Factors Involved in the Successful Transition to and Subsequent use of Electronic Health Records (EHRs) Systems by Individual and Group-Practice Physicians

The use of Electronic Health Records (EHRs) by healthcare professionals has been recommended as a way of improving healthcare quality, patient safety, and workflow efficiency, and lowering costs in the long run. While large hospital systems integrate EHRs into their services, individual and group practice-owning physicians, especially those of specialties and subspecialties, are often left wondering whether they should follow the trend and whether the transition from traditional, paper-chart systems or older EHRs to newer, commercial ones will truly benefit their patients and their practice as a whole. These physicians also often wonder whether benefits such as electronic-prescribing, clinical decision support, and patient results tracking outweigh obstacles such as initial costs, reliability, and user adaptability. This investigation sought to provide a more informed perspective in considering the decision to either transition to an Electronic Health Records system or maintain a traditional paper-chart style system. A number of studies examining care quality improvement and physician satisfaction in regards to transitions to EHRs under various conditions, such as specialty type, previous EHR-experience, and difficulty of transition, among others, were investigated to form this perspective. The improvement of care quality and physician satisfaction as a result of adopting EHRs relies heavily on both the efficiency and completeness of the transition and the EHR\u27s degree of customization towards a practice’s specific needs. Since EHRs are continuously being developed and improved, the transition to an EHR system and its subsequent use can be successful with proper preparation for the transition, extended clinician training, and choosing one that is well-tailored to the needs of the specialty and its patients’ medical conditions.https://scholarscompass.vcu.edu/uresposters/1169/thumbnail.jp

The effect of Electronic Health Records on the medical professional identity of physicians:a systematic literature review

Electronic Health Records (EHR) have become standard practice and have altered the way physicians work and communicate with their patients. This changing work environment may subsequently influence the perceived professional identity of physicians. In this study, we aim to understand the impact of EHR use on the medical professional identity of physicians. We conducted a systematic literature review which resulted in the analysis of 34 papers that met inclusion quality criteria. The literature suggests that EHRs make the interaction between patients and physicians more formal and standardized. In addition, physicians experience a decrease in their autonomy which negatively influences their experienced professional identity. Based on these findings, we recommend examining how EHRs can allow physicians to focus more on medical work and communication with their patients and be less distracted by EHR requirements so that their medical professional identity can be restored or enhanced

A systematic literature review on safe health information technology use behaviour

The implementation of health information technology (IT) is one of the strategy to improve patient safety due to medical errors. Nevertheless, inappropriate use of health IT may have serious consequences to the quality of care and patient safety. Most of the previous studies have been focused on the sociotechnical factors contributed to health IT related errors. Little focus has been given on the use behavior that influence the safety of health IT adoption. In order to address this gap, this study investigates the use behavior that influence the safety of health IT adoption. Systematic literature review was conducted to identify articles pertinent to safety of health IT. Science Direct, Medline, EMBASE, and CINAHL database were searched for reviews relevance articles. A total of 23 full articles were reviewed to extract use behavior that influence the safety of health IT adoption. Workarounds, adhere to procedure, vigilant action, and copy and paste behavior were discerned as the significance use behavior that influence health IT safety adoption. This study may be of significance in providing useful information on how to safely practice health IT adoption

Understanding patient needs and gaps in radiology reports through online discussion forum analysis

Our objective is to investigate patient needs and understand information gaps in radiology reports using patient questions that were posted on online discussion forums. We leveraged online question and answer platforms to collect questions posted by patients to understand current gaps and patient needs. We retrieved six hundred fifty-nine (659) questions using the following sites: Yahoo Answers, Reddit.com, Quora, and Wiki Answers. The questions retrieved were analyzed and the major themes and topics were identified. The questions retrieved were classified into eight major themes. The themes were related to the following topics: radiology report, safety, price, preparation, procedure, meaning, medical staff, and patient portal. Among the 659 questions, 35.50% were concerned with the radiology report. The most common question topics in the radiology report focused on patient understanding of the radiology report (62 of 234 [26.49%]), image visualization (53 of 234 [22.64%]), and report representation (46 of 234 [19.65%]). We also found that most patients were concerned about understanding the MRI report (32%; n = 143) compared with the other imaging modalities (n = 434). Using online discussion forums, we discussed major unmet patient needs and information gaps in radiology reports. These issues could be improved to enhance radiology design in the future

