What is true for big labs eventually becomes true for small labs, mostly because volume discounts drive affordability. This is most recently true for PCR, a technology that has arrived in small laboratories for two platforms, the Meridian Illumigene and Nanosphere Verigene.
But is PCR ready for small labs?
I’m intrigued by this technology, and I can easily imagine it playing a role in small laboratories. This kind of platform offers rapid, definitive testing for infectious agents such as C. diff, pertussis, and bacterial agents in blood culture specimens. Testing a stool specimen for the C. diff toxin can eliminate the need for GDH antigen testing that detects non-toxin producing strains. Identifying bacteria sooner in a blood culture can give the physician a 24-hour head start. In theory this faster turnaround time with better results will reduce length of stay and assist antibiotic stewardship programs.
One reason I’m on the fence is expense. It’s great to claim that a new instrument will reduce length of stay, but bean counters aren’t impressed by soft cost savings that can’t really be quantified. Unless one is testing for something completely new that changes a protocol - the introduction of BNP comes to mind - it can be hard to convince bean counters that a faster turnaround time equals fewer inpatient days.
Another reason is wondering how having these results will change treatment. Clinicians embrace technology at different rates. How many of you are still running cardiac troponin and CKMB, for example? How many are still reporting percentile differentials with absolutes? How many are still performing more ESRs than CRPs? It sounds great to me to give the docs a better, faster result, but clinicians have to buy into new technology and use it to its potential. As primary information consumers they always drive demand for technology.
Finally - and this is a big reason - new platforms with radically different technology require a lot of training and competency assessment to get off the ground. In a small lab staffing is often sparse, raising questions such as, “What happens on weekends?” and “What happens when a doc wants it done STAT in the middle of the night?” The advantages of rapid PCR testing imply STAT requests, after all. Labs with squeezed budgets and payroll will have a difficult time fitting anything new and different into their menus, no matter how wonderful. It all takes time, money, attention to detail, and bodies to run the tests. In the current healthcare climate it can be hard enough just to get the bread and butter tests done in a timely fashion as more and more labs adopt a rapid response model.
I don’t know the answer, but I don’t hear physicians beating down the door for in-house PCR just yet.
I’m interested in how this technology has affected your laboratory. Has it lived up to the hype, and what problems have you encountered? Is it worth the expense?
NEXT: Slide Review or Manual Diff?
One of the phrases I hear lately is “we need to move the needle,” meaning enough effort has to be put into change to not just make it stick, but change what matters. This might be customer satisfaction scores, test volumes, or cost containment.
If there’s one thing that change has taught me, it’s that no matter how much things change they seem to stay the same. The needle almost never moves.
I’ve witnessed countless alphabet soup campaigns, LEAN initiatives, customer service gimmicks, changed hours, changed protocols, and new technology. It isn’t so much that each change is filled with false promises or defeated by dashed hopes. In fact, we can all be easily convinced that any of these things can make a difference. They almost never do. Change is a constant in a world stubbornly set in the present rather than anticipating the future.
There are several good reasons. We are motivated by emotions, not numbers. Data is an excellent rationalization tool, but it won’t convince people to change how they feel about something. We each have a gut feeling about what works and what doesn’t based on the culture we work in. That is an extremely powerful force to try to overcome from within. Indeed, it may be impossible for a negative culture to change itself.
We are also motivated by leadership, a quality rare enough that we don’t just know it when we see it - we are surprised. I think leadership is a skill like many others that can be acquired with a good working knowledge of what it is. Without good leaders who can articulate a vision and make decisions that cement values in place, change is just pointless change that has no lasting effects.
Finally, each of us views change as something different. The classic management wisdom is “people hate change,” which is misleading. People love change if it means making their lives more convenient. What they don’t like about change varies enormously. Some don’t like change because they don’t trust the motives behind it; others don’t like it if they weren’t included in the decision making; still others have too much stress in their life outside of work to deal with one more change. Management frequently forgets that change happens everywhere in life, and often a workplace is the most stable environment a person has.
So, how do we move that needle?
For me why people are “resistant” hints at the answer. We need leaders who are not afraid to motivate people with emotions and who understand that our work lives are but a part of whatever we are going through. We need leaders who can articulate in plain, blunt language the stakes. We need the values to be articulated honestly and plainly enough to be supported by human interest stories that really motivate people. Leadership needs to walk the talk.
