Health care professionals' perceptions towards the use of computerized clinical decision support systems in antimicrobial stewardship in Jordanian hospitals: A two institutional study

Health care professionals' perceptions towards the use of computerized clinical decision support systems in antimicrobial stewardship in Jordanian hospitals: A two institutional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Health care professionals' perceptions towards the use of computerized clinical decision support systems in antimicrobial stewardship in Jordanian hospitals: A two institutional study Fares Albahar, Rana K Abu-Farha, Osama Y Alshogran, Hamza Alhamad, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1751250/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Understanding health care professionals' perceptions towards a Computerised Decision Support System (CDSS) may provide a platform for the determinants of successful adoption and implementation of CDSS. Therefore, this study examines health care professionals' perceptions of barriers and facilitators to adopting a CDSS for antibiotic prescribing in Jordanian hospitals. Methods This cross-sectional study was conducted among healthcare professionals in Jordan's two tertiary and teaching hospitals (n = 254). The survey was adapted from a previous study and comprised demographic items and scales to measure perceptions of healthcare professionals towards the barriers and facilitators to the adoption of CDSS for antibiotic prescribing were developed. In addition, Uni and multivariate logistic regression analyses were applied to screen for factors affecting participants' awareness of using electronic prescribing and electronic health record systems in AMS. Results The majority (n = 84, 72.4%) were aware that electronic prescribing and electronic health record systems could be used to facilitate antibiotic use prescribing. The essential facilitator made CDSS available in a portable format (n = 224, 88.2%). While, insufficient training to use CDSS was the most significant barrier (n = 175, 68.9%). The female providers showed significantly lower awareness (P = 0.006) and the nurses significantly higher awareness (P = 0.041) about using electronic prescribing and electronic health record systems. Conclusion This study examined health care professionals' perceptions towards adopting CDSS in AMS. Results provide insight into the perceived barriers and facilitators to adopting CDSS in AMS. Figures Figure 1 Figure 2 Figure 3 1. Background The prevalence of multidrug resistance has increased alarmingly worldwide ( 1 ). Also, the inappropriate use of antimicrobial agents has been correlated with antimicrobial resistance (AMR) ( 2 , 3 ). The World Health Organisation (WHO) released a recent feasible toolkit concerning the use of Antimicrobial Stewardship (AMS) in healthcare settings in low and middle-income countries to optimize the use of antibiotics and contain the problem of AMR ( 4 ). The Jordanian minister of health's national four-year action plan aligned with the WHO global action plan to maintain the efficiency of existing antibiotics through AMS ( 5 ). The national plan was developed considering the importance of healthcare information technology to combat AMR ( 5 ). Many information technology systems have been developed to aid clinicians in decision-making ( 6 , 7 ). One such system is the Computerised Clinical Decision Support System (CDSS). The CDSS provides real-time, evidence-based decision support at the point of care about the choice of antimicrobial agents in selected infections ( 7 , 8 ). However, the CDSS is less commonly used in clinical practice despite its effectiveness in reducing AMR ( 7 – 9 ). The impact of CDSS has been evaluated through many different clinical settings ( 7 , 8 , 10 – 12 ). Some studies showed positive impacts such as improved patient care processes, health care costs, physician workflows, and adherence to the guidelines ( 7 , 8 , 13 , 14 ). In contrast, others showed a negative effect and failed to achieve their intended outcomes ( 12 , 15 , 16 ). Given that negative perceptions of health care professionals towards CDSS could affect the acceptance of such systems. Understanding the perceptions and attitudes of health care professionals towards CDSS may provide a platform for the determinants of the successful adoption and implementation of CDSS. Therefore, it is interesting to study healthcare professionals' perceptions of CDSS ( 17 , 18 ) and their role in CDSS adoption ( 19 , 20 ). In addition, this study examines potential barriers and facilitators that hinder or enable CDSS use in clinical practice and AMS. Highlighting these factors would provide a framework for successful CDSS implementation and use. 2. Methods 2.1 Hospital setting and participants This prospective cross-sectional study was conducted in two tertiary teaching hospitals, the University of Jordan and King Abdullah University Hospitals. The University of Jordan hospital is a large (600-bed) academic centre located in Amman (Middle), Jordan. King Abdullah University Hospital (750-bed) is another large academic centre located in Irbid (North), Jordan. Both hospitals have infectious diseases departments that apply AMS principles which curtailed the use of broad-spectrum antimicrobials within the hospital. Two categories of healthcare professionals were invited to participate: medical and non-medical healthcare professionals. In addition, senior and junior doctors from different specialties were asked to participate in the survey and other healthcare professionals, including pharmacists, microbiology experts, and infection control experts. 2.2 Survey development and data collection The complete survey has been adopted from Zaidi et al. ( 21 ), as shown in appendix 2. A pool of ten items to measure barriers and nine items to measure facilitators were initially drafted into a survey tool. Two clinical pharmacists and one infectious diseases consultant reviewed the drafted survey items. These items were then reviewed by research experts familiar with study design in two universities. The reviewers' comments were about wording, clarity, comprehensiveness, and whether each survey item was pertinent to the study's goals and objectives. These comments were used to develop the final version of the survey. The final version of the survey included 38 items divided into four domains. The first domain collected participants’ demographic data such as age, gender, specialty, and experience in a specialist role. The second domain collected information about the perceptions of healthcare professionals towards AMS. The third domain collected information about the awareness of using CDSS and the perceived benefits. The last domain collected information on the perceived barriers and facilitators towards using CDSS. The survey was piloted in the local region, especially with two clinical pharmacists and one infectious diseases consultant, in March 2021. Two clinical pharmacists distributed the questionnaire in a paper-based format for senior and junior prescribers and non-prescribers at the University of Jordan Hospital and King Abdullah University Hospital. Healthcare professionals were informed that participation is voluntary, information collected will be anonymous, and the survey would require 10–15 minutes to finish. The delivery of the questionnaire lasted four weeks, started on June 15, 2021, and was closed on July 14, 2021. A reminder was sent four weeks later. 2.3 Statistical analysis The statistical package for social science (SPSS®) version 22 (SPSS® Inc., Chicago, IL, USA) was used for data analysis. The mean ± SD and frequency (percentages) were used for continuous and categorical variables, respectively. Uni and multivariate logistic regression was employed to screen for factors that affect participants’ awareness about using electronic prescribing and electronic health record systems in AMS. Variables that were significant on a single predictor level (P-value < 0.25) using univariate logistic regression analysis were contained in the logistic regression analysis model. In the logistic regression analysis, variables independently associated with awareness about the use of electronic prescribing and the electronic health record system in AMS were identified. Statistical significance was considered at P-value < 0.05. 