Healthcare management is the prime focus of this paper, it can be defined as the type of management which is required in a healthcare organization considering their physical and the non-physical assets of the organization. Healthcare management is very much required for all the healthcare industry to deal with the important aspect of the business such as the networking system, public health systems and medical facilities (Joshi et al. 2014). Utilization of the available resources is another significant business perspective of healthcare management. Efficient recruitment process is very much important for maintaining healthcare management. The role of healthcare managers is very much important for managing the different departments of healthcare management. Decision making is a very important business perspective of the healthcare management considering different departments such as the marketing team, finance team, policy analyzing team and the accounting team (Shirley 2016). The foremost determination of this paper is to focus on the importance of the modelling and optimization performance of healthcare operations. Like every business organization, the healthcare industry faces adverse business conditions which can be solved effectively with the help of modelling and optimization.
This segment of the paper will be focusing on the need for optimization in healthcare management. Like every business organization, hospital industry also has numerous data sources which are managed with the help of big data as it helps in enhancing the transparency of the business processes. Transparency is very much important for the healthcare industry as it can be required in any hour of the day (Cervero-Liceras, McKee and Legido-Quigley 2015). There are complexities in finding specialist doctors in case of the emergency situations. Big data analytics is a huge aspect which is used practically in all the healthcare industry for managing the large volumes of data which is daily maintained in the business environment such as the community data, self-quantification data and public and private data (Ahmadi-Javid, Jalali and Klassen 2017). Public data are generally obtained from the local communities and the governmental organization, private data comes from private organizations such as the non-profit organizations which are connected to the hospital. The private data may include the supply chain of the organization which provides the raw materials required in the hospital such as the advanced technologies and machineries associated with the hospital.
The importance of optimization in healthcare management will be discussed in this section of the paper. The transactions of the consumers also fall in the category of the private data, the data associated with the physical assets of the organization, data obtained from the website browsing of the internal stakeholders and the data obtained from the mobile devices which are used dedicatedly for the business purposes are included in the private data of the healthcare industry (Shrivastava, Shrivastava and Ramasamy 2017). The data having limited value in the business environments such as the ambient data falls under the category of the exhausted data. Community data includes different types of dynamic and unstructured data. The data obtained from the consumers of the healthcare industry in the official portal of the industry as well as in their social media sites are the community data. Quantifying the behaviour and action of the stakeholders of the organization is included in the self-quantification data (Cresswell, Bates and Sheikh 2016). All these different categories of data exist in the healthcare industry which are effectively managed by the big data.
Optimization techniques can be applied to each of the stakeholders associated with the organization starting from the operation level to the designing of the healthcare policies (Loo, Mauri and Ortiz 2016). The other different departments which may fall under the category of optimization are as followings:
Most of the healthcare organization have different types of stakeholders associated with them and there are conflicts due to their common or shared organizational goals but the optimization techniques are very much important for the resolving those issues (Hejazi, Badri and Yang 2018.). Different types contracts are there between the stakeholders of the hospital industry such as the Service Level Agreements (SLA) which are needed to be managed considering the privacy of the data. Web services and the connectivity issues of the hospital can be identified with the organization can also be understood with the help of the big data. Data sharing agreements is need for the protection of the different types of data. Confidentiality, Integrity and availability of the data are very much important considering the healthcare management which is the need for the incorporation of big data analytics in this industry. All the stakeholders associated with the data of hospital industry can be effectively managed and edited with the use of the big data analytics.
The latest digital data sources such as the mobile calls of the patients, conversation between the stakeholders and choice of the consumers of the organization in terms of specialists doctors is better handled with the help of the data mining process. The developmental efforts of the hospital organization are carefully managed with the application of the data mining techniques. The traffic patterns and the vulnerabilities associated with the diseases is one of the most important usefulness of the big data (Mahfoud, Abdellah and El Biyaali 2018). The different types of challenges associated with the hospital sector can also be managed with the help of the big data.
The prime determination of this unit of the paper is to focus on the use of big data in healthcare management. The application of the big data is very much important for the optimizing the data associated with the healthcare industry as it is very important to store and manage those data for the growth and progress of the industry. The application of the big data very much useful to prevents the medication errors in the hospital industry which is a major concern. The differentiation between the low-risk patients and the high-risk patients is sometimes a huge concern for the management team of the healthcare industry (Raghupathi and Raghupathi 2014). There are different types of added costs and overhead costs associated with complicated treatments which is a problem for the management team as the families of the patients raises huge issues in the middle of the treatment, these administrative issues can be solved purposefully with the help of big data. Waiting time is the other concern for the management team of the hospital industry. The extensive developments in the field of science and technology have led to the growth of new cybersecurity issues for the healthcare industry such as the ransomware, this kinds of securities issues can be easily detected if the organization have a tightened security system considering the big data. These kinds of security breaches are very important business perspective of the management team of the healthcare industry (Dimitrov 2016). These fraudulent activities can be prevented with the use of big data. The internal security issues of the healthcare industry can be significantly reduced with the help of big data analytics. Optimization of the conventional patient engagement strategies should be replaced by the latest big data enabled systems as it is very much useful to improve the connection between the hospital authorities and the family of the patient (Van Schoten et al. 2016). Thus it can be said that the use of big data is very much useful to manage these administrative aspects of this industry.
