The key functionality of a computerized provider order entry (CPOE) is that of clinical decision support (CDS). According to French (2014), the Center for Medicare and Medicaid Services (CMS) explains that the CDS is a health information technology that is part of an electronic health record that gives providers needed information that is filtered and organized in a timely way to improve health and healthcare. Under CMS guidelines health care providers are expected to implement a relevant CDS rule appropriate to their practice setting to meet meaningful use (MU). Whenever a CDS is effectively applied it can improve healthcare quality, interoperability, efficiency, and outcomes, reduce medical errors, adverse events, and cost while increasing health care provider and patient satisfaction. CDS does have a variety of tools that healthcare providers use to assist their decision-making during care delivery.
While CDS serves many benefits to acute care hospitals some barriers have been noted to prevent effective use of the system. One main barrier that providers may encounter is ineffectively using the CDS to alert clinical providers of abnormalities that are presented during care delivery. This can also contribute to healthcare organizations losing out on reimbursement funding from CMS. According to Charles, Cannon, Hall, and Coustasse (2014), a cost-effective approach of CPOE systems can be shown in avoiding adverse drug events ranging from $7 to $16 million and $92,000 annually that is due to a reduction in tests performed. On the other hand, their use can ensure that patients receive appropriate, timely, and preventative care. In addition, they can aid in providing patients and providers with to deliver care at the right time, testing, medication, and treatment. Therefore this report seeks to further explore CDS standards development and management. Ash, McCormack, Sittig, Wright, McMullen, and Bates (2012) further support this review findings by asking if CDS assists in meeting meaningful use through standardized care practice that is supported by the evidence-based practice during care delivery and support CMS meaningful use for funding reimbursement to providers. Therefore, CDS usage can meet MU to increase patient safety, provide accurate communication amongst providers, and capture delivered services for billing.
The methodology for the evaluation or assessment of the benefits and barriers of using CDS to meet meaningful was grounded in the basic tenets of a systematic review as demonstrated in the literature. The study was conducted in three stages: (1) identifying the literature and collecting the data, (2) analyzing and evaluating the literature found, and (3) categorizing the literature.
Step1: Literature Identification and Collection
The literature identification and review of case studies were performed in September 2015. The Academic Search EBSCOE and Google Scholar electronic databases were searched for the terms “CPOE” “EHR” “CDSS” “CDS” “Standards” “Meaningful Use” “Implementation” and “CMS”. Accordingly, most citations and abstracts that were identified in the search process were also evaluated not only to identify the relevancy of the articles but also to check for the credibility and validity of contents.
Step 2: Literature Analysis
Literature was selected for review based on meaningful use, electronic health records with clinical decision system standards, Center for Medicare and Medicaid Services, and HITECH Act. Inclusion and exclusion criteria were as follows: Only articles published from 2010 to 2015 were utilized and the search was restricted to sources that could be obtained as full texts written in the English language. Furthermore, the researcher took the initiative to only include articles, reviews, and research studies published by reputable authors in the discipline of health information systems (HIS). Accordingly, the findings of the articles, studies, and reviews were identified and analyzed for inclusion in the present project. From a total of 10 references found, 10 citations were used for this study. The results were structured with subheadings that described the clinical decision supports meeting meaningful use.
Potential and Actual Cost-Benefit Effectiveness
Analyzing the Literature Review
Individual Critical Analysis
This literature review focuses on analyzing four articles on important variables that have impacted the use of clinical system software (CDSS) with the view to aiding in meeting meaningful use. The review examines how the variables and outcomes were defined and measured in the existing research. A matrix has been formed for the literature analysis collection and includes major headings, namely author, year, title, purpose, data collection methods, measurement tools, and results.
In this article which was part of a larger examination of computer physician order entry (CPOE), Charles, Cannon, Hall, and Coustasse (2014) looked at the benefits and barriers involved in the adoption of a CPOE as an effective solution for hospitals. In addition, the article looked at the benefits and barriers involved as well as the causes of medical errors. The authors’ demonstrated that CPOE adoption was beneficial in reducing medical errors and adverse drug events. Their methodology utilized a systematic review of a qualitative study which was conducted in three stages, namely (1) identifying the literature and data collection, (2) analyzing and evaluating the selected literature, and (3) categorizing the literature. Data collection was performed between 2013 and 2014. The case studies reviewed were narrowed down to 51 references and were carried out through electronic databases such as PubMed, Proquest, ScienceDirect, and Google Scholar. The article’s strength was demonstrated in the benefits of adopting a CPOE with a clinical decision support system as an effective software for hospitals to utilize in mitigating medical errors and adverse drug events with the view to optimizing healthcare savings in millions of dollars. The search strategies created limitations because they lacked an adequate volume of databases accessing. In addition, the review was performed at the time when CPOE adoption was fairly new limiting sufficient data.
