Commentary :
Healthcare
is a complex combination of system engineering and clinical science which
includes many aspects of care and numerous types of professionals, including
clinical providers, information technologists, data scientists, insurance professionals,
pharmacists, etc. Clinical
care in system engineering should be evidence-based and have a wide
research base to ensure quality care. Medical professionals, patients,
technologies, insurance, policies and standards, etc. ensure quality care in
system healthcare engineering. Currently, Big Data analytics help form
healthcare systems, policies and procedures, treatments and assessments, and
achieve better outcomes, also leading innovation and research to strengthen
evidence-based medicine. Neuroscience
is one are today that patients are finding it necessary to expect personalized
treatment and an evidence-based plan of care due to the complications
associated today with opioid use and chronic pain management. Acute and chronic
pain management spending is reaching heights never expected. The use of
opioids has become so rampant that even adolescents are using prescription
narcotics for pain relief. Overwhelmingly, at the top of the list for
behavioral problems today is opioid overdose, now a severe problem in the US as
addiction becomes a primary factor in treating behavioral problems. Currently
our emergency providers need education and access to medications such as
Narcan, which is an antidote for opioid overdose and reverses the effects to
instantly reduce the symptoms and sequalae associated with opioid use [1].
Using Big Data analytics, providers can manage the massive amounts of data
associated with acute and chronic pain management such as -omics, sensor data,
smartphone data, social media data, clinical data, family and patient history,
etc. Chronic and acute
pain treatment now dominates primary care, specialty care, and emergency
departments nationwide. Our providers are becoming increasingly overwhelmed by
the number of patients with chronic pain; clinics and emergency departments
nationwide are just unprepared to deal with the sheer number of complaints and
complications related to opioid use.
Unfortunately, self-medication
has become a toxic problem among many age groups, including teens, young
adults, and even middle-aged adults of both sexes who self-medicate with
friends’ and family members’ narcotics, leaving too many patients with fatal or
near-fatal opioid intoxication. Also, chronic
pain treatment has reached an all-time high but the use of
narcotics on a regular basis for chronic pain results in a high number of drug
addiction problems, as well as manyunforeseen clinical side effects
such as constipation, respiratory problems, etc. [2]. Healthcare providers in
all clinical areas should receive special training and should recognize the
problems associated with pain management as these patients require extensive
time and understanding. Social media has become an
excellent resource for providers as well as patients, as individuals suffering
from pain often turn to one of the numerous outlets such as Facebook, Twitter,
Instagram, etc. as an outlet for expressing feelings related to pain
management, such as pain, pain relief, what works, what doesn’t work, and
side effects. Other important resources include smartphone apps, sensors,
wristbands, etc. which can help document symptoms and side
effects to help providers with treatment [3]. It is also important for
society to come to an understanding of the complex intricacies associated with
pain and pain management. Pain management treatment options can not only lead
to overuse, misuse, and addiction; overdose, fatalities, and long-term
disabilities can result from narcotic use as well as family problems, loss of
relationships, financial, and other psychological
problems. Nurses and physicians must also consider another crucial factor:
their own attitudes about patients with pain. Many patients develop a
“frequent-flyer” reputation, or worse, a “drug
seeker” reputation when they do not get adequate treatment for pain and use
the emergency department for intermittent pain relief. Many emergency providers
do not like to prescribe or even medicate patients with opioids due to the much
legality associated with the drugs. Patients who present in primary care are
likely to receive more compassionate treatment than patients who present in the
emergency department due to healthcare provider perceptions of seeking
treatment for chronic pain in the emergency department of clinic. Long-term use
of narcotics can also result in serious side-effects such as constipation,
sleepiness, disability, depression, anxiety, etc. Public
health has been seriously affected by the long-term use of opioids.
Modern data registries, created
to take advantage of the use of EHR systems, are all wanting data to move
directly from the medical record to the databank, without requiring human
construct. The problem with this model is the heterogeneity of today’s
electronic data. A few elements, such as vital signs and medication
doses, are relatively standard from one EHR system to another, but other
essentials, such as outcomes and complications, are deficient in consistent
definitions across practices and software vendors. There are several types of
questions that cannot be asked using single datasets that are supported by the availability
of large shared datasets [4]. In standard cognitive
neuroscience studies, one generally uses a manipulation within a single
task to identify the neural systems that are putatively involved in the
manipulated mental process. This approach has resulted in the association of
several brain regions with a varied range of mental processes; for example, the
anterior cingulate cortex has been associated with mental processes as diverse
as pain, speech, cognitive
control and tongue movement. An alternative method, which has the potential
to provide more selective structure-function associations, is to examine the
underlying neural components that span across multiple task manipulations.
Therefore, data science in an atmosphere of healthcare systems engineering will
have far-reaching consequences such as transferring data from one EHR system to
another easily, data mining for history of both patient and family, examining
vital signs, complaint data, etc. This ease of data access will allow the
clinician to become an expert on the patient’s needs and status. For example,
for a patient taking narcotics, if the patient travels from one doctor to
another in various states, data mining can produce quick results and indicate
fraudulent activity and prevent serious side-effects from overdose. One of the most relevant
discoveries about data is that as more data becomes accessible to computer
algorithms, predictions can be made with greater precision. Research into the
field of machine learning for natural language has found that statistical machine
translation and statistical speech recognition
have become much more precise as more and more data have become available.
Opioid use is at a crisis level in the United States. Providers need a clinical
weapon that will wipe out the far-reaching toxic effects of this serious and potentially
fatal epidemic. With data mining, the use of Big Data analytics, so much
information can be at the clinician’s fingertip at any time. 1. Dutton RP. Using big data for big
research: MPOG, NACOR and other anesthesia registries (2015) Anesthesia
Business Consultants, USA. 2. Poldrack RA and Gorgolewski KJ.
Making big data open: Data sharing in neuroimaging (2014) Nature neuroscience 17:
1510-1517. https://doi.org/10.1038/nn.3818 3. Nambisan P, Luo Z, Kapoor A,
Patrick TB and Cisler RA. Social media, big data, and public health
informatics: Ruminating behavior of depression revealed through twitter (2015) 48th
Hawaii International Conference, USA, 2906-2913. https://doi.org/10.1109/HICSS.2015.351 4. Volkow ND. National Institute on
Drug Abuse 2016-2020 Strategic Plan (2015) White Paper, UK. Alexander
CA, Chief Research Scientist, Technology and Healthcare Solutions Inc, USA,
Tel: 207-213-7408, E-mail: cheryl@techhealthsolutions.org Alexander
CA. Healthcare Big Data and Pain Management: A Look into the Epidemic (2018)
Nursing
and Health Care 3: 65-66 Pain management, Health care, Clinical care
Healthcare Big Data and Pain Management: A Look into the Epidemic
Full-Text
References
*Corresponding author
Citation
Keywords
