Impact of COVID-19 infections and vaccination on menstrual cycle symptoms in the south of Jordan: a cross-sectional study.

BACKGROUND: Several recent studies have highlighted the need for more evaluation of the impact of COVID-19 infections and vaccines on the reproductive system and menstruation. This study aimed to assess the impact of COVID-19 infection and vaccines on menstrual symptoms. METHODS: A cross-sectional survey utilizing face-to-face interviews from January 1 to 31 March 2022 was conducted in the city of Al-Karak in southern Jordan. The questionnaire included sociodemographic characteristics, medical and reproductive history, the contraceptive method used if any, menstrual cycle (MC) status, previous medical and drug history, and the impact of infection and vaccination on the MC. RESULTS: The study questionnaire was completed by 400 participants with a mean age of 32.1±12.6 years. Regarding the history of COVID-19 infections, 33.8% of the participants reported a history of confirmed COVID-19 infections, 77.8% of them did not report any menstrual changes following the infection, while the remaining 22.2% reported changes in menstruation. The most commonly reported post-COVID-19 manifestations were irregular (27.6%) and light menstrual cycle (MC) (24.15) or dysmenorrhea (24.1%). Heavy menstruation was reported by 17.2% of participants post-COVID-19 infection. Two-thirds of the study participants (66.6%) reported no changes in the MC following the administration of the COVID-19 vaccine. The most reported symptoms for those who experienced changes in the MC following the vaccination were irregular cycle (13.1%), heavy menstruation (7%), and light menstruation (7%). Other reported symptoms were dysmenorrhea (4.6%), intermenstrual bleeding (1.2%), and amenorrhea (0.5%). CONCLUSION: This study revealed minor changes in the MC following COVID-19 infections and administration of the COVID-19 vaccine. These findings are consistent with published reports. It is recommended that future clinical trials for new vaccines for women of childbearing age include outcomes related to sex hormones and MC. Women should be encouraged to take the vaccines and report symptoms to healthcare professionals for further assessment.

Improvement of Dialysis Dosing Using Big Data Analytics.

OBJECTIVES: Large amounts of healthcare data are now generated via patient health records, records of diagnosis and treatment, smart devices, and wearables. Extracting insights from such data can transform healthcare from a traditional, symptom-driven practice into precisely personalized medicine. Dialysis treatments generate a vast amount of data, with more than 100 parameters that must be regulated for ideal treatment outcomes. When complications occur, understanding electrolyte parameters and predicting their outcomes to deliver the optimal dialysis dosing for each patient is a challenge. This study focused on refining dialysis dosing by utilizing emerging data from the growing number of dialysis patients to improve patients' quality of life and well-being. METHODS: Exploratory data analysis and data prediction approaches were performed to gather insights from patients' vital electrolytes on how to improve the patients' dialysis dosing. Four predictive models were constructed to predict electrolyte levels through various dialysis parameters. RESULTS: The decision tree model showed excellent performance and more accurate results than the support vector machine, linear regression, and neural network models. CONCLUSIONS: The predictive models identified that pre-dialysis blood urea nitrogen, pre-weight, dry weight, anticoagulation, and sex had the most significant effects on electrolyte concentrations. Such models could fine-tune dialysis dosing levels for the growing number of dialysis patients to improve each patient's quality of life, life expectancy, and well-being, and to reduce costs, efforts, and time consumption for both patients and physicians. The study's results need to be validated on a larger scale.

Identification of Coronary Artery Diseases Using Photoplethysmography Signals and Practical Feature Selection Process.

