Predictors Of Patient Satisfaction Research Articles

Supplemental Material for Patients’ Beliefs as Predictors of Patient Satisfaction and Health-Related Quality of Life in Pediatric Rehabilitation

Supplemental Material for Patients’ Beliefs as Predictors of Patient Satisfaction and Health-Related Quality of Life in Pediatric Rehabilitation

Computed tomography radiomics in predicting patient satisfaction after robotic-assisted total knee arthroplasty.

After robotic-assisted total knee arthroplasty (RA-TKA) surgery, some patients still experience joint discomfort. We aimed to establish an effective machine learning model that integrates radiomic features extracted from computed tomography (CT) scans and relevant clinical information to predict patient satisfaction three months postoperatively following RA-TKA. After careful selection, data from 142 patients were randomly divided into a training set (n = 99) and a test set (n = 43), approximately in a 7:3 ratio. A total of 1329 radiomic features were extracted from the regions of interest delineated in CT scans. The features were standardized using normalization algorithms, and the least absolute shrinkage and selection operator regression model was employed to select radiomic features with ICC > 0.75 and P < 0.05, generating the Rad-score as feature markers. Univariate and multivariate logistic regression was then used to screen clinical information (age, body mass index, operation time, gender, surgical side, comorbidities, preoperative KSS score, preoperative range of motion (ROM), preoperative and postoperative HKA angle, preoperative and postoperative VAS score) as potential predictive factors. The satisfaction scale ≥ 20 indicates patient satisfaction. Finally, three prediction models were established, focusing on radiomic features, clinical features, and their fusion. Model performance was evaluated using Receiver Operating Characteristic curves and decision curve analysis. In the training set, the area under the curve (AUC) of the clinical model was 0.793 (95% CI 0.681-0.906), the radiomic model was 0.854 (95% CI 0.743-0.964), and the combined radiomic-clinical model was 0.899 (95% CI 0.804-0.995). In the test set, the AUC of the clinical model was 0.908 (95% CI 0.814-1.000), the radiomic model was 0.709 (95% CI 0.541-0.878), and the combined radiomic-clinical model was 0.928 (95% CI 0.842-1.000). The AUC of the radiomic-clinical model was significantly higher than the other two models. The decision curve analysis indicated its clinical application value. We developed a radiomic-based nomogram model using CT imaging to predict the satisfaction of RA-TKA patients at 3 months postoperatively. This model integrated clinical and radiomic features and demonstrated good predictive performance and excellent clinical application potential.

How much improvement in Oswestry Disability Index is Necessary to make your Patient Satisfied after Lumbar Surgery?

Retrospective review of cohort studies. To clarify the necessary ODI improvement for patient satisfaction two years after lumbar surgery. Evaluating elective lumbar surgery care often involves patient-reported outcomes (PRO). While postoperative functional improvement measured by ODI is theoretically linked to satisfaction, conflicting evidence exists regarding this association. Baseline ODI and 2-year postoperative ODI were assessed. Patient satisfaction, measured on a scale from 1 to 5, with scores ≥4 considered satisfactory, was evaluated. Patients with incomplete follow-up were excluded. Statistical analyses included Mann-Whitney-U and multivariable logistic regression adjusted for age, sex, and BMI. Receiver operating characteristic (ROC) analysis determined threshold values for ODI improvement and postoperative target ODI indicative of patient satisfaction. 383 patients were included (mean age 65±10y, 57% female). ODI improvement was observed in 91% of patients, with 77% reporting satisfaction scores ≥4. Baseline ODI (median 62, IQR 46-74) improved to a median of 10 (IQR 1-10) 2 years postoperatively. Baseline (OR 0.98, P=0.015) and postoperative ODI scores (OR 0.93, P<0.001), as well as the difference between them (OR 1.04, P< 0.001), were significantly associated with patient satisfaction. Improvement of ≥38 ODI points or a relative change of ≥66% was indicative for patient satisfaction, with higher sensitivity (80%) and specificity (82%) for the relative change versus the absolute change (69%, 68%). With a sensitivity of 85% and a specificity of 77%, a postoperative target ODI of ≤24 indicated patient satisfaction. Lower baseline ODI and greater improvements in postoperative ODI are associated with an increased likelihood of patient satisfaction. A relative improvement of ≥66% or achieving a postoperative ODI score of ≤24 were the most indicative thresholds for predicting patient satisfaction, proving more sensitivity and specificity than an absolute change of ≥38 points.