3. Results A total of 254 healthcare providers agreed to participate in this study and completed the survey with a response rate of 46% (254 out of 550). The majority of participants (n = 193, 76%) were aged between 20–30 years old, and 59.1% (n = 150) were females. About 60% (n = 154) of the participants were physicians, while the remaining were pharmacists (n = 60, 23.6%) and nurses (n = 40, 15.7%). Study Demographics are presented in Table 1 . Table 1 Socio-demographic characteristics of the study sample (n = 254) Parameter n (%) Age (years) o 20–30 o 31–40 o 41–50 o 51–60 o > 61 193 (76.0) 54 (21.3) 5 (2.0) 0 (0.0) 2 (0.8) Gender o Males o Females 104 (40.9) 150 (59.1) Speciality o Clinical pharmacist o Physicians o Nurse 60 (23.6) 154 (60.6) 40 (15.7) Participants were asked about their awareness of the use of electronic prescribing and electronic health record systems in general and in AMS (Table 2 ). The majority (n = 220, 86.6%) reported knowing about the presence of electronic prescribing and electronic health record systems at their hospitals. In addition, around three-quarters (n = 84, 72.4%) were aware that such systems could be used to facilitate antibiotic use prescribing. However, a lower percentage of the respondents (n = 161, 63.4%) were aware that those systems could provide a clinical decision support function to support evidence-based practice. Table 2 Participants' awareness about the use of electronic prescribing and electronic health record systems in antimicrobial stewardship (n = 254) Statements Strongly Agree/agree Have you previously used electronic prescribing and electronic health record systems? o Yes o No/Not sure 220 (86.6) 34 (13.4) Are you aware that electronic prescribing and electronic health record systems can be used to facilitate antibiotic prescribing? o Yes o No/Not sure 184 (72.4) 70 (27.6) Are you aware that electronic prescribing and electronic health record system is capable of providing clinical decision support function in order to support evidence-based practice? o Yes o No/Not sure 161 (63.4) 93 (36.6) All participating healthcare providers responded to five statements to express their perception of AMS (Table 3 ). First, healthcare providers showed a positive perception of AMS, where 88.2% of respondents (n = 224) agreed/strongly agreed that AMS programs might improve patient care. Similarly, 89.7% of respondents (n = 228) believed that those programs might reduce the problem of AMR. In addition, more than 90% of respondents agreed/strongly that stewardship programs should be incorporated at a hospital level and that healthcare providers should be provided with adequate training on antimicrobial use. On the other hand, only 52.4% of the respondents (n = 133) believed that the antimicrobial prescribing at their hospital is already as good as possible. Table 3 Perception of participants towards antimicrobial stewardship (n = 254) Statements Strongly Agree/agree Neutral Strongly disagree/disagree Antimicrobial prescribing at your hospital is already as good as it can be 133 (52.4) 46 (12.1) 75 (29.5) Antimicrobial stewardship programs may improve patient care. 224 (88.2) 16 (6.3) 14 (5.5) Antimicrobial stewardship should be incorporated at a hospital level 229 (90.2) 11 (4.3) 14 (5.5) Antimicrobial stewardship programs may reduce the problem of antimicrobial resistance. 228 (89.7) 12 (4.7) 14 (5.5) Adequate training should be provided to health care professionals on antimicrobial use 235 (92.5) 5 (2.0) 14 (5.5) Participants were also asked about their perceived benefits of using electronic prescribing and electronic health record systems in AMS. Results showed that respondents believed that those systems might reduce the expenditure on antibiotics (n = 212, 83.4%), improve the safety of antibiotic use (n = 210, 82.7%), and may improve the ability to deliver AMS (n = 205, 80.8%). For more details, refer to Fig. 1 . Regarding the barriers against the use of electronic prescribing and electronic health record systems in AMS (Fig. 2 ), results demonstrate that the most important barrier was the insufficient training to use the systems (n = 175, 68.9%), followed by the lack of access to reliable technical support (n = 173, 68.1%). The least important barrier was the limitation to medical autonomy (n = 111, 43.7%). On the other hand, Fig. 3 illustrates the perceived facilitators of AMS electronic prescribing and electronic health record systems. Results showed that the most important facilitator was making the system available in a portable format like mobile or personal digital assistant (n = 224, 88.2%), followed by linking radiology and laboratory results to the system (n = 220, 86.6% for both). For more details, refer to Fig. 3 . Finally, logistic regression (Table 4 ) showed that female healthcare providers showed significantly lower awareness about using electronic prescribing and electronic health record systems in AMS than males (P = 0.006). Also, nurses showed significantly higher awareness about using those systems in AMS than pharmacists and physicians (P = 0.041). Table 4 Assessment of factors affecting participants awareness about the use of electronic prescribing and electronic health record systems in antimicrobial stewardship (n = 254) Parameter Awareness [0: No, 1: Yes] OR P-value# OR P-value $ Age (years) o 20–30 years o > 31 years Reference 3.135 0.005^ 2.130 0.079 Gender o Male o Female Reference 0.394 0.003^ 0.402 0.006* Speciality o Physicians o Pharmacists o Nurses Reference 1.322 4.327 0.410 0.008^ 1.636 3.249 0.172 0.041* # using simple logistic regression, $ using multiple logistic regression, ^ eligible for entry in multiple logistic regression, * significant at 0.05 significance level 4. Discussion This is a two-centre study (both large tertiary and teaching hospitals) from the middle and north area of Jordan in which 254 healthcare professionals provided their insights about their positive perceptions toward AMS, demonstrated by their agreement that its use would improve patient outcomes and curtail AMR. This study aimed to examine the potential barriers and facilitators that hinder or enable CDSS use in clinical practice and AMS based on the healthcare professionals' views. Therefore, understanding perceived barriers and facilitators to CDSSs is vital to maximise the technology's adoption and uptake and potentially impact patient outcomes. The study survey adopted was refined to study CDSS considering various contexts, from two healthcare centres where the healthcare professionals would be unfamiliar with the technology to those in mature stages in its implementation. Consequently, the results from this study are expected to help guide the development of strategies and recommendations essential to introducing and integrating CDSS into wider national healthcare settings, including the two hospital centres. This study showed that healthcare professionals had a positive awareness and perceptions toward the electronic prescribing and electronic health record systems explained by their understanding that AMS use would improve patient outcomes and limit AMR. Also, the healthcare professionals perceived that electronic prescribing is beneficial and would reduce the high cost of prescribing antibiotics (i.e., reduce the expenditure of antibiotics), improve the efficacy and the safety of antibiotic use, and may improve the ability to deliver AMS to optimise the rational use of antibiotics. In addition, many systematic reviews and studies demonstrated the impact of adopting the CDSS on antibiotics management and AMS ( 12 , 13 , 22 – 29 ). The lack of appropriate training to use the electronic prescribing and electronic health record systems and the lack of access to reliable technical support were the most perceived barriers to CDSS adoption among healthcare professionals. Also, more than half of the healthcare professionals had a low level of awareness and were unfamiliar with using electronic prescribing and electronic health record systems. Furthermore, given that healthcare professionals have busy work schedules, they do not have enough time to learn how to use the system. Therefore, adequate training should be encouraged for novice and experienced healthcare professionals to use the CDSS system and improve workflow effectively. Also, technical support should be provided to the healthcare professionals in each ward of the hospital to avoid any difficulties in using the systems and to maximise the effective use of CDSS. Previous studies reported similar results ( 21 , 29 – 33 ). For example, one recent cross-sectional study from Australia that evaluated the impact of CDSS adoption on antibiotics management reported that the lack of appropriate training and technical support was an essential barrier to CDSS adoption ( 29 ). In addition, the significance of training and technical support for CDSS adoption was evident in previous studies ( 21 , 34 – 36 ). Making the system in an easily portable format (i.e., like a mobile or a personal digital assistant) was the most perceived facilitator for adopting CDSS by healthcare professionals. This is expected to enable healthcare professionals to make a decision regarding the prescribing and monitoring of antibiotics from remote areas without the need to be in the ward or even in the hospital to prescribe and monitor antibiotics, thus, making work more flexible. Also, lab and radiology results linked to the CDSS are facilitators for adopting CDSS. As a result, healthcare professionals will not be required to check different databases to confirm the diagnosis and adjust treatment based on laboratory results. This will make the work schedule more flexible and efficient. Similar studies reported the same results ( 21 , 31 , 33 ). For example, one cross-sectional study conducted in a tertiary care university hospital in Melbourne, Australia, reported making the CDSS in an easily portable format, linking lab and radiology results as a facilitator to the adoption of CDSS ( 21 ). This was also evident in a recent systematic review ( 33 ) and a previous study ( 31 ). The logistic regression results about the factors affecting participants' awareness about the use of electronic prescribing and electronic health record systems in antimicrobial stewardship showed that female healthcare providers had significantly lower awareness about using electronic prescribing and electronic health record systems. In contrast, the nurses showed significantly higher awareness about using those systems in stewardship programs. Gender as a factor affecting participants' awareness about the use of electronic prescribing and electronic health record systems was studied in the literature ( 37 – 40 ), with studies showing no difference ( 39 ), and others showed higher awareness among females ( 38 , 40 ) contrasted to the results from our study. Considering that males and females are supposed to have equal technological exposure, knowledge, and awareness, the results from our