A low-cost, fast, dependable, repeatable, non-invasive, portable, and simple-to-use vascular screening tool for coronary artery diseases (CADs) is preferred. Photoplethysmography (PPG), a low-cost optical pulse wave technology, is one method with this potential. PPG signals come from changes in the amount of blood in the microvascular bed of tissue. Therefore, these signals can be used to figure out anomalies within the cardiovascular system. This work shows how to use PPG signals and feature selection-based classifiers to identify cardiorespiratory disorders based on the extraction of time-domain features. Data were collected from 360 healthy and cardiovascular disease patients. For analysis and identification, five types of cardiovascular disorders were considered. The categories of cardiovascular diseases were identified using a two-stage classification process. The first stage was utilized to differentiate between healthy and unhealthy subjects. Subjects who were found to be abnormal were then entered into the second stage classifier, which was used to determine the type of the disease. Seven different classifiers were employed to classify the dataset. Based on the subset of features found by the classifier, the Naïve Bayes classifier obtained the best test accuracy, with 94.44% for the first stage and 89.37% for the second stage. The results of this study show how vital the PPG signal is. Many time-domain parts of the PPG signal can be easily extracted and analyzed to find out if there are problems with the heart. The results were accurate and precise enough that they did not need to be looked at or analyzed further. The PPG classifier built on a simple microcontroller will work better than more expensive ones and will not make the patient nervous.

Survey for Computer-Aided Tools and Databases in Metabolomics.

Metabolomics has advanced from innovation and functional genomics tools and is currently a basis in the big data-led precision medicine era. Metabolomics is promising in the pharmaceutical field and clinical research. However, due to the complexity and high throughput data generated from such experiments, data mining and analysis are significant challenges for researchers in the field. Therefore, several efforts were made to develop a complete workflow that helps researchers analyze data. This paper introduces a review of the state-of-the-art computer-aided tools and databases in metabolomics established in recent years. The paper provides computational tools and resources based on functionality and accessibility and provides hyperlinks to web pages to download or use. This review aims to present the latest computer-aided tools, databases, and resources to the metabolomics community in one place.

Untargeted approach to investigating the metabolomics profile of type 2 diabetes emiratis.

Type 2 Diabetes (T2D) is expected to be the seventh most significant cause of death worldwide by 2030. Although research into its mechanism has received the attention it deserves, our understanding of T2D is still limited. This case-control study employs untargeted metabolomics to explore novel T2D plasma biomarkers in the Emirati population. Ninety-two UAE nationals were included in the cohort, with fifty T2D and forty-two non-T2D profiles. Participants were then stratified into three groups based on metabolic profiles, clinically verified diabetic status, and current HbA1c values: namely controlled diabetics, uncontrolled diabetics and prediabetics, and non-diabetics. The study identified fifteen significant differentially abundant metabolites between the uncontrolled diabetics group and the prediabetics or controlled diabetics group. Interestingly, some metabolites essential for the corticosteroid and thyroid signaling pathways were found to be significantly elevated in poorly controlled T2D, including cortisol, glycocholic acid, bile acids, thyroxine, and the tryptophan metabolite, 5-hydroxyindoleacetic acid. These findings align with those from prior western cohorts and suggest an intriguing linkage between T2D glycemic control and thyroid and adrenal signaling that may provide new diagnostic and prognostic indicators. RESEARCH SIGNIFICANCE: This study investigates the underlooked metabolomic role and correlation with T2D in the UAE population. The report indicates fifteen significant differentially abundant metabolites between on diabetics, uncontrolled diabetics and or controlled diabetics or prediabetics. This panel of metabolites such as thyroxine and corticosteroids should be considered further as potential diagnostic or prognostic biomarkers for T2D in the region.

Quality of Life and Psychological Wellbeing of Breast Cancer Survivors in the Kingdom of Saudi Arabia.

