OIG Approach To Medicare Part D Opioid Prescribing

The pharmacoepidemiology of opioids in the United States depends on a fragmented approach.  I recently posted a CDC study that used a commercial pharmacy database to look at the characteristics of opioid prescribing across individual counties in the United States.  In the past week I came across this data brief from the Office of Inspector General (OIG) of the US Department of Health & Human Services.  Their database is the 43.6 million beneficiaries of Medicare Part D.  Their stated goals are to protect beneficiaries and the community from prescription drug abuse, to prevent diversion and illegal sales, and to protect the program from fraud and unnecessary expense.

Their methodology is unique.  They look at prescription drug events (PDE) for all opioids prescribed in 2016 that are paid for by Medicare Part D.  Any prescription paid by cash or by another insurer is not counted.  Every time a prescription is dispensed and covered by the program a PDE record is sent to CMS (Centers for Medicare and Medicaid Services).  In this case they calculated total spending on opioids, total Schedule II and III opioid prescriptions, and a number of parameters that look at total cost.  They also determined the the prescriptions per beneficiary, and the average daily morphine equivalent dose (MED).  In most of the literature on opioid dosing the milligram morphine equivalents (MME) is a common measure.  MME is just the total mg of opioid multiplied by a conversion factor.  The MED is basically the same measure but it factors in the total duration of the prescription.  As an example for a one day supply of either Vicodin (hydrocodone) 10 mg tabs or Percocet (oxycodone) 5 mg tabs:

 hydrocodone:  12 tabs x 10 mg = 120 mg x 1 (conversion factor) = 120 MME or MED

oxycodone:      16 tabs x   5 mg  = 80 mg x 1.5 (conversion factor) = 120 MME or MED

In addiction practice these are common doses encountered in the low range of prescription opioid use disorders.  I used the brand names for hydrocodone and oxycodone preparations here because that is what people commonly report to me and it typically requires more investigation.  For example "Percocet" or "Perc30s" commonly refers to higher dose oxycodone without acetaminophen - a single 30 mg tablet of oxycodone or 45 MME.  The authors of this brief do not need to be concerned about those data discrepancies because they are able to get specific claims data.

In terms of outcome data, they looked at all of the prescriptions and cost variables as well.  They looked at total exposure.  One in three Medicare Part D beneficiaries received at least one opioid prescription.  That amounts to 14.4 million people out of a 2016 beneficiary base of 43.6 million people.   There were a total of 28.2 million hydrocodone-acetaminophen prescriptions, 5 million oxycodone-acetaminophen prescriptions and 14.8 million tramadol prescriptions.  Tramadol is not typically included in opioid studies even though the M1 metabolite is a mu receptor agonist.  Tramadol is a prodrug metabolized by CYP2D6, metbolism is necessary to to create M1 and slow metabolizer are less likely to experience the analgesic effect and addiction risk.

Of these beneficiaries 501,008 received high dose opioids (MED > 120 mg/day).  The indication here was for noncancer or chronic noncancer pain.  Hospice patients and cancer patients were excluded.  The most common opioid prescribed in this high dose group was oxycodone 30 mg.  The study also defined extreme amounts of opioids as an MED of 240 mg and 69,563 patients received that amount.  There were 678 patients receiving high extreme amounts a MED of 1,000 mg for an entire year.  The concern with very high levels is whether the prescriptions are indicated and whether they might be diverted.  The authors also suggested that fraud could be an issue due to stolen Medicare identification number.  They did give an example of a patient who got 62 opioid prescriptions on one year (61 from the same family physician) with an average daily MED of 3,130 mg.

The brief also estimates the degree of doctor shopping or seeking prescriptions from more than one physician and pharmacy.  The criteria used for this report was 4 prescribers and 4 pharmacies.  A total of 22,308 beneficiaries met that criteria and they also had an average daily MED > 120 mg for a period of three months.  They also identified 162 beneficiaries who got opioid prescriptions from 10 different prescribers and 10 different prescribers in the same time period.  Even larger number of prescribers and pharmacies were noted in the most extreme cases.  That number represents about 0.02% of the total number of beneficiaries using opioids and that is the same order of magnitude of a previous estimate from a large commercial prescription database (4).  

