Sample Essay on IT, Big Data & Firm Organization

Introduction

The healthcare sector is considered as one of the most essential sectors of the economy. This is largely because it is responsible for the wellbeing of citizens whose health is definitive of the level of productivity of an economy. The ability of the sector to operate in an efficient and effective manner is dependent on, among other factors, its ability to handle large amounts of data in ways that facilitate the operations of the sector. Big data cloud computing and machine-learning form an important part of data handling technologies whose application will enhance operations in the health sector. This will develop considering the enormous nature of the opportunities for researchers and healthcare experts to invest their efforts and resources in conducting innovations. In addition, it will ensure high impact through the available services in the field of information technology. The main objective of this paper is to provide an understanding of the role that big data cloud computing and analytics would play in facilitating data management in the health sector.

Big Data, Analytics & Decisions

Big data is a computing technology that allows for the collection of large sets of data and analyses them through computation to reveal patterns, trends, and relationships, especially when relating different aspects of human behavior and interaction (Minelli et al 2014, p. 14).

Cloud computing is a technological innovation that allows for the use of a network of remote servers which are hosted on the internet as a platform of storing, managing, and processing data (Raj et al 2014, p. 12).

Analytics is a field of data analysis that involves the study of past historical data and the prevailing circumstances to analyze and evaluate the performance in a specific scenario. The objective of analytics is the improvement of the process of gaining knowledge and using that information to make changes in a business environment (Raj et al 2014, p. 18).

Sources of Inefficiency in the Health Market
Payment systems

The payment system is characterized by differentiations in terms of the amount of financial resources that are required for the treatment of different diseases. The payment system within the US also varies in different states, and this creates the notion that there exist different forms of inequality within the United States. In addition, varied techniques and strategies that the government uses in determining the payments of different diseases affect those considered as the most vulnerable in the society (Emanuel 2014, p. 67). The process of improving the efficiency and ensuring equality of access to healthcare facilities requires the harmonization of the payment system. Through such harmonization initiatives, and subsidization of the financial resources required to access healthcare facilities, it will be relatively easier for the most vulnerable in the society to access the best medical care (Emanuel 2014, p. 67).

Communication

The healthcare sector is often characterized by red tape in access and the delivery of services. The process of diagnosing and treating diseases often take longer period to actualize (Jacobs 2006, p. 30). This is largely because of the numerous but unnecessary procedures that have been necessitated by unwarranted demands of transparency and accountability in the health sector. It is important to introduce procedures within the sector that will ensure a reduction of bureaucratic mechanisms (Jacobs 2006, p. 34). These procedures must be those that enhance communication and coordination between different departments in the health sector. In addition, such coordination must also be channeled towards ensuring efficiency and effectiveness of the sector especially on matter related to the time taken in diagnosing and treating diseases (Emanuel 2014, p. 77).

How big data, IT and analytics are likely to help eliminate the inefficiencies
Coordination and communication cost reduction

Big data, cloud computing, and machine learning are relatively complex for the employees to fully comprehend their functioning. However, with the introduction of these technological developments coupled with an understanding of the nature of predictive markets, it will be relatively easier for healthcare managers to operate these systems. In addition, through the experts, the management will be engaged in a successful process of identifying and analyzing all bits of disparate data types that comprise big data (Khosla 2013, 9). Cloud computing and big data would also introduce a system where healthcare providers would not be able to ignore any data on patient related issues. This would not only make the healthcare sector relevant but also competitive in the respective market (Wikler et al 2012, p. 9).

Through the introduction of big data, cloud computing, and analytics in healthcare organizations, it would be relatively easier for the management to host practices that would reduce red tape for patients. These technological advances would lead the management into the initiation of effective materials such as swipe cards that not only store patients’ data but also provide a perfect platform of sharing information about different patients and their illnesses among healthcare experts (Khosla 2013, 14). In addition, the swipe cards would help in the harmonization of payment procedures in the healthcare sector hence improving efficient and organization of patient records.

