Critical Analysis Of Deep Smarts Model To Increase Team’s Effectiveness In Healthcare Field

Introduction

Chess - a mental simulating game, consists of six different pieces with different functions founded in medieval times, was played in China and Persia, quickly spread to Europe after a series of invasions. All pieces have specific strengths and weaknesses, thus using a single favorite piece can be limiting whereas coordinating moves with difference pieces and taking calculated risks with the other pieces can prove to be powerful. The team must have a clear objective of forming a defense alliance to secure the king and an attack strategy to win the game. Fast-forward to the 20th century, healthcare systems complexity, intertwined nature involves an intersection of important stakeholders including patients, healthcare professionals, employers, IT, biomedical technology, insurance and pharmaceutical firms. As a result, organizational development has gained interest from healthcare industries to enhance patient-centered services.

These include three important dimensions for an organization: culture, individual competency and application. It has been agreed by multiple researches that effective teamwork is becoming a key instrumentation in successful delivery of high quality patient-centered care. In the past two decades, various traditional models in teamwork effectiveness from the literature (1985-2004) have been examined. It concluded that an effective model would be one that is customized to the team’s work and healthcare setting, more specifically the integrated team effectiveness healthcare model (ITEM).

Healthcare managers no longer apply a single model as the ‘one size fits all’ is less effective due to the complex phenomena of dynamic healthcare delivery. In addition to that, they are becoming increasingly inclined towards application of tailored models to particular types of teams and work processes. Recently, a new perspective of achieving effectiveness through capturing and transferring of know-hows, emotional intelligence and capabilities from individuals to teams working within and across. The “Deep Smarts” model addresses issues faced by health managers in smooth coordination of activities for patient positive outcomes. In this paper, the aim is to assess teamwork effectiveness dimensions using Deep Smarts, explore and analyze the model to be applied in a multi-disciplinary, real healthcare teams and practicality in application to achieve measurable indicated purposes.

The Need for ‘Deep Smarts” teams in Healthcare

Unlike mechanical systems that interact linearly to produce a predictable controlled output using formulated equations, healthcare systems are dynamic, nonlinear and unpredictable. It is proposed that effective interactions and collaborations between all parties including patients, physicians, nurses, pharmacists, and related staff to achieve organizational objectives. At the same time, medical error is estimated to be “the third most common cause of deathin the US”, and teamwork failures (e. g. , failures in communication) account for up to 70-80 percent of serious medical errors With technological advances and increased specialization in clinical sciences, the challenges faced by multi-disciplinary teams are greater than ever. This has sparked interest into enhancing teamwork efficiency, which as a result, leads to improved quality patient-care. However, this is not solely dependent on healthcare professionals competency, but also on systems that sponsors contexts, processes, settings that is fundamental for good practice and minimizing medical errors. One other reason for the introduction of teamwork is that the patient’s journey in healthcare involves multiple professionals, and therefore collaboration is required for tailored patient treatment.

There is a demand in translating capabilities and integrated knowledge to sustain continuous change and enhance team learning and performance. It was noted that a team centered-learning approach enables healthcare organizations in adjusting to rapid changes to population needs. Teamwork is an integral part in making this change possible; moreover, dependence on individual competencies regardless of level of expertise is not sufficient to ensure safe patient-centered care. Deep Smarts are usually integrative, networking roles that employ clinical, organization and human capital skills within and across teams team effectiveness such as a nurse case manager and patient flow coordinator. Deep Smarts known as “boundary spanners” have the ability to view standard operating procedures from multiple perspectives and spot opportunities for improvements within teams. Successful identification and onboarding of people with such skills within healthcare teams can counteract siloed approach to patient-centered care. Hallmarks of ‘Deep Smarts’ Traditional characteristics of effective teams include: common objectives alignment, identity, cohesion, shared mental models, relations’ conflict, shared sense of trust, accountability, and commitment, which have been studied in earlier researches. Less research examine deep smarts characteristics, however it has been shown that deep smarts focuses on individual characteristics that enables them to empower others and bring about change in teams and across organizations. The critical abilities of the later enable them to integrate complex thinking system with organizational behavioral information. Deep smarts people have potent expertise knowledge “know-hows” based on real experiences that enables them to analyze, act and refocus other members attention on a common plan and purpose of the assigned objectives.