Using the estimates of high dose opioids and degree of doctor shopping allowed for an estimate of serious risk of opioid overuse or overdose.  The number estimate in that category was 89,843 or about 0.6% of the entire group taking opioids.

The brief also looks at the issue of who is prescribing the opioids.  For the 89,843 there were an estimated 115,851 prescribers who wrote at least one of those prescriptions.  A total of 401 prescribers were determined to be "far outside the norm".  One hundred and ninety eight ordered opioids for patients getting extreme amounts of opioids (MED of 240 mg), 264 ordered opioids for patients who appeared to be doctor shopping, and 61 ordered opioids for patients who were members of both groups.  The total number of prescriptions written by prescribers in this group was 256,260 opioid prescriptions.  There were 15 prescribers who ordered opioids for > 98 beneficiaries receiving extreme amounts (MED of 240 mg).   Of the 401 prescribers with questionable prescribing 1/3 or 133 were nurse practitioners (N=81) or physicians assistants (N=52).

Are there any conclusions possible from this administrative look at opioid prescribing in a subset of Medicare patients?  I think that there are a few.  My conclusions assume that generalizations from this data are possible:    

1.  Opioids are commonly prescribed to Medicare recipients - and the vast number of these prescriptions appear to be appropriately managed.

2.  A small number of prescribers appear to be responsible for most of the inappropriate prescriptions - and there are some outliers practicing at the extremes in terms of prescribing patterns.  Very extreme prescribing described in a few cases would appear to be a function of unnecessary use rather than patients with special needs who require extremely high doses of opioids (MED > 375 mg).  That is an important point because concentrations of high dose opioid prescribing is often attributed to the special needs of patients or referral patterns resulting in concentrations of these patients and the need for the prescriber to write prescriptions for these amounts.  If this was a case of biological variability - a much larger fraction of the patients who require extreme amounts of opioids.

3.  The problem of inappropriate prescriber appears to be easy to follow on the CMS data base - the standard political approach to the opioid epidemic is to blame all doctors and mandate various education programs about opioid prescribing.  It should be clear that a minority of physicians or in this case prescribers are problem and there should be a targeted approach.  At the very minimum the prescribers in the top 1% of all prescribers or the group who is prescribing extreme amounts of opioids, to people who are probably doctor shopping, or both should be receiving active feedback from CMS.

4.  Not counting opioids prescribed for cancer or hospice care is an important omission -  This is a problem with very little research or policy making.  Patients undergoing end-of-life care are  prescribed liberal amounts of opioids for pain relief.  There is no question that these patients should have adequate pain relief by whatever medication is necessary.  The question is what happens when there are opioids from these prescriptions that the patient never uses?  One palliative care study (3) noted that of the hospice care agencies responding to their poll, over a third noted that substance use and diversion were a problem for their agency.  Diversion of drugs is known to occur in health care systems where there is monitoring and checks and balances.  There are large amounts of opioids out in in-home hospice care settings with much less accountability.  A similar study looking at the amounts of opioids prescribed in these settings and what happens to that medication is needed.

5.  Opioids are not prescribed in isolation - CMS and the OIG are not medical research organizations.  A more comprehensive approach to the problem would look at all of the medications that these patients are receiving and not opioids in isolation.  Benzodiazepines frequently accompany opioid prescriptions and in some cases with sedative hypnotics for sleep.  Prescribing both compounds can lead to serious and in some cases fatal drug interactions.  That would result in an additional category of inappropriate prescribing of opioids.

Although this is an administrative database, it does illustrate how this data can be used for pharmacosurveillance purposes.  There was emphasis about the cost of opioid prescribing and the need to prevent fraud from a CMS perspective.  The data could also be used to provide valuable feedback to physicians and other prescribers as well as politicians and regulators.

It can be used to counter some myths that seem to exist on both sides.


George Dawson, MD, DFAPA




References:



1:  US Department of Health and Human Services: Office of the Inspector General.  Opioids in Medicare Part D: Concerns about Extreme Use and Questionable Prescribing.  HHS OIG Data Brief OEI-02-17-00250.