Prevention, early predictions and diagnosis

The success of big data and cloud computing does not only rely on the abilities of the healthcare sector but also the involvement of the government and other commercial player. It will therefore be the responsibility of the management to engage in the development of partnerships with these institutions to ensure that the introduction of these advancements in technology lead to the introduction of tighter but mandatory standardized format of data analysis and interpretation (UnitedHealth Center for Health Reform & Modernization Working Paper 2 2009. p. 6). This would not only streamline data conservation in the healthcare sector but it will also provide a platform for the development of a common understanding of different concepts and disease that define the healthcare sector.

The process of initiating strategies of protecting patient information would compel the management to introduce cloud computing. Through such technology, the healthcare sector would only be effective if it played a complementary role in the sector. Cloud computing and big data will play the role of assisting healthcare sector in managing large amounts of data considering the number of patients that access public and private healthcare facilities (UnitedHealth Center for Health Reform & Modernization Working Paper 2 2009. p. 6). This would alter the function of the management considering that the decision making process will have to include other stakeholders such as experts in the field of analysis and interpretation of data. The decision making process will therefore be an initiative that will include all the other departmental heads in the considering the need to provide evidence from available data. The data will them be subjected to an elaborate discussion and this would eventually lead to the development of an informed decision (Wikler et al 2012, p. 13).

Speeding up discovery and innovation

Through big data and cloud computing technologies, the management at the healthcare sector will have a platform through which it will ensure that the services are articulated to the value proposition of the patients. This will ensure the comfort of the patients in sharing health related information. In addition, it will also act with the objective that the information given is confidential and can only be used by the healthcare practitioners in the promotion of healthcare services. The realization of integration between machine learning and artificial neural network will be a way through which the management will standardize the interaction between the healthcare providers and their patients. This will increase the probability that the management with the help of the available data will make decisions based on the demand of the patients (UnitedHealth Center for Health Reform & Modernization Working Paper 2 2009. p. 6).

      Through data driven initiatives, the programs and technological developments introduced in this sector will be aimed at facilitating large-scale discoveries that result in long-term and transformative impacts. These will be based on how best the available data can be used in understanding the best techniques through which patients can ensure that they treat illnesses and maintain their health (Chandra et al 2012, p. 30). Through the technology, a data driven healthcare industry would merge its initiatives with those of the government and academia. This will developed considering the enormous nature of the opportunities that for researchers and healthcare experts to invest their efforts and resources in conducting innovations. In addition, it will ensure high impact through the available services in the field of information technology (Cutler et al 2012, p. 1875).

Automating diagnosis

A data driven organization, especially in the healthcare industry, operates according to the tenets of radical invention theory (Klepper & Simons 2001, p. 4). The development of technological advancements such as big data, machine learning and cloud computing are founded on the improvement of healthcare services and this, according to radical invention theory, arises from the need to trigger some form of shakeout in the technological world (Chen 2013, 79). The role of the management in such an environment is to consider the possibility of embracing alternative forms of technology according to demand and the desire to yield changes in the sector (Cabral 2011, p. 546).

The introduction of big data and cloud computing and big data is based on the realization that a rise in the population of people accessing health care facilities means that there will be an increase in data generated from the high patient traffic (Chandra et al 2012, p. 41). It will be necessary for the management to seek a technology that would not only manage the data effectively but also yield patterns that will enhance the efficiency and effectiveness of the data analysis and interpretation process (Klepper & Simons 2001, p. 8). The introduction of complementary changes in data driven organizations must also be understood on the role of that data in improving organizational performance and the role of different employees in introducing and implementing these changes as a way of enhancing the decision making process (Einav & Levin 2014, p. 18).

 Cost reductions

Through the introduction of big data, cloud computing and machine learning in healthcare organizations, it would be relatively easier for the management to host practices that would reduce red tape for patients. These technological advances would lead the management into the initiation of effective materials such as swipe cards that not only store patients’ data but also provide a perfect platform of sharing information about different patients and their illnesses among healthcare experts and making payments (Khosla 2013, 14).

