Healthcare Professional Acceptance of Clinical Decision Support - Term Paper Example

Introduction Bioinformatics has lived up to expectations in revolutionizing healthcare both for professionals and patients. The term implies that computers the use of computation processes to gather, integrate, and utilize biological and genetic information for medical purposes. One of the key fields that have prospered in bioinformatics is clinical decision support systems (CDSS). Decision support systems are systems of information aimed at providing healthcare professionals (HCP), patients and other stakeholders with person-specific or medication-specific information based on a stored repository of clinical information that is carefully and intelligently filtered to enhance health, healthcare and manage cost of healthcare (Fillmore 2013). Other noted benefits of CDSS include lowering the errors in administering, dispensing and ordering drugs for patients (Kasselheim et al., 2010). However, despite the noted benefits of CDSS, its uptake, acceptance and application is subject to a number of influencing factors such as area of application, compiled clinical knowledge, the design of CDSS, vendors, (Moxey, et al., 2012) systems purchasers and users (Litvin, 2012). Several authors agree that acceptance and uptake of CDSS by healthcare professionals varies a lot with context, organization, healthcare system, local culture among others (de Vries et al., 2013; Heselmans, et al., 2012). This implies that studies to understand the uptake of CDSS in terms of challenges and opportunities is best done by a qualitative approach that can capture richer data though from a relatively smaller sample than from quantitative studies. Current and previous studies have revealed several constraints and factors that promote CDSS adoption by healthcare professionals. Some of them include improve the human–computer interface, implementation processes knowledge and database content of the CDS (Eberhardt, et al., 2012). A relatively new study reveals that patients derogate physicians who use CDSS but the study does not indicate how that affects the uptake of CDSS by healthcare professionals (Schaffer, et al., 2013). Other studies have shown the impact of CDSS on both healthcare professionals and patients. Majority of the systematic reviews on CDSS assess the efficiency of the systems in managing the outcomes on the part of patients and outcomes. There is knowledge gap in how the perceived and expected outcomes, challenges and opportunities of using CDSS have on the acceptance and uptake of the technology by healthcare professionals. This study thus uses a systematic review approach to summarize the findings on SR’s on effect on CDSS and the perceived attitudes of the healthcare professionals who use the system collected through relevant descriptive studies. Methods The researcher conducted a systematic review from published articles on factors affecting the uptake of clinical decision support systems by healthcare professionals. To do so, the researcher developed asset of questions that would enable the researcher identifies the best way to identify relevant studies to meet the SR’s objectives. The questions were formulated by assessing other studies that have addressed the impact of CDSS on patients, healthcare professionals, cost of healthcare and the suitability of the systems themselves. The studies to be reviewed had also to answer questions on the potential pitfalls that face use and implementation of CDSS. Other questions pertain to the uptake of CDSS are based on the people element. This includes attitudes, use impact on the decision, impact on the perception by others such as patients or fellow professionals in use of CDSS. There is only one study (Hor et al., 2010) that assessed the appropriateness of CDSS on specific situation, e-prescribing, while the all the others addressed the appropriateness of CDSS in general healthcare. None of the studies addressed the exact design of a CDSS as provided by different vendors and how the various features would impact on its usefulness, ease of use and its acceptability. Of much interest was whether the system for instance gave specific recommendations or just provided advice that required additional input by the user. Search strategy The search was limited to studies published between 2010 and 2014. The databases used for the search were CINAHL, AMED and Medline. The researcher conducted a search for relevant articles published in English language using terms “clinical decision support systems”, CDSS, “computerized decision support systems healthcare” “DSS” “uptake of DSS” contained in the title or abstract either as a combination or stand-alone. The articles had to be published in English language in the major healthcare technology and healthcare related peer reviewed journals in the developed world. The search was conducted between the 17th of May 2014 and 21st