A Concept Analysis of Person-Centered Care and Personalized Medicine/Health Care as a Basis for an Indivualized AI and Big Data Driven Nursing and Health Care

    


    


    Flow Chart 2: From: Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. doi: 10.1136/bmj.n71

    

Results

In this results section, the individual elements of the concept analysis are first presented separately for personalized medicine and then for person-centered nursing.

Personalized Medicine

Surrogate terms/Synonyms: Different synonyms are sometimes used for personalized medicine within the texts, such as precision health care, precision medicine, precision medicine, stratified medicine, individualized medicine, genomic medicine, pharmacogenomics, personalized treatment, integrated meidince, precision medicine, stratified medicine, genomics medicine and so on which are not necessarily explained in the many articles [34,32,18,17,15,51,2,3]. It can be seen that over the years the terminology has changed from personalized medicine to precision medicine. It is recognizable that this is intended to clarify that the therapy and treatment of patients should be tailored to individuals with the help of bio-genetic procedures.

Antecedents

While the understanding of personalized medicine was originally very biomedical and shaped by various genome projects in different countries [23,34,13,32,18,17,9,22,27,2] the few publications from the field of nursing sciences on personalized medicine are based more on a person-centered understanding of personalized healthcare [20,24,15,51]. The focus is more on the biopsychosocial understanding of a person. However, more recent publications on personalized medicine are also increasingly turning to the realization that data from clinical care and other data must also be taken into account for personalized healthcare if the patient is to receive individually appropriate medical care [2,17,22]. It is clearly recognized that genetic information alone is not enough. Rather, it is emphasized that the particular challenge will be to combine the different data appropriately. Abul-Husn & Kenny [1] discuss how, for example, the wealth of data available in electronic documentation systems (e.g. longitudinal, real patient data, standard clinical care data, demographic data, medical and healthcare data, structured and unstructured data, etc.) can be used by patients for personalized medicine.

Attributes

The outstanding characteristic of personalized medicine is, first of all, genetic analyses, the reference to very large databases with genetic information [23,34,13,32,17,18,9,22,27,2]. Further publications will then add other aspects that appear to be important for personalized medicine, such as phenotypes or knowledge of people's lifestyles, living environment or clinical data from electronic patient documentation systems [17,22,2,20,24,15,51].

Uses of Concept/Examples

As the literature analyzed for this concept analysis mainly deals with personalized medicine in general, the possible examples or uses of personalized medicine are not clearly presented. Some publications indicate that personalized medicine is still predominantly a research topic and has not yet made its way into clinical care [34,23,32,18]. The potential is generally seen in the individualized medical treatment of diseases. The possibility of prevention on the basis of genome analyses is also repeatedly seen, but this is not elaborated on in the underlying publications. The potential is generally seen in the individualized medical treatment of diseases [34,32,18,17,2,27,51]. The publications that address personalized medicine from a nursing science perspective list possible roles and responsibilities that nursing professions can take on in personalized medicine. These include, for example, counselling patients, coordinating healthcare or collecting all relevant information from patients, their environment, family backgrounds and more [20,24,27,15,51].

Consequences

The listed consequences of personalized medicine still seem to be in the realm of the possible, rather than actually achieved as personalized medicine [13,17,3]. It is hoped that patients may experience fewer side effects due to customized therapies, that healthcare outcomes will improve and that diseases or therapies will be better understood [13,22]. Another necessary consequence formulated in the literature is that data from traditional personalized medicine, such as genome analyses, should be combined with data from electronic patient records and other personal data such as lifestyles, health and illness behavior, environmental factors and more [32,17]. The need for interdisciplinary and multidisciplinary collaboration is also necessary in personalized medicine so that all relevant information about the patient can be obtained and included in the data analysis [23,29,9,15].

Definitions

In most definitions, reference is first made to the basic genetic disposition of individuals [23,34,13,9,22], with the aim of referring to tailor-made therapies for the particular individual, as it supports the decision-making process for the most suitable and effective treatment [32,17,18,2]. Further definitions add that personalized medicine is about meeting the healthcare needs of individuals. Other definitions state that personalized medicine focuses primarily on preventive medicine. More recent developments in the understanding of personalized medicine add the need to understand and integrate the social contact of patients, their preferences, behavior, etc [ 20,24,17,15,22,51].