Impacts of Stress, Satisfaction and Behavioral Intention on Continued Usage: Evidence from Physicians Transitioning to a New Drug Management System

A survey of physicians taking part in a pilot study involving the transition from an e-prescribing system to a new integrated drug management system was conducted. Data about physicians’ level of stress induced by the system transition, satisfaction with the new system, and intention to continue to use the system, were collected as well as system usage logs before, during, and after the transition. Results indicate that physicians experiencing higher level of stress used the new system less during the transition as well as during the two months post-transition than their counterparts who reported lower level of stress. Although satisfaction with the new system was positively related to physicians’ intention to use, it was not significantly related to actual usage. A discussion of our results and their implications for research and practice concludes the paper

KLASYFIKACJA CHOROBY PARKINSONA I INNYCH ZABURZEŃ NEUROLOGICZNYCH Z WYKORZYSTANIEM EKSTRAKCJI CECH GŁOSOWYCH I TECHNIK REDUKCJI

This study aimed to differentiate individuals with Parkinson's disease (PD) from those with other neurological disorders (ND) by analyzing voice samples, considering the association between voice disorders and PD. Voice samples were collected from 76 participants using different recording devices and conditions, with participants instructed to sustain the vowel /a/ comfortably. PRAAT software was employed to extract features including autocorrelation (AC), cross-correlation (CC), and Mel frequency cepstral coefficients (MFCC) from the voice samples. Principal component analysis (PCA) was utilized to reduce the dimensionality of the features. Classification Tree (CT), Logistic Regression, Naive Bayes (NB), Support Vector Machines (SVM), and Ensemble methods were employed as supervised machine learning techniques for classification. Each method provided distinct strengths and characteristics, facilitating a comprehensive evaluation of their effectiveness in distinguishing PD patients from individuals with other neurological disorders. The Naive Bayes kernel, using seven PCA-derived components, achieved the highest accuracy rate of 86.84% among the tested classification methods. It is worth noting that classifier performance may vary based on the dataset and specific characteristics of the voice samples. In conclusion, this study demonstrated the potential of voice analysis as a diagnostic tool for distinguishing PD patients from individuals with other neurological disorders. By employing a variety of voice analysis techniques and utilizing different machine learning algorithms, including Classification Tree, Logistic Regression, Naive Bayes, Support Vector Machines, and Ensemble methods, a notable accuracy rate was attained. However, further research and validation using larger datasets are required to consolidate and generalize these findings for future clinical applications.Przedstawione badanie miało na celu różnicowanie osób z chorobą Parkinsona (PD) od osób z innymi zaburzeniami neurologicznymi poprzez analizę próbek głosowych, biorąc pod uwagę związek między zaburzeniami głosu a PD. Próbki głosowe zostały zebrane od 76 uczestników przy użyciu różnych urządzeń i warunków nagrywania, a uczestnicy byli instruowani, aby wydłużyć samogłoskę /a/ w wygodnym tempie. Oprogramowanie PRAAT zostało zastosowane do ekstrakcji cech, takich jak autokorelacja (AC), krzyżowa korelacja (CC) i współczynniki cepstralne Mel (MFCC) z próbek głosowych. Analiza składowych głównych (PCA) została wykorzystana w celu zmniejszenia wymiarowości cech. Jako techniki nadzorowanego uczenia maszynowego wykorzystano drzewa decyzyjne (CT), regresję logistyczną, naiwny klasyfikator Bayesa (NB), maszyny wektorów nośnych (SVM) oraz metody zespołowe. Każda z tych metod posiadała swoje unikalne mocne strony i charakterystyki, umożliwiając kompleksową ocenę ich skuteczności w rozróżnianiu pacjentów z PD od osób z innymi zaburzeniami neurologicznymi. Naiwny klasyfikator Bayesa, wykorzystujący siedem składowych PCA, osiągnął najwyższy wskaźnik dokładności na poziomie 86,84% wśród przetestowanych metod klasyfikacji. Należy jednak zauważyć, że wydajność klasyfikatora może się różnić w zależności od zbioru danych i konkretnych cech próbek głosowych. Podsumowując, to badanie wykazało potencjał analizy głosu jako narzędzia diagnostycznego do rozróżniania pacjentów z PD od osób z innymi zaburzeniami neurologicznymi. Poprzez zastosowanie różnych technik analizy głosu i wykorzystanie różnych algorytmów uczenia maszynowego, takich jak drzewa decyzyjne, regresja logistyczna, naiwny klasyfikator Bayesa, maszyny wektorów nośnych i metody zespołowe, osiągnięto znaczący poziom dokładności. Niemniej jednak, konieczne są dalsze badania i walidacja na większych zbiorach danych w celu skonsolidowania i uogólnienia tych wyników dla przyszłych zastosowań klinicznych

