Journal of Health Care Communications Open Access

Keywords

Patient-physician always-on online communication and advice; Patient negative, positive and global health status; Primary care medicine health broad-spectrum delivery model; Life and health indices and scientific biomedical secular tendencies; Intelligent mobile healthcare information network; Patient health reserve self-enhancement and safeguard; Healthcare quality and cost improvement

Introduction

Historical premises

In the 5^th-century BC, standard Euryphon’s Cnidus school of primary care (PC) and general medical (GM) science concentrated on disease classification, grouped by symptoms and syndromes to organize diagnosis and therapy. Meanwhile, Hippocrates’ Cos school of PC-GM art focused on 1) observation of individual and environment, recorded in case-histories and 2) reasoning for guidance in diagnosis, prognosis, prevention and therapy [1-7]. Individual health normalcy was an initial experience, while the healing powers of nature battled one’s sickness. The general physician (GP) nurtured and preserved the individual’s positive (+) health enhancer factors and states, protected him from negative (-) health risk factors, and alleviated his suffering and cured his diseases [8,9]. According to the goddess ‘Hygeia’, health was the natural order of things to which man is entitled if life is governed wisely. The function of PC-GM was to discover and teach the laws that will ensure health. The followers of the god ‘Asclepius’ believed that the GP’s key role is to be a healer, replacing Hygeia cult in the 3rd century BC. Since then, GPs mostly treat patient disease and reactively restore health by medicating or operating. However, treating disease is not the same thing as creating proactively health. Health is the expression of the way in which the individual responds and adapts to the challenges met in everyday life, and has been valued as 90% of one’s happiness [1].

In the 2nd-century AD, Galen, wrote, “Health is such a condition in which we neither suffer pain nor are hindered in the functions of daily life.” He preserved patient health by carefully directing attention to “air, cleanliness, exercise, food, drink, occupation, sleep, sexual life, and emotions.” The preservation and attainment of health is the moral responsibility of the individual [7-9]. Galen stated, “Given a congenitally sound constitution and a politically free situation, an individual could -with recurring effort and constant attention- attain health.” He championed human choice and free will for everything. “Humans alone have the capacity to modify their feelings by choosing responses, activities, and regimens, which will make moderation a reality as well as an ideal [1].” In the middle ages, the Hippocratic concept of individual medicine was replaced by that of community medicine. In the 1600s, Newton used the scientific method as an iterating cycle of Bacon’s empirical and Descartes’ rational steps in the pursuit of objectivity [2,3,10], guiding Sydenham to link the Hippocratic patient’s observation approach with the Euryphon focus on disease classification. Sauvages patho-nosology science still confusing symptoms with diseases, was not useful, emphasizing clinical phenomenology, evading the conflicting anatomic, physiologic, and etiologic speculative systems [11-13]. A similar nosology is still being used in diagnosing patient mental disorders, with poorly recordable, measurable, and reproducible factors regarding etio-pathogeneses [5,11-14].

In 1760, democratic, scientific and industrial revolutions began to increase freedoms, knowledge-technologies, and life-health standards in some western nations [15,16]. The French-style general hospital isolated patients from their PC environment for specialized critical clinical-surgical secondary level care, raising efficiency, while some ones evolved to German-style institutes for more specialized tertiary level care and research [2,10]. The birth of thousands of somatic diseases, hundreds of psychic and dozens of psychosomatic disorders, broke down the unified individual mind-body health concept [17,18]. Thus, the fragmented PC-GM could not progress scientific and technologically in the patient’s global and + health, as much as it did it in the hospital care of his somatic diseases [19-25].

Present premises

In 2013, we designed a 30 year US research program for quality and cost improvement of healthcare via measurement of patient global bioecono-psychosocial (+ ± -) health outcome using e-health record and sociobio-sensed data. Continued study and exchanges with experts have prompted us to clarify further the necessity for the creation of a patient global health clinical decision support system (CDSS), using health information technologies (HIT), to strengthen our Western/ US PC-GM [26]. With respect to the enhancement and preservation of the healthiest patient, we doubt the adequacy of the Hippocrates’ individual-based PC and Euryphon’s science GM models, reduced 2200 years ago to handle mainly patients’ somatic diseases and risks, and 200 years ago to porter the hospital technological critical care, and manage the uncritical PC. However, upgrading the original Hippocratic PC human health broad-spectrum and Euryphon’s GM science can permit us to create a patient global health index, classification, intelligence and advice mobile HIT/CDSS managed by our GPnurse team.

Objective

Our objective here is to justify more historical and logically the scientific need of a US broader model of PC’s health delivery and GM’s scientific research and engineer further our health intelligence mobile HIT/CDSS algorithm.

Methods

Study design and tasks

We made observational analyses of 194 nations (world population), in a ‘quasi-experimental’ evaluation of the intervention of the democratic-scientific-industrial revolution policies since 1760, assessing on. We assessed baseline and post-intervention outcomes values and trends by numerical comparisons between 1750 and 1900, 1957, 2015, using 106 variables of life-support, healthcare, biomedical and info-medical models, methods, knowledge and technologies in the following two tasks:

1. Quantitative cohort study of outcomes of global life and health population indices from 1750 to 2014, by percent of change of 90 indices between both years. It included a comparison of longitudinal outcomes by US trends 1900 to 1956 vs. 1957 to 2014, and of a cross-section contrast in 2014, of the US value per index vs. the best value of reference of the other 27 most developed nations, with non-probabilistic contrasts [27-31].

2. Qualitative longitudinal study of scientific results with 16 variables on global healthcare problems with scientific discoveries of etio-pathogenesis and preventive-therapeutic knowledge and technologies 1750 to 2015, by nation and year of origin, application in the US and world. It included a comparison of the percents of US vs. global achievements 1900 to 1956 vs. 1957 to 2015 periods, with non-probabilistic contrasts [32, 33].

We engineered our PC-GM delivery model on the bases of our conceptual premises [34-48] and empirical results of our first two tasks, integrating healthcare main components defragmented 1760 to 2015 in two more tasks.

3. Searching for new relations of principal components, levels and elements via system analysis and categorization by analogy-making, we optimized our preliminary CDSS PC-GM delivery model solution to amplify the patient- GP communication through HIT apps {e-health record (EHR), wireless-sensing wearables of the patient internal/ external milieu, intelligent mobile smartphone-computer networks}.

