International Journal of Hospital Research
Volume:2 Issue: 3, Summer 2013

Pharmacovigilance is central to the control of the menace of adverse drugs reactions. Despite the fact that development of policy and practice framework to improve patients’ safety partly rely on availability of authentic data on pharmacovigilance activities, knowledge about pharmacovigilance activities among healthcare professionals in Nigeria is limited. To help fill this gap, this study explored the awareness, attitude and practice of pharmacovigilance activities among the healthcare professionals in the Nigerian Nnamdi Azikiwe University Teaching Hospital. A descriptive cross-sectional survey was carried out among healthcare professionals in the Nnamdi Azikiwe University Teaching Hospital, Nnewi. The participants were doctors, pharmacists, nurses and health records officers employed in the teaching hospital. The sample was selected using stratified random sampling. A structured, self-administered questionnaire was used as the survey instrument. Key informant interview was also conducted among hospital’s administrative officers using standard interviewer guide. Descriptive statistics were calculated for the demographic variables. Quantitative data were compared using inferential statistics. Low level of awareness among the healthcare professionals about pharmacovigilance activities was observed. About half of them, 130 (50.4%), stated that they were not aware of the Nigerian National Pharmacovigilance tool that is used for documenting and reporting of adverse drug reactions. Only about one tenth of the respondents, 35 (13.7%), mentioned that they use this tool for documenting and reporting of adverse drug reactions whereas the majority of them, 220 (86.3%), stated that they had not used the tool. The study indicated that the healthcare professionals in Nnamdi Azikiwe University Teaching hospital, NAUTH (Nnewi) have low awareness about pharmacovigilance. There is also low frequencyof utilization of the Nigeria NPV tool for documentation and reporting of ADRs. Our findings highlight the need for educational and managerial interventions to improve ADRs monitoring and reporting within an all-inclusive pharmacovigilance system in this country.

Evaluating the performance of clinical units is critical for effective management of health settings. Certain assessment of clinical variables for performance analysis is not always possible, calling for use of uncertainty theory. This study aimed to develop and evaluate an integrated independent component analysis-fuzzy-data envelopment analysis approach to accurate the performance measurement of clinical units under uncertainty. Correlations between the input variables were calculated using Pearson’s correlation coefficient. Independent component analysis was used to extract independent components from input variables. Independent components were filtered against Gaussianity using Kurtosis parameter. An integrated independent component analysis-fuzzy-data envelopment analysis method was developed by using the uncertainty theory in the nonlinear fractional model proposed by Charnes, Cooper, and Rhodes (1978). The resulting fuzzy efficiency numbers were converted into normal ranking values by calculating amatrix of degree of preference. Under certainty, while data envelopment analysis identified 12 out of the 19 units as efficient units, independent component analysis-data envelopment analysis approach identified only three efficient units. On the other hand, under fuzzy conditions, while fuzzy-data envelopment analysis identified 12 efficient units, independent component analysis-fuzzy-data envelopment analysis identified only three units as efficient units. The results indicated that independent component analysis-fuzzy-data envelopment analysis offers the same efficiency measurement performance under fuzzy conditions as corresponding non-fuzzy method does under certain conditions. Our findings, hence, recommend use of the new approach in estimating efficiency of clinical units when access to reliable data is limited.