Acceptance Measurement of Health Insurance Information System Based on Technology Acceptance Model

The objective of this research is to evaluate P-Care BPJS information system based on Technology Acceptance Model (TAM). The type of research is analytical, cross sectional approach. Number of respondents 206 P-Care BPJS users at primary health care. Data analysis using linear regression. Based on correlation test external variables with percieved usefulness, showed high correlation = 0.6 (p <0.001); external variables with percieved ease of use showed moderate correlation = 0.4 (p <0.001); perceived ease of use with attitude showed moderate correlation = 0.5 (p <0.001); percieved usefulness with attitude showed high correlation = 0.7 (p <0.001); perceived usefulness with actual use showed moderate correlation = 0.5 (p <0.001); behavioral intention to use with percieved usefulness showed moderate correlation = 0.5 (p <0.001); attitude with behavioral intention to use showed high correlation = 0.6 (p <0.001); behavioral intention to use with actual use showed high correlation = 0.7 (p <0.001)

How do stakeholders experience the adoption of electronic prescribing systems in hospitals? A systematic review and thematic synthesis of qualitative studies

Background: Electronic prescribing (ePrescribing) or computerised provider/physician order entry (CPOE) systems can improve the quality and safety of health services, but the translation of this into reduced harm for patients remains unclear. This review aimed to synthesise primary qualitative research relating to how stakeholders experience the adoption of ePrescribing/CPOE systems in hospitals, to help better understand why and how healthcare organisations have not yet realised the full potential of such systems and to inform future implementations and research. Methods: We systematically searched 10 bibliographic databases and additional sources for citation searching and grey literature, with no restriction on date or publication language. Qualitative studies exploring the perspectives/experiences of stakeholders with the implementation, management, use and/or optimisation of ePrescribing/CPOE systems in hospitals were included. Quality assessment combined criteria from the Critical Appraisal Skills Programme Qualitative Checklist and the Standards for Reporting Qualitative Research guidelines. Data were synthesised thematically. Results: 79 articles were included. Stakeholders’ perspectives reflected a mixed set of positive and negative implications of engaging in ePrescribing/CPOE as part of their work. These were underpinned by further-reaching change processes. Impacts reported were largely practice related rather than at the organisational level. Factors affecting the implementation process and actions undertaken prior to implementation were perceived as important in understanding ePrescribing/CPOE adoption and impact. Conclusions: Implementing organisations and teams should consider the breadth and depth of changes that ePrescribing/CPOE adoption can trigger rather than focus on discrete benefits/problems and favour implementation strategies that: consider the preimplementation context, are responsive to (and transparent about) organisational and stakeholder needs and agendas and which can be sustained effectively over time as implementations develop and gradually transition to routine use and system optimisation