study should be further explored. The response rate was less than optimal similar to other response rates in the literature ( 29 , 41 ); this may affect the representative of the data obtained and may be a limitation to this study. Nevertheless, it is vital to note that the study attracted healthcare professionals with various degrees of system usage. Therefore, the sample seems adequate to address the study's aims. This study has several strengths. First, the sample size of 254 healthcare providers (despite a low response rate = 46%) from two large tertiary teaching hospitals is considered satisfactory and would add to the representativeness of the results drawn from this study. Second, the CDSS system was designed by developers independent of the end-user healthcare professionals. So, the healthcare professionals were not involved in designing and implementing the CDSS. This is expected to reduce the potential for investigator bias. Finally, it is noteworthy that the use of the CDSS was optional, which minimises the likelihood that healthcare professionals were influenced by hospital policy to use the CDSS system. While the CDSS system is increasingly gaining popularity in implementing hospital guidelines for prescribing antibiotics, significant barriers to its adoption exist. To implement CDSS systems successfully, the developer needs to understand the barriers to their adoption. The present study measures healthcare professionals' perceptions of using the CDSS system in two tertiary care settings in Jordan's middle and north areas. Both the study setting and study participants represent a metropolitan area. Therefore, the findings from the study could apply to other healthcare settings interested in the launch and implementation of CDSS systems. While the study investigators are independent of the developer and implementer of the CDSS system at the study hospitals, the present study results have been available to them to improve the implementation and deployment strategies. 5. Conclusion This study examined health care professionals' perceptions towards adopting CDSS for antibiotic prescribing from Jordan's two tertiary and teaching hospitals. Implementing CDSS in Antimicrobial Stewardship (AMS) would help reduce antibiotic resistance and improve patient safety. In addition, results would provide insight into the perceived barriers and facilitators to adopting CDSS and provide a platform for other healthcare settings interested in implementing CDSS in AMS locally and globally. Also, this study would help inform policy decision-makers in Jordan to react by implementing the CDSS system at the national level. Therefore, future studies should focus on establishing guidelines and a policy framework to examine the adoption of the CDSS for AMS. Declarations Ethics approval and consent to participate: This study was approved by the Zarqa University Ethics Committee for Scientific Research (ECSR) (supplementary material), following the principles of the protection of human subjects and the ethical principles related to research studies, and was given an approval number (3/3/2018-2019), and Jordan University Hospital (80/2019/23), and King Abdullah University Hospital (49/128/2019). Also, an informed consent form was obtained from all participants before participating in the study, ensuring that participation was voluntary and participants could withdraw at any stage, with their answers treated confidentially. All methods were performed according to the relevant university’s guidelines and regulations. Consent for publication: “Not applicable”. Availability of data and materials: All data generated or analysed during this study are included in this published article [and its supplementary information files]. Competing interests: The authors declare that they have no competing interests Conflict of interest: The authors declare that they have no conflict of interest. Funding: This research did not receive any grant from funding agencies in the public, commercial, or not-for-profit sectors. Author’s contribution : Fares Albahar and Hamza Alhamad contributed to the design and conception of the study, acquisition of data, analysis, and interpretation of data, drafting of the article, critically revising, and final approval of the version to be published. Rana Abu-Farha contributed to the analysis and interpretation of data, drafting the article, critically revising, and final approval of the version to be published. Osama Alshoqran contributed to the acquisition of data, analysis, interpretation of data, and final approval of the version to be published. Chris Curtis contributed to the study's design and conception, drafting the article, critically revising it, and final approval of the version to be published. Finally, John Marriott contributed to the design and conception of the study drafting the article, critically revising, and final approval of the version to be published Acknowledgments : The authors acknowledge the healthcare professionals who participated in this study. References Johnson S V, Hoey LL, Vance‐Bryan K. Inappropriate vancomycin prescribing based on criteria from the Centers for Disease Control and Prevention. Pharmacother J Hum Pharmacol Drug Ther. 1995;15(5):579–85. Talbot GH, Bradley J, Edwards Jr JE, Gilbert D, Scheld M, Bartlett JG. Bad bugs need drugs: an update on the development pipeline from the Antimicrobial Availability Task Force of the Infectious Diseases Society of America. Clin Infect Dis. 2006;42(5):657–68. Nusair MB, Al‐azzam S, Alhamad H, Momani MY. The prevalence and patterns of self‐medication with antibiotics in Jordan: A community‐based study. Int J Clin Pract. 2021;75(1):e13665. Organization WH. Antimicrobial stewardship programmes in health-care facilities in low-and middle-income countries: a WHO practical toolkit. 2019; Hashemite Kingdom of Jordan I. National Action Plan to Combat Antimicrobial Resistance. 2018; Sutton RT, Pincock D, Baumgart DC, Sadowski DC, Fedorak RN, Kroeker KI. An overview of clinical decision support systems: benefits, risks, and strategies for success. NPJ Digit Med. 2020;3(1):1–10. Curtis CE, Al Bahar F, Marriott JF. The effectiveness of computerised decision support on antibiotic use in hospitals: a systematic review. PLoS One. 2017;12(8):e0183062. Al Bahar F, Curtis CE, Alhamad H, Marriott JF. The impact of a computerised decision support system on antibiotic usage in an English hospital. Int J Clin Pharm. 2020;42(2):765–71. Baysari MT, Oliver K, Egan B, Li L, Richardson K, Sandaradura I, et al. Audit and feedback of antibiotic use. Appl Clin Inform. 2013;4(04):583–95. Pawloski PA, Brooks GA, Nielsen ME, Olson-Bullis BA. A systematic review of clinical decision support systems for clinical oncology practice. J Natl Compr Cancer Netw. 2019;17(4):331–8. Klarenbeek SE, Weekenstroo HHA, Sedelaar JP, Fütterer JJ, Prokop M, Tummers M. The effect of higher level computerized clinical decision support systems on oncology care: a systematic review. Cancers (Basel). 2020;12(4):1032. Rawson TM, Moore LSP, Hernandez B, Charani E, Castro-Sanchez E, Herrero P, et al. A systematic review of clinical decision support systems for antimicrobial management: are we failing to investigate these interventions appropriately? Clin Microbiol Infect. 2017;23(8):524–32. Bright TJ, Wong A, Dhurjati R, Bristow E, Bastian L, Coeytaux RR, et al. Effect of clinical decision-support systems: a systematic review. Ann Intern Med. 2012;157(1):29–43. Roshanov PS, Misra S, Gerstein HC, Garg AX, Sebaldt RJ, Mackay JA, et al. Computerized clinical decision support systems for chronic disease management: a decision-maker-researcher partnership systematic review. Implement Sci. 2011;6(1):1–16. Garg AX, Adhikari NKJ, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. Jama. 2005;293(10):1223–38. Kawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. Bmj. 2005;330(7494):765. Gadd CS, Baskaran P, Lobach DF. Identification of design features to enhance utilization and acceptance of systems for Internet-based decision support at the point of care. In: Proceedings of the AMIA Symposium. American Medical Informatics Association; 1998. p. 91. Rosenbloom ST, Talbert D, Aronsky D. Clinicians’ perceptions of clinical decision support integrated into computerized provider order entry. Int J Med Inform. 2004;73(5):433–41. Satsangi S, Weir CR, Morris AH, Warner HR. Cognitive evaluation of the predictors of use of computerized protocols by clinicians. In: AMIA Annual Symposium Proceedings. American Medical Informatics Association; 2003. p. 574. Zheng K, Padman R, Johnson MP, Diamond HS. Understanding technology adoption in clinical care: clinician adoption behavior of a point-of-care reminder system. Int J Med Inform. 2005;74(7–8):535–43. Zaidi STR, Marriott JL. Barriers and facilitators to adoption of a web-based antibiotic decision support system. South Med Rev. 2012;5(2):42. Paskovaty A, Pflomm JM, Myke N, Seo SK. A multidisciplinary approach to antimicrobial stewardship: evolution into the 21st century. Int J Antimicrob Agents. 2005;25(1):1–10. Paterson DL. The role of antimicrobial management programs in optimizing antibiotic prescribing within hospitals. Clin Infect Dis. 2006;42(Supplement_2):S90–5. Bearden DT, Allen GP. Impact of antimicrobial control programs on patient outcomes. Dis Manag Heal Outcomes. 2003;11(11):723–36. Samore MH, Bateman K, Alder SC, Hannah E, Donnelly S, Stoddard GJ, et al. Clinical decision support and appropriateness of antimicrobial prescribing: a randomized trial. Jama. 2005;294(18):2305–14. McGregor JC, Weekes E, Forrest GN, Standiford HC, Perencevich EN, Furuno JP, et al. Impact of a computerized clinical decision support system on reducing inappropriate antimicrobial use: a randomized controlled trial. J Am Med Informatics Assoc. 