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DXplain Project Implementation and Evaluation Essay

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Updated: Jul 6th, 2020


Healthcare practitioners make decisions that uphold patient safety and quality services to attain desirable results in clinical practice. The integration of decision support systems (DSS) in the healthcare sector has facilitated efficient operations that have led to improved patient care due to the streamlined decision-making processes. However, clinicians face challenges in making decisions regarding clinical manifestations of certain diseases. For this reason, the deployment of DXplain has helped health professionals in making decisions. Therefore, the successful implementation of the DSS relies on the approach, goals, and the plan that guides the process. In this regard, an evaluation of the implementation process based on the outcomes is essential for determining its success or failure in assisting health professionals in decision-making.


In the healthcare sector, decision-making is essential for the delivery of quality services to the patients. In essence, healthcare practitioners ought to considerdecision-making as a crucial aspect of their professional endeavors. The development of decision support systems (DSS) has revolutionized the decision-making processes in the healthcare organizations through the integration of technological advancements (Hernández et al., 2013). In this paper, the identified DSS system is DXplain, which is characterized by computerized components that enhance the explanation of clinical manifestations of a broad range of diseases. Practical implementation of DXplain in a particular healthcare organization is essential for streamlining decision-making processes to attain high standard care and patient satisfaction. Thus, the development of an implementation plan should focus on the realization of specific goals that would guide the evaluation of the DSS (Dennis, Wixom, & Roth, 2012).

The healthcare institution’s management should create an environment that favors the implementation and evaluation of DXplain for the sake of fostering active decision-making. This paper will develop a DXplain implementation approach that focuses on the attainment of individual goals through a defined implementation plan. Additionally, an evaluation of the approach, goals, and the plan for DSS implementation would be carried out to gauge its success in improving decision-making processes in healthcare organizations.

The Implementation Approach

The implementation approach provides a strategy that ensures effective integration of the DSS in the healthcare environment to facilitate the decision-making processes. Therefore, the identification of the problem, the steps, criteria for accessing the DSS, and the involvement of the management and users is essential for streamlining the implementation approach (Fathauer & Meek, 2012).

Problem solved by DXplain

The essence of a DSS system in the nursing and healthcare fraternity is directed towards the generation of solutions to various problems that practitioners face in their line of duty. In particular, the implementation of DXplain seeks to solve the problem of diagnostic inefficiencies that healthcare professionals face. Additionally, the employment of the DSS purposes to curtail diagnosis errors by fostering active differential diagnosis endeavors that would augment the appropriate treatment for the actual diseases causing patients’ poor health status. The DXplain features can describe and provide comprehensive references to over 2400 disorders. Furthermore, the problem that requires remedy would be fostered through the DSS’ ability to conduct a differential diagnosis of at least 5000 clinical findings.

The Description of the DSS – key steps and criteria for selecting the vendor and software

DXplain is a DSS system that assists clinicians or nurses in discerning clinical manifestations of various diseases. The medical reference system that is coupled with an electronic medical textbook improves the decision-making course to attain accuracy in the diagnosis and treatment aspects of healthcare provision. The system can describe at least 2400 diseases whereby the signs and symptoms are considered together with the etiology, prognosis, and pathology. The reference feature of the DSS ranks the accepted clinical findings by providing a diagnosis list that clarifies the clinical manifestations.

Deciding whether to build or buy a DSS project can be challenging. However, the vendors of the DXplain software, viz. the Laboratory of Computer Science of the Department of Medicine at Massachusetts General Hospital (MGH), provide clear procedures for accessing the software.Thus, obtaining the buy project would follow the purchasing processes laid down by the vendor.

The initial step for accessing DXplain requires subscription to their Annual License Agreement whereby a License Fee Request Form is submitted after a description of the organization. Afterward, the MGH would provide a free Institutional Evaluation License after signing the agreements and forwarding to the vendor’s address together with the payment. MGH would then provide directions for accessing the DSS after receiving the requirements.

The criterion for selecting DXplain is founded on its components that suit the remedy for the diagnosis problem in patient care. Further, the positive results recorded from the DSS’ application in various health organizations spanning over 25 years justify the choice owing to its previous successes (Massachusetts General HospitalLaboratory of Computer Science, 2015).

Users and management involvement

The implementation approach

The users and management need to know the decisions that the DXplain DSS has to support. Hence, the participation of the management and clinicians should consider whether the identified decision that requires support would improve patient care. Thus, their involvement in the implementation approach assists in the prioritization of the decisions that need computerized support (Fathauer & Meek, 2012).

