Pharmacist Suicide Risk: What We Know and Don’t Know

by | Sep 27, 2018 | Burnout, Career

Pharmacist Suicide


It’s no secret that pharmacists have work stress. What you may not know is the truth about pharmacist suicide risk. 

Anecdotally, I hear pharmacists saying, “burnout runs rampant through the pharmacy industry,” just as it does through other healthcare professions. Because pharmacists face issues like unrealistic metric goals from management, odd shifts, increased workload, decreased support staff, unachievable expectations from the public (i.e., never make a mistake), our industry is ripe for mental health trouble.

Coupled with the high-stress environment and the fact that pharmacists often work in isolation, it should come as no surprise that pharmacists are more likely to struggle with mental health issues and burnout, and face a greater suicide risk than many other occupations, as this article aims to prove.

However, the data reported in the literature and other sources are scant and sorely outdated (or inaccurate).

Why pharmacist burnout risk matters

Burnout left unchecked makes its mark on those who suffer from it: exhaustion, chronic fatigue, alienation, insomnia, loss of appetite and a higher risk of suicide. One study found a higher risk of suicide in physicians who scored higher on the Oldenburg Burnout Inventory and Beck’s Hopelessness Scale.

For those in the healthcare profession, burnout manifests as a lack of compassion for patients and coworkers and a loss of interest in things they once enjoyed. It can ultimately lead to, as one review put it, “depression; anxiety; sleep disturbances; fatigue; alcohol and drug misuse; marital dysfunction; premature retirement and perhaps most seriously suicide.

Burned out employees must address the physical and psychological components or face dire consequences.

Data on pharmacy burnout is sparse. The majority of studies listed on PubMed are related to physicians. One would think that research would be plentiful on such a perverse problem.

From the corporate perspective, there’s a tangible cost for high pharmacist turnover, a likely outcome from high burnout. Conservative estimates suggest that the cost of losing an employee is 1.5 – 2.0 times the employee’s annual salary. When you consider the costs to hire, onboard, and train employees, the pharmacist’s salary in addition to the loss of productivity, the cost of turnover is incredibly high.

Burnout is a predictor for poor mental health, which, in turn, can lead to suicide. It’s not a stretch to suggest that the increased incidence of burnout could account for pharmacy’s 20% higher than average substance abuse rate or its 1.29 odds ratio for pharmacist suicide according to an excessively linked article, a calculation which the author could not determine.

It’s time for an update on what we know about pharmacist suicide risk.

Evaluating pharmacist suicide risk (Methods)

To determine just how severe the problem is, I worked with Syed Haider, PharmD to review the Center for Disease Control and Prevention (CDC) publically available data from the National Occupational Mortality Surveillance (NOMS). Occupational mortality surveillance identifies trends in work-related deaths to identify jobs and work environments that present increased hazards for the people who work there. Think of NOMS as the first line of defense noticing alarming trends in occupations. The data is somewhat helpful, but the results are not as useful as data from a double-blind placebo-controlled trial.

NOMS is a CDC partnership that monitors changes in cause of death by industry and seeks to protect workers by identifying patterns and emerging risks as well as suggesting interventions to prevent them. The program is voluntary. States send in death certificate reports to NOMS. NOMS analysts have to analyze about 15% (as of 2018) of the data as free text, thus indicating a potential point for errors. Additionally, a death certificate may report multiple death causes. For the sake of brevity (even though this article is longer than average), we eliminated reviewing other causes of death. In the future, I hope to discuss other stress-related deaths.

The database allows querying the system by Industry or Occupation. Our results below were searched by the “Pharmacist” occupation. You can query the database found here.

The database is split into two time-bound categories:

Dataset 1: 1985-1998

Dataset 2: 1999, 2003-2004, 2007-2012

The time-bound databases will be referred to as dataset 1 (1985-1998) and dataset 2 (1999, 2003-2004, 2007-2012). Dataset 2 has multiple missing years of data.

Only 26 states submitted data for the first database (1985-1998), whereas 24 states in the USA submitted information in the second database (1999, 2003-2004, 2007-2012). The data sets do not have the same states reporting data, therefore, we are not comparing apples to apples. Thus we cannot make comparisons over time as the authors originally intended. NOMS is a Surveillance System, not a research outlet.

NOMS reports the number of deaths and the proportionate mortality ratio, or PMR. NOMS calculates the PMR using data related to the cause of death, occupation, industry, age, race (only white or black reported), and gender.