INTRODUCTION: Breast cancer is the most common cancer among Saudi population. Breast cancer patients suffer from several negative consequences after treatment and these include pain, fatigue, sexual problems, appearance and body image concerns, with psychological dysfunction. This could affect the patient quality of life and psychological well-being. METHODS: a multicenter cross-sectional study to assess quality of life and psychological wellbeing and their predictors for female breast cancers survivors diagnosed between 1 January 2015 and May 2017 with the assessment conducted at 12 to 36 months after initial diagnosis. Assessment was performed using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30), the Breast Module (QLQ-BR23) and the Hospital Anxiety and Depression Scale (HADS). RESULTS: 246 Breast cancer patients participated in the study with a mean age of 49.5±10.9. The mean global health status has a mean of 72.7±23.5. The worst domain of the functioning scales was physical functioning (mean score of 62.14±26.03, while the best scores were for social functioning of 80.06±29.18. For the symptom scales, the worst scores were reported for fatigue and pain. Results of HADS scale showed that 57% had moderate to severe depression, while 44% had moderate to severe anxiety. Only 6.8% of the participants reported receiving psychosocial support. DISCUSSION: Breast cancer survivors in the KSA have overall good quality of life scores when compared with patients from Western countries. However, their psychological wellbeing is more impaired. There is an urgent need for psychosocial support programs and psychological screening and consultation for breast cancer patients at cancer care centers in the KSA.

Untargeted Metabolomic Plasma Profiling of Emirati Dialysis Patients with Diabetes versus Non-Diabetic: A Pilot Study.

Diabetic kidney disease (DKD) is a severe irreversible complication of diabetes mellitus that further disturbs glucose metabolism. Identifying metabolic changes in the blood may provide early insight into DKD pathogenesis. This study aims to determine blood biomarkers differentiating DKD from non-diabetic kidney disease in the Emirati population utilizing the LC-MS/MS platform. Blood samples were collected from hemodialysis subjects with and without diabetes to detect indicators of pathological changes using an untargeted metabolomics approach. Metabolic profiles were analyzed based on clinically confirmed diabetic status and current HbA1c values. Five differentially significant metabolites were identified based on the clinically confirmed diabetic status, including hydroxyprogesterone and 3,4-Dihydroxymandelic acid. Similarly, we identified seven metabolites with apparent differences between Dialysis Diabetic (DD) and Dialysis non-Diabetic (DND) groups, including isovalerylglycine based on HbA1c values. Likewise, the top three metabolic pathways, including Tyrosine metabolism, were identified following the clinically confirmed diabetic status. As a result, nine different metabolites were enriched in the identified metabolic pathways, such as 3,4-Dihydroxymandelic acid. As a result, eleven different metabolites were enriched, including Glycerol. This study provides an insight into blood metabolic changes related to DKD that may lead to more effective management strategies.

Quality of Life and Psychological Wellbeing of Colorectal Cancer Survivors in the KSA.

INTRODUCTION: Colorectal cancer (CRC) ranked first among cancers reported in males and ranked third amongst females in Saudi Arabia. CRC cancer symptoms or symptoms secondary to treatment, such as diarrhea, constipation, fatigue and loss of appetite are very common and has significant negative effects on the quality of life (QoL). METHODS: This project was a cross-sectional study of colorectal cancer survivors diagnosed between 1 January 2015 and May 2017. Assessment was performed using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30), the colorectal cancer specific module (EORTC QLQ-CR 29) and the Hospital Anxiety and Depression Scale (HADS). Data on potential predictors of scores were also collected. RESULTS: 115 CRC patients from Middle, Eastern and Western regions of the KSA participated in the study. Participants have unexpectedly low global health score with a mean of 56.9±31.3. Physical functioning scale had the lowest score of 61.3±27.7. Regarding the generic symptoms of cancer, fatigue was the worst symptom, followed by appetite loss. Psychological wellbeing assessment utilizing HADS reveals alarming outcomes for survivors of CRC in the KSA with high proportion of participants with moderate to severe depression (55%) and a good proportion of participants with moderate to high anxiety (31%). Only 3.7% of participants reported receiving psychosocial support. DISCUSSION: Results of this project reveal an overall trend of low scores of quality of life amongst colorectal cancer patients in the KSA when compared with regional or international figures. Consistent results for psychological wellbeing were reached. We recommend routine screening for quality of life and psychological wellbeing and including the outcomes per individual patient care. Psychological support is highly needed for cancer survivors.

