The healthcare industry is not lacking for data – but using that data to generate actionable insights that drive clinical and process improvements is another matter.
Approximately 30% of the world’s data volume today is being generated by the healthcare industry, according to RBC Capital Markets. By 2025, the compound annual growth rate of data for healthcare will reach 36%, significantly faster than manufacturing, financial services, and the media and entertainment industries.
The challenge healthcare leaders face revolves around not simply acquiring data, but how to access data quickly and efficiently to successfully implement clinical-quality and process improvements that lead to better patient outcomes and improved business results.
Using data to improve care for kidney-transplant patients
In clinical programs, there are processes and workflows that have a trickle-down impact on patient care and access. One area where this is particularly true is for patients who may be in need of a kidney transplant, a clinical process that may last up to two years due in part to delays and bottlenecks.
Typically, a patient seeking a kidney transplant undergoes a four-stage process: First, the patient is referred from a community nephrologist as a transplant candidate to a hospital. Next, the patient undergoes an evaluation process by a multi-disciplinary team from the hospital that assesses the patient’s candidacy for a transplant, considering factors such as patient history, lab results, future outlook, and more. Then, the case is presented to a selection committee that considers whether to approve the case. Finally, once a case has been approved, a request for surgery is submitted.
To improve the process for patients and clinicians, one hospital performed a data-driven evaluation of its kidney-transplant program from end-to-end. The team responsible for kidney transplant orchestration began by gathering and studying data to understand bottlenecks and determine how long each stage of the process lasted, on average. This included seeking out answers to critical questions, such as:
- How many days occur between each of the stages?
- What are the workflows in place that are part of each stage?
- Who are the players involved? What are their limitations?
- How do we better document the process?
After reviewing the data, the team identified two stages of the process that could be streamlined and accelerated: referral to the completion of evaluation, which sometimes took up to 16 months due to limited availability of key decisionmakers, and surgery, which may not occur until several months after a patient is approved for a transplant.
The referral and evaluation stages of the transplant process are essential steps to screen patients to confirm whether they are appropriate for the level of service they are requesting. To optimize these stages, administrative leadership must create processes and workflows that minimize variation between patients. For example, there can be a questionnaire that administrative staff follow to document appropriate reasons patients must fulfill to obtain the service. In transplant surgery, not all patients can start the transplant evaluation process because there are certain indicators like lab results (creatinine being too low, for example) and medical history (need for dialysis) that prioritize the urgency of a patient to undergo a procedure.
Similar to referral, the evaluation stage is a resource-intensive process. During evaluation, all stakeholders must align to create the most efficient schedule for the day. In transplant services, a patient often must see five clinicians (nephrologist, surgeon, nurse transplant coordinator, pharmacist, and social worker), obtain x-ray and lab work, and may need additional approval from other specialties, such as cardiology, hematology, and endocrinology to confirm a thorough evaluation prior to an invasive surgery. Aligning these services to occur in the most convenient schedule possible for clinicians, patients, and staff is a challenge.
To overcome these bottlenecks, the hospital’s transplant service line leadership implemented two key process improvements. First, to streamline the evaluation process, the hospital established partnerships with third-party groups that could deliver services such as cardiac testing and radiology. Next, the team established the following standardized one-day schedule to evaluate potential transplant patients:
As a result of the changes, the hospital was able to decrease time and money spent on non-productive work while increasing the rate at which transplants are scheduled. Additionally, quicker time to surgery equates to less time on dialysis for patients, better long-term outcomes, and greater quality of life.
Similar to this hospital’s improvement of its kidney-transplant program, health systems across the nation have an abundance of targets for clinical and operational improvement at their fingertips. They simply need to empower their departmental staff to ask the right questions and follow where the data leads.
Katherine Jean is a Clinical Specialist with MDClone.