4. Developing further the main multi-algorithm-components, scale-levels and element-variables of our preliminary broad-spectrum health-metrics of the patient’s global health status and factors {index and classification of +health states, enhancer factors, besides the - health or disease states, and risk factors}.

5. Details of our preliminary HIT/CDSS and broad-spectrum health-metrics can be found in our paper of 2013 [26].

Limitations of the study

In the two first tasks, we were obliged to estimate for Table 1 some world/US populations’ life and health indices for the years 1750, 1900, and even 1957, absent in the Universities of Pennsylvania, Yale and Miami Libraries’ Databases and Web sources in 2010- 2016. We estimated these by analogy with Maddison and other indirect econometric methods for incomplete pre-modern historical series (even for the year 1 AD) [49-58]. We marked these estimates in the table, so the accurate analyses of some trends are limited. We think that is better to have than to lack now these first modest estimates by the expert method, which can be adjusted further iteratively with more information and other methods. For the Boxes 1-3 a selection bias of healthcare advances’ sources in English language, overestimating slightly the US percents of advances in 1957-2015, was verified comparing percent with the national institutions of 210 Nobel Prize laureates 1901 to 1956 and 1957 to 2015. We had heuristic limitations in the last two tasks, in operational system and mathematical research, which require research of other professionals.

Table 1: Impact of the scientific revolution in the long-term trends of life and health in the world in 1760-2014 and in the US in 1900-1957-2014.

Results

Impact of the democratic-scientific-industrial revolutions in the life and the health of the world

Table 1 shows how, since 1760 modern human development in the United Kingdom (UK), France, US, Germany, and other nations, accelerated life and health growth, allowing liberation from global main disease’s risk factors: extreme oppression, inequality, hunger, poverty, ignorance [46] and dystrophy, distressing the poorest class, 99% of world population in 1750. Dirt, pestilence, wars and natural disasters, affected and prevailed in affluent and poorest classes. These 10 hazards caused most premature deaths, suffering and disabilities by nutritional, infectious and chronic diseases, and injuries, before the 26 years of average life expectancy at birth (ALE-B). The percents of change followed empirically Nobelist Fogel’s ‘human techno-physiological evolution/physio-capital enhancement theory. Rising freedoms fostered the growth of education, scientific-technologies, and productivity of agro-artisanal industries, and food output allowed increased daily intake of required nutrients per person, reducing the chronic caloric-protean malnutrition. Former beggars without enough energy (25% of labor force) began to work, increasing the standards of living and health of the affluent 1% and a growing middle class, but much more so of the declining poorest class [49,50].

Better nutrition improved the health and longevity, allowing future parents to reproduce with bodies that were more robust. Better education increased their awareness of and ability to assume responsibly for their lives, environment, and health. Parental health led to more physiological conceptions, pregnancies, and less intrauterine nutritional, traumatic, infectious and other ecological insults to the embryos-fetuses. Newborns were sturdier and breast-fed more often, protecting child health. New contraceptive and safer abortion methods decreased the gross -and adolescent- birthrates and mean fertilities. Hospital deliveries reduced neonatal, infant and maternal mortality rates (IMR, MMR). Cultureconosocio-psychoneuro-biophysiological health reserve increased with each new generation, resisted acute diseases and postponed the onset of chronic diseases, their complications and deaths, increasing overall/disease-free survival rates, and reducing adult mortality rates too. Gross and healthy ALE-B (HALE-B) trends grew rapidly 1900 to 2014, but their 1900 to 1956 fastest-growing trends, slightly slowed up to 2014, from 28-51 years to 71 years and 16-40 years to 62 years [56,58,61,65,76,77,80,91,92]. This slowdown concurred with a fast rise of the quality, equity, survival and cost of care rates on high incidence rates of most lethal and disabling chronic diseases and injuries, stagnated along with high incidence rates of chronic disorders and risks in infants, children and teenagers.

Impact of the democratic-scientific-industrial revolutions in the life and the health of the US

The US did well increasing its population’s access to all types of over 150 human rights, though very few civil ones still need attention. Thus, the US grew its middle class and equity, reduced its poor class and achieved top world years of schooling. In 1957- 2013, US top world gross domestic product (GDP) rose nine-fold [79]; share of GDP tripled for health (excluding 5% lost by patients unable to work and on welfare), halved for defense, and slightly rose for education and research. Health expenses threaten to reach nearly a third of GDP in 2040 [50]. Caloric intakes per person and body mass index are on average excessive, while safe drinking water is about to reach 100% in rural/urban areas. The US lost the top world human development index with its slowed rise of ALE-B, due to a decelerated rate of fall in IMR, because a braked fall of birth rates in adolescent pregnant, preterm, and percent of low birth weight newborns [105-111], and a slowed fall in adult 15-59 years mortality rates, mainly in males [93,112]. Though the US kept the world’s first rank on ALE-B standardized by fatal injuries, ALE over 74 years old [85,112], and self-perceived best health status in 1980-2012 [86], its ALE-B and HALE-B ranking 7th in 1957 worsened five-fold mostly in 1990-2014 to the 35th positions [59-65,76,77,91-93,100,112]. These anomalies seem related with high incidence rates of chronic cultureconosociopsychoneuro- biophysiological disorders, addictions, violence, HIV/AIDS, obesity and lifestyle factors, disturbing infant, child and teen health [48-50, 59-63,82-86,91-93,100-116], and US involvement in six wars overseas 1950-2014, while freedom, GDP, ALEs, and other life-health standards in Europe, Canada, Japan, Australia, Israel, and rest of the world improved. Access to the world’s highest standards and technologies of emergent/critical hospital care, community-based PC, diagnosis, therapy, rehabilitation, prevention, reproductive risk, peri-natal, infant medical facilities continue to increase in the US.