Transient high thyroid stimulating hormone and hypothyroidism incidence during follow up of subclinical hypothyroidism.

Objectives. Given the high prevalence of subclinical hypothyroidism (SCH), defined as high thyroid stimulating hormone (TSH) and normal free thyroxine (FT4), and uncertainty on treatment, one of the major challenges in clinical practice is whether to initiate the treatment for SCH or to keep the patients under surveillance. There is no published study that has identified predictors of short-term changes in thyroid status amongst patients with mild elevation of TSH (4.5-10 mIU/L). Subjects and Results. A cohort study was conducted on patients with SCH detected through a general population screening program, who were followed for six months. This project identified factors predicting progression to hypothyroid status, persistent SCH and transient cases. A total of 656 participants joined the study (431 controls and 225 were patients with SCH). A part of participants (12.2%) developed biochemical hypothyroidism during the follow-up, while 73.8% of the subjects became euthyroid and the remained ones (13.4%) stayed in the SCH status. The incidence of overt hypothyroidism for participants with TSH above 6.9 mIU/L was 36.7%, with incidence of 42.3% for females. Anti-thyroid peroxidase antibodies (TPO) positivity is an important predictor of development of hypothyroidism; however, it could be also positive due to transient thyroiditis. Conclusions. It can be concluded that females with TSH above 6.9 mIU/L, particularly those with free triiodothyronine (FT3) and FT4 in the lower half of the reference range, are more likely to develop biochemical hypothyroidism. Therefore, it is recommended to give them a trial of levothyroxine replacement. It is also recommended to repeat TSH after six months for male subjects and participants with baseline TSH equal or less than 6.9 mIU/L.

Prediction of COVID-19 Hospital Length of Stay and Risk of Death Using Artificial Intelligence-Based Modeling.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly infectious virus with overwhelming demand on healthcare systems, which require advanced predictive analytics to strategize COVID-19 management in a more effective and efficient manner. We analyzed clinical data of 2017 COVID-19 cases reported in the Dubai health authority and developed predictive models to predict the patient's length of hospital stay and risk of death. A decision tree (DT) model to predict COVID-19 length of stay was developed based on patient clinical information. The model showed very good performance with a coefficient of determination R 2 of 49.8% and a median absolute deviation of 2.85 days. Furthermore, another DT-based model was constructed to predict COVID-19 risk of death. The model showed excellent performance with sensitivity and specificity of 96.5 and 87.8%, respectively, and overall prediction accuracy of 96%. Further validation using unsupervised learning methods showed similar separation patterns, and a receiver operator characteristic approach suggested stable and robust DT model performance. The results show that a high risk of death of 78.2% is indicated for intubated COVID-19 patients who have not used anticoagulant medications. Fortunately, intubated patients who are using anticoagulant and dexamethasone medications with an international normalized ratio of <1.69 have zero risk of death from COVID-19. In conclusion, we constructed artificial intelligence-based models to accurately predict the length of hospital stay and risk of death in COVID-19 cases. These smart models will arm physicians on the front line to enhance management strategies to save lives.

BRCA1 and BRCA2 genes mutations among high risk breast cancer patients in Jordan.