Investigating Patient Satisfaction Through Web-Based Reviews of Norwegian Dentists: Quantitative Study Using the Meaning Extraction Method.

Challenging encounters in health care professions, including in dentistry, are relatively common. Challenging encounters can be defined as stressful or emotional situations involving patients that could impact both treatment outcomes and patients' experiences. Through written web-based reviews, patients can share their experiences with health care providers, and these posts can be a useful source for investigating patient satisfaction and their experiences of challenging encounters. This study aims to identify dominant themes from patient-written, web-based reviews of dentists and investigate how these themes are related to patient satisfaction with dental treatment. The study data consisted of 11,764 reviews written by dental patients, which included 1- to 5-star ratings on overall satisfaction and free-text comments. The free-text comments were analyzed using Linguistic Inquiry and Word Count software, and the meaning extraction method was used to group words into thematic categories. These themes were used as variables in a multilevel logistic regression analysis to predict patient satisfaction. Eight themes emerged from the analyses, of which 6 (75%)-explanation (odds ratio [OR] 2.56, 95% CI 2.16-3.04; P<.001), assurance (OR 3.61, 95% CI 2.57-5.06; P<.001), performance assessment (OR 2.17, 95% CI 1.84-2.55; P<.001), professional advice (OR 1.81, 95% CI 1.55-2.13; P<.001), facilities (OR 1.78, 95% CI 1.08-2.91; P=.02), and recommendation (OR 1.31, 95% CI 1.12-1.53; P<.001)-increased the odds of high patient satisfaction. The remaining themes (2/8, 25%)-consequences of treatment need (OR 0.24, 95% CI 0.20-0.29; P<.001) and patient-centered care (OR 0.62, 95% CI 0.52-0.74; P<.001)-reduced the odds of high patient satisfaction. The meaning extraction method is an interesting approach to explore patients' written accounts of encounters with dental health professionals. The experiences described by patients provide insight into key elements related to patient satisfaction that can be used in the education of dental health professionals and to improve the provision of dental health services.

The Dysmorphic Concern Questionnaire: Is It Possible to Predict a Satisfactory Result After Cosmetic Eyelid Surgery?

As oculofacial surgeons performing esthetic surgery, the most valuable result is a satisfied patient. It can be extremely frustrating to have an unhappy patient with, what we believe is, a satisfactory result. Therefore, the ability to predict satisfaction is of extreme importance. We studied our cosmetic eyelid surgery patients to try to find factors that can predict satisfaction. We retrospectively studied 454 consecutive patients, who underwent any combination of 7 cosmetic surgical procedures. Patients answered the Dysmorphic Concern Questionnaire (DCQ) before surgery. We studied age, gender, type and number of procedures performed, DCQ score, presence of complications, and history of previous fillers. At the 3-month follow-up visit, patients were given an outcome report survey to graduate their surgical results on a scale from 1 to 5. Results were evaluated using a model of binary logistic regression in which the outcome variable was divided into 2 groups. Three hundred eighty-six patients (85%) were female and the median age was 54.8 years old. The median for the number of procedures was 2 (range, 1-5). Two hundred two of the 454 patients (44.5%) had a history of fillers. Twenty-five patients had complications. DCQ score was significantly lower in the satisfied group (median score, 3) versus the unsatisfied group (median, 6), p = 0.007. In the multiple binary logistical model, the variables age, male gender, DCQ, presence of complications, and upper eyelid blepharoplasty resulted as significant. We found a significant positive association with upper lid blepharoplasty and a negative association with increasing age, male gender, occurrence of complications, and DCQ score, as predictors of patient satisfaction. We routinely administer the DCQ to all cosmetic patients: It is a brief, sensitive, and specific screening instrument for body dysmorphic disorder.

Rate and Predictors of Patient Satisfaction After Total Joint Arthroplasty: A Cross-Sectional Study in a Low-to-Middle-Income Country.

