PMID: 36462398 DOI: 10.1016/j.ijmedinf.2022.104931] [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: 03/29/2022] [Revised: 06/30/2022] [Accepted: 11/16/2022] [Indexed: 11/27/2022]
Abstract
PURPOSE Enabling cancer patients to self-manage symptoms through mobile applications can result in more informed, autonomous patients who are partners in their care, consequently reducing the burden on health services. Electronic patient reported outcomes completed before a clinical review can increase the frequency and quality of holistic assessments, while integration into electronic health records can maximise clinical utility. The ability of apps to integrate with electronic health records is key to providing a real-time interface between patient reports and healthcare response. This review identifies patient-facing cancer apps which can record patient reported outcomes, and explores their purpose, functionality, quality, and ability to integrate with electronic health records. METHODS A systematic app review and content synthesis was conducted on patient-facing cancer apps available in the United Kingdom. Where applicable, the review aligned with the Preferred Reporting Items for Systematic Reviews and meta-Analysis. Two validated scales assessed functionality and quality: The IMS Institute for Healthcare Informatics functionality score and the Mobile App Rating Scale. Flesch-Kincaid metrics explored readability. RESULTS Apple App and Google Play stores identified 405 apps, of which 12 met the eligibility criteria. All were free to download, 1 (8%) had in-app purchases/subscriptions. Nine (75%) were affiliated with a professional health body/charity. Six (50%) analysed inputted data and provided medical advice based on answers. The average Flesch Reading Ease score was 42.7 out of 100. The apps had an average of 7.3 functions each and a mean MARS score of 4/5. None integrated with electronic health records. CONCLUSION While many cancer apps exist, few enable patient reported outcomes to be recorded and shared with clinicians in real-time. Further research is warranted to explore the feasibility of integrating with electronic health records, as this function can improve patient experience and outcomes, and increase efficiency of hospital resources through more proactive care.
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Affiliation(s)
- Amy Vercell
- The Christie NHS Foundation Trust, Wilmslow Road, Manchester M20 4BX, United Kingdom; Division of Nursing, Midwifery and Social Work, School of Health Sciences, University of Manchester, Manchester, United Kingdom.
| | - Norina Gasteiger
- Division of Nursing, Midwifery and Social Work, School of Health Sciences, University of Manchester, Manchester, United Kingdom; Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, Manchester, United Kingdom
| | - Janelle Yorke
- The Christie NHS Foundation Trust, Wilmslow Road, Manchester M20 4BX, United Kingdom; Division of Nursing, Midwifery and Social Work, School of Health Sciences, University of Manchester, Manchester, United Kingdom
| | - Dawn Dowding
- Division of Nursing, Midwifery and Social Work, School of Health Sciences, University of Manchester, Manchester, United Kingdom
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Negash YT, Calahorrano Sarmiento LS. Smart product-service systems in the healthcare industry: Intelligent connected products and stakeholder communication drive digital health service adoption. Heliyon 2023; 9:e13137. [PMID: 36820023 PMCID: PMC9937901 DOI: 10.1016/j.heliyon.2023.e13137] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 01/14/2023] [Accepted: 01/17/2023] [Indexed: 01/26/2023] Open
Abstract
Smart product-service systems (PSSs) have emerged as a solution for the ongoing digitalization of products and services, especially during the COVID-19 pandemic and under social distancing. However, the conditions for smart PSS adoption remain unclear, requiring the identification of driving attributes and the interrelationships of the attributes for smart PSS implementation in the healthcare industry. This study contributes by determining the cause-effect interrelationship among smart PSS attributes and by identifying and prioritizing the criteria that drive smart PSS adoption in chronic disease management. The study constructed a five-aspect theoretical model to deepen the understanding of digital health service adoption drivers. Data were collected from 233 healthcare industry practitioners to validate the smart PSS adoption attributes. Exploratory factor analysis (EFA) determined the structure of the attributes, the reliability of the criteria, and the validity of the aspects. The EFA result suggested 24 valid and reliable criteria drivers of smart PSS adoption in the healthcare industry, and they were grouped into five aspects. Following the smart PSS literature and stakeholder theory, the aspects are named digital health service adoption, intelligent connected products, stakeholder communication, environmental benefits, and use schemes. In addition, 17 practitioners treating patients with chronic conditions were interviewed to understand the interrelationships among the aspects and criteria. The fuzzy decision-making trial and evaluation laboratory (FDEMATEL) determined the cause-effect interrelationships based on their dependence and driving power. The FDEMATEL results indicated that intelligent connected products and stakeholder communication are the causal and focal attributes of improving digital health service adoption and providing alternative use schemes. For patients and physicians, the driving criteria include managing data, multifunctionality, data reliability, interoperability, patient communication, and resource efficiency. The theoretical and managerial implications are discussed.