In the second article Ash, McCormack, Sittig, Wright, McMullen, and Bates, (2012) performed a systematic review revolving around the hospitals that were improving care with the use of CPOE with clinical decision support (CDS). The analysis identified patterns and trends with descriptive statistics and a qualitative approach that relate to CDS. The data collection was gathered from thirty-four community hospitals that had at least five years of CPOE experience to review their CDS standard practices. The initially collected data was from 448 hospitals from Health Information Management System Society (HIMSS) 2005 analytics database on various hospitals. 176 hospitals respond agreeing to an interview survey. The survey was prolonged into 2010 to track CPOE infusion progress over time. The data sample size was forty-nine hospitals. The survey was performed with a qualitative semi-structured questionnaire interview in the form of fixed or open-ended questions. STATA was used to compare and differentiate hospitals’ responses of non-respondent about bed size, geography, and ownership. Descriptive statistics examined the fixed choice response. While a QSR NVivo qualitative data analysis software analyzed the interview transcripts. Since the last survey CPOE use increased from seventy-two percent to eight-three percent (Ash et al., 2012). Some reported not using the CDS to identify duplicate test orders. Additionally, some healthcare institutions reported that customizing the CDS would make it more effective in meeting meaningful use. The article’s strength was noted in the volume of data collected over a five-year period which contributed to the authors’ having adequate time for the CPOE infusion and progress. This supported the standard practices that hospitals implement to govern their CDS usage. A major limitation of the study revolved around the use of a small sample size since it did not conduct a nationwide survey on hospitals that use CPOE. This can warrant the move for a substantial level of needed CPOE customization in most institutions.
Levick, Stern, Meyerhoefer, Levick, and Pucklavage (2013) focused on clinical decision support (CDS) intervention development and use. The authors found that the innovation was important in healthcare contexts for providing CPOE alerts that identify medical errors for overuse diagnostic laboratory tests. When CPOE has installed CDS capabilities, it can assist in improving quality of care, minimizing repeat treatment interventions, and reducing medical errors. The systematic review used a qualitative observational study and was performed between 2008 and 2011. Multiple regression analysis examined a sample size of 41,306 in a Pennsylvania hospital on patients admitted with orders for laboratory samples of B-Type Natriuretic Peptide (BNP). The CDS was customized to carry out searches on pending orders for BNP during their stay. The CDS would alert clinicians on prior BNP recent results to avoid testing duplications. This significantly reduced the amount of unnecessary testing during admission visits, hence saving costs. The strength of the study was in the large sample size that was used to demonstrate the CDS effectively by applying multiple variables to the studies. The limitation was noted in the study’s inability to demonstrate how independent CPOE factors resulted in the BNP testing results to support yearly cost savings.
Castaneda, Nalley, Mannion, Bhattacharyya, Blake, Pecora, and Suh (2015) explained that information silos exist because of the absence of a universally accepted management system, departments, and institutions. This continues to create difficulties for patients and providers to access valuable medical data. Creating structured annotation forms to support common data elements can enable capturing and sharing of laboratories and clinics’ real-time data. The systematic review employed a qualitative approach and a case study research design to review the impact of EHRs on primary health care in the 21st century. It was found that the electronic systems provided both structural and process benefits to healthcare institutions, providers, and patients, though there was a noted lack of data on enhanced patient outcomes. A comprehensive EHR comes equipped with CDS features. An EHR that lacks this capability will continue to place patient data in silo databases. The report looks at different variables that impact the use of CDS in benefits and barriers that may improve patient diagnosis and care delivery. Its strength is grounded in demonstrating how large data in EHRs can be integrated and secured via CDSS to improve clinical outcomes. The limitation of the study lies in the lack of standardized methods to support data collection and the absence of details on CDS interoperability connection to meet meaningful use.