But that’s just me. What about your lab?
NEXT: Is PCR Ready for Small Labs?
One of the oft-quoted nuggets in The Elements of Style is “omit needless words.” I’ve seen this rule praised and criticized with equal fervor. As a writer, pruning and trimming prose seems like a necessary path to clarity for the reader. It is also intensely personal and driven by one’s own style. But in general, it’s a good rule of thumb. If it takes 4 words to say the same thing in 15, use 4. (Have politicians read Strunk and White?)
Unfortunately as bench techs we don’t have the option to rewrite and revise with time to mull over or forget what we’ve written. What we tell physicians has to be clear, concise, unequivocal, and reproducible. The more judgment that is involved in a test, the more difficult this can be and the more variation one encounters.
Variation dilutes quality, clinically significant or otherwise, and invites STAT abuse. If, for example, 95% of in-house chemistry tests are completed in a narrow time frame, there is less variation and the process creates consistent expectations for providers. They are less likely to order a test STAT to bump it to the top of a queue that has widely variable turnaround times. To a lesser extend, limiting variability in reporting non-numeric values builds similar expectations and can reduce telephone calls, repeats, and requests for further review.
I described a way to simplify urinalysis and reduce variation in a recent blog. While seemingly trivial, this kind of approach reduces the number of choices made by techs, another form of variation that increases the amount of work done.
One of the advantages information technology brings to the laboratory is the ability to reduce variation by defining result entry parameters. For numeric results this can mean entering a lower reportable limit in a test definition that causes the system to automatically change a value below the assay range to less than that range. For alphanumeric (text) values this can mean limiting the number of choices to a drop down list or selection box.
A simple example is limiting qualitative testing results to Positive or Negative. This can be improved in a few ways, perhaps. Positive can be offset with characters e.g. ***Positive, or these can be abbreviated to ***POS and NEG. One problem I have run into with fine-tuning what these look like on native reports is that usually formatting is lost in HL7 translation to another system such as Athena or the T-System. Something to think about.
Other examples: blood bank types, RBC morphology choices, urinalysis dipstick values, Gram stain morphology. Most information systems out there have this capability to limit input in the sense that only a few selections are available to result the test. From an IT perspective this makes sense when assigning SNOMED codes and uploading discrete data to central database systems. The fewer results listed in “comments,” the better.
What about your lab? Have you limited input, and does this improve quality?
NEXT: Moving That Needle
The laboratory is a unique clinical department. The possible tests and their associated billable codes that are routinely ordered day in and day out can number in the thousands or even tens of thousands. The big moving target is referral lab testing, which may change according to where it is forwarded, reflex testing, or method changes. I spend a significant amount of time comparing bills to the charge master. If we don’t get paid, we can’t keep the doors open forever. Are you getting paid?
Some of the issues that make laboratory work complex include:
- Associated charges that change. Some associated charges are routine, but many reflex or are conditional. This can be a real problem with referral or esoteric testing.
- Charges that have to be bundled with other charges. Many physicians have patterns, but there are only so many patterns that can be learned. The sheer volume of testing and ordering tactics make this a constantly moving target.
- Late charges. Many late charges are related to testing that is performed a day or two after collected, such as with microbiology cultures or pathology specimens. Still others are caused by invoices with additional charges.
- Incorrect CPT codes. CPT codes change year to year, but they also change when methods change in laboratories. This is another constantly moving and often confusing target.
As a manager, you can tread dangerous ground stressing accurate billing. What we do is for the good of our patients. But if you don’t get paid, you can’t keep the doors open. And if you don’t charge for everything accurately, you won’t be able to justify the staff you have. Another lab with the same workload that bills for everything will look better.
I’ve puzzled over this idea of charge reconciliation - how do we know we have charged for everything? - for the past few months. It is not an easy problem for a laboratory to solve. Laboratory testing is complex.
One crucial strategy is to make sure your referral testing - easily the biggest target in terms of change - is accurate. Ask for an electronic version of your bill in Excel. From there it’s easy to compare it to a download from your information system to make sure you’re billing accurately.
Another strategy is to look at duplicates, missing tests, and things that don’t look right from day to day. This is extraordinarily difficult and time consuming in anything but the smallest labs, even more so when short staffed. I’ve created a SQL report that pulls out CPT codes and totals them by test per account number. Anything that could be a panel missing CPT codes or is a duplicate is flagged as an error. This is a great report, but I have a history of computer programming. I’ve no idea how any other lab would do such a thing. But we have to get paid. And if you don’t bill, you won’t get paid.
