Emergency physicians, and all other health care providers, are going to have to develop and adopt meaningful and responsible strategies to reduce the cost of care in our country, regardless of the outcome of the next election. The American College of Emergency Physicians has chosen to bypass the Choosing Wisely Campaign as insufficiently rigorous, and the College has some legitimate concerns. However, this simply means that the College must commit to a course that yields compelling, useable, and evidence based strategies that in turn result in significant cost savings while preserving patient satisfaction and improving outcomes. This is the challenge of the decade for ACEP (and the rest of the house of medicine), and the College’s Cost Effective Care Task Force is faced with a daunting task.
Defining ‘cost effective care’ is the first step, and it is a challenge in itself. Given the limited resources available for the development of these strategies, the lack of much published research on cost effectiveness in the acute care continuum, the political and public relations need for an expedited set of recommendations, and the wide variety of social and medical conditions that emergency physicians confront every day; this Task Force (and other members of the EM community) will need to find ways to target the most significant opportunities for cost savings in the practice of emergency medicine. They also need to identify strategies that practicing EPs and hospitals can readily adopt (perhaps based in part on the KISS principle). Elaborate, complicated protocols or decision trees that are difficult to remember or use are unlikely to be very effective. In addition, these strategies need to accommodate the regulatory restrictions on shared-savings incentives that may be needed to encourage adoption. Access to utilization data to monitor the actual cost savings that ensue will be critical. It is simply unacceptable to come up with proposed solutions to this economic crisis that just make it LOOK like the College and the specialty is doing its part: the solutions need to actually work, and measurably deflect the rising cost curve. This will be a work in progress for many, many years.
Willie Sutton supposedly said, when asked why he robbed banks, “it’s where the money is”. In medicine, Sutton’s law is about looking to the most likely diagnosis to explain the signs and symptoms, and in the management accounting version, Sutton’s law stipulates that you should look to where the highest costs are incurred to find the greatest potential for cost reduction. I believe that when it comes to cost-effective care in the ED, we must consider not simply the most common diagnosis, or the most expensive tests and treatments, but an amalgam of these laws. To carry the analogy a bit too far: a smart bank robber doesn’t just rob any bank, he robs the banks that hold the largest deposits, are relatively ‘easy pickin’s’, and aren’t likely to get him burned. To get more bucks for the bang, we need to look at the clinical challenges that EPs face from a population perspective, and at the clinical decisions that carry the greatest economic consequence for the greatest number. We need to know where and how we spend the health care dollar, and THEN consider whether we can fashion relatively simple, evidence based, responsible and patient-centric strategies around these clinical conditions and costly decisions, tests and treatments. By ‘costly’ I mean cost times frequency, not necessarily ‘most expensive’ on a per-unit basis.
Some things are obvious: the decisions to admit or discharge home are clearly costly decisions for the ER population as a whole, and strategies that impact these decisions are likely to have real potential: but it makes little sense to try to exploit a strategy that influences the decision to admit or discharge for a condition like early anaphylaxis that is not that commonly encountered. Perhaps using a pneumonia severity index like the CURB-65 score that would allow safe outpatient treatment of more of these pneumonia patients might be a great strategy, since CAP is common (but remember, pneumonia is also the eighth leading cause of death in the US). I say perhaps because you really can’t answer this question without looking at how many admissions you could defer, and how much money each deferred admission would actually save relative to outpatient treatment. Ok, I admit, now we are talking about the kind of analysis that might take lots of money and years to conduct; but that does not mean we shouldn’t at least make a stab at estimating the impact, and the usability, of the CURB-65 score as a cost-effective care strategy. Likewise, finding ways to treat patients that do not need ED care in more appropriate, less expensive venues may be cost-effective, if it can be done in a non-punitive, reliable, and respectful way: but it is spurious to assume that deferral of ED care saves money without carefully examining ALL the costs associated with the alternatives, given the relatively small percentage of the total ED care dollar that is spent on the ED patients who might be candidate for deferral.
When ACEP’s CEC Task Force surveyed EPs for ideas about potential strategies to reduce the cost of care in the ED, they got hundreds of different suggestions; but it is simply not feasible to expect physicians to quickly adopt hundreds of different change-in-care strategies into their daily practice. I believe if it is possible to vet these strategies first by looking at the economic impact they may have, this might be a good way to focus the effort. Alternatively, it might be useful to first identify where the money goes, and then try to find the strategies that address these conditions and decisions, again as an early step in the process. To accomplish either approach, we need data: we need to know where the money goes.
Recently, I was able to convince a major health plan (which prefers to remain unnamed) to provide me with diagnosis specific, age and CPT defined, charge and payment data on 637,000 consecutive ED patients discharged from the ED, involving over 4600 separate primary ICD-9 diagnoses, and more than 3000 coded procedures, tests and services; along with similar data on 24,000 patients (shorter time frame) admitted from the ED. The discharged patients accounted for $963 M in payments (average around $1500 per visit), and the admitted patients accounted for $1.9 M in payments (around $7,900 per admission). This data included primarily commercial visits (~ 543,000) and a mix of Medicaid, Senior, Healthy Families, and other insurance coverage visits (~ 94,000), and the data for these different coverage types was aggregated by the plan so as not to reveal proprietary and confidential payment rate information. To some extent, this aggregation limits the utility of the data when it comes to deriving average cost per diagnosis, or payment per CPT coded service, but did allow me to arrive at ball-park estimates, which is generally suitable for targeting the best opportunities for cost-effective care.