of May 2014. The researcher then examined the articles based on their titles and abstracts. Studies were included if they attained the following requirements. i. Studies had to be either systematic review or descriptive study ii. Data searches were conducted at Medline iii. The reviewer(s) had assessed the methodological quality of the studies included iv. CDSS characteristics were discussed v. Articles had to be published between 2010 and 2014 including citations vi. Data on the effect of CDSS as an intervention process vii. Addressed implementation processes viii. Addressed factors influencing adoption and implementation process Articles were omitted from the list if i. Did not involve humans ii. Conducted in third world countries The researcher then assessed the reference list of the selected articles for any additional relevant publications. The retrieved articles from the references list were also subjected to the same process where their relevance was assessed through their title and abstracts against the search terms used for the systematic review. Some of the articles were relevant in terms of the search terms in their titles and research questions as expressed in the abstracts but they failed to meet the date criteria given that this particular review sought to identify the most current information regarding this rapidly changing field of bioinformatics. PRISMA Flow Diagram Results Searching through the online databases, peer reviewed publications were identified using the search strategy. The title was the main indicator of the suitability of the articles with the abstract used to further assess the suitability of the articles. A total of 65 articles were identified and two added after perusing the bibliography lists of these articles. Only four authors had previously published works in the same topic but the articles were not reviewed as they were published earlier than 2010. The articles were examined based on their abstracts for their relevance to the subject and the key words identified. Thirty eight articles were excluded from this assessment. The abstracts were reviewed further and the articles objectives compared to the systematic review’s objectives which saw an additional nine articles being excluded. Systematic reviews were assed based on the method of identifying relevant articles. The articles had to indicate the procedures the reviewers used to arrive at the articles. Articles were further assed based on the selection criteria which saw an additional 12 articles being excluded as they did not meet the inclusion criteria which favoured qualitative studies. The data collection method and study objectives were also assessed on their ability to provide relevant data and information on the current review. At the final stage, only eight articles qualified to be used in the systematic review. Figure 1 summarizes the procedure that utilized the PRISMA model in identifying appropriate articles. Methods and study design aspects There were three systematic reviews (Moxey et al., 2012, Bright et al., 2012; Mair et al., 2012) and one synthesis of systematic reviews (Jaspers et al., 2011). There were four descriptive studies (Shibl, 2013; Hor et al., 2010; Esmaeilzadeh, et al., 2012; Heselmans et al., 2012) which addressed CDSS use by healthcare professionals in Australia, Malaysia and Ireland, and Belgium. One of the descriptive studies combined a descriptive study approach and a case study approach thus was labelled a descriptive study (Shibl, 2013). One other qualitative study is titled as a cross sectional study though it uses a descriptive study hence was categorised as such as it addressed key issues relevant to the current SR (Hor, et al., 2010). However, one article categorised as a systematic review is not titled as an SR though the mechanism used in identifying the articles follow the PRISMA mechanism as required of SR (Moxey et al., 2012). Another article (Jaspers et al., 2011), was a synthesis of past SRs on CDSS and its impact on healthcare professionals, organizations and patients. The review addressed 85 past SRs obtained from searches from Medline with no time limit. A total of 82 studies were reviewed. The SRs capture a wider data range while the qualitative/descriptive provide a more detailed look at the contextualized factors that affect uptake of CDSS by HCPs. The three SRs (Mair et al., 2012; Moxey, et al., 2012; Bright et al, 2012) reviewed a total of 243 articles with a majority of them assessing the impact on CDSS on healthcare processes, healthcare outcomes and patients rather than professionals to confirm lack of adequate research on impact of CDSS on HCPs. Nonetheless the effect of CDSS on healthcare outcomes and organizational processes was shown to sway HCPs responses to perceptions, acceptance and uptake of CDSS but the evidence is weak (Bright). CDSS characteristics The CDSSs studied in one of the qualitative studies related