Health Care Industry Annual Turnover Rate About 32%

The health care industry is experiencing roughly 32% turnover annually, of which about two-thirds represent “voluntary separations.”  Health centers realize turnover is a significant problem, and a difficult one to tackle.  While everyone wants to reduce turnover, many organizations don’t know what a typical turnover level is – making it difficult to know if your efforts are succeeding.  Merces includes turnover data in our surveys, but the health care market is much broader, and large sample data of this type can be helpful.

The Bureau of Labor Statistics provides data on job openings, hires, and separations in its JOLTS study, produced monthly.  The May 7, 2019 Economic News Release provides some information that health centers may find useful:

  • There are currently more job openings than there are job seekers.  This means you can expect a longer “time to hire” for nearly all openings, as there is competition throughout the market.
  • Health care “hire rates” are averaging about 3%/month over the last year (36% for the year).  That means that every month the industry has been hiring about 3 new employees for every 100 currently on staff.  Remember that these numbers also include growth, not just replacements for staff that leave.
  • “Total Separations” are occurring at a rate of about 2.7% in health care (32% for the year), compared to about 3.7% (44%) overall.
  • “Voluntary Separations” in health care are averaging about 2.0% (24% annually), somewhat lower than the 2.3% (28%) in general industry.  The balance of separations are layoffs and discharges.

What does all this mean for health centers?  Total turnover data is good to look at, but because almost a third of turnover is involuntary, total turnover partly represents how good you are at hiring – finding people who you will not need to terminate down the road.  The better “apples to apples” comparison for retention is voluntary separations, representing your ability to keep staff.  Bringing your voluntary turnover down to the 24% industry level is certainly a start, but your target should be much lower.

How to start?

  • Classify your turnover by voluntary and involuntary.  High involuntary turnover levels suggest you may need to improve your hiring or promotion processes.  High voluntary turnover means there is something about the employment relationship that hasn’t been optimized.
  • Break down your turnover by job and job family.  Losing one provider when you have ten is not a high percentage (10%) but can result in a devastating loss of productivity.  Averaging low turnover in some functions with high turnover in others may make your overall picture look better than it really is.
  • Break down your turnover by the reasons people are leaving.  Remember that the reason people may say they are leaving may not be the real reason.  The easiest thing to say is that you’re leaving for better pay or benefits , because people don’t want to burn bridges.  Look to see if turnover is higher in certain departments, or in particular clinics.

Once you have a handle on where your turnover is coming from, and why people are leaving, you can start a systematic approach to bringing your turnover down.

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Oregon Pay Equity Law – Many of The Old Exemptions are Gone!

Some have observed that the Oregon Pay Equity Law goes farther than Federal and other state regulations, and they are correct. This is no more clearly seen than in the elimination of some of the old exemptions that make many pay equity regulations not particularly equitable.

Gone is the day when market differentials rule. Different market rates are not included in the list of  “bona fide” exceptions. This is very important for health centers, typically dominated by women in jobs that are traditionally paid less than occupations dominated by men (which comparable character of work is considered).

If you have a market-data-based compensation program (i.e., you assign jobs to pay grades based primarily on their market rates), you will not be compliant.

If you rely on any market data provider, or subscribe to any system that is based solely on market rates, you will need to change your approach.  This does not mean that market data can’t be used in establishing pay ranges – in fact it needs to be in order to ensure you are competitive – but that market data is NOT the determinant of which jobs are paid comparably.

Another factor that is no longer an exception is the existence of a union contract.  In other states with pay equity legislation (and of course Federal laws and regulations) a collectively bargained pay scale is typically exempt from scrutiny.

If you have a collective bargaining agreement in place, you will eventually have to renegotiate the pay structure to ensure that it meets the requirements of the pay equity law.

It is not clear what the impact is on existing agreements; although the rules do not provide for any grace period, they also do not call for immediate negotiation. It is likely this is simply something that the regulators did not consider.

There are still legitimate exceptions to pay differentials, such as a bona fide merit system, or systems based on quality and and quantity of production.  Seniority systems (which actually perpetuate pay inequity) also provide an exception, although we do not recommend them except in situations where the distrust between labor and management is so pronounced that a performance-based system cannot be used.

All Oregon employers should ensure that their programs, even if they comply with Federal law and regulations, comply with the Oregon rules. Many practitioners used to the market and union-contract exemptions will need to embrace other techniques more likely to actually achieve pay equity.