Progress of medicine and health care with sciences, industries and business in the world and US

Boxes 1-3 show how the biomedical sciences in two-dozen advanced nations, created new theories, models, methods, and technologies for health promotion and disease preventiontherapeutics, empowering individual and population health 1760 to 2015. Box 1 shows that scarcely 29% (10 of 35) of the main advances in etio-pathogenesis and protective measures of infectious, nutritional, cancerous, and genetic diseases were discovered by US institutions 1900 to 1956, while 86% (24/28) of the main advances including also metabolic, cardiovascular, mental, and other chronic diseases were found in the US 1957 to 2015. Box 2 displays how 1900 to 1956, 37% (26/70) of new clinical-surgical diagnosis, therapeutic, and rehabilitation means for infectious and chronic diseases were accomplished in the US, whereas Box 3 reveals that 75% (49/65) of all those advances 1957 to 2015 were discovered in the US. Notably, the US institutions 1901 to 1956, achieved 31% (22 of 70) of Nobel Prize laureates in physiology-medicine among 17 nations, while 1957 to 2015 accomplished 59% (83/140) among 13 nations [117-124].

Box 1: Development of scientific theories, vaccines, and sanitation on the health of the US and the world in 1760-1956 and in 1957-2015.

Box 2: Development of scientific theories, medicines, and procedures on the health of the US and the world in 1760-1956.

Box 3: Developmentof scientific theories, medicines, and procedures on the health of the US and the world in 1957-2015.

In 1747, Lind began scientific controlled preventive trials. In 1761, based on Vesalius, Harvey and others’ post-mortem pathoanatomic and pre-mortem patho-physiologic findings, disease was no longer considered as only the clinical manifestations experienced by the patient and GP. From 1800 to 1820, Bichat, Broussais, Pinel, and Cabanis assisted the birth of ‘internal medicine’ [1,5,11-13], disease now considered as the organ and tissue anatomic ‘lesion’ or physiologic ‘disturbance’ caused by ‘modifiers’. Louis started controlled therapeutic trials. Based on Darwin’s theory of evolution through adaptation, Bernard developed the Hippocratic dictum that health is universal sympathy. He argued that life balance and fitness depend of constant multiple interplays between the external and internal milieu of the patient. Virchow stated, “Disease is the altered vital state of larger or smaller number of cells or cell-territories; not life under abnormal conditions, not the disturbance as such, engenders a disease, rather disease begins with the insufficiency of the regulatory apparatuses [1,5,11-13].” A more accurate classification of diseases increased the probabilities of exact diagnosis, therapy and cure. Hundreds of somatic diseases, based on thousands of patho-morphophysiological biophysico-chemical ‘inner-body macro/micro-parameters’ were found earlier than an isolated from dozens of psychic and psychosomatic disorders, grounded on hundreds of not well-recordable, measurable and reproducible ‘outer-cultureconosocial and inner-psychoneurological parameters’. In 1855-1885, Snow, Hirsch, Koch and Pasteur’s contributions on germs’ transmission began ‘Medicine’s first golden era of hygiene-epidemiology, microbiology-immunology, and physiology-cell biology’ [124]. The patient’s history and exam, correlated with lab findings, completed the clinical method, with the pathologist arbiter of the true diagnosis, therapy and pathogenesis [2,10].

In the eve of the 1900s, the GP rescued a PC-GM short-range health examination, pursuing more somatic than psychic/psychosomatic diseases [125-128]. Cannon developed Bernard ‘homeostasis’, as the condition of actively sustained equilibrium prevailing in the organism by neuroendocrine regulatory mechanisms. Biophysicochemical labs appeared for diabetes, cancer, cardiovascular, and other diseases’ applied and basic research, beginning a boom of discoveries of theories and technologies’ inventions and innovations, starting ‘Medicine’s second golden era of biophysical imaging-radiation, chemotherapy, biochemical genetic-molecular and micro, endoscopic, transplantation surgery’. These advances sowed the seeds of ‘evidence-based medicine’, diverting attention from individual living processes, and causing a self-imposed segregation from the cultureconosocio-psychological health dimensions. This truncated clinical method focusing mainly on diseases and risks, restored the patient’s physiological equilibrium, excluding +health states, enhancer factors, cultureconosociopsychoneuro- biophysiological harmony, and global quantity and quality of health [1,2,5,17-26]. Staging classification in cancer advised according to prognostic evolutionary factors the spectrum and strength of the therapies. In 1946, Hill began randomized controlled trials (RCTs), and cross-section/cohort controlled surveys, empowering with probability errors and epidemiologic criteria the proof of cause-effect relationships judged by a biostatistician. Small and middle-size RCTs need stratification by bad or - prognostic factors of patients’ population/sample before random allocation of intervention to trial and control groups, or after in the outcome analysis, rising groups homogeneity to detect intervention effects with statistical testing. In the 1980s, began ‘Medicine’s third golden era of personalized, precision, telemedicine, robotic-surgery, tele-education / research, with genetic, biotechnology, computer, internet, and mobile HIT apps’ [2,10].

Optimizing the individual-based PC-GM delivery and science models with our HIT/CDSS

Our broad PC-GM HIT/CDSS fused Hippocrates’ PC delivery and Euryphon’s GM science models with Snow’s transmission theory (1855), Pasteur’s germ theory (1862), Flexner’s biomedical model (1913), Watson and Crick’s biomolecular theory (1953), Backer’s patient health equation, Engel’s biopsychosocial model (1977), Antonovski’s salutogenesis concept (1979), McWhinney’s patientcentered method (1983), Foss and Rothenberg’s info-medical model (1987), Hollnagel and Malterud’s health resource/risk balance (1995), Archimedes’ simulation for control of diabetes risks (2002), and Collins and Varmus’s personalized/precision medicine for cancer and diabetes (2015) [2,26,129-135]. Since the 1800s, the PC-GM had no differentiated technological research field, and stayed only with a partial-health integrated care [136,137]. The discovery of new + health enhancer factors and states, interacting with - health risks and diseases, to materialize the patient global health index and classification, are GP-nurse teams’ new differentiated and integrated high-technological research fields. It is time to re-evaluate the best 60 year tools created by GP-nurse teams with psychologists, sociologists and mathematicians on patient’s health-metrics [26]. These teams must measure patient global (+ ± -) health status, as engineers and scientists use to do with every object of study [26]. The patient needs this automated health assessment, intelligence and advice HIT/CDSS to re-build its individuality and re-engage him in his own PC. It shall be always ready to work when he consults the GP-nurse team, between visits and virtual exchanges, wanting to know how his health is and what to do to his freedom to choose. Practice-based research networks must strengthen the HIT/ CDSS function and integrate it in family PC programs [26,138]. It shall actively ‘transmit’ + health potentiating factors and states throughout the patient’s life, fostering and preserving his health reserve free from potential subclinical diseases, and decreasing the hazards and costs of hospital care [5].