2006;13(4):378–84. Albarillo FS, Labuszewski L, Lopez J, Santarossa M, Bhatia NK. Use of a Clinical Decision Support System (CDSS) to improve antimicrobial stewardship efforts at a single academic medical center. Germs. 2019;9(2):106. Nassar H, Abu-Farha R, Barakat M, Alefishat E. Antimicrobial Stewardship from Health Professionals’ Perspective: Awareness, Barriers, and Level of Implementation of the Program. Antibiotics. 2022;11(1):99. Laka M, Milazzo A, Merlin T. Factors That Impact the Adoption of Clinical Decision Support Systems (CDSS) for Antibiotic Management. Int J Environ Res Public Health. 2021;18(4):1901. Lugtenberg M, Weenink J-W, van der Weijden T, Westert GP, Kool RB. Implementation of multiple-domain covering computerized decision support systems in primary care: a focus group study on perceived barriers. BMC Med Inform Decis Mak. 2015;15(1):1–11. Varonen H, Kortteisto T, Kaila M, Group EbmS. What may help or hinder the implementation of computerized decision support systems (CDSSs): a focus group study with physicians. Fam Pract. 2008;25(3):162–7. Khairat S, Marc D, Crosby W, Al Sanousi A. Reasons for physicians not adopting clinical decision support systems: critical analysis. JMIR Med informatics. 2018;6(2):e24. Westerbeek L, Ploegmakers KJ, de Bruijn G-J, Linn AJ, van Weert JCM, Daams JG, et al. Barriers and Facilitators Influencing Medication-Related CDSS Acceptance According to Clinicians: A Systematic Review. Int J Med Inform. 2021;104506. Lai F, Macmillan J, Daudelin DH, Kent DM. The potential of training to increase acceptance and use of computerized decision support systems for medical diagnosis. Hum Factors. 2006;48(1):95–108. Trivedi MH, Kern JK, Marcee A, Grannemann B, Kleiber B, Bettinger T, et al. Development and implementation of computerized clinical guidelines: barriers and solutions. Methods Inf Med. 2002;41(05):435–42. Tsiknakis M, Kouroubali A. Organizational factors affecting successful adoption of innovative eHealth services: a case study employing the FITT framework. Int J Med Inform. 2009;78(1):39–52. Rahal RM, Mercer J, Kuziemsky C, Yaya S. Factors affecting the mature use of electronic medical records by primary care physicians: a systematic review. BMC Med Inform Decis Mak. 2021;21(1):1–15. Randhawa GK, Shachak A, Courtney KL, Kushniruk A. Evaluating a post-implementation electronic medical record training intervention for diabetes management in primary care. BMJ Heal care informatics. 2019;26(1). Msiska KEM, Kumitawa A, Kumwenda B. Factors affecting the utilisation of electronic medical records system in Malawian central hospitals. Malawi Med J. 2017;29(3):247–53. Paré G, Raymond L, de Guinea AO, Poba-Nzaou P, Trudel M-C, Marsan J, et al. Electronic health record usage behaviors in primary care medical practices: a survey of family physicians in Canada. Int J Med Inform. 2015;84(10):857–67. Asch DA, Jedrziewski MK, Christakis NA. Response rates to mail surveys published in medical journals. J Clin Epidemiol. 1997;50(10):1129–36. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1751250","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":162142962,"identity":"6a11a9c3-b242-405f-96cb-58a409c6bdec","order_by":0,"name":"Fares Albahar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYBAC9gbmNgbGBgYGfjCXjQHMwQt4DjBCtEg2kKzF4ABUC0HAw36w7cHPHXb5xufPGDB8KDvMwNxOwBoensR2w94zyZbbDpwxYJxx7jADY88B/FrsGRLbJHjbmA3MDvYYMPO2AbXMSCBgC//DNsm/bfUGxs08Bsx/idIikdgmDTTcwIANqIWROC0P241l244bSJxhKzjYcy6dh6BfePiTjz1821ZtwN9/eOODH2XWcoaEQgwFgIznMSRFBwTIk6xjFIyCUTAKhjsAAG4SQoqmlRyRAAAAAElFTkSuQmCC","orcid":"","institution":"Zarqa University","correspondingAuthor":true,"prefix":"","firstName":"Fares","middleName":"","lastName":"Albahar","suffix":""},{"id":162142964,"identity":"083ddb34-26aa-49d7-aa3a-cd2f3a90c73f","order_by":1,"name":"Rana K Abu-Farha","email":"","orcid":"","institution":"Applied Private Science University","correspondingAuthor":false,"prefix":"","firstName":"Rana","middleName":"K","lastName":"Abu-Farha","suffix":""},{"id":162142966,"identity":"fa6bf923-fb1b-4706-8e39-b4e8a204df51","order_by":2,"name":"Osama Y Alshogran","email":"","orcid":"","institution":"Jordan University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Osama","middleName":"Y","lastName":"Alshogran","suffix":""},{"id":162142968,"identity":"ca12a428-22ab-436f-b3d6-da0e48606a42","order_by":3,"name":"Hamza Alhamad","email":"","orcid":"","institution":"Zarqa University","correspondingAuthor":false,"prefix":"","firstName":"Hamza","middleName":"","lastName":"Alhamad","suffix":""},{"id":162142970,"identity":"3c061527-bd5f-4322-9afd-573879a1b77a","order_by":4,"name":"Chris Curtis","email":"","orcid":"","institution":"University of Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Chris","middleName":"","lastName":"Curtis","suffix":""},{"id":162142972,"identity":"bcb3d78f-177d-4883-a053-f1408b14ce6e","order_by":5,"name":"John Marriott","email":"","orcid":"","institution":"University of Birmingham","correspondingAuthor":false,"prefix":"","firstName":"John","middleName":"","lastName":"Marriott","suffix":""}],"badges":[],"createdAt":"2022-06-12 22:29:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1751250/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1751250/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":31126741,"identity":"fe09102a-b12c-4824-aced-698e72b05248","added_by":"auto","created_at":"2023-01-04 22:17:30","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":67290,"visible":true,"origin":"","legend":"\u003cp\u003eParticipants perceived the benefits of using electronic prescribing and electronic health record systems in antimicrobial stewardship (n= 254)\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1751250/v1/1209b5d352a7cc6bbf482ca4.jpg"},{"id":31126742,"identity":"2d1832d1-5288-484a-800f-27ec7c5e052c","added_by":"auto","created_at":"2023-01-04 22:17:30","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":74618,"visible":true,"origin":"","legend":"\u003cp\u003eParticipants perceived barriers to using electronic prescribing and electronic health record systems in antimicrobial stewardship (n= 254)\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1751250/v1/087173d99341e7390dea6349.jpg"},{"id":31126743,"identity":"17fa85ab-58ce-488b-8a10-6878323ad8ed","added_by":"auto","created_at":"2023-01-04 22:17:30","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":88980,"visible":true,"origin":"","legend":"\u003cp\u003eParticipants perceived facilitators to use electronic prescribing and electronic health record systems in antimicrobial stewardship (n= 254)\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1751250/v1/7fabc3cc5a3847f1fedb4fa0.jpg"},{"id":31935876,"identity":"11ca0719-8f3b-4f03-8c15-30c6fca9f527","added_by":"auto","created_at":"2023-01-23 10:44:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":512100,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1751250/v1/9e867c87-2d50-4d22-a73c-ed04f4854a29.pdf"},{"id":31126744,"identity":"e5ffc239-232e-43ad-98a8-e94c8eeaed7f","added_by":"auto","created_at":"2023-01-04 22:17:30","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1150584,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-1751250/v1/4e6c0d1088feeef862d446e9.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Health care professionals' perceptions towards the use of computerized clinical decision support systems in antimicrobial stewardship in Jordanian hospitals: A two institutional study","fulltext":[{"header":"1. Background","content":"\u003cp\u003eThe prevalence of multidrug resistance has increased alarmingly worldwide (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Also, the inappropriate use of antimicrobial agents has been correlated with antimicrobial resistance (AMR) (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). The World Health Organisation (WHO) released a recent feasible toolkit concerning the use of Antimicrobial Stewardship (AMS) in healthcare settings in low and middle-income countries to optimize the use of antibiotics and contain the problem of AMR (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). The Jordanian minister of health's national four-year action plan aligned with the WHO global action plan to maintain the efficiency of existing antibiotics through AMS (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). The national plan was developed considering the importance of healthcare information technology to combat AMR (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMany information technology systems have been developed to aid clinicians in decision-making (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). One such system is the Computerised Clinical Decision Support System (CDSS). The CDSS provides real-time, evidence-based decision support at the point of care about the choice of antimicrobial agents in selected infections (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). However, the CDSS is less commonly used in clinical practice despite its effectiveness in reducing AMR (\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). The impact of CDSS has been evaluated through many different clinical settings (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Some studies showed positive impacts such as improved patient care processes, health care costs, physician workflows, and adherence to the guidelines (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn contrast, others showed a negative effect and failed to achieve their intended outcomes (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Given that negative perceptions of health care professionals towards CDSS could affect the acceptance of such systems. Understanding the perceptions and attitudes of health care professionals towards CDSS may provide a platform for the determinants of the successful adoption and implementation of CDSS. Therefore, it is interesting to study healthcare professionals' perceptions of CDSS (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) and their role in CDSS adoption (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). In addition, this study examines potential barriers and facilitators that hinder or enable CDSS use in clinical practice and AMS. Highlighting these factors would provide a framework for successful CDSS implementation and use.