Clinical Health Services Management

Introduction

In the process of providing healthcare services in a clinical setting, decision-making is a vital process, which guides the approaches to clinical decision-making towards the delivery of the required services to a patient. Decision-making involves many disciplines and resources, which include the practitioners’ knowledge and skills, the availability of decision support systems such diagnostic tools, the support, and the input of other practitioners among other factors that contribute in one way or another towards the final decision concerning the best approaches suit the patient (Seidman et al., 2010).

However, the current decision-support systems have majorly focused on the measurement of severity of symptoms in a patient while ignoring the measurements on short-term changes in patients’ health concerning the conditions they face. Further, these diagnostic or decision-support systems vary in terms of cost-effectiveness, accessibility, and reliability. This paper offers a general framework for clinical and management decision support that will steer the health sector towards the provision of excellent services using quality delivery systems. The paper considers financing, quality improvement, and human resource considerations crucial areas that must be addressed to achieve an exceptional standard for delivery services.

Financing

Any health facility requires financial support for it to run smoothly. However, when implementing decision-support systems, financial resources pose the greatest challenges for any health care facility. Such systems are not only expensive in terms of the required initial financial resources but also in terms of the needed intellectual investment (Seidman et al., 2010). Therefore, a good implementation of decision-support systems considers various factors such as the expertise, clinical trends, and operational activities in a facility to ensure maximum utilization of the available financial resources that are dedicated to the provision of quality care.

To guarantee adequate financing towards decision support systems, there is a need to ensure that the available financial resources are dedicated to the implementation of the most needed decision-support systems for a given population (Lobach et al., 2012). This goal can be achieved through research and studies that identify the immediate and relevant needs of a particular population. Further, through research and development, the health care sector can guide the process of implementing decision-support systems that are relevant to the current health needs.

The financing of decision-support systems also requires a consideration of the expertise that can be adapted to utilize such systems fully in a health care facility. Without adequate and appropriate skills, decision-support systems are likely to fail in their mandate of providing accurate and pertinent decision backup to inform practice and service delivery (Seidman et al., 2010). Consequently, it is crucial for financial resources to target the training of practitioners to ensure that they can use such systems for decision-making purposes. Such an approach will not only lead to better health care outcomes for patients but also an adequate utilization of the available monetary possessions that have been dedicated to implementing decision-support systems in the health care setting.

Quality Improvement

The primary aim of any decision support system in a clinical or health care setting is the quality improvement of health care delivery and patient outcomes. Hence, ensuring that the practitioners have the relevant information concerning a patient and his or her healthcare diagnostics needs increases the chances of receiving the right health care and hence better health results (Lobach et al., 2012). However, it is central to note that the implementation of decision support systems must adhere to the set quality standards as guided by the relevant authorities and individual health care facilities. One of the exemplary ways through which decision-support systems can be used to support quality improvement is through the availability of the right information for each medical situation that arises during a practitioner-patient interaction. In this case, decision support systems allow medical practitioners to not only access the right information but also ensure that such information is delivered promptly to guarantee faster healthcare delivery and better outcomes.

Another central aspect through which decision support systems improve the quality of health care is through the increased safety that such systems help to establish in a health care setting (Lobach et al., 2012). The availability of critical information to help practitioners in delivering the best health care services is evident, especially through the availability of relevant information concerning each patient. This situation allows the avoidance of dangerous outcomes such as medicine-related reactions, as well as misdiagnosis.

The sharing of information with other practitioners is a very crucial way through which health providers can work together towards improving care services. In this case, a high-quality decision-support system must provide a platform through which health care practitioners can easily contact each other and share information to inform decision-making concerning any issue that may arise in day-to-day practice. Further, such health care decision-support systems should provide an elaborate data and information source that can allow the retrieval of such information wherever it is needed in a health care setting to manage the arising situations that practitioners face.

Lastly, it is crucial to establish quality measurement approaches that will guarantee quality care (Levin, Hennessy & Petrila, 2007). Such approaches will also help to identify any areas of improvement. In this case, since the use of decision support is a significant aspect of improved healthcare outcomes, evaluation mechanisms should be applied to ensure that such systems are adding value to the health services and health care outcomes. Through such approaches, it will be possible to pinpoint areas of failure and consequently make decisions concerning the approaches that should be used to improve the decision support in health care facilities and the medical practice in general.

Human Resource Considerations

Decision-support systems are used to aid in decision-making. They do not decide on behalf of the practitioners. Consequently, it is very crucial to understand that the human factor plays a key part in the process of ensuring that such systems are valuable in a health care setting. Firstly, health care provision requires a wide range of expertise that cannot be offered by a single individual. According to Pombo, Araújo, and Viana (2014), human resources are required to run the various computer-aided services that enhance the treatment of patients. Although such technologies are meant to reduce human efforts, it is vital to appreciate that they have to be steered physically to help medical practitioners to make the right decisions concerning any treatment procedures. Hence, collaborative efforts are vital in guiding decision-making, even with the use of decision-support systems. Further, the interpretation of the information and facts that are availed through decision-support systems can have a wide range of interpretations. Hence, collaboration allows the proper decision-making to guide the approaches to addressing a given situation in the health care provision process.

Secondly, patients’ and practitioners’ safety prevails in the process of ensuring timely and quality health care provision. As such, it is advisable to appreciate the significance of providing secure and safe health care facilities for both patients and practitioners at all times (Levin et al., 2007). This goal can be achieved through the application safety guidelines in all health care facilities or the use of elaborate codes of conduct that guide professional contact. Such measures will go a long way in ensuring proper guidelines towards practice and safety requirements, hence increasing health care outcomes to all patients.

Lastly, it is vital to recognize the human skills are central to ensuring good health care outcomes. In this case, the health care sector should ensure that medical practitioners have the right skills and capabilities to provide the required services (Lobach et al., 2012). Through training, the health care sector can have adequate and highly skilled workers who make the right decision, even in the presence of decision-support systems in the health care setting.

Conclusion

The provision of relevant and quality health care services is highly dependent on the ability of practitioners to make the right diagnosis and the right health care decisions concerning issues that they face in their daily activities. The process of making decisions is greatly aided by the decision-support system that allows practitioners to access the right information wherever it is needed for decision-making purposes. Therefore, it is crucial to establish a relevant and up to date decision-support system. Such systems require a thorough consideration of all factors such as financing, quality implications, and human resource components, which are all central to ensuring that the expected health care outcomes are achieved. The paper has addressed the role that these factors play in upgrading the health care sector in terms of providing excellent services to the patients. Any health facility that wishes to perform exemplarily has to address these key areas fully.

Reference List

Levin, B., Hennessy, K., & Petrila, J. (2010). Mental Health Services: A Public Health Perspective. Oxford: Oxford University Press

Lobach, D., Sanders, G., Bright, T., Wong, A., Dhurjati, R., Bristow, E., & Kendrick, A. (2012). Enabling health care decision-making through clinical decision support and knowledge management. Meta-Analysis Review, 203(1), 1-784.

Pombo, N., Araújo, P., & Viana, J. (2014). Applied computer technologies in clinical decision support systems for pain management: A systematic review. Journal of Intelligent & Fuzzy Systems, 26(5), 2411-2425.

Seidman, E., Chorpita, B., Reay, W., Stelk, W., Garland, A., Kutash, K., Mullican, C., & Ringeisen, H. (2010). A Framework for measurement feedback to improve decision-making in mental health. Adm Policy Ment Health,37(2), 128-131.