The US PC-GM shall be potentiated with our HIT/CDSS, if we individualize +health enhancement and -health safeguard, and search for the healthiest social milieu, life-styles, as well as immune-defenses, genes, and biomolecules. This must accelerate the enhancement of the patient cultureconosociopsychoneuro- biophysiological (+ ± -) health reserve, slowing its deterioration. The private-charity-public sectors ought to develop research programs on patient’s +health causes, enhancer factors and states. It would facilitate support of richer global health status decisions on PC-GM interventions by the patient, growth of GP-nurse team, and a better managerial evaluation. Our HIT/CDSS shall work in parallel and on personalized+and global health reserve enhancement, too abstractedly done by public health programs now. It shall complement novel community-based PC delivery models, i.e., medical home, retail clinics protocol-based for conditions handled by nursing software, and digitized models focusing risks and diseases monitoring and intervention. Potentiating tele-health providers, smartphone-based apps, networks, and consumer-oriented devices, a HIT/CDSS shall help enrich a personal ‘always-on’ PC-GM [139,140].

Toward a patient multi-level-variable global health index and classification algorithm

Figure 1 depicts an algorithm for our global health measures of 2013 [26]. We defined a comprehensive + and -health matrix with symptoms, signs, milieu, and lab variables, as well as a research path to build an integral health semiology, nosology, algorithms and equations, more ambitious than simply mirroring opposite taxonomies to the current ones of thousands of symptoms and diseases. These tools shall offer shortest numerical and categorical answers to the GP and the patient’s question about his degree of health. This query usually involves a GP synthetic judgment of dozens of present and past patient self-perceived symptoms, feelings, and biosocial milieu variables referred, plus dozens of objective signs, factors, lab, and milieu parameters observed. Our HIT/ CDSS shall give more exact and standardized answers than the ones the GP can process mentally in an ordinal scale of gross qualities as: excellent, good, regular, bad, and worst health. Our model of multiple organization levels of patient’s global health is for best assisting the reasoning of the GP and patient by using thousands, rather than dozens of interacting variables at the memory, using linear and non-linear functions and equations. Not viable for the GP’s brain, such ‘homeodynamic’ model [131] needs automated mathematical software acting on an expanded patient lifelong EHR database, running in a secure smartphone-computer network. It shall be fed by biosocial sensors (in watch, belt, glasses with camera, shoes, blood monitors and other wearables) indicating trends and fluctuations in personalized cultureconosocio-psychoneurobiophysiological parameters. It must work according to patient’s life-cycle stage, gender, environment and time, assisting him and the GP-nurse team in managing the complex healthcare of his individuality [26].

Figure 1: Patient global health index (GHI) and classification (GHC) rules of inference to optimize health reserve potential growth.

Discussion

Impacts of freedoms, scientific-technologies, industries, and businesses on health

From 1855 to 2015, the US and Western developed nations’ main axes of modernization have allowed achieve the ‘Greatest Enhancement of Health and other Living Standards on Earth’. However, 1957 to 2015 trends of quality, equity, survival, and cost of hospital care rates grew exponentially, while high-lethal chronic diseases/injuries’ mortality and incidence rates, and cultureconosocio-psychoneuro-biophysiological distresses and risks’ incidence rates declined logarithmically in the best health systems [85-87,93,95-99, 102-104]. This seems due to the forgotten value and power of the individualized health information [131,132]. This is increasingly being used by digitally savvy ‘millennials’, adults, and even ‘boomers’, through the explosion of social networks, online websites and HIT biosensing apps, overloading self-individual PC [141] with nonwell evaluated health promotion information, in relation to the well-focused disease prevention-therapeutics means with besttested biomedical-biopharmaceutical technologies. With our individual-based broad-spectrum health delivery PC system to measure, enhance, and safeguard his health reserve, upgraded with information sciences/technologies, we can evaluate/reduce objectively the redundant health information overload, and the possibility of ‘cyberchondria’ [141], in our young and adult individuals.

We read frequently, “The US healthcare system is broken and must be fixed [142]”. Nobelist Fogel suggested increasing access to the best standard and technology community-based health promotion, lifestyle change, preventive PC, and intensive outreach programs [49, 50]. Thus, the US shall re-boost a part of the slowed rising trends of ALEs and HALEs. The problem is that the current PC-GM model is of the disease era in the 1800s [143], when personal hygiene was subsumed by public hygiene and preventive medicine of groups, and abandoned the study of the healthy individual, life processes, lifestyles, and hygiene. Later, mental hygiene became applied psychology and preventive psychiatry, as bodily hygiene became applied physiology and preventive medicine [144]. The 200 year successful diseasetherapy oriented hospital care [36,40,85,97,98] needs harmonization with a long-range view of health-centered individual-based PC-GM to increase patient quantity and quality of health reserve, even in the ‘absence’ of subclinical diseases and risks [26]. Although much suffering is relieved and many diseases are regressed or stabilized, yet many risks of diseases and injuries are neither well-known nor well-controlled yet.

We think that what not only the US but all other world healthcare systems have broken is the concept of individual cultureconosocio-psychoneuro-biophysiological (+ ± -) health reserve. Its upgraded reintegration could accelerate the + health outcomes and broaden the PC clinical history, method and delivery model scopes to the original Hippocratic ones. The GP left behind the logical PC-GM path to enhance the patient + health enhancement factors and states, because as disease and other failures of adaptation are obvious and often dramatic, whereas health and fitness are considered the ‘normal’ state and therefore unnoticed [1], it is not surprising that he tended to be very busy and focused in the restoration and protection of the patient’s biophysiological health. While this happened, public health specialists absorbed these +health promotion tasks, but at the abstract level of diverse populations of patients. The US patient needs personalized health information by a HIT/CDSS built with Euryphon’s GM science, to enable him to administer in a wiser and healthier way, the amazing freedom, knowledge, and wealth that he owns.