The increasing pressure on health systems to improve quality of health care, require them to develop novel conceptual framework and indices aimed at evaluating decision variables in the contemporary complex community. Customer Quality is a newly introduced concept addressing capability of patients in contribution to healthcare process and cooperation with healthcare providers for an improved healthcare services provision. This concept has been suggested to be regarded as a new dimension to quality of healthcare delivery. To further explore the potential impact of this factor on clinical outcome and health care performance, this study surveys Customer Quality among angiography patients. In a cross-sectional study, 202 cardio-vascular patients from Educational-Medical Shahid-Madani Center (Tabriz, Iran) were surveyed in 2013. A 19-item 5-point Likert-type Customer Quality questionnaire was used for data collection. Based on cumulative score of response to the questions, the patients were categorized into four ordinal self-management-capability groups: 1-19: belief in the importance patient role in healthcare process improvement; 20-50: having adequate confidence and knowledge to participate in healthcare provision; 50-80: being ready to take action to improve health care outcome; >80: maintaining care practices even under stressful situations. The data were summarized using descriptive statistical methods. T-test and ANOVA were used to compare the mean values. The mean Customer Quality was calculated to be 60.42±10.07. While ~84.4% of the patients fell in the third self-management-capability category, ~86% stated that they can help prevention of diseases or decrease the risks related to their health, ~97.% believed that their participation in provision of healthcare services is important to their health improvement, ~83% stated that after receiving treatment from the medical teams, they themselves are responsible for their health, 75% of patients consider themselves as a member of health team, and ~53% stated that they are not informed about development and prognosis of their disease. Our results clearly indicate the positive attitudes of cardiovascular patients towards contributing to healthcare process and self-care. Despite strong implication of of this positive attitude in attaining a high Customer Quality level, its potential impact on healthcare performance remains untapped due to the limited knowledge of patients on the nature of their diseases and the associated health-care and health-efficacy. Our findings implies the need for systematic inclusion of training services in health setting for increasing the awareness of patients on different aspects of their diseases and improving their communicative and self-efficacy skills, in order to attain higher Customer Quality-based healthcare outcome.

Postoperative ileus is common after abdominal resection. It causes gas store, distention, nausea, vomiting, and even pain. This study examines the impact of gum chewing as a type of sham feeding on the duration of postoperative ileus. In this randomized control trial study, 70 patients in two groups (each group n=35) underwent abdominal resection. The A group chewed sugarless gum three times (each time 20 minutes) in 4,10, and 18 hours after discharge on operation room. Both groups were matched in terms of demographics, intraoperative and postoperative care data. The data resending the first passage of flatus, defecation and bowel sound in every two hours for each patient were completed in questioning. With esthetes cop muse ring each two hours. T-test was used for comparison of the means. The initial bowel sound began at 3±1.3 and 2.8± 1.3 hours after operation in the gum and control groups, respectively. No significant difference was found between the two groups. Furthermore, gas passing has been reported at 18.3±10.5 and 36.28±12.6 hours after operation in gum and control group respectively. The first defecation was an accident at 36.8±21.7 and 69.5±19.2 hours after operation in gum and control groups, respectively (P=0.001). This study indicates that gum-chewing in the immediate postoperative period helps to enhance movement of intestines and facilitates recovery from ileus following abdominal resection. This inexpensive and well-tolerated treatment also results in earlier hospital discharge.

Efficient cost management in hospitals’ pharmaceutical inventories have the potential to remarkably contribute to optimization of overall hospital expenditures. To this end, reliable forecasting models for accurate prediction of future pharmaceutical demands are instrumental. While the linear methods are frequently used for forecasting purposes chiefly due to their simplicity, they have serious deficiencies in capturing nonlinearities in real-world problems. On the other hand, real world time series data are rarely pure linear or nonlinear, calling for development of forecasting models accounting for both these features of the data. To help meeting this need in the health/healthcare domain, this study undertook development of a hybrid framework consisting of a linear and a nonlinear component to improve forecasting of operating rooms’ pharmaceutical demand. A hybrid modeling framework combining AutorRgressive Integrated Moving average (ARIMA) as the linear component, and Artificial Neural Network (ANN) as the nonlinear component was developed. The method encompasses three phases: 1) Fitting a linear ARIMA model to the targeted time series, (2) Building an ANN model based on the residuals of the ARIMA model, and (3) Build the hybrid model by combining ARIMA and ANN models for the final forecast. Using the pharmaceutical inventory database of the Iranian Mohem Hospital for fitting AMIRA model and training ANN model, the forecast performance of all three models was compared by calculating the corresponding mean squared error and mean absolute error values, and by superimposing the time series patterns of the operating rooms’ drug demand independently predicted by each model to the corresponding observed pattern. Both quantitative and intuitive comparisons demonstrated that our hybrid ARIMA-ANN framework outperforms forecasting capability of either ARIMA or ANN models. In particular, the hybrid model showed remarkably superior capability in capturing the nonlinear behavior of the operating rooms’ pharmaceutical demand time series. Our proposed framework sets a ground for developing mathematical and computational forecasting models with ever higher predictive accuracy and supports the promotion of using such forecasting models in practical cost optimization in health facilities.