Objective This study aimed to assess the rate of patient satisfaction after primary total joint arthroplasty (TJA) using a validated satisfaction measure. Materials and methods A cross-sectional study was conducted, including all patients who underwent primary TJA between December 2021 and February 2023. The age of the study population was found to range from 23 to 86 years. Patient satisfaction was assessed using a validated tool comprising four questions and a quality of life (QoL) question. Results A total of 197 patients were included, with a mean age of 60.9 ± 12.7 years. Total knee replacement (TKR)was performed in 124 patients (62.9%), andtotal hip replacement (THR) in 73 patients (37.1%). The mean patient satisfaction score was 86.6 ± 14.4 out of a maximum of 100. A significant negative correlation was observed between the Charlson Comorbidity Index (CCI) and the overall satisfaction score (p-value = 0.029). The majority of the patients (52.3%, n = 103) answered that their QoL had greatly improved, and a similar level of improvement was noted in elderly vs. adult patients (p-value = 0.17). A significantly higher proportion of male patients reported improvement more than they ever expected compared to female patients, the majority of whom reported their QoL was greatly improved (p-value = 0.025). Conclusion Total joint arthroplasty has been shown to achieve good patient satisfaction and an improvement in QoL. However, an increased comorbidity index and female gender were identified as factors for reduced satisfaction. Hence, it is recommended to consider these factors and counsel patients accordingly based on local patient data.

Effective Communication in Providing Medication Information and Patient Satisfaction: A Cross-sectional Survey in Denpasar

Background: Pharmacy personnel should provide pharmaceutical care concerning the applicable standards. Furthermore, pharmacy management must consider patient satisfaction to ensure business continuity. Patient subjective factors strongly influence satisfaction. Meanwhile, patient perceptions of pharmaceutical services will change as their experience increases. The pharmacy must improve its services effectively and efficiently. Factors that affect patient satisfaction can assist pharmacies in improving service quality. Effective communication does not require additional resources to improve service quality. The same information can have different effects when presented in different ways.Objectives: Predict the domain of effective communication that influences patient satisfaction.Methods: The cross-sectional survey using a valid and reliable questionnaire was conducted in Denpasar. The research involved 100 pharmacy consumers and was taken with a convenience sampling technique. Data were analyzed descriptively, followed by a Chi-square test and multivariate analysis using logistic regression. The research involved four independent variables: pharmacy atmosphere, pharmacist performance, pharmaceutical technical competence, and interpersonal communication competence. Patient satisfaction is the dependent variable in this study. Results: Communication factors generally affect patient satisfaction in providing drug information. Among all the independent variables tested, interpersonal communication competence plays a significant role in predicting patient satisfaction with a p-value of 0.043 (Logistic regression with 95% confidence level).Conclusion: Patients who perceive pharmacists as having good interpersonal communication competence are 3,133 times more likely to be satisfied. Thus, pharmaceutical staff must train interpersonal communication skills to provide drug information to achieve patient satisfaction outcomes in pharmaceutical services.

Competitive priorities and engagement: can they be a source of satisfaction? Customer-centered model

Purpose This study aims to investigate and test the impact of competitive priorities, in terms of quality, speed, dependability, flexibility, cost and patient engagement, on patient satisfaction with healthcare services. It considers patients’ rather than managers’ points of view to collect responses about competitive priorities.Design/methodology/approach This research employed a cross-sectional survey design to analyze a sample of customers through an empirical study of 488 patients in Qatar’s healthcare service context.Findings The confirmatory factor analysis results show that competitive priorities and engagement positively and significantly impact patient satisfaction.Research limitations/implications Researchers can use this methodology to explore the role of competitive priorities in different service contexts and sectors. The researchers conducted the study in Qatar; therefore, the results are not generalizable to all healthcare sectors. However, regardless of geographic location, the research approach can be used in healthcare.Practical implications Managers can employ the developed scales to diagnose competitive priorities and improve customer service experiences.Originality/value The paper is original as it suggests using competitive priorities as a measurement tool for predicting patient satisfaction compared to prior research that mostly measured competitive priorities based on internal perspectives (managers’ perspectives). Further, this paper is original because it depends on the external perspective (customers’ perspective) for the competitive priorities for measuring patient satisfaction.