NEXT: Limit Input
Urinalysis is one of the simpler screening tests laboratories perform. Modern dipstick readers have standardized and simplified the chemical analysis of urine. But what about the microscopic? Shouldn’t that also be simplified?
Beckman Coulter and Sysmex offer instrumentation that performs cell counting. For many if not most labs, urine sediment is examined under light microscopy. White and red blood cells are reported as an average per HPF.
Sounds simple enough. Count the number of white cells in 10 fields, move the decimal point, and report that.
In fact what labs do is much more complicated and more difficult to reproduce with any precision. Cellular elements are reported as a range of cells and are only accurate to the degree where counting or estimating becomes cumbersome. In recent data mining I discovered a wide variation that implies the method is far more precise than possible e.g. 10-12, 15-17, 20-25, 50-60, 70-80, etc. This reflects more tradition than accuracy. More importantly, does it meet the needs of the ordering physician?
At a meeting I asked physicians about clinical efficacy. One replied, “It’s pretty straightforward. I want to know are there a few, some, a lot, or too many to count?”
So we changed reporting as follows:
WBC = 0, <5, 5-20, 20-100, >100
RBC = 0, <3, 3-20, 20-100, >100
While a cutoff of 20 cells per HPF is arbitrary, it is also practical. It’s easy to count 20 per HPF by counting the average per quarter of a field. And while 100 per field can be estimated accurately but counting cells along an arc of the field, a guesstimate works just fine for clinical purposes.
It’s nice to have more reproducible results, even if some physicians may not notice. More importantly, consistent, reproducible results improve quality. To put it another way, when techs report microscopic elements with a wide degree of variation this dilutes quality. A physician may understand the imprecision of a method, but he or she will also guess that finer distinctions won’t matter. “A few, some, a lot, or too many” is what they will read when they see the report. Why not make that easier for them?
Finally, while it may seem that 20-100 is too broad, it is consistent with implied imprecision. Assuming these are probable ranges, 5-20 is an expected 30% coefficient of variation and 20-100 33%. Thus, what we claim is consistently precise; it is easier to estimate 5-20 cells than any significant interval between 20-100 e.g. 50-75. 5 and 3 are cutoffs related to reflex culture criteria and microhematuria respectively.
Of course, arbitrary limits are just that. An implication that 30, 40, 60, and 80 mean the same thing to a clinician may or may not be true. There is also great variation among doctors. That’s why I asked first.
NEXT: Are You Getting Paid?
A nursing paradigm has been the “working manager,” a nurse who also works the floors and pitches in when needed. This model has been used in ancillary departments such as radiology and respiratory therapy. It makes sense to have a manager with first hand knowledge of the day to day workflow.
I don’t know how common this is in laboratories, but I suspect not very. It seems odd in a small hospital laboratory to have a manager sitting in an office while three or four staff members process specimens, but it happens.
There are some good reasons for this separation of labor, however. One is the complexity of the laboratory. Managing a flow of information that includes ordering, contracts, quality control, proficiency testing, competency assessment, procedures, and a charge master ever in flux is time consuming. Add to that going to meetings, organizing meetings, scheduling, dealing with personnel issues, and handling complaints, and that’s a busy job for anyone.
I’ve been in both kinds of roles. I’ve been a manager when very little bench work was needed and when 1-3 days a week was needed. If one is competent at managing information and people, being a working manager is advantageous.
Advantages: a first-hand knowledge of bench issues, giving credibility to changes that are suggested; greater respect from peers; for veterans, a (mostly welcome) break from the stress that the office often brings.
Disadvantages: can be extremely difficult for rookie managers; often means longer hours to get caught up on office work; sometimes difficult to concentrate fully on bench work with projects in mind; difficult to maintain skills not done as often.
A less obvious advantage is that working the bench can force a manager to delegate many tasks to others to have more time to get critical projects done. These might include submitting quality control, submitting proficiency testing online, scheduling, and even payroll. There isn’t anything special about most office work, and spreading the wealth can make it all the easier when vacations roll around.
A political advantage that should not be overlooked is respect from management peers, especially those working managers who ask the obvious if you don’t work the bench, “What makes you special?”
