Approximately 2/5 persons don't understand their insurance coverage, i.e., which healthcare services are being covered under their current plan and, 1 in 5, "have avoided visiting a doctor for a general health concern within the past 12 months because of cost concerns."
Also, about 1/2 of U.S. adults (117 million) have at least one chronic condition2, of which 14% of (or 16.4 million persons) "have avoided a doctor's visit in the past 12 months because of cost concerns. While chronic conditions such as heart disease, asthma, and diabetes are generally incurable, they can be managed through early detection, improved lifestyle and treatment."
The above is from a Harris Poll survey that was run on behalf of SCIO Health Analytics® as published in 'Survey Reveals One in Five Insured Americans Avoid Seeing a Doctor Due to Fear of Cost" W. Hartford, CT, Jan. 22, 2015 /PRNewswire
The future of health care seemed promising. We had great hopes in chart digitalization, and then the "American Recovery and Reinvestment Act" ("Recovery Act" in short) was born. I'm still waiting, however. It seems we take one step forward only to take three back, Worse, this 'progress' is adding to the cost of care as it gives practitioners a quick and dirty way to code for services not rendered or not justified, examinations not competed and practitioners charging more services than they are worth (i.e., upcoding).
The "Recovery Act" provided $19 Billion and up to $44,000 per doctor to purchase and use the computer system and have it perform in a "meaningful" way.
Why are the benefits of Health Information Exchanges, health information technology and evidence-based medicine not filtering down to the front line of medicine, the primary care practitioners, if not the overcharging specialists?
Health information exchanges (HIE) help in the translation of data into information. They also faciitate giving access to such data, enabling communication, tracking (montoring) and fostering cooperation in patient care. "But HIE can also bring the cooperation between providers to a higher level – population health management, enabled through data aggregation and subsequent health data analytics. Thus, multiple health information exchange vendors start to enable the capabilities for identifying the health needs and risks across the nation."
Lola Koktysh. "HIE For Population Health Management: A Case Study." ScienceSoft Sept. 21, 2017.
See also "In 2nd Look, Few Savings from Digital Health Records," by Reed Ableson and Julie Oreswell, NY Times, Jan. 10 2013; it speaks to a RAND Corporation study, the "2005 Report," which grossly overstated expected savings.
Contrast that with the Consensus Document. It’s more credible having gotten the imprimatur of the AARP, American Academy of Family Physicians, Joint Commission, America's Health Insurance Plans, and the National Committee for Quality Assurance.
Note also, the Act could be a Trojan Horse
In "EHR Financial Incentives Tied to 'Meaningful Use'" [Pediatric News. June 2009;43(6):34], "Dr. John Halamka defined this phase of health care information technology as “processes and workflows that facilitate improved quality and increased efficiency.” The same article also spoke to the Markle Foundation's “simple” definition of patient-centered "meaningful use"–“The provider makes use of, and the patient has access to, clinically relevant electronic information about the patient to improve patient outcomes and health status, improve the delivery of care, and control the growth of costs.” [Here I have to make a distinction - the Foundation is really talking about sharing "data," not "information," per se. They could be one and the same, however you need analytics to translate data into information, and, currently, health care analytic expertise and real-time, point of contact heuristics is in short supply.]
Surely there will efficiencies gained by digitalizing the patient registry, appointment scheduling, the medical record, tests, orders, plan, prescriptions and patient education. However, I find myself documenting what "should be," not "what was." And don't even think I am being dishonest, either. Yes! I want what should be for my patients, but what I think is medically necessary in the office, may not be on the patient's priority list of things to do when they have left it–After all, what I recommend may not be affordable; the family may have competing interests; they're nervous, not hearing and they simply don't understand. They've got 'better' or more pressing things to do then take the medicine 4 times a day, get the X-ray for an ankle sprain or apply the hot soaks, as directed.
We now have HIPPA "protections," but with it I am often finding it difficult to get the other doctor's or hospital's records or labs. And who can blame them?–We don't have a collaborative relationship, after all. (So much for "meaningful use," which assumes there will be good communication and let turf issues be damned). And then there's Big Brother-1984, looking over my shoulder– could the EHR be an entry to governmental oversight? I have no problem with unobtrusive feedback into my practice (and I know the value of acuity indexing, a longitudinal patient record and an "episode of care" kind of picture [see 3M™'s CRGs, below]), but 'been there; done that.' Indeed, one of the reasons HMOs lost favor was they became judgmental and uncaring—the business of medicine rather than medical business; you know, 'Monday Morning Quarterbacking'—"Doc, I'm really on your side; I'm here to help ya." And,
- Oh, Dr. Kaplan: We see you've not immunized X patients. (Could it be that I'm not their PCP?)