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Hospital setting and participants\u003c/h2\u003e \u003cp\u003eThis prospective cross-sectional study was conducted in two tertiary teaching hospitals, the University of Jordan and King Abdullah University Hospitals. The University of Jordan hospital is a large (600-bed) academic centre located in Amman (Middle), Jordan. King Abdullah University Hospital (750-bed) is another large academic centre located in Irbid (North), Jordan. Both hospitals have infectious diseases departments that apply AMS principles which curtailed the use of broad-spectrum antimicrobials within the hospital.\u003c/p\u003e \u003cp\u003eTwo categories of healthcare professionals were invited to participate: medical and non-medical healthcare professionals. In addition, senior and junior doctors from different specialties were asked to participate in the survey and other healthcare professionals, including pharmacists, microbiology experts, and infection control experts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Survey development and data collection\u003c/h2\u003e \u003cp\u003eThe complete survey has been adopted from Zaidi et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), as shown in appendix 2. A pool of ten items to measure barriers and nine items to measure facilitators were initially drafted into a survey tool. Two clinical pharmacists and one infectious diseases consultant reviewed the drafted survey items. These items were then reviewed by research experts familiar with study design in two universities. The reviewers' comments were about wording, clarity, comprehensiveness, and whether each survey item was pertinent to the study's goals and objectives. These comments were used to develop the final version of the survey. The final version of the survey included 38 items divided into four domains. The first domain collected participants\u0026rsquo; demographic data such as age, gender, specialty, and experience in a specialist role. The second domain collected information about the perceptions of healthcare professionals towards AMS. The third domain collected information about the awareness of using CDSS and the perceived benefits. The last domain collected information on the perceived barriers and facilitators towards using CDSS. The survey was piloted in the local region, especially with two clinical pharmacists and one infectious diseases consultant, in March 2021. Two clinical pharmacists distributed the questionnaire in a paper-based format for senior and junior prescribers and non-prescribers at the University of Jordan Hospital and King Abdullah University Hospital. Healthcare professionals were informed that participation is voluntary, information collected will be anonymous, and the survey would require 10\u0026ndash;15 minutes to finish. The delivery of the questionnaire lasted four weeks, started on June 15, 2021, and was closed on July 14, 2021. A reminder was sent four weeks later.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Statistical analysis\u003c/h2\u003e \u003cp\u003eThe statistical package for social science (SPSS\u0026reg;) version 22 (SPSS\u0026reg; Inc., Chicago, IL, USA) was used for data analysis. The mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD and frequency (percentages) were used for continuous and categorical variables, respectively. Uni and multivariate logistic regression was employed to screen for factors that affect participants\u0026rsquo; awareness about using electronic prescribing and electronic health record systems in AMS. Variables that were significant on a single predictor level (P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.25) using univariate logistic regression analysis were contained in the logistic regression analysis model. In the logistic regression analysis, variables independently associated with awareness about the use of electronic prescribing and the electronic health record system in AMS were identified. Statistical significance was considered at P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eA total of 254 healthcare providers agreed to participate in this study and completed the survey with a response rate of 46% (254 out of 550). The majority of participants (n\u0026thinsp;=\u0026thinsp;193, 76%) were aged between 20\u0026ndash;30 years old, and 59.1% (n\u0026thinsp;=\u0026thinsp;150) were females. About 60% (n\u0026thinsp;=\u0026thinsp;154) of the participants were physicians, while the remaining were pharmacists (n\u0026thinsp;=\u0026thinsp;60, 23.6%) and nurses (n\u0026thinsp;=\u0026thinsp;40, 15.7%). Study Demographics are presented in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSocio-demographic characteristics of the study sample (n\u0026thinsp;=\u0026thinsp;254)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003cp\u003eo 20\u0026ndash;30\u003c/p\u003e\n \u003cp\u003eo 31\u0026ndash;40\u003c/p\u003e\n \u003cp\u003eo 41\u0026ndash;50\u003c/p\u003e\n \u003cp\u003eo 51\u0026ndash;60\u003c/p\u003e\n \u003cp\u003eo \u0026gt;\u0026thinsp;61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e193 (76.0)\u003c/p\u003e\n \u003cp\u003e54 (21.3)\u003c/p\u003e\n \u003cp\u003e5 (2.0)\u003c/p\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003cp\u003e2 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003cp\u003eo Males\u003c/p\u003e\n \u003cp\u003eo Females\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e104 (40.9)\u003c/p\u003e\n \u003cp\u003e150 (59.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpeciality\u003c/p\u003e\n \u003cp\u003eo Clinical pharmacist\u003c/p\u003e\n \u003cp\u003eo Physicians\u003c/p\u003e\n \u003cp\u003eo Nurse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e60 (23.6)\u003c/p\u003e\n \u003cp\u003e154 (60.6)\u003c/p\u003e\n \u003cp\u003e40 (15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\u003c/br\u003e\n\u003cp\u003eParticipants were asked about their awareness of the use of electronic prescribing and electronic health record systems in general and in AMS (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The majority (n\u0026thinsp;=\u0026thinsp;220, 86.6%) reported knowing about the presence of electronic prescribing and electronic health record systems at their hospitals. In addition, around three-quarters (n\u0026thinsp;=\u0026thinsp;84, 72.4%) were aware that such systems could be used to facilitate antibiotic use prescribing. However, a lower percentage of the respondents (n\u0026thinsp;=\u0026thinsp;161, 63.4%) were aware that those systems could provide a clinical decision support function to support evidence-based practice.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParticipants' awareness about the use of electronic prescribing and electronic health record systems in antimicrobial stewardship (n\u0026thinsp;=\u0026thinsp;254)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatements\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStrongly Agree/agree\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHave you previously used electronic prescribing and electronic health record systems?\u003c/p\u003e \u003cp\u003eo Yes\u003c/p\u003e \u003cp\u003eo No/Not sure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e220 (86.6)\u003c/p\u003e \u003cp\u003e34 (13.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAre you aware that electronic prescribing and electronic health record systems can be used to facilitate antibiotic prescribing?\u003c/p\u003e \u003cp\u003eo Yes\u003c/p\u003e \u003cp\u003eo No/Not sure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e184 (72.4)\u003c/p\u003e \u003cp\u003e70 (27.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAre you aware that electronic prescribing and electronic health record system is capable of providing clinical decision support function in order to support evidence-based practice?\u003c/p\u003e \u003cp\u003eo Yes\u003c/p\u003e \u003cp\u003eo No/Not sure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e161 (63.4)\u003c/p\u003e \u003cp\u003e93 (36.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAll participating healthcare providers responded to five statements to express their perception of AMS (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). First, healthcare providers showed a positive perception of AMS, where 88.2% of respondents (n\u0026thinsp;=\u0026thinsp;224) agreed/strongly agreed that AMS programs might improve patient care. Similarly, 89.7% of respondents (n\u0026thinsp;=\u0026thinsp;228) believed that those programs might reduce the problem of AMR. In addition, more than 90% of respondents agreed/strongly that stewardship programs should be incorporated at a hospital level and that healthcare providers should be provided with adequate training on antimicrobial use. On the other hand, only 52.4% of the respondents (n\u0026thinsp;=\u0026thinsp;133) believed that the antimicrobial prescribing at their hospital is already as good as possible.