Results from Scientific Studies Are Not Synomymous With Actual Value In Healthcare Practices

 

Results from scientific inquiry do not necessarily create value in health care practices. Read this article to understand why and what we should be doing differently to build population health and economic value.

Scientific studies and clinical trials do not necessarily equate to actual value in clinical practices for patients and health systems. Scientific inquiry is of course necessary, as are clinical trials, but even if these avenues of inquiry demonstrate statistical significance and adequate patient safety, there are other factors that must be considered to create value for population health and for each practice and unique patient. The most important thing in research to improve our health is to ask the right questions. Currently, in scientific inquiry, once an investigation question is identified, it is called the hypothesis, and methods are chosen for controls, measures, and reporting of the data. A randomized control trial is held to the highest standard for this inquiry process, with excellent controls, attempts to eliminate bias, and recognized quality standards. Following this process, if the science finds merit to conduct a clinical trial on patients, this is the next step. This all sounds good, except scientific studies and clinical trials do not reflect real world variables in medical care. There is a field of study, called Real World Effectiveness (RWE) which has been under research for several decades, and there are now improved methods to assess actual effectiveness before a health system adopts a new intervention in health care and it has nothing to do with profits.  Briefly, here are the reasons the current study methods do not provide the information patients and health systems need to optimize efficacy of treatment. (Porzsolt, 2024) (Franz Porzsolt M. W., 2024) Efficacy means the efficiency and the treatment or evidentiary value of an intervention.

1.  Scientific findings of statistical significance are not synonymous with value in the real-world practice of medicine.

2.  Scientific studies do not necessarily include patient populations which are similar in a medical practice, because patients may have multiple co-morbidities, which may exclude them from study participation.

3. Clinical trials attempt to show actual treatment effectiveness, but there is also bias in the patient selection for clinical trials, because the drug company or medical device manufacturer want to show their product works. Thus, clinical trials cherry-pick patients who will conform to the methodology restrictions, and not include a lot of other issues such as health comorbidities.

4. Real world medical practices have many more variables than clinical trials. This is primarily due to the intimate relationship the clinician has with the patient and the customized approach he or she may use to meet the best treatment paradigm for her patients. This phenomenon makes it nearly impossible to make uniform strategies for all the risk profiles.

Thankfully, there is a method for identifying real world impacts of treatments, which would allow health systems and most importantly, the patient, to identify whether a drug, medical device, or procedure is worth it. Just like anything else which informs a decision, the individual weighs risks, potential benefits, proven reliability, and the cost. Unfortunately, unless you work in medical research, are a clinician, or some policy expert, you will not have this information to inform your treatment process.  In many healthcare systems today, the person has more information up front on the vehicle they purchase, then a health care intervention. This practice needs to change and I outline how RWE works and can be applied in real clinical settings here.

The Cochrane strategy, which is the international standard for the highest degree of efficacy in research includes these three questions: (Franz Porzsolt, 2024) The first question is called the principle of proof (POP)and means, can the intervention work. The second question is does the intervention work and what is the real-world effectiveness (RWE) through pragmatic (clinical trial) or observational study (used where clinical trial is not an appropriate study method). Further study will either demonstrate effectiveness or not. But the third question that needs to be asked is does this intervention demonstrate enough value given other treatments currently available. All too often this is swept aside so that the new drug or treatment will supplant existing more economical ones, because of monetary incentives. The third question needs to be applied to any patient health intervention so that the best use of resources for each patient is considered. Currently, in the United States this comes into play based on the type of insurance a person has, because everything is driven by reimbursement, and volume of care. Providing more expensive care to people who can afford it does not mean their outcomes are necessarily better, especially from a population health standpoint. Benefiting a few outliers does not mean large populations would necessarily benefit. The solution is to observe the actual outcomes of care in a medical practice, which is somewhat like the Centers of Medicare and Medicaid Innovation Grant Programs. Unfortunately, there is often a rush to bring a drug or medical device, or practice into approval and adoption before the actual patient effectiveness has been vetted. This results in wasted money and patient harm in many instances, because organizations feel pressured to show their idea works and to receive recognition and of course financial remuneration.

Finally, why do we care about further refinement of experimental results and treatments, because we can treat more people optimally for less money if we include the question, Is it worth it, in our final decision model before adoption of the treatment. This requires decisions to be made at a systemic level, in clinical practice, and as an informed patient.  Only by including the last question and comparing results will we learn what is actually the best treatment for various patient groups. People are not a one-size-fits-all and we should not be using science to justify treatments for some as appropriate for all.

And this is the healthpolicymaven signing off, encouraging you not to sign blanket release forms when you have medical procedures, do stipulate that for which you agree and for which you decline. Also, it is a good idea to get a POLST document in place with your health system, which states your wishes for interventional treatment to extend your life. And this is not the same as a medical power of attorney, whom you have chosen, but it alerts EMT's and others in the care continuum.

Roberta Winter is a freelance journalist who accepts no money from health care entities for this column. Opinions expressed here are her own. Her guidebook to the U.S. healthcare system was published by Rowman & Littlefield in 2013. https://rowman.com/ISBN/9781442222977/Unraveling-U.S.-Health-Care-A-Personal-Guide

References

Franz Porzsolt, M. P. (2024). The Front-End Processor Developed By Engineers-A Useful Tool for Describing the Quality and Quantity of Progress in Healthcare. Qeois-Open Peer Review, 1-19.

Franz Porzsolt, M. W. (2024). Applying the Rule of Designers and Architects "Form Follows Function (FFF) Can Reduce Misinterpretations and Methodical Shortcomings in Healthcare. Trends in General Medicine, 2(1), 1-7. Retrieved September 2024, 2024

Porzsolt, F. (2024). An Evidence-based Hypothesis: Doctors Do Not Make Decisions Randomly but Based on Individual Patient's Risk Profiles. Private Research Insitute of Economics (PRICE), Ulm, Germany, 1-11.