I wonder: have staffing shortages and cutbacks in small hospitals created more working managers? Do hospital administrations look at other departments and expect laboratories to follow suit? And what happens when someone who has been a manager for 20 or more years is suddenly asked to work the bench? Keep in mind lab managers are asked to do more and more all the time.
NEXT: Simplify Urinalysis
The Joint Commission National Patient Safety Goal 2 is to improve communication. For a laboratory, this means reporting critical results on a timely basis. Labs have to define critical results, by whom and to whom they are reported, and an acceptable length of time between “availability” and reporting.
Have computers lengthened our reporting window?
In all labs I’ve worked with an LIS, a critical value is called when the result appears on the screen across an interface. The results are on the screen, sometimes highlighted, and sometimes a hard stop forces the user to enter who was called, that a readback was performed, etc. That’s great.
But before computers, I never called after I finished handwriting the result on a lab slip. I called when the repeat result printed on the instrument. That’s where my feet were held to the fire, because that’s when the result was available. (And still is.)
A casual review of our lab has shown a similar perception of “availability” as when it is electronically available. It could be a critical in a stack of routine results, a CBC waiting for a smear review, or something else. Modern analyzers will often autorepeat critical values, further distancing a bench tech from the instrument.
This leads me to think that a critical results policy must define what “availability” means. In the case of transcribed or manual methods, this is often when the result is entered into the LIS - unless your lab still tracks everything on paper. If, for example, a positive C. diff test is a critical result, is it available when you write it on a log sheet or after you go to the computer, log in, navigate to the record, and record the result? Labs typically don’t write times on log sheets. But this is at least one good argument for getting rid of them and adopting real-time reporting.
For analyzers, availability is what it has always been: the time on the printout. As great as information systems are, it can sometimes take a while for results to appear in a queue. In the meantime, the result has been confirmed and available, just like in the days before computers. What I’m suggesting is that computer interfaces have conditioned us to rely on its electronic reporting as a redefinition of availability, when they are really a proxy reporting tool largely disconnected from the testing itself.
Of course many bench techs will telephone an extreme or critical result when it prints. But is this true for all critical results? I’m not sure, but the only way to know is to audit the printout to report time gap. Keep in mind when developing a policy that nursing also has a similar policy with a time limit; their clock starts ticking when they receive the call from the laboratory. If both times are at maximum defined by policy, this can add a significant delay to the treatment of the patient.
NEXT: Working Managers
A lab tech’s job is very linear. Requisitions arrive, specimens are collected that match the tests that are checked off, the work is done, the tests are reported. We know what docs want. Right?
For the most part, yes. Most docs - especially younger ones - are not afraid to order lab tests. Many docs have favorite tests or favorite referral labs. But the sheer volume and variety of referral and esoteric testing is overwhelming. Even tests performed in-house can vary greatly from lab to lab in terms of sensitivity and specificity. Physicians are bombarded with information on all aspects of care and can’t be expected to keep up on every new development in diagnostic testing.
In other words, docs don’t always know what they want. Not exactly, anyway. That’s where we come in.
We forget how much docs rely on our experience and expertise that can be extended to making suggestions and recommendations. A physician once told me, “You guys run the tests and are the experts. I figure if you tell me a result is good, I have to believe you, because I don’t do what you do.” We need to remember that our specialized knowledge is unique in the healthcare setting. It’s true that docs interpret laboratory testing, but we often know what testing is best or what factors affect a result. As long as we are assertive in the best interests of the patient, the physician will not mind.
This goes clearly against the grain of the older, seasoned techs who learned to work in an environment where the physician was never questioned. It was a weird way to work, in which we were excluded from care plans and decision making and just left to perform the tests like robots.
These days the laboratory should be expected to take a much more active role. At my new position I attend an interdisciplinary team daily at which the hospitalist reviews inpatient cases with those in attendance. This includes nurses, social workers, physical therapy, dietary, pharmacy, and (since I have accepted this position) me. I have a sense it is unusual to have a lab person at these meetings. But I am often asked questions about cultures, sendouts, or blood bank. And if I can contribute, I will.
What’s interesting from a lab tech standpoint is how often the nurses suggest ideas to be supportive. A nurse might say, “Should we order a swallow eval on that patient?” and the doctor will say, “Oh, great idea, let’s do that.” It is apparent to me that docs simply can’t think of everything and remember everything at once. They appreciate help that comes from an interest in the best care of the patient.