Synthesis Discussion of Evidence
Management of CDS
For health care providers meaningful use is the focus of meeting the patient’s needs. As reported in the study carried out by the Institute of Medicine titled “Crossing the Quality Chasm: A New System for the 21st Century” (IOM, 2001). This further supports delivering care that is safe, efficient, effective, timely, patient-centered, and equitable. The American Recovery and Reinvestment Act (ARRA) of 2009 economic stimulus package along with the Health Information Technology for Economic and Clinical Health (HITECH) Act targets to structure a paperless national health information network. Providers who meet meaningful use through appropriate documentation in EHR, such as patients’ smoking status and current medications can unlock a significant amount of healthcare dollars as part of their reimbursements. Stage 2 encourages providers to improve the process, whereas stage 3 will cause improvement in outcomes (Classen & Bates, 2011). There are three stages of meaningful use in primary care settings, namely Stage 1: data sharing and transferring to EHRs; stage 2: providing patients’ online access to their health data and providers exchanging electronic health information; and stage 3: implementation. In 2014 stage 2 of meaningful use built on the existing meaningful use of stage 1. This allows the focus on the use of clinical decision supports that will improve health conditions outcomes. These standards allow patients to have online access to their health information as well as for their providers to share and exchange electronic health information.
Available literature demonstrates that clinical decision support (CDS) systems form an important component of clinical information systems which are designed to assist health care professionals in clinical decision making during the process of care (Charles et al., 2014). While most of these systems can be delivered in healthcare settings in a multiplicity of media, including paper-based interventions, the term CDS is mostly employed to denote computer-based interventions that are in large part delivered through available clinical information systems. Common types of CDS, according to Wright, Sittig, Ash, Sharma, Pang, and Middleton (2009), include “drug-interaction checking, preventive care reminders, and adverse drug event detection” (p. 637). According to these authors, “there is substantial evidence to suggest that clinical decision support systems, when well designed and effectively used, can be powerful tools for improving the quality of patient care and preventing errors and omissions” (p. 637). Such systems can contribute to substantial cost savings in the care industry, in large part due to reducing medical errors and minimizing the duplication of tests and other medical procedures (Charles et al., 2014).
Measurement and Management
Computerized physician order entry (CPOE) with clinical decision support (CDS) has been proven beneficial towards enhancing healthcare quality and efficiency. Ash et al., (2012) reported that eleven percent of the 5795 US hospitals had either basic or comprehensive electronic records. Most were larger, urban academic hospitals that were capable of mandating providers’ use.
Of the eighty-six percent of a community hospitals in the United States (US), only 6.9 percent of them had a basic clinical information system (Ash et al., 2012). Providers must make effective use of CPOE to meet meaningful use of clinical decision systems. The CDS system is managed by the hospital or vendor IT group with assistance from clinicians. A metric is used to measure the CDS performance by the ways of alert tracking the amounts of overrides rates by physicians, individual order sets effectiveness, and the number of alert filings.
CMS uses quality measures to benchmark health care processes from CPOE, which in turn is complemented with CDS to capture structured patient data. McCullough, Casey, Moscovice, and Prasad (2010) explained that CDS provides real-time, patient-specific recommendations that are collected from routine clinical point-of-care documentation and patient stated preferences and unique characteristics such as learning preferences and care plan barriers.
For quality measures to be Meaningful they ought to be done promptly, have understanding, and transmit feedback to providers to help improve clinical outcomes, contribute to community health, and have a positive effect on indicators of the patient experience while interacting with the health care system.
A major inadequacy of CDSSs is that most of the existing clinical information systems in healthcare settings are unable to accommodate decision support. This is even though “the most effective decision support systems are integrated with clinical information systems, such as inpatient and outpatient electronic health records (EHRs) and computerized provider order entry (CPOE) systems” (Wright et al., 2009). Other inadequacies include high initial cost for implementation, adoption challenges, as well as lack of universally accepted standards for use and interpretation (Agrawal, 2009).
CDSS Need for Precision Medicine
Available literature shows that “a critical step for achieving precision medicine will be to integrate old and new data into validated information and to convert this information into knowledge directly applicable to diagnosis, prognosis, or treatment” (Castaneda et al., 2015, p. 331). This, according to these authors, “will entail developing an integrated knowledge environment that continually captures information, grows, accumulates, organizes, and institutionalizes new information, making it accessible to health care providers” (Castaneda et al., 2015, p. 331). The need for precision medicine is therefore more profound, as healthcare providers increasingly share the knowledge accumulated from scientific research and clinical data contained in CDSSs to reduce medical errors and improve treatment outcomes for patients.
Meaningful Use Stages and CDSS
The three stages of meaningful use include data capture and sharing, advanced clinical processes, and improved outcomes. In terms of CDSS, stage one of meaningful use focus on electronically capturing health information in a standardized format, using the information to track key clinical conditions, communicating that information for care coordination processes, initiating the reporting of clinical quality measures and public health information communicating that information for care coordination processes, and using the information to engage patients and their families in their care (Jones, Stewart, Darer, & Sittig, 2013).
