Community pharmacists' perspectives on cardiovascular disease pharmaceutical care in the United Arab Emirates: a questionnaire survey-based analysis

Background: Community pharmacists play an intermediary role between prescribing physicians and patients in the United Arab Emirates (UAE) and thus are responsible for ensuring that patients receive optimal cardiovascular disease (CVD) pharmaceutical care. Methods: we used a cross-sectional design to assess the perceptions and practices of community pharmacists concerning pharmaceutical care for patients with CVD. A trained researcher visited randomly selected community pharmacies and used a structured questionnaire to conduct in-person interviews with pharmacists. The questionnaire collected demographic data and information on perceptions and practices regarding CVD pharmaceutical care. Results: Five hundred and fifty-one participants were recruited. The average participant age (mean ± SD) was 35 ± 2.7 years. The average perception score regarding CVD prevention and management was 75.6% (95% confidence interval [CI] 77.1%-74.2%), and the average practice score for CVD prevention and management was 87.1% (95% CI 76.5%-79.6%). Bivariate analysis revealed that gender (p = 0.001), education level (p < 0.001), pharmacy position (p = 0.004), work experience (p < 0.001), number of patients served per day (p < 0.001) and being trained on CVD prevention and management (p < 0.001) were significantly associated with perceptions about the prevention and management of CVD. Better practice scores were seen among older participants (OR 1.01; 95% CI 1-1.019), postgraduates (OR 1.77; 95% CI 1.66-1.89), workers at chain pharmacies (OR 1.24; 95% CI 1.11-1.39), pharmacists in charge (OR 1.22; 95% CI 1.01-1.47), pharmacists with >10 years of experience (OR 11.3; 95% CI 6.01-15.62), pharmacists with 6-10 years of experience (OR 4.42; 95% CI 3.90-5) and pharmacists trained on CVD prevention and management (OR 1.29; 95% CI 1.15-1.46). Conclusion: Pharmacy practitioners working in community pharmacies in the UAE actively engage in delivering pharmaceutical care to patients, playing a role in CVD management and prevention. However, they showed low levels of involvement in other healthcare services, specifically in screening and measuring patients' weight, glucose levels, and blood pressure, monitoring treatment responses, maintaining medical records, and reviewing medication refill histories. Activities such as educating patients, providing medication counseling, offering support for treatment adherence, and fostering collaborative relationships with other healthcare providers should be encouraged among UAE community pharmacists to ensure the provision of high-quality patient care.

Bridging the health gap: Measuring the unmet social needs of patients within a dental school clinic

OBJECTIVES

As safety-net clinics, dental school clinics are uniquely positioned to evaluate the unmet social need. There is evidence that patients treated in a safety-net type clinic, such as dental schools, report experiencing one or more of the determinants of health. However, there is limited evidence describing screening for Social Determinants of Health (SDOH) in dental clinics. The purpose of this study is to gain knowledge of the types of social determinants of health that exist in a dental school clinic and how it is reflected in the geographic region of the school.

METHODS

This cross-sectional prospective study used a 20-item questionnaire assessed unmet social needs in a predoctoral clinic. The questionnaire contained multiple choice and binary yes/no questions, organized under SDOH domains: housing, food, transportation, utilities, childcare, employment, education, finances, and personal safety. Socioeconomic and demographic information was captured. The questionnaire was administered via iPad using Qualtrics XM. The data were descriptively and quantitatively analyzed at a significance level of p ≤ 0.05.

RESULTS

There were 175 respondents with a 93.6% response rate, males (49.7%), females (49.1%), and 1.1% nonbinary. Overall, 135 (77.1%) respondents reported having at least one unmet social need. The greatest number of unmet needs was in the domains of employment and finances, with 44% and 41.7% respectively. Respondents who were unable to work stated they often or sometimes worried about running out of food before getting money to buy more, (p = 0.0002), and or the food didn't last before there was money to get more (p = 0.00007). A comparison of annual incomes of respondents earning less than $40K with those earning $40K or more, demonstrated statistically significant differences in unmet social needs for housing (p < 0.0001), food (p = 0.0003, p < 0.0001), utilities (p = 0.0484), employment (p = 0.0016), education (p < 0.0001), and finances (p < 0.0001).

