Task analysis of healthcare delivery: A case study

Carstens, Deborah Sater; Patterson, Pauline; Laird, R.; Preston, Paula

doi:10.1016/j.jengtecman.2009.03.006

Cited by 7 publications

(6 citation statements)

References 16 publications

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“…Publikasi WHO pada tahun 2004, di berbagai Negara Amerika, Inggris, Denmark dan Australia, ditemukan KTD dengan rentang 3,2 -16,6%. Laporan IOM menyimpulkan 4 hal pokok: a) Masalah accidental injury adalah suatu hal yang serius, b) Penyebabnya bukan kecerobohan individu, tetapi kesalahan sistem, c) Perlu redesign sistem pelayanan, d) Patient Safety harus menjadi prioritas nasional (Carstens, Patterson, Laird, & Preston, 2009;Chuan-Jun & Tsung-Ching, 2008). Emergency Departement (ED) adalah tiga lokasi tertinggi di rumah sakit untuk terjadinya error disamping unit perawatan intensif (ICU) dan kamar operasi.…”

Section: Latar Belakangunclassified

Factors Analyze on the Performance of Nurses in the Implementation of Patient Safety

Sukaesi¹

2017

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Nurse have an important good role for safety of patients by monitoring the patients' condition to prevent the occurrence of incidents, provide health education, detect faults and near misses, and perform other tasks to solve a problem of the patients by high-quality care. The problems have been existing in ER related to the implementation of patient safety is that the patient safety has not been accomplished in accordance with the SPO and Patient Safety Guide. The purpose of this study is to analyze the factors associated with the performance of nurses in the implementation of patient safety. The research uses analytical descriptive design with cross sectional approach. The number of samples used is 23 respondents with total sampling technique . The calculation results of multiple regression analysis of patient safety knowledge factors have the most dominant influence with standardized ß coefficient of 0.678 and 0.329 meaning that it has a significant effect while the supervision does not. Optimizing the development of the individual nurse requires efforts to increase knowledge and skills in the context of patient safety; therefore, they are able to show high-quality performance.

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Section: Latar Belakangunclassified

Factors Analyze on the Performance of Nurses in the Implementation of Patient Safety

Sukaesi¹

2017

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“…Literature shows that in the U.S. alone, approximately 770,000 injuries or deaths occur every year due to an inappropriately prescribed medication (Brownlee and Garber, 2019 ; Matsuyama et al, 2021 ) with estimated expenses between “$1.56 and $5.6 billion annually” (Slight et al, 2018 ). The Center for Disease Control (CDC) reported that between 2011 and 2014 more than 66% of people over 65 took three or more prescription medications (Carstens et al, 2009 ; Veteran Affairs, 2021 ). An aging population with multiple medications can lead to potentially inappropriate prescribing (Hoel et al, 2021 ) of medications (PIMs) (Bradley et al, 2017 ; Burkhardt et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Pharmacogenomics driven decision support prototype with machine learning: A framework for improving patient care

et al. 2022

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IntroductionA growing number of healthcare providers make complex treatment decisions guided by electronic health record (EHR) software interfaces. Many interfaces integrate multiple sources of data (e.g., labs, pharmacy, diagnoses) successfully, though relatively few have incorporated genetic data.MethodThis study utilizes informatics methods with predictive modeling to create and validate algorithms to enable informed pharmacogenomic decision-making at the point of care in near real-time. The proposed framework integrates EHR and genetic data relevant to the patient's current medications including decision support mechanisms based on predictive modeling. We created a prototype with EHR and linked genetic data from the Department of Veterans Affairs (VA), the largest integrated healthcare system in the US. The EHR data included diagnoses, medication fills, and outpatient clinic visits for 2,600 people with HIV and matched uninfected controls linked to prototypic genetic data (variations in single or multiple positions in the DNA sequence). We then mapped the medications that patients were prescribed to medications defined in the drug-gene interaction mapping of the Clinical Pharmacogenomics Implementation Consortium's (CPIC) level A (i.e., sufficient evidence for at least one prescribing action) guidelines that predict adverse events. CPIC is a National Institute of Health funded group of experts who develop evidence based pharmacogenomic guidelines. Preventable adverse events (PAE) can be defined as a harmful outcome from an intervention that could have been prevented. For this study, we focused on potential PAEs resulting from a medication-gene interaction.ResultsThe final model showed AUC scores of 0.972 with an F1 score of 0.97 with genetic data as compared to 0.766 and 0.73 respectively, without genetic data integration.DiscussionOver 98% of people in the cohort were on at least one medication with CPIC level a guideline in their lifetime. We compared predictive power of machine learning models to detect a PAE between five modeling methods: Random Forest, Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), K Nearest neighbors (KNN), and Decision Tree. We found that XGBoost performed best for the prototype when genetic data was added to the framework and improved prediction of PAE. We compared area under the curve (AUC) between the models in the testing dataset.

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“…Health information technology (HIT) has been recognized as one of the most important means to improve the quality, efficiency and effectiveness of healthcare services (Agarwal et al 2010;Bhattacherjee et al 2006;Carstens et al 2009;Goldschmidt 2005;Teoh et al 2012). However, a number of studies have indicated that the adoption of HIT remains limited (Anderson 2007;Bhattacherjee et al 2006;Ford et al 2006;Goldschmidt 2005;Teoh et al 2012) and healthcare organizations considering the adoption of HIT face many financial, technical and cultural barriers.…”

Section: Introductionmentioning

confidence: 99%

“…This is common in a healthcare context. In a case study that investigates healthcare processes, Carstens et al (2009) found that multiple HIT systems are implemented in the process of emergency care, from patient admission, patient information collection, to emergency care providing. Weber-Jahnke et al (2012) similarly noted that eHealth information systems manage a series of activities in the delivery of health care services from scheduling and billing to clinical decision support, and interoperability among the systems is important for the "continuum of care".…”

Section: Introductionmentioning

confidence: 99%

“…Similarly a clinical decision support system involves not only physicians but also other clinicians in completing the clinical tasks (Kaplan 2001a;2001b). Indeed the collaborative use of HIT among various user groups is common as the delivery of healthcare service demands joint effort of participants such as patients, nurses, physicians, pharmacists, and so on (Balka et al 2012;Carstens et al 2009;Davidson and Chismar 2007;He et al 2012). This important dimension of collaboration among different user groups in HIT adoption, however, is largely neglected in the previous review of the HIT adoption literature.…”

Section: Introductionmentioning

confidence: 99%

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Understanding health information technology adoption: A synthesis of literature from an activity perspective

Sun

2014

Inf Syst Front

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The vast body of literature on health information technology (HIT) adoption features considerably heterogeneous factors and demands for a synthesis of the knowledge in the field. This study employs text mining and network analysis techniques to identify the important concepts and their relationships in the abstracts of 979 articles of HIT adoption. Through the lens of Activity Theory, the revealed concept map of HIT adoption can be viewed as a complex activity system involving different users, technologies and tasks at both the individual level and the social level. Such a synthesis not only discloses the current knowledge domain of HIT adoption, but also provides guidance for future research on HIT adoption.

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Task analysis of healthcare delivery: A case study

Cited by 7 publications

References 16 publications

Factors Analyze on the Performance of Nurses in the Implementation of Patient Safety

Factors Analyze on the Performance of Nurses in the Implementation of Patient Safety

Pharmacogenomics driven decision support prototype with machine learning: A framework for improving patient care

Understanding health information technology adoption: A synthesis of literature from an activity perspective

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