Familial breast cancer is estimated to account for 15-20% of all cases of breast cancer. Surveillance for familial breast cancer is well-established world-wide. However, this service does not exist in Jordan, due to the scarcity of information with regard to the genetic profiling of these patients, and therefore lack of recommendations for policy-makers. As such, patients with very strong family history of breast or ovarian cancers are not screened routinely; leading to preventable delay in diagnosis. Whole coding sequencing for BCRA1/BCRA2 using next-generation sequencing (NGS)/Ion PGM System was performed. Sanger sequencing were then used to confirm the pathogenic variants detected by NGS. In this study, 192 breast cancer patients (and 8 ovarian cancer cases) were included. The prevalence of recurrent pathogenic mutations was 14.5%, while the prevalence of newly detected mutations was 3.5%. Two novel pathogenic mutations were identified in BRCA2 genes. The common mutations in the Ashkenazi population used for screening may not apply in the Jordanian population, as previously reported mutations were not prevalent, and other new mutations were identified. These data will aid to establish a specific screening test for BRCA 1/BRCA2 in the Jordanian population.

Do modern family planning methods impact women's quality of life? Jordanian women's perspective.

BACKGROUND: Although Jordan has made progress in meeting Family Planning (FP) needs in last decades, recently the use of FP methods has declined significantly. Women's personal experiences, knowledge, and perceptions of how a FP method might impact their quality of life (QoL) can influence FP decisions. However, a lack of comprehensive understanding of the impact of modern FP methods on women's QoL continues to exist among Jordanian couples. Therefore, this study aimed to investigate the relationship between the use of common modern FP methods and QoL among Jordanian women. METHODS: Using the WHOQOL-BREF questionnaire along with other questions, non-pregnant women of reproductive age were interviewed at their homes through face-to-face structured interviews. Women who visited the obstetrics and gynecology clinic of King Abdullah University Hospital for contraceptive advice and follow-up consultations were also included. RESULTS: A total of 548 women aged between 18 and 49 participated in the study. Based on the WHOQOL-BREF scale, the overall mean (SD) scores of the four domains were found to be average. Our findings show that women who used Intra Uterine Devices (IUDs) and women whose husbands used condoms had better QoL in the four domains (physical health, psychological health, social relationships, and environment) than those who used Oral Contraceptives (OCs). Women who used implant and injectable hormonal contraceptives had better QoL in terms of the physical health and social relationships domains. In contrast, women who had undergone permanent sterilization had lower QoL scores in all of the four domains. Further analysis revealed that women who had undergone tubal sterilization were less satisfied overall and more likely to experience side effects than women who used OCs. CONCLUSION: The choice to use contraceptives and decide freely whether and when to have children is regarded as a fundamental reproductive health right and is strongly linked to women's health and QoL. Women who use OCs and women who have undergone permanent sterilization are likely to have lower QoL than women who use IUDs or implant and injectable hormones and those whose husbands use condoms.

A Cross-Sectional Study to Assess the Prevalence of Adult Thyroid Dysfunction Disorders in Jordan.

Background: Insufficient production of thyroid hormones results in hypothyroidism, while overproduction results in hyperthyroidism. These are common adult disorders, with hypothyroidism more common in the elderly. Jordan has had past problems with dietary iodine deficiency but there are no published studies assessing the population prevalence of these disorders in the Arab Middle East. Methods: A cross-sectional study was conducted in three representative areas of Jordan. There were 7085 participants with a mean age of 40.8 years. Participants completed a questionnaire and had blood taken for thyroid analysis. Results:Hypothyroidism: The prevalence of any hypothyroidism (already diagnosed and/or identified by blood testing) was 17.2% in females and 9.1% in males. Undiagnosed prevalence was 8% and 6.2% for females and males, respectively. The prevalence of subclinical hypothyroidism, defined as high serum thyrotropin (TSH) and normal serum-free thyroxine (fT4), was 5.98% among females and 4.40% among males. The prevalence of overt hypothyroidism, defined as high TSH and low fT4, was 2.00% among females and 1.80% among males. Only 53.5% (55.3% for females, 42.1% males) of those previously diagnosed with hypothyroidism had TSH levels within the appropriate range. Hyperthyroidism: The prevalence of any hyperthyroidism (already diagnosed and/or identified by blood testing) was 1.8% in females and 2.27% in males. The undiagnosed prevalence was 1.4% and 2.1% for females and males, respectively. The prevalence of subclinical hyperthyroidism (low TSH and normal fT4) was 1.20% and 1.80% among males and females accordingly. The prevalence of overt hyperthyroidism (low TSH and high fT4) was 0.2% among females and 0.3% among males. About 85.7% (83.3% for females, 100% males) of those previously diagnosed with hyperthyroidism had TSH levels within the appropriate range. Conclusions: The results of this study reveal that the total prevalence of thyroid dysfunction among adult females and males in Jordan is very high compared with international statistics, particularly in the rates of undiagnosed cases. This indicates the need for further assessment of the value of screening for adult hypothyroidism in Jordan.