CONCLUSION

Screening patients in the dental clinic was an efficient way to uncover the level of unmet social needs. Annual household income was a predominant driver of unmet social needs: with the greatest number of unmet needs existing in the domains of employment and finances. The results suggest that screening for social determinants of health dental school clinics could be incorporated into routine patient data collection.

Perioperative Management Strategies for the COVID-19 Pandemic at a Facility in China

The spread of coronavirus disease 2019 posed a public health crisis beginning in January 2020, affecting hospitals and health care personnel worldwide and disrupting perioperative services. Organization leaders at Xijing Hospital, Xi'an, China, developed a mitigation system for the OR that involved creating a pandemic response team to identify and implement appropriate infection control practices to prevent virus transmission. The leaders addressed managing the daily surgery schedule through patient screening and a focus on the urgency and volume of procedures. They required increased use of personal protective equipment and more stringent cleaning and disinfection protocols and ensured that the physical and mental health of staff members were monitored and prioritized. This article describes how leaders implemented these enhanced processes to protect personnel from infection as they continued to provide patient care. It also describes how high-risk procedures involving patients with confirmed or suspected infections were managed and discusses lessons learned.

Patient Recruitment System for Clinical Trials: Mixed Methods Study About Requirements at Ten University Hospitals

BACKGROUND

Clinical trials are the gold standard for advancing medical knowledge and improving patient outcomes. For their success, an appropriately sized cohort is required. However, patient recruitment remains one of the most challenging aspects of clinical trials. Information technology (IT) support systems-for instance, patient recruitment systems-may help overcome existing challenges and improve recruitment rates, when customized to the user needs and environment.

OBJECTIVE

The goal of our study is to describe the status quo of patient recruitment processes and to identify user requirements for the development of a patient recruitment system.

METHODS

We conducted a web-based survey with 56 participants as well as semistructured interviews with 33 participants from 10 German university hospitals.

RESULTS

We here report the recruitment procedures and challenges of 10 university hospitals. The recruitment process was influenced by diverse factors such as the ward, use of software, and the study inclusion criteria. Overall, clinical staff seemed more involved in patient identification, while the research staff focused on screening tasks. Ad hoc and planned screenings were common. Identifying eligible patients was still associated with significant manual efforts. The recruitment staff used Microsoft Office suite because tailored software were not available. To implement such software, data from disparate sources will need to be made available. We discussed concrete technical challenges concerning patient recruitment systems, including requirements for features, data, infrastructure, and workflow integration, and we contributed to the support of developing a successful system.

CONCLUSIONS

Identifying eligible patients is still associated with significant manual efforts. To fully make use of the high potential of IT in patient recruitment, many technical and process challenges have to be solved first. We contribute and discuss concrete technical challenges for patient recruitment systems, including requirements for features, data, infrastructure, and workflow integration.

A Patient-Screening Tool for Clinical Research Based on Electronic Health Records Using OpenEHR: Development Study

Background

The widespread adoption of electronic health records (EHRs) has facilitated the secondary use of EHR data for clinical research. However, screening eligible patients from EHRs is a challenging task. The concepts in eligibility criteria are not completely matched with EHRs, especially derived concepts. The lack of high-level expression of Structured Query Language (SQL) makes it difficult and time consuming to express them. The openEHR Expression Language (EL) as a domain-specific language based on clinical information models shows promise to represent complex eligibility criteria.

Objective

The study aims to develop a patient-screening tool based on EHRs for clinical research using openEHR to solve concept mismatch and improve query performance.