2: CDC, “Increases in Drug and Opioid-Involved Overdose Deaths: United States, 2010–2015.” MMWR Morb Mortal Wkly Rep, December 30, 2016, pp. 1445–52. Accessed at https://www.cdc.gov/mmwr/volumes/65/wr/mm655051e1.htm on July 16, 2017

3: Blackhall LJ, Alfson ED, Barclay JS. Screening for substance abuse and diversion in Virginia hospices. J Palliat Med. 2013 Mar;16(3):237-42. doi: 10.1089/jpm.2012.0263. Epub 2013 Jan 5. PubMed PMID: 23289944

4: McDonald DC, Carlson KE. Estimating the prevalence of opioid diversion by"doctor shoppers" in the United States. PLoS One. 2013 Jul 17;8(7):e69241. doi: 10.1371/journal.pone.0069241. Print 2013. PubMed PMID: 23874923.

Significantly Lower Mortality With Antipsychotic Use

It is always an interesting phenomenon to see the headline grabbing news about how toxic psychiatric medications are killing people.  At first it was just  cult news, but these days it seems that some people can make a fairly good living at it.  A knowledge of psychiatry or clinical experience is never a prerequisite.  It always requires the reader to suspend their sense of reality and what they know happens in real life.  That reality is that a family member, neighbor, or friend was having some very serious problems - saw a psychiatrist and got better.  It also requires a suspension of belief in the tremendous history of what happens with untreated psychotic disorders both in terms of morbidity and mortality.  Finally it requires suspension of a belief in the usual regulatory mechanisms.  If so many people were dying from treatment - it would be obvious and somebody would be held accountable.  Every state has medical boards that basically solicit complaints against physicians.  Surely any group of physicians prescribing an inordinately toxic medication would come to light.  You have to suspend all of these realities of course because none of it has occurred.  Despite those reality factors there are any number of antipsychiatrists or people claiming to be critics who are basically using the same rhetoric warning people about the toxicities and how many people are killed by these medications each year.  Some of their estimates are astronomical and suggest a clear and biased agenda.  Actual community surveillance reveals an accurate picture and the medications with the highest complication rates are easily recognized by any psychiatrist or primary care physician.

That is not to say that the medications prescribed by psychiatrists are perfectly safe.  As I just posted - no medical decision including one that involves taking a common medication is risk free.  I spend a good deal - if not over half of my time warning people about side effects that will never happen, warning people about severe but rare side effects, managing side effects that do happen, and screening for potential side effects that might go unnoticed by the patient like electrocardiogram abnormalities or blood tests for a specific bodily systems.  In 30 years of practice, I have diagnosed the most severe problems including serotonin syndrome, neuroleptic malignant syndrome, prolonged QTc interval, various degrees of heart block, arrhythmias, myocardial infarctions, strokes, drug-induced liver disease, agranulocytosis, diabetes mellitus, diabetes insipidus, hypo/hyperthyroidism and many other that were either caused by a medication or picked up as a result of my screening for a medical complication or pre-screening for safe use.  But relative to primary care, the number of diagnoses in psychiatric practice for this reason is smaller.  The most significant cause of mortality in psychiatric populations is cigarette smoke.  The most significant number of medical conditions are pre-existing and if the psychiatric disorder is caused by an underlying medical condition - it is not common.

All of the factors in the first two paragraphs led me to read an article on the epidemiology of antipsychotics, antidepressants, and benzodiazepines in a well determined population and the effects on mortality in the June American Journal of Psychiatry.  The authors have a number of studies that appear to use a similar epidemiological approach.  For this study they identified cohort participants from national health care registers of all people 17-65 living in Sweden in 2005.  They identified anyone receiving health care for schizophrenia or psychosis (by ICD-10 codes) and anyone on disability for schizophrenia.  They also  determined all of the antipsychotics, antidepressants and benzodiazepines dispensed from 2006-2010.  They were classified by Anatomical Therapeutic Chemical Codes (ATC codes).  They calculated cumulative exposures using the WHO defined daily dose (DDD) methodology.  The WHO web site has a search engine that will let you search for the defined daily dose of medications.  Examples for antipsychotic medications would include 10 mg for olanzapine and 5 mg for risperidone.  The researchers summed the follow up days minus any hospitalization days and divided this into the sum of the dispensed medication.  That allowed the subjects with schizophrenia to be broken into four DDD groups: 1) no antipsychotics, antidepressants or benzodiazepines during the follow-up, 2) low dose -  small or occasional medications (0-0.5 DDD/day), 3) moderate doses (0.5-1.5 DDD/day, inclusive), and 4) high doses (>1.5 DDD/day).  Using the olanzapine example that would mean a dose range from 0 - >15 mg/day cross all 4 groups.  

