Application: Planned Change in an Hospital Unit
Current development in technology and the increasing need for higher performance in various sectors of the economy has driven the necessity of change in almost all institutions and organizations, particularly the health care sector. New policies demand that quality performance be maintained to safeguard patient safety and foster the generation of positive results in medical practices. Most fundamentally, the move towards integration of modern technology in health care functionalities has become one of particular interest. This paper proceeds from the thesis that Electronic Health Records, especially in the outpatient setting, is an important component that would serve to improve quality of services in health care facilities, if adequately implemented following Kurt and Kotter’s 8-Step Change Models.
Several analyses have so far identified numerous discrepancies in service delivery throughout healthcare system. Technology has become an unalienable component of every single operation in the sector, especially where quality of service delivery is upheld in high esteem. Statistical evidence shows that the outpatient sector is faced with numerous problems, especially as concerns prescription of drugs, and maintaining an efficient follow-up on progress and connectivity of recurrent conditions (Rothman, Leonard & Vigoda, 2012). Consequently, it is reported that the highest cases of erroneous prescribing are found in the said unit, with discrepancies occurring at the rate of 1.5-5.4 for every a hundred orders.
One of most important functionalities of the EHR component is computerized prescribing, which would be very effective in reducing the number of errors reported in the outpatient unit. Secondary problems associated with such reduced performance include increased litigation based on customer complaints about wrong prescriptions. In research done in by Calman et al (2012), it is reported that through the application of computerized prescribing, errors among outpatients were reduced by approximately 80%, and a possibility of better results was very probable (Rothman, Leonard & Vigoda, 2012). This modern system allows physicians to attain the highest efficiency and safety in dealing with patients’ medication, and maintaining appropriate backup of information to aid in future diagnosis. It is alleged that the nature of treatment in the unit (which is based on clinical signs to a greater extent), is the main cause of wrong prescriptions. In addition, efficient use of this application allows health care facilities to save a huge amount of their budget, especially that that would gone to referrals, drug replacement, and handling litigations (Calman, et al, 2012). The Institute of Medicine (2000) pointed out that medication errors are estimated to be the major causes of deaths which occur every year; thus, adopting a planned change to integrate computerized prescribing would be imperative in averting this precedence, and producing sterling results in the medical sector.
Heraclitus, a Greek philosopher, reiterates that the only constant thing in this world is change (Battilana & Casciaro, 2012). Various scholars have developed quite a number of change models, which in essence have the same functionality, although they have different steps and criteria. In particular, Kurt Lewin proposes a simplified three-step model of change management implementation including unfreeze, transition, and freeze. The unfreeze segment involves making people realize the need for a change occurrence, by creating a desperate situation or a provocative problem that would act as a catalyst towards the pressure for change. Usually, it is the people’s attitude that presents the biggest barrier to change adoption; thus, the ‘unfreeze’ stage ensures creation of the right attitude and positive thinking, especially through communication and dialogue.
The transition stage aims to alter individual behavior of stakeholders, so as to foster the search for new and alternative methods to do things. This is usually the most lengthy of all stages, as people take time to get acquainted with an innovation. Once the benefits of the new project become manifest, the stakeholders start accepting it as their own and actively participate in its implementation. However, this stage is faced with a myriad of challenges, as a portion of stakeholders are naturally skeptical towards new changes. Plenty of dialogue and communication usually see the process through.
Lastly, at the completion of the implementation process, it is advisable that the entire change phase is locked up so as to prevent people from reverting back to their old ways. In retrospect, Kotter’s model advises that new processes and functionalities need to be in place to monitor compliance to the new change. For instance, in the medical prescribing technology implementation, outpatient health care personnel need to be subjected to new performance appraisal programs that serve to show inconsistency with the old procedure.
Apart from Kurt’s model, there are other classic change models that have been proposed by other scholars, for instance, Kotter’s eight-Step Change Model, Lewin’s Change Management Model, and McKinsey’s 7-S Model (Battilana & Casciaro, 2012). This paper makes a comparison between Kurt’s and Kotter’s model, with reference to the implementation of an EHR program in a health institution. The first stage of the Kotter’s model, Create Urgency, is similar to Kurt’s initial stage – ‘unfreeze’ (Kritsonis, 2005). They both involve development of a need for an emergency change in operations. The subsequent stages, that is, Form a Powerful Coalition; Create a Vision for Change; Communicate the Vision; Remove Obstacles; Create Short-term Wins; and Build on the Change all correspond to the second stage of Kurt’s model, Transition. The two models do not, however, agree on the style of winding the change implementation process, as the former proposes anchoring of the changes so far implemented in corporate culture of the organization, while the latter talks about freezing of the entire project to prevent a rebound (Kritsonis, 2005).
Focusing on the Kurt’s model, implementation of an EHR project with an electronic prescribing functionality would basically take three major phases. The ‘unfreeze’ would involve active lobbying and dialogue aimed at convincing stakeholders of the need to embrace a new EHR tool; and creating a desperate situation such as presenting statistical analysis of deaths caused by medical errors that would warrant the commissioning of an electronic prescribing package (Mitchell, 2013). This is a very crucial part of the change management project, since potential obstacles could possibly hinder its subsequent success. The early innovators in the health institution would spearhead this stage, as well as other external IT experts. The second stage, which would be the largest, would involve all elements of Kotter’s model, as they correspond to transitioning. Such specific activities as program assessment, planning, selection of vendors, implementation, evaluation, and improvement would be conducted, with each section being headed by a project leader (Kritsonis, 2005). The stage would also involve intensive training of staff in preparation for change of operations and adoption of the new innovation. Lastly, the project would then be frozen by the overall project leader so as to prevent staff members from going back to the old system.
A holistic approach to the implementation process of the EHR technology would be crucial in driving the organization towards the achievement of its goal of quality service delivery to all patients. Consequently, medical errors would be effectively minimized, thereby reducing the number of deaths recorded in outpatient settings. The Kurt and Kotter’s models offer perfect strategies which can be employed synergistically to successfully steer the initiation of a change management plan in any organization.
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Calman, N., Hauser, D., Lurio, J., Wu, W. Y., & Pichardo, M. (2012). Strengthening Public Health and Primary Care Collaboration Through Electronic Health Records. American Journal Of Public Health, 102(11), e13-e18.
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Mitchell, G. (2013). Selecting the best theory to implement planned change. Nursing Management – UK, 20(1), 32-37.
Rothman, B., Leonard, J. C., & Vigoda, M. M. (2012). Future of Electronic Health Records: Implications for Decision Support. Mount Sinai Journal Of Medicine, 79(6), 757-768.