Pengaruh Pengalaman Pasien, Kepuasan Pelanggan Terhadap Loyalitas dengan Ewom Sebagai Mediasi pada Pasien Rawat Jalan di Rumah Sakit X Jawa Barat

Ranah Research Journal of Multidisciplinary Research and Development, Год журнала: 2024, Номер 6(3), С. 395 - 407

Опубликована: Апрель 30, 2024

Riset ini bertujuan untuk menganalisis pengaruh pengalaman pasien, kepuasan pelanggan terhadap loyalitas dengan eWOM sebagai mediasi pada pasien rawat jalan tenaga di rumah sakit umum X. Peserta penelitian berjumlah 156 orang yang mengisi kuesioner merupakan bagian dari Path Analysis memanfaatkan Structural Equation Modeling (SEM) software Smart Partial Least Square (PLS). Berdasarkan hasil analisis data ditemukan bahwa berpengaruh signifikant eWOM, positif dan signifikan eWOM. Penelitian juga menemukan meskipun tidak berdampak promosi (eWOM), namun signifikan. EWOM memiliki dampak besar pelanggan, gilirannya dipengaruhi secara oleh layanan mereka terima. Dimensi paling tinggi yaitu komunikasi perawat (55,6%), dimensi satisfaction toward Quality (72,1%), konten (67,2%), kesetiaan produk (75,9). Manajemen karyawan perlu melakukan pembenahan pengembangan pelayanan penerapan EMR, meningkatkan paradigma costumer value, maintenance semua fasilitas utama pendukung, penyesuaian tarif biaya obat branchmarking ke terdekat, retensi menyelenggarakan event-event, memberikan atau diskon seperti MCU gratis, maupun konsultasi, penjemputan gratis ambulans penggunaan media sosial website upload informasi kesehatan bervariasi melibatkan RS.

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Revealing patient-reported experiences in healthcare from social media using thedesign-acquire-process-model-analyse-visualise framework

Digital Health, Год журнала: 2024, Номер 10

Опубликована: Янв. 1, 2024

Understanding patient experience in healthcare is increasingly important and desired by medical professionals a patient-centred care approach. Healthcare discourse on social media presents an opportunity to gain unique perspective patient-reported experiences, complementing traditional survey data. These reports often appear as first-hand accounts of patients' journeys through the system, whose details extend beyond confines structured surveys at far larger scale than focus groups. However, contrast with vast presence patient-experience data potential benefits offers, it attracts comparatively little research attention due technical proficiency required for text analysis. In this article, we introduce design-acquire-process-model-analyse-visualise framework provide overview techniques approach capture experiences from We apply case study prostate cancer /r/ProstateCancer, demonstrate framework's value capturing specific aspects concern (such sexual dysfunction), discourse, show narrative emotional progression these stories. anticipate wide variety areas healthcare, including differentiating across minority groups, geographic boundaries, types illnesses.

Язык: Английский

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Multimodal Sentiment Analysis for the Malay Language: New Corpus using CNN-based Framework

ACM Transactions on Asian and Low-Resource Language Information Processing, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 11, 2024

Sentiment analysis in the Malay language has traditionally focused on text-based data. is native of Malaysia and other surrounding countries. While sentiment shown good performance, it often lacks accuracy due to absence speaker's affective state intentions, which can lead misinterpretations. Multimodal addresses these shortcomings demonstrated improved performance various prediction tasks. Unfortunately, there been little research this area for language, a lack corpus baseline studies. This paper introduces new Corpus, ‘MyMSC’, with annotations at both multimodal unimodal text levels. It contains 1208 segments covering political social topics. The development processes are described detail, along necessary guidelines considerations. proposes CNN-based framework late fusion method as model. Experiments proposed model demonstrate that approach (F1 score = 0.77) outperforms 0.68), validating contribution multimodality classification performance. differences between two types their impact further elaborated. full available https://github.com/serenaroseaini/MyMSC .

Язык: Английский

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Predicting counseling behavioral propensity based on temporal return visits patterns and current perceived intensity with chronic conditions management

Information Processing & Management, Год журнала: 2024, Номер 62(3), С. 104024 - 104024

Опубликована: Дек. 7, 2024

Язык: Английский

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The potential use of Google reviews to assess patient satisfaction in the emergency department

The American Journal of Emergency Medicine, Год журнала: 2021, Номер 52, С. 110 - 113

Опубликована: Дек. 9, 2021

Язык: Английский

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