ORIGINAL_ARTICLE
An Analysis of Gene Expression Variations in Lymphoma, Using a Fuzzy Classification Model
Introduction: Cancer is a major cause of mortality in the modern world, and one of the most important health problems in societies. During recent years, research on cancer as a system biology disease is focused on molecular differences between cancer cells and healthy cells. Most of the proposed methods for classifying cancer using gene expression data act as black boxes and lack biological interpretability. The goal of this study is to design an interpretable fuzzy model for classifying gene expression data of Lymphoma cancer.Method: In this research, the investigated microarray contained 45 samples of lymphoma. Total number of genes was 4026 samples. At first, we offer a hybrid approach to reduce the data dimension for detecting genes involved in lymphoma cancer. In lymphoma microarray, six out of 4029 genes were selected. Then, a fuzzy interpretable classifier was presented for classification of data. Fuzzy inference was performed using two rules which had the highest scores. Weka3.6.9 software was used to reduce the features and the fuzzy classifier model was implemented in MATLAB R2010a. Results of this study were assessed by two measures of accuracy and precision.Results: In pre-processing stage, in order to classify gene expression data of Lymphoma, six out of 4026 genes were identified as cancer- causing genes, and then the fuzzy classifier model was applied on the obtained data. The accuracy of the results of classification was 96 percent using 10 rules with the highest scores and that using 2 rules with the highest scores was about 98 percent.Conclusion: In the proposed approach, for the first time, a fully fuzzy method named a minimal rule fuzzy classification (MRFC) was introduced for extracting fuzzy rules with biological interpretability and meaning extraction from gene expression data. Among the most outstanding features of this method is the ability of extracting a small set of rules to interpret effective gene expression in cancer patients. Another result of this approach is successfully addressing the problem of disproportion between the number of samples and genes in microarrays with the proposed Filter-Wrapper Feature Selection method (FWFS).Keywords: Lymphoma Cancer, Cancer Diagnosis, Microarray, Gen Expression, Fuzzy Classifier
https://jhmi.sums.ac.ir/article_42680_28407bbf900e1255a0e99bee8203638a.pdf
2017-01-01
1
6
Zahra
Roozbahani
roozbahani2@gmail.com
1
LEAD_AUTHOR
Jalal
Rezaei Noor
2
AUTHOR
Mansoureh
Yari Eili
3
AUTHOR
Ali
Katanforoush
4
AUTHOR
Petersen PE. Oral cancer prevention and controlâThe approach of the World Health Organization. Oral oncology.
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P, G., Aruldoss, T., Devaraj, D., & Renukadev, M. Design of fuzzy Expert system for microarray data âclassification,using a novel Genetic Swarm Algorithm. Expert Systems with Applications, 39, 2012: 1811-1821.
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Deepa T, Sathiyabhama B, Akilandeswari J, Gopalan NP.
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49
ORIGINAL_ARTICLE
Does implementation of ISO standards in hospitals improve patient satisfaction?
Introduction: Around the world, a large number of projects have been developed with the aim of assessing patient satisfaction especially in hospitals. As an important indicator of the quality of health care system, Patients’ perception of health care has been the center of attention over the recent 20 years.Method: 402 patients who were hospitalized in teaching hospitals affiliated to the Shiraz University of Medical Sciences were investigated. Patients’ satisfactions of the health care services were assessed using the translated and modified version of the KQCAH consisted of 44 questions divided to7 categories of Respect and Caring, Effectiveness and Continuity, Appropriateness, Information, Efficiency, Meals, First Impression, Staff Diversity. All of the patients were asked to fill out the questionnaire (with written informed consents) at the time of discharge from the hospitals.Results: Regarding total score of patient satisfaction the ISO-certified hospitals did not show advantages over the uncertified hospitals. The total score of patients’ satisfaction ranged from 66.5 to 77.5 in. Overall, only in one ISO-certified hospital the total score of patient satisfaction representing all dimensions, was significantly higher comparing to other hospitals included in the study.Conclusion: It seems that solitary application of ISO standards could not improve patient satisfaction in hospitals affiliated to Shiraz University of Medical Sciences. Keywords: ISO, Patient satisfaction, Teaching hospitals
https://jhmi.sums.ac.ir/article_42681_eae286b0dc5e2d2b86023f352e0e5ad7.pdf
2017-01-01
7
11
Vahid
Keshtkar
keshtkarv@gmail.com
1
LEAD_AUTHOR
Meisam
Bazgir
2
AUTHOR
Mehrdad
Anvar
3
AUTHOR
Chung KP, Yu TH. Are quality improvement methods a fashion for hospitals in Taiwan? International Journal for Quality in Health Care. 2012;24(4):371-9.