Identification of Emotional Spectrums of Patients Taking an Erectile Dysfunction Medication: Ontology-Based Emotion Analysis of Patient Medication Reviews on Social Media.

Patient medication reviews on social networking sites provide valuable insights into the experiences and sentiments of individuals taking specific medications. Understanding the emotional spectrum expressed by patients can shed light on their overall satisfaction with medication treatment. This study aims to explore the emotions expressed by patients taking phosphodiesterase type 5 (PDE5) inhibitors and their impact on sentiment. This study aimed to (1) identify the distribution of 6 Parrot emotions in patient medication reviews across different patient characteristics and PDE5 inhibitors, (2) determine the relative impact of each emotion on the overall sentiment derived from the language expressed in each patient medication review while controlling for different patient characteristics and PDE5 inhibitors, and (3) assess the predictive power of the overall sentiment in explaining patient satisfaction with medication treatment. A data set of patient medication reviews for sildenafil, vardenafil, and tadalafil was collected from 3 popular social networking sites such as WebMD, Ask-a-Patient, and Drugs.com. The Parrot emotion model, which categorizes emotions into 6 primary classes (surprise, anger, love, joy, sadness, and fear), was used to analyze the emotional content of the reviews. Logistic regression and sentiment analysis techniques were used to examine the distribution of emotions across different patient characteristics and PDE5 inhibitors and to quantify their contribution to sentiment. The analysis included 3070 patient medication reviews. The most prevalent emotions expressed were joy and sadness, with joy being the most prevalent among positive emotions and sadness being the most prevalent among negative emotions. Emotion distributions varied across patient characteristics and PDE5 inhibitors. Regression analysis revealed that joy had the strongest positive impact on sentiment, while sadness had the most negative impact. The sentiment score derived from patient reviews significantly predicted patient satisfaction with medication treatment, explaining 19% of the variance (increase in R2) when controlling for patient characteristics and PDE5 inhibitors. This study provides valuable insights into the emotional experiences of patients taking PDE5 inhibitors. The findings highlight the importance of emotions in shaping patient sentiment and satisfaction with medication treatment. Understanding these emotional dynamics can aid health care providers in better addressing patient needs and improving overall patient care.

Predictors of Patients' Satisfaction with Primary Health Care Services in the Kingdom of Saudi Arabia: A Systematic Review.

Understanding the factors influencing patients' satisfaction with primary healthcare services in the Kingdom of Saudi Arabia is essential for improving healthcare outcomes and patient experiences. This research work is concerned with the identification of the patient satisfaction predictors with the primary health care services by conducting a systematic review in the Kingdom of Saudi Arabia. The three databases in the form of Google Scholar, PubMed, and Medline have been used for article extraction. Keywords have been used to search the articles related to this work, such as the predictors of patient satisfaction. The different journals selected were associated with the selected data basis. The research studies selected for the systematic review were evaluated with the help of PRISMA and JBI assessments. The cross-sectional studies have been included in this systematic review. The 3125 articles identified were from the three databases PubMed (1352), Medline (1103), and Google Scholar (670). All the selected studies were evaluated and screened with the help of PRISMA. After extracting the 25 articles for the systematic review, the JBI assessment was applied to the methodologies. The overall quality satisfaction indicated that all the selected studies were suitable for the systematic review. Studies have consistently identified five key predictors of patient satisfaction in primary healthcare: availability, accessibility, communication, rational conduct, technical skills, and personal qualities. Policymakers, healthcare providers, and researchers can use these insights to inform strategies to optimize healthcare services and foster higher levels of patient satisfaction in the Kingdom.

Evaluating therapeutic benefits of ubrogepant via latent class models: A post hoc exploratory analysis of the ACHIEVE I and ACHIEVE II trials.

