"Health Information System Evaluation Models" is a great example of a paper on the health system. Important elements in the evaluation of health programs can be extended to health information technology evaluation in a bid to produce robust and useful outcomes. As a matter of fact, many researchers are of the opinion that integration of the framework of public health evaluation to existing best practices in health IT evaluation has the potential to yield a more robust set of evaluation methods than each on its own. In general, evaluation can be more useful if standard outcome measures are applied, despite the challenges that the implementation of such standards face.
The need for careful selection of health information system evaluation models is therefore as important as the process of evaluation itself. Nonetheless, the chosen model should incorporate practical issues in public health, including the quality of data, cost elements, and transferability of the technology. This paper looks into appropriate models that can be used in the evaluation of a scenario where the Chief Medical Officer at a hospital is interested in finding out the impact of a new decision support system on the number of adverse events occurring in the past year. Health system evaluation models More often than not, evaluation, or systematic investigation of merit, worth, or significance of a study object is overlooked, more especially in instances where complicated intervention such as the implementation of health information systems.
Nonetheless, there is a lot to be learned in the performance of evaluations and analysis of findings, results of which can be used in improving existing systems, in addition to informing the implementation of future findings.
Several possible models are considered, that is, IS Success model, IT Organization fit model, and CDC’ s Public Health Evaluation Model. Nonetheless, despite considering three models, only two are proposed for possible implementation. IS Success Model This model takes into consideration six success categories/dimensions with causal and temporal links. This is in line with the fact that success is considered a dynamic rather than a static condition. Various studies have assessed multi-dimensional relationships among IS success measures and explicitly pointed out that the six system dimensions include system Quality, information quality, service quality, information use, user satisfaction, and the net benefits of the system (Willcocks, 2007).
IS model illustrates clear, specific dimensions of IS success/effectiveness and the relationships between them. Nonetheless, the model does not include organizational factors pertinent to IS evaluation. Additionally, researchers have discovered that various measures such as, user involvement in system development and organizational culture fail to match the framework’ s dimension. Consequently, the extension of the framework is recommended in order to add the proposed dimensions as well as clinical measures in relation to the healthcare domain.
The model is illustrated below, Figure 1: IS Success Model (Friedman & Wyatt, 2004). IT Organization Fit model Management in the 90s is a renowned IT Organization Fit Model. It includes internal and external fit elements (Friedman & Wyatt, 2004). This is illustrated in the diagram below which illustrates the concept of fit between the major organization elements. Figure 2: IT Organization fit (Friedman & Wyatt, 2004). Internal fit is achieved through a dynamic equilibrium of organizational elements such as business strategy, organization structure, management processes, as well as roles and skills. External fit on the other and is achieved through the formulation of an organizational strategy on basis of environmental trends and changes including market, industry, and technology with the internal and external fit considered as the enablers.
As a matter of fact, information technology is expected to impact on the management process, and hence impact on the management process, and hence to an extent, the strategy. Nonetheless, according to the model, the successful realization of IT benefits involves three prerequisites. For starters, organizational vision and the purposes behind it need to be clear to members of the organization members in order to prepare them for organizational changes and reduce challenges in transformation management (Anderson & Aydin, 2005).
Secondly, the organization’ s corporate strategy, information technology, and organizational dimensions need alignment to each other. Thirdly, a robust IT infrastructure like an electronic network and well-understood standards need to be equipped within the respective organization. The three prerequisites alongside internal and external fit are usable in the identification of IT implementation problems. The model, being new, has however not been widely implemented healthcare. However, it has been identified as being capable of identifying main organizational elements that affect IS and emphasize essential alignment or fit between the elements.
Furthermore, the model is comprehensive due to its inclusion of multiple factors such as technology, human roles, and skills as well as organization strategy/structure and management process. The factors can further be grouped into specific evaluation dimensions. For instance, IT can be grouped into system and information quality. In the same manner, roles and skills can be linked to use and user satisfaction. CDC’ s Public Health Evaluation Model The reason this model is preferred in the evaluation of the scenario provided is that it takes into consideration real data which will be related to the number of adverse events and how the decision support system was used in dealing with the same (Kaplan, 2009).
Additionally, it looks into the outcomes of the decisions, and hence holistically covers the scenario presented. This model is presented in the figure below, Evidently, other than a critical look at the scenario present, the steps involved in the model ensures the system and its environment are adequately analyzed.
Its cyclic nature also allows for continuous evaluation of the system. It allows for a description of the system, including its implementation goals. Due to the fact that the system is not implemented in a vacuum, the description definitely covers organizational factors such as system use, expectations, clinical and administrative workflows it affects, expected downstream and reporting variations, as well as required resources. Additionally, the model looks into the system’ s degree of sophistication and implementation stages. An alternative model proposed for this evaluation is IS-Success earlier discussed.
Like the CDC model, its success can be targeted at the systems’ successful handling of the adverse events encountered during the evaluation period. Such an evaluation will ignore capacity issues but rather focus on the events recorded only and their corresponding successes.
Anderson, J., & Aydin, C. (2005). Evaluating the organizational impact of healthcare information systems. New York: Springer.
Friedman, C. P., & Wyatt, J. C. (2004). Evaluation methods in biomedical informatics. New York: Springer.
Kaplan, B. (2009). Evaluating informatics applications-some alternative approaches: theory, social interactionism, and call for methodological pluralism, Int. J. Med. Inf., 64 (1), pp. 39–56.
Willcocks, L. (2007). Managing technology evaluation—techniques and processes. Oxford, pp. 365–381.