The healthcare industry has over the years been characterized by initiatives aimed at the realization of technological investments that would not only reduce the cost of providing and seeking medical attention but that would also hasten the possibility of reducing the time taken to access healthcare services (Khosla 2013, 5). This process would be realized by providing effective and efficient services. Big data, cloud computing and machine learning comprise some of the technological initiatives that would revolutionize the world of healthcare. This is largely because through such initiatives hospitals are bound to offer potential vast shifts for private and public institutions in the healthcare industry.

How will the health sector evolve in response to these innovative technologies?

The development of healthcare facilities into data driven sectors will help in the development of different levels of competitive advantages in the health sector. This is because by embracing big data, analytics and cloud computing technologies the public and private healthcare sectors will be aiming at improving on their market share and customer base. The main of competition will be between those engaged in traditional operations especially in handling emergency health matters and  those using big data, cloud computing and analytics in handling patients’ data.

The rise of data driven firms in the healthcare sector will leads to the development of a holistic approach on how best to handle mattress related to the provision of health services in both private and public healthcare centers (Frankovich et al 2011, p. 1758). The introduction of data handling technological devices such as the electronic medical record (EMR) is considered as a technique through the healthcare sector will be restructured and improved. This will be in terms of capacity as a way of ensuring that this technology plays its complementary role in improving service provision within the sector (Frankovich et al 2011, p. 1758). Through the EMR, the medical fraternity will be able to engage in the use of relatively sophisticated informatics and analytics tool. The growth in the use of EMR in the healthcare industry will also advance the use of a data driven approach to the delivery of healthcare services (Frankovich et al 2011, p. 1759).

Chart 1.0: Impact of IT and Big Data on Healthcare

The charts above indicate the impact of IT and big data in the healthcare sector. One possible way through which the potential impact of IT and big data can be perceived is in its ability to raise fixed costs while at the same time requiring the development of  a new layer of infrarastructure whose orientation is capital intensive. This lifts up the average total cost curve while increasing the minimum efficient scale of the firm. In addition, it ensures a minimization of ATC in terms of its output level. The development of analytics, big data, and IT will most probably lower the variable cost of soft operation through a reduction of the administrative cost such as medical errors. This will in turn lower the marginal cost at each level of output. The evolution of IT and big data will lead to industry consolidation and the rise of larger firms. The actual impact however is dependent on among other factors, whether the lift in ATC is stronger or a fall in the MC curve.

The rise of data driven firms and the ability to operate through big data will also lead to the development of data driven medicine. Through this technology, the healthcare sector will be patient centered. This is because big data will necessitate the evolution of proactive, predictive and participatory structures within the sector (Shah & Tenenbaum 2012, p. 3). Through data driven medicine, healthcare facilities will also have the ability to discover new medicine with the help of the multi-model measurement approach on medicine. In addition, through the available data, healthcare practitioners will be able to learn and understand essential trends embed in the diagnosis, prescriptions accorded to millions of patients (Shah & Tenenbaum 2012, p. 3).

The rise of data driven firms will also provide a platform through which the healthcare sector will be able to address issues related to drug malfunction or the side effects to the use of different drugs on patients. This will be necessitated by an analytical study of the trends and common symptoms (Shah & Tenenbaum 2012, p. 3). Through the identification of these symptoms, it will be easier for the healthcare sector to develop medicine that is applicable in instances of drug malfunction or possible side effects.  This will only be realizable when big data will be used in the management of massive amounts of data to generate patterns and make accurate predictions (Shah & Tenenbaum 2012, p. 3).