Person-Centered Nursing – Health Care

Surrogate Terms/Synonyms

Various synonyms for the concept of "person-centred care" are used in the literature, such as patient-centered care, resident and family-centered care, patient-involvement, personalized care, relationship-centered care, person-directed care person-focused care [14,10,19,47,25,49,5,44]. However, all terms are not differentiated from each other in the publications, but are sometimes only mentioned as an alternative to the term "person-centered care".

Antecedents

The concept has obviously emerged from critical analyses of the term "patient-centered care" in order to detach from the understanding that people receiving healthcare are only passive beings who are merely recipients of disease diagnoses and therapy [14,48,49,5]. With the person-centered care approach, the aim is to shift away from the biomedical view of people as patients in the healthcare system and implement a biopsychosocial approach to individuals in healthcare [6,14,21,47,48,5]. Person-centered care is about the person who is interdependently linked with others and the environment [14,53]. It recognizes that health and illness are not only biomedically determined, but that many other factors can be significant [53]. Some of the publications refer to the scientific-theoretical foundations of personhood and individuality [30,10].

Attributes

The attributes or characteristics of person-centered healthcare are similar in almost all of the publications included. These characteristics are as follows: shared decision making, autonomy, taking patients' values and preferences into account, including patients' needs and requirements, care coordination, effective communication [ 7,19,53,47,26,5,44]. A key characteristic of person-centered care is that the patient is at the center of healthcare and the entire healthcare provision is based on the needs and requirements of the patient. Patients' values and standards are part of healthcare that always has dignity in its sights [6,14,10,48,49]. Furthermore, a core element is that the relationship between healthcare professionals and patients is understood as a partnership and that the patient's perspective is incorporated into healthcare and included in the documentation [ 30,6,10, 53,49,26]. Healthcare is organized across all settings and sectors, enabling improved communication across all levels of healthcare [47]. Patients are an active part of healthcare, which is also reflected in shared decision-making [30,19,26,5].

Consequences

The consequences of person-centered care are reported to be partnership-based healthcare, the patient as an active part of healthcare, improved communication and care coordination and outcomes and better patient satisfaction and less fragmented health care [7,6,10,19,47,43,44]. Patients' needs and requirements are better understood and if these are then incorporated into healthcare decisions, the quality of healthcare also improves [49,25].

Use of Concept/Examples

As described above in the description of the results on personalized medicine, there are no specific examples of its application, as the literature analyzed was primarily intended to deal with the concept of person-centered care in general, in accordance with the inclusion criteria. However, the literature reviewed indicates that the concept of person-centered care with the biopsychosocial approach can be used in all settings and sectors and for all patient and population groups [53,47].

Definitions

There are various definitions of person-centered care. What they have in common is, that this concept is a biopsychosocial approach that takes a respectful approach to the needs, preferences and values of patients and it contributes to empower patients. Person-centered care guarantees the right to respect for human rights by taking into account the dignity and rights of patients regardless of gender, age and state of health. Person-centered nursing care involves identifying the values and preferences as well as health and life goals of patients and people in need of care in healthcare. The goal of person-centered care is a meaningful life for patients [43,53,21,49,10,5,44]. It is believed that person-centered care is likely to have a nursing care is likely to have a statistically significant impact on improving patient care, so the integration of person-centered care is important for outcomes and quality [25].

Discussion

This conceptual analysis of these two concepts initially suggests that they appear to have a different focus. Personalized medicine has a predominantly biomedical approach [34,32,17,18], although more recent publications recognize that people are not just made up of genetic data. More recent publications on personalized medicine emphasize that clinical data on healthcare is just as necessary as knowledge of social circumstances, personal values, attitudes and should include a more biopsychosocial approach and focus more on the needs of patients [13,22]. It has even been suggested that personalized medicine could develop into "precision public health" [2].

At this point, the crossover or a developing interface to person-centered care becomes obvious. Person-centered care, on the other hand, is based on a completely different level of scientific theory. On the one hand, it becomes clear that the concept of person-centered care has been the result of a critical discussion of the term patient-centered care. The aim of person-centered care is to no longer see patients in healthcare as merely passive recipients of healthcare measures, but as an active part and as a person who is embedded in a life and has values and preferences and is influenced by lifestyles and living environments [6,14,53,49,48]. This also illustrates that person-centered care, unlike personalized medicine, is based on complex scientific theoretical foundations such as the concept of the individual, personhood or people as biopsychosocial entities [30].

