Five VALUE Offerings of the Ideal Health Management Company


     In previous posts I discussed the importance of population health management and the essentials of ideal population management digital tech.  One of my tenets as a consultant in digital health is that technology itself is not a solution.  A technology is a tool which only becomes a solution when it is placed in a context of healthcare needs, provider, patient and caregiver workflows, and incorporates human interactions which close the loop on significant outlying data. Though there are many similarities in technologies (connected care devices, data collected) among companies, the human component and workflows can vary significantly.  This is where the rubber meets the road regarding outcomes. There are now many companies in the health management space with both verified and unsubstantiated claims. I will discuss five areas which I believe are going to make a difference in patient reported outcomes.

  1. Virtual visits. It is clear from industry trends that virtual visits are rapidly becoming part of the healthcare landscape. In fact more than half of all patient interactions at Kaiser Permanente are virtual ones via smartphone, kiosk, or computer. Virtual visits are now part of medicine worldwide.  A healthcare management company must have virtual visits as a key component because it meets the mission of transforming the point of living into point of care.
  2. Aging at home. It is not a secret that people wish not to be institutionalized in their ‘golden years.’ The potential benefits of digital tech in the home of the aging have implications for societal cost savings and improved patient reported outcomes. Just as important is keeping patients with chronic diseases stable enough to avoid being hospitalized and receiving non-critical care at home.  In addition, the overall benefits to society of home care should not be minimized.  Healthcare management companies can best be utilized to prevent hospitalizations by encouraging and supporting self-management of chronic diseases as well as providing services which support medical care at home.
  3. Literacy improvement. The issue of health literacy is not a new one.  However, given increasingly complex care patients need (see healthcare navigation below), expanding cultural diversity and aging populations, decreased face to face encounter time, and the epidemic of chronic diseases, the lack of health literacy has become a major barrier to better patient outcomes. Health management companies must have health literacy as a major focus, without which other initiatives are sure to fail. Literacy must e considered in human coaching interactions (explaining the diagnosis, rationale of care, and instructions for medication/device use), the type of technologies offered to patients, and in patient and caregiver educational materials provided.
  4. Unmet needs (navigation, rare diseases). A primary concern of many patients and caregivers today is not necessarily the quality of the healthcare provider or even getting the medicines they need but where to go to or call and when.  This is known as healthcare navigation which can literally be pivotal in determining life and death of people. This is no more vividly experienced than in the case of a cancer patient and more so with a patient with a rare disease, cancer or otherwise. Home health management companies can assist with patient and caregiver navigation by providing emotional support and educational and care coordination resources.
  5. Empathy.  The Oxford Dictionary’s definition of empathy is “The ability to understand and share the feelings of another.” A more in depth and interesting discussion on empathy is offered by the Center for Building a Culture of Empathy.  Dr. Jodi Halpern in an article in the Journal of General Internal Medicine describes the concept of clinical empathy. According to Halpern, barriers to clinicians’ empathy towards patients include anxiety arising from time constraints, the inability for the physician to recognize the importance of patients’ emotional needs in the context of care, and preexisting tension between the doctor and patient. However, it has been demonstrated that physicians can learn empathy.  Empathy must be part of a healthcare management company’s mission statement. Having this mindset run in both the forefront and background of operations reminds all concerned that we are dealing with people not the disease they have.

A healthcare management company in essence is acting in a patient advocacy role. The success of such companies is testimony to gaps in care that exist in the system.  As we experience a growth in the deployment of digital technologies for population health management, aging at home, wellness, and preventive medicine, we must always be cognizant of the importance of human interaction.  The best healthcare management companies will always be those who have the most dedicated, trained, and empathetic people.

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Five Ways Digital Technologies can Address Cancer


There have been remarkable strides in prevention and treatment of disease in the past 5 decades.  Few have rivaled targeted cancer therapies based on digital health, specifically genomics in scope and breadth.  I’d like to touch on a few ways in which digital technology is impacting cancer.

1. Targeted therapies. One only has to watch the avalanche of television commercials for cancer centers both local and national to appreciate the role genomics now plays in choosing therapies today for cancer. In simple terms, cancers have genetic fingerprints which are becoming specific targets of newer drugs. Different types of cancers may share similar genetic markers. Getting more layered in complexity, the same cancer may experience genetic changes during its course.  The National Cancer Institute offers a more in depth discussion of genomics and cancer.  An ambitious initiative with far-reaching implications is the National Cancer Institute’s NCI-MATCH (Molecular Analysis for Therapy Choice) trial. IBM Watson Health has recently partnered with Quest Diagnostics to provide clinicians with recommended “… unbiased, evidence-based approaches based on a detailed view of the tumor’s mutations, scientific journals, and MSK’s OncoKB, a precision oncology knowledge base..” The possibilities are indeed many in this space and the use of digital tools like genomics and artificial intelligence are accelerating our knowledge and successes.

2. Registries.The traditional collection of information on cancer has been with the collection of limited data derived from patient demographics, health history and episodic office encounters. There are now digital technologies now which incorporate raw data from pathology, genomics, imaging studies, patient reported symptoms and follow-up and more. In a previous post I describe ways in which a well-designed registry can address multiple stakeholder needs. The value of an excellent tech-based registry is best appreciated in oncology and rare diseases. As someone who has a family member with a very rare cancer, I have seen first-hand the potential benefits of and resistance (primarily ‘political’) to such registries which would expedite decision-making via pooled experiences.

3. Connected care: apps: Connected care today includes such technologies as wearables and mobile health apps. Benefits of connected care include triangulating the transmission of information (among clinicians, patients and caregivers), convenience, and timeliness. Three impressive mobile apps in the oncology space are:

a. Pocket Cancer Care Guide. Helps patients and caregiver obtain information about specific cancers, understand medical terminology, builds lists of questions to ask physicians, and provides the ability to record and save clinicians’ answers to questions.

b. Cancer Side-Effects Helper by pearlpoint. “…offers trusted nutrition guidance and practical tips to help survivors feel better, maintain strength, and speed recovery from common cancer side effects…”

c. My Cancer Genome. Managed by the Vanderbilt-Ingram Cancer Center, this award-winning app has both clinician and patient-facing information on cancer genomes, targeted therapies, and provides updated appropriate available clinical trials.

4. Connected clinical trials. The rising cost of clinical trials, the increasingly recognized importance of patient reported outcomes, and the transformation of trials with electronic data capture all suggest the value proposition of digital tech in clinical trials. Obtaining real-time vital sign trends, patient-reported adverse events (drug side effects/toxicities, unplanned ER or office visits), and outcomes data will make clinical trials more relevant (by recruiting a larger and more diverse patient population via digital tools), less costly and safer.

5. Social media support. The convergence of social media and healthcare was both inevitable and beneficial for patients. The advantages of online support groups over traditional in real life organizations are many. Access to information, governmental agencies, empathy, and convenience are some of them. Twitter has contributed greatly in this regard. TweetChat groups focusing  on specific diseases abound.

Critics of digital technology in healthcare raise valid issues regarding accuracy and reliability of information, privacy and security, and patient safety. There are existing regulatory guidelines addressing these, arguably not comprehensively enough.  Accurate and reliable information about cancer is available via many digital avenues. Digital technologies are an integral part of cancer diagnosis and treatment today.  We are living in an age where they might be among the most important tools we have as clinicians, patients, and caregivers. Hats off to those dreamers who make it possible!

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Digital Health Technologies for Alzheimer’s Disease


The statistics related to Alzheimer’s disease (Ad) are astonishing. According to The Alzheimer’s Association there are over 5 million Americans with Ad. It is the sixth leading cause of death. More than 15 million caregivers provided an estimated 18.1 billion hours of unpaid care at a value of approximately $221.3B. The impact of this disease is also well-illustrated in a recent  PBS documentary.  While it might seem incongruous on the surface to discuss digital technology and a population with significant cognitive challenges, I will illustrate how it can be beneficial at different stages of the disease’s course.

Cognitive Assessment Tools.  Most tools for assessing cognitive abilities have been of the traditional written form, as offered by the Alzheimer’s Association.  The ability of digital tools to detect early diagnosis of Ad is important in medical and social planning for the patient and family. Some have taken traditional diagnostic tools and transformed them into a digital platform. Such is the case with Quest Diagnostics’ CogniSense.  A more transformational approach is one seen with utilization of the Anoto Pen which can measure the writing instrument’s position up to 80 times per second. An exciting study by the Lahey Medical Center and MIT’s Computational Science and Artificial Intelligence Laboratory looked at using the Anoto Pen versus traditional cognitive assessment tools for Ad and other diseases. This method has already shown advantages over traditional tools, described in an MIT News piece: “… while healthy adults spend more time on the dCDT [digital clock drawing test via Anoto] thinking (with the pen off the paper) than “inking,” memory-impaired subjects spend even more time than that thinking rather than inking. Parkinson’s subjects, meanwhile, took longer to draw clocks that tended to be smaller, suggesting that they are working harder, but producing less — an insight not detectable with previous analysis systems…”  A digital platform called Neurotrack claims it has the ability to detect Ad at its earliest stages by assessing recognition memory, a function specific to the brain’s hippocampal region which is affected early in the course of Ad. Digital assessment tools like these can also save clinician time and offer a better objective patient assessment.

Cognitive Improvement tools. A handful of small studies have shown that ‘brain exercise’ in the form of cognitive augmentation games decreases the risk in normal individuals of getting Ad. One would naturally ask if this carries over to those already diagnosed AD. Some earlier studies suggested this was the case. An older review of multiple small studies showed that while they suggest that brain exercises slowed progression of cognitive decay they did not affect mood or the ability to care for oneself.  It is worthy of noting that patients with larger baseline ‘cognitive reserve’ do better to a point then characteristically have a rapidly progressive course. In a previous post I discussed the merits of music as an ideal digital health tool. Music should be considered as a potentially much appreciated and useful tool.  Relative to Ad specifically, I would reference the incredibly informative and moving award-winning film Alive Inside, documenting the response of patients with severe Ad to music relevant to their personal past. An intriguing interactive game/tool is Tovertafel, a Dutch technology which projects via suspended box visuals onto a table.  There are various exercises and games on the platform which are both enjoyable and mentally stimulating. Less sophisticated yet popular games are offered by the Alzheimer’s Association.

Tools for monitoring daily activities. Technologies have been developed to aid patients with mild to moderate disease and their caregivers to make daily activities easier and safer. SmartSole makes an innersole with a GPS locator with an associated smartphone app and call service for alerts. Silver Mother by Sen.se is a customizable digital tech platform (front door position, room temperature, and water and food containers) connecting caregivers with love ones’ activities of daily living.  For patients with early dementia or for caretakers to connect with loved ones at a distance, grandCARE is a very comprehensive platform and service.

While one might associate digital tools with those of us who are “connected,” their utility in the realm of Ad can be profound.  I would submit that the potential for digital tech to prolong independence and/or improve lives of caregivers in the home or at a distance must be the subject of clinical studies.  Public health policy might very well change as a result of such outcome studies.

As a disclaimer I am not associated with any technology or organization mentioned in this post.

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Opioid Drug Addiction: How Digital Health Technologies Can Help


After a hiatus I am returning to my beloved Digital Health Corner.  I appreciate all my loyal followers and have attempted to bridge my absence with posts in other social media.

In a previous post I discussed important public health issues that digital technology can address. Among them is drug addiction. We are all aware of the opioid epidemic and the human destruction in its wake.  However statistics have an impact that reaches beyond qualitative descriptions.  According to the National Institute on Drug Abuse (NIDA) from 2001 to 2014, deaths due to overdoses in the USA were noted as:

  • 8 fold increase due to prescription drugs
  • 4 fold increase due to prescription opioids
  • 6 fold increase due to heroin
  • 5 fold increase due to benzodiazepines
  • 42% increase due to cocaine

Tragic personal narratives provide a human fabric to the now commonplace trumpeting of generic news stories about the extent of the drug problem.  An important keystone for any healthcare strategy for chronic disease is patient self-management.  Giving patients tools to support them in their journey of recovery is imperative.  Digital technology use in the addiction space is not a new concept. The use of computer-based programs for addiction prevention and treatment was described as far back as ten years ago. The creation of virtual resources for information, guidance and support is necessary to addicts who are, for the most part digitally connected. I will touch on some potential applications of digital technologies to all relevant stakeholders.

The NIDA of the NIH  has a group of evidence-based screening tools for adolescents and adults to be used by health professionals. Notwithstanding this, many healthcare providers fail to utilize evidence-based treatments because they are not trained to do so. Technology can become a vehicle used to bridge this knowledge gap while also addressing logistical and economic challenges in drug treatment. Digital resources for families and caregivers are necessary as well.

There are various types of tech-assisted treatments. One is known as the Technology Educational System which is a multimedia approach focused on behavioral training. Another such program is the CBT4CBT (Computer-Based Training for Cognitive Behavioral Therapy).  Studies of TES and CBT4CBT on outcomes and other endpoints are favorable. A nice summary of the studies by the NIDA discusses the impressive positive effects on abstinence.

The classification of substance abuse as a chronic condition by the ACA has implications with regards to digital health. It has spawned interest in telehealth as a treatment tool. There are medication assisted treatment (MATx) mobile apps to guide physicians in utilizing pharmaceutical drugs to treat addiction. It includes prescribing guides, clinical support information, and contact resources.

Drug addiction affects all age groups. Digital technology, especially mobile technology is not something to be used in a vacuum in this clinical setting. There are significant physical and mental health issues associated with opioid substance abuse which require human intervention, at times on a frequent outpatient or inpatient basis. However, as supportive mechanisms for providers, patients, and caregivers, it can facilitate better care, communication, and education. As in other areas of healthcare, the question as to which publicly available mobile apps are safe, useful, and supported by healthcare professionals is always present. This is, as readers of this blog know well, a topic for other discussions. The toll of opioid addiction on Society, the prohibitive cost of rehab, and shortage of mental health personnel and addiction specialists mandates a call to arms for quality accessible and effective mobile tools. I look forward to all the brilliant minds in digital health and those whose lives have been affected by addiction to step forward and not wait for a government ‘fix’ to this problem.

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Five Public Health Needs for Digital Health Technology


 

Digital health technology has seen an incredible growth in the last few years, fueled by a combination of consumerization of wearable technologies,  ubiquity of mobile devices, proliferation of technology incubators, attention by government health and regulatory agencies and involvement of large companies heretofore not focused on healthcare. The fastest path to widespread adoption of these technologies is the application to the most pressing public health needs.  The mission of public health is to improve the public health and achieve equity in health status. A review of studies of text messaging for health demonstrates a general positive effect on health-related behavior. These findings, as well as growing demand for more economical, convenient, and outcome-oriented data-focused care are driving interest in digital health tools.

A recent report on public health state by state by the Trust for America’s Health describes the dilemma of increased general healthcare spending and increased public health needs with their associated decreased funding allocations. I would like to highlight what I see as public health issues ripe for digital health technologies, some of which have already spurred initiatives.

  1. Mental Health. The disappointingly slow recognition of mental illness as a medical problem is compounded by the paucity of human and digital educational, and monitoring resources in the field. While there are currently some technologies focused on mental health, their scope lies more in the consumer than medical realm.  An interesting recent review of mental health mobile apps in the journal Nature discusses positive feasibility studies but a lack of robust outcomes data. In addition, some unintended consequences of at least one app were found.  Tools providing support for medication adherence, urgent virtual visits with clinicians and self-management will have maximal effects in this sector.
  2. Opioid addiction. The National Institute on Drug Abuse has long recognized the potential of mobile health technologies for its mission. The Agency for Healthcare Research and Quality is launching a three-year $19M initiative focusing on mobile apps and telehealth aids for rural physicians in efforts to treat opioid addiction.  The Substance Abuse and Mental Health Services Administration recently released a free mobile app for clinicians called MATx.  It provides information and guidance to medication assisted treatment of opioid addiction. An interesting company to watch in the sector is Pear Therapeutics which offers a patient-facing mobile app combining digital tools to be used in association with medication-associated treatment for opioid dependence (other tools in their portfolio address other disorders such as PTSD and schizophrenia).
  3. Childhood nutrition. Nutrition is an important aspect of a child’s health regardless of age.  CDC statistics on childhood obesity are sobering.  Supporting education about the problem are reports such as the WHO Guidelines for Sugars Intake and the Global Nutrition Targets which includes its Childhood Overweight Policy Brief.  Digital health technology is going to be critical to providing educational and self-management tools to young people and their parents. Digital natives are experiencing the obesity epidemic and expect digital resources to help them. One company in the forefront of this effort is My Shapers which targets children ages 6-11 years old.
  4. Adult physical inactivity. Physical inactivity is a known significant risk factor for cardiovascular diseases. I have discussed threads between consumer and traditional healthcare digital strategies in previous pieces. Front and center in these discussions are wearable sensor devices intended to promote physical activity.  Though use of activity trackers has failed in one study to result in weight loss they resulted in improved fitness, body composition, diet, and increased physical activity.  They are used by millions of people to at least remind them to be more active which itself might promote better health. Trackers are being ‘tweaked’ to improve the user experience.
  5. Asthma has been well-studied from an epidemiologic standpoint. It is the most common chronic illness in children, found in 1/10 of them in the USA with increasing numbers. It impacts society from morbidity, mortality, and financial perspectives. Allergens causing asthma are ubiquitous and have documented to be common in schools according to a study by Boston Children’s Hospital and Harvard Medical School published in JAMA Pediatrics. Interestingly mice allergens were found in 99.5% of school samples. Digital technology in the form of an allergen sensor is commercially available from Alersense (disclosure: the author is an advisor to Alersense). It allows for custom programming of allergen sensor thresholds to alert the user before symptoms may occur.

     Digital health tools are by no means meant to replace clinicians but the potential scale, convenience, support of self-management, potential effects on cost savings and patient reported outcomes are all very significant.  Public health consumes a lot of healthcare resources which as noted above are decreasing.  With an epidemic rise in chronic diseases, the need becomes magnified.  Strives must be made to demonstrate improved outcomes and provide the privacy and safety that patients demand and deserve.

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Five Ways a Good Digital Health Registry Addresses Healthcare System Needs



Registries have traditionally been viewed as static repositories of data to be reviewed in a summary fashion after a predetermined time period.  The expanding need for drilled down relevant data has led to the development of creative sophisticated data analytics technologies.  We have witnessed the transformation of registry data collection which now includes curation of relevant raw data ranging from medical images and pathology slides to genomics.  Clinical or other predetermined data relevant to a given patient can be collected real-time from anywhere the patient is seen, regardless of the data’s EHR vendor of origin. In addition, the way in which the data is viewed real-time can be customized according to the viewer’s profile.  These developments have evolved the registry into a living digital narrative. I will discuss below some of the most useful applications of such exemplary registries.

  1. Provide real-world data for regulators. The Physician Quality Reporting System (PQRS) has been used since 2015 as a metric to determine negative Medicare payment adjustments to providers who do not meet quality standards. Without getting into unnecessary detail, one of the options of providing these metrics is reporting from clinical registries.  These registries are chosen from an approved list of registries.  The FDA has chimed in with a Guidance on the Use of Real-World Data to Support Regulatory Decision-Making for Medical Devices. The FDA recognizes that real-world data “…may be of sufficient quality to help inform or augment FDA’s understanding of the benefit-risk profile of devices at various points in their life cycle…”  Registries therefore have found their strength in reflecting the real world experiences of patients and physicians.  Clinical trials by design are rigorous and closely monitored. Adverse events and effectiveness of therapy many times require longer follow-up with more real world experience (without the restrictions placed by trials) to become known.
  2. Improve patient safety. A corollary to adverse events and efficacy is patient safety. The safety of a medication or device may reflect predictable or unpredictable serious adverse events. It might be a universal issue which is discovered only after a prolonged period of exposure. Examples are found in  the implantable pacemaker and defibrillator and orthopedic device industries or long-term risk of certain medications (ex. anti-inflammatory drugs and risk of heart attack). Registries can collect post-marketing real world data and lead to discovery of patient safety issues significantly in advance of word of mouth communications which have a bias of the threshold of information transmission.
  3. Supplant claims data with more accurate and relevant data. The inferiority of administrative claims data versus clinical registry data has been known for years. Some believe that the use of the more granular ICD-10 diagnostic claims codes will close the accuracy gap between claims and clinical data. I personally do not believe claims data will ever supplant patient reported outcomes (PRO) data because PRO data reflects not only outcomes but the outcome relevant to that patient.  I have previously discussed the importance of PROs. In addition, the aggregation of raw data can even potentially affect disease treatment strategies.  Consider the hypothetical situation in which a cancer registry pairs pathology slide data with imaging, chemistry, genetic, treatment and clinical data from physical examination.  Subgroups of patients might be identified from various combinations of data which benefit from different treatments they received (or didn’t).
  4. Provide a vehicle for PRO standardization. Patient reported outcomes are the key to determining quality. The importance of PROs and their standardization are eloquently discussed in an editorial in the New England Journal of Medicine: “…Experience in other fields suggests that systematic outcomes measurement is the sine qua non of value improvement. It is also essential to all true value-based reimbursement models being discussed or implemented in health care. The lack of outcomes measurement has slowed down reimbursement reform and led to hesitancy among health care providers to embrace accountability for results…”  Data sets derived from registries or any patient portal can be used in the development of PRO standards.  In addition, the data can be compared real-time to existing international standards thereby facilitating changes in treatment strategy earlier than would otherwise be guided by government reported analytics via feedback many months later. One might hypothesize that the visualization of data relevant to them compared to others who achieved best outcomes standards by patients via self-management platform portals might affect changes.
  5. Real-world patient reported data for price support of effective new drugs.  Many specialty medications notably biologics are very expensive. They obtain FDA approval and are priced out of reach for most patients.  They are denied reimbursement by many insurance carriers either outright or via impossible barriers to overcome.  A prime example is reimbursement for new injectable cholesterol medications for refractory familial hypercholesterolemia (which is not rare with an estimated prevalence of 1:200 Americans and as high as 1:60 persons in central Pennsylvania).  Some carriers require genetic testing to document a diagnosis (though the diagnosis can be made via significantly high blood levels alone), but won’t pay for the genetic testing which costs $2-3K dollars. Would payers rather pay for heart bypass surgery? Post-marketing patient registries which provide patient reported outcomes could significantly lower drug costs by providing data showing better efficacy than the approval studies.  This might tip the benefit-cost ratio for payers to support a drug or other treatment’s cost.

As one can see, registries performed with quality technologies can have profound effects on healthcare from many standpoints. Investment in digital tools which make Big Data come alive and transform it into relevant data can be helpful to all healthcare stakeholders. One must see this as an ROI for cost savings at its finest.

 

 

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Five Essentials of a Population Management Digital Health Technology


Population health management (PHM) means different things to different people. It is a term which is in vogue now because of its injection into healthcare provider payment models and describes a strategy in which individual and patient subgroups are cared for outside of the traditional office and hospital sites.  In a previous post I discussed why population health management matters.  Such a strategy necessitates technology which interacts with patients and their caregivers in a bidirectional way with clinicians and ancillary staff.  These interactions should involve both objective data and subjective insights from patients.  In this piece I’d like to give my thoughts on what constitutes ideal patient management technology irrespective of one’s definition or the long-term survival of ‘population health management’ in payment models.

  1. Patient-facing portal. I was taken aback in discussions with some PHM technology vendors whose product had no patient-facing aspect.  Such an approach defeats the mission of PHM which by definition incorporates patient self-management and behavior modification. The aim of PHM is to extend care outside of the brick and mortar of traditional venues, transforming points of living into points of care. If most chronic diseases are preventable in large part with lifestyle changes, then PHM must extend to the patient/consumer and the places where these choices are made.
  2. Mobile platform. Any technology which addresses direct patient care today needs to be on a mobile platform.  It is unfortunate that mobile versions of most electronic health records are woefully inadequate today. The mobility of a PHM platform should be a given, since it is something both providers and patients expect today. Due to the critical nature of patient/consumer involvement required for self-management, mobile is a prerequisite component for success because most patients and caregivers expect this from any digital technology.
  3. Connected care tools. PHM is all about collecting data and at the same time transforming it into relevant  Objective information via patient-generated data sets is a critical component of PHM.  The types of data sets collected would hopefully depend upon the patient or disease state population in question.  The data must be filtered to be relevant to both clinicians and patients.  Patient-derived data tools (relevant to vital signs usable for heart or lung disease, diabetes, activity tracking, medication adherence, behavioral health) may be provided as third party technologies or proprietary to the PHM platform vendor. Patient-derived data also comes in the form of subjective data. Objective data must be supported with patient reported outcomes which provide necessary real world evidence. Together, the objective and subjective data complete a picture that benefits the individual patient (who can ideally view personal data relative to others in the population examined) a targeted patient population, the clinician, payer, and other stakeholders in HIPAA compliant ways.
  4. Real-time analytics. There is no arguing that Big Data is critical in healthcare today.  What is underappreciated is the value of real-time analytics to enterprise operations, patient safety, and better clinical outcomes.  Yet analytics are woefully underutilized by healthcare enterprises.  In a Deloitte Center for Health Solutions 2015 US Hospital and Health System Analytics Survey of CIOs, CMIOs, and senior IT leaders, less than 50% had a clear integrated analytics strategy.  As correctly pointed out in the survey, value-based care will necessitate such a strategy in order  “…to blend financial, operational, clinical, and other data to achieve their goals of improving quality, providing access, controlling cost, and managing provider networks…”  A platform which curates such data in real-time with customizable analytics by each stakeholder (including patients themselves) is what makes the data relevant.  Big Data collected by payers (including Medicare), regulatory agencies and others is often up to 12 months old. Process and patient outcome improvement as well as patient satisfaction cannot be dependent upon such outdated information.  In addition, the data is raw, unfiltered, and not user-specific. Enterprises need to pivot quickly to provide the best services in the most economical way.  The ability to have current accessible relevant data is expected and available in all business settings.  It is imperative and even more important in a sector of the economy which utilizes almost 18% of the USA’s GDP.
  5. Social interaction. As stated above, active patient participation in a PHM is critical.  This relates primarily to the importance of human behavior as a driver of health, wellness, shared decision making and treatment.  The importance of social media in healthcare cannot be underestimated.  Social media in healthcare involves both patients and clinicians exemplified by such online sites as  Mayo Clinic Direct.  Such interaction promotes communication which improves treatment adherence as well as serving as a source of patient reported outcomes (PRO) data (see above).  The value of online patient communities has been appreciated for a while now and supports a comprehensive PHM strategy.

As one can see, PHM is a concept which is not standardized and developing both in terms of strategy as well as the role of digital technology in it.  I am eager to observe how the challenges of digital divides, patient behavior, and the culture of traditional healthcare affect the extent and rate of adoption of PHM strategies. I look forward to and am optimistic about the future in this regard.

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Five Reasons Why Digital Health Needs Patient Reported Outcomes


According to the National Quality Forum, patient reported outcomes or patient reported outcomes measures (PROs) can be defined as “any report of the status of a patient’s health condition that comes directly from the patient, without interpretation of the patient’s response by a clinician or anyone else.”  Initially utilized as a clinical research tool, they have since become a critical component of assessing quality of care.  Digital health technology has long been touted as a way to promote patient engagement. There is significant opportunity for patient and other stakeholder benefit in the incorporation of PROs into any patient-facing digital health technology. In this piece I will try and give a focused look at PROs, why they are becoming important and the interplay with digital health technologies.

1. PROs are now determinants of healthcare payments. A good example of the interplay between PROs and value based payments can be found in a discussion of the Function and Outcomes Research for Comparative Effectiveness in Total Joint Replacement (FORCE-TJR).  Some of the lessons learned and described from over 25,000 patients reporting into the registry are interesting and worth sharing because they are universal and not specific to joint replacement; (A) PROs provide actionable data to help guide clinical decision-making. (B) Identifying key risk factors…can go a long way toward managing the entire 90-day episode of care and successfully participating in value-based contract gainsharing.  (C) Making PROM data collection easy for both patient and surgeon’s office is key to success. (D) Post-TJR PROMs can be a valuable patient satisfaction and engagement tool. PROs are not just represented by patient satisfaction surveys.  Payment for care is also tied to PROs relating to patient engagement and clinical outcomes.

2. PROs put the focus back on the patient. Quality of care can only be determined by the patient.  Treatment goals can vary substantially for individual patients with the same clinical problem, whether it is acute or chronic. In this way, care can be liberated from a ‘one size fits all must meet strict evidence-based guideline model’ which dominates pay for performance payment systems today.  PROs can help evaluate the same patients in a longitudinal fashion (at various points in time), maintaining the subject, not necessarily the disease or treatment as the focal point. In this way, patients themselves, armed with PRO data can change the direction of treatment with the identification of logistical, medical, emotional or financial challenges which might adversely or positively affect care.

3. PROs can be used to close gaps in care. Disparities in healthcare in the USA have been well documented. PROs can be used to study patient populations with similar clinical problems from diverse ethnic, socioeconomic, and geographical demographics.  By comparing standardized PROs, best practices might be readily identified.   One recent interesting study examined the disparity between patient reported outcomes measures and assigned triage priority levels for elective surgical procedures in British Columbia, Canada. This is an excellent example of how patient generated data can crystallize an inherent pitfall of healthcare policy and transform it to benefit patients.

4. PROs add a necessary dimension to clinical trials  The incorporation of PROs in oncology care has proven feasible and demonstrated to result in better patient outcomes. PROs are used in various ways in clinical trials.  Some of these include measuring study endpoints, monitoring adverse events, quality of care, symptoms, and longitudinal reporting during the study. PROs provide critical information to longitudinal follow-up of patients either in clinical drug, device or intervention studies or specific population registries.  A fertile area for the use of PROs is comparative effectiveness studies. Pharma needs real world evidence for post-market surveillance, reimbursement support, and relationships with patients. The use of PROs in clinical trials supports those goals. PROs via mobile technology in clinical trials facilitate patient engagement as well.

5. PROs provide real-world evidence. The FDA’s recent Draft Guidance on the Use of Real-World Evidence to Support Regulatory Decision-Making for Medical Devices is a progressive acknowledgement of the value of non-clinical trial data in evaluating medical devices. Real-world data is data collected from sources outside of traditional clinical trials. These sources may include large simple trials, or pragmatic clinical trials, prospective observational or registry studies, retrospective database studies, case reports, administrative and healthcare claims, electronic health records, data obtained as part of a public health investigation or routine public health surveillance, and registries (e.g., device, procedural, or disease registries)…” Digital health is critical in this type of process, because “…The data is typically derived from electronic systems used in health care delivery, data contained within medical devices, and/or in tracking patient experience during care, including in home-use settings.”  Part of this data will certainly include PRO data which will aid in the FDA process.

As described above, PROs are becoming an integral part of many facets of healthcare: quality assessment, payment models, clinical trials, product evaluation, and patient engagement with digital technologies.  The culture of healthcare is slowly (isn’t that always the case?) shifting to an appreciation of patient reported outcomes and patient generated data. Let’s look forward to PROs becoming something which patients expect to participate in and to benefit from …for that is what will ultimately change healthcare.

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Five Reasons We Must Untrap Digital Health’s Big Data


We tend to think of Big Data as a Land of Oz where we can find any information we need. What is not appreciated by most in healthcare is that there is a lot of Big Data collected but most is not relevant data, nor is it easily located or even accessible. The implications of this are enormous. The true value proposition of Big Data in healthcare lies in how the data is analyzed and presented.  In my last post I discussed ways in which Big Data can be transformed into relevant data.  I will discuss five reasons why freeing up ‘trapped’ data is critical to making it relevant.

  1. Population health management. Analytics are the building blocks to population health management, one of the new drivers of healthcare payment models. It is interesting to note that a 2015 HIMSS Analytics Survey found that 67% of surveyed organizations had population health management programs in place but only 25% of them utilized an outside vendor solution to address their needs. Population health management’s purpose is to emphasize shared decision-making and care between the clinician and the patient with an emphasis on accomplishing this outside of the healthcare facility or clinic. While this has always been the aim, we now have digital tools which can facilitate this as well as the shortage of providers increasing the demand for such tools.
  2. Patient outcomes data. There is a major discrepancy between quality measures and patient outcomes. According to the National Quality Data Clearinghouse only 139 of its 1958 quality indicators are patient outcomes and 32 are patient-reported outcomes. As correctly pointed out in a recent piece in the New England Journal of Medicine, we have used evidence based medicine metrics as a substitute for patient outcomes.  The International Consortium for Health Outcomes Measurement (ICHOM) has already approved 20 sets of outcomes standards and projects to have over 50% of disease burden covered by 2017.  Patient outcomes data whether derived from data sets directly from the electronic health record (EHR) or from patient-derived data emanating from mobile or other digital technology is critical to determining outcomes. The problem lies in how to collect data that lie with disparate EHR or other digital formats.
  3. Support digital and mobile clinical trials. Imagine discrete data                                 from any individual clinical trial patient’s point of care (regardless of the provider’s EHR brand) coupled with direct patient-generated data delivered to a mobile clinical trial platform. Such a scenario is possible and will save Pharma and CROs huge amounts of money, improve accuracy and decrease lost or missing data. In addition, integration and interoperability between hospital records and data registries that flag patients seen urgently at a distant site helps save lives.  In this way a patient in a clinical study, even winding up in an out of town emergency room can ideally have pertinent data automatically sent to the clinical trial platform.
  4. Save money. Harnessing relevant data from Big Data can save money in many ways. As mentioned above, the costs of clinical trials can be markedly decreased. Organizations (governmental, healthcare enterprises, professional societies) who maintain clinical registries by definition require relevant longitudinal data. The ability to seamlessly collect relevant data automatically across disparate EHRs results in a more complete picture of the cancer or chronic disease patient with comorbidities. Doing so can hopefully improve outcomes translating in higher value based payment. In another example, it is not uncommon for a cardiac patient to be in separate mandated registries for coronary stents, a heart valve, and/or an implantable defibrillator.  A single database collecting all the longitudinal data on such a patient would save millions of dollars to the sponsor and the provider (via improving efficiencies of clinical data staff) in addition to contributing to outcomes measures in a more meaningful way.
  5. Other stakeholders need real-world evidence. Just as a picture is worth a thousand words, relevant collected data helps pain the real picture of the patient. Post marketing surveillance registries and studies of drugs and medical devices by industry need relevant discrete data sets provided in an efficient way. Payers need this data to determine true outcomes. Providers need relevant data to determine true outcome measures, quality metrics, and inputs for value based payment models.

One can see how static Big Data is useless without the ability to make it relevant by ‘untrapping’ it. The technology exists. It can save time, money, and address interoperability challenges.  The critical importance of patient outcomes becoming the focus of quality measures for use in new payment models, drug and device development, and clinical trials will drive adoption of such tools in the near future.

 

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Five Ways to Turn Big Data into Relevant Data


‘Big Data’ may be defined as data that is so large or complex that it cannot be processed by the usual applications. Current common uses of Big Data in healthcare include the collection of genomic data, insurance claims data, medication prescription data, mandated hospital reporting data (admissions, diagnoses, readmissions, other).  The problem with amassing such data is that much of it is trapped in silos across the healthcare continuum and not available (even for studies obtaining consent and protect privacy) for analysis.  Robust analytical tools are not a part of most IT platforms utilized at points of care.  Organizations which can profoundly influence treatment guidelines incorporated into evidence-based medicine, healthcare policy and patient advocacy are not availing themselves of relevant data. I will discuss some ways in which Big Data can be transformed into little or relevant data.

  1. Longitudinal follow-up. As a clinician I appreciate the enduring contributions of  Sir William Osler, considered to be the father of modern medicine.  One fundamental concept he championed was the study of the natural history of a disease and the longitudinal follow-up of treated patients. The recording and storage of data longitudinally is called a registry.   Registries can serve as potential sources of relevant data. If data set query is large enough, the right questions are asked of the mined data and adequate and creative analytics are applied, it’s not difficult to transform Big Data from registries into relevant data.
  2. Obtaining data across disparate digital platforms. Following a patient longitudinally often necessitates obtaining data points acquired from providers who utilize different EHR platforms. This presents problems for clinicians, epidemiologists, and patients and their caregivers. This cross-logistical data is critical for registries. A patient participating in a clinical trial or registry unexpectedly seen in an emergency setting away from home or even by a specialist nearby with an EHR different than that of the patient’s registry clinician/investigator presents both logistical and technical challenges of incorporation of pertinent data into the patient’s registry profile. A platform which can ‘scrape’ data of a specific patient across EHR silos assures the collection of all relevant data.
  3. Customizable Interfaces and analytics. Not all clinicians desire to view all or the same data collected on patients involved in a registry or population health IT tool.  They might want to view the same data in a different visual context. This type of customization is a welcomed reprieve from the confines of traditional EHRs and registry tools. Customization of this type transforms Big Data into relevant data for clinicians. Looking at data in different ways can stimulate the viewer to approach a patient, group of patients or a treatment plan in a different manner.
  4. Applying best practice guidelines and evidence-based medicine results. A data collection platform which furnishes evidence-based practice guidelines for treatment of a specific disease and provides the ability to compare real-time individual or population health group data to outcomes of optimally treated patients can be very powerful.  It thus provides a direct connection of big data to relevant data, allowing for mid-treatment corrections during care to meet best practice outcome metrics. In addition it can serve as a mechanism to correct the significant geographic variations in healthcare.
  5. Incorporation of patient-reported outcomes measures. Patient reported outcomes measures (PROMS) have been described with relevance to healthcare economics for over eight years. PROM is an integral part of the value-based payment system which will dominate how healthcare will be paid for.  These outcomes are determined from the collection of specific clinical data sets. Population health management IT tools must incorporate these measures to meet payment requirements. This goal can be accomplished in a piecemeal fashion with multiple IT vendors or ideally with one.

Much has been said about the power and prospects of Big Data. But this data, like the food we eat needs to be distributed, filtered, and relevant parts applied to good use. Healthcare may lag behind in the use of digital and mobile technologies, but the amount of Big Data garnered by all its stakeholders is incredible. The future of improvements in healthcare (whether they be in cost savings, clinical outcomes, efficiency or other areas) lies in the way in which Big Data can be made relevant. It’s like the old adage, “All politics is local.”

As a disclosure I am an advisor to Pulse Infoframe which has capabilities to accomplish all of the above.

 

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