This is completely different from the world I was trained in. Lab techs are not trained to be active participants in patient care, which is odd considering how much doctors and nurses rely on lab tests. But to know what the doctor wants, you have to pay attention, ask questions, and sometimes make suggestions.
NEXT: Critical Time Limits
According to one site, 1 in 40 adults (about 2.3% of the US population) suffer from obsessive-compulsive disorder. While it’s a serious condition that can be treated and is no laughing matter, I can’t help musing if the percentage of lab techs with OCD is higher. Most techs I’ve known joke about OCD, because the field requires a lot of learned behaviors that can appear compulsive.
On the Oscar to Felix scale of compulsiveness, for example, most lab techs are closer to Felix and the Oscars of the world drive them (OK, us) batty. Oscars make it difficult to step in and help on the bench, and even more difficult to follow work.
I know, I know. We are all different, we all have to get along, and one person’s chaos is another’s organization. I suppose. But it’s also a patient safety issue. If we don’t know what someone else has done, what someone else is working on, or what is pending, results can be delayed or incorrectly reported. Eventually, all techs get burned on an experience like this. We all know those on the bench we are happy to follow even if they leave work behind, and those we hope finish everything before they leave for the day.
Much of the compulsive behaviors I have observed involve checking pieces of paper or using paper to track a workflow, even though information systems are designed to do this with greater speed and accuracy. There isn’t anything wrong with all this paper, but it can create a chaotic mess on the bench. I’ve seen techs put paper in piles, leave it as a trail wherever they go, hang it on multiple clipboards or hooks, create numerous forms to track miniscule details, and order stickers alphabetically by patient name. Some techs are just-so, and some are not.
This isn’t a criticism. I understand the need to have a system that accurately tracks a large amount of information that must be accurate and timely. But our systems make it easier or harder to follow each other.
They are also time and space consuming. For example, if instrument tapes are compared to results in the information system, stickered for identification, saved with the day’s work, bundled at the end of the month, and bundled at the end of the year for storage, that is five times paper is handled (and additional expense to store for at least two years) when it can be thrown out if there is an electronic record. Many instruments allow results to be stored on a thumbdrive, capturing repeats, which allows all paper to be discarded.
We bristle at criticism, especially when our habits reassure us that we aren’t missing tests. But I’ve seen paper lost or misplaced countless times and work missed. It’s a big reason for why information systems are designed to alert users when work is overdue in one way or another. While a computer interface is consistent - unlike our paper interfaces for tracking - the next question is can you follow the computer?
NEXT: Know What Docs Want
Do older techs hate change? It’s a cliche that an old dog can’t be taught new tricks. When someone is “resistant to change,” ageism inevitably follows. “She’s old and close to retirement,” I’ll hear. Conversely, young people are assumed to be champions of change, malleable, and willing.
All of which may be true to an extent, but adopting such a view dismisses experience as a variable. The reason “older” techs hate change is because they’ve been there, done that, and have a closet full of tee shirts. It’s true that in time we all become tired of change for the sake of change, but it’s worse to be ignored or dismissed. Decades of experience working the bench includes decades of change, large and small. That counts for something, surely.
And younger techs naturally embrace change because it levels the playing field. A lack of experience prevents you from seeing unintended consequences of change. And all change has unintended consequences, hopefully more good than bad.
As a manager, I’ve always taken the approach that resistance is information. “Why would we do that?” and “That is a waste of time,” to mention two classics, should open a dialogue. And here is where it gets interesting.
Why would we do that? Decisions are based on values, whether we appreciate it or not. We value the patient experience, the support of employees, quality, the bottom line, etc. All managers approach their position with a set of values that overlap with those of the organization. Unpopular change involves unpopular or unknown values. Good managers are consistent in expressing their values through decisions. But when a decision doesn’t make sense or is out of synch, it’s natural for people to ask the question.
That is a waste of time. This is a clear clash of values and vision. As a manager you might see a change as important, and when challenged in this way there are several alternatives. You might, for example, attempt to explain why. You could invite the group to brainstorm alternatives to the change and possibly be surprised. Or you could just pull rank and tell everyone to suck it up. What you choose will be a reflection of your values.
The mantra in management training is that “resistance” is inevitable. I disagree. Like a trick, the acceptance is in the presentation. The last thing that any tech who works a hard 40 hours a week is that he or she will be asked to do more. Or less! Efficiency can be threatening to those worried about losing hours.