The clinicians applying the DSS would be involved in identifying the critical areas in the diagnosis aspects that trigger problematic situations in practice. Besides, the management would facilitate the development of a well-defined strategy that is essential for the implementation and support of the introduced technology. The management should also be involved in the provision of support and education to the health professional for its successful implementation. Additionally, the management needs to let the users know when to apply the DSS and accept the resultant clinical judgment (Hernández et al., 2013)

Goal development and implementation

Active involvement of both the management and clinicians in goal development is crucial for the stakeholders’ ownership of the implementation process. Therefore, the end-users and management would develop the goals based on the DSS’ ability to provide the relevant information required to make accurate diagnosis judgments. Besides, the involvement of the parties would facilitate the development of goals that heighten the competency of the healthcare practitioners (Fathauer & Meek, 2012).

Implementation and evaluation planning

The role of the management and the clinical practitioners is highly regarded as essential for the formulation of plans that envision the realization of the predetermined goals. In this regard, Unit Managers, Director of Quality, and the Director of Information Technology in a particular organization would cooperate with nursing staff from every department in the organization to develop a plan that would guide the DSS implementation (Rahimi & Vimarlund, 2007). Thus, the incorporation of a care plan module that focuses on the diagnostic aspects of care would consider the resources required and potential challenges that would inhibit the implementation of DXplain system in the healthcare institutions.

The approach for evaluating the implementation of the DSS should focus on the success or failure of the DSS to meet its decision-making functions. Therefore, the managers would gauge the extent to which the DXplain facilitated quality service provision through streamlined decision-making processes. Further, the clinician would assess the essence of the DSS concerning its usefulness in enabling them make calculated diagnosis judgments besides using the DSS (Rahimi & Vimarlund, 2007).

Securing management and user “buy-in”

Obtaining the support for the implementation of the DSS from the management and clinical practitioners requires the application of strategic approaches. The management’s support would be acquired by underscoring the essence of the decision-making approach that encourages a bottom-up approach. Further, informing the management about the performance and quality improvement benefits of the DSS would be strategic in obtaining their support.

The health professional’s buy-in would be fostered through educational programs that would facilitate easy navigation of the application. Besides, communicating the benefits of the DSS to the clinicians’ decision-making endeavors securing their support for the technology is crucial. Clarifying that the DSS would not replace but complement the clinicians’ decision-making roles would also safeguard the clinicians’ buy-in.

Implementation goals

The implementation goals would focus on the important aspects of the DSS, its integration with healthcare databases, and the management elements of DXplain. Therefore, the attainment of the health institutions’ goals pertaining improved decision-making endeavors in disease diagnosis would concentrate on the effectiveness of the components, its connectivity with other systems, and ease of managing the DSS in the healthcare environment.

Key characteristics and capabilities of DXplain

As mentioned earlier, DXPlain is composed of two main elements that support the interpretation of clinical findings to assist health professional in the diagnosis of various diseases by eliminating potential errors. One of the two components is the electronic medical textbook that provides the clinicians with over 2400 different health complications.

The medical reference system is similar to a case analysis model that interprets identified signs, symptoms, and laboratory data to provide an ordered list of the diagnoses that explain the clinical findings. DXplain can justify the consideration for each of the diseases, and thus its ability to reduce adverse patient outcomes would constitute one of the implementation goals. Additionally, the functionality of DXplain facilitates the suggestion of further collection of data that would be useful for differential diagnosis. Thus, the implementation goals would consider the extent to which clinicians apply differentiation techniques for diseases with similar clinical exhibitions (Fathauer & Meek, 2012).

The connectivity and integration of DXplain to databases and other systems

The compatibility of DXplain with other medical databases and healthcare systems foster its utility in facilitating streamlined operations that favor the improvement of patient care services. DXplain can be connected with the electronic medical records (EMR) systems to promote effective diagnosis and treatment. The integrated system would rank the diseases according to the history and clinical findings provided to foster accuracy in the diagnosis and treatment of the identified disorder.

The connectivity of DXplain with knowledge management resources through the Internet also proves its significance in the nursing practice. Specifically, the electronic medical textbook component of the DSS could be fortified with the updated references for clinical findings thereby supporting the diagnosis and treatment processes. Additionally, the ease of leveraging the DXplain’s knowledge base for projects like patient simulation exercises boosts the learning processes regarding the diagnosis of different medical conditions.

Data management

Managing the information cycle aspect of DXplain is necessary for attaining consistent results throughout the diagnosis endeavors. Particularly, the data management approach would consider data extraction from the patients (Varonen, Kortteisto, & Kaila, 2008). Besides, a regular update of the DXplain knowledge base is essential for the diagnosis of different diseases.

Model management

The model management approach should provide nurses and other healthcare experts with clear information regarding their responsibility when handling the DXplain technology. The model management approach would emphasize an interdisciplinary strategy that seeks to assist in the fortification and review of the DSS performance. Therefore, regular checking of the tool should be prioritized to enhance the point of care services through the integration of web-based search tools (Turban et al., 2011).

