Personalized Health Care (PHC) refers to a model that is applied in the medical field which allows the separation of individuals into different groups based on their medical profiles. It enables the implementation of practices, interventions and medical decisions that focus on people at an individual level depending on their presumed disease risk or predicted response to treatment (Simmons et al., 2014). Individual practitioners are likely to use the terms personalized health care and personalized medicine interchangeably, but it is crucial to note that there is a slight difference between the two words. Personalized medicine focuses specifically on the application of genomics and genetics whereas personalized health care takes a more holistic approach to patient care that factors in both genetics and genomics as well as other biological factors essential to determine disease risk and potential patient response to treatment (Medicine, 2012).
Personal Health Care Analysis
The past few years have marked the introduction of a new era in the medical field, a result of the alteration in the medical product development formula. The rate of FDA approval of cancer drugs for use among patients whose tumors present specific genetic properties has increased. Moreover, the FDA is also recorded to have approved a new therapy for patients with cystic fibrosis that display a particular gene mutation. Also, in 2013, three-dimensional (3D) printing technology was employed to make a bioresorbable tracheal splint, which was used in the treatment of an infant that was critically ill (US FDA, 2013). All the said solutions are examples of personalized therapy that resulted from physician realization of the fact that patients that have similar symptoms may suffer from different illnesses, caused by varied factors hence necessitating the variation in the medical interventions applied. Nonetheless, it has become clear that medical interventions that work well for one patient may not exhibit the same result in another patient dealing with the same ailment (Schork, 2015).
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Both genomic and biotechnological advances have led to the gradual discovery of the biology and heterogeneity of diseases. The result has been the introduction of high-throughput molecular assay technologies like protein arrays and single-nucleotide polymorphism (SNP), which have facilitated the discovery of potentially new biomarkers and the creation of complex signatures that have been applied in personalized patient care. The utilization of high-throughput technologies has also elicited the application of data based analytical approaches for high dimension genomics information ( Antoniou et al., 2016) .
Another essential component of personalized healthcare is the application of biomarkers in the diagnosis, prediction, and prognosis processes. As the term suggests, diagnostic biomarkers are used to diagnose illness or establish disease severity. However, among the said biomarkers, the most important ones are screening biomarkers, used to determine the difference between healthy individuals and those that are experiencing disease in its early stages. Among the tests that apply biomarker diagnostic techniques is Rheuma-Chec and CCPoint ( Mirzaei et al., 2016) . After diagnosis, prognostic biomarkers are used to determine the likely course of the disease under standard treatment conditions. For instance, MammaPrint ® is a DNA tumor biomarker used in cases of breast cancer prognosis after surgery to determine the risk of metastasis and guide physicians in establishing the best form of treatment for a given patient ( van Schooneveld et al., 2015) . Finally, predictive biomarkers are applied to determine the response a patient is likely to have to specialized treatment in terms of safety and efficacy, factors that are crucial to clinical decision making ( Gibney et al., 2016) . Thus, genome-wide association studies conducted demonstrated that the presence of the IL28B gene hints the high likelihood of response to standard treatment among patients with hepatitis C virus-1 infections ( Ziegler et al., 2012).
Personalized Health Care Costs
Therefore, in an era where medical precision is crucial to the quality of care that patients receive, especially in oncology, there have been knowledge explosions in the molecular profiling of disease. The decreasing cost of genomic sequencing that has resulted in increased affordability of the same has allowed the classification of a large number of tumors from a biological perspective based on tumor biomarker status. In terms of drug development, new generation trials have emerged, which target selected patients with a specific tumor type, as per the analysis of the biological and molecular characteristics of the same. Initial drug development phases entail bucket trials which focus on molecular aberrations of several tumor types, whereas umbrella trials are more specific and target various molecular subtypes in a single type of tumor. The said innovative approaches to drug development at the clinical level had revolutionized treatment to facilitate the establishment of targeted therapies. They have promoted the potential elimination of the traditional treatment paradigm characterized by the treatment of many unselected patients using the same procedures resulting in inefficiency, cost ineffectiveness and ethical challenges (Lin, 2016).
However, according to Weiss (2016), the implementation of personalized healthcare requires the application of electronic medical record systems as well as training and empowering researchers and clinicians. The said factors are likely to elicit the question of the cost-effectiveness of the implementation of PHC, especially considering that health care has low business margins. The government and third-party payers, like insurance companies, reimburse medical institutions for services rendered and to control costs, the said payers deny payment for services deemed not to be cost effective. Thus, PHC, characterized by molecular diagnostics, is not considered critical to care decisions and the high costs associated with the same do not favor the cost efficiency requirements dictated by the government and third-party payers. Additionally, considering that patients already have to cover high out of pocket costs in the case that specialized medical care is required, further complications in medical procedures, as a result of PHC, are likely to increase the said costs even more (Geruso et al., 2018).
Regardless, the latter does not nullify the fact that PHC is crucial to the improvement of patient care and the betterment of the utilization of healthcare resources. Instead of fighting the incorporation of PHC in healthcare, solutions to the associated cost issues can be realized through the identification and quantification of personalized medicine through economic evaluation (Shabaruddin et al., 2015).
Influence of Biometrics on the Future of PHC
Since the objective of healthcare is to maximize the efficiency of personalized health care, biometrics becomes crucial to the realization of the said objective as it can facilitate increased efficiency of the administrative process and free patient care process of error (BI, 2018). By 2020, it is expected that biometrics in healthcare, on a worldwide scale, will have reached US$5.6 billion (Snyder, 2010), biometric technology will be used for most of the applications in the healthcare sector (Gates, 2007) and developing countries will also have adopted biometrics in health care, allowing the biometric identification of patients requiring emergency services (Frost & Sullivan, 2018). Thus, owing to the correlation between PHC and biometrics, it is inevitable that personalized health care will also be significantly revolutionized in the process.
First, the application of programs like the Care Coordination/Home Telehealth (CCHT) network, which is placed in homes and used to monitor and communicate patient health status remotely to care providers will increase. Secondly, telehealth will allow the engagement of patients in their care, leading to enhanced collaboration with care systems and providers. Additionally, through telemedicine, the healthcare industry will stand a chance at resolving the issue of shortage of healthcare providers by replacing face to face patient-provider encounters with telehealth solutions that incorporate biometrics and telecommunication (Dinsen et al., 2016). Moreover, the biometric revolution will also influence PHC in future through the increased availability of biometric wearables, including garments, that assess body variables and transmit the biometric data collected remotely ( Vogenberg & Santilli, 2018).
Conclusion
Personalized health care is a crucial component in the revolution of the healthcare industry and so is biometrics. It is highly likely that since both PHC and biometrics are based on technological advancements in the medical industry, changes in one area could lead to alterations in the other. So, the implementation of biometrics and personalized healthcare in future medical practices will translate into increased efficiency of the healthcare industry around the world.
References
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