Patient experience of treatment decision making for wet age-related macular degeneration disease: a qualitative study in China

Bian, Wei; Wan, Junli; Tan, Mingqiong; Wu, Xiongfei; Su, Jun; Wang, Lihua

doi:10.1136/bmjopen-2019-031020

Cited by 10 publications

(15 citation statements)

References 39 publications

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“…Several available publications in the ophthalmological field directed towards managing patients with cataract, diabetic retinopathy, glaucoma, age-related macular degeneration, and exotropia in providing a qualitative analysis by using standard interviews with healthcare workers and/or patients [25][26][27][28][29] and support the need for more patient involvement in shared making decision process. So far, none of these studies aimed to estimate the outcome of the SDM on the patients' satisfaction with the final/post-op result.…”

Section: Introductionmentioning

confidence: 99%

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Shared decision making and patients satisfaction with strabismus care—a pilot study

Paduca

Arnaut

Beschieru

et al. 2021

BMC Med Inform Decis Mak

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Background Strabismus is a complex disease that has various treatment approaches each with its own advantages and drawbacks. In this context, shared decisions making (SDM) is a communication process with the provider sharing all the relevant treatment alternatives, all the benefits, and risks of each procedure, while the patient shares all the preferences and values regarding his/her choices. In that way, SDM is a bidirectional process that goes beyond the typical informed consent. Therefore, it is known a little of the extent to which SDM influences the satisfaction with the treatment outcome along with strabismus patients. To study this correlation, an SDM-Q-9 questionnaire was provided within surgical consultations where treatment decisions were made; the SDM-Q-9 aims to assess the relationship between the post-operative patient’s satisfaction and their SMD score. Methods The study is considered a prospective observational pilot study. Eligible patients were adult patients diagnosed with strabismus, who had multiple treatment options, were given at the right of choice without being driven into a physician’s preference. Ninety-three strabismus patients were asked to fill out the SDM-Q-9 questionnaire related to their perception of SDM during the entire period of strabismus treatment. After the treatment, patients were asked to rate their satisfaction level with the surgical outcome as excellent, good, fair, and poor. Descriptive statistics and the linear regression statistical tests (Spearman, Mann Whitney U, and Kriskal–Wallis) were used as analysis tools. Results The average age of the participants was 24, where 50.6% were women. The mean SDM-Q-9 score among patients was 32 (IQR = 3). The postoperative patient satisfaction was rated as being excellent by 16 (17.2%) patients, good by 38 (40.9%), fair by 32 (34.4%), and poor by 7 patients (7.5%). Data analysis by linear regression statistical tests showed a positive correlation between the SDM-Q-9 score and the patient satisfaction related to the surgery outcome (B = 0.005, p < 0.001). Criteria in assessing patients’ satisfaction were age, gender, and strabismus type. A positive correlation between SDM and real satisfaction (r = 0.834, p < 0.01) was found with age, and no significant relationship was found while taking into consideration the responder’s gender and the strabismus type. Conclusions Assessing patient satisfaction after choosing a treatment for strabismus method helped us evaluate the gaps in constructive dialogue that would lead to a positive outcome for both patient and clinician. The correlation between the SDM process and the patients’ satisfaction with surgery outcome, adjusted by age, has been established. These findings can serve as a springboard to further communicative improvements related to the SDM process and between patients and physicians, thereby consequently leading to patients’ satisfaction raise in strabismus care. The study underlines the importance of further analysis and validation of on-ground interactions among the adolescent and adult patients and the clinicians across the strabismus management trajectory. A multicentral study and its validation will follow.

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Section: Introductionmentioning

confidence: 99%

“…Median (95% CI) 23(19)(20)(21)(22)(23)(24)(25)(26) 23 (23-28) 27 (24-34) 25(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33) …”

mentioning

confidence: 99%

Shared decision making and patients satisfaction with strabismus care—a pilot study

Paduca

Arnaut

Beschieru

et al. 2021

BMC Med Inform Decis Mak

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“…Age‐related macular degeneration (AMD) is one of the leading causes of vision loss, and eventually results in blindness 1 . As estimated in 2015 by the Vision Loss Expert Group, AMD ranked fourth among the major causes of blindness globally 2,3 . It is forecasted that the prevalence of AMD will increase further with an increasingly aging population.…”

Section: Introductionmentioning

confidence: 99%

“…It is forecasted that the prevalence of AMD will increase further with an increasingly aging population. Moreover, the severe impact of AMD on the quality of life leads to a substantial social and financial burden 2 . Therefore, the efficient screening and monitoring of AMD allow for better management is of great importance.…”

Section: Introductionmentioning

confidence: 99%

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Attention‐based deep learning system for automated diagnoses of age‐related macular degeneration in optical coherence tomography images

et al. 2021

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Purpose The progression of age‐related macular degeneration (AMD) is critical to treatment decisions in clinical practice. The disease can be classified into four categories namely, drusen, inactive choroidal neovascularization (CNV), active CNV, and normal, according to severity based on optical coherence tomography (OCT) images. Interpreting numerous OCT images is still time‐consuming and labor‐intensive, especially for the detection of the CNV activity. To address this problem, we developed a deep learning (DL) system based on OCT images, with the assistance of an attention mechanism, to automatically diagnose AMD. Methods A public dataset (total 51,140 OCT images) and a private dataset (total 4951 OCT images) were utilized as a training dataset and a clinical validation dataset, respectively, to develop the DL model. A ResNet‐34 DL model, with convolutional block attention module (CBAM) block integrated into each unit, was pretrained on the public dataset first and then finetuned on our private dataset to automatically diagnose AMD and assist clinical decision‐making. GradCam, a visualization technique, was used to improve the interpretability of our model. Results The precision and recall of our model were, respectively, 84.3% and 87.3% for drusen, 81.2% and 80.0% for inactive CNV, 97.7% and 90.2% for active CNV, and 93.7% and 96.5% for normal. The area under the curve (AUC) corresponding to drusen, inactive CNV, active CNV, and normal for our model reached 0.9395, 0.9476, 0.9880, and 0.9925, respectively. The heatmaps indicated a high level of correspondence in the region of interest between our model and ophthalmologists on the diagnosis. Conclusions The implementation of finetuning and attention mechanism improve the performance of our model in a distinct dataset. Our model successfully assisted in the diagnosis of AMD and achieved a detection precision and recall equal to those of ophthalmologists. The results of our study could contribute to the precise diagnosis of and decision‐making regarding AMD.

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Motivations, psychosocial burdens, and decision-making modes of post-partum women with stress urinary incontinence engaging in pelvic floor physical therapy: a qualitative research

Huang

et al. 2023

Int Urogynecol J

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Patient experience of treatment decision making for wet age-related macular degeneration disease: a qualitative study in China

Cited by 10 publications

References 39 publications

Shared decision making and patients satisfaction with strabismus care—a pilot study

Shared decision making and patients satisfaction with strabismus care—a pilot study

Attention‐based deep learning system for automated diagnoses of age‐related macular degeneration in optical coherence tomography images

Motivations, psychosocial burdens, and decision-making modes of post-partum women with stress urinary incontinence engaging in pelvic floor physical therapy: a qualitative research

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