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePerception of participants towards antimicrobial stewardship (n\u0026thinsp;=\u0026thinsp;254)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatements\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStrongly Agree/agree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNeutral\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStrongly disagree/disagree\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntimicrobial prescribing at your hospital is already as good as it can be\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e133 (52.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46 (12.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75 (29.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntimicrobial stewardship programs may improve patient care.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e224 (88.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14 (5.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntimicrobial stewardship should be incorporated at a hospital level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e229 (90.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14 (5.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntimicrobial stewardship programs may reduce the problem of antimicrobial resistance.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e228 (89.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14 (5.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdequate training should be provided to health care professionals on antimicrobial use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e235 (92.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14 (5.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eParticipants were also asked about their perceived benefits of using electronic prescribing and electronic health record systems in AMS. Results showed that respondents believed that those systems might reduce the expenditure on antibiotics (n\u0026thinsp;=\u0026thinsp;212, 83.4%), improve the safety of antibiotic use (n\u0026thinsp;=\u0026thinsp;210, 82.7%), and may improve the ability to deliver AMS (n\u0026thinsp;=\u0026thinsp;205, 80.8%). For more details, refer to Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eRegarding the barriers against the use of electronic prescribing and electronic health record systems in AMS (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), results demonstrate that the most important barrier was the insufficient training to use the systems (n\u0026thinsp;=\u0026thinsp;175, 68.9%), followed by the lack of access to reliable technical support (n\u0026thinsp;=\u0026thinsp;173, 68.1%). The least important barrier was the limitation to medical autonomy (n\u0026thinsp;=\u0026thinsp;111, 43.7%).\u003c/p\u003e \u003cp\u003eOn the other hand, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates the perceived facilitators of AMS electronic prescribing and electronic health record systems. Results showed that the most important facilitator was making the system available in a portable format like mobile or personal digital assistant (n\u0026thinsp;=\u0026thinsp;224, 88.2%), followed by linking radiology and laboratory results to the system (n\u0026thinsp;=\u0026thinsp;220, 86.6% for both). For more details, refer to Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eFinally, logistic regression (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) showed that female healthcare providers showed significantly lower awareness about using electronic prescribing and electronic health record systems in AMS than males (P\u0026thinsp;=\u0026thinsp;0.006). Also, nurses showed significantly higher awareness about using those systems in AMS than pharmacists and physicians (P\u0026thinsp;=\u0026thinsp;0.041).\u003c/p\u003e \n\u003cdiv class=\"gridtable\"\u003e\u003ctable border=\"1\" id=\"Tab4\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAssessment of factors affecting participants awareness about the use of electronic prescribing and electronic health record systems in antimicrobial stewardship (n\u0026thinsp;=\u0026thinsp;254)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eAwareness\u003c/p\u003e\n \u003cp\u003e[0: No, 1: Yes]\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value#\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003cp\u003eo 20\u0026ndash;30 years\u003c/p\u003e\n \u003cp\u003eo \u0026gt;\u0026thinsp;31 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e3.135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.005^\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003cp\u003eo Male\u003c/p\u003e\n \u003cp\u003eo Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e0.394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003^\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.402\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.006*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpeciality\u003c/p\u003e\n \u003cp\u003eo Physicians\u003c/p\u003e\n \u003cp\u003eo Pharmacists\u003c/p\u003e\n \u003cp\u003eo Nurses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e1.322\u003c/p\u003e\n \u003cp\u003e4.327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e0.410\u003c/p\u003e\n \u003cp\u003e0.008^\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e1.636\u003c/p\u003e\n \u003cp\u003e3.249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e0.172\u003c/p\u003e\n \u003cp\u003e0.041*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e# using simple logistic regression, $ using multiple logistic regression, ^ eligible for entry in multiple logistic regression, * significant at 0.05 significance level\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e This is a two-centre study (both large tertiary and teaching hospitals) from the middle and north area of Jordan in which 254 healthcare professionals provided their insights about their positive perceptions toward AMS, demonstrated by their agreement that its use would improve patient outcomes and curtail AMR. This study aimed to examine the potential barriers and facilitators that hinder or enable CDSS use in clinical practice and AMS based on the healthcare professionals' views. Therefore, understanding perceived barriers and facilitators to CDSSs is vital to maximise the technology's adoption and uptake and potentially impact patient outcomes.\u003c/p\u003e \u003cp\u003eThe study survey adopted was refined to study CDSS considering various contexts, from two healthcare centres where the healthcare professionals would be unfamiliar with the technology to those in mature stages in its implementation. Consequently, the results from this study are expected to help guide the development of strategies and recommendations essential to introducing and integrating CDSS into wider national healthcare settings, including the two hospital centres.\u003c/p\u003e \u003cp\u003eThis study showed that healthcare professionals had a positive awareness and perceptions toward the electronic prescribing and electronic health record systems explained by their understanding that AMS use would improve patient outcomes and limit AMR. Also, the healthcare professionals perceived that electronic prescribing is beneficial and would reduce the high cost of prescribing antibiotics (i.e., reduce the expenditure of antibiotics), improve the efficacy and the safety of antibiotic use, and may improve the ability to deliver AMS to optimise the rational use of antibiotics. In addition, many systematic reviews and studies demonstrated the impact of adopting the CDSS on antibiotics management and AMS (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan additionalcitationids=\"CR23 CR24 CR25 CR26 CR27 CR28\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe lack of appropriate training to use the electronic prescribing and electronic health record systems and the lack of access to reliable technical support were the most perceived barriers to CDSS adoption among healthcare professionals. Also, more than half of the healthcare professionals had a low level of awareness and were unfamiliar with using electronic prescribing and electronic health record systems. Furthermore, given that healthcare professionals have busy work schedules, they do not have enough time to learn how to use the system. Therefore, adequate training should be encouraged for novice and experienced healthcare professionals to use the CDSS system and improve workflow effectively. Also, technical support should be provided to the healthcare professionals in each ward of the hospital to avoid any difficulties in using the systems and to maximise the effective use of CDSS. Previous studies reported similar results (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan additionalcitationids=\"CR30 CR31 CR32\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). For example, one recent cross-sectional study from Australia that evaluated the impact of CDSS adoption on antibiotics management reported that the lack of appropriate training and technical support was an essential barrier to CDSS adoption (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). In addition, the significance of training and technical support for CDSS adoption was evident in previous studies (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMaking the system in an easily portable format (i.e., like a mobile or a personal digital assistant) was the most perceived facilitator for adopting CDSS by healthcare professionals. This is expected to enable healthcare professionals to make a decision regarding the prescribing