The use of echocardiographic and clinical data recorded on admission to simplify decision making for elective percutaneous coronary intervention: a prospective cohort study.

BACKGROUND: Coronary artery disease (CAD), a leading cause of mortality, affects patient health-related quality of life (HRQoL). Elective percutaneous coronary interventions (ePCIs) are usually performed to improve HRQoL of CAD patients. The aim of this study was to design models using admission data to predict the outcomes of the ePCI treatments on the patients' HRQoL. METHODS: This prospective cohort study was conducted with CAD patients who underwent ePCIs at the King Abdullah University Hospital in Jordan from January 2014 through May 2015. Six months after their ePCI procedures, the participants completed the improved MacNew (QLMI-2) questionnaire, which was used for evaluating three domains (physical, emotional and social) of HRQoL. Multivariate linear regression was used to design models to predict the three domains of HRQoL from echocardiographic findings and clinical data that are routinely measured on admission. RESULTS: The study included 239 patients who underwent ePCIs and responded to the QLMI-2 questionnaire. The mean age (± standard deviation) of the participants was 55.74 ± 11.84 years, 54.58 ± 11.37 years for males (n = 174) and 59.11 ± 12.49 years for females (n = 65). The average scores for physical, emotional and social HRQoL were 4.38 ± 1.27, 4.4 ± 1.11, and 4.37 ± 1.32, respectively. Out of the 42 factors inputted to the models to predict HRQoL scores, 10, 9, and 9 factors were found to be significant determinants for physical, emotional and social domains, respectively, with adjusted coefficients of determination of 0.630, 0.604 and 0.534, respectively. Basophil levels on admission showed a significant positive correlation with the three domains of HRQoL, while aortic root diameter showed a negative correlation. Scores for the three domains were significantly lower in women than in men. Hypertensive and diabetic patients had significantly lower HRQoL scores than patients without hypertension and diabetes. CONCLUSION: The prediction of HRQoL scores 6 months after an ePCI is possible based on data acquired on admission. The models developed here can be used as decision-making tools to guide physicians in identifying the efficacy of ePCIs for individual patients, hence decreasing the rate of inappropriate ePCIs and reducing costs and complications.

Engagement of Jordanian Physicians in Continuous Professional Development: Current Practices, Motivation, and Barriers.

BACKGROUND: Mandatory relicense of all physicians in Jordan went into effect at the beginning of May 2018. The bylaw states that all physicians should engage in Continuing Professional Development (CPD) in order to upgrade their knowledge and maintain competency as a prerequisite to renew their license every 5 years. The characteristics of effective CPD are different from one country to another. Jordan has decided to link CPD to mandatory relicense; however, no research has been done to identify the factors that influence CPD offerings, needs, practices, experiences, and effectiveness in the healthcare sector in Jordan. This paper reviews the history of CPD and CME, and the different options to upgrade and improve the competence of physicians. It explores the current practices, motivation, and barriers for physicians to get engaged in CPD activities in Jordan. PURPOSE: The purpose of this research was to provide a better understanding of the state of CPD in the healthcare sector in Jordan with a view to informing the development of Jordan's first CPD framework. The findings of this research will provide policymakers with baseline information concerning current CPD practices, experiences, and attitudes of physicians towards CPD, and enablers and contributors to effective CPD in Jordan. METHODS: Stratified clustered self-selected participants that represented physicians working at all healthcare sectors in Jordan were used in this study. A structured pre-tested self-reported questionnaire was used to collect the data. A total of 457 physicians were included in the sample according to one-proportion sample size calculation method, and they were distributed among the healthcare sectors based on their shared proportions. CONCLUSION: Despite considerable evidence supporting the role of CPD in maintaining competency of physicians, participating in CPD activities in Jordan is compromised by lack of mandatory laws and barriers related to staff shortage, heavy workload, limited funds, lack of time, and cost. Personal interests and career progression are the top motivators for CPD. Most Jordanian physicians are interested in CPD activities related to health/medical informatics and enhancing their skills in evidence-informed practice. We recommend that future interventions and health policy directions should be informed by these findings in order to optimize uptake of CPD programs in Jordan.