to e-Prescribing. The study assessed the willingness of general practitioners (GPs) in west Ireland to use an unnamed CDSSs in assisting them in making decision when making prescriptions as opposed to using other indexes printed on paper such as from British National Formulary (BNF), Monthly Index of Medical Specialties Ireland (MIMS) and international or local guidelines. Another qualitative study preferred using a sample of doctors from various backgrounds (GPs, Radiologists, anaesthesiologists etc.) aware of CDSS and its applications but not experienced in using it. The five SRs used did not address the vendor or mechanism used by the CDSSs assessed. All the five reviews a series of mechanisms among them search terms “CDSS” or “clinical decision support system” or “computerized decision support system” to identify articles without articulating what a CDSS entails. The third qualitative study used a sample of GPs with no clear indication of the characteristics of CDSS or its application in the specific cases. The fourth descriptive study involved family physicians in Germans and assessed their willingness to use CDSS and analysed the data both quantitatively and qualitatively (Heselmans et al., 2012). Data synthesis The study identified the common themes that influence uptake and implementation of CDSS in various situations and contexts. These factors, though largely human and organizational, were categorised into recurring themes that promote uptake and those that act as barriers to uptake of CDSS by HCPs. Barriers to and facilitators of CDSS uptake The quality and quantity of infrastructure provided and the way in which the CDSSs were implemented were key factors impacting on the uptake of decision support. Studies reported Attitudes and perception of HCPs In one of the descriptive studies, 46% of the respondents interviewed in three counties in Ireland believed that paper mechanisms on prescribing guidelines provided by a several national and international professional bodies were superior to the computerised CDSS in e-prescribing with a further 38% believed that the appear and computerised tools were at par (Hor et al., 2010). The second descriptive study involving interviews with 37 GPs in Australia revealed that only about 18.9% of respondents were familiar in using CDSS despite the fact that all were experienced in using computers with an average of 21 hours computer use per week (Shibl 2013). This kind of attitude is shared by the findings of the third descriptive study which showed that Malaysian HCPs especially those in the reference category viewed CDSS as competing for their roles hence discouraged and sabotaged any move to increase use and reliance of CDSS by junior physicians and nurses (Esmaeilzadeh et al., 2012). The fourth descriptive study involving Belgian family physicians showed that majority of the family physicians (66%) were very positive about CDSS and were looking forward to use them in future based on ease of use, usefulness and facilitating conditions (Heselmans et al., 2012). A synthesis of past studies on CDSS use show that studies on the outcome of CDSS use by HCPs are very few as only one of out the 18 SRs reviewed address HCPs with the rest addressing outcome on the part of patients (Jaspers et al.,., 2011). Despite this huge interest in patient outcomes, the evidence is inconclusive. However, other studies note that there is inadequate evidence on the impact of CDSS use on HCPs (Mair et al., 2012; Bright et al., 2012) Degree of involvement Two studies noted that the degree of involvement of HCPs in using the system and acting on its recommendations influences uptake due to COMPETING PRIORITIES (Mair et al.,, 2012; Esmaeilzadeh et al., 2012). Some HCPs in Malaysia also indicated that they felt the need to be involved more in the development and implementation of such systems to ensure that they systems did not in any way contradict to any previously held knowledge and practices by the HCPs especially where customized CDSSs are involved (Esmaeilzadeh et al., 2012). Confidence, security and accountability One study noted that HCPs were concerned about the security of data used by systems to make recommendations (Mair et al., 2012). HCPs were concerned whether they could own up to errors that could be prompted by errors in the system. In short, HCPs were concerned about the knowledge base of CDSS systems as compared to conventional decision support tools. This concern in confidence in the accuracy of the CDSSs versus the knowledge of HCPs can act as a barrier or promoting factor in the uptake and acceptance of HCP. This is because among the noted benefits of CDSS are reduced errors in healthcare related decision such as prescriptions. In terms of security, one review noted that 116 out of 801 articles had recorded cases of HCPs being worried about the accessibility of the system by unauthorised persons and how the system is poised to address