HIT/CDSS improvement of population healthmetrics and randomized clinical trials efficiency

The HIT/CDSS software for the US patient global health index values calculation and profile identification could be programmed by a multidisciplinary research team with GPs, nurses and other professionals [26], supported by the National Collaborative for Improving Primary Care through Industrial and Systems Engineering, Patient-Centered Outcomes Research Institute, and Primary Care Extension Program [138]. It could run experimentally in supercomputers of the National Institutes of Health Center for HIT and Centers for Disease Control/Prevention. The software shall receive big data from the patient’s EHR and sensors through secure GP-patient smartphones-computer network, upon a standardized personalized health data matrix created by the GPnurse research team. The software response in near real-time, to each patient enquiry or virtual consultation to the GP-nurse team, could give also an instantaneous bottom-up more real health aggregate index and profile results to the city, county, state, CDC, and US Department of Health [145].

Some have criticized the effectiveness of general health checks, screening, and lifestyle counseling in reducing chronic disease and injury mortality and even incidence [146-149]. Our patient global health index, profile and +health enhancers, can help perfect the PC health promotion RCTs, causal-healthgenic surveys, preventive and even therapeutic RCTs, mainly immunologic and genetic, and etio-pathogenic case-control/exposed-control surveys [150]. New good or +prognostic and health enhancer factors discovered could help balance and reduce better the bias allowed by randomized designs and analyses of RCT trials and surveys, contributing to higher homogeneity of baseline and outcome test and control groups through a broader prognostic stratification. This will allow more valid research conclusions about new intervention effects, new individual causal factors of +health, and healthy lifestyles. Thus, our research program also offers new means for the enhancement and safeguard of the patient health reserve.

Conclusion and Implications

We have argued the necessity of an individual health broadspectrum HIT/CDSS, fusing the upgraded Hippocrates’ PC delivery and Euryphon’s GM science models with the models of the past 160 years. Giving personalized mobile integral health intelligence to the individual, empowering self-health induction with prompt data-exchange shall amplify healthcare communication with the GP-nurse team and potentiate healthier outcomes. This can make possible, very necessary medical work before the patient is distressed, suffers, or is disabled.

A more aware patient can better solve -health weaknesses, build up +health strengths, and balance his cultureconosociopsychoneuro- biophysiological (- ± +) ‘health reserve’, enriching and guarding it supported by the GP-nurse team. Besides personalized/precise biomedical, pharmaceutical, genetic, and biomolecular means to reduce - health, we shall also research and use more the individualized healthy-lifestyle info tools to increase + and global health.

We have advanced our HIT/CDSS algorithm architecture to reopen the patient health scope of the non-critical PC-GM delivery model, and process his ‘entire life data’ resulting in automatic multi-level and variable global health results by mathematical software that shall be created. Measuring individual global health reserve with more information sciences/technologies, we can help evaluate/reduce objectively the health information overload of our ‘millennials’, adults, and even ‘boomers’.

It needs communities with rapid and secure access to Internet, EHR, wearable-sensors and smartphone-computers’ networks. Responses in near real-time to patient/GP enquiries and comments on enhancement and safeguard of patient global health output, could offer also automatically bottom-up more real health aggregate index and profile outcomes to local, state and US health departments. Patient global health index, profile, good or +prognostic and enhancer factors and states, besides debilitating - prognostic, risk factors and diseases, are crucial to all RCTs and surveys’ results validity. Searching for and testing new healthier-lifestyles is essential.

Our proposal is, through this research program, to encourage the progression of pleasant and optimal comprehensive wellness feelings, hyper-abilities, healthiest, and happiest states in each patient, as well as the regression or stabilization of even subclinical diseases and risk factors. Health economics benefits, always sought and valued, must result from this approach. Its effectiveness at improving quality of patient global healthcare and lowering its costs, would allow our nation’s wealth to be shared with other necessary priorities.

Acknowledgement

We are very grateful for the encouragement of medical historian Guenter B Risse of the UCSF/UWS to bring our PCGM HIT/CDSS of 2013 into routine patient-GP interaction; and for the kind suggestions of Past Presidents of WONCA, Chris van Weel of the Universities of Nijmegen/Australia, and Richard G Roberts of the University of Wisconsin, and James W. Mold, Chair, Committee on Advancing the Science of Family Medicine of the University of Oklahoma, and NAPCRG, to be cautious avoiding disruption of the successful patient- GP relationships. In addition, this paper reflects valuable teachings on multivariate analyses of visiting neurophysiologist Thalia Harmony of the UNAM-Querétaro in 1976-1977 and biostatistician John Fertig of Columbia University in 1976 and 1979. Finally, we are thankful with the help of the reviewers of this paper to be able to reach this improved version.