Interestingly, publications from the field of nursing science that address personalized medicine also tend to be based on the theories of personhood, the individual or the person as a biopsychosocial being [20,15,51]. They seem to combine the initially biomedical approach of personalized medicine with the predominantly biopsychosocial approach of person-centered care. This approach is also the one that should be pursued for the further development of AI and big data in healthcare. If the initially predominantly biomedical approach of personalized medicine is pursued further and incorporated into AI development and big data analysis, there is a risk that a lot of data will be missing for customised therapy and healthcare. The current impression is, that the concept personalized medicine dominates the discussion in developing AI and anlysing the huge amount of data in health care. Already, Alyass, Turcotte & Mayre [4] identify a bottleneck problem in the development of personalized medicine and big data analysis. The challenge is not so much data generation, but data management, data analysis, data integration and interpretation. It would therefore already seem important to take a critical look at the understanding of personalised medicine and demonstrate that an at least person-centred approach should be integrated for AI development and big data analysis that is intended to benefit patients and perceive them as a whole person. In this case, the complexity of data storage, analysis and interpretation becomes even more complex, but should be considered from the very beginning in order to ensure that AI and big data analysis in healthcare meets the needs of patients and can improve decision-making with a bio-psycho-social approach and outcomes.

Burau`s et al [9] article reveals that hat the current discussions on personalized medicine tend to take place in the context of state or higher-ranking interests, i.e. in the context of interests of pharmaceutical companies, or other companies in healthcare industry, but the perspective, interests and benefits of citizens, who are also part of a state, are hardly ever discussed. At the moment, the concept analysis hints, that the interests of individuals as the fundamental part of personalized medicine are not discussed and integrated in the development of personalized medicine. In the context of increasing digitalization and AI development as well as big data analysis, this finding must be viewed critically, as it is questionable which data and information will then be included, whether people will still be part of the decision-making process at all and how the biopsychosocial approach is to be implemented in AI and big data analysis in healthcare. This critical point advocates conceprually bringing together personalized medicine with person-centered care to ensure that all relevant data and information is incorporated into AI development and big data analysis to improve healthcare and outcomes. It remains to be recognized that people are comprised of more than just genetic information and treatment success is dependent on many factors that are not only biomedically based. At the moment, the biomedical assumption of the effects of personalized medicine is still in the realm of "wishful thinking". So far, the assumption, that personalized medicine enables a more focused therapy is unproven. Although more genetic information is being identified, personalized medicine as it is currently understood has not yet been effectively implemented [23,29,28].

Smith et al. [46] clearly state that person-centered care was developed in response to the depersonalization of people in the healthcare system. This aspect must be strongly considered when it comes to the development of AI and big data in healthcare. If the focus is too much on personalized medicine in the traditional sense and in the biomedical approaches, there is a great risk that previous achievements in healthcare, such as person-centered healthcare, shared decision-making, patients' wishes and needs, their circumstances and much more will be disregarded. For this reason alone, it is highly relevant to analyze the characteristics of person-centered care and to ask which data and data sources can be used to integrate these into AI development and big data.

The attributes of personalized medicine initially appear to be genetic analyses and large databases. But subsequently, the ideas for personalized medicine open up around the need for data from clinical care and the individual living environment. This is precisely where the connection point of person-centered care can be found, which not only focuses on the patient, but also on joint decision-making, the values, needs, priorities, perceptions and bio-psycho-social circumstances of the patient. For an AI and big data analysis in healthcare that is not only committed to a personalized medicine but also to being person-centered, it is important to integrate the characteristics of person-centered healthcare or to develop a joint concept that can be used for further AI development.

The common concept would therefore be that the findings of the genetic analyses and biomarkers are supplemented by the findings on values, norms, preferences, lifestyles, environmental and personal factors, responses to therapies, existing co-morbidities cognitive and emotional factors, presentation of symptoms, self-management and other factors are also added. Furthermore, the goals of combined AI-based personalized and person-centered healthcare must be defined. Cirillo & Valencia (2019) ask how knowledge is gained from the large amount of data in the healthcare sector. This question is highly relevant if AI and big data analysis in healthcare should be personalized and person-centered, taking into account the choices, wishes, needs and circumstances of patients in the healthcare system. This requires concrete knowledge about personal orientation and which data is required.