Do older techs hate change? I don’t think so, at least not in any meaningful sense. Experience hones instincts and brings wisdom, two qualities any manager needs to succeed. Ask why people hate a change, and they are likely to tell you. Opening this kind of dialogue is a first step to success.
NEXT: Who Can You Follow?
In my last blog, I described how to create a table in a database that stores blood bank index card file information. At a minimum, this should contain the patient name, date of birth, and a checkbox to indicate if the patient has antibodies. That’s the easy part, and it can be done in a few minutes.
The other features of OpenOffice (and Access) are creating Queries (search filters), Reports (to print or view data), and Forms (to enter and view data). At a minimum you’ll want a to create a form to make data entry easy. The good news is that creating a form is even easier that creating a table.
- Click Forms
- Click Use Wizard to Create Form...
- The form wizard will list all the fields in your database table. Add all fields but the ID field (a unique record identifier) by highlighting and clicking the right arrow. You should see the field names move to the box on the right.
- Click Next
- Leave Add Subform unchecked. Click Next.
- Click a control arrangement for your form e.g. Columnar - Labels on Top.
- Click Next 3 times to select defaults.
- Enter a name for the form e.g. Edit Cards. Click Finish.
Once you open the form, it looks something like this:
It’s nothing pretty, but it is functional and gets the job done. You can enter data, using Tab or Enter to go to the next field. At the bottom of the window are tools to search and page through your records.
For those of you who are database savvy or know someone in the building who is, it’s possible to optimize this form by creating a date mask in the DOB field (so all you have to do is enter six digits) and skipping the Antibodies checkbox when routinely entering data. This will allow you to enter data as quickly as possible. If you are entering the data sequentially from the card file, you can also use Windows cut (Ctrl-C) and paste (Ctrl-V) shortcuts for last names.
Once all the cards are entered, then what? Here are ideas:
- Use the mirror to see if a card is in the file. This can be done before or after. If you choose to add blood type to your table, it can be helpful for the blood banker.
- Plan to scan. Although this can be involved, it’s easy to add links to scanned images associated with the patient, such as handwritten cards, transfusion reaction workups, antibody panels, etc.
- Create another table for the data on the card itself and link it to the main table using your ID key. This is slightly more complicated than creating the simple form above, but OpenOffice makes it very easy.
Entering demographic information is the hard part. Once data is entered you may, for example, decide to migrate card information as needed to the database, gradually eliminating your paper card system. You can begin by migrating those patients with antibodies or other unique needs that make misplacing their cards such a high risk.
NEXT: Do Older Techs Hate Change?
In building a blood bank cardfile mirror, the main element is the database table. A table is a collection of records that stores data in fields. In the case of OpenOffice Base, when you open the program (called Database in the OpenOffice main menu) a dialogue asks if you want to create or open a database. Then the screen looks something like this:
Create Table in Design View…
Use Wizard to Create Table…
Your blood bank cardfile table is created in the [highlighted] tables tab, and all tables appear below. To create a new table, click Create Table in Design View and enter your field names and type of data. Free text the Field Name and choose Field Type from a drop down.
The ID field indexes your table. It also allows you to link records to other tables. Right click the box to the left of the ID Field Name and select Primary Key. Then make sure AutoValue in the Field Properties tab on the bottom of the screen says Yes. Save and you’re done.
It’s easy enough to add fields to this table. For example, you may find it useful to add a blood type field. This would also be a Text [VARCHAR] type. Note that all this works very similar in Microsoft Access.
The hard part is always data entry. Blood bank history files are deceptively large. It’s easy for a small hospital laboratory to collect thousands of cards over the years, but all the information has to be entered. It’s something to think about when designing your table. You’ll want to enter a minimal amount of data as quickly as possible. You can always add more later.
If you double click on your table, you can start entering data in what looks similar to a spreadsheet. But is there a better, easier way? Next, I’ll describe how you can create a data entry form in minutes.
NEXT: Form and Function
The concept of a database is simple: data is stored in tables and linked together. Once the data is stored in a table of fields you design, you can do anything with it. You can sort, print, or filter it.
The problem of a blood bank card file mirror may sound trivial, but the impact can be significant. If, for instance, 5% of 5000 cards are misfiled, that means 250 cards are not exactly where they should be. Depending on your population, your lab will have a variable population of patients with clinically significant alloantibodies. But let’s assume for the sake of argument that 1 out of every 250 antibody screens is positive. All it takes is one.