References

1. Dubos R (1959) Mirage of Health. Utopias, Progress, and Biological Change (1stedn) Harper, New York.
2. Stusser RJ (2012) Research Challenges of Primary Health Care Medicine Progress. UNESCO EOLSS, Paris.
3. Razis DV (1988) How progress has been achieved in medicine. Biomed Pharmacother 42: 625-627.
4. Fabrega H Jr (1997) Earliest phases in the evolution of sickness and healing. Med Anthropol Q 11:26-55.
5. Galdstone I (1953) The Epidemiology of Health. Health Education Council, 1st edn. New York Academy of Medicine Book, New York.
6. Biggart JH (1971) Cnidos v. Cos. Ulster Med J 41:1-9.
7. Temkin O (1973) “Health and Disease”. In Wiener PP, ed, Dictionary of the History of the Ideas. Charles Scribners and Sons, New York, Vol. II, 395-407.
8.  Burns CR (1975) "Diseases versus Healths: Some Legacies in the Philosophy of Modem Medical Science." In: Engelhardt and Spicker (eds), Evaluation and Explanation in the Biomedical Sciences. D. Reidel Publishing Co., Boston.
9. Burns CR (1976) The Nonnaturals: A Paradox in the Western Concept of Health. J Med Philosophy 1:3:202-211.
10. Stusser RJ (2006) Reflections on the scientific method in medicine. In MansourianBP,Wojtezak A, Mahfouz SM (eds), Medical Sciences. Encyclopedia of Life Support Systems. UNESCO-EOLSS Pub, Oxford. https://www.eolss.net
11. Engelhardt HT (1996) The Foundation of Bioethics, 2nd edn. Oxford University Press Inc, New York.
12. King LS (1964) The debt of modern medicine to the 18th century. JAMA 190:829-832.
13. Risse GB (1971) The quest for certainty in medicine: John Brown’s system of medicine in France. Bull History Med 45(1):1-12.
14. American Psychiatric Association (2015). DSM-5 Development.https://www.dsm5.org/Pages/Default.aspx Accessed 10 February 2016
15. Fogel RW (1986) Nutrition and the decline in mortality since 1700: Some preliminary findings. In Engerman and Gallman (eds.). Long-term Factors in American Economic Growth. Chicago: University of Chicago Press.
16. Fogel RW (1993) Nobel Prize Lecture in Economic Sciences: Economic Growth, Population Theory, and Physiology: The Bearing of Long-Term Processes on the Making of Economic Policy.
17. McWhinney IR (1986) Are we on the brink of a major transformation of clinical method? Canadian Med Ass 135(8):873-8.
18. McWhinney IR, Epstein RM, Freeman TR (2001) Rethinking somatization. Advanced Mind Body Med 17: 232-239.
19. Kass LR (1975) Regarding the end of medicine and the pursuit of health. Public Interest 40:11-42.
20. Schlenger WE (1976) A new framework for health. Inquiry 13:207-14.
21. Hollnagel H, Malterud K (2000) From risk factors to health resources in medical practice. Med Health Care Philos 3:257-64.
22. Stange KC (2009) A science of connectedness. Ann Fam Med 7:387-395.
23. Stusser RJ (2009) Reintegration could involve also improvement of the truncated clinical method. Ann Fam Med (March 29), e-letter.
24. Del Mar C (2009) Is primary care research a lost cause? BMJ 339:b4810.
25. Stusser RJ (2009) Neglected virgin areas in primary health care basic and applied research. BMJ,Nov 20, e-letter.
26. Stusser RJ, Dickey RA (2013) Quality and cost improvement of healthcare via complementary measurement and diagnosis of patient general health outcome using electronic health record data: research rationale and design. J Med Syst 37:9977.
27. Sigerist HE (1941) Medicine and human welfare. Yale University Press, New Haven.
28. World Health Organization (1946) Definition of health. Preamble to the Constitution of the World Health Organization as adopted by the International Health Conference.WHO, New York.
29. United Nations (1948) Universal declaration of human rights. UN Publ, New York.
30. United Nations (1954) Report on international definition and measurement of standards and levels of living. UN Publ (Doc. E/CN.5/299), New York.
31. United Nations (1961) International definition and measurement of levels of living. An interim guide.UN Publ (Doc. E/CN.3/270 Rev. 1 E/CN.5/353), New York.
32. Weatherall D (1995) Science and the Quiet Art. The Role of Medical Research in Health Care, 1st edn. WW Norton & Co, London.
33. Le Fanu J (2000) The Rise and Fall of Modern Medicine, 1st edn. Carrol& Graf Publ., Inc, New York.
34. United Nations (1953) The determinants and consequences of population trends. UN Publ., New York.
35. United Nations (1973) Determinants and consequences of population trends. UN Publ., New York.
36. McKeown T (1948) American medical services. Br J Soc Med2:77-105.
37. McKeown T (1976) The modern rise of population. London: Edward Arnold.
38. McKeown T (1979) The role of medicine: dream, mirage, or nemesis? Princeton University Press, Princeton.
39. McKeown T (1988) The origins of human disease. Basil Blackwell, Oxford.
40. Linder FE (1966) The health of the American people. Sci Am 214:21-9.
41. Preston SH (2007) The changing relation between mortality and level of economic development. Int J Epidemiol 36:484–490.
42. Fogel RW, Costa DL (1997) A theory of technophysio evolution, with some implications for forecasting population, health care costs, and pension costs. Demography 34:49-66.
43. Fogel RW (2003) Secular trends in physiological capital: implications for equity in health care. PerspectBiol Med 46(3 Suppl):S24-38.
44. Costa D(2013) Health and Economy in the United States from 1750 to the present. Natl Bu Econom Res, Working Paper 19685, Cambridge.
45. Pritchett L, Summers LH (1996) Wealthier is healthier. J Hum Resour 31:841-868.
46. Sachs JD (2005) The end of poverty. Economic possibilities for our time, 1st edn. Penguin Press, New York.
47. Everitt A, Roth G, Le Couteur D, et al (2005) Caloric restriction vs. drug therapy to delay the onset of aging diseases and extend life. Age 27:39-48.
48. Cutler D, Deaton A, Lleras-Muney A (2006) The determinants of mortality. J EconomPerspec 20:97-120.
49. Fogel RW (2004) The Escape from Hunger and Premature Death, 1700–2100: Europe, America, and the third world, 1st edn. Cambridge University Press, New York.
50. Fogel RW (2012) Explaining Long-Term Trends in Health and Longevity. Cambridge University Press, New York.
51. Kennedy P (1989) The rise and fall of the great powers. Economic change and military conflict from 1500 to 2000, 2nd edn.Vintage Books, New York.
52.  Landes DS (1999) The wealth and poverty of nations: why some are so rich and some so poor? 1st edn. WW Norton and Co., New York.
53. Sen A (1999) Development as freedom. 1stedn.Alfred A. Knopf, Inc, New York.
