Use of social media for the improvement of radiation safety knowledge among Saudi Arabian radiographers.

BACKGROUND: Radiographers have used social media networks for education, research, professional development and other purposes. However, in Saudi Arabia, there are no studies on the use of social media by radiographers. Therefore, the objective of this research was to evaluate the use of social media for the improvement of radiation safety knowledge among Saudi Arabian radiographers. METHODS: A questionnaire was designed to collect the data from Saudi Arabian radiographers. The questionnaire was created using Google Forms and was sent to 530 radiographers using WhatsApp. In total, 159 participants completed and returned the questionnaire through WhatsApp. The response rate was 30%. Basic descriptive statistics were employed to analyse the data. RESULTS: Most of the participants (79.9%) thought that social media could be used as a tool for the improvement of radiation safety knowledge. Also, almost half of participants (49.7%) employed social media when they needed to obtain information about radiation protection. Similarly, a majority of respondents (69.2%) used social media when they required information related to radiation safety. In addition, 81.7% of participants observed on video the existing information on radiation safety. Also, 71.7% of them were disposed to expand the use of social media to obtain information for radiation protection in their professional activities. CONCLUSION: The results indicate that social media can help to improve radiation safety knowledge among Saudi Arabian radiographers. Consequently, participants were willing to increase the use of these tools in their professional work.

Identifying the Most Costly Patients in Radiation Oncology and Predicting the Top Spenders.

PURPOSE: Quality payment programs aim to adjust payments on the basis of quality and cost; however, few quality metrics exist in radiation oncology. This study evaluates and predicts the top spenders (TS) after radiation therapy (RT). MATERIALS AND METHODS: Patient characteristics, cancer details, treatments, toxicity, and survival data were collected for patients treated with RT at Mayo Clinic from 2007 to 2016. Standardized costs were obtained and adjusted for inflation. TSs were identified as those with greater than 93rd percentile costs (≥ $120,812). Prediction models were developed to predict TSs using training and validation sets using information available at consultation, after RT, and at last follow-up. RESULTS: A total of 15,131 patients were included and 1,065 TSs identified. Mean cost overall was $55,290 (median, $39,996) for all patients. Prediction models 1, 2, and 3 had concordance statistics of 0.83 to 0.83, 0.85 to 0.85, and 0.87 to 0.88, respectively in training and validation, indicating excellent prediction of TSs. Factors that were most predictive of TSs included stage N/A and stage 4 (v stage 0; odds ratio [OR], 18.23 and 8.44, respectively; P < .001); hematologic, upper GI, skin and lung cancers (v breast; OR, 11.45, 7.69, 3.81, and 2.43, respectively; P < .01); immunotherapy, surgery, and chemotherapy use (OR, 4.36, 2.51, and 1.61, respectively; P < .01); hospitalizations within 90 days of RT (OR, 2.26; P < .01); or death during the episode (OR, 1.56; P < .01). CONCLUSION: This is the first study of its kind to predict with high accuracy the highest spenders in radiation oncology. These patients may benefit from pre-emptive management to mitigate costs, or may require exclusion or adjustment from quality payment programs.

Cost of Acute and Follow-Up Care in Patients With Pre-Existing Psychiatric Diagnoses Undergoing Radiation Therapy.

PURPOSE: The impact of psychiatric comorbidities on the cost of cancer care in radiation oncology practices is not well studied. We assessed the acute and 24-month follow-up costs for patients with and without pre-existing psychiatric comorbidities undergoing radiation therapy. METHODS AND MATERIALS: Patients with cancer undergoing radiation therapy at our institution from 2009 to 2014 were denoted as having pre-existing psychiatric conditions (Psych group) if they had associated billing codes for any of the 422 International Classification of Diseases, 9th revision psychiatric conditions during the 12 months before their cancer diagnosis. The Elixhauser comorbidity index was calculated, excluding psychiatric categories. Medicare reimbursement was assigned to professional services, and Medicare departmental cost-to-charge ratios were applied to service line hospital charges and adjusted for inflation to create 2017 standardized costs. Acute (0-6 month) and follow-up (6-24 month) costs were subcategorized into clinic, emergency department, hospital inpatient, and outpatient costs. RESULTS: Among 1275 patients, 126 (9.9%) had at least 1 pre-existing psychiatric diagnosis. On univariate analysis, both acute and long-term costs were higher in the Psych group. The largest significant differences in costs were follow-up hospital inpatient costs ($5861 higher; 95% confidence interval [CI], $687-$11,035; P = .002), follow-up hospital outpatient costs ($2086 higher; 95% CI, -$142 to $4,314; P = .040), and follow-up emergency department costs ($396 higher; 95% CI, $149-$643; P < .001). Age, race, sex, and treatment modalities were comparable, but the Psych group patients had more median comorbidities (2 vs 1) and had more respiratory cancer diagnoses than the nonpsychiatric group (31% vs 17%). On multivariate analysis adjusted for age, sex, cancer diagnosis, and comorbidities, global follow-up costs remained 150% higher in the Psych group (P < .001). Acute costs were similar after adjustment (P = .63). CONCLUSIONS: Psychiatric comorbidities independently predict elevated healthcare costs in patients treated for cancer. Radiation oncology payment models should consider adjustments to account for psychiatric comorbidities because addressing these may mitigate cost differential.

Patient portal adoption and use by hospitalized cancer patients: a retrospective study of its impact on adverse events, utilization, and patient satisfaction.

BACKGROUND: Portal use has been studied among outpatients, but its utility and impact on inpatients is unclear. This study describes portal adoption and use among hospitalized cancer patients and investigates associations with selected safety, utilization, and satisfaction measures. METHODS: A retrospective review of 4594 adult hospitalized cancer patients was conducted between 2012 and 2014 at Mayo Clinic in Jacksonville, Florida, comparing portal adopters, who registered for a portal account prior to hospitalization, with nonadopters. Adopters were classified by their portal activity during hospitalization as active or inactive inpatient users. Univariate and several logistic and linear regression models were used for analysis. RESULTS: Of total patients, 2352 (51.2%) were portal adopters, and of them, 632 (26.8%) were active inpatient users. Portal adoption was associated with patients who were young, female, married, with higher income, and had more frequent hospitalizations (P < .05). Active inpatient use was associated with patients who were young, married, nonlocals, with higher disease severity, and were hospitalized for medical treatment (P < .05). In univariate analyses, self-management knowledge scores were higher among adopters vs nonadopters (84.3 and 80.0, respectively; P = .01) and among active vs inactive inpatient users (87.0 and 83.3, respectively; P = .04). In regression models adjusted for age and disease severity, the association between portal behaviors and majority of measures were not significant (P > .05). CONCLUSIONS: Over half of our cancer inpatients adopted a portal prior to hospitalization, with increased adoption associated with predisposing and enabling determinants (eg: age, sex, marital status, income), and increased inpatient use associated with need (eg: nonlocal residence and disease severity). Additional research and greater effort to expand the portal functionality is needed to impact inpatient outcomes.