Methods

A patient-screening tool based on EHRs using openEHR was proposed. It uses the advantages of information models and EL in openEHR to provide high-level expressions and improve query performance. First, openEHR archetypes and templates were chosen to define concepts called simple concepts directly from EHRs. Second, openEHR EL was used to generate derived concepts by combining simple concepts and constraints. Third, a hierarchical index corresponding to archetypes in Elasticsearch (ES) was generated to improve query performance for subqueries and join queries related to the derived concepts. Finally, we realized a patient-screening tool for clinical research.

Results

In total, 500 sentences randomly selected from 4691 eligibility criteria in 389 clinical trials on stroke from the Chinese Clinical Trial Registry (ChiCTR) were evaluated. An openEHR-based clinical data repository (CDR) in a grade A tertiary hospital in China was considered as an experimental environment. Based on these, 589 medical concepts were found in the 500 sentences. Of them, 513 (87.1%) concepts could be represented, while the others could not be, because of a lack of information models and coarse-grained requirements. In addition, our case study on 6 queries demonstrated that our tool shows better query performance among 4 cases (66.67%).

Conclusions

We developed a patient-screening tool using openEHR. It not only helps solve concept mismatch but also improves query performance to reduce the burden on researchers. In addition, we demonstrated a promising solution for secondary use of EHR data using openEHR, which can be referenced by other researchers.

A Prediction of NPVR ≥ 80% of Ultrasound-Guided High-Intensity Focused Ultrasound Ablation for Uterine Fibroids

Objective: To evaluate factors in predicting the treatment outcome of ultrasound-guided high-intensity focused ultrasound (USgHIFU) ablation for uterine fibroids with a non-perfused volume ratio (NPVR) of at least 80%.

Methods: One thousand patients with uterine fibroids who received USgHIFU were enrolled. Thirty-two independent variables of four dimensions of data set, including general information of patients, clinical symptoms, laboratory tests, and fibroid imaging characteristics, were used to investigate the potential predictors of the NPVR of at least 80% by multivariate logistic regression. NPVR was the gold standard for evaluating the efficiency of HIFU ablation, and a NPVR of at least 80% was considered sufficient ablation, while partial ablation was defined as having an NPVR of <80%.

Results: Out of 1,000 fibroids, 758 obtained sufficient ablation and 242 obtained partial ablation, and the median NPVR was 88.3% (interquartile range: 80.3–94.8%). The probability of NPVR reaching 80% fibroids with a signal intensity of T2WI of hypointense, isointense, and hyperintense was 86.4, 76.5, and 62.6%, respectively; fibroids with an enhancement type of T1WI of slight, irregular, and regular was 81.5, 73.6, and 63.7%, respectively; and fibroids with uterine anteroposterior of 30–130 mm was 57.7–78.3%, respectively. In patients with a platelet count of 50 × 10⁹/L−550 × 10⁹/L, the probability of NPVR reaching 80% is from 53.4 to 80.1%, respectively.

Conclusions: In predicting NPVR ≥ 80%, the signal intensity on T2WI was the most important factor affecting ablative efficiency, followed by enhancement type on T1WI, uterine anteroposterior, and platelet count.

Applied Practice and Possible Leverage Points for Information Technology Support for Patient Screening in Clinical Trials: Qualitative Study

BACKGROUND

Clinical trials are one of the most challenging and meaningful designs in medical research. One essential step before starting a clinical trial is screening, that is, to identify patients who fulfill the inclusion criteria and do not fulfill the exclusion criteria. The screening step for clinical trials might be supported by modern information technology (IT).

OBJECTIVE

This explorative study aimed (1) to obtain insights into which tools for feasibility estimations and patient screening are actually used in clinical routine and (2) to determine which method and type of IT support could benefit clinical staff.

METHODS

Semistandardized interviews were conducted in 5 wards (cardiology, gynecology, gastroenterology, nephrology, and palliative care) in a German university hospital. Of the 5 interviewees, 4 were directly involved in patient screening. Three of them were clinicians, 1 was a study nurse, and 1 was a research assistant.