54. Clark G (2007) A farewell to alms. A brief economic history of the world, 1st ed. Princeton University Press, Princeton.
55.  Maddison A (2007) Contours of the World Economy, 1-2030. Essays in Macro-Economic History, 1st edn. Oxford University Press, Oxford.
56. 56. Mitchell BR (1975) European Historical Statistics 1750-1970. Macmillan, London.
57. 57. Mitchell BR (1995) International Historical Statistics: Africa, Asia and Oceania 1750-1988, 2nd rev. edn. Stockton, New York.
58. 58. Mitchell BR (1998) International Historical Statistics: The Americas 1750-1993, 4th edn. Macmillan, London.
59. World Health Organization (2000) The world health report 2000 — health systems: improving performance. WHO Publ., Geneva.
60. World Health Organization (2013) The world health reports 1995-2013
61. World Health Organization (2015) World Health Statistics 2015. WHO Publ., Geneva.
62. World Health Organization (2014) World Annual Health Statistics Reports 2006-2014.
63. World Health Organization (2014) Global status report on non-communicable diseases. WHO Press, Geneva.
64. United Nations (2008) Demographic Yearbook(s) 1948-2008, 1st-52nd Issue. UN Publ, New York.
65. United Nations (2009) Statistical Yearbook(s) 1948-2008, 1st-52nd Issue. UN Publ, New York.
66.  Freedom House (2015) Freedom in the world. Annual global survey of political-rights and civil-liberties 1973-2015.
67. Heritage Foundation (2015) Indexes of economic freedom. WCAS, 1995-2015.
68.  State of the World Liberty Project (2006), Free People, Free Market, Free Thought, Free Planet, 2006, 2014.
69. Howlader N, Noone AM, Krapcho M et al (eds) (2015) SEER Cancer Statistics Review, 1975-2012, National Cancer Institute. Bethesda, MD.
70. United Nations Children’s Fund and World Health Organization (2004) Low birth weight. Country, Regional and Global Estimates. UNICEF Editorial and Publications Section, New York.
71. United Nations Children’s Fund (2015) State of the World‘s Children Reports and Statistical Tables, 1990-2014. UNICEF Publ, New York.
72.  United Nations Population Fund (2014) State of World Population Reports and Statistical Tables 1998-2014, UNFPA Publ, New York.
73. United Nations Educational, Scientific and Cultural Organization (1957), Progress of literacy in various countries; World illiteracy at mid-century. Monographs on fundamental education VI, XI 1953, 1957. UNESCO Publ., Paris.
74. United Nations Educational, Scientific, and Cultural Organization (1999) Statistical Yearbook – Statistical Tables of Historical Data of Expenditures Research and Experimental Development. UNESCO, Paris.
75. Food and Agriculture Organization (2013) Statistical Yearbooks - World food and agriculture 2004-2013, FAO Publ, Rome.
76. Roberts WC (2001) Facts and ideas from anywhere. Proc (BaylUniv Med Cent) 14:199-208.
77. United Nations Development Program (UNDP) (2015) Annual Human Development Reports and Indicators from 1985-1990 to 2015. UNDP, New York.
78.  Stockholm International Peace Research Institute (2015) Global military expenditure yearbooks 1968-2015.
79.  Groningen Growth Development Center (2015) Total economy database; Angus Maddison historical statistics database, 2008.
80. University of California-Berkeley and Max Planck’s Institute for Demography Research (2015), Human mortality and life tables databases, 1800-2014.
81. World Life Expectancy (2015), Life expectancy in the World.
82. Preston SH (1976) Mortality Patterns in National Populations. Academic Press, New York.
83. Venkitachalam L, Wang K, Porath A; REACH Registry (2012) Global variation in the prevalence of elevated cholesterol in outpatients with established vascular disease or 3 cardiovascular risk factors according to national indices of economic development and health system performance. Circulation 125:1858-1869.
84. Gapminder Foundation (2010) Data on maternal mortality for 14 countries up to 200 years.
85.  Ohsfeldt RL, Schneider JE (2006) The Business of Health. The Role of Competition, Markets, and Regulation.American Enterprise Institute Press, Washington, D.C.
86.  Organization for Economic Cooperation and Development iLibrary (2015) OECD Health Statistics 1961-2014.
87. World Bank (2015) World Development Indicators 2009-2013.
88. Loudon I (1992) Death in Childbirth. An International Study.1st edn. Oxford University Press, New York.
89. Guttmacher Institute (2014) Advancing sexual and reproductive health worldwide through research, policy, analysis and public education.
90. Blencowe H, Cousens S, Oestergaard MZ (2012) National, regional, and worldwide estimates of preterm birth rates in the year 2010 with time trends since 1990 for selected countries: a systematic analysis and implications. Lancet 379:2162-2172.
91.  Salomon JA, Wang H, Freeman MK (2012) Healthy life expectancy for 187 countries, 1990-2010: a systematic analysis for the Global Burden Disease Study 2010. Lancet 380:2144-2162.
92. GBD 2013 DALYs and HALE Collaborators; Murray CJ, Barber RM, Foreman KJ (2015) Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013: quantifying the epidemiological transition. Lancet doi: 10.1016/S0140-6736(15)61340-X.
93. Rajaratnam JK, Marcus JR, Levin-Rector (2010) Worldwide mortality in men and women aged 15-59 years from 1970 to 2010: a systematic analysis. Lancet 375:1704-1720.
94. Stusser RJ, Dickey RA, Norris TE (2007) Enhancing global rural health utilizing comprehensive and electronic primary health and life care and research. Personal Working Paper, Havana-Hickory-Seattle.
95. Schieber GJ, Poullier JP (1987) Recent trends in international health care spending. Health Aff (Millwood) 6:105-112.
96. Anderson GF, Poullier JP (1999) Health spending, access, and outcomes: trends in industrialized countries. Health Aff (Millwood) 18:178-192.
97.  Kelley E (2007) Health, spending and the effort to improve quality in OECD countries: a review of the data. J R SocPromot Health 127:64-71.
98. White C (2007) Health care spending growth: how different is the United States from the rest of the OECD? Health Aff (Millwood) 26:154-161.
99.  Fuchs VR (2012) Major trends in the U.S. health economy since 1950. N Engl J Med 366:973-977.
100. Murray CJ, Atkinson C, Bhalla K; US Burden of Disease Collaborators (2013) The State of US Health, 1990-2010. Burden of Diseases, Injuries and Risk Factors. JAMA 310:591-608.
101. U.S. Bureau of the Census (1960) Historical Statistics of the United States, Colonial Times to 1957, Government Printing Office, Washington, D.C.
