Searches in Pubmed, CINAHL, and Ovid revealed few articles that were published between 2013 and 2018 on the themes of either P4 medicine or participatory medicine or health care in the context of general practice. None of the retrieved articles related to issues relevant to P4 medicine in the sense of personalised, participatory, preventive, or predictive. The term participatory was found in the title words, abstracts and full texts of all of these articles but they referred to a care process where the provider would tailor the treatment for the individual patient, as opposed to the concept of "participatory care" envisioned in P4 medicine where the patients and providers would together share data and information to arrive at the best care process and optimise health outcome in the context of general practice.  Hence in the remainder of the paper, we discuss personalised, preventive, predictive, and participatory health care in the context of general practice and emphasise how participatory health care can be a cornerstone of this new paradigm of care and how general practitioners can be at the forefront of this practice.

The structure of the human genome was elucidated in 2003 (project started in 1995); this work was accomplished in record time; however this only provided a roadmap and structure of the human genome with the lists of genes and their locations (citation?). Further work on networks of genes, transcriptomes, and molecules provided deeper knowledge in how the networks of the different structures determined the function of these entities in biology. This is referred to as “systems biology”. Systems medicine refers to the phenomenon of applying the principles and practices of systems biology to the domain of human diseases (cites??). 

Hood and Auffrey (2013) 

Flores et.al. (2013) has provided an overview of systems medicine and P4 medicine, from the perspectives of critiquing a review of three reports by the US Institue of Medicine on systems medicine \cite{Flores:2013kc} . Flores has argued that a new kind of engagement with patients will be needed for systmes medicine or P4 medicine to work effectively, and that three defining characteristics are drivng forces behind the emergence and adoption of systems medicine and P4 health care now. In no particular order, these are as follows: first, systems medicine/systems biology is an emergent trend; second, availability of data analytic tools, specifically, big data analytic tools and advances in computing; third, emergence of networks of people where individuals are getting increasingly connected through social networks or otherwise in a trend of increasing use of social  networks not only for communication but also for archives of data sharing for individuals.

Flores has argued that in future, driven by these emergent trends, health care will undergo five transformations. First, production of medical knowledge and advancements in medical and surgical procedures will undergo a transformation from its current state of being driven by “serendipity” and small samples of homogenous populations to one that will be based on large data sets and their analyses (referred to as big data). Second, diseases will undergo a change in their taxonomy: at present, diseases are classified based on symptomatology: in future, diseases will be classified based on their genetic and molecular signatures and genetic and gene-environmental interactions that relate to their causes of occurrence. Third, pharmacological discoveries will be based on systematic innovations and development of new technologies. Leroy Hood (2013) has argued that biology will drive technology will drive analyses and new idea generation and this will set up a cycle (Hood??). Hence, the proponents of systems medicine argue that in future, discoveries in Medicine and health sciences will likely to be less driven by serendipity and more driven by emphasis on hypotheses generation that will be systematically invesigated. Fourth, delivery of health care, at this time, is centred on clinics & hospitals; in future, with empowered patients and focus on wellness,  provision of health will increasingly shift from hospitals and clinics to the home and workplaces where patients spend most of their time, and patients will take more ownerships of their health status. Fifth, the focus of health care delivery will shift from care of the diseased to wellness care. This will lead to the emergence of a new class of healthcare industry based on "wellness care" and "keeping people healthy” so that transition probability of a healthy person to a diseased state would be “diagnosed early” and resources will be spent to “keep people healthy as long as possible”. 

Such changes would form the basis of P4 health care; the four “P”s include:  personalised, preventive, predictive, and participatory health care. Personalised health care would mean that analysis of big data and "data cloud" for each person will lead to finer classification and stratification of patients based on molecular signatures with respect to their disease progression and prognosis and likelihood of development of disease and complication. For example, by identifying gene signatures and network patterns, it'd be possible to stratify an individual patient whether he will develop complications of type II diabetes and indeed, the typology of diabetes will change as well, and more subtypes will be identified and these subtypes will then determine the course of treatment and prognosis. This is also the basis of precision medicine. As systems medicine has focused on identifying the network of different genes, molecules, cells, and organs, the proponents of systems medicine argue that transition from a state of health to a state of illness is explained by a change in the network; if this network effect were to be studied and manipulated it would mean that the disease conditions could be either “reversed” in their earlier stages of kept from occurring as long as is feasible (“predictive” and “preventive”). “Participatory" indicates that patients will ncreasingly take part actively by self measuring and providing data and connecting with each other through networks.

Hood (2017) has argued that in 2016, P4 medicine is at a "tipping point" \cite{Hood:2017eo}. Malcolm Gladwell (2006) has described the phrase "tipping point" in his book by the same name as a phenomenon where a slow growing idea at a point in time gets adopted by majority population and spreads rapidly \cite{gladwell2006tipping} . Hood (2017) has predicted that "P4 medicine” will help to model transition from health to disease state and therefore enable earlier detection of diseases and their halting will lead to emergence of, what he has termed as "scientific wellness". The term “predictive” in the connotation of P4 medicine and systems medicine indicates that as the genetic risk for diseases can be estimated for most diseases, these would enable model the transition of a healthy person to a diseased person and with the assumption, if that were be determined "early enough” in the pathogenesis of a disease condition, then it would be possible to generate therapy or approaches that would prevent the emergence of disease from wellness.