To evaluate an alternative method of defining acute treatment success in migraine by combining multiple indicators into a single dichotomous measure of success. Migraine is characterized by a symptom complex; combining these features as a single endpoint may improve the measurement of treatment effects and better predict patient satisfaction with treatment. We used a confirmatory latent class model (LCM) with two latent classes interpreted as treatment success and treatment failure. Pooled data for placebo and ubrogepant 50 mg from the ACHIEVE I and ACHIEVE II trials and data for ubrogepant 100 mg from ACHIEVE I were used. LCM inputs included pre-dose and 2-h post-dose measures of pain severity (0-3), the presence/absence of associated symptoms (nausea, photophobia, and phonophobia [0 or 1]), and functional disability (0-3). All definitions were validated against satisfaction with study medication (SWSM) at 24 h post-dose; results were compared with 2-hour pain freedom (2hPF). This pooled analysis included 2247 participants. At 2 h post-dose in the ubrogepant 50 and 100 mg dose groups, 53.2% (472/887) and 54.9% (246/448) of participants, respectively, were classified as achieving treatment success using the LCM-based approach, compared to 39.0% (356/912) of participants in the placebo group. The results for treatment success using the 2hPF endpoint were 20.7% (184/887) and 21.5% (96/447) in the ubrogepant 50 and 100 mg dose groups, respectively, compared to 12.7% (116/912) for placebo. Using 24-h SWSM as an external validator, the LCM approach sensitivity and correct classification rates were higher than for 2hPF. The LCM approach led to higher rates of treatment success and greater separation between ubrogepant and placebo and was a more sensitive predictor of treatment satisfaction than the regulatory endpoint of 2hPF.

The development of machine learning algorithms that can predict patients satisfaction using baseline characteristics, and preoperative and operative factors of total knee arthroplasty

BackgroundPatient satisfaction following primary total knee arthroplasty (TKA) is a crucial part to evaluate the success of the procedure. The purpose of this study was to develop to predict patient satisfaction following TKA. MethodsSatisfaction outcome data after 435 consecutive conventional TKAs performed between August 2020 and December 2021 were retrospectively collected. The total 26 input data were collected. The most favorable algorithm was first found using logistic regression (LR) and machine learning (ML) algorithms. To evaluate the predictive performance of the models, both area under curve (AUC) and F1-score were used as the primary metrics. The shapley additive explanations (SHAP) feature explanation in XGBoost and LR analysis were performed to interpret the model. ResultsThe performance of extreme gradient boosting classifier (XGBoost) was only higher than that of conventional LR in AUC (0.782 vs. 0.689). Comparing the F-1 score, only XGBoost showed better performance than LR (0.857 vs. 0.800). The most predictive feature in XGBoost was Short Form-36 physical and mental component summary scores (SF-36 MCS), followed by Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain, Bone mineral density (BMD). In the LR analysis, lumbar spine disease, WOMAC pain, and BMD were statistically significant. ConclusionXGboost showed the best performance and was superior to conventional LR in the prediction of patient satisfaction after TKA. The SF-36 MCS was the most important feature in the ML model. WOMAC pain and BMD were meaningful variables and demonstrated a linear relationship with satisfaction in both the LR and ML models.Level of evidence: Retrospective cohort study; Level of evidence 3.

Modeling Patient Perceptions About Generic Drug Quality and Trust With Doctors: An Empirical Analysis for Creating Sustainable Healthcare

As envisioned in SDG3, health equity is a fundamental component of sustainable healthcare systems, and generic drugs remove financial barriers. However, there is scant research on the quality of generic drugs from the user's perspective. This study aims to identify patient perceptions of generic drug quality and estimate its impact on their satisfaction by developing a model with misconceptions as a negative moderator and patients' trust with prescribing doctors as a positive moderator. Additionally, this research attempted to understand the difference in users’ perceptions about generic drugs and branded equivalents for quality benchmarking. Adopting the psychometric scale development procedure, validated 20 items, a five-factor multidimensional scale for generic dug quality using a cross-sectional survey that collected responses from patients ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> = 385). The analysis included exploratory factor analysis, confirmatory factor analysis, and regression analyses using the SPSS process macro. Findings from the study show that five dimensions, such as effectiveness, accessibility, consumption easiness, governmental controls, and packaging quality measured generic drug quality, which significantly predicts patient satisfaction. Further, the research compares quality attributes of generic drugs with branded equivalents to draw valuable insights helpful to achieving SDG3.