RESULTS

The existing state of study feasibility estimation and the screening procedure were dominated by human communication and estimations from memory, although there were many possibilities for IT support. Success mostly depended on the experience and personal motivation of the clinical staff. Electronic support has been used but with little importance so far. Searches in ward-specific patient registers (databases) and searches in clinical information systems were reported. Furthermore, free-text searches in medical reports were mentioned. For potential future applications, a preference for either proactive or passive systems was not expressed. Most of the interviewees saw the potential for the improvement of the actual systems, but they were also largely satisfied with the outcomes of the current approach. Most of the interviewees were interested in learning more about the various ways in which IT could support and relieve them in their clinical routine.

CONCLUSIONS

Overall, IT support currently plays a minor role in the screening step for clinical trials. The lack of IT usage and the estimations made from memory reported by all the participants might constrain cognitive resources, which might distract from clinical routine. We conclude that electronic support for the screening step for clinical trials is still a challenge and that education of the staff about the possibilities for electronic support in clinical trials is necessary.

Vaccine-Derived Poliovirus Infection among Patients with Primary Immunodeficiency and Effect of Patient Screening on Disease Outcomes, Iran

Patients with immunodeficiency-associated vaccine-derived poliovirus (iVDPV) are potential poliovirus reservoirs in the posteradication era that might reintroduce polioviruses into the community. We update the iVDPV registry in Iran by reporting 9 new patients. In addition to national acute flaccid paralysis surveillance, cases were identified by screening nonparalyzed primary immunodeficiency (PID) patients. Overall, 23 iVDPV patients have been identified since 1995. Seven patients (30%) never had paralysis. Poliovirus screening accelerated the iVDPV detection rate in Iran after 2014.The iVDPV infection rate among nonparalyzed patients with adaptive PID was 3.1% (7/224), several folds higher than previous estimates. Severe combined immunodeficiency patients had the highest risk for asymptomatic infection (28.6%) compared with other PIDs. iVDPV2 emergence has decreased after the switch from trivalent to bivalent oral poliovirus vaccine in 2016. However, emergence of iVDPV1 and iVDPV3 continued. Poliovirus screening in PID patients is an essential step in the endgame of polio eradication.

Deep Learning-Based Natural Language Processing for Screening Psychiatric Patients

The introduction of pre-trained language models in natural language processing (NLP) based on deep learning and the availability of electronic health records (EHRs) presents a great opportunity to transfer the "knowledge" learned from data in the general domain to enable the analysis of unstructured textual data in clinical domains. This study explored the feasibility of applying NLP to a small EHR dataset to investigate the power of transfer learning to facilitate the process of patient screening in psychiatry. A total of 500 patients were randomly selected from a medical center database. Three annotators with clinical experience reviewed the notes to make diagnoses for major/minor depression, bipolar disorder, schizophrenia, and dementia to form a small and highly imbalanced corpus. Several state-of-the-art NLP methods based on deep learning along with pre-trained models based on shallow or deep transfer learning were adapted to develop models to classify the aforementioned diseases. We hypothesized that the models that rely on transferred knowledge would be expected to outperform the models learned from scratch. The experimental results demonstrated that the models with the pre-trained techniques outperformed the models without transferred knowledge by micro-avg. and macro-avg. F-scores of 0.11 and 0.28, respectively. Our results also suggested that the use of the feature dependency strategy to build multi-labeling models instead of problem transformation is superior considering its higher performance and simplicity in the training process.