A total of 1,591/21,492 or 7.4% of the cohort died in follow-up.  That was 4.8 times higher than a control group of age and gender matched patients.  The commonest causes of death were cardiovascular disease, neoplasms, respiratory diseases, and suicide in that order.  No interactions were noted at the level of demographic variables.  Mortality rates and hazard ratios for antipsychotic, antidepressant, and benzodiazepine use were calculated and the following observations were noted:

1.  Any exposure to antipsychotics or antidepressants was associated with a lower rate of mortality (15-40% lower) compared to no use.          

2.  High exposure to benzodiazepines was associated with a 74% higher risk of death than no exposure.  Benzodiazepine users had the highest mortality, highest risk of suicide, and more frequent visits to health care services.  

3.  In terms of cardiovascular mortality, only high dose antipsychotic use showed an equal mortality to no exposure to antipsychotics with low and moderate dose showing decreased mortality.

4.  A sensitivity analysis of first episode patients showed that there was a decreased risk of mortality with exposure to low and moderate exposure to antipsychotics and increased mortality with exposure to moderate to high dose benzodiazepines.  More striking is the fact that during the follow up period this was a cohort of 1,230 patients and 45 (4%) of them died.  Most of the patients with first episode psychosis who I treated were otherwise healthy 20 year olds, illustrating the significance of this problem.

This is an excellent study from a number of perspectives.  It looks at well defined data across a population that is generally possible only in Scandinavian populations.  By contrast studies done in the US typically look at either incomplete retail pharmacy data designed originally for pharmaceutical sales or detailed health interview data that is based entirely on self report using long and detailed questionnaires.  The study uses WHO methodology suggested for pharmacoepidemiological research.  The follow-up period is during a times when most atypical antipsychotic medications are widely available.  These are the drugs that are suggested as a source of higher cardiovascular mortality in psychiatric patients.  The authors findings are discussed in light of several other studies that show similar effects.

 The finding of this study will come as no surprise to acute care psychiatrists across the US.  It is the reason why psychiatrists cover these settings despite the hardships involved.  They know they are treating very difficult problems with very little assistance and that even in the absence of a continuum of care they can be successful.  These psychiatrists are also aware of the medication toxicity and more importantly as this article points out - they can identify high risk patients and safely treat them.  Despite the concerns about the metabolic effects of atypical antipsychotic medication there is an implication that other factors (like smoking) may be more significant in the development of cardiovascular disease (3).  The risk of antidepressant and antipsychotic medication can be seen in an appropriate context in this study and that is lowering mortality rather than causing it.

The study also provides very useful guidance on benzodiazepine use.  In my opinion, benzodiazepines should be used only briefly for the treatment of catatonia and acute agitation in patients with psychotic disorders.  They should not be used on a long terms basis.  I agree with the authors' idea that tolerance is a problem.  When dose escalation fails or results in withdrawal and panic attacks or protracted insomnia, the risk for impulsive behavior and increasing depression is much greater.  More frequent primary care visits can also occur due to tolerance and the need for dose escalation and more discussions of appropriate use.  Treating this population in the United States is problematic because at a certain point, people can be safely detoxified from benzodiazepines only in an inpatient unit, and those services are widely unavailable.   This study is a blueprint for quality assurance projects using the same methodology on electronic health records (EHR) across the country.   Every clinical population should be examined using the authors' techniques and followed for outcomes and active interventions.

The reference provides an opportunity to see the realistic risk and benefits of treatment in people with high risk psychiatric illness.  It also presents an opportunity to use this methodology to provide better treatment to people with the same illness and prescription profiles everywhere.  Instead of using the EHR to catalogue useless full text information and track physicians, the authors methods can be used with much finer tracking of details like BMI, blood pressure, smoking status and other relevant lifestyle factors.  Apart from the aspects of polypharmacy, the overall difference in mortality due to a diagnosis of a psychotic disorder needs to be addressed, and it needs the level of detail available in an EHR.  Psychiatrists in major health plans using large databases could get active feedback in a very similar manner.  The EHR could finally be used the way they advertised it a decade ago.         

George Dawson, MD, DFAPA

1: Tiihonen J, Mittendorfer-Rutz E, Torniainen M, Alexanderson K, Tanskanen A. Mortality and Cumulative Exposure to Antipsychotics, Antidepressants, and Benzodiazepines in Patients With Schizophrenia: An Observational Follow-Up Study. Am J Psychiatry. 2016 Jun 1;173(6):600-6. doi: 10.1176/appi.ajp.2015.15050618. Epub 2015 Dec 7. PubMed PMID: 26651392.

2: Robinson DG. Early Mortality Among People With Schizophrenia. Am J Psychiatry.2016 Jun 1;173(6):554-5. doi: 10.1176/appi.ajp.2016.16030334. PubMed PMID: 27245185.

3:  Newcomer JW, Hennekens CH. Severe mental illness and risk of cardiovascular disease. JAMA. 2007 Oct 17;298(15):1794-6. PubMed PMID: 17940236.

The Beginnings Of True Pharmacosurveillance

From:  Morbidity and Mortality Weekly Report (MMWR)  October 16, 2015/ 64 (9): 1-14.

I am an advocate of real pharmacosurveillance of anyone prescribing medications in the United States.  To some that might seem like a controversial statement and it needs to be argued at a couple of levels.  There will be some privacy advocates who suggest that medication information is protected information.  Sensitive medical information can be extrapolated from prescriptions and all medical diagnoses are not seen as equal in the eyes of employers or average citizens.  In this era, the knowledge that a person has a significant amount of specific medication in their possession may also put them at risk for theft or exploitation.  There are very good reasons for making sure that this information is not leaked to the general public.  The overriding argument is public safety defined as making sure that a person seeking medical help is going to see competent physicians or in this era competent prescribers.  There are many reasons why a prescriber may not be competent and may put patients at risk, but one of the most significant reasons is that they have developed a practice or prescribing that makes them an outlier.  They are prescribing medications or combinations of medications in a manner that is not like the majority of practitioners. That prescribing pattern may be frivolous or unsafe.  In the case of unsafe patterns, the practitioner should receive immediate feedback and where necessary intervention.

Some reviews currently happen at some level in the US.  In hospitals and care systems where there is routine review of physicians, some cases are reviewed prescribing patterns are observed and they are given feedback.  That process is limited by a lack of standardization and objectivity.  Just a few cases may be reviewed when today's information technology (IT) capability allow for reviewing all of a physician's caseload all of the time.  The review is often part of a larger process like an annual review where there may be conflicting agendas like spinning the review to make the person look as good or as bad an an administrator wants them to look.  Physicians can also be contacted by managed care organization (MCOs) or pharmaceutical benefit managers (PBMs) with letters expressing various concerns.  Examples might be patients who have filled only one prescription for antidepressants, patients seeing multiple prescribers, and polypharmacy.  These letters are often poorly thought out, probably don't apply to the physician or patient at the time the letter is sent, and seem to be heavier on public relations than the technical details of prescribing medications.  In some cases these reviews can be totally inappropriate.  To cite an example, a reviewer notifies nursing staff that a patient on lithium needs follow up and immediate blood tests upon discharge because the inpatient physician has not ordered the appropriate tests when they do not have the most recent records, have not spoken to that physician, and don't know that all of the testing has been done.

Another very relevant question for pharmacosurveillance is: "Who owns the data?"  Any managed care company that I am aware of treats patient data as their own proprietary data whether they know what to do with it or not.  I gave the previous example on this blog of asking a managed care executive for permission to use deidentified brain images for teaching purposes and being told: "Why would we want you to use our data?" despite the defined teaching purpose of the institution and a long history in medicine of teaching all of the available abnormal findings for the purpose of developing better diagnosticians.  Prescription and pharmacy data has an even more clandestine history.  Most physicians were not aware until very recently that all of their prescription data was collected from pharmacies everywhere by a company called IMS America and that information was used primarily by pharmaceutical company sales forces to monitor the products being prescribed and whether their detailing people were having an impact on those prescriptions.  The individual physician was not able to see these records or look at the trends in their prescribing data over time.  The data collection was centralized only for the purpose of selling the collected data to pharmaceutical companies or (for the past 15 years or so) buried in clinic or hospital electronic health records.  The best a physician could do would be to request prescribing data on a particular patient from their pharmacy.  That might result in 20 or 30 faxed pages of lines and lines of prescriptions, usually encompassing only the most recent years.

The state may not only claim the data, but set in place mandatory rules about how practitioners collect the data and transmit it to them.  In the state of Minnesota, all practitioners treating depression are mandated to have their patient complete PHQ-9 rating scales for depression and have those results sent to the state.  The state also monitors prescribing data on stimulant prescriptions for children and mandates that any person taking an antipsychotic medication needs to sign a written consent form.   Currently 49 of 50 states participate in Prescription Drug Monitoring Programs (PDMPs) to track drugs classified on the Controlled Substances Act Schedules II - IV.  The PDMP programs were originally set up to help law enforcement identify illegal activities with controlled substances but developed into a resource for physicians who wanted to know if their patient was getting multiple prescriptions or prescriptions that increased the risk of medications that they might be prescribing.  These pre-existing systems led the CDC and the FDA to develop the Prescription Behavior Surveillance System (PBSS) to look at the trends in the prescriptions of controlled substances.   Typically all pharmacies within a state submit data on controlled substances within a week of the prescription being filled.  The PBSS categorizes all of the data into three categories: benzodiazepines, stimulants, and opioid analgesics.  Buprenorphine is classified in the opioid analgesic category even though the primary use is for treating opioid dependent patients.  Tramadol was not included in the database until it was reclassified in 2014.  There is also a miscellaneous category that includes zolpidem and carisoprodol.  I think it probably makes sense to include GABA enhancing sedative hypnotics like zolpidem, zaleplon, and eszopiclone in the benzodiazepine category.

The preliminary data from the PBSS system that was just released in October is very interesting.  In terms of a representative sample, the eight states reported cover 1/4 of the US population and represent all 4 US Census Bureau Regions.  Prescription rates were calculated as the prescription rate per 1,000 residents as given by the most recent Census data.  Perhaps most surprising is that the rate of opioid prescribing approaches nearly one prescription for every state resident in some states in some states and the rate of opioid prescribing is twice as high as the rate of benzodiazepine or stimulant prescribing.  There are two to four fold differences in state-to-state prescribing of controlled substances across the board.   The top 1% of opioid prescribers in Delaware wrote for one out of four opioid prescriptions in the state.   The top decile of prescribers account for 50-60% of opioid prescribing but that decile does not solely account for state-to-state differences.  Specialists in pain clinics (pain medicine, surgery, physical medicine) were more likely to write more prescriptions per day but are thought to account for < 20% of all opioid prescriptions per day.   The authors suggest that most of the prescriptions in that category are written by general practitioners, family medicine, internal medicine, and midlevel practitioners.

Overlapping prescriptions ( benzodiazepines and opioids and long-acting and short acting opioids) were common.  Multiple provider episodes or MPEs defined as a resident filling a controlled substance prescription from 5 or more prescribers at 5  or more pharmacies in any 6 month period varied significantly by state, age, and the number of controlled substance schedules added.  The totals ranged from a low of 4.4/100,000 residents in Louisiana to 66.8/100,000 in Ohio.  An overall first impression of this system is that there are limitation but it clearly provides valuable information on prescribing behavior relevant to controlled substances.

The current epidemic of accidental overdose deaths was the driving force for the PBSS system.  It shows that a pharmacosurveillance system is possible, but that there are some limitations.  Data quality as inputted from the pharmacies needs to have quality control measures to assure consistency.  An ideal system would also include a diagnosis or indication.  Physician speciality would also be a useful marker.  I think that the best use of a system like this would be to allow physicians to mine their own prescription data and see how they compare with other physicians in general and within their own speciality.  Specific strategies could be developed for self correction at the earliest possible stages.  I wrote about a pharmacosurveillance system used in Wales in a previous post.  The top 5 drugs causing complications in that system were opioids, antibiotics, warfarin, heparin, and insulin - in that order.  With a sophisticated system it would be possible to pick up significant adverse drug events and monitor those events as well.    

All of the talk about patient safety these days is really about patient safety being practiced in the silos: health care businesses, hospitals, and clinics.  Places where individual health care data is considered proprietary - at least until there is a complication big enough that the state authorities mandate that it be reported for investigation.  These businesses have an inherent conflict of interest in reporting adverse drugs events and severe complications.  Pharmacosurveillance should be out there across the entire health care landscape.  It should not depend on reports about complications made by businesses that are in effect protected by patient privacy.  Complications can be actively sought out and investigated any time a prescription suddenly stops or changes.  This data also needs to be freely available to physicians so that they can look at their prescribing data relative to their peers and make changes where necessary.

It is time to view the process as as a way to learn about how to provide the safest possible environment for patient care,  rather than a way to "catch" somebody when something goes wrong.        


George Dawson, MD, DFAPA


References:

1:  Paulozzi LJ, Mack, KA, Hockenberry JM.  Vital Signs: Variation Among States in Prescribing of Opioid Pain Relievers and Benzodiazepines — United States.   Morbidity and Mortality Weekly Report (MMWR) July 4, 2014 / 63(26): 563-568.

2: Paulozzi LJ, Strickler GK, Kreiner PW, Koris CM.  Controlled Substance Prescribing Patterns — Prescription Behavior Surveillance System, Eight States, 2013. Morbidity and Mortality Weekly Report (MMWR)  October 16, 2015/ 64 (9): 1-14.

From Morbidity and Mortality Weekly Report (MMWR) October 16, 2015/ 64 (9): 1-14.

Dangerous Medications - Part One

Some of the most common rhetoric used against psychiatrists is that the drugs that psychiatrists prescribe are somehow more dangerous than other drugs.  There are numerous problems with the argument including the fact that psychiatrists don't really influence what medications are approved by regulators and the majority of the so-called psychotropic medications (up to 80%) are prescribed by primary care physicians.  There are the associated arguments that they are overprescribed and ineffective and I will address those at another time.  What is the evidence about dangerousness?  I have previously commented on the issue of whether or not the medications used by our field cause a person to become homicidal.  I will restrict this post just to the issue of medication complications and whether or not regulatory action needs to be taken against a medication.

The areas of pharmacovigilance and  pharmacoepidemiology offer some insights into the area of drug dangerousness, but at this point there are few good studies available in public access formats.  One study done in Wales showed that over a 5 year period there were about 100,000 incident reports related to medications or about 9.7% of all patient safety incidents.  The incidents resulted in severe harm or death in 822 patients (0.9%) of the medication related incidents.  The majority of reports were skewed toward reports from hospitals (75%) as opposed to primary care clinics.  Looking only at the severe and fatal outcomes by drug class (Table 8) 2/13 drugs could be classified as medications used to treat mental illness.  Benzodiazepines and antipsychotics were ranked 6th and 12th respectively.  The top 5 drugs starting with number one were opioids,  antibiotics, warfarin, heparin, and insulin.  Any physician working on hospital safety committees is aware of the number of complications due to anticoagulation.  To add further context the total population of Wales in 2011 was about 3 million people, but the total prescriptions per drug class or the critical denominator to determine any true complication rate is unknown.

Unfortunately in the US, we have no complete systems for pharmacovigilance.  We have a long standing data base that has been around for decades that was used primarily to monitor physicians prescribing practices for pharmaceutical companies.  Pharmaceutical representatives would detail physicians (introduce product information) and this company would sell the information about whether the detailing resulted in increased prescriptions of that product.  Occasionally data from this large data base makes it out into the medical literature, but there is a serious question about how well marketing information works for pharmacovigilance.  There is publicly available data from the Centers for Disease Control (CDC) indicating that there are about 50,000 deaths per year attributable to medications.  The majority of these deaths are accidental and intentional overdoses and there is no granularity to look at common severe side effects like anaphylaxis.  A third source of data is proprietary databases from health care companies, hospitals, and government agencies.  Those sources often lead to questions about the generalizability of the conclusions from those studies.

A potentially useful regulatory measure is the number of medications that have been identified as problematic in post marketing surveillance and removed from the market for safety reasons.  The best review I could find on that topic is reference 2.  The paper looks at market withdrawals of new molecular entities (NMEs) approved by the FDA between the years 1980 and 2009.  Of a total of 740 NMEs during that period, 118 (15.9%) were discontinued.  Twenty six drugs out of 118 were withdrawn due to safety reasons or a total of 3.5% of the original approvals.  Nervous system drugs represented a total 104/740 approved drugs and a total of 6.7% of the discontinuations as a percentage of the approvals.  Safety withdrawals were a total of 3 drugs or 2.9% of the total approvals in this therapeutic class.  The bottom line is that a total of 1 drug used for psychiatric indications out of 740 NMEs in the last 3 decades was a medication was withdrawn for safety reasons.

The authors go on to provide a high degree of granularity with a complete list of all NMEs that were withdrawn for safety reasons and they are listed in Table 3.  The three nervous system drugs listed are nomifensine (an antidepressant), levomethadyl acetate ( a drug used to treat opioid dependence), and pergolide mesylate (a drug used to treat Parkinson's Disease and restless leg syndrome).  The  study apparently does not look at the issue of drugs where the manufacturer voluntarily discontinued sales.  As an example, Bristol Myers Squibb discontinued sales of Serzone (nefazodone) in 2003 due to a low incidence of hepatotoxicity with serious outcomes like liver failure and the need for transplantation.   The conclusion of this article is that the majority of of drug discontinuations are due to commercial reasons and not safety.  They noted a trend for decreasing NMEs over time and an associated decrease in drug discontinuations.

Part of the problem with the perception of drug dangerousness, especially with medications used for psychiatric indications seems to be the idea that they should be devoid of side effects.  That is certainly the ideal scenario, but that is not the approach taken by regulatory bodies like the FDA.  Like any regulatory body that depends on politicians for funding there will always be a variety of political influences.  In some cases the bureaucratic structure may be prioritized over scientific review.  The paper by Qureshi, et al is a good example of a certain threshold of severe side effects that may lead to drug discontinuations for those reasons, but any inspection of current approved medications and their rare but serious side effects shows that there are plenty of concerns out there for commonly prescribed drugs in all classes.  The regulatory concern is that many of these medications are useful for the people who really need them.  When any medication is applied over a population of people, there is a likelihood of rare but very serious side effects.  That is not a reason to call the drug dangerous, especially if there are people who benefit from taking it.  There is also a likelihood of common side effects that are less dangerous but adversely impact quality of life.  It is also easy to see the problem politically.  In other words there is some kind of conspiracy driving the prescription of some medications as opposed to others.

The reality is that the patient has a decision to make and as I have pointed out before, I have really never encountered a person (including myself as a patient) who takes that decision lightly.  There are additional interpersonal and psychological factors.  My personal bias as a physician is that the primary goal of treatment is minimal to no side effects and that tolerating side effects is a decision made by the patient but informed by the physician.  It always needs to be balanced against any therapeutic effect of the medication.  


George Dawson, MD, DFAPA:

1:  Cousins DH, Gerrett D, Warner B. A review of medication incidents reported to the National Reporting and Learning System in England and Wales over 6 years (2005-2010). Br J Clin Pharmacol. 2012 Oct;74(4):597-604. doi:10.1111/j.1365-2125.2011.04166.x. Review. PubMed PMID: 22188210; PubMed Central PMCID: PMC3477327.

2:  Qureshi ZP, Seoane-Vazquez E, Rodriguez-Monguio R, Stevenson KB, Szeinbach SL.  Market withdrawal of new molecular entities approved in the United States from  1980 to 2009. Pharmacoepidemiol Drug Saf. 2011 Jul;20(7):772-7. doi: 10.1002/pds.2155. Epub 2011 May 14. PubMed PMID: 21574210