Predictors of patient satisfaction with Mohs micrographic surgery at time of surgery and 3 months postsurgery: A prospective cohort study

Despite the importance of patient satisfaction in ensuring high-quality care, studies investigating patient satisfaction in Mohs micrographic surgery (MMS) are limited. We investigated the factors associated with patient satisfaction in MMS for nonmelanoma skin cancer and how patient satisfaction changes in the postoperative period. In this prospective cohort study including 100 patients, patient satisfaction surveys were administered at the time of surgery and at 3months postsurgery. Sociodemographic characteristics, medical history, and surgical parameters were collected by chart review. Univariate linear and logistic regression models were created to examine these relationships. Decreased satisfaction was observed in patients requiring 3 or more MMS stages both at the timeof surgery (P=.047) and at 3months post-surgery (P=.0244). Patients with morning procedures ending after 1:00 pm had decreased satisfaction at the time of surgery (P=.019). A decrease in patient satisfaction between the time of surgery and 3months postsurgery was observed in patients with surgical sites on the extremities (P=.036), larger preoperative lesion sizes (P=.012), and larger defect sizes (P=.033). Single-institution data, self-selection bias, and recall bias. Patient satisfaction with MMS is impacted by numerous factors and remains dynamic over time.

Perceptions of Patient-Centered Care and Their Association With Patient Satisfaction in Abortions for Medical Reasons.

Abortions for medical reasons, which happen in the event of fetal abnormalities or maternal life endangerment, are highly politicized and understudied given their prevalence. Our objective was to understand the health care experiences of U.S. individuals who had an abortion of a wanted pregnancy for medical reasons in the second or third trimester. Participants were recruited on Facebook and completed surveys with their demographic information, their perception of their health provider's cultural sensitivity, their patient satisfaction, and their satisfaction with their decision to proceed with an abortion for medical reasons. Participants were 132 women who were mostly between the ages of 31 and 40 (72.7%), highly educated (84.1% had at least a 4-year college degree), and non-Hispanic White (85.6%). There was no statistically significant difference in patients' rated highest average item score on their providers' Competence or Sensitivity; however, average item scores of providers' Competence and Sensitivity were both higher than Respect scores. Linear regression results show that experiencing patient-centered care significantly predicted patient satisfaction (β=.73, t(131)=12.03, p<.001) and decision satisfaction (β=.37, t(131)=4.63, p<.001). Our findings underscore the importance of training providers to deliver patient-centered care that empowers patients to adapt to challenging situations, such as the diagnosis of medical concerns during pregnancy. Providers understanding and supporting the complex process of an abortion for medical reasons can ameliorate the emotional impact of this procedure.

Levels and predictors of patient satisfaction during flexible bronchoscopy procedures.

Flexible bronchoscopy (FB) is a safe and commonly performed procedure in pulmonary medicine. Bronchoscopy literature mainly focusing on technical aspects. However, data on patients satisfaction and bronchoscopy is rare. To evaluate levels and factors affecting patient satisfaction with flexible bronchoscopy (FB). This prospective study, conducted between June 2017 and May 2019 at King Abdulaziz University Hospital (Jeddah, Saudi Arabia), included all consecutive diagnostic bronchoscopies for adult patients. Patient willingness to return for another bronchoscopy (definitely not, probably not, unsure, probably would, or definitely would) was used as the indicator of satisfaction. Patients ranked their experiences with doctors, nurses, and process of care using a 5-choice scale (poor, fair, good, very good, or excellent). A total of 351 patients participated in this study. Overall, patients were highly satisfied with their doctors, nurses, and process of care. However, only 34.1% of patients indicated that they would return for another FB if necessary. Predictors of return for FB were younger age (<65 years), university education, use of midazolam and higher doses of fentanyl >100 mcg, and inpatient setting. Logistic regression demonstrated that younger age (P = 0.005) and inpatient setting (P = 0.02) were significantly linked to willingness to return for bronchoscopy. Patient satisfaction with bronchoscopy was lower in our study compared to other studies, despite high ratings of doctors' and nurses' skills. Elderly patients and patients with outpatient bronchoscopies were less likely to return and should therefore be approached with extra care. Physicians can improve FB-related patient experiences by decreasing discomfort during bronchoscope insertion and by improving topical anesthesia.