Health Services and Infrastructure Recovery of a Major Public Hospital in Liberia During the 2014-2016 Ebola Epidemic

During the 2014-2016 Ebola outbreak, health services in Liberia collapsed. Health care facilities could not support effective infection prevention and control (IPC) practices to prevent Ebola virus disease (EVD) transmission necessitating their closure. This report describes the process by which health services and infrastructure were recovered in the public hospital in Monrovia, Liberia. The authors conducted an assessment of the existing capacity for health care provision, including qualitative interviews with community members, record reviews in Ebola treatment units, and phone calls to health facilities. Assessment information was used to determine necessary actions to re-establish services, including building and environmental renovations, acquiring IPC supplies, changing health care practices, hiring additional staff, developing and using an EVD screening tool, and implementing psychosocial supports. On-site monitoring was continued for 2 years to assess what changes were sustained. Described in the report are 2 cases that highlight the challenge of safely re-establishing services with only a symptom-based screening tool and no laboratory tests available on-site. Despite fears among the public, health workers, and the international community, the actions taken enabled basic health care services to be provided during EVD transmission and led to sustainable improvements. This experience suggests that providing routine medical needs helps limit the morbidity and mortality during times of disease outbreak. (Disaster Med Public Health Preparedness. 2018;13:767-773).

Using intuition or a formal palliative care needs assessment screening process in general practice to predict death within 12 months: A randomised controlled trial

BACKGROUND

Population ageing will lead to more deaths with an uncertain trajectory. Identifying patients at risk of dying could facilitate more effective care planning.

AIM

To determine whether screening for likely death within 12 months is more effective using screening tools or intuition.

DESIGN

Randomised controlled trial of screening tools (Surprise Question plus the Supportive and Palliative Care Indicators Tool for Surprise Question positive patients) to predict those at risk of death at 12 months compared with unguided intuition (clinical trials registry: ACTRN12613000266763).

SETTING/PARTICIPANTS

Australian general practice. A total of 30 general practitioners (screening tool = 12, intuition = 18) screened all patients ( n = 4365) aged ≥70 years seen at least once in the last 2 years.

RESULTS

There were 142 deaths (screening tool = 3.1%, intuition = 3.3%; p = 0.79). General practitioners identified more at risk of dying using Surprise Question (11.8%) than intuition (5.4%; p = 0.01), but no difference with Surprise Question positive then Supportive and Palliative Care Indicators Tool (5.1%; p = 0.87). Surprise Question positive predicted more deaths (53.2%, intuition = 33.7%; p = 0.001), but Surprise Question positive/Supportive and Palliative Care Indicators Tool predictions were similar (5.1%; p = 0.87 vs intuition). There was no difference in proportions correctly predicted to die (Surprise Question = 1.6%, intuition = 1.1%; p = 0.156 and Surprise Question positive/Supportive and Palliative Care Indicators Tool = 1.1%; p = 0.86 vs intuition). Screening tool had higher sensitivity and lower specificity than intuition, but no difference in positive or negative predictive value.

CONCLUSION

Screening tool was better at predicting actual death than intuition, but with a higher false positive rate. Both were similarly effective at screening the whole cohort for death. Screening for possible death is not the best option for initiating end-of-life planning: recognising increased burden of illness might be a better trigger.

The New York PTSD risk score for assessment of psychological trauma: male and female versions

We previously developed a new posttraumatic stress disorder (PTSD) screening instrument-the New York PTSD Risk Score (NYPRS). Since research suggests different PTSD risk factors and outcomes for men and women, in the current study we assessed the suitability of male and female versions of this screening instrument among 3298 adults exposed to traumatic events. Using diagnostic test methods, including receiver operating characteristic (ROC) curve and bootstrap techniques, we examined different prediction domains, including core PTSD symptoms, trauma exposures, sleep disturbances, depression symptoms, and other measures to assess PTSD prediction models for men and women. While the original NYPRS worked well in predicting PTSD, significant interaction was detected by gender, suggesting that separate models are warranted for men and women. Model comparisons suggested that while the overall results appeared robust, prediction results differed by gender. For example, for women, core PTSD symptoms contributed more to the prediction score than for men. For men, depression symptoms, sleep disturbance, and trauma exposure contributed more to the prediction score. Men also had higher cut-off scores for PTSD compared to women. There were other gender-specific differences as well. The NYPRS is a screener that appears to be effective in predicting PTSD status among at-risk populations. However, consistent with other medical research, this instrument appears to require male and female versions to be the most effective.

