More of the Truth – When Ageism and Sexism Hit Home


PBMs and Pharma are both at the Informative/Analytical levels in HIT productivity, research and utilization.  On a scale of 1-10, most are at the Level 4, and whenever they fail to integrate true statistics, represent a major failure in the contemporary ACA defined healthcare system.


It helps to document these things.

Sometimes they are so recurring you tend to forget the earliest examples of prejudice and insecurity showing their faces in the job world. There were two recent encounters I had in interviews that stank of Ageism–that behavior that tells you they are going to accept or reject you for a position due to personal prejudice rather than anything to do with pro-corporate success.

A national PBM was recently searching for experts in pharma marketing research strategies.

Obviously, having a very lengthy and rich background in researching the demographics and health economics of the nation should be in your favor. However, this is not the case when they team initiating this program hasn’t an inkling of an idea of what the pharma industry is like at the small group age-gender-culture level.

When one cannot read the map to success, one is unlikely to ever blaze the trail needed to make it to the end of a new adventure.

Such is the case with this major pharmacy benefits management company I had the opportunity to meet face to face with.  I have known this company’s database for more than a decade, and know its potentials, which have never been utilized to their fullest extent.  Why the delay I wondered?  I figured the reason for this was just like for other PBMs, lack of the necessary skill set to see the potential applications for ths data, and know how to make those successes in just a few weeks–not a year.

So, many companies are in fact very out of tune with their populations–their consumers.  The focus for too long has been on cost analyses rather than quality of service analyses.  As a result, these companies expect little advancements or innovations to come their way in the pharma PBM work (this particular example is not, by the way, for the #1 PBM in this country, so don’t worry you others from that company because you recognize my name; your failures come by way of other midguided paths, lack of skillsets.)

This first event seemed to ring of  “ageism.”  A company that has superficially experienced managers who succeeded in career changes without undergoing much advancement in knowledge, produce a band of thinkers who cannot implement change.  So what do they do, they look outside the facility, try to meet people who know what to do.  This is always where my face-to-faces and direct calls to HIT Seniors and Directors seem to fit in.  But one example wasn’t really that convincing for me, that ageism was a barrier to their success.

But then another example of this error in corporate behavior surfaced in a work place.

To improve and redefine a “team”, three changes were made.  Three of of the three changes involved the few remaining males in the research group, who were removed one after the other.   The order in which these changes happened resulted in elimination of those with the most experience, the richest background, most successful problem solving history–so the team got worse in weeks.  Next, his counterpart who untrained in the same processes for analyses, failed to improve morale or team success–someone else had to go, and HE (not SHE) did.

This second loss involved the most important IT/HI member of the team–the individual who designed the original investigative research processes and IT data mining pathways.

The aura about his departure was that he was leaving left due to personality changes or perhaps conflicts; the same incidentally that caused the first male manager to be told to leave.

When the third of three males was told to step down, however, why this was happening finally made sense.

Being on the mailing list for team projects, any inferred plans to undergo change can also reach you, which they did at my end.  So imagine for a moment suspecting you are being ousted from the team, for whatever reason, and as a result of your departure you know there is no other person there now trained in your skillset.  But there are new people being hired, who in months or a year or two, may get an idea of what to do.

Now obviously, you are going to wonder, who made this decision?  You ask because obviously it is counter to producing any end products required by contracts in the near future.

So, this mailing goes around the group.  It’s kind of like those rumors that bunches of kids spread around a school.  You see all the hints that a new “team” is forming at school.  Some are excluded from the list of tasks at hand.  Yet they still receive the memos about the tasks that are due, perhaps to make them think they’ll be a part of this change.

The only problem with this logic is that when the brainstorming begins, and you are not invited to those meetings, as the duties of each members get defined, you know you are next on the chopping block for improving the workforce.

If you have any doubts, look at the list of those who are included; are there any demographic changes worth noting?

Ageism and Sexism thus are revealed.