Association of Patient Anthropometric Measurements and Dental Implant Treatment.

Dental implants are currently one of the most preferred treatment modalities for replacing missing teeth, as they are the most comparable to natural teeth. Even so, satisfaction with such treatment may differ depending on patient nature. The aim of this article was to examine the relationships between different anthropometric measurements on dental implant patient's satisfaction. Self-administered questionnaire (structured questions) were given to patients who had dental implant treatment to evaluate their satisfaction level with dental-implant treatment. Different anthropometric measurements were taken: body height; weight; body mass index (BMI); body composition; waist/hip ratio; and circumferences at the waist, hip, and neck. The overall BMI was 28.9±4.7 kg/m2, there was a highly-significant difference in patient satisfaction among the different BMI groups (P< 0.000). The significant difference in most of those groups was between the obese group and the other groups. For neck circumference and waist/hip ratio, a significance difference between the normal weight and obese groups (P< 0.000) was found, while for percentage of muscle, the differences were between the overweight and obese groups (P< 0.000). According to BMI groups a highly significant difference in many patient satisfaction domains were found (P< 0.000). These significant differences were between the obese group and non-obese groups for most aspects of patient satisfaction. For patient satisfaction with final appearance, the normal BMI group differed significantly from the overweight BMI group (P=0.013). Additionally, for patient satisfaction with dentist performance and communication, the overweight BMI group showed significantly higher satisfaction than the normal BMI group (P=0.019). Body measurements were correlated negatively with overall patient satisfaction, and positively with satisfaction with prosthesis. The obese group patients had the lowest rate of patient satisfaction. BMI and other body measurements can be used to predict patient satisfaction with the outcome of dental implant treatment.

Oral health-related quality of life and patient-reported outcome measures after 10 years of supportive periodontal care

ObjectiveThe aim of this retrospective study was to evaluate the oral health-related quality of life (oHRQoL) and patient-reported outcome measures (PROMs) after 10 years of supportive periodontal care (SPC).Material and methodsPatients were re-examined 120±12 months after active periodontal therapy. Dental and periodontal status and oHRQoL by completing Oral Health Impact Profile-G49 (OHIP-G49) and PROMs by marking a visual analogue scale (VAS) for self-perceived esthetics (VASe), chewing function (VASc), and hygiene ability (VASh) were assessed. Patient- and tooth-related factors (age, insurance status, number of SPC, compliance, change of therapist, smoking, tooth loss, need for surgery or antibiotic intake, bleeding on probing (BOP), periodontal inflamed surface area) influencing oHRQoL and PROMs were evaluated.ResultsOne hundred eight periodontally compromised patients (59 female, mean age 65.4±10.7 years) lost 135 teeth during 10 years of SPC. At re-examination, 1.8% of all sites showed PPD ≥6mm. The mean OHIP-G49 sum score was 17.6±18.5, and VAS resulted in 76.0±22.5 (VASe), 86.3±16.3 (VASc), and 79.8±15.8 (VASh). Linear regression analyses identified a positive correlation with oHRQoL and/or PROMs for private insurance status (OHIP-G49, p=0.015, R2=0.204; VASc, p=0.005, R2=0.084; VASh, p=0.012, R2=0.222) and compliance to SPC (VASe, p=0.032; R2=0.204), as well as a negative correlation for active smoking (VASc, p=0.012, R2=0.084), increased BOP (VASh, p=0.029, R2=0.222) at the start of SPC, and number of lost molars (VASh, p=0.008, R2=0.222).ConclusionIt is realistic to obtain satisfactory oHRQoL and PROM values in most of the patients after 10 years of SPC. The identified factors may help to predict patient satisfaction in the long-term course of therapy.Clinical relevanceSystematic therapy of periodontally compromised patients provides values for oHRQoL and PROMs in a favorable range 10 years after therapy. This should encourage dentists to implement SPC in their daily routine.Clinical trial numberNCT03048045

Safety and Efficacy of Midface Augmentation Using Bio-Oss Bone Powder and Bio-Gide Collagen Membrane in Asians.