and monitoring of antibiotics from remote areas without the need to be in the ward or even in the hospital to prescribe and monitor antibiotics, thus, making work more flexible. Also, lab and radiology results linked to the CDSS are facilitators for adopting CDSS. As a result, healthcare professionals will not be required to check different databases to confirm the diagnosis and adjust treatment based on laboratory results. This will make the work schedule more flexible and efficient. Similar studies reported the same results (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). For example, one cross-sectional study conducted in a tertiary care university hospital in Melbourne, Australia, reported making the CDSS in an easily portable format, linking lab and radiology results as a facilitator to the adoption of CDSS (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). This was also evident in a recent systematic review (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) and a previous study (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe logistic regression results about the factors affecting participants' awareness about the use of electronic prescribing and electronic health record systems in antimicrobial stewardship showed that female healthcare providers had significantly lower awareness about using electronic prescribing and electronic health record systems. In contrast, the nurses showed significantly higher awareness about using those systems in stewardship programs. Gender as a factor affecting participants' awareness about the use of electronic prescribing and electronic health record systems was studied in the literature (\u003cspan additionalcitationids=\"CR38 CR39\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e), with studies showing no difference (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e), and others showed higher awareness among females (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e) contrasted to the results from our study. Considering that males and females are supposed to have equal technological exposure, knowledge, and awareness, the results from our study should be further explored.\u003c/p\u003e \u003cp\u003eThe response rate was less than optimal similar to other response rates in the literature (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e); this may affect the representative of the data obtained and may be a limitation to this study. Nevertheless, it is vital to note that the study attracted healthcare professionals with various degrees of system usage. Therefore, the sample seems adequate to address the study's aims.\u003c/p\u003e \u003cp\u003eThis study has several strengths. First, the sample size of 254 healthcare providers (despite a low response rate\u0026thinsp;=\u0026thinsp;46%) from two large tertiary teaching hospitals is considered satisfactory and would add to the representativeness of the results drawn from this study. Second, the CDSS system was designed by developers independent of the end-user healthcare professionals. So, the healthcare professionals were not involved in designing and implementing the CDSS. This is expected to reduce the potential for investigator bias. Finally, it is noteworthy that the use of the CDSS was optional, which minimises the likelihood that healthcare professionals were influenced by hospital policy to use the CDSS system.\u003c/p\u003e \u003cp\u003e While the CDSS system is increasingly gaining popularity in implementing hospital guidelines for prescribing antibiotics, significant barriers to its adoption exist. To implement CDSS systems successfully, the developer needs to understand the barriers to their adoption. The present study measures healthcare professionals' perceptions of using the CDSS system in two tertiary care settings in Jordan's middle and north areas. Both the study setting and study participants represent a metropolitan area. Therefore, the findings from the study could apply to other healthcare settings interested in the launch and implementation of CDSS systems. While the study investigators are independent of the developer and implementer of the CDSS system at the study hospitals, the present study results have been available to them to improve the implementation and deployment strategies.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study examined health care professionals' perceptions towards adopting CDSS for antibiotic prescribing from Jordan's two tertiary and teaching hospitals. Implementing CDSS in Antimicrobial Stewardship (AMS) would help reduce antibiotic resistance and improve patient safety. In addition, results would provide insight into the perceived barriers and facilitators to adopting CDSS and provide a platform for other healthcare settings interested in implementing CDSS in AMS locally and globally. Also, this study would help inform policy decision-makers in Jordan to react by implementing the CDSS system at the national level. Therefore, future studies should focus on establishing guidelines and a policy framework to examine the adoption of the CDSS for AMS.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThis study was approved by the Zarqa University Ethics Committee for Scientific Research (ECSR) (supplementary\u0026nbsp;material), following the principles of the protection of human subjects and the ethical principles related to research studies, and was given an approval number (3/3/2018-2019), and Jordan University Hospital (80/2019/23), and King Abdullah University Hospital (49/128/2019). Also, an informed consent form was obtained from all participants before participating in the study, ensuring that participation was voluntary and participants could withdraw at any stage, with their answers treated confidentially. All methods were performed according to the relevant university\u0026rsquo;s guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003e\u0026ldquo;Not applicable\u0026rdquo;.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials: All data generated or analysed during this study are included in this published article [and its supplementary information files].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no conflict of interest.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research did not receive any grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contribution\u003c/strong\u003e: Fares Albahar and Hamza Alhamad contributed to the design and conception of the study, acquisition of data, analysis, and interpretation of data, drafting of the article, critically revising, and final approval of the version to be published. Rana Abu-Farha contributed to the analysis and interpretation of data, drafting the article, critically revising, and final approval of the version to be published. Osama Alshoqran contributed to the acquisition of data, analysis, interpretation of data, and final approval of the version to be published. Chris Curtis contributed to the study\u0026apos;s design and conception, drafting the article, critically revising it, and final approval of the version to be published. Finally, John Marriott contributed to the design and conception of the study drafting the article, critically revising, and final approval of the version to be published\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e: The authors acknowledge the healthcare professionals who participated in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eJohnson S V, Hoey LL, Vance‐Bryan K. Inappropriate vancomycin prescribing based on criteria from the Centers for Disease Control and Prevention. Pharmacother J Hum Pharmacol Drug Ther. 1995;15(5):579–85. \u003c/li\u003e\n\u003cli\u003eTalbot GH, Bradley J, Edwards Jr JE, Gilbert D, Scheld M, Bartlett JG. Bad bugs need drugs: an update on the development pipeline from the Antimicrobial Availability Task Force of the Infectious Diseases Society of America. Clin Infect Dis. 2006;42(5):657–68. \u003c/li\u003e\n\u003cli\u003eNusair MB, Al‐azzam S, Alhamad H, Momani MY. The prevalence and patterns of self‐medication with antibiotics in Jordan: A community‐based study. Int J Clin Pract. 2021;75(1):e13665. \u003c/li\u003e\n\u003cli\u003eOrganization WH. Antimicrobial stewardship programmes in health-care facilities in low-and middle-income countries: a WHO practical toolkit. 2019; \u003c/li\u003e\n\u003cli\u003eHashemite Kingdom of Jordan I. National Action Plan to Combat Antimicrobial Resistance. 2018; \u003c/li\u003e\n\u003cli\u003eSutton RT, Pincock D, Baumgart DC, Sadowski DC, Fedorak RN, Kroeker KI. An overview of clinical decision support systems: benefits, risks, and strategies for success. NPJ Digit Med. 2020;3(1):1–10. \u003c/li\u003e\n\u003cli\u003eCurtis CE, Al Bahar F, Marriott JF. The effectiveness of computerised decision support on antibiotic use in hospitals: a systematic review. PLoS One. 2017;12(8):e0183062. \u003c/li\u003e\n\u003cli\u003eAl Bahar F, Curtis CE, Alhamad H, Marriott JF. The impact of a computerised decision support system on antibiotic usage in an English hospital. Int J Clin Pharm. 2020;42(2):765–71. \u003c/li\u003e\n\u003cli\u003eBaysari MT, Oliver K, Egan B, Li L, Richardson K, Sandaradura I, et al. Audit and feedback of antibiotic use. Appl Clin Inform. 2013;4(04):583–95. \u003c/li\u003e\n\u003cli\u003ePawloski PA, Brooks GA, Nielsen ME, Olson-Bullis BA. A systematic review of clinical decision support systems for clinical oncology practice. J Natl Compr Cancer Netw. 2019;17(4):331–8. \u003c/li\u003e\n\u003cli\u003eKlarenbeek SE, Weekenstroo HHA, Sedelaar JP, Fütterer JJ, Prokop M, Tummers M. The effect of higher level computerized clinical decision support systems on oncology care: a systematic review. Cancers (Basel). 