Stage two of meaningful use focuses on more rigorous health information exchange (HIE), enhanced requirements for e-prescribing and incorporating laboratory results, electronic transmission of patient care summaries across multiple settings, and more patient-controlled data (Jones et al., 2013). Finally, in terms of CDSS, stage three of meaningful use focuses on enhancing the quality and efficiency of healthcare to achieve improved health outcomes, providing decision support for national high-priority conditions, availing patient access to self-management tools, guaranteeing access to comprehensive patient data through patient-centered HIE, and improving population health (Jones et al., 2013).
Table 1 Examples of stage 2 measures (Source)
|Meaningful Use Objective||Measure|
|“Use CPOE for medication, radiology, and laboratory orders.”||“More than 60% of medication, 30% of laboratory, and 30% of radiology orders during the EHR reporting period are recorded using CPOE.”|
|“Use clinically relevant information to identify patients who should receive reminders for preventive/follow-up care and send these patients the reminder, per patient preference.”||“More than 10% of all unique patients who have had two or more office visits within the 24 months before the beginning of the EHR reporting period were sent a reminder, per patient preference when available.”|
|“Generate lists of patients by specific conditions to use for quality improvement, reduction of disparities, research, or outreach”.||“Generate at least one report listing patients with a specific condition.”|
|“Automatically track medications from order to administration using assistive technologies in conjunction with an electronic medication administration record (eMAR).”||“More than 10% of medication orders during the EHR reporting period are tracked using eMAR.”|
|“Record smoking status for patients age 13 years or older.”||“More than 80% of all unique patients age 13 years or older have smoking status recorded as structured data.”|
CPOE and CDSS Adoption
The adoption of CPOE and CDSS in American healthcare institutions has been slow as available literature demonstrates that it is only a few educational-oriented, large medical centers that have fully implemented the systems (Wright et al., 2009). The slow adoption of the systems can be attributed to a multiplicity of factors which include funding deficits for development and implementation, challenges in coding information into an executable format, slow awareness levels, as well as socio-cultural and technological barriers. Other challenges to adoption include the complexity of clinical workflows and demands on staff time, limitations in deployment and scope, difficulty in incorporating the extensive quality of clinical research being published on an ongoing basis, and lack of consistency in evaluation (Wilcox & Whitman, 2003).
Benefits and Barriers
CDS has numerous benefits. Available literature demonstrates that “when CDS is applied effectively, it increases the quality of care, enhances health outcomes, helps to avoid errors and adverse events, improves efficiency, reduces costs, and boosts provider and patient satisfaction” (Curtain & Peterson, 2014, p. 344). This view is consistent with that of Levick et al (2013), who argue that CPOE with CDS frameworks can provide medical alerts, identify medical errors for overuse diagnostic laboratory tests, save costs, avoid test duplications, reduce unnecessary tests during admissions, as well as improve quality of care. Among the barriers, it is evident that there are known integration challenges between CDSS and other clinical information systems such as EHRs and CPOE (Wright et al., 2009). Other barriers include lack of common understanding of the CDS system’s overall objectives, failure to align the information system with its strategies, difficulties gaining physician acceptance and utilization of CDS interventions, obstacles to integrating CDS interventions into the workflow, and difficulties in translating written guidelines into computer-executable code (Eichner & Das, 2010).
Medical Error Prevention
Available literature demonstrates that “systems that use information technology (IT) such as computerized physician order entry, automated dispensing, barcode medication administration, electronic medical reconciliation, and personal health records are vital components of strategies to prevent medication errors, and a growing body of evidence calls for their widespread implementation” (Agrawal, 2009, p. 681). CDS has been known to substantially reduce medication errors due to the computerization component. Such a reduction in medical errors has been positively correlated with a substantial reduction in preventable adverse drug effects (Wilcox & Whitman, 2003). Health institutions that effectively implemented CDS, CPOE and EHRs are associated with fewer patient complications, lower mortality rates, as well as lower costs.
CDS encompasses a multiplicity of tools including, but not limited to 1) computerized alerts and reminders for providers and patients, 2) clinical guidelines, 3) condition-specific order sets, 4) focused patient data reports and summaries, 5) documentation templates, 6) diagnostic support and 7) contextually relevant reference information (Ash et al., 2015). These functionalities may be deployed on a multiplicity of platforms such as mobile, cloud-based, or installed; however, it is important to underscore that they are not intended to replace clinician judgment but rather to assist care professionals in making timely, informed, and higher quality decisions.