102. Allemani C, Weir HK, Carreira H; CONCORD Working Group (2015) Global surveillance of cancer survival 1995–2009: analysis of individual data for 25 676 887 patients from 279 population-based registries in 67 countries (CONCORD-2). Lancet 385:977-1010.
103. National Center for Health Statistics (2014) Health, United States, 2012-2014.CDC/NCHS, Hyattsville.
104. National Center for Health Statistics (2014) Mean Body Weight, Height, and Body Mass Index, United States 1960–2002. The National Health and Nutrition Examination Survey Program.Advanced Data from Vital and Health Statistics. No. 347, Oct. 27.
105. MacDorman MF, Mathews TJ (2009) The challenge of infant mortality: have we reached a plateau? Public Health Rep 124:670-681.
106. Stusser RJ (2009) Comments in US infant mortality plateau to the CDC/CCHIS/NCHS. Email sent to the author from Havana on 10/28-11/08.
107. MacDorman MF, Hoyert DL, Mathews TJ (2013) Recent declines in infant mortality in the United States, 2005-2011. NCHS Data Brief 120:1-8.
108. MacDorman MF, Mathews TJ (2013) CDC. Infant deaths - United States, 2005-2008. MMWR Surveill 62 Suppl 3:171-175.
109. Kvale K, Cronk C, Glysch R (2000) Racial disparities in African American and white infant mortality United States and Wisconsin, 1980 to 1998. WMJ 99:52-54.
110. Ventura SJ, Freedman MA (2000) Teenage childbearing in the United States, 1960-1997. Am J Prev Med 19(1 Suppl):18-25.
111. Drevenstedt GL, Crimmins EM, Vasunilashorn S (2008) The rise and fall of excess male infant mortality. ProcNatlAcadSci USA 105:5016-521.
112. Ho JY, Preston SH (2010) US Mortality in an International Context: Age Variations.PopulDev Rev 36: 749–773.
113. Peltzman S (2009) Mortality Inequality. J Econ Perspect 23:175-190.
114. Musgrove P (2003) Judging health systems: reflections on WHO's methods. Lancet 361:1817-1820.
115. Murray CJ, Frenk J (2010) Perspective. Ranking 37thmeasuring the performance of the U.S. health care system. N Engl J Med 362:98-99.
116. Musgrove P (2010) Health care system rankings. N Engl J Med 362:1546-1547.
117. Nobel Prize (2015) Nobel Laureates in Physiology or Medicine 1901-2014. Stockholm.
118. Liu MA (1993) Vaccines timeline. Interview by Philip Cohen. BMJ 319:1301.
119. Immunization Action Coalition (2013) Vaccine Timeline. Historic Dates and Events Related to Vaccines and Immunization.
120. College of Physicians of Philadelphia, University of Pennsylvania (2015)The Story of Vaccines. Timelines, Philadelphia.
121. Southeast Public Health Training Center (2012) Public Health History Timeline.
122. Pearson Education (2014) Medical Advances Timeline.
123. DeVita VT, DeVita-Raeburn E (2015) The Death of Cancer: After Fifty Years on the Front Lines of Medicine, a Pioneering Oncologist Reveals Why the War on Cancer Is Winnable--and How We Can Get There. 1st edn.Sarah Crichton Books, New York.
124. Kernahan PJ (2012) Was there ever a "golden age" of medicine? Minn Med 95:41-45.
125. Ingalls TH, Gordon JE (1966) Periodic health examination 1900, 1965. Am J Med Sci 251:333-350.
126. Sackett DL (1972) The family physician and the periodic health examination. Can Fam Physician 18:61-65.
127. Spitzer WO, Brown BP (1975) Unanswered questions about the periodic health examination. Ann Intern Med 83:257-263.
128. Bruhn JG (1979) The complete health checkup: fad, fiction, or fact. South Med J 72:865-868.
129. Dunn HL (1959) High-level wellness for man and society. Am J Public Health Nations Health 49:786-792.
130. Antonovsky A (1979) Health, Stress and Coping. San Francisco: Jossey-Bass.
131. Pauli HG, White KL, McWhinney IR (2000) Medical education, research, and scientific thinking in the 21st century (part I, II, III). Educ Health (Abingdon) 13: 15-25,165-172,173-186.
132. Foss L (2002) The End of Modern Medicine. Biomedical Science under a Microscope. Albany: State University of New York Press.
133. Hollnagel H, Malterud K (1995) Shifting attention from objective risk factors to patients' self-assessed health resources: a clinical model for general practice. FamPract 12:423-429.
134. Schlessinger L, Eddy DM (2002) Archimedes: a new model for simulating health care systems-the mathematical formulation. J Biomed Inform 35:37-50.
135. Collins FS, Varmus H (2015) A new initiative on precision medicine. N Engl J Med 372:793-795.
136. Stusser RJ (1994) Emergentist Research Strategy to Assist the Formation of Unifying Principles, Medical-Health Integral Hypotheses, and Complement the Reductionist Research Program. Plaza Community Polyclinic, Havana. [Submitted to the WHO HQs, Geneva]
137. Stusser RJ (1996) The Creation of Family Medicine New Research Spaces. Plaza Community Polyclinic, Havana. [Submitted to the WHO HQs, Geneva].
138. Krist AH, Green LA, Phillips RL et al, NAPCRG HIT Working Group (2015) HIT needs help from primary care researchers. J Am Board Fam Med 28:306-310.
139. Hwang J (2009) Keynote Address—The Innovator’s Prescription. An Examination of the Future of Health Care through the Lenses of Disruptive Innovation. Arch Pathol Lab Med 133:513-520.
140. Topol EJ (2015) The patient will see you now. The future of medicine is in your hands. Basic Books, New York.
141. Baumruk R (2016)How To Avoid Health Care Information Overload.
142. Institute of Medicine and National Academy of Engineering (2011) Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary.The National Academies Press, Washington, D.C.
143. Engel GL (1992) How much longer must medicine's science be bound by a seventeenth century world view? PsychotherPsychosom 57:3-16.
144. Ryerson ES (1938) Health and medical education. J Ass Am Med Coll 13:1-6.
145. Wilson RW (1981) Do health indicators indicate health? Am J Public Health 71:461–463.
146. Gøtzsche PC, Jørgensen KJ, Krogsbøll LT (2014) General health checks don’t work. It’s time to let them go. BMJ 348:g3680
147. Krogsbøll LT, Jørgensen KJ, Grønhøj Larsen C, Gøtzsche PC (2012) General health checks in adults for reducing morbidity and mortality from disease. Cochrane Database Syst Rev 10:CD009009.
148. Krogsbøll LT, Jørgensen KJ, Grønhøj Larsen C, Gøtzsche PC (2012) General health checks in adults for reducing morbidity and mortality from disease: Cochrane systematic review and meta-analysis. BMJ 345:e7191.
149. Jørgensen T, Jacobsen RK, Toft U, Aadahl M, Glümer C, Pisinger C (2014) Effect of screening and lifestyle counseling on incidence of ischemic heart disease in general population: Inter99 randomized trial. BMJ 348:g3617.
150. Stusser RJ (2008) Clinical discoveries randomized controlled trials and surveys. Ann Fam Med (Feb 24), e-letter.