Proportionate Mortality Ratio: Number of deaths within a population due to a specific disease or cause divided by the total number of deaths in the breadth during a period such as a year.

PMR is calculated by dividing the proportion of deaths in population A by the proportion of deaths in the total population, then multiplying by 100.

From the CDC, “A PMR greater than 100 indicates that a particular cause accounts for a greater proportion of deaths in the population of interest than you might expect.”

Thus, a value of 200 means the given occupation has double the proportion of all deaths certified as suicide than would be expected from the proportion of the general population.

I spoke with CDC epidemiologist Andrea Steege Ph.D. MPH, about the NOMS program. When asked about how to discuss PMR data, she concluded that one could say,

“When compared to the general public, a higher PMR indicates a higher risk.”

The PMR is problematic with a few limitations. For example, we can’t claim that all pharmacists have a higher odds of suicide based on the data. Thus, the data does not support calculating a suicide odds risk of 1.29 (which the article mentioned above claims to cite). We can say there is a higher or lower risk of suicide based on the PMR.

The CDC NOMS data reviewed by “intentional self-harm” on death certificates. Only intentional self-harm data was reviewed due to the breadth of data needed to be reviewed for future articles.

Age is separated into three groups: 18-64, 65-90, or 18-90. Our data only examined ages 18-64, as this is the most likely age for an active working pharmacist. While pharmacists often work beyond the age of 65, they are less likely to be working full time.

Intentional Self Harm or suicide is defined as the taking of one’s own life voluntarily and intentionally.

We excluded the following causes of death, but do feel like a full examination of these deaths in pharmacists is worth examining in the future:

  • mental disorders, mental disorders related to substance abuse, mental disorders related to alcohol abuse, drug-related deaths, alcoholism, mental disorders excluding schizophrenia and retardation, and potentially other deaths related to stress such as cardiovascular death

For our purposes, PMR could not be calculated for datasets with less than five deaths, and thus were not evaluated

Beyond the CDC data, little information exists about pharmacists and suicide. No article was found assessing NOMS pharmacist suicide data or from any other source.

Evidence of pharmacist suicide

First, let’s compare pharmacists to the 481 listed occupations in the USA.

Using the NOMS dataset 2, when combining all ages (18-64), races (black and white), and genders, the pharmacist PMR for intentional self-harm was number 14. Out of 482 list occupations in the USA, pharmacists have the 14th highest intentional self-harm PMR (PMR = 198, p <0.01; CI: 159-244)

Pharmacist Suicide

# Occupation PMR Deaths Significance level Lower 95% CI Upper 95% CI
1 DENTISTS 316 70 p<0.01 247 400
2 PODIATRISTS 282 5 92 658
3 VETERINARIANS 281 35 p<0.01 196 391
5 NUCLEAR ENGINEERS 250 8 p<0.05 108 492
7 BIOLOGICAL, LIFE, & MEDICAL SCIENTISTS 220 72 p<0.01 172 277
8 PHYSICIANS 219 224 p<0.01 191 249
9 LAWYERS & JUDGES 217 331 p<0.01 195 242
10 ELEVATOR INSTALLERS & REPAIRERS 208 28 p<0.01 138 301
13 AEROSPACE ENGINEERS 200 56 p<0.01 151 259
14 PHARMACISTS 198 88 p<0.01 159 244
15 MARINE ENGINEERS & NAVAL ARCHITECTS 196 12 p<0.05 102 343
17 PHYSICIANS’ ASSISTANTS 195 23 p<0.01 123 292
18 ENVIRONMENTAL & GEOSCIENTISTS 192 73 p<0.01 150 241
19 AGRICULTURAL & FOOD SCIENCE TECH 191 20 p<0.05 117 295
20 OCCUPATIONAL THERAPISTS 185 27 p<0.01 122 269


Dataset 2 (1999, 2003-2004, 2007-2012) suggests the risk of suicides as a cause of death in pharmacist is twice (PMR: 198 p<0.01; CI: 159-244) the general population of workers.

The dataset 2 intentional self-harm PMR was higher for all races/genders combined when compared to dataset 1, from PMR 198 to 182, respectively. However, as stated before, different states reported death information between dataset 1 and 2. The number of deaths was lower, from 119 to 88 due to suicide. However, the second dataset is from 8 years while the first dataset is over 13 years.