Low quality of life in hemodialysis patients is a major factor leading to cardiovascular diseases and other important outcomes such as hospitalization and death. The present study attempted to examine the impacts of training intervention on perceived psychological health and quality of life among hemodialysis patients. In this cross-sectional intervention study, 51 hemodialysis patients were examined using census sampling method. The Short Form (SF-36) Health Survey was used to assess psychological quality of life for these patients. For 7 patients with psychological health scores (1SD) lower than the mean score, a supplementary questionnaire (Hamilton rating scale for depression and anxiety) was administered by a psychologist, to confirm existence of and identify the type of a psychological disorder. Then a training course on coping and communicating skills was developed and implemented. The effect of training program on patients’ targeted skills was examined by post-intervention administration of the Hamilton rating scale. T-test was used for comparison of the mean values between the two genders. While women gained higher mean scores than men in role physical, role emotional, vitality, mental health, social functioning, and bodily pain, and men scored higher in physical functioning and general health. No significant difference in HRQOL dimensions was found between the two genders, but in bodily pain (P < 0.05). After training, a 20% enhancement in the coping and communicating skills was achieved. Training of hemodialysis patients can lead to improvement of their coping and communicative skills, thereby enhancing their quality of life. Hence this study recommends systematic inclusion of training-based HRQOL improvement interventions as an integral part of a comprehensive hemodialysis patient treatment strategy.

Reliable evaluation of hospital performance requires the use of assessment methods relying on multiple indicators. Pabon Lasso analysis is among these methods that combine the indicators such as bed occupancy rate, bed turnover rate, and average length of stay to yield a comprehensive assessment of current hospital performance. Given that the use of this analysis is new to Iranian hospitals, in this study, we conducted a Pabon Lasso analysis of the performance of hospitals affiliated to Qazvin University of Medical Sciences (QUMS) to indicate the usefulness and help promotion of this analysis method in Iranian hospitals. This cross-sectional study was conducted in 2012 by using the hospital data obtained from ospitals affiliated with Qazvin University of Medical Sciences (QUMS), during 2008-2010. The means of bed occupation rate and bed turnover rate of hospitals for each year were computed and the Pabon Lasso graphs were plotted accordingly. Based on these data, the location of each hospital was specified on the diagram. While, in 2008, only one hospital has been resided on Zone 3, only a single hospital could manage to enter this zone during the following two years. In addition, while Zone 4 has not been occupied by any hospital in 2008, one hospital has fallen to this zone in the following two years. Other hospitals could maintain their location on the Pabon Lasso graphs across three years. The results indicated that six out of the seven hospitals studied do not follow an effective performance improvement program. This is due to either lack of planning towards higher performance, or ineffectiveness of the plans, which need revision. Hence, using Pabon Lasso analysis, the hospital administrators can gain insight into the present situation of their hospitals, the effectiveness of the current management and decision-making processes, and seek for the true direction towards higher performance in future.

Today, expert systems are widely applied in medicine for prognosis, diagnosis, checkup, and treatment of various kinds of diseases. A comprehensive system for the checkup and treatment of different types of diabetes is still lacking. This paper reports development of such a system, its validation, and its utility in facilitating medical decision-making and supporting self-care.