In order to assess the validity of P4 approach, this argument, Hood et.al. (2016)  collected personal data for 108 individuals over a 9-month period. The data included whole genome sequences; clinical tests, metabolomes, proteomes, and microbiomes at three time points (xxx, xxx, xxxx); and they also tracked daily activities of the 108 participants . Using all of these data, they generated a correlation network to identify communities of related analytes associated with physiology and disease. Connectivity within analyte communities enabled the identification of known and candidate biomarkers (e.g., gamma-glutamyltyrosine was densely interconnected with clinical analytes for cardiometabolic disease). They calculated polygenic scores from genome-wide association studies (GWAS) for 127 traits and diseases, and used these to discover molecular correlates of polygenic risk (e.g., genetic risk for inflammatory bowel disease was negatively correlated with plasma cystine). They used behavioral coaching informed by personal data that was designed to help participants to improve clinical biomarkers. The results suggest that measurement of personal data clouds over time can improve our understanding of health and disease, including early transitions to disease states. 

Participatory health care refers to the care process where patients and doctors form a therapeutic alliance where patients bring in their "expertise" of the disease process and form their own alliances not only with the providers but also with other patients using digital social media. In participatory health, patients and physicians form an equal level partnerships in managing the disease process.

Nicola Bragazzi (2013) has described this as P6 medicine rather than P4 medicine  \cite{Bragazzi:2013is}. Bragazzi has discussed the case study of an Italian deisgner Salvatore Iaconesi, who was diagnosed with brain tumour and he decided to open up his medical records and details to the world using his weblog and allowed anyone with an interest in his history to "find a cure" \cite{Anonymous:g}.  Bragazzi has argued that incorporating patient perspective in treatment planning is likely to improve the process of care as patients are experts on their own right about their clinical conditions. Citing the case study of Iaconesi, he has put forward his hypothesis that medical care has transitioned from P0 through P3, P4, P5 and P6 models of care. P0 medicine is physician-centred paternalistic model of care where the patient and the patient's viewpoint was not taken into consideration. P3 model of care was where the patient, the physician and the pathology were the three main considerations in patient care and diagnosis. Here too, the treatment or care was not patient centric. P4 care is about personalised, predicive, preventive, and participatory medicine, where the care process is patient-centric, where patients use social networking and digital technologies to gain better understandng about the disease process and share therapy. Personalised medicine takes into acocunt the advances in systems medicine and genomics and digital technology to create a "cloud of data" around the patient that can be analysed; predctive therapy is where networks of information would be used to develop predictions about the course of action of the disease. Preventive medicine in this context is about understanding the possible course of the disease and specifically, transition from healthy state to disease state and understanding the changes in the network and development of strategies to address these isues. Bragazzi discusses P5 medicine as elements of P4 medicine plus psycho-cognitive medicine where the patient psychological reactions and psychological profiles determine the care process and are taken into consideration. P6 extends the concept of P4, and P5 to the domain of public medical care where the team of caregivers are expanded by including everyone in the world or the disease process is publicised, as Salvatore Iaconesi had done. P6 is the combination of the new technology to make diseases more of a public domain ownership thanks to emergent new technologies, and it therefore behooves that physicians take a more wellness focus rather than cure illnesses. Final Conclusion. -- Medicine has undergone a transition from P0 to P6 medicine and has become patient-centric. Reasoning. -- Inclusion of patient perspective benefits the patient and allows for better care because of therapeutic alliance and patient as an expert + issues around cancer diagnosis and communication by physicians particularly for the adolesents and young adults whose compliance with the treatment and clinical course can be less than optimal; evidence. -- that medical care has shifted from a focus on physicians to patient-centric and further patients are taking advantage of the digital media is further evidenced by the case of Savatore Iaconesi; critique of hte study. -- this study highlighted using one case study how medical care has undergone changes, No direct evidence was established in support of this change. questions. -- what are some of the best ways to establish or capture the nature of these changes? 

In explaining what constitutes evidence based medicine, the existing paradigm of clinical care, Sackett et.al. (1996) wrote that evidence based medicine was about incorporating the patient perspective in the process of care

\cite{sackett1996evidence}. But in describing that process, the participatory nature of the physician-patient interaction was not clear. This was in the so-called web-2.0 era when social networking tools as we know them today did not exist, nor was access to the Internet as nearly ubiquitous as it is today. Susannah Fox (2007) has argued that the two major drivers are availability of broadband and personal motivation.  Availability of home broadband is a determinant for Internet access. Those with chronic conditions are more likely to search for internet based health information. those with recent diagnoses are more likely to engage with their doctors on the information they identified on the net.  Pew's 2007 Internet Life project found that despite wide availability of health related information, doctors were stil main source of information for the patients. Only three percent reported that they were harmed by information they received online \cite{fox2008engaged}. 

Dave deBronkert (famously known as "e-patient Dave", 2013) is perhaps the most famous example of an e-patient in this context where patients as partners in care is increasingly gaining currency . deBronkert has narrated a personal experience in the transition of care paradigms where patients were seen as passive partners in care so that the physicians would arrive at “clinical decisions” with . When he first wrote about his comments about medical record  in a blog, Boston Globe, a newpaper in the US questioned his authority or right to write about something he was not supposed to know. He had renal cell carcinoma with multiple metastases and fractured femur in 2009. He underwent nephrectomy. He has argued what is value in the context of medicine from a patient's perspective.  Awareness of status (he did not know at the time of his diagnosis that he had cancer, a "spot" in his Xray was the diagnostic marker); accuracy of diagnosis - his doctors used both radiological findings and biopsy to confirm the diagnosis;  he received state of the art treatment that are denied to most people he knows; his surgical & clinical care was excellent. Among the system varialbles, he has listed access to care, access to information, choice of provider. Beyond systemic and instutitional issues, he listed that his being informed and engaged helped him. He has defined value as creative destruction or disruptive innovation. He compares this with the desktop publishing that Mac brought about. In the early days, Mac's desktop publishing provided metrics and measurements and the laser printers were able to print out pages but the printers and typesetter were able to do better jobs. However, stakholders and end users liked the desktop publishing more than the printers' jobs.