User Interface

Since the DSS is compatible with the standard operating systems like Windows and iOS, the interface would require customization to suit the clinicians’ needs when carrying out the diagnosis undertakings. Hereafter, the organization would engage in thecontinuous management of the DSS to develop the user-friendliness feature of the software.

Knowledge management

The management of the DXplain’s knowledge base requires a trusted and sound reference database. Importantly, the management of the technology’s knowledge management would focus on the accurate ranking of the diseases according to the data provided for analysis. In this respect, the system would adopt an embedded evidence-based knowledge that improves clinical workflows (Turban et al., 2011).

Implementation plan

Performing a critical review of the success of DXplain in another healthcare organization is strategic for devising a functional implementation plan. The ability of the DSS to reinforce the health data and information obtained from patients should guide the implementation plan (Hernández et al., 2013). Furthermore, the management of the results retrieved from both the electronic textbook and the reference system requires attention for the implementation plan to gauge the users’ useful application of the results in their decision-making roles.

Studying the standing processes and redesigning of the DXplain implementation strategies requires the formulation of a team that would steer the implementation plan. The executive and project sponsors together with the team members would formulate a steering committee that would spearhead discussions on how the DSS would meet their needs. Therefore, developing an understanding of the end-users needs would be strategic towards securing the clinicians’ buy-in. The redesign would focus on the existing system knowledge, documentation of the essential improvements, and formulating the requirements of the new system.

Factors for successful implementation

Technological challenges could pose a threat to the successful implementation of DXplain due to the technicalities required in navigating the system. Thus, the management team shouldtrainend users to familiarize them with the operational maneuvers of the DSS. The behavior of the clinicians might portray some resistance due to the introduction of the new technology. Combating the resistance requires the implementation team to involve the clinicians to enhance their comfort in using the system and to own the implementation process (Hernández et al., 2013).

The use of collaboration, communication, and group support DSS

The implementation of a DSS project requires effective communication strategies that direct the stakeholders’ efforts towards the realization of the set goals. Therefore, the formulation of departmental nursing teams to attain the interoperability benefits based on collaborative efforts is strategic for the enhancing the communication when implementing the DSS. Thus, group-based DSS would help in the identification of the potential inhibitors that would undermine the integration of the DSS in the healthcare setting (Kawamoto, Houlihan, Balas, & Lobach, 2005)

DXplain Evaluation


After the implementation of DXplain in the healthcare institution, carrying out an assessment is paramount to detect the success of the system. The evaluation of the approach would focus on issues like reliability, cost, functionality, and vendor credential would be vital. The evaluation should be based on whether the system could solve the diagnosis problem at hand (Dennis et al., 2012).

Goals and outcomes

The successful realization of the goals should be based on the improvement of the diagnostic solutions that DXplain seeks to facilitate and the integration of the system in the nursing processes. Attaining patient security and desirable outcomes is also an aspect that requires evaluation. Overall, the system should foster the improvement of the patient standard of care and alter the organizational structurepositively (Kawamoto et al., 2005).


Evaluation planning would commence after the accessibility and implementation phases of the DSS project. The planning assessment should focus on the functionality of the DSS and the degree to which it meets the organizational expectations. Thus, the plan evaluation would consider the integration effectiveness, support requirements, and task accomplishment. Continued evaluation should be done to ensure the DSS meets the needs of the stakeholders thereby depicting its effectiveness in goal attainment (Dennis et al., 2012).


The integration of DSS systems in the healthcare sector has improved the decision-making processes significantly. This move has improved the quality of patient care and outcomes. DXplain has depicted considerable results over the years of its application in the diagnosis of diseases. The successful implementation of such a DSS is usually based on the implementation goals and plan that focuses on the improvement of clinical processes. In this regard, carrying out an implementation plan that is in line with the predetermined goals implies that the evaluation aspects of the projects would record positive outcomes.


Dennis, A., Wixom, H., & Roth, M. (2012). Systems analysis & design. Hoboken, NJ: John Wiley & Sons.

Fathauer, L., & Meek J. (2012). Initial implementation and evaluation of a Hepatitis C treatment clinical decision support system (CDSS): a nurse practitioner-driven quality improvement initiative. Applied Clinical Informatics,3(3), 337-348.

Hernández,E., Liu, S., Delibasić, B., Zaraté, P., Dargam, F., & Ribeiro, R. (2013). Decision Support Systems II – Recent Developments Applied to DSS Network Environments. Berlin, Heidelberg: Springer.

Kawamoto, K., Houlihan, A., Balas, A., & Lobach, F. (2005). Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ, 330(7494), 765.

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Rahimi, B., & Vimarlund, V. (2007). Methods to evaluate health information systems in healthcare settings: a literature review. Journal of medical systems, 31(5), 397-432.

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Varonen, H., Kortteisto, T., & Kaila, M. (2008). What may help or hinder the implementation of computerized decision support systems (CDSSs): a focus group study with physicians. Family Practice, 25(3), 162-167.

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