sabotage issues (Mair et al., 2012). Technical support and training Two studies showed usefulness and facilitating conditions attained through organizations offering needed training and support enhance uptake (Bright et al., 2012 & Heselmans et al., 2012). One of the studies concluded that better understanding of the usefulness and role of CDSS as a complementary tool rather than a competing tool improved attitudes towards the system, encouraged used and increased uptake by recommending the system to other HCPs (Heselmans et al., 2012). Factors that promote uptake of CDSS by HCPs There is need to offer adequate training on use and importance of using CDSS. All the studies noted that HCPs required adequate training on the use of CDSS whether as stand lone systems to address specific situations such as managing a specific diseases or where CDSSs are applied as comprehensive systems. One article adds that the notion of CDSSs competing with senior HCPs in their reference capacity can be addressed through proper training and understanding the role and place of CDSS in providing healthcare services (Esmaeilzadeh et al., 2012). Positive attitude towards CDSS promotes uptake and acceptance. All the studies acknowledge that addressing the noted factors that are likely to promoted resistance to CDSS encourages use and support after implementation. One article specifically notes that a positive attitude towards CDSS can be promoted through proper training of HCPs to understand on the best was they can use and capitalise on the system such as improving their clinical knowledge (Bright et al., 2012) Limitations The study’s main issue was the absence on adequate random controlled studies on the acceptance and uptake of CDSS. This is an issue that was also highlighted by the systematic reviews used which also observed that majority of the studies on implication of CDSS concentrated on the impact of CDSS use on patients and organizations. Another limitation that encountered this study was the need to retain currency on the issues facing HCPs uptake of CDSS. Several studies were locked out as a result which could impact on the confidence of the findings of this review. There was limited access to recent full text articles for use in the study. Majority of relevant articles identified in the initial search from the various databases were excluded because only the abstracts were available. Abstracts do not provide comprehensive research findings and procedures but rather summarizes the study findings. Limited information on the published articles denies this systematic review the opportunity to address the acceptance and uptake of CDSSs by their specific features. Future studies on the CDSS use and acceptance should address the specific design features of the systems that can influence use, acceptance and usefulness to HCPs and healthcare organizations. To motivate such studies without bias, there journal editors should set minimum standards to researchers so as to encourage studies in that direction without necessarily comprising on bias through funded studies. Conclusion The review systematically selected and analysed published articles on CDSS acceptance and uptake by HCPs. Different methodologies and approaches to the topic were used in the analysed studies with varying samples or professionals. The studies reveal a worrying trend in the implementation process of CDSS with developers and healthcare organization assuming that CDSSs are automatically acceptable to HCPs based on the reported benefits of the systems on patients and healthcare outcomes. The current analysis has pointed out that there is glaring lack of enough evidence or large scale studies on uptake of CDSS by HCPs. This review breaks new ground in showing that there is a wide range of factors that come into play in influencing acceptance and uptake of CDSS by healthcare professionals. However, due to shortage of adequate research in this field, the findings of this study are not adequate evidence although they point to a new filed of research that should be given more attention both by healthcare organizations, CDSS developers and researchers to understand how best the benefits of CDSS can be realized better with increased uptake and penetration of CDSS. References Anchala, et al. (2012). Decision support system (DSS) for prevention of cardiovascular disease (CVD) among hypertensive (HTN) patients in Andhra Pradesh, India’ – a cluster randomised community intervention trial. BMC Public Health 12:393 Anchala, R. et al. (2012). The role of decision support system (dss) in prevention of cardiovascular disease: a systematic review and meta-analysis. PLOS 7(10); 1-8. Bright, T., Wong, A., Dhurati, R. Bristow, E. et al.,. (2012). Factors known to influence acceptance of clinical decision support systems. A systematic review Ann Intern Med. 157:29-43. Cercone, N. et al. 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