Journal Hospital Practices and Research

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23 articles
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Samaneh Shirazi, Behroz Mahdavi Poor, Mohammad Asgharzadeh, Seyyed Reza Moaddab, Jalil Rashedi
Hospital Practices and Research, Volume 1, pp 103-104; doi:10.20286/hpr-0103102

Emmanuel Ugwa, Ugwa Charity
Hospital Practices and Research, Volume 1, pp 79-82; doi:10.20286/hpr-010379

Alireza Ehsanbakhsh, Nasrin Khorashadizadeh, Aburi Amin
Hospital Practices and Research, Volume 1, pp 101-102; doi:10.20286/hpr-010399

Parisa Mehdizadeh, Nooredin Dopeykar, Ezzatollah Gol-Alizadeh, Maryam Yaghoubi
Hospital Practices and Research, Volume 1, pp 95-99; doi:10.20286/hpr-010395

Seyed Abbas Tavalaei, Shervin Assari, Vahid Tavalaei, Roghieh Nooripour
Hospital Practices and Research, Volume 1, pp 87-90; doi:10.20286/hpr-010387

Soleiman Hosseini Khalifani, Mehdi Morshedi, Hassan Ali Mohebi, Gholamali Ghorbani, Shahram Manoochehry
Hospital Practices and Research, Volume 1, pp 83-86; doi:10.20286/hpr-010383

Samaneh Aghajani, Mehrdad Kargari
Hospital Practices and Research, Volume 1, pp 51-56; doi:10.20286/hpr-010251

Abstract:Background: Length of stay is one of the most important indicators in assessing hospital performance. A shorter stay can reduce the costs per discharge and shift care from inpatient to less expensive post-acute settings. It can lead to a greater readmission rate, better resource management, and more efficient services.Objective: This study aimed to identify the factors influencing length of hospital stay and predict length of stay in the general surgery department.Methods: In this study, patient information was collected from 327 records in the surgery department of Shariati Hospital using data mining techniques to determine factors influencing length of stay and to predict length of stay using three algorithms, namely decision tree, Naïve Bayes, and k-nearest neighbor algorithms. The data was split into a training data set and a test data set, and a model was built for the training data. A confusion matrix was obtained to calculate accuracy.Results: Four factors presented: surgery type (hemorrhoid), average number of visits per day, number of trials, and number of days of hospitalization before surgery; the most important of these factors was length of stay. The overall accuracy of the decision tree was 88.9% for the training data set.Conclusions: This study determined that all three algorithms can predict length of stay, but the decision tree performs the best.
Ahmad Salimzadeh, Alireza Jalali-Farahani, Mohammadjavad Alishiri, Ali Ayoubian
Hospital Practices and Research, Volume 1, pp 39-40; doi:10.20286/hpr-010239

Abstract:Having access to information technology in all levels particularly in the health sector has followed with rapid progresses in recent years. Rapid penetration of this technology among people has led to changes in the lifestyles of them and working procedures of institutions. In 2014 the number of internet users reached to 3 billion people and this number is predicted to reach over than 8 billion in 2014. According to statistics, the number of Iranian users has been estimated about 45 million. In 2014, over than 80% of internet users have been searching for health information. Today, internet plays a vital role in providing health services that include education, disease management, support, and basic medical treatment decisions, and patient communication.
Maryam Yaghoubi, Marzieh Javadi, Saied Karimi, Elham Ehsani
Hospital Practices and Research, Volume 1, pp 65-69; doi:10.20286/hpr-010265

Abstract:Background: Patient safety is a serious global public health issue. Estimates show that every day many patients are harmed while receiving hospital care. Health care staff plays a key role in providing quality and safe patient care, especially physicians who are main members of the medical team and a critical element in patient safety efforts.Objective: The current study used a Theory of Planned Behavior (TPB) framework to investigate predictors of patient safety intentions and behavior of physicians.Methods: This descriptive analytical study was conducted in 8 hospitals with 52 physicians participating. A researcher-designed questionnaire was prepared to investigate patient safety behaviors and behavior constructs of physicians based on the guidelines of constructing a TPB Questionnaire: Conceptual and Methodological Considerations. The content validity and reliability of the questionnaire were confirmed. Binary logistic regression analysis was performed using SPSS18.Results: The total mean score of physician safety behavior indicated that 3.8±0.92. 42% of physicians reported their safety behavior at a good level. There was no significant difference between the patient safety function of physicians in public and private hospitals (P=0.8) and working in medical or surgical wards (P=0.4). Among TPB constructs, “normative beliefs” had the greatest influence on physician intention for safety behaviors (wald=3.828, P=0.05).Conclusion: The results showed that “normative beliefs” had the greatest influence on physician intention for safety behaviors; therefore, it seems that patient safety must be the most important concern of all health care staff, specifically managers and executives throughout health care centers.
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