Listen Up

Thursday, May 14, 2015

‘Measure Yourself Medical Outcome Profile’


Measure Yourself Medical Outcome Profile’, what does that mean?

"The Quantified Self, or Patient Centered Medicine.  MYMOP, and QSPCM are terms designed around self monitoring using standard items such as scales, blood pressure measurements, blood glucose levels and other markers of health.  Predictions are that many of these markers will be monitored remotely by high tech devices such as wearable wi-fi remote monitors, and using skin applied tattoos with embeded micro circuits.  Some of these are already in development.

These terms developed simultaneously with the passage of the affordable care act, and the formation of accountable care organization.



24/7 Tracking

The idea behind the quantified self movement is that either through manually tracking or the kind of 24/7 tracking that can be achieved by wearable tech with little to no input from the patient, data about a patient’s state of health can be collected in real-time and then analyzed to help get a more quantified picture of their overall health. Through specially designed computer algorithms and statistics, linear regression can be used to assess the quality of the data and find correlations between variables that might bring about key insights into a patient’s lifestyle.

What to Track?

Factors like caloric intake, number of hours of sleep, activity level and even blood pressure and body temperature can be gathered on a daily basis for years, meaning that the wealth of available data for the patient and their healthcare team is larger than ever before. There is practically limitless potential for this data to help healthcare providers and their patients make connections between lifestyle and health, perhaps even discovering never-before known correlations that could lead to treatment innovation and perhaps even cures for conditions.
Particularly with the advent of wearable tech, it’s not only practical for patients to collect the data, but easy. As the technology continues to expand and improve, even the cost to acquire a piece of tech, whether in the form of a wristband or a phone, continues to lower as well. Meaning that a larger demographic of patients will be able to afford the technology and integrate it seamlessly into their everyday lives.

Data Tracking = Key Metrics for Physicians

For physicians, the data of the quantified self movement will be priceless. Self-reported patient activities, particularly when it comes to lifestyle, are notoriously unreliable. Patients don’t always intend to be inaccurate historians, but for simply asking a patient to track their caloric intake, blood pressure reading or blood sugar welcomes in human error.
Certainly patients may also feel pressured to exclude instances where they have sidestepped treatment recommendations or not met their targets, making the data moot. In some cases a physician may not even be sure what data would be the most helpful, but by having the input from wearable tech they can get an overview first and then assess what measures may warrant a more in-depth examination.

The Ultimate “Life Hack?”

Techies are also promoting the idea that having patients track their data this intently is the ultimate “life hack”: having such a wealth of information at their fingertips means they can’t deny their state of health; hard data doesn’t lie. The concept of self-knowledge and data gathering isn’t new by any means: Benjamin Franklin quite famously journaled daily in the hopes of achieving self-improvement through self-awareness. But he didn’t have a FitBit to help him.
Technology has made the concept of the quantified self more accessible and computer technology combined with advanced statistics will not only change the way we practice medicine, but most likely contribute to population health recommendations for years to come.

Are Patients Already Tracking Their Data?

Almost 70% of adults track and report least one health measure; but half of them are trying to do it all in their heads, meaning that the data is likely unreliable. Patient participation, of course, is of utmost importance but these patients also need to be working with physicians and healthcare providers who are open to incorporating and helping them analyze the data as part of their treatment.

Genetic Sequencing

An even deeper approach to self-quantified patient data has come in the form of genetic sequencing, which has now become more available to consumers through companies like 23andMe. Patients now have genetic data available to them that can tell them everything from disease risk to natural immunity to illnesses like Norovirus.
They can also make connections between their family history and their actual genetic risk for conditions later in life, like heart disease. Taking this information and pairing it up with their current health data can help patient’s prioritize their lifestyle changes according to what conditions they are most at risk for developing.

Exciting Changes in Healthcare with Wearable Tech

Quantifying a patient’s life has already begun to change the way we practice medicine, and it reaffirms the partnership between patients and their healthcare providers that’s being promoted in patient-centered medical homes. It may not be the right choice for every patient, but it may be one way to engage certain demographics that have been difficult to engage in the past, particularly young people who, glued to their phones, might be the perfect market for wearable tech.
Engaging these patients in the research and development of these tools may be the most exciting healthcare development of the next decade, and certainly this year.