Inability to see the problems leading up to this stage detail exceptionally porr, out of touch managers.

For some reason, with this position, people left and did not leave behind any history of their HIT work.   This is like a scientist claiming he made a discovery and then destroying all documents providing his point.  Companies should always have retraceable research notes; this company didn’t.

So next, you have to wonder, was the lack of these notes due to disgruntlement, or incompetence, or simple sloppy record keeping?

But the better question is who is best to blame for these fiascos?  It is not the researcher/analyst ultimately at fault for this–it is the HIT team and its manager, leader, advisor.  We penalize physicians for not keeping good patient records.  Companies fail to take actions to prevent workers from not producing retracable research steps, when billion dollar drugs and million dollar therapies are being tested for their efficacy or not with particular patient populations.   Is there anything less ethical than this failure management process?

So companies favoring the younger, inexperienced workers, are in effect eliminating the only ones who knew how to engage in a detailed statistical study in the first place.

And managers are ultimately the decision makes here, the producers or the worst possible errors, at least at the corporate finances level.

Managers who make such errors exist for only one reason.  In the PBMs we see them as businessmen trying to understand the differences between treating different ICDs, histotypes, or genetic histories.  They most likely don’t know the differences between adenine or guanosine, and cannot explain why IgE is important here, and IgA there.   In one very important research data set I was reviewing, I saw drug names provided only by first initial.  The researcher/analyst then has to ask, is that C for a cancer drug of Class I or 2, they each have the same beginning letter?  Unfortunately!  Without prior data resources and examples, you are now left with the dilemma of retracing your original dataset entries.

Time is the issue in the workplace.  It should only take days to complete any study, once you have the EMR/EHR/Med Rec data.  But. “Garbage In = Garbage Out”, or so they say.

When a manager or higher up cannot see why a particular manner of keeping data is problematic, failure is inevitable–thus the reasons for continued failure following the ageism-genderism changes–reasons for failure: part II.

In this case, the reverse sexism is well documented by the corporate emails, which essentially have the atmosphere of management stating “okay girls, here is what we’re gonna do–let’s divvy up these skills and see if we can figure it all out . . . ”

It takes more than just a team of people trying to break the code to produce intelligent results.

Ultimately, clients (companies) and patients are the victims of these poor management steps by a health industry dependent upon reliable health research data.

Poor managers are the reasons that projects in the non-clinical health industry setting–the PBMs, the contracted HEORs and QOC researchers, etc–ultimately fail.  Managers who are not well experienced in the field, and lack the knowledge and experience required to provide the best care,  are certainly not going to make the best decision makers, and sometimes become poor team leaders, the reasons for failure.

“Human Resources” can play a role in this setting as well.  You know that HR hasn’t paid much attention whenever a company loses its best talent due to management decisions.   This places Talent Searchers back to square one with their projects, and the overall company in an even worse position.

So it’s back to Square One, so they say.

Square One means that it’ll be another year or two or three before the new team catches up with the old.

Three years in any HIT field is equal to a generation. That means that 3 years from now, they will have someone with the right experience and skills to implement innovation and change.

Meanwhile, their competitors will become 1, 2 or 3 years ahead of them.

Sometimes, the best members of a team just never get the acceptance they are due, and the team never advances.

This chaos is actually going on all through the HIT professions right now, not just Pharma, not just PBMs.  They don’t know who or what to hire, because they don’t know what tasks have to be done, or understand the tasks well enough to stop placing the square peg in the round hole.

Few managers/VP/COs/Presidents are willing to hire new recruits, new skills, or pay for the experts.  Of the majority who claims this is not true, they fail to do what they claim, and even then miss the opportunities for hiring innovators.

Hospitals that hire only nurses to engage in non-nursing tasks look good on paper, but fail in terms of improving their quality of care and even possible lower morbidity or mortality rates.    They too have not hired the experts, only those skills sets they are familiar with.

In the end, it is the patient that suffers the most here, and the leaders/managers who are most responsible for an industry’s failure.


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