Through the use and transference of their explicit knowledge they are able to develop others and organizations to fulfill mutual objectives. Under complex organizational pressure, these individuals in teams are able to take charge, make positive decisive decisions, based on their on the understandings resulted from experiences. These gained experiences are sharpened by reflection and sustained engagements for long periods. Moreover, facilitating other team members activities, communicating issues, negotiating complexities and interconnections through boundary spanning activities to plan and mange cohorts of patients across individuals. This complex boundary spanning activity remains a stumbling block in many organizations.

The addressed issue for teams in healthcare necessitates that they work together effectively including managers, healthcare professionals, employees to bring about a patient-focused culture.

Discussion (Critique)

It was identified that certain communication processes are critical to a teams success; Firstly, ensuring that individual team members with relevant knowledge speak up when one’s expertise can be helpful to others across the organization. Secondly, influencing the team’s work so that the team does its collective what’s best for the patient. To support this model with appropriate evidence, a study was carried out to analyze causes of poor teamwork between junior doctors and nurses and rule out if failure in teamwork is linked to increased patients risks. The tool employed were critical incident technique interviews in two teaching hospitals in Ireland. The results showed that most of included scenarios of teamwork failures were attributed to lack of shared mental model, poor communication as high risk, whereas poor quality collaboration, poor leadership, lack of coordination as medium risk scenarios. As a result, there is an urgent need for the attributes of deep smarts that will foster the complex issues faced by teams in healthcare. It is claimed that deep smarts to be of beneficial approach for healthcare managers to identify individual critical capabilities to nurturing resilient, high-performing teams. Subsequent identification and integrating deep smarts people, will in turn, lead to opportunities for the development of other team members. In light of this information, the article was not able to propose a detailed framework for the application of the model across teams in healthcare settings.

Moreover, it emphasizes the role of one-team member (deep smarts) critical abilities in achieving coordinated patient care without taking into consideration the importance of other team members role (characteristics) in facilitating this success. Development of team members to become deep smarts is Pursuing this direction is important because an effective, supportive team can enable other team members to develop, allowing them the opportunity to gain experience, insights, knowledge and understanding, and so potentially to become a deep smarts person.

Supported argument to use Deep Smarts in healthcare teams is supported through 13 various strategies - However, some of the conditions for deep smarts development have been associated with implementation difficulties. Therefore, consideration of the organization processes, contexts, team, available resources and support, to enhance deep smarts growth, is necessary. When seeking to introduce these strategies drawing on the lessons from the implementation science field will help promote their successful uptake. The research also encourages further research using proposed strategies to implement Deep Smarts in teams across organizations. A present limitation is that investigations using the deep smarts model have only been examining the individuals. There is no published healthcare research specifically investigating if, collectively, people-displaying deep smarts characteristics, leading to the questions: can people collaborate and integrate to be a deep smarts team? If so, what interactions, processes, contexts, resources or structures enable and enhance a deep smarts team? Studies on deep smarts have been carried forward, yet application of the model across teams is still in its infancy with lack of data to support for effectiveness in large healthcare organizations. Research provides theoretical basis for the proposed model, nevertheless limited case examples as to how it can impact the team and organizational performance overall. There is clearly a lack of evidence regarding the implementation and impact of team-based models of primary care to inform what works, for whom and in what circumstances.

Conclusion

Although chess is only a strategy skill board game, yet it can teach us a lot of life-lessons that can be applied to several settings, including healthcare. Firstly, every move has a defined purpose, with which other pieces must coordinate actions in accordance through a predetermined strategy. Secondly, Seizing initiatives to make timely effective decisions. Thirdly, being flexible and quickly adjusting when faced with uncertainties. Fourthly, looking beyond the obvious. Even when things seem to be going perfectly, good chess players anticipate what could go wrong and plan accordingly. All these added lessons could be facilitated through effective teamwork in the presence of appropriate contexts and processes. Future research on deep smarts can focus into developing framework that involves applied quantitative and qualitative parameters for deep-smarts. Building forward on the available theoretical basis, practical application in tertiary healthcare settings can validate the proposed model. Research into tools and methods development and training of team members to become deep smarts. Furthermore, implication of the model’s application in predetermined teams effectiveness parameters and across organizations.