Complaint-Push Model and Data-Pull Model - Coursework Example

Health Services Strategic Marketing Complaint-Push Model and Data-Pull Model In health care service delivery, the complaint-push model represents a simplified characterization of the current service model adopted by health care providers in many developing and developed nations (Tan & Payton, 2010). In this model, patients with complaints call for appointments or access the service location directly where the health care providers assess the complaint and recommend further tests before diagnosing (Tan & Payton, 2010).

On the other hand, the data-pull model represents a future service model for health care providers. In this case, health care providers monitor available ICT and health care data from a wearable device and invite patients to utilize the system where the patient enters their data to a central databank with an aim of enhancing health care service (Tan & Payton, 2010). To improve the effectiveness of the complaint-push model, health care providers should create awareness and adopt advanced communication methods like emails, websites, social media, and blogs that can allow patients to reach the health care providers with ease and enable the health care providers to respond to the complaints with speed and relevance.

On the other hand, to improve the effectiveness of the data-pull model, health care providers should ensure that patients have prior and detailed knowledge of the information and communication technologies for health care delivery before inviting them to utilize the system. The fragmented system of care delivery in U.S is a significant aspect of a complex health care system that represents barriers to a more rapid diffusion of HIT. To minimize this aspect, we must adopt a federal-state framework for HIT implementation that will foster HIT diffusion by creating an oversight mechanism for the implementation of HIT in U.S. This will enhance quality improvement, access, and integration of health care organisation, HIT systems, health information, and healthcare administration.

Notably, Brenda Hunt’s address of complaint-push model and data pull model was relevant in that it related to previous literature as discussed by Joseph Tan, Fay Cobb Payton. Hunt’s strategy of improving the effectiveness of these models was logical and practicable in that it related to the need for advanced technologies in healthcare delivery. These technologies are available and effective. They will guarantee quality and timely healthcare delivery. With respect to a significant aspect of a complex health care system that hinders the diffusion of HIT, Hunt identified a dominant aspect that relates to the need for change in healthcare delivery.

Indeed, some people are still refusing to adopt the new changes and technologies in healthcare and hence the need to motivate them by defining the benefits for adopting such changes. Continuous Quality Improvement (CQI) is a key process in the delivery of health care services that would be more efficient and effective through the application of a specific model of HIT. The CQI process promotes the use of health information technology (IT) to improve quality health care (The National Learning Consortium, 2013).

Indeed, CQI refers to a quality management process that encourages all health care team members to consider the current state of health care and how they can improve healthcare delivery. In adopting this process, health care stakeholders rely on clinical and administrative data through EHRs (The National Learning Consortium, 2013). The CQI process helps the health providers to capture healthcare data in an effective and efficient manner. This helps in the transformation of healthcare. Indeed, various health care organizations have adopted the CQI strategies since it forms the basis for deriving the best strategy for healthcare delivery.

The implementation of HIMS faces numerous barriers. Indeed, misinterpreting responses, inaccurate patient information, cost of hardware, and conservative behaviors are barriers to the implementation of HIMS in a complex adaptive system (CAS). These barriers hinder the adoption of change, limit access to hardware that support HIMS in a complex adaptive system, and lead to biased and inaccurate health data. The misinterpreted responses lead to wrong diagnosis and limit the perception of HIMS in healthcare.

Moreover, these barriers limit quality improvement in healthcare delivery subject to the reduced rates of the implementation of HIMS. Notably, we can reduce the level of resistance from the clinical staff during a transition from CAS to HIMS innovations by creating awareness and informing the clinical staff about the benefits of the transition. Moreover, by allowing the clinical staff to own the transition and considering their views in designing and implementing the transition would motivate them to accept and adopt the innovations.

Implementing the transition in phases will equally reduce the level of resistance from the clinical staff during a transition from CAS to HIMS innovations. Notably, Darrell Harris addresses a fundamental process of delivering efficient and effective health care services through the application of a specific model of HIT. Indeed, the mobile health (mHealth) defines an effective and efficient process that relies on modern technologies to provide numerous benefits in healthcare. The mHealth process is practical and viable since it relates to modern technological advancements adopted by most health care stakeholders.

Considerably, Harris noted the barriers in integrating CAS with other systems. Indeed, as an interactive complex delivery system, it is challenging to integrate it with other systems. The proposed strategy to help reduce the level of resistance from the clinical staff during a transition from CAS to HIMS innovations is equally viable and practical. Darrell Harris was considerate and rational in proposing this strategy. References Tan, J, & Payton, F. (2010). Adaptive Health Management Information Systems: Concepts, Cases, & Practical Applications: Concepts, Cases, & Practical Applications.

Massachusetts: Jones & Bartlett Publishers. The National Learning Consortium. (2013). Continuous Quality Improvement (CQI) Strategies to Optimize your Practice. Retrieved form: http://www.healthit.gov/sites/default/files/tools/nlc_continuousqualityimprovementprimer.pdf