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Affiliation(s)
- Yeneneh Tamirat Negash
- Department of Business Administration, Asia University, Taiwan,Institute of Innovation and Circular Economy, Asia University, Taiwan,Corresponding author. Department of Business Administration, Asia University, Taiwan.,
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Simon AR, Ahmed KL, Limon DL, Duhon GF, Marzano G, Goin-Kochel RP. Utilization of a Best Practice Alert (BPA) at Point-of-Care for Recruitment into a US-Based Autism Research Study. J Autism Dev Disord 2023; 53:359-369. [PMID: 35089434 PMCID: PMC9329488 DOI: 10.1007/s10803-022-05444-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/10/2022] [Indexed: 02/04/2023]
Abstract
Provider referral is one of the most influential factors in research recruitment. To ease referral burden on providers, we adapted the Best Practice Alert (BPA) in the EPIC Electronic Health Record and assessed its utility in recruiting pediatric patients with autism spectrum disorder for the national SPARK study. During a year-long surveillance, 1203 (64.0%) patients were Interested in SPARK and 223 enrolled. Another 754 participants not recruited via the BPA also enrolled; 35.5% of these participants completed their participation compared to 58.3% of BPA-referred participants. Results suggest that (a) a BPA can successfully engage providers in the study-referral process and (b) families who learn about research through their providers may be more engaged and effectively retained.
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Affiliation(s)
- Andrea R Simon
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
- Autism Center, Texas Children's Hospital, Houston, TX, USA
- Department of Health Care Administration, Trinity University, San Antonio, TX, USA
| | - Kelli L Ahmed
- Autism Center, Texas Children's Hospital, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Danica L Limon
- Autism Center, Texas Children's Hospital, Houston, TX, USA
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
- Department of Clinical Psychology, Brigham Young University, Provo, UT, USA
| | - Gabrielle F Duhon
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
- Autism Center, Texas Children's Hospital, Houston, TX, USA
- Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Gabriela Marzano
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
- Autism Center, Texas Children's Hospital, Houston, TX, USA
| | - Robin P Goin-Kochel
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA.
- Autism Center, Texas Children's Hospital, Houston, TX, USA.
- Meyer Center for Developmental Pediatrics and Autism, 8080 N. Stadium Drive, Suite 100, Houston, TX, 77054, USA.
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Lauffenburger JC, Khatib R, Siddiqi A, Albert MA, Keller PA, Samal L, Glowacki N, Everett ME, Hanken K, Lee SG, Bhatkhande G, Haff N, Sears ES, Choudhry NK. Reducing ethnic and racial disparities by improving undertreatment, control, and engagement in blood pressure management with health information technology (REDUCE-BP) hybrid effectiveness-implementation pragmatic trial: Rationale and design. Am Heart J 2023; 255:12-21. [PMID: 36220355 PMCID: PMC9742137 DOI: 10.1016/j.ahj.2022.10.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 09/29/2022] [Accepted: 10/01/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND While racial/ethnic disparities in blood pressure control are documented, few interventions have successfully reduced these gaps. Under-prescribing, lack of treatment intensification, and suboptimal follow-up care are thought to be central contributors. Electronic health record (EHR) tools may help address these barriers and may be enhanced with behavioral science techniques. OBJECTIVE To evaluate the impact of a multicomponent behaviorally-informed EHR-based intervention on blood pressure control. TRIAL DESIGN Reducing Ethnic and racial Disparities by improving Undertreatment, Control, and Engagement in Blood Pressure management with health information technology (REDUCE-BP) (NCT05030467) is a two-arm cluster-randomized hybrid type 1 pragmatic trial in a large multi-ethnic health care system. Twenty-four clinics (>350 primary care providers [PCPs] and >10,000 eligible patients) are assigned to either multi-component EHR-based intervention or usual care. Intervention clinic PCPs will receive several EHR tools designed to reduce disparities delivered at different points, including a: (1) dashboard of all patients visible upon logging on to the EHR displaying blood pressure control by race/ethnicity compared to their PCP peers and (2) set of tools in an individual patient's chart containing decision support to encourage treatment intensification, ordering home blood pressure measurement, interventions to address health-related social needs, default text for note documentation, and enhanced patient education materials. The primary outcome is patient-level change in systolic blood pressure over 12 months between arms; secondary outcomes include changes in disparities and other clinical outcomes. CONCLUSION REDUCE-BP will provide important insights into whether an EHR-based intervention designed using behavioral science can improve hypertension control and reduce disparities.