Emerging Patient-Driven Health Care Models

Three emerging patient-driven health care models are now discussed in detail: health social networks, consumer personalized medicine and quantified self-tracking.

2.1. Health Social Networks

2.1.1. Health social networks introduction

Social networks have become a powerful tool for bringing people with shared interests together to interact. In addition to general social networks (examples: FaceBook, MySpace) and career social networks (examples: LinkedIn, Plaxo), more specific purpose-driven social networks are emerging. In the Finance 2.0 area, social networking has become an overlay or a property of asset and expense management websites like Wesabe, Mint, Zecco, Cake Financial and Expensr. In the health space, over twenty health social networks have launched in the last few years including PatientsLikeMe, CureTogether, DailyStrength, MedHelp, HealthChapter, MDJunction, Experience Project, peoplejam, and OrganizedWisdom (Table 1 has URLs for all health social networks mentioned).

2.1.2. Health social networks definition

A health social network is a website where consumers may be able to find health resources at a number of different levels (Figure 2). Services may range from a basic tier of emotional support and information sharing to Q&A with physicians to quantified self-tracking to clinical trials access.
One key value health social networks provide is the potential to find others in similar health situations and share information about conditions, symptoms and treatments. A health condition is a particularly strong affinity and the collective learning and experience of others can be leveraged and shared to help individuals make decisions. Health social networks are primarily directed at patients but caretakers, researchers and other interested and knowledgeable parties may be able to participate.
The largest and best-known health social network is PatientsLikeMe, which started in 2004 and had, as of December 2008, 26,059 patients (http://www.patientslikeme.com/all/patients). Also as of December 2008, membership was growing 10% per month with the company having the goal of reaching one million patients encompassing 200 different diseases by 2012 [5]. 5% of all amyotrophic lateral sclerosis (ALS) patients in the U.S. are site members; this is the largest current existing data set on the disease [6].
To date, health social networks have been focused mainly on medical conditions for which cures are sought, although some websites have user communities for healthy living. Some health social networks serve as a point resource for over 700 conditions (examples: MDJunction, HealthChapter) and in fact, a key benefit of health social networks is that they can offer a more comprehensive look at a patient’s health by covering a deeper and broader range of conditions than is expedient for traditional medicine. Other health social networks focus on fewer conditions more profoundly (examples: PatientsLikeMe, CureTogether), using additional functionality such as quantified self-tracking and collaborative filtering to identify potentially related conditions patients might be experiencing and match patients in similar situations. Collaborative filtering has been identified as a critical mechanism in facilitating patient information-seeking and trust-building in Internet health models [7].

2.1.3. Services provided by health social networks

This section has an in-depth review of the services provided by health social networks: emotional support and information sharing, physician Q&A, quantified self-tracking and clinical trials access.

Emotional support and information sharing

The basic services offered by the majority of health social networks are a mix of emotional support and information sharing at no cost to registered site users. Some health social networks may emphasize one area more, such as information and research citations (example: OrganizedWisdom) or social connection and support (example: DailyStrength). Websites may auto-populate general condition information from Internet health resources such as Wikipedia articles and PubMed links. In addition to the general information, patients may be able to enter qualitative and quantitative data about their own conditions, symptoms, treatments and overall experiences.
Emotional support, social support and patient empowerment are important components of health social networks, available both implicitly and explicitly. Implicitly, emotional support is experienced by seeing that there are others with similar conditions, that “I am not alone.” Implicit emotional support is also felt by being a community member, participating in the process of creating a personal profile (Figure 3) and recording health information, seeing how other non-medical professionals describe the same conditions and symptoms and finding out what remedies others have tried. Emotional support is also offered explicitly in some health social networks through user interaction. Site members may have the ability to comment on forums, publicly or privately message each other, give each other advice and transmit lightweight social greetings, such as hugs, as shown in excerpts from DailyStrength’s activity feed (Figure 3).
The impact of emotional support and patient information sharing is thought to be quite positive but is not fully understood yet. PatientsLikeMe has conducted some research, finding that “patients who choose to explicitly share health data within a community may benefit from the process, helping patients engage in dialogues that may inform disease self-management [8].”