Figure 1: Example of real-world application of optimization
(Source: Created by the author)
The prime focus of this unit of the paper is to focus on the impact of modelling in healthcare management, the importance of models will be discussed in the paper. Business management models are very much important in the healthcare management; conceptual frameworks are increasingly used in the management purposes in the healthcare industry in order to resolve the complexities associated with the industry (Zhang et al. 2017). The needs and requirements of the consumers of this industry are changing with time which is the main reason behind the discarding of the conventional business models. Quality of products and services can be improved significantly with the use of new business models. The most important modelling tool used in most of the management unit of the healthcare is Total Quality Management (TQM). TQM has helped the healthcare industries to improve the performance of the stakeholders. Both the clinical staffs and the non-clinical staffs can be managed in an effective way with the help of TQM. Collaboration and team effort is required in every aspect of healthcare management which is one of the positive impact of this business model in healthcare industries. TQM is hugely beneficial to improve the customer satisfaction of the consumers who are the prime stakeholders of this business (Ahmad et al. 2017). Flexibility is a key prospect for maintaining the business in the healthcare industry is the other significant specification of TQM. Change in the administration process is a very critical stage in the health industry as the changes may or may not be suitable to the business environments as well from the business perspective, TQM plays a huge role in these kinds of circumstances. The following table will be guiding us to understand the role of TQM during the transitional phase in healthcare management.
|
Communication between the stakeholders of the organization |
Autocratic management |
Improves the participation of each employee associated with the organization. |
|
Resistance to change |
Limited managerial role |
Holding effective meeting sessions with the concerned employees. |
|
Change in job design |
Industrial engineering methods |
Improves decision making ability and problem solving skills. |
|
Performance evaluation |
Concerned focused |
Improves the focus on the teams. |
|
Performance comparisons |
Each healthcare industry has their unique methods to compare the performance of their organization with the other organizations considering the new changes. |
Benchmarking is the most important role of TQM considering the performance comparisons. |
Table 1: Role of TQM considering different factors
(Source: Created by the author)
This unit of the paper will be focusing on the effectiveness of the use of a specific business management model which is Total Quality Management (TQM). TQM is one of the most widely accepted business models used in the healthcare management as it helps in improving the relationship with the consumers of the healthcare management, quality of patient care, lowering the costs of the advanced systems used in this industry (Nicolaou and Kentas 2017). Sometimes it is feared that the business models will be focusing only on the profits and efficient of the resources of the organization more than human values such as participation in the annual events, but TQM is a very important business model which looks after both the efficiency of the resources as well as the human values of the employees (Mosadeghrad and Ferlie 2015). The effectiveness of the business management models such as the TQM can be improved significantly with the help of effective training sessions by expert professionals who have years of experience working with different types of business management models as they know the insight out of the effectiveness of those models. Their knowledge can be hugely capitalized in a massive way for the growth and progress of the healthcare industry. The complexities of the healthcare organizations can be solved effectively with the use of the business management models (Al Ghamdi et al. 2016). The cost of the different modules of the healthcare management and quality of services provided by the health organizations can be significantly impacted by the application of Total Quality Management.
Decision making is one of the key aspect of modelling and optimization in the healthcare industry. There are lots of challenges associated with the healthcare industry such as the customer service department, which can be effectively solved with the help of optimization. Complexities in the challenges is a very important aspect of healthcare management, as the level of complexities may keep on changing with time (Ross 2017). The different internal and external stakeholders associated with healthcare management is hugely benefitted with the use of modelling and optimizing. The modelling and optimization is very much important to meet the demands of the patient as well as the internal stakeholders of the organization (Mohammad 2014). Optimization of specific segments in healthcare management is very much important as constant changes are necessary for this industry. The business process around healthcare management such as the cost control of the infrastructure and maintenance costs needs efficient modelling techniques to be managed (Mosadeghrad 2015). The variations in healthcare management should be managed in a professional way so that the desired results are obtained. Most of the healthcare industry is linked with numerous external stakeholders such as the distributors, private clinics, marketing team; these stakeholders are needed to be administered in a useful way so that the growth and progress of the organization is maintained. Capacity planning decisions are one of the other essential aspects of healthcare management.
Conclusion
The paper helps in concluding the impact of the modelling based healthcare management as it helps in improving the business decision of the healthcare organizations. Efficient allocation of the resources is very much important for the healthcare organization which is done with the help of optimizing the existing business processes. The reduction in the waiting time for the patients is considered to be the parameter for the progress of healthcare management. Queueing, simulation, scheduling are the three prime aspects of the healthcare industry which are needed to be considered for optimization. The business models which are applied in the healthcare should be properly evaluated before being incorporated into the working environment of healthcare industries so that the desired results are obtained as there may be some issues associated with the business models which can negatively impact the organization. The business model which is focused in this paper is the TQM which is the Total Quality Management. Different aspects of these tools were identified in this paper. The paper was helpful to understand the impact of this business model in the healthcare industry. This paper provides the role of the TQM considering different factors in a tabular form. The need for optimization can also be understood from the paper as like most of the organization, healthcare industry needs certain optimization techniques to meet the ever-changing needs and requirements of the consumers who are their primary stakeholders. The different complexities in healthcare management are identified with the help of the latest optimization techniques. The optimization techniques can be applied to any unit of the healthcare industry starting from the operations team to the productive units. The paper was also helpful to understand the importance of the data optimization as data is considered as an asset in most of the global healthcare organization. The data optimization techniques which are discussed in the paper is very much useful to protect the data from the cybercriminals and also from the threats coming from the insiders of the organization. This paper is very much useful as its contents are analyzed in the paper itself, the effectiveness of the optimizing and modelling is stated in the paper with primary importance. Different aspects of optimization and modelling such as the costs associated with them fraudulent activities associated with the business is understood in a better way with the help of this paper. Thus the paper was very much useful to understand the impact of Big data which is readily used in most of the organization to manage different types of data such as the structured and the unstructured data.
Reference
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