1
Boyer L. Perception and use of the results of patient satisfaction surveys by care providers in a French teaching hospital. International Journal for Quality in Health Care.
2
;18(5):359-64
3
Salomon L, Gasquet I, Mesbah M, Ravaud P. Construction of a scale measuring inpatientsâ opinion on quality of care. International Journal for Quality in Health Care. 1999;11(6):507-
4
Auquier P, Blache JL, Colavolpe C, Eon B, Auffray JP, Pernoud N, et al. Ãchelle de vecu perioperatoire de lâanesthesie. I â Construction et validation. Annales Françaises dâAnesthesie et de Reanimation. 1999;18(8):848-57.
5
Labarere J. Development of a French inpatient satisfaction
6
questionnaire. International Journal for Quality in Health Care.
7
;13(2):99-108.
8
Oja PI, Kouri TT, Pakarinen AJ. From customer satisfaction survey to corrective actions in laboratory services in a university hospital. International Journal for Quality in Health Care.
9
;18(6):422-8.
10
Sower V, Duffy J, Kilbourne W, Kohers G, Jones P. The Dimensions of Service Quality For Hospitals: Development and Use of the KQCAH Scale. Health Care Management Review.
11
;26(2):47-59.
12
Vaziri S. Survey on patient satisfaction about hospital quality services with KQCAH scale in namazi and shahid faghihi hospitals: BSc thesis of Shiraz University of Medical Sciences;
13
Jha AK, Orav EJ, Zheng J, Epstein AM. Patientsâ Perception of Hospital Care in the United States. New England Journal of Medicine. 2008;359(18):1921-31.
14
Klazinga N. Re-engineering trust: the adoption and adaption of four models for external quality assurance of health care services in western European health care systems. International Journal for Quality in Health Care. 2000;12(3):183-9.
15
Heuvel J, Koning L, Bogers A, Berg M, Dijen M. An ISO 9001 quality management system in a hospital Bureaucracy or just benefits? Int J Qual Health Care. 2005;18:361-9.
16
Braithwaite J, Travaglia JF. An overview of clinical governance
17
policies, practices and initiatives. Australian Health Review.
18
;32(1):10.
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Jenkinson C. Patientsâ experiences and satisfaction with health care: results of a questionnaire study of specific aspects of care. Quality and Safety in Health Care. 2002;11(4):335-9.
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RodriguezâCerrillo M, FernandezâDiaz E, IñurrietaâRomero A, PozaâMontoro A. Implementation of a quality management system according to 9001 standard in a hospital in the home unit. International Journal of Health Care Quality Assurance.
21
;25(6):498-508.
22
Sanchez E. A descriptive study of the implementation of the EFQM excellence model and underlying tools in the Basque Health Service. International Journal for Quality in Health Care.
23
;18(1):58-65.
24
Alaloola NA, Albedaiwi WA. Patient satisfaction in a Riyadh Tertiary Care Centre. International Journal of Health Care Quality Assurance. 2008;21(7):630-7.
