For any patient, for any given procedure, there are a wide range of variables that can not only drive up the costs of care but also impact outcomes. Hospitals and clinicians have processes and within these processes are multiple steps: during the assessment, treatment and recovery process, despite the steps that may even be documented through protocol, there will be variation. That variation exists among providers as well as patients and procedures.
What if we could harness and examine that variation to identify opportunities for improvement and best practice dissemination? A strategic approach to data collection and analysis can make that possible.
Wide Variation in TKR
Let’s consider one of the most common procedures that patients in the United States undergo in hospitals—total knee replacements (TKRs). We know that there is widespread variation in TKRs, within and across facilities. One way of measuring this variation is by cost of care. As one study across 29 high-volume US hospitals revealed: “despite having similar patient demographics and readmission and complication rates, the average cost of care for total knee arthroplasty across the hospitals varied by a factor of 2 to 1.”
The Healthcare Bluebook suggests that the range of pricing for TKR varies between $23,134 and $73,743 with the average CJR bundled payment around $36,000. While complication rates following TKR are low, the cost of complications can be quite high. For example, thromboembolic disease is associated with significantly increased cost, estimated at $18,000 when identified during the index hospitalization and nearly $6000 when diagnosed after discharge, creating a readmission. Similarly, the economic burden of periprosthetic joint infection is astronomical, with an average cost of $116,383 per episode.
The cost of comorbidities has been well documented over the past two decades. Bozic et al. evaluated all payments to Medicare providers up to 30 days postoperatively and found mean episode-of-care payments ranged from $25,568 for primary TJA in patients with no comorbidities to $50,648 for revision TJA in patients with major comorbidities or complications. Modifiable and non-modifiable risk factors have been well documented, but there has been no easy way a hospital or surgical team could capture all the data associated with these variables, much less parse and analyze it in real time. The ability to focus on whether preoperative optimization of chronic medical conditions and variables can reduce postoperative complication rates would change health care for the better. Seeing, in real time, whether this reduces episode costs while delivering better patient outcomes would be the holy grail.
For a typical procedure there will be variables that can impact cost. But it’s not just cost that we’re concerned about, although that is certainly an area of heightened focus for both providers and patients these day. An equally, if not more important, concern is quality of care and positive outcomes. A significant point to make here is that higher quality of care and better outcomes are not, necessarily or naturally, associated with higher costs. In fact, by gaining insights into variation and best practices, health care organizations can drive out costs while increasing quality of care and achieving better options. That’s a win-win-win—for providers, patients and society.
Identifying Sources of Variation
At each stage of care—from pre-op, to the surgery itself (intra-operative) to post-surgical, a wide range of actions are taking place—actions that, if monitored and documented, can yield important insights not only for an individual patient but, when aggregated, for an organization’s processes and approaches to a given surgery. (Taking this one step further, of course, if aggregated across multiple care settings, even broader insights can be gleaned; but let’s keep this focused on one facility for the purpose of this illustration.)
Things would be complex enough if the only determinants of the cost and success of a procedure, like a TKR, were driven by things that the hospital could control. Added complexity enters the picture, of course, when we consider potential patient impacts—pre- and post-surgery; things like whether they have diabetes, whether they smoke, whether they comply with pre- and post-surgical directions, etc.
What if a hospital was able to gather information at every step in this process, and enter it into a system where it could be evaluated to identify factors that might impact both cost of care and care outcomes? Let’s take a look at some key steps in the TKR process where costly variation may occur:
Intra-Operative (during surgery)
The ability to effectively capture and understand what happens during surgery, such as pain protocols, surgical antibiotic prophylaxis, and blood loss doesn’t only affect patient care—it also affects the cost of care. For instance, do you have surgeons that use Exparel? Since it is technique based and costs more than other pain protocols, would it be helpful to know which surgeons have better seventy-two-hour pain control than others? Or how this compares to surgeons who only use IV Tylenol or Tylenol BID. The ability to automatically collect and easily analyze aggregated data can help yield insights into process improvements benefitting both patients and the bottom line.
What implications do personal characteristics of patients have on outcomes and costs of care? Patients with diabetes, for instance, represent risks associated with complications related to poor glycemic control, neuropathy and higher post-operative infection rates. Patients who are smokers are known to have higher rates of complications after surgery, including poorer bone ingrowth into orthopedic implants. To what extent do these factors impact clinical outcomes and costs? What can be done to help manage and minimize these costs? Collecting the right data in real time and analyzing these impacts can save money—and lives.
Capturing information from a patient pre-surgery can help with both short- and long-term follow-up. The Patient-Reported Outcomes Measurement Information System (PROMIS), Knee Injury and Osteoarthritis Outcome Score (KOOS) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) are all widely used measures relying on patient input to manage patient care prior to, and after, surgery. Capturing this data electronically allows the ability to aggregate and study impacts to help improve care and modify processes and protocol for better results. Allowing the patients to complete the surveys at home also encourages more truthful responses and saves valuable time at the office.
Patient Compliance Pre-Surgery
How well do patients understand and comply with pre-surgery directives and clinician advice? Joint Camp offerings help patients and their families understand what to expect before, during and after surgeries—but only provide clinical and financial benefit if patients understand and complete the classes. Automating the process and capturing patient data can help make improvements in these offerings to boost both comprehension and completion.
Treatment and follow-up after surgery is impacted by many variables—some of which might be the determining factor for reimbursement and/or readmission rates. Days at a skilled nursing facility (SNF), the use of pain medication and PT visits can vary by patient and facility. Again, patient compliance can impact outcomes and drive up costs of care—e.g. using more medications than necessary, not performing range of motion exercises. Optimizing post-surgical treatment decisions can be positively impacted by collecting and analyzing data on how variations in both patient actions and clinical decisions affect outcomes. Patient input can also be leveraged to improve the patient experience and boost Net Promoter Scores which are highly correlated with patient loyalty and positive word-of-mouth.
Capturing and reporting this data in real time and making it available for providers to review and compare can yield to individual insights. That is only one step along the road to process improvement. Bringing providers and administrators together to more deeply focus on the real-time data—and what it’s telling us—can yield weekly or monthly best practice process improvements and the elimination of variation. The net outcome will be better results, lower costs, and enhanced profitability in the recon service line.
When hospitals and health systems are able to easily collect, analyze, and report what is driving outcomes throughout the surgical care continuum they can adjust processes and communications. These changes can improve outcomes and drive down costs.
TKR is just one—but one very prevalent and costly—procedure performed in hospitals around the country. This same process of data collection, discovery, discussion and process improvement can be applied to all orthopedic cases. Prioritizing areas of focus—by overall cost, number of procedures, impact on outcomes, etc.—can be a great place to start analyzing your own cases to see where improvements may be not only needed, but necessary.