Physician Q&A

A second service offered by several health social networks (examples: MedHelp, WellSphere, MDJunction, ehealth forum, iMedix, WeGoHealth) is the ability to pose questions to physicians. Questions and responses are usually displayed publicly unless the patient marks them as private. Posing questions may be free or fee-based, for example at MedHelp, it is $22 to pose a question to a physician directly and free to post a question in the medical communities where peers or professionals may respond. The websites generally have doctor profile pages where physicians complete information about their expertise, background and affiliations, with links to previous question responses on the site and possibly their medical blog entries (Figure 4).
This transparency and willingness to interact helps to start changing the image of doctors as 10-minute diagnosticians to accessible collaborators in care. Many doctors are willing to answer questions and recommend next steps, and possibly provide a preliminary and well-caveated diagnosis. Even this basic mechanism of lightweight doctor-patient interaction could help ease burdens on the health care system. The conventional wisdom may have been that physicians would not take part for legal, reputational and other reasons but the key point is that they are willing to participate and in fact may find reputational enhancement and other benefits.

Quantified self-tracking

A third type of service offered by some health social networks (examples: PatientsLikeMe, CureTogether, MedHelp, SugarStats) is quantified self-tracking. The self-tracking functionality consists of easy-to-use data entry screens for condition, symptom, treatment and other biological information. The information can then be seen in a graphical display, possibly with views by individual, aggregated population or custom groups.
For example, Figure 5 shows a detailed patient profile from PatientsLikeMe including disease progression, prescription drugs and symptom tracking for a 37 year-old male who has had ALS for six years, and Figure 6 shows an aggregated view of the top treatments tried by the CureTogether endometriosis community. Individual tracking data, medications and other relevant information can be printed from the websites to expedite interaction at in-person doctor visits.
Self-tracking information is further incorporated into the PatientsLikeMe site by mapping the data to a graphical representation of the patient as shown in Figure 7, a stick figure shaded with different colors per symptom severity and disease stage so anyone looking at the profile can assess the patient’s status immediately. Figure 7depicts two patients with ALS, one with arms onset (top diagonal line) and one with bulbar onset (bottom diagonal line), tracking their condition progression by year (x-axis, years 0–10) and decline in Functional Rating Scale (FRS) (y-axis, 0–45). The site’s collaborative filtering allows users to find “patients like me,” which is important since similar others are the most relevant for providing and sharing information.

Clinical trials access

A fourth type of service offered by some health social networks is information regarding clinical trials. Even the presence of health social networks makes traditional clinical trials more efficient through the availability of large searchable online databases of patients with health history and condition information. Pharmaceutical companies, industry analysts, policy architects and other interested parties can assess demand and market size directly from health social network websites.
PatientsLikeMe and Inspire are at least two health social networks offering access to clinical trials at present, selling anonymized data to pharmaceutical companies, universities and research labs. For example, in May 2008, Novartis recruited clinical trial participants from PatientsLikeMe estimating that they were able to speed up their 1,200-patient study of a new medicine for multiple sclerosis by a few months [9]. In another instance, PatientsLikeMe contacted 1,500 ALS patients for another research project and received 50 DNA samples (3.3%) [10]. The yield might not seem high but the time and cost savings in identifying, screening, contacting and obtaining responses from relevant patients is significant.
In addition to lower-cost patient recruitment, there are three other ways that health social networks are improving the quality of clinical trials. First, the depth of information generated through large online patient communities creatively interacting and monitoring their conditions with quantitative tracking tools can lead to new findings that give a better understanding of the underlying conditions. PatientsLikeMe in-house research staff is publishing some of these findings, such as the identification of non-motor symptoms of Parkinson’s disease in younger sufferers [11]. Second, health social networks provide a feedback loop to the clinical trials process. For example, PatientsLikeMe patients noticed and suggested corrections and improvements to the graphical display of data in ALS clinical trials [12]. Third, online health tracking in conjunction with clinical trials means that patients can make their experience feedback, including response to drugs, available as a public resource.
The obvious next phase of active patient participation in health social networks is patient-inspired research and patient-run research. This concept is also called open source health research and crowd-sourced health research. Self-run clinical trials and structured self-experimentation is emerging as patients may no longer have the inclination to wait for formal research findings and pharmaceutical company-sponsored clinical trials, and can possibly fill the medicine gap for orphan diseases and other conditions that do not make good business cases in the existing pharmaceutical model. Patients can review research literature and other remedy suggestions on their own and try them, tracking the results in a rigorous manner, sharing the information and running non-traditional clinical trials themselves. In one example, a PatientsLikeMe patient, newly diagnosed with rapidly progressive and young-onset ALS gathered 250 patients to self-experiment with lithium [13] per a research paper he had found [14]. The self-run patient study results were preliminary and found that the use of lithium did not slow disease progression. The example highlights many elements of the new power and role of patients, their ownership of the health care process and the attendant contentious legal, ethical, methodological and other issues.
Inevitably, fraud is likely to arise or may already exist in health social networks as there are significant economic incentives for drugs and other treatments to have high patient usage statistics and favorable reputations. The bona fide peer community may be one of the most helpful resources in detecting and policing fraud due to the deep knowledge of patients regarding their conditions and remedies, and their time spent on the websites.