25
ORIGINAL_ARTICLE
Evaluation of the Users’ Continuous Intention to Use PACS Based on the Expectation Confirmation Model in Teaching Hospitals of Shiraz University of Medical Sciences
Introduction: Users’ behavioral intention to use the Picture Archiving and Communication System (PACS) is important in the systems’ success and is an indicator of the users’ satisfaction with commitment and dependence on information systems. The present study aimed to evaluate the users’ continuous intention to use PACS based on the expectation confirmation model in educational hospitals of Shiraz University of Medical Sciences.Method: This cross-sectional study was conducted in Nemazee and Shahid Faghihi hospitals, Shiraz, Iran in 2014. The subjects were50 general practitioners, residents and specialists selected through stratified random sampling. The study data were collected using a researcher-made questionnaire. The content validity of the questionnaire items was confirmed by five experts in health information management. To evaluate the accuracy of relationships among the measurement models, reliability criteria, including Cronbach’s alpha and composite reliability, convergent and divergent validity were used which showed acceptable reliability and validity. The data were entered into Smart PLS software, version 3.1.9 and analyzed through Structural Equation Modeling (SEM) by using Partial Least Squares (PLS) approach.Results: The results showed appropriate fitness of reliability indices (Cronbach’s alpha >0.7, composite reliability >0.7, loading >0.7), validity indices (AVE >0.5), structural model (redundancy =0.395, Q2CI=0.364, f2H5=0.524, R2CI=0.687), and the total model (GoF=0.518). Moreover, all the research hypotheses, except H1 (the relationship between expectation confirmation and perceived usefulness) with T-value of <1.96, showed a significant relationship (T-value >1.96).Conclusion: Expectation confirmation, perceived usefulness, and satisfaction were effective in continuous intention to use PACS. Thus, these factors should be considered by designers, developers, and managers while designing and implementing information systems to guarantee their success and improve the quality of health services.Keywords: Information Systems, Expectation confirmation model, PACS, Satisfactio
https://jhmi.sums.ac.ir/article_42682_dc50f097c966b0c64262c20f86aa86d9.pdf
2017-01-01
12
16
Mohtaram
Nematolahi
1
LEAD_AUTHOR
Mojtaba
Kafashi
kafashim@gmail.com
2
AUTHOR
Roxana
Sharifian
sharifianroxana@gmail.com
3
AUTHOR
Hossein
Monem
ali.monem@gmail.com
4
AUTHOR
Van de Velde R, Degoulet P. Clinical Information Systems: A
1
Component-Based Approach. 2003.
2
Huang H. PACS and Imaging Informatics: Basic Principles and
3
Applications,2nd Edition 2010.
4
Hurlen P, Borthne A, Dahl FA, Ostbye T, Gulbrandsen P.
5
Does PACS improve diagnostic accuracy in chest radiograph interpretations in clinical practice? European journal of radiology. 2012 Jan;81(1):173-7.
6
De Backer AI, Mortele KJ, De Keulenaer BL. Picture archiving and communication system--Part one: Filmless radiology and distance radiology. JBR-BTR. 2004 Sep-Oct;87(5):234-41.
7
Mansoori B, Erhard KK, Sunshine JL. Picture Archiving and
8
Communication System (PACS) implementation, integration
9
& benefits in an integrated health system. Acad Radiol. 2012
10
Feb;19(2):229-35.
11
Pare G, Trudel MC. Knowledge barriers to PACS adoption and implementation in hospitals. Int J Med Inform. 2007
12
Jan;76(1):22-33.
13
Bhattacherjee A. Understanding information systems continuance: an expectation-confirmation model. MIS Q.
14
;25(3):351-70.
15
Thong JYL, Hong S-J, Tam KY. The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of Human- Computer Studies. 2006;64(9):799-810.
16
Santos J, Boote J. A theoretical exploration and model of consumer expectations, post-purchase affective states and affective behaviour. Journal of Consumer Behaviour.
17
;3(2):142-56.
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Brown SA, Venkatesh,Viswanath, Kuruzovich,Jason, Massey,Anne P. Expectation confirmation: An examination of three competing models. Organizational Behavior and Human Decision Processes. 2005;105:52-66.
19
Mou J, Cohen J. A Longitudinal Study of Trust and Perceived Usefulness in Consumer Acceptance of an eService: The Case of Online Health Services. Pacific Asia Conference on Information Systems2014.
20
Cheng Y. What Drives Nursesâ Blended e-Learning Continuance
21
Intention? . Educational Technology & Society. 2014;17(4):203-
22
Koo C, Wati Y, Park K, Lim MK. Website quality, expectation, confirmation, and end user satisfaction: the knowledge-intensive website of the Korean National Cancer Information Center. Journal of medical Internet research. 2011;13(4):e81.
23
Lee M-C. Explaining and predicting usersâ continuance intention toward e-learning: An extension of the expectationâ confirmation model. Computers & Education. 2010;54(2):506-
24
Stone RW, Baker-Eveleth L. Studentsâ expectation, confirmation, and continuance intention to use electronic textbooks. Computers in Human Behavior. 2013;29(3):984-90.
25
Palm J-M, Dart T, Dupuis I, Leneveut L, Degoulet P. Clinical Information System Post-Adoption Evaluation at the Georges Pompidou University Hospital. AMIA Annual Symposium Proceedings. 2010 11/13;2010:582-6.
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Tabibi J, Farhangi A, Nasiripour A, Baradaran Kazemzadeh R, Ebrahimi P. The Effect of Supervisors and Work Group on Hospital Information System Acceptance Model. Journal of Health Administration. 2013;15(50):52-64.
27
Hadji B, Dupuis I, Leneveut L, Heudes D, Wagner JF, Degoulet P. Determinants of continuance intention in a post-adoption satisfaction evaluation of a clinical information system. Stud Health Technol Inform. 2014;205:990-4.
28
Lippert SK. Investigating Postadoption Utilization: An Examination Into the Role of Interorganizational and Technology Trust. IEEE Transactions on Engineering Management.
29
;54(3):468-83.
30
Wang Y-S. Assessing e-commerce systems success: a respecification and validation of the DeLone and McLean model of IS success. Information Systems Journal. 2008;18(5).
31
Davari A, Rezazadeh A. equation modeling with PLS. Tehran: Jahad University2013.
32
Chin W. Issues and opinion on structural equation modeling.
33
MIS quarterly. 1998;22(1):7-16.
34
Cohen J. Statistical Power Analysis for the Behavioral Sciences
35
Hillsdale, New Jersey: Lawrence Erlbaum Associates; 1988.
36
Henseler J, Ringle CM, Sinkovics RR. The use of partial least squares path modeling in international marketing. Advances in international marketing. 2009;20(1):277-319.
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Wetzels M, Odekerken-Schröder G, Van Oppen C. Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS Quarterly. 2009:177-
38
Po-An Hsieh JJ, Wang W. Explaining employeesâ Extended Use of complex information systems. European Journal of Information Systems. 2007;16(3):216-27.
39
ORIGINAL_ARTICLE
Key performance indicators in hospital based on balanced scorecard model
Introduction: Performance measurement is receiving increasing verification all over the world. Nowadays in a lot of organizations, irrespective of their type or size, performance evaluation is the main concern and a key issue for top administrators. The purpose of this study is to organize suitable key performance indicators (KPIs) for hospitals’ performance evaluation based on the balanced scorecard (BSC).Method: This is a mixed method study. In order to identify the hospital’s performance indicators (HPI), first related literature was reviewed and then the experts’ panel and Delphi method were used. In this study, two rounds were needed for the desired level of consensus. The experts rated the importance of the indicators, on a five-point Likert scale. In the consensus calculation, the consensus percentage was calculated by classifying the values 1-3 as not important (0) and 4-5 to (1) as important. Simple additive weighting technique was used to rank the indicators and select hospital’s KPIs. The data were analyzed by Excel 2010 software.Results: About 218 indicators were obtained from a review of selected literature. Through internal expert panel, 77 indicators were selected. Finally, 22 were selected for KPIs of hospitals. Ten indicators were selected in internal process perspective and 5, 4, and 3 indicators in finance, learning and growth, and customer, respectively.Conclusion: This model can be a useful tool for evaluating and comparing the performance of hospitals. However, this model is flexible and can be adjusted according to differences in the target hospitals. This study can be beneficial for hospital administrators and it can help them to change their perspective about performance evaluation.Keywords: Hospital, Balanced scorecard, Performance, Indicator
https://jhmi.sums.ac.ir/article_42683_47ca95be0efe77f30d8854687ce63557.pdf
2017-01-01
17
24
Hamed
Rahimi
s.hamedrahimi68@gmail.com
1
LEAD_AUTHOR
Zahra
Kavosi
zhr.kavosi@gmail.com
2
AUTHOR
Payam
Shojaei
pshojaei@yahoo.com
3
AUTHOR
Erfan
Kharazmi
4
AUTHOR
Shukri NFM, Ramli A. Organizational Structure and Performances of Responsible Malaysian Healthcare Providers: A Balanced Scorecard Perspective. Procedia Economics and Finance. 2015;28:202-12.
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2
Abdullah MT, Shaw J. A review of the experience of hospital autonomy in Pakistan. The International journal of health planning and management. 2007;22(1):45-62.
3
Abolhallaje M, Bastani P, Monazam K, Abolhasani N, Ramezanian M. Health System Financing from ExpertsPoint of View. Middle-East J Sci Res. 2012;12(10):1386-90.
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Koumpouros Y. Balanced scorecard: Application in the General Panarcadian Hospital of Tripolis, Greece. International Journal of Health Care Quality Assurance. 2013;26(4):286-307.
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Kairu EW, Wafula MO, Okaka O, Odera O, Akerele EK.
7
Effects of balanced scorecard on performance of firms in the
8
service sector. European Journal of Business and Management.
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;5(9):81-8.
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Okwo IM, Marire IM. Performance Measurement in Business Organizations: An Empirical Analysis of the Financial Performance of Some Breweries in Nigeria. Research Journal of Finance and Accounting. 2012;3(11):48-57.
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ORIGINAL_ARTICLE
The impact of organizational culture on employees’ organizational silence In Shiraz University of Medical Sciences
Introduction: Organizational Culture is one of the most important factors that can change the climate of silence. The main aim of this research was to investigate the influence of organizational culture on employees’ organizational silence in Shiraz University of Medical Sciences.Method: This research was a descriptive-correlation one. The target population was chosen from 1900 staff of the University of Medical sciences and Health Care headquarter in Shiraz. Thus 311 employees were selected using the Krejcie and Morgan sampling table. The instrument used in this research was Denison (2006) organizational culture questionnaire and Dimitris Buratas and Maria Vacula (2007) organizational culture. Cornbrash’s alpha method was used to calculate the reliability. The Item analysis and expert consensus were applied to calculate the validity of instruments. All gathered data analyzed with PLS software.Results: The results showed that the four dimensions of organizational culture include organizational involvement, organizational adaptability, organizational concistency and organizational mission was moderate and the mean scores obtained for each factor were 2.85, 2.82, 2.94 and 2.93 respectively. Structural equation model showed Organizational culture has a significant positive impact on organizational silence (β=0.68; P<.001).Conclusion: Based on the results and impact of organizational culture on organizational silence that is positive and significant; The organization further efforts to strengthen various aspects of organizational culture, especially the employees’ involvement in decision making; Employees can better express their opinions and thus reduced their organizational silence. In other words strengthening corporate culture is combined with the reduction of organizational silence. Medical organizations can establish appropriate reward system for creative ideas and suggestions to encourage people express their ideas As a result, reduced organizational silence.Keywords: Organizational culture, Organizational silence, Structural equation model, Shiraz University of Medical Sciences
https://jhmi.sums.ac.ir/article_42684_9708da64248cc2508967b7e35ce497ef.pdf
2017-01-01
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Ebrahim
Parcham
saadat4794@yahoo.com
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LEAD_AUTHOR
Alireza
Ghasemizad
ghasemizad@kau.ac.ir
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AUTHOR
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