Overall, the literature on AI in healthcare indicates that these goals and an overall framework for AI in healthcare are lacking [46]. However, defining the objectives is highly relevant in order to be able to define the outcomes in the end, not to lose the focus on people, who should also be the center of attention in AI development and big data analysis, and to structure research accordingly and give possible personalized, person-centered directions.

Of course, the question remains whether it would not be sufficient to incorporate PROMs (patient related outcomes) as person-centered factors in AI development and big data analysis. But it is questionable whether the PROMs are sufficient for this and reflect the outcomes from the patient's perspective or their expectations or merely the assumptions of the healthcare professionals conducting the research [11]. There is evidence in the literature that the PROMs do not reflect patients' specific views of favorable outcomes, that they can`t visualize more nuanced or at least supplementary outcomes and their measurements and they have little relevance for the clinical healthcare of patients [37,11].

It should also be noted that in the reality of healthcare, the aspects of person-centered care are sacrificed first due to time and personnel limitations [44]. Under difficult time and personnel conditions, healthcare professionals are less likely to provide person-centered care and are also less interested in doing so [44]. Against the background that AI and big data are increasingly influencing healthcare and at the same time the framework conditions are not getting any easier due to a shortage of qualified staff, increasing economization of the healthcare system, and so forth, it can therefore be concluded from the discussion above that a conceptual clarification of the important elements of person-centered and personalized healthcare appears to be highly significant. On this basis, it would then be possible to derive which information and data are required, how they can be analyzed and linked in a high-quality manner and which outcomes they should lead to in the interests of the individual. Further research is needed in the future to clarify these aspects so that AI development and big data analysis can be carried out in a person-centered and personalized manner.

Vincente et al. [54] describe in their vision for personalized medicine for the year 2030 that this will overcome intersectoral boundaries and combine clinical care, clinical research and the health professions, patients with personalized medicine. But this will definitely require further research, as it is questionable how the data from interprofessional clinical research and the perspectives of patients and healthcare professionals should be incorporated into the development of personalized medicine and which data is needed.

Conclusion and Implications

While personalized medicine is predominantly based on genome analyses and other biomedical tools, the question remains as to whether personalized care and healthcare should be more broadly based [23,29,28]. In the course of increasing digitalization and the use of digital data through AI and big data, it seems highly relevant to consider person-centeredness conceptually and in research in order to include the perspective, goals, values and expectations of patients and those in need of health care. In light of the fact that AI and big data are increasingly influencing healthcare and at the same time the framework conditions are not becoming any easier due to the shortage of specialists, increasing economization of the healthcare system, etc., the question should be asked as to precisely which aspects of person-centered and personalized healthcare need to be digitized and which need to be maintained in personal interaction. The envisioned concept should be to develop an understanding of hybrid healthcare that combines personalized and person-centered care in such a way that the bio-psychosocial approach to healthcare is also enabled by digitalization, AI and big data.This proposed approach seems so important because the existing digitalization of the healthcare system will go hand in hand with further digitalization, as new digital applications are constantly being added. In the medium and long term, a digital ecosystem will emerge that must be centered around people with healthcare needs and generate and analyse high-quality data. It is precisely against this background that it is so important to conceptualize the terms of person-centeredness and personalized medicine so effectively that all information relevant to people in need of is incorporated into digitized and AI-based healthcare.

Furthermore, PROMs only serve to analyze the impact of healthcare interventions. The review by Rivera et al. [37] even shows that PROMs have hardly any effect or influence in the reality of healthcare. Furthermore, if we consider the attributes of person-centered care and how the concept of personalized medicine has been expanded to include a biopsychosocial understanding or the development towards public health-oriented personalised medicine, it is apparent that AI-based healthcare and big data analysis require further information about people in order to make useful healthcare suggestions for patients. It is left to further research to deal with the results of this concept analysis, to develop a hybrid understanding of personalised-person-centered healthcare, which then shows the data collection tools, the required information and linkages of different data sources and more that need to be integrated.

Based on the attributes, possible consequences and definitions identified in this concept analysis, a reasonable approach could be to first define the goal of hybrid personalized-person-centered healthcare, to define or possibly develop the possible appropriate data collection instruments and data bases and to determine the outcomes that are to be achieved. This requires an interprofessional, interdisciplinary and participatory research approach that also involves patients.

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