The rise of data driven firms in the healthcare industry is bound to provide better and cheaper healthcare services to those in need of medical attention. This is largely because data driven firms will use data generated through big data and cloud computing in faster and effective diagnosis of diseases, considering that different experts in the medical fraternity have a platform of knowledge sharing (Chen 2013, 78). Through the rise of data driven firms, the healthcare industry will have the ability of introducing effective curricula in the management of health related issues (Carte et al 2005, p. 413). The emerging doctors will have the ability of solving biomedical puzzles largely because the use of big data and cloud computing will encourage sharing of information between countries, hence increasing the possibility of cross country expert consolation (Wikler et al 2012, p. 10). This will also help the healthcare sector in a reduction of the level of investment in technological infrastructure. This is an indication that through data driven technology, the management in the healthcare industry will have the ability perform cost optimization at both patient and policy levels, thereby influencing the entire operation of the industry towards the realization of desired goals and objectives (Klepper & Simons 2001, p. 12).

Conclusion

The ability of the sector to operate in an efficient and effective manner is dependent on, among other factors, its ability to handle large amounts of data in ways that facilitate the operations of the sector. Big data cloud computing and machine-learning form an important part of data handling technologies whose application will enhance operations in the health sector. Through big data and cloud computing technologies, the management in the healthcare sector will have a platform through which it will ensure that the services are articulated to the value proposition of the patients. The rise of data-driven firms in the healthcare sector will lead to the development of a holistic approach on how best to handle matters related to the provision of health services in both private and public healthcare centers. This will develop, considering the enormous nature of the opportunities for researchers and healthcare experts to invest their efforts and resources in conducting innovations. In addition, it will ensure a high impact of the available services in the field of information technology.

References

Cabral, L. 2011. Technology Uncertainty Sunk Costs and Industry Shakeout. Industrial and

Corporate Change, Vol 1, No. 3

Carte, T., Shaft, T & Zmud, R, 2005. Advanced Business Intelligence at Cardinal Health. MIS

Quarterly Executive Vol. 4, No.4

Chandra, A., Finkelstein, A & Syverson, C, 2012. Healthcare Exceptionalism? Productivity and

Allocation in the US Healthcare Sector. Chicago University: Chicago

Chen, H, 2013. Smart Health and Wellbeing. University of Arizona: Arizona

Emanuel, Ezekiel J. 2014. Reinventing American health care: how the Affordable Care Act will

improve our terribly complex, blatantly unjust, outrageously expensive, grossly inefficient, error prone system. Cambridge University Press: Cambridge

Jacobs, Rowena, Peter C. Smith, and Andrew Street. 2006. Measuring efficiency in health care

analytic techniques and health policy. Cambridge [etc.]: Cambridge University Press.

Raj, Pethuru, and Ganesh Chandra Deka. 2014.

Cutler, D., Wikler, E & Basch, P. 2012. Reducing Administrative Costs and Improving

the Health Care System. The New England Journal of Medicine. Massachusetts Medical Society

Einav, L & Levin, J, 2014. The Data Revolution and Economic Analysis. The National Bureau of

Economic Research

Frankovich, J & Longhurst, C & Sutherland, S, 2011. Evidence Based Medicine in the EMR Era.

The New England Journal of Medicine. Massachusetts Medical Society

Khosla,V, 2013. Do we need Doctors or Algorithms. Tech Crunch.

Klepper, S & Simons, K, 2001. Industry Shakeouts and Technological Change. Carnegie Mellon

University: Pittsburg

Minelli, Michael, Michele Chambers, and Ambiga Dhiraj. 2013. Big data, big analytics:

emerging business intelligence and analytic trends for today’s businesses.

Mohanty, Soumendra, Madhu Jagadeesh, and Harsha Srivatsa. 2013. Big data imperatives:

enterprise big data warehouse, BI implementations and analytics. New York: Apress

Shah, Nigam & Tenenbaum, Jessica. 2012. The Coming Age of Data-driven Medicine:

Translation Bioinformatics’ Next Frontier. Journal of American Medical Information Association. June 2012, Vol. 19. No. e1.

Cost Containment –How Technology Can Cut Red Tape and Simplify Health Care Administration. United Health Group: USA

Wikler, E., Basch,P & Cutler, D. 2012. Paper cuts: Reducing Healthcare Administrative Costs.

Center for American Progress: USA