Design of a supply chain distribution network for communicable diseases: Hepatitis A in Jordan as a case study.

PURPOSE: Distribution network plays a vital role on the efficiency and the responsiveness of a supply chain. Any product or service goes through a network until it reaches the final customer. Health care systems incorporate distribution networks to better provide health services to patients. In this study, a distribution network for communicable diseases has been developed. The proposed network addresses Hepatitis A in Jordan as a case study, as it is considered one of the common communicable diseases in Jordan. FINDINGS: A regression model was developed to predict future incidents of Hepatitis A in Jordan to build a distribution network based on the future required resources. An optimization clustering model was used to structure the appropriate distribution network. The proposed network was compared with the current network used for distribution of medications for Hepatitis A. CONCLUSION: The new network incurs less cost in delivering medications to the required hospitals as the traveling distance is less. As future work, it is recommended to incorporate more communicable diseases to develop more realistic distribution network.

The Impact of Applying Quality Management Practices on Patient Centeredness in Jordanian Public Hospitals: Results of Predictive Modeling.

Targeting the patient's needs and preferences has become an important contributor for improving care delivery, enhancing patient satisfaction, and achieving better clinical outcomes. This study aimed to examine the impact of applying quality management practices on patient centeredness within the context of health care accreditation and to explore the differences in the views of various health care workers regarding the attributes affecting patient-centered care. Our study followed a cross-sectional survey design wherein 4 Jordanian public hospitals were investigated several months after accreditation was obtained. Total 829 clinical/nonclinical hospital staff members consented for study participation. This sample was divided into 3 main occupational categories to represent the administrators, nurses, as well as doctors and other health professionals. Using a structural equation modeling, our results indicated that the predictors of patient-centered care for both administrators and those providing clinical care were participation in the accreditation process, leadership commitment to quality improvement, and measurement of quality improvement outcomes. In particular, perceiving the importance of the hospital's engagement in the accreditation process was shown to be relevant to the administrators (gamma = 0.96), nurses (gamma = 0.80), as well as to doctors and other health professionals (gamma = 0.71). However, the administrator staff (gamma = 0.31) was less likely to perceive the influence of measuring the quality improvement outcomes on the delivery of patient-centered care than nurses (gamma = 0.59) as well as doctors and other health care providers (gamma = 0.55). From the nurses' perspectives only, patient centeredness was found to be driven by building an institutional framework that supports quality assurance in hospital settings (gamma = 0.36). In conclusion, accreditation is a leading factor for delivering patient-centered care and should be on a hospital's agenda as a strategy for continuous quality improvement.

Using decision trees to explore the association between the length of stay and potentially avoidable readmissions: A retrospective cohort study.