A table is a list of fields. Conceptually, it’s very similar to a spreadsheet where each column is a field and each new record is a new row. In this case, the fields are Last Name, First Name, Date of Birth. The simpler you make it, the easier it is to enter data. For now, all we want to know is if there is a card in the database.
Not all cards are equal. The possibility of the patient with a titer of anti-Kell too low to be detected is significant, for example. Fields can store a variety of data: text, date, integer (a whole number), and Boolean, a $64 word that means “true” or “false.”
In my database, I added a field called “Antibodies,” a Boolean type that flags a patient with ANY reason to order special blood types (usually antigen-negative). These are the cards you never want misfiled.
You can see where I’m going with this. A patient arrives in the ED, and you check the database to see if a card exists. Even if you don’t find the card, it helps if “Antibodies” is unchecked. But without a mirror database, you have no idea how many cards are misfiled.
If you Google “openoffice base video tutorial,” you can get started. It’s easy. Next, I’ll describe what the finished table looks like.
NEXT: Cards on the Table
There are many kinds of software licenses, some more restrictive than others. If your hospital uses Microsoft Office, for example, a certain number of licenses has been purchased to match the number of workstations the software can be installed on. Typically, the cost of these volume licensing agreements are customized to the type of organization, number of users, and infrastructure, and it isn’t cheap. These days, it’s a cost of doing business.
I have used Access, a database application packaged with Office, in previous positions to create a simple mirror of a blood bank cardfile, for example. Manually filing paper cards always risks misfiling, and there is a small but significant chance that a lost card containing information about a patient alloantibody could enable a transfusion reaction. The concept of a database mirror is simple: if a patient is in the database, there is a card in the cardfile. If the card can’t be found, it must be misfiled.
Access is easy to use and wizard driven. No programming is required.
But not all flavors of Office come with Access. If your hospital has purchased Office without Access or has a limited number of Access licenses, is there an alternative that is easy to use?
You could, for instance, maintain a list of names in the cardfile in a spreadsheet such as Microsoft Excel. The problem with Excel is that it can’t easily do what a database does: search on complex terms and link tables together. It’s also too easy to alter information in the file. But sure, Excel could do the job.
Fortunately, there are free alternatives to Access. OpenOffice Base, part of the OpenOffice suite, is an open source product that is completely free. “Open source” means the source code is freely distributed, allowing programmers to modify and improve the program. This kind of collaborative coding improves code for its own sake instead of profit. The power of open source software is that it is always being improved.
Can OpenOffice Base create a blood bank cardfile mirror? Sure. It can do much more. Next, I’ll explain how.
NEXT: Building a Cardfile Mirror
Each new year brings change after a season of excess. At home it’s time to hit the gym, dust off the exercise bike, and put the juicer back on the kitchen counter. At work it’s time to bundle up 2015, discard old records, and think about planning vacations for the year. Perhaps, you have resolved to mend relationships, forge new ones, or rekindle old ones. A new year is a fresh start.
List makers (and you know who you are) already started a week ago. But for the rest of us, the year is a clean slate. Here’s what I’m looking forward to in 2016:
- Online blood bank cards. Many blood banks have a paper card system to look up recipient history. But what happens when a card is misfiled? In 2016 I’ll begin migrating cards to an online database that is fast, simple, and easy to make.
- Autoverification. I’ve tried autoverification with other systems without much success. It could be an idea best left to middleware. Our current system has this capability, and I’d like to try it. The amount of time a tech spends reading and verifying normal values is too large to be ignored.
- Simpler competency assessment. Competency assessment is something all labs struggle with, but it should be treated like any other aspect of method validation. Time spent on competency assessment adds up, too. And all tech time costs money.
Labor shortage woes are well known. I don’t have a sense that movers and shakers are motivated to help our industry. As more techs retire or move on because of pay or advancement issues, doctors rely more on accurate, timely testing. That’s one big iceberg ahead.
I often think a layperson would be surprised at how much our industry still relies on paper. The electronic medical record is coming, but it has been bedeviled by the complexity of delivering care, interface woes, and Federal sticks and carrots. 2016 could be the year of the computer in healthcare.
In this blog, I’ll begin describing how to build a simple card database. Did I mention it’s free?
NEXT: The Power of Open Source