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Affiliation(s)
- Julie C Lauffenburger
- Center for Healthcare Delivery Sciences (C4HDS), Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
| | - Rasha Khatib
- Advocate Aurora Research Institute, Advocate Aurora Health, Downers Grove, IL
| | - Alvia Siddiqi
- Enterprise Population Health, Advocate Aurora Health, Downers Grove, IL
| | - Michelle A Albert
- Center for the Study of Adversity and Cardiovascular Disease (NURTURE Center), Division of Cardiology of Medicine (Cardiology), University of California, San Francisco, San Francisco, CA
| | | | - Lipika Samal
- Division of General Internal Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Nicole Glowacki
- Advocate Aurora Research Institute, Advocate Aurora Health, Downers Grove, IL
| | | | - Kaitlin Hanken
- Center for Healthcare Delivery Sciences (C4HDS), Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Simin G Lee
- Center for Healthcare Delivery Sciences (C4HDS), Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Gauri Bhatkhande
- Center for Healthcare Delivery Sciences (C4HDS), Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Nancy Haff
- Center for Healthcare Delivery Sciences (C4HDS), Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Ellen S Sears
- Center for Healthcare Delivery Sciences (C4HDS), Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Niteesh K Choudhry
- Center for Healthcare Delivery Sciences (C4HDS), Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
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The Implementation of Integrated Health Information Systems - Research Studies from 7 Countries Involving the InterRAI Assessment System. Int J Integr Care 2023; 23:8. [PMID: 36819613 PMCID: PMC9936911 DOI: 10.5334/ijic.6968] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 01/24/2023] [Indexed: 02/16/2023] Open
Abstract
Introduction In the past years, governments from several countries have shown interest in implementing integrated health information systems. The interRAI Suite of instruments fits this concept, as it is a set of standardised, evidence-based assessments, which have been validated for different care settings. The system allows the electronic transfer of information across care settings, enabling integration of care and providing support for care planning and quality monitoring. The main purpose of this research is to describe the recent implementation process of the interRAI instruments in seven countries: Belgium, Switzerland, France, Ireland, Iceland, Finland and New Zealand. Methods The study applied a case study methodology with the focus on the implementation strategies in each country. Principal investigators gathered relevant information from multiple sources and summarised it according to specific aspects of the implementation process, comparing them across countries. The main implementation aspects are described, as well as the main advantages and barriers perceived by the users. Results The seven case studies showed that adequate staffing, appropriate information technology, availability of hardware, professional collaboration and continuous training are perceived as important factors which can contribute to the implementation of the interRAI instruments. In addition, the use of electronic standardised assessment instruments such as the interRAI Suite provided evidence to improve decision-making and quality of care, enabling resource planning and benchmarking. Conclusion In practice, the implementation of health information systems is a process that requires a cultural shift of policymakers and professional caregivers at all levels of health policy and service delivery. Information about the implementation process of the interRAI Suite in different countries can help investigators and policymakers to better plan this implementation. This research sheds light on the advantages and pitfalls of the implementation of the interRAI Suite of instruments and proposes approaches to overcome difficulties.
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The case for including microbial sequences in the electronic health record. Nat Med 2023; 29:22-25. [PMID: 36646805 DOI: 10.1038/s41591-022-02157-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
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