BACKGROUND: There is a growing concern that reduction in hospital length of stay (LOS) may raise the rate of hospital readmission. This study aims to identify the rate of avoidable 30-day readmission and find out the association between LOS and readmission. METHODS: All consecutive patient admissions to the internal medicine services (n = 5,273) at King Abdullah University Hospital in Jordan between 1 December 2012 and 31 December 2013 were analyzed. To identify avoidable readmissions, a validated computerized algorithm called SQLape was used. The multinomial logistic regression was firstly employed. Then, detailed analysis was performed using the Decision Trees (DTs) model, one of the most widely used data mining algorithms in Clinical Decision Support Systems (CDSS). RESULTS: The potentially avoidable 30-day readmission rate was 44%, and patients with longer LOS were more likely to be readmitted avoidably. However, LOS had a significant negative effect on unavoidable readmissions. CONCLUSIONS: The avoidable readmission rate is still highly unacceptable. Because LOS potentially increases the likelihood of avoidable readmission, it is still possible to achieve a shorter LOS without increasing the readmission rate. Moreover, the way the DT model classified patient subgroups of readmissions based on patient characteristics and LOS is applicable in real clinical decisions.

Risk assessment of comorbidities on 30-day avoidable hospital readmissions among internal medicine patients.

RATIONALE, AIMS AND OBJECTIVES: Reducing the rate of hospital readmissions, particularly avoidable ones, has significant implications on patient outcomes, cost containment, and quality of care. Given that the reason of readmission may differ from the patient's main diagnosis in the index admission, this study aims to assess the influence of index comorbidities on the primary readmission diagnoses and explore the risk of deemed avoidable readmission because of prior comorbidities. METHODS: A retrospective review of 3962 discharges was conducted at a 527-bed teaching hospital in Jordan, utilizing data related to 2025 internal medicine patients. RESULTS: Among all discharges, 29% were followed by a 30-day readmission, of which 13% were identified as potentially avoidable. Of all readmissions, 36% of patients were readmitted because of one of the comorbidities that had been identified at index admission. In addition, 47% of the potentially avoidable readmissions had a main diagnosis that was one of the index comorbidities. The results also showed an association between readmission for one of the index stay's comorbidities and being avoidable, with an adjusted odds ratio of 2.12 (95% confidence interval, 1.65-2.72). Overall, the presence of certain diseases, being identified as one of the preceding comorbidities, was found to have a substantial influence on the risk of potentially avoidable readmission. These diseases included digestive, circulatory, respiratory, genitourinary systems, and infectious and parasitic diseases (adjusted relative risks = 1.57, 1.49, 1.36, 1.30, and 2.30, respectively). CONCLUSION: To help reduce the rates of readmission, potential gains seem available if hospitals adopt clinical practices that support the patient's care during the post-discharge transition. This implies that health care providers need to pay more attention to the comorbidities of high-risk patients to be closely monitored after discharge.

Delay in Presentation, Diagnosis, and Treatment for Breast Cancer Patients in Jordan.

Breast cancer is the most common cancer, and one of the leading causes of death for females in Jordan and many countries in the world. Studies have shown that delay in symptoms presentation, diagnosis or treatment would result in poor prognosis. There has been no published study from Jordan on delays in patient presentation, delays in diagnosis, or delays in treatment. Therefore, we conducted this study to assess these important quality indicators aiming to improve prognosis for breast cancer patients in Jordan. This project was a cross-sectional study on female breast cancer patients in Jordan. The total number of participants was 327. The proportion of patients with presentation delay, diagnosis delay, and treatment delay was 32.2%, 49.1%, or 32.4%, respectively. The main reported reasons for delay in presentation were ignorance of the nature of the problem (65.6%), limited/lack of knowledge that symptoms were suggestive of cancer diagnosis (16.7%), and misdiagnosis (16.7%). Predictors of delay and mean time for presentation, diagnosis, and treatment were identified. Our results reveal that breast cancer patients in Jordan are experiencing delays in presentation, diagnosis, and treatment. This could justify the advanced stages at diagnosis and poor outcomes for breast cancer patients in Jordan. We recommend revising the current early detection and down-staging programs in Jordan.