- Dr. D. Mellitus: Your Hgb A1c levels? (Could it be that some of these patients lost their coverage or are non-compliant?)
- Dr. C.A.P.: Too many of your patients are being admitted to the hospital. (Could it be that many of them continue to smoke? Could there be financial barriers to access? Are there enough primary care practitioners?)
- Etc., Etc.
An even greater disappointment is that my iPhone can tell me when I've not filled in the blanks correctly, but my electronic health record (EHR) cannot even alert me to duplicate, fractionalized, inefficient, or ineffective care, patients who are 'lost to follow-up' (falling through the cracks, communication failures, opportunity costly), endemic disease, trends, resistent organisms, epidemics, discoveries in medicine or denials.
The "What," "Why" and "How"
I am convinced the way to gaining this awareness lies within HIE and HIT, but first we need need, with sufficient granularity,* the "why," "how," and "what" defines the health care the patient has received and what has been ordered but not completed—the big picture, in other words and that the longitudinal record or the episode of care—all the care over time, regardless of setting like 3M™'s CRGs. Also, here's a paradigm shift–we also would be remiss if we didn't factor in the patient's life events, the vicissitudes of life, biases, prejudices and fears, and the affordability of care.
- "Why" is the patient seeking care? What are their needs and expectations? Why, for instance, did they go to the E.R., unbeknownst to me? Is that test going to help or is it just ordered as a CYA precaution (because of the fear of someday being accused of malpractice)? Do I understand the patient? Do they understand me?
- Then there's the "how"of medical practice. You can get that aspect from Donabedian's structure, process and outcomes of care.
- The "what" is simply a fair representation of what works and what does not. In I.T. terms that means closing the feedback loop at the point of contact with the patient and communicating better.
Clarification of "granularity"
"ICD – any version including 10 – is a pretty blunt instrument for representing the clinical aspects of a patient encounter. Rarely do physicians use it for their purposes, which has led them to invent more detailed systems like SNOMED. Perhaps when computers get even more powerful and can be fed a few years worth of rich EHR data to learn from, they can deduce broad categories from fine detail. But for now, blunt is what the rest of us who are concerned with payment and analysis prefer."
Heterogeneity and Uncertainty
When data scientists build statistical models to predict how children may be affected by environmental insults or respond to nutrition interventions, they must distinguish between uncertainty (accuracy of measurements) and heterogeneity (healthy and pathological variability within and among children). Integrated data sets enable us to test correlations and covariation between pertinent variables more effectively than we could with individual data sets, helping us to separate signal from noise, quantify effects at the extremes of distributions, build accurate models, and understand how to give the right intervention to the right child at the right time for the right cost.
N. L’ntshotsholé Jumbe, Ph.D., Jeffrey C. Murray, M.D., and Steven Kern, Ph.D. "Data Sharing and Inductive Learning — Toward Healthy Birth, Growth, and Development." N Engl J Med 2016; 374:2415-2417June 23, 2016DOI: 10.1056/NEJMp1605441
- American Health Information Management Association (AHIMA); Planning & Preparation Checklist; see: http://library.ahima.org/
- Workgroup for Electronic Data Interchange (WEDI); ALO< vendor Questions, [Link difficulties 3/20/15, but try nchica.org/]
- Centers for Medicare & Medicaid Services (CMS); ICD-10ImplementationTimelines.html
- Soni SM, Giboney P, Yee, Jr HF. "Development and Implementation of Expected Practices to Reduce Inappropriate Variations in Clinical Practice." JAMA. 2016;315(20):2163-2164. doi:10.1001/jama.2016.4255.
"Variation in clinical practice is substantial and is associated with poorer health outcomes, increased costs, and disparities in care.[1,2]" Therefore, reducing unnecessary differences in practice patterns. is a reasonable, but difficult objective. "Challenges to reducing variation include heterogeneity and gaps in clinicians’ knowledge; economic incentives for undesired clinical behaviors; concerns about malpractice risk; physicians’ value of autonomy and personal preference; inadequate communication and decision support tools; and imbalances between clinical demand and resource capacity. Another fundamental barrier to practice standardization is that good clinical practice must sometimes vary to reflect a patient’s specific social, environmental, and biological situation. Sometimes a standard practice would not be best for a given patient" [etc.]. Hence, there may always be exceptions to prescriptive guidelines, protocols or best-practice standards.