A brief screening tool for assessing psychological trauma in clinical practice: development and validation of the New York PTSD Risk Score

OBJECTIVE

The objective was to develop a brief posttraumatic stress disorder (PTSD) screening instrument that is useful in clinical practice, similar to the Framingham Risk Score used in cardiovascular medicine.

METHODS

We used data collected in New York City after the World Trade Center disaster (WTCD) and other trauma data to develop a new PTSD prediction tool--the New York PTSD Risk Score. We used diagnostic test methods to examine different clinical domains, including PTSD symptoms, trauma exposures, sleep disturbances, suicidal thoughts, depression symptoms, demographic factors and other measures to assess different PTSD prediction models.

RESULTS

Using receiver operating curve (ROC) and bootstrap methods, five prediction domains, including core PTSD symptoms, sleep disturbance, access to care status, depression symptoms and trauma history, and five demographic variables, including gender, age, education, race and ethnicity, were identified. For the best prediction model, the area under the ROC curve (AUC) was 0.880 for the Primary Care PTSD Screen alone (specificity=82.2%, sensitivity=93.7%). Adding care status, sleep disturbance, depression and trauma exposure increased the AUC to 0.943 (specificity=85.7%, sensitivity=93.1%), a significant ROC improvement (P<.0001). Adding demographic variables increased the AUC to 0.945, which was not significant (P=.250). To externally validate these models, we applied the WTCD results to 705 pain patients treated at a multispecialty group practice and to 225 trauma patients treated at a Level I Trauma Center. These results validated those from the original WTCD development and validation samples.

CONCLUSION

The New York PTSD Risk Score is a multifactor prediction tool that includes the Primary Care PTSD Screen, depression symptoms, access to care, sleep disturbance, trauma history and demographic variables and appears to be effective in predicting PTSD among patients seen in healthcare settings. This prediction tool is simple to administer and appears to outperform other screening measures.

Patient difficulty using tablet computers to screen in primary care

BACKGROUND

Patient-administered computerized questionnaires represent a novel tool to assist primary care physicians in the delivery of preventive health care.

OBJECTIVE

The aim of this study was to assess patient-reported ease of use with a self-administered tablet computer-based questionnaire in routine clinical care.

DESIGN

All patients seen in a university-based primary care practice were asked to provide routine screening information using a touch-screen tablet computer-based questionnaire. Patients reported difficulty using the tablet computer after completion of their first questionnaire.

PATIENTS

Ten thousand nine hundred ninety-nine patients completed the questionnaire between January 2004 and January 2006.

MEASUREMENTS

We calculated rates of reporting difficulty (no difficulty, some difficulty, or a lot of difficulty) using the tablet computers based on patient age, sex, race, educational attainment, marital status, and number of comorbid medical conditions. We constructed multivariable ordered logistic models to identify predictors of increased self-reported difficulty using the computer.

RESULTS

The majority of patients (84%) reported no difficulty using the tablet computers to complete the questionnaire, with only 3% reporting a lot of difficulty. Significant predictors of reporting more difficulty included increasing age [odds ratio (OR) 1.05, 95% confidence interval (CI) 1.05-1.05)]; Asian race (OR 2.3, 95% CI 1.8-2.9); African American race (OR 1.4, 95% CI 1.2-1.6); less than a high school education (OR 3.0, 95% CI 2.6-3.4); and the presence of comorbid medical conditions (1-2: OR 1.3, 95% CI 1.2-1.5; > or =3: OR 1.7 95% CI 1.5-2.1).

CONCLUSIONS

The majority of primary care patients reported no difficulty using a self-administered tablet computer-based questionnaire. While computerized questionnaires present opportunities to collect routine screening information from patients, attention must be paid to vulnerable groups.