2020;12(4):1032. \u003c/li\u003e\n\u003cli\u003eRawson TM, Moore LSP, Hernandez B, Charani E, Castro-Sanchez E, Herrero P, et al. A systematic review of clinical decision support systems for antimicrobial management: are we failing to investigate these interventions appropriately? Clin Microbiol Infect. 2017;23(8):524–32. \u003c/li\u003e\n\u003cli\u003eBright TJ, Wong A, Dhurjati R, Bristow E, Bastian L, Coeytaux RR, et al. Effect of clinical decision-support systems: a systematic review. Ann Intern Med. 2012;157(1):29–43. \u003c/li\u003e\n\u003cli\u003eRoshanov PS, Misra S, Gerstein HC, Garg AX, Sebaldt RJ, Mackay JA, et al. Computerized clinical decision support systems for chronic disease management: a decision-maker-researcher partnership systematic review. Implement Sci. 2011;6(1):1–16. \u003c/li\u003e\n\u003cli\u003eGarg AX, Adhikari NKJ, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. Jama. 2005;293(10):1223–38. \u003c/li\u003e\n\u003cli\u003eKawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. Bmj. 2005;330(7494):765. \u003c/li\u003e\n\u003cli\u003eGadd CS, Baskaran P, Lobach DF. Identification of design features to enhance utilization and acceptance of systems for Internet-based decision support at the point of care. In: Proceedings of the AMIA Symposium. American Medical Informatics Association; 1998. p. 91. \u003c/li\u003e\n\u003cli\u003eRosenbloom ST, Talbert D, Aronsky D. Clinicians’ perceptions of clinical decision support integrated into computerized provider order entry. Int J Med Inform. 2004;73(5):433–41. \u003c/li\u003e\n\u003cli\u003eSatsangi S, Weir CR, Morris AH, Warner HR. Cognitive evaluation of the predictors of use of computerized protocols by clinicians. In: AMIA Annual Symposium Proceedings. American Medical Informatics Association; 2003. p. 574. \u003c/li\u003e\n\u003cli\u003eZheng K, Padman R, Johnson MP, Diamond HS. Understanding technology adoption in clinical care: clinician adoption behavior of a point-of-care reminder system. Int J Med Inform. 2005;74(7–8):535–43. \u003c/li\u003e\n\u003cli\u003eZaidi STR, Marriott JL. Barriers and facilitators to adoption of a web-based antibiotic decision support system. South Med Rev. 2012;5(2):42. \u003c/li\u003e\n\u003cli\u003ePaskovaty A, Pflomm JM, Myke N, Seo SK. A multidisciplinary approach to antimicrobial stewardship: evolution into the 21st century. Int J Antimicrob Agents. 2005;25(1):1–10. \u003c/li\u003e\n\u003cli\u003ePaterson DL. The role of antimicrobial management programs in optimizing antibiotic prescribing within hospitals. Clin Infect Dis. 2006;42(Supplement_2):S90–5. \u003c/li\u003e\n\u003cli\u003eBearden DT, Allen GP. Impact of antimicrobial control programs on patient outcomes. Dis Manag Heal Outcomes. 2003;11(11):723–36. \u003c/li\u003e\n\u003cli\u003eSamore MH, Bateman K, Alder SC, Hannah E, Donnelly S, Stoddard GJ, et al. Clinical decision support and appropriateness of antimicrobial prescribing: a randomized trial. Jama. 2005;294(18):2305–14. \u003c/li\u003e\n\u003cli\u003eMcGregor JC, Weekes E, Forrest GN, Standiford HC, Perencevich EN, Furuno JP, et al. Impact of a computerized clinical decision support system on reducing inappropriate antimicrobial use: a randomized controlled trial. J Am Med Informatics Assoc. 2006;13(4):378–84. \u003c/li\u003e\n\u003cli\u003eAlbarillo FS, Labuszewski L, Lopez J, Santarossa M, Bhatia NK. Use of a Clinical Decision Support System (CDSS) to improve antimicrobial stewardship efforts at a single academic medical center. Germs. 2019;9(2):106. \u003c/li\u003e\n\u003cli\u003eNassar H, Abu-Farha R, Barakat M, Alefishat E. Antimicrobial Stewardship from Health Professionals’ Perspective: Awareness, Barriers, and Level of Implementation of the Program. Antibiotics. 2022;11(1):99. \u003c/li\u003e\n\u003cli\u003eLaka M, Milazzo A, Merlin T. Factors That Impact the Adoption of Clinical Decision Support Systems (CDSS) for Antibiotic Management. Int J Environ Res Public Health. 2021;18(4):1901. \u003c/li\u003e\n\u003cli\u003eLugtenberg M, Weenink J-W, van der Weijden T, Westert GP, Kool RB. Implementation of multiple-domain covering computerized decision support systems in primary care: a focus group study on perceived barriers. BMC Med Inform Decis Mak. 2015;15(1):1–11. \u003c/li\u003e\n\u003cli\u003eVaronen H, Kortteisto T, Kaila M, Group EbmS. What may help or hinder the implementation of computerized decision support systems (CDSSs): a focus group study with physicians. Fam Pract. 2008;25(3):162–7. \u003c/li\u003e\n\u003cli\u003eKhairat S, Marc D, Crosby W, Al Sanousi A. Reasons for physicians not adopting clinical decision support systems: critical analysis. JMIR Med informatics. 2018;6(2):e24. \u003c/li\u003e\n\u003cli\u003eWesterbeek L, Ploegmakers KJ, de Bruijn G-J, Linn AJ, van Weert JCM, Daams JG, et al. Barriers and Facilitators Influencing Medication-Related CDSS Acceptance According to Clinicians: A Systematic Review. Int J Med Inform. 2021;104506. \u003c/li\u003e\n\u003cli\u003eLai F, Macmillan J, Daudelin DH, Kent DM. The potential of training to increase acceptance and use of computerized decision support systems for medical diagnosis. Hum Factors. 2006;48(1):95–108. \u003c/li\u003e\n\u003cli\u003eTrivedi MH, Kern JK, Marcee A, Grannemann B, Kleiber B, Bettinger T, et al. Development and implementation of computerized clinical guidelines: barriers and solutions. Methods Inf Med. 2002;41(05):435–42. \u003c/li\u003e\n\u003cli\u003eTsiknakis M, Kouroubali A. Organizational factors affecting successful adoption of innovative eHealth services: a case study employing the FITT framework. Int J Med Inform. 2009;78(1):39–52. \u003c/li\u003e\n\u003cli\u003eRahal RM, Mercer J, Kuziemsky C, Yaya S. Factors affecting the mature use of electronic medical records by primary care physicians: a systematic review. BMC Med Inform Decis Mak. 2021;21(1):1–15. \u003c/li\u003e\n\u003cli\u003eRandhawa GK, Shachak A, Courtney KL, Kushniruk A. Evaluating a post-implementation electronic medical record training intervention for diabetes management in primary care. BMJ Heal care informatics. 2019;26(1). \u003c/li\u003e\n\u003cli\u003eMsiska KEM, Kumitawa A, Kumwenda B. Factors affecting the utilisation of electronic medical records system in Malawian central hospitals. Malawi Med J. 2017;29(3):247–53. \u003c/li\u003e\n\u003cli\u003eParé G, Raymond L, de Guinea AO, Poba-Nzaou P, Trudel M-C, Marsan J, et al. Electronic health record usage behaviors in primary care medical practices: a survey of family physicians in Canada. Int J Med Inform. 2015;84(10):857–67. \u003c/li\u003e\n\u003cli\u003eAsch DA, Jedrziewski MK, Christakis NA. Response rates to mail surveys published in medical journals. J Clin Epidemiol. 1997;50(10):1129–36. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-1751250/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1751250/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eUnderstanding health care professionals' perceptions towards a Computerised Decision Support System (CDSS) may provide a platform for the determinants of successful adoption and implementation of CDSS. Therefore, this study examines health care professionals' perceptions of barriers and facilitators to adopting a CDSS for antibiotic prescribing in Jordanian hospitals.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis cross-sectional study was conducted among healthcare professionals in Jordan's two tertiary and teaching hospitals (n\u0026thinsp;=\u0026thinsp;254). The survey was adapted from a previous study and comprised demographic items and scales to measure perceptions of healthcare professionals towards the barriers and facilitators to the adoption of CDSS for antibiotic prescribing were developed. In addition, Uni and multivariate logistic regression analyses were applied to screen for factors affecting participants' awareness of using electronic prescribing and electronic health record systems in AMS.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe majority (n\u0026thinsp;=\u0026thinsp;84, 72.4%) were aware that electronic prescribing and electronic health record systems could be used to facilitate antibiotic use prescribing. The essential facilitator made CDSS available in a portable format (n\u0026thinsp;=\u0026thinsp;224, 88.2%). While, insufficient training to use CDSS was the most significant barrier (n\u0026thinsp;=\u0026thinsp;175, 68.9%). The female providers showed significantly lower awareness (P\u0026thinsp;=\u0026thinsp;0.006) and the nurses significantly higher awareness (P\u0026thinsp;=\u0026thinsp;0.041) about using electronic prescribing and electronic health record systems.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study examined health care professionals' perceptions towards adopting CDSS in AMS. Results provide insight into the perceived barriers and facilitators to adopting CDSS in AMS.\u003c/p\u003e","manuscriptTitle":"Health care professionals' perceptions towards the use of computerized clinical decision support systems in antimicrobial stewardship in Jordanian hospitals: A two institutional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-01-04 22:17:25","doi":"10.21203/rs.3.rs-1751250/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5ebd4cb5-fc6d-42d3-8ee0-438d442ce215","owner":[],"postedDate":"January 4th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-01-23T10:44:39+00:00","versionOfRecord":[],"versionCreatedAt":"2023-01-04 22:17:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1751250","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1751250","identity":"rs-1751250","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}