Dataset 1: 1985-1998

Race Sex Age Group Occupation Cause of Death (ICD) PMR Deaths Significance level Lower 95% CI Upper 95% CI
All Races/Sexes Combined 18-64 PHARMACISTS INTENTIONAL SELF HARM  182 119 p<0.01 151 218


Dataset 2: (1999, 2003-2004, 2007-2012)

Race Sex Age Group Occupation Cause of Death PMR Deaths Significance level Lower 95% CI Upper 95% CI
All Races/Sexes Combined 18-64 PHARMACISTS INTENTIONAL SELF HARM  198 88 p<0.01 159 244


Suicide by Gender and Race

Dataset 2 shows that white males have the highest PMR at 202, while white females report lower PMR at 156. Both indicate a higher risk of suicide as compared to the general population. Previous literature indicates that males are more successful in their attempts at suicide, which may account for the higher numbers of deaths.

Interesting, both datasets do not have PMRs for black as less than five deaths were reported for all black-related suicide deaths.

Dataset 1: Suicide by Gender, Sex (1985-1998)

Race Sex Age Group Occupation Cause of Death (ICD) PMR Deaths Significance level Lower 95% CI Upper 95% CI
W M 18-64 PHARMACISTS INTENTIONAL SELF HARM 159 100 p<0.01 129 193

Race Sex Age Group Occupation Cause of Death (ICD) PMR Deaths Significance level Lower 95% CI Upper 95% CI
W F 18-64 PHARMACISTS INTENTIONAL SELF HARM 159 100 p<0.01 129 193

Dataset 2: Suicide by Gender, Sex (1999, 2003-2004, 2007-2012)

Race Sex Age Group Occupation Cause of Death (ICD) PMR Deaths Significance level Lower 95% CI Upper 95% CI
W M 18-64 PHARMACISTS INTENTIONAL SELF HARM 202 69 p<0.01 157 255


More questions than answers

Because there’s a lack of information about pharmacists and suicide, it’s difficult to draw meaningful conclusions from the statistics.

The NOMS data suggest that pharmacists are twice at risk to commit suicide when compared to the general public. From the data shown, pharmacists have an increased risk of suicide when compared to the general public, but the extent of the risk is unknown. But there is so much we don’t know due to lack of information.

This research created more questions, such as

What ages are pharmacists most likely to commit suicide?

Are there geographic differences amongst suicide victims?

Is there a difference amongst practice sites?

What difference, if any, between new and seasoned pharmacists?

Though it is possible to draw conclusions from the data, PMR is a poor tool for assessing the risk of suicide by pharmacists. PMR doesn’t establish causality, but rather it suggests an association. The PMR is used as a tool to determine whether a population experience differs from the general population. If there’s a significant difference, this could justify more research (as this article will call for).

The topic demands much more research to be meaningful.

Males have a higher risk of suicide in the profession, what mental health prevention steps can alleviate this problem?

We don’t know when the pharmacist held the occupation of a pharmacist. It’s more likely they held the occupation due to the age range we reviewed. However, there is a possibility the suicide occurred during unemployment or part-time employment.

The future of burnout and suicide risk in pharmacists

Our industry must develop more research related to pharmacists and suicide.

According to a 2004 survey by David A. Mott of the University of Wisconsin, almost 70% of pharmacists surveyed experienced job stress and role overload.

Another study reported a hospital pharmacist survey burnout rate was high at 61.2%, largely related to emotional exhaustion.

Because more pharmacists are reporting feelings of burnout, and because burnout is linked to depression and other psychological illnesses, it is vitally important that researchers learn more about the connection between burnout and suicide.

I am not a researcher, nor an academic. My first attempt at a grant proposal seeking more information about burnout was rejected, but I will keep trying. The proposal aimed to perform a burnout survey amongst Michigan pharmacists.

As an effort to improve our industry, I believe it imperative pharmacists know working conditions before entering new employment. This information is not available to the public. For a pharmacist to find this out, he or she needs an inside source, something not always available.

Additionally, pharmacists say when filling out an exit survey that they know their answers will not change anything. Also, if they write something negative, this could come back and bite them.

That’s why I created an anonymous pharmacist employee exit survey. I urge all pharmacists to fill out this survey about your previous job.

We wish to publish this data and make it widely known to all pharmacists before they begin working at a company. That way, they can know all the positive or negative attributes of a company before agreeing to employment.

A special thanks to Syed Haider, Jackie Boyle, and Chrisovalantis Paxos. I would not have finished, or even dared to publish this article, without your help.

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