3 Ways Your Current Finance Strategy Is Failing Your Hospital

Hosptial Finance Strategy

We've talked before about how hospital systems and other healthcare provider organizations need to focus on obtaining actionable intelligence. EMRs and other data collection capabilities are wonderful, but if the data isn't producing valuable insight, it's a waste of your time, effort and investment. For many healthcare providers, this is unfortunately still the case. Data collection and storage are happening, but the resources aren't there to sift, sort, analyze, synthesize and act upon all that information.

“Today, we are perhaps a small percent of the way toward using healthcare data effectively," Derek Gordon, general manager of health information technology (HIT) at Healthline, told The Journal of mHealth. "Data still gets stuck in its various silos, making it nearly impossible to create a true longitudinal patient record."

For hospital finance directors, this situation represents a serious challenge. On the one hand, you are under a tremendous amount of pressure from internal and external stakeholders to show a return on the HIT investments that the organization has rushed to make since passage of the Affordable Care Act.

On the other hand, the money you need to invest in order to fully realize the potential of your spend has, in many cases, not materialized — often because there is a distinct lack of resources to use the data you've gathered to increase your efficiencies and competitive advantages. It's a Catch-22 scenario, with serious implications for the long-term health of our institutions and our national care delivery system.

With seemingly little appetite on Capitol Hill and in state legislatures to underwrite additional investment in the industry's HIT capabilities, we must find the way out ourselves. Each organization will need to develop a finance strategy that facilitates the development of in-house analytics.

But so many are locked into play-it-safe thinking, or short-sighted board or shareholder-driven strategies. And those strategies are hamstringing our ability to evolve. With that in mind, let's take a look at 3 ways that your hospital's finance strategy might be preventing your organization from realizing Big Data's big promise.

1. We fail to invest in developing more intuitive automation.

It's one thing to invest in an advanced EMR. It's another thing to pay for the EMR's licensing and equipment, custom software development and data entry — particularly if you are relying on physicians themselves to function as their own data entry clerks (at a rate of several hundred dollars per hour of, essentially, lost productivity).

Although many doctors hire scribes to do this work for them, this creates friction. For one, physicians resent being forced to pay additional money out of their own pockets (especially as payer reimbursements continue to fall) to meet data entry requirements, so unless hospitals are subsidizing scribe costs, provider dissatisfaction increases. Two, physicians still must spend time training the scribe, reviewing the scribe's notes for medico-legal accuracy and, often, editing or re-drafting.

A doctor must therefore spend additional, unreimbursed time (sometimes many hours per week) re-doing the data entry. Then we wonder why they push back.

And even if a physician works with an expert, experienced scribe whose notes need little revision, whose compensation is provided by contract with the facility, the data that is captured is not readily searchable. Free-form notes and scanned documents are wonderful from a ready-retrieval standpoint — no more ordering charts from the Medical Records department and waiting for hours or days to receive them — but where does one begin to look? Physicians simply don't have enough time, in a clinical setting like the emergency room or in the ICU, to read each patient's entire electronic chart to skim out all the pertinent bits of information.

EMR companies really haven't helped much, either. Often, their approach to the searchability problem relies upon building screen after screen of templated, clickable menus — for history of present illness, for review of symptoms, for physical exam and more.

But as we might easily imagine, templating works both for and against us in the clinical care setting. On the one hand, it gives the searchability needed to gain patient insights and build smarter protocols. On the other, it wastes a great deal of clinical productivity by requiring the provider or scribe to blow through screen after screen of often-unnecessary negative inputs just to get to the few positive inputs required.

Are there ways we can build more intuitive templates and EMR cascades? We walk a fine line here: if we rely too much on templating and automation, inaccurate information can get into our charts and produce future liabilities. Should we rely on our EMR vendors to provide better automation? Or would it be better to invest in developing in-house solutions that are clinician-driven?

2. We spend far too much on short-term fixes.

How many times have you spent additional money to jury-rig an EMR solution, to develop a shortcut or an interoperability workaround? How many times have you had to repeatedly revisit the same problem, through iteration after iteration of workarounds?

“The goal of systems improvement is to reduce waste,” asserted a white paper produced by the National Quality Forum. "Poorly designed health IT systems, insufficient health data interoperability, and immature technologies contribute to workarounds that end up squandering more time than they save, especially when new processes are built upon the shaky foundations of old shortcuts."

We're in a strange position. Many of the systems we've invested in and that we're attempting to rush into the clinical setting simply don't work as advertised. And we fail to accept that.

Here's the thing — with any new movement in technology, time and financial allowances must be made for reconcepting, redesigning and repeated shakedown cruises. But, for some reason, we allow ourselves to buy into expectations of instant gratification.

Do you for a moment think that the earliest commercial versions of the automobile lived up to the eventual promise of the automobile? Of course not. In 1879, one-seater Benz's automobile contraptions were rickety, inefficient, noisy trikes that were slow, broke down often, fouled the air and got extraordinarily poor gas mileage. And they were expensive, to boot.

But within the first decade of their existence, the Benz company's product had evolved to incorporate a more stable four-wheel design, rubber tires, seating for two, multi-geared transmissions and safety lighting. Within 10 more years, open-air, puttering horseless carriages were becoming fully-enclosed vehicles capable of doing 25 to 35 miles per hour. Soon, they were in mass production and downright affordable.

To get there, car designers weren't cobbling together add-ons for the 1879 prototype. They were designing, building, testing strengths and weaknesses, then going back to the drawing board. Somewhere along the way in healthcare, we seem to have lost sight of the importance of the design-redesign cycle. Hospitals need to allot funds and time to tear down underperforming EMRs and build anew.

3. We base many of our analytics on fuzzy assumptions.

Sometimes, we fail to design our analytics projects around the right questions. That's understandable — particularly if the lack of meaningful searchability and interoperability hinder understanding of the full range of possible questions.

Even when we ask the right questions, though, hospitals too often jump headlong into data analysis projects without first aligning on what the measurables could, should or will be. There is a distinct lack of scientifically valid A/B testing and a failure to identify and institute proper controls. Expectations and assumptions drive analyses, rather than letting the available data drive experiment designs.

We can't afford to rely on emotive, irrational or reactive thinking. We must approach our analyses from a detached, logical and, most importantly, strategic standpoint. If the long-term goal of an analysis project isn't clear, the project shouldn't be undertaken.

Many healthcare institutions fail outright to budget properly for the resources needed — time, money, manpower, leadership and oversight — to develop useful reporting.

And that's where hospital finance directors can make the most direct impact to improve procedures. The job is, of course, to consider resource allocation above all else. If you are leading the charge for meaningful analytics, you must also make sure that your executive colleagues understand all the variables that must be invested in before a project begins.

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