2.1.4. List of health social networks

A list of current health social networks is presented in Table 1, organized into three categories: patient-focused general multi-condition websites, patient-focused cause-specific websites and physician-focused social networks. Most patient-focused health social networks offer the basic level of service, emotional support and information sharing, for a variety of medical conditions. About half also offer the second level of service, some sort of Q&A with physicians, and a few offer the third and fourth levels of service, quantitative self-tracking and clinical trials access.
A second class of patient-focused health social networks is cause-specific, offering primarily the basic emotional support and information sharing service. Physician-focused health social networks are also starting to have a presence, both for the usual industry-related networking but also as collaboration platforms, notably the Medical Image and Video Exchange ( http://www.medting.com) which in December 2008 had over 2,011 cases with 17,812 images and videos uploaded and available for collaboration, and OR-Live, which presents live interactive webcasts of surgical procedures to physicians, patients and the public.

2.2. Consumer Personalized Medicine

2.2.1. Consumer personalized medicine introduction

In the last several decades, advances in science have been enabling new paradigm understandings of biological life. Molecular biology was one such key shift, genomics is another that is occurring now, and proteomics, metabolomics and any or all of the other twenty “omics” fields ( http://omics.org) may further revolutionize the understanding and management of all biological processes. Current unsolved disease states such as cancer are complex and expressed differently in diverse groups of patients. Initially, it is easiest to tackle cases where the patients have certain characteristics or the disease is expressed in certain ways. Therefore therapies are targeted to sub-groups of patients, for example Imatinib for certain chronic myelogenous leukemia (CML) patients and Tamoxifen for certain breast cancer patients.
It is starting to be realized that obtaining and understanding a whole new level of detailed individual biological information could be necessary for advances in both institutional medicine and patient-driven medicine. The required information is starting to be known to the consumer and is increasingly available publicly, without the individual needing to wait for a condition to advance to the stage of symptoms or for a doctor to know that the information is available and relevant or notice that a particular condition could be assessed via testing. Consumers are taking it upon themselves to obtain a better understanding, resolution and possible prevention of disease conditions.

2.2.2. Consumer personalized medicine definition

The core definition of personalized medicine is using an individual’s specific biological characteristics to tailor therapies to that person, including drugs, drug dosage and other remedies. There are other more expansive descriptions, for example, as offered by the Personalized Medicine Coalition (http://www.personalizedmedicinecoalition.org/sciencepolicy/personalmed-101_overview.php). Part of the change in how health and health care are now being understood and realized is in using systemic personalized medicine approaches to individuals (Box 2). A systemic approach may incorporate a combination of an individual’s genetic, blood and other biomarker, environmental, lifestyle and other data. Consumer personalized medicine is the further step of individuals collecting and synthesizing their own data and using it to proactively manage their health.


The Quantified Self leaves much out. Subjectivity is a large part of health or disease. And there are many problems that cannot be quantified with a numerical value. Emotional well-being or the opposite can be a large factor in disease.  How does the QS detect depression, anxiety, or insomnia ?

No comments: