Children with medical complexity account for less than 1% of all U.S. kids but contribute to an estimated 30% of pediatric healthcare costs and 86% of hospital charges at American children’s hospitals.
Worse yet, hospitalizations for children with chronic conditions have increased nationally by 33% in the past decade. Even more staggering, the CDC now says 40% of children struggle with a chronic illness.
Dr. William Hay Jr. is chief medical officer at Astarte Medical, a precision medicine company. He served as professor of pediatrics at the University of Colorado Denver, where he did deep research on these and other problems.
We spoke with him to discuss how healthcare provider organizations can turn the tide – and what new digital tools and protocols may need to be in place to improve outcomes for vulnerable pediatric patients.
Q. What is the problem with high-risk pediatric patients being overlooked or receiving inappropriate care?
A. Too often, people have assumed children are small adults with small problems. Children’s medical disorders are just as complex as those in adults, and many, probably most, set the child up – program the child – for later life complications.
While children indeed are resilient and can overcome many adverse effects of medical disorders early in their lives, such adversity can cause or predispose the child to develop later life medical disorders and even early mortality. Underestimating the complexity of childhood medical disorders and their longer-term consequences, therefore, can adversely affect the child for its lifetime.
A few examples highlight this problem of early life origins of later life disease. Preterm birth continues to affect a large fraction of newborn infants – 10-12% in the U.S. – and remains the leading cause of death in newborns around the world.
Preterm birth also predisposes the infant to many later life adverse outcomes, including limitations of physical and mental and behavioral capacity. Undernutrition and malnutrition at the critical stages of early childhood development, particularly in preterm infants but also young children, limit normal neurological development and cognitive and behavioral outcomes that are difficult or impossible to reverse.
Obesity that begins in infancy and childhood becomes chronic, and this increasingly common disorder promotes the development of childhood diabetes and cardiovascular disorders such as hypertension that worsen with time and increase the risk of early mortality. Obesity also is associated with liver damage that has become the leading risk for needing liver transplants in affected children.
Allergic disorders, particularly asthma, that begin in infancy and childhood markedly limit the capacity of affected children to lead healthy lives. Inflammatory bowel diseases take a devastating toll on the capacity for children to eat normal diets, have normal activity and join in normal childhood activities.
Children from disadvantaged backgrounds – racial, socioeconomic, environmental – are especially vulnerable to adverse outcomes for all of these and many more serious medical conditions.
Q. How can information technology and digital tools help overcome these problems?
A. Throughout all of modern medicine, but especially in children, and most critically in children and preterm infants in intensive care units, information technology and the amount of data collected have expanded well beyond the capacity of any one caregiver – physician or nurse or dietician or respiratory therapist – regardless of how well-trained and experienced, to be able to know and remember and use to make the most effective therapeutic plans, let alone the necessary follow-ups to see what worked and how well and what didn’t work and why.
The advent of electronic health records has helped to document reams of information, but the EHR itself does nothing to liberate that data for any kind of clinical utility. Clinicians document considerable information manually, but they are often unable to organize the data in an efficient yet comprehensive manner that makes a tangible impact at the bedside.
And manually entering prescribed information in the EHR ignores the exponential amount of data from all forms of electrical monitoring that are universal and fundamental in the intensive care unit. Furthermore, clinicians are constantly pressed to not make a mistake, but the overwhelming amount of data is beyond the capacity of any one clinician’s capacity to manage effectively and without error.
Pediatricians are on the front lines of all childhood medical disorders and many forms of childhood adversity that require a solid, evidence-based foundation for understanding causes and developing and administering preventions and treatments.
What makes this requirement especially vexing for preventing these many serious disorders and reducing their adverse effects on children throughout their lifespan is that the expansion of knowledge in the digital age and the incredible amounts of new medical tests and data have increased exponentially.
These disorders require extensive evaluations, collection and analysis of extraordinary amounts of data, and use of such extensive evaluations to provide the most effective approaches to minimizing or preventing bad outcomes.
Unfortunately, most approaches to increased data collection and analytical measures, including artificial intelligence and machine learning, have been focused on adults and their medical conditions. Furthermore, different diseases may impose different burdens on an individual child.
Diseases vary significantly with respect to their pathological features, perceived symptoms, treatment strategies and health outcomes, and the data for each of these is unique and expansive. Furthermore, a “one size fits all” approach to documenting the burden of disease ignores the many unique aspects of a disease in an individual child.
A more effective approach requires multiple data sources to examine each disease in each child when determining the best strategy for treatments. This makes the need for a better approach to data collection and analysis more critical.
As a specific example, preterm infants in the neonatal intensive care unit are exceedingly complex with multiple pathological conditions, extensive numbers of physiological and biochemical and hematological and nutritional tests, and a myriad of treatments, each with significant outcomes that affect health, growth and development.
Because many factors impact the assessment and treatment of such infants, it is essentially impossible for any one person to capture, measure and assess an infant in the intensive care unit in a reasonable amount of time and have confidence in treatment plans.
Information technology has considerable power to enhance the quality and precision of clinical care for infants, especially preterm infants in the NICU, whose medical problems are hugely complex, most often involve all organ systems and commonly are chronic.
This generates huge amounts of data and clinical, physiological and nutritional information. Information technology can rapidly and efficiently provide exceptionally detailed and comprehensive assessments of such enormous amounts of information that can help clinicians understand in much greater depth an infant’s or a group of infants’ conditions and provide more detailed and accurate insight about how to provide more optimal treatment.
Information technology also adds hugely increased capacity to follow medical conditions longitudinally to assess outcomes and how those might be improved. This makes the assessment and treatment of such infants more personalized, more efficient and more effective in much greater detail than any one group of caregivers could provide.
Q. What kinds of outcomes can provider organizations expect from this use of technology with this growing population of children with medical complexity?
A. Protocols, guidelines and best practices. Information technology can provide rapid, comprehensive, and detailed current and longitudinal assessment of many conditions among all infants in the intensive care unit, including how the population of infants in the ICU respond to institution of and changes in clinical protocols.
This not only helps determine how generalizable individual management and treatment plans are but also provides the capacity for research and collaborations with other institutions and their ICUs.
Monitoring. Information technology can play a much greater role in better assessment of the huge amounts of electrical, digital information that is increasingly prominent in ICUs – blood pressure, heart rate, respiratory rate, temperature and blood oxygen saturation (both pulse oximetry and near infrared spectrophotometry or niroscopy).
Information technology can address second-by-second and longitudinal changes in such data in greater detail, allowing better interpretation of the acute and longer-term impacts of singular events such as a fall in blood pressure or repeated events such as apneic spells, biochemical disorders such as hypo- and hyperglycemia, hematological changes such as acute and chronic anemia, and many more.
Diagnostics. Genomic analysis is now capable of providing unique diagnoses of many disorders that were impossible only a few years ago, aiding in understanding the genetic basis of a child’s abnormal behavior or cognition.
Genomic and transcriptomic analyses, modified by the environment (epigenetics), provide unique insights into phenotypic presentations of specific genetic disorders. Proteomic and metabolomic data can be analyzed to document the molecular and biochemical results of altered gene and transcript functions.
Microbial analysis in extreme detail and over time can produce microbiome signatures of many infectious diseases, immunological conditions, responses to nutrition and illnesses and medications that will aid in earlier, more accurate diagnoses and improved and more specific treatments.
Personalized genetic and epigenetic information can help tailor many medications to specific patients and to specific diseases. All of these omics involve huge amounts of data that information technology now can analyze in exquisite detail that can be assessed functionally through artificial intelligence and machine learning derived algorithms.
Treatment plans. Gathering deidentified data from the EHR can provide essential real-world evidence of many aspects of a child’s medical condition, progress – or not – over time, responses to treatments and related outcomes that cannot be accomplished in even randomly controlled trials.
Insights gained from such detailed assessments of past, current and longitudinal data allow for better understanding of conditions and treatments for individuals and ICU populations and the establishment of best practices that most ICUs can’t achieve on their own.
As a specific example, information technology allows use of the EHR to collect and analyze myriad amounts of nutritional data and coordinate with extensive clinical information (gestational age, current and ongoing anthropometric measurements, clinical disorders and their treatments, and laboratory tests).
This can be done at one time and over time to produce much more accurate assessments of nutritional sufficiency – or not – and outcomes such as length, head circumference and weight growth and their prediction of neurodevelopment and cognition.
Presentation of extensive and complex data. A particularly important feature of information technology is the capacity to generate tables and figures that display huge amounts of patient data almost instantaneously and with both depth and breadth as well as longitudinal assessments.
This increases efficiency of medical care and provides much clearer pictures and understanding of how an individual infant or the population of infants in the ICU is doing.
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