Available literature demonstrates that “irrespective of the kind of decision-support task, CDSSs should be smoothly integrated within the clinical information system, interacting with other components, in particular with electronic health record (EHR)” (Marcos, Maldonado, Martinez-Salvador, Bosca, & Robles, 2013, p. 676). These authors underscore the need for developers and implementers to come up with integrated frameworks as most of the available CDSSs lack interoperability attributes despite decades of developments. It is documented that “interoperable Health Information Technologies (HIT) can connect to, exchange, and use patient data in ways that will improve clinical, safety, efficiency, cost, and population health outcomes” (Fetter, 2009, p. 524). Systems need to be closely integrated and shareable across healthcare delivery systems and settings over large geographic areas with the view to not only enhancing cost savings but also improving quality of care.
Cost savings for CDS are achieved in terms of improved efficiency, reduction of medical errors, improvement in care outcomes, as well as enabling the capturing and sharing of laboratories and clinics’ real-time data (Castaneda et al., 2015; Dalaba et al., 2015). Available literature demonstrates that CDS “represents a promising approach to not only improve care but to reduce costs in the inpatient setting” (Fillmore, Bray, & Kawamoto, 2013, p. 1). However, according to these authors, there are concerns about the lack of sufficient, rigorous data related to the cost benefits of clinical information systems such as CDS and CPOE in the inpatient setting.
New Understanding Generated by the Evidence
Drawing from the ongoing, it is evident that the adoption of CPOE with CDS has immense benefits for healthcare institutions as well as patients. Critical CDS features that have been incorporated into CPOE systems have been credited for reducing medical errors and subsequent adverse drug events. Such systems can contribute to substantial cost savings in the care industry, in large part due to reducing medical errors and minimizing the duplication of tests and other medical procedures (Charles et al., 2014). This view is consistent with that of Levick et al (2013), who argue that CPOE with CDS frameworks can provide medical alerts, identify medical errors for overuse diagnostic laboratory tests, save costs, avoid test duplications, reduce unnecessary tests during admissions, improve quality of care, as well as capture and share laboratories’ and clinic’s real-time data.
Although strong evidence supports the employment of CDS and CPOE, available literature demonstrates that “insufficient reporting of implementation and context of use makes it impossible to determine why some health IT implementations are successful and others are not” (Jones, Rudin, Perry, & Shekelle, 2014, p. 48). Many of the limitations of CDS are noted during the implementation phase. These limitations include (1) the substantial resources required to develop, curate, and maintain large knowledge bases for CDS content, (2) a lack of technical standards and approaches that facilitate effective sharing of clinical CDS content, (3) the difficulty of integrating clinical decision support into clinical workflow effectively and unobtrusively while avoiding alert fatigue, (4) clinician fears of “cookbook” medicine, (5) a lack of a clear business case for use of CDS, and (6) a relatively small number of hospitals that have CPOE and EHR (Wright et al., 2009).
In conclusion, a part of adopting CPOE is that it will be able to assist the organization meets meaningful use. Stakeholders must look at the benefits and barriers involved for hospitals to adopt CPOE. The main reported barrier was that of provider alert trigger fatigue. CPOE that are complemented with CDSS were noted as beneficial in reducing medical errors and adverse drug events while at the same time enhancing efficiency and workflow processes. In addition, the use of CDSS can optimize healthcare savings by millions of dollars. As part of the standards and quality improvements process for any hospital that uses CDSS, a continual review of standard practice and policies will help in delivering efficient, safe, quality health care. This approach will assist in customizing the CDS to make it more effective in meeting meaningful use. CDS systems are useful in alerting clinicians of prior test results to avoid testing duplications. This not only significantly reduces the amount of unnecessary testing during admission visits, but also leads to cost savings.
Whenever an information silo is present within healthcare patients and providers often encounter inaccessible to needed medical records which are related to the absence of management systems, departments, and institutions. Creating structured explanation forms can assist in supporting common data elements that can enable the capturing and sharing of laboratories’ and clinics’ real-time data. Overall, a comprehensive EHR that is equipped with CDS features will deter patients’ data from being placed in silo databases. For CPOE to meet the meaningful use, patient data should be in EHRs that allow integration and security via CDSS to improve clinical outcomes. According to Silow-Carroll, Edwards, and Roding (2012), the core feature of an EHR involves patients’ information collection and updating that is not consistently provided or documented in all hospitals, such as a complete medication and allergy, smoking status, and preferred language demographic data.
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