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Oregon Pay Equity Law: Comply With Job Evaluation

Compliance with the Oregon Pay Equity Law can be simple and straightforward (albeit a good bit of work) by following traditional “best practice” job evaluation principles that have been used for decades nationwide, and in a number of FQHCs.  There are many aspects to the Pay Equity Law, but this post focuses on the requirement of job analysis and evaluation – that is, compliance with the requirement that there can be no differences in pay (subject to exceptions to be discussed later) for individuals performing work “of comparable character:”

(17) “Work of comparable character” means work that requires substantially similar knowledge, skill, effort, responsibility and working conditions in the performance of work, regardless of job description or job title, as defined in OAR 839-008-0010.

In each of the five general categories (knowledge, skill, effort, responsibility, and working conditions) there are examples of the types of considerations, e.g,:

(d) Responsibility considerations may include, but are not limited to, the following:

(A) Accountability, decision-making discretion or impact of an employee’s exercise of their job functions on the employer’s business;

(B) Amount, level or degree of significance of job tasks;

(C) Autonomy or extent to which the employee works without supervision;

(D) Extent tow which the employee exercises supervisory functions; or

(E) Extent to which an employee’s work or actions expose an employer to risk or liability.

The text of the rules makes it clear that none of these various considerations need be determinative, nor need they be included, nor are they exclusive.  This essentially means that the employer is free to develop its own model for  determining work of comparable character, so long as it is within the spirit of the regulations (and doesn’t run afoul of any specific one, of course).

The process for doing this is called “job evaluation” and is a “best practice” method of compensation program design. It involves selecting a set of characteristics (such as those described in the rules), creating a set of levels for each, building a scoring model, and then applying it to each job. HR professionals may have run into these kinds of plans if they worked in hospitals, governmental agencies or larger organizations – in those environments they are typically called “classification systems.”  A job evaluation method is used to determine which jobs are assigned to each pay grade, and market data is then applied to create ranges for each grade.

While it is not particularly difficult to design a job evaluation plan (and an accompanying pay structure), it is not something that one should do by simply scouring the internet and downloading samples.  A job evaluation plan must include characteristics that are relevant to the organization, should reflect the organization’s values (e.g., how the various factors are weighted) and be tested statistically.  They also need to be tested and analyzed with relevant labor market data, to ensure that the plan will still allow the organization to be competitive.

Merces has developed dozens of these plan for health centers nationwide. Before you go down the road working with any organization, ensure they have the experience not just with pay equity and job evaluation techniques, but an understanding of how they work in the industry.

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Beware the PayScale Marketing Trap

The current PayScale “Develop a Market-Based Pay Structure” marketing publication is deceptive, inaccurate, and, given the apparent quality of their data, could set you up for a non-competitive and divisive pay program that increases turnover and employee dissatisfaction.

PayScale is a popular online market pricing “tool” presented by the company as a solution to compensation planning.  The company’s marketing strategy involves convincing you that every other approach to compensation program development and maintenance is expensive and time-consuming, and that you need nothing but their data tool and all your pay problems will be solved.  Think of those late night commercials for “only available on TV” products where the actors over-emote at the tragedy of the cheese burning on the pan, leaving the only option as their $49.99 unique patented special pan (order now and we’ll throw in a set of steak knives!).   No, seriously, there’s a stock photo of a young woman with a shell-shocked expression tearing at her hair under a caption “Do you have time to fill out salary surveys?”

The current marketing brochure makes the following arguments/claims (among others):