Analysis of approximate cost per unit and frequency data for patients aged 4-64 allowed me to identify nine diagnostic tests that accounted for 17% of all the funds paid for all diagnostic and therapeutic procedures ordered (figure 1) and nine primary diagnoses that accounted for 19% of all costs for discharged ED patients in this age range (figure 2).
One could focus on these tests and procedures to search for potential cost effective care strategies, and this is not an unreasonable approach. However, trying to define a strategy or even several strategies to reduce the use of ‘CT head of brain, without contrast’ is complicated by the fact that this study is used in a multitude of clinical presentations and conditions, and most such strategies are condition or symptom complex specific. Focusing on the ‘most costly’ diagnoses (again, cost per visit times number of such discharged ED patients) could be useful; but a higher yield approach involved combining 62 of these diagnoses (out of 4500) into eight clinical groupings that were characterized by related or similar presentations, or diagnostic and therapeutic challenges. These eight diagnostic groupings, which I termed ‘clinical challenges’, accounted for more than 41% of all of the costs of care for the entire population of aged 4-64 discharged ED visits (figures 3 and head injury example – table 1).
Using this methodology, I identified several clinical challenge groupings that I felt identified the best potential targets for possible cost effective care strategies in five different demographic populations (table 2).
For each of these clinical challenges and the aggregated data for each of the included ICD-9 coded diagnoses, I broke down the services, tests and procedures that were reimbursed to identify where the best opportunities for cost-savings might reside (see example in Table 3 below).
This was further broken down by individual CPT codes (see Table 4 below).
Using this kind of analysis facilitates the identification of potential targets for cost effective care strategies that could have significant impact on the overall cost of care, based first on where the significant costs are incurred. Thus, in the case of the ‘Cough / Respiratory infection’ clinical challenge, the use of chest xrays in uncomplicated cases is a reasonable target to consider, and one possible strategy might be to specify the indications for chest x-rays in such cases, based on published evidence, in an effort to limit the unnecessary use of this fairly frequently ordered diagnostic test. In order to overcome the typical barriers to adoption of such a strategy, it would be helpful to provide, along with the strategy itself: the economic considerations behind the selection of the strategy, the epidemiologic considerations around the clinical challenge, the relative costs or charges for some of the tests and treatments used in these related disorders, the rationale behind the strategy, a suggested script to assist the clinician in explaining the strategy to the patient, and references to studies supporting the strategy. (Figure 4)
Cost effective care strategies for ED care can take on many different forms: listing indications for tests or procedures in a way that discourages unnecessary reliance on these services; recommending against the use of unnecessary treatments (like Rhogam in pregnant patients who have vaginal bleeding in the first trimester); suggesting alternative, less expensive options (like using PO Motrin instead of IV Ketamine in mild to moderate renal colic), or promoting the use of acuity/risk scores (CURB-65 in community acquired pneumonia) to enable clinicians to feel comfortable treating more of these patients as outpatients. The advantage of using this amalgamation of Sutton’s laws for medicine and accounting is that it may allow us to focus on strategies that have a greater chance of impacting health care decisions that are associated with significant costs. With the right data sets, this approach can be used by any and all specialties in a variety of health care venues. I strongly recommend that CMS make this kind of data available to the medical societies of specialists (like EPs) who frequently care for Medicare patients.
Another benefit of focusing on a relatively limited cadre of simple, validated and financially impactful cost effective care strategies is that, through a kind of halo effect, clinicians may be encouraged to incorporate consideration of the cost of care into their entire scope of medical decision making. It should be recognized, however, that most hospitals currently remain dedicated to a fee-for-service business model, and until these hospitals, and their medical staffs, are fully aligned behind the risk-assumption business model that is part and parcel of payment reform, there will not be a lot of encouragement for the adoption of these strategies.
Disclaimer: I need to point out that the analysis I have provided in this discussion is not a scientifically rigorous effort. Unfortunately, the data given to me was not discrete – it was aggregated in ways that make it impossible to determine with much certainty numbers such as the average payment for any particular coded test or service. Some pro fees for consultation services were not included; and the fact that the same exact codes are used to represent both professional E&M services and ED facility charges (how foolish was THAT decision?) limit the analysis. It is difficult to extrapolate this payment data to the typical ED, or to the entire cadre of 135 million visits a year to the nation’s EDs: 5/6ths of the claims represented are commercial claims, and I have never heard of an ED that has this kind of payer mix. The use of plan contracting practices like case-limit rates, and the inclusion of several different categories of insurance coverage into the mix will also have impacted this data. I am, however, more confident about the validity of the frequency of services and diagnoses information. In addition, the fact that EMTALA encourages EPs to use a standard approach to medical screening across all payer categories may limit the impact of a payer mix that is skewed heavily towards commercial claims.
Not withstanding these limitations, I do believe it is possible to use this data to arrive at a ballpark estimate of how we spend health care dollars in the ED, and on inpatients admitted through the ED; and to target the best opportunities to reduce the cost of this care. I plan to share the bulk of this data and my ‘clinical challenge’ analyses with the ACEP Cost Effective Care Task Force, and hope they will find it helpful in the development of meaningful cost effective care strategies for the ED.