(1) Background: Asians tend to have a regressive midface. Midface augmentation is an effective treatment, and various materials have been used as fillers for this purpose. Bio-Oss bone powder has a strong positive effect on promoting new bone regeneration, and has been used in the dental field for over 30 years. However, it has not been used and reported as a filler in midface augmentation. (2) Objective: To evaluate the safety and efficacy of midface augmentation using Bio-Oss bone powder in treating midface retrusion and resulting nasolabial folds, and to develop a predictive model for patient satisfaction. (3) Methods: 85 patients underwent midface augmentation through an intraoral approach with Bio-Oss. Treatment efficacy was assessed by blinded investigators. The data on safety were collected from patient interviews at each follow-up visit. A questionnaire was used for investigating patient satisfaction. The influencing factors of satisfaction were analyzed by univariate and multivariate analysis. A nomogram to predict the risk of dissatisfaction was built based on significant factors with R software. Results: Compared to baseline, there was a significant improvement (p < 0.001) in Wrinkle Severity (4) Rating Scale scores at week 24, with a mean decrease of 0.52 ± 0.57. The aesthetic improvement rate evaluated by the Global Aesthetic Improvement Scale was 92.9%. Four mild treatment-related adverse events were noted. The majority of patients were satisfied overall. A nomogram with good prediction performance was plotted. (5) Conclusions: This new procedure yielded safe and satisfactory aesthetic results. A nomogram with good test performance and discriminative ability was established for predicting patient satisfaction.

Predicting Patient Satisfaction With Medications for Treating Opioid Use Disorder: Case Study Applying Natural Language Processing to Reviews of Methadone and Buprenorphine/Naloxone on Health-Related Social Media.

Medication-assisted treatment (MAT) is an effective method for treating opioid use disorder (OUD), which combines behavioral therapies with one of three Food and Drug Administration-approved medications: methadone, buprenorphine, and naloxone. While MAT has been shown to be effective initially, there is a need for more information from the patient perspective about the satisfaction with medications. Existing research focuses on patient satisfaction with the entirety of the treatment, making it difficult to determine the unique role of medication and overlooking the views of those who may lack access to treatment due to being uninsured or concerns over stigma. Studies focusing on patients' perspectives are also limited by the lack of scales that can efficiently collect self-reports across domains of concerns. A broad survey of patients' viewpoints can be obtained through social media and drug review forums, which are then assessed using automated methods to discover factors associated with medication satisfaction. Because the text is unstructured, it may contain a mix of formal and informal language. The primary aim of this study was to use natural language processing methods on text posted on health-related social media to detect patients' satisfaction with two well-studied OUD medications: methadone and buprenorphine/naloxone. We collected 4353 patient reviews of methadone and buprenorphine/naloxone from 2008 to 2021 posted on WebMD and Drugs.com. To build our predictive models for detecting patient satisfaction, we first employed different analyses to build four input feature sets using the vectorized text, topic models, duration of treatment, and biomedical concepts by applying MetaMap. We then developed six prediction models: logistic regression, Elastic Net, least absolute shrinkage and selection operator, random forest classifier, Ridge classifier, and extreme gradient boosting to predict patients' satisfaction. Lastly, we compared the prediction models' performance over different feature sets. Topics discovered included oral sensation, side effects, insurance, and doctor visits. Biomedical concepts included symptoms, drugs, and illnesses. The F-score of the predictive models across all methods ranged from 89.9% to 90.8%. The Ridge classifier model, a regression-based method, outperformed the other models. Assessment of patients' satisfaction with opioid dependency treatment medication can be predicted using automated text analysis. Adding biomedical concepts such as symptoms, drug name, and illness, along with the duration of treatment and topic models, had the most benefits for improving the prediction performance of the Elastic Net model compared to other models. Some of the factors associated with patient satisfaction overlap with domains covered in medication satisfaction scales (eg, side effects) and qualitative patient reports (eg, doctors' visits), while others (insurance) are overlooked, thereby underscoring the value added from processing text on online health forums to better understand patient adherence.