  • “Market pricing is the most effective approach to job evaluation.”  FALSE – market pricing, by definition, IS NOT job evaluation.  Job evaluation is the systematic analysis of jobs to determine their contribution to the organization, irrespective of the market. It is the only way to correctly determine how your jobs truly compare to those in the market, how to deal with jobs that have no market rates, and how to properly address jobs with combined or multiple functions.  Market data is a tool to anchor an internally valid pay structure to ensure competitiveness — but it is just a tool.
  • “[market data] takes less time to maintain.”  FALSE – market-based pay programs are very time consuming to maintain, because every year you have to go out and collect market data for every single job.  To do it right, you have to review multiple sources, and then figure out what to do when (inevitably) market rates for particular jobs rise or fall — do you put them in different grades only to have them move again next year? I’ve seen organizations spend hours on a single job trying to determine how much to adjust a market rate to account for lead responsibilities, or added responsibilities, or additional educational requirements.  How do you adjust your ranges overall to reflect the multiple changes that go on with jobs and in the market — ever sit there with a spreadsheet struggling to develop a structure that accounts for pay compression, differing rates of market movement, or organization growth, all without any logic?  With an effective internal evaluation structure in place, you can update a pay structure in a couple of days each year.
  • “It is harder to manipulate the results [with market data]”  FALSE – there is nothing easier to do than manipulate market data — to pick and choose which surveys to use for a particular job, which “cut” of the data, how much to age it, or weight a survey. The bottom line is that in a market-based system, you can use “legitimate” data sources to come up with just about any number you want.
  • “A smart alternative to the expense of multiple survey sources is to use a data source that has good comprehensive coverage.  PayScale is a good single-source option”  FALSE — on so many levels.  The reason that “real” compensation consultants (PayScale uses the word “traditional,” presumably as a way to suggest that PayScale is more “progressive”) recommend using multiple sources of data (we suggest, frankly, as many as you can find) is that each survey has its own “trends” — some attract higher-paying employers, some have different business models than you, some have smaller or larger samples.  Multiple sources compensate for variance, and give you more reliable results, as well as increasing the likelihood of finding as many jobs as possible.  No single source can cover all the variables  — and no “algorithm” can substitute for real data.
  • “The goal is to benchmark 75-80% of the positions within your organization.” FALSE — of course, if the only way you have to assign jobs to pay grades is through market data, you really need 100% of the positions, or some kind of internal equity model to fix the other 20-25%.  On the other hand, with an internal equity structure tied to the market, you can do quite well with data for only about one-third of the jobs.   That certainly makes it easier than scrambling through multiple sources trying to come up with “something” to use as a market rate.   PayScale ends up with the obvious — suggesting using an internal evaluation method to slot jobs without market rates into pay grades — so they still say you need one, you just don’t use it effectively, only to cover the holes in their database.

Speaking of their database — probably the biggest and most worrisome critique of the PayScale tool is the very algorithm they brag about that they use for their predictions. PayScale’s data comes only from job seekers — it DOES NOT incorporate the entire spectrum of what people are paid.  Given that you can assume that more highly-paid folks are less likely to be seeking jobs, and that those with longer service (generally earning more) are also less likely to be looking, we can make a pretty fair assumption that the PayScale model is set below the market.

In two tests we’ve done this year (one sitting in on a client’s PayScale sales pitch, and the other from data on a couple dozen jobs that a client purchased from PayScale) we found the PayScale data to be about 10-15% lower than the data from traditional surveys, particularly in entry-level jobs where the risk of pay-related turnover is so high.  We’ve seen similar comments on message boards.

It’s taken us a number of years, but we’ve successfully moved all of our clients off of “pure-market based” pay structures, and helped many others fix compensation systems broken by over-reliance on market data.  It’s not magic, and it can be done internally if people have the knowledge and exposure to the right techniques. Regardless of how you choose to establish your pay ranges, remember that survey data is only a tool, and only part of the process of establishing an effective compensation program. Relying on a single-source “product” with a  modeling method that seems guaranteed to provide non-competitive results is likely to result in failure.


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Provider Compensation 101 – Maybe Extra Pay Isn’t Worth the Extra Work

[This is part of a new series on specific issues related to provider compensation, designed to be “short and sweet” and prompt thinking before doing.]

When improving productivity will take time away from your providers’ personal lives, expect push-back.  When trying to change behavior, we need to look at the reasons for the behavior — and when it comes to “quality of life” and “work/life balance” issues, we need to recognize that frequently these will be more important than money, and that all the incentives in the world won’t change that.  Let’s take a look at the “extra effort” that increasing productivity may involve.

Recently I spoke with a Medical Director contemplating a change to their provider incentive program.  The current productivity target for family practice medical providers (doctors and mid-levels) is 24 visits per day.  While many exceed that figure, many are stubbornly stuck at about 18.  The current incentive plan is relatively generous (to the point that some providers need to dial back on productivity to focus on quality), so there is a definite financial incentive.  Assuming for the moment that processes and patient load would permit every provider to have an average 24 visit (a very big assumption), there should be no reason other than effort why a provider couldn’t see 24 patients in a day, right?

Here’s one thought.  The Medical Director estimated that their providers spend an average of two hours per evening at home working on their charts and notes (many providers tell me its closer to three hours, but lets be conservative).  For an “18 visit” provider, this would amount to about seven minutes per visit.   If I’m the provider, I should be able to increase my productivity to 24 visits without changing my time in the clinic — however, my math says those extra six visits can add another 42 minutes (three and a half hours a week) of time taken away from my home life.

Now I have to ask myself, what is it worth to give up another three and a half hours a week  of my life (a 35% increase) that I can’t give to myself or my family?  How much money will it take to make up for missing yet another concert, ball game, helping with homework, watching “Survivor,” or a night out?  I already make a lot of money, and I don’t need more.  Will $25 more a day do it?  $200 a week?  $15,000 a year?

Not that easy, is it?  What would you do in that position?


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