HBR — Harvard Business Review
by Mohamad Bydon Fred Meyer
September 30, 2021
Many health care systems have a valuable asset that they are underutilizing: clinical registries.
These database systems collect information from each patient encounter, including comorbidities, surgical procedures, post-operative complications, and patient-reported outcomes via standardized surveys.
But they often are not being fully used.
- If select information from registries is displayed through dashboards, they can serve as tools to provide a comprehensive overview of a clinic’s performance in terms of quality, cost, and volume data for various procedures.
- Such registries can be used to identify areas in need of improvement, gain more favorable terms in contract negotiations with payers, and enhance patient-physician discussions and decision-making.
The Mayo Clinic’s Department of Neurologic Surgery did just that.
In 2016, the department’s leadership recognized the need to accurately collect and measure surgical quality in a systemic manner that tracked the Mayo Clinic’s expanding neurosurgery practice, which had grown to six campuses with 51 neurosurgeons in different parts of the United States. The two of us led a multi-site pilot effort to create a solution.
Our pilot was successfully completed in 2019 and new data is now being fed into our registry and dashboards on a continuous basis, with the exception of complications data, which data management analysts manually enter daily.
Our results have demonstrated that a departmental registry is an effective tool for tracking surgical outcomes in disparate practice settings.
Based on our pilot, other departments at Mayo Clinic are launching similar efforts.
Here are steps that we learned during the pilot that can serve as a guide to other health care institutions interested in creating a similar system:
- Identify the opportunity and the barriers to its success.
- Get widespread buy-in.
- Ensure adequate financial resources.
- Enumerate the variables of interest.
- Assemble a project team of talented people from all essential areas
- Create a feedback loop to improve and enhance the dashboard.
- Include predictive analytics.
- Use the data.
1. Identify the opportunity and the barriers to its success.
Our neurosurgery practice identified the need for a performance measurement system that would provide a comprehensive overview of the value of our highly specialized neurosurgical care that includes complex surgery on brain tumors, cranial aneurysms, spinal deformity, and other neurological conditions. The assignment — designing an efficient clinical registry tool for a complex and highly integrated health care organization like Mayo Clinic — was daunting.
Complicating matters was the geographic distance between Mayo Clinic’s various campuses. Mayo has one of the nation’s most robust neurosurgical practices, with 20 neurosurgeons in Rochester, Minnesota; 11 in Jacksonville, Florida; 12 in Phoenix, Arizona; and eight in community-based Mayo Clinic Health System hospitals in the Midwest. All told, our neurosurgeons perform approximately 11,000 surgical cases annually.
2. Get widespread buy-in.
An effort to create a data-driven department requires a significant investment of money and talent and must achieve buy-in from the departmental as well as institutional leadership. Therefore, the first step in developing useful data-reporting practices and dashboards is to get staff at all levels of the organization to recognize that creating them is essential to ensure the organization delivers high-quality, cost-effective care and remains competitive in the marketplace. We achieved the buy-in of our department’s staff by holding educational sessions at the department’s six locations where we discussed the need for obtaining such data and having user-friendly solutions.
3. Ensure adequate financial resources.
Prior to this project, Mayo Clinic had made significant investments in developing a clinical registry infrastructure within the neurosurgical specialty area. But it took a significant additional investment to transform this data into a dashboard designed to inform business operations decisions and contracts with payers. This required a total investment — including time, personnel, and active abstraction — in the range of $1.5 million over a five-year period.
4. Enumerate the variables of interest.
We envisioned that this neurosurgery practice database and dashboard would allow for clear, insightful visualization of operational indicators such as case volumes, outcomes, and relative value units (RVUs), a metric that’s used by Medicare, Medicaid, and commercial insurers for calculating reimbursement. The database captured variables such as postoperative readmissions, complications, returns to the operating room, mortality, length of hospital stay, and discharge disposition for all patients who undergo a neurosurgical procedure at Mayo Clinic. The registry would also report and visualize financial indicators such as total hospital costs and charges for all operative neurosurgical admissions.
The dashboard would become an important feedback mechanism for neurosurgery department chairs at each site that would facilitate multi-site discussions about performance and quality-improvement projects to enhance patient care. (The current version of our dashboard allows the user to visualize performance metrics by date, Mayo Clinic site, procedure category, and individual surgeon. The average cost associated with admissions for different surgical categories also can be viewed, which allows for cost comparisons across different sites.)
The idea was to create a kind of “balanced scorecard” as has been proposed by Robert Kaplan, David Norton, and others. Our team embraced it and recognized that we had the opportunity to create a nonintimidating, easy-to-use dashboard that would provide insights into quality and cost-effectiveness.
5. Assemble a project team of talented people from all essential areas.
We created a committee with expertise in clinical, administrative, financial, supply chain and IT areas as well as quality reporting and practice improvement. All six Mayo Clinic hospitals where complex neurosurgical procedures are performed were represented, as were data analysts, statisticians, and experts on the display of data. It was critical to have both data experts and data novices on the committee to ensure that the final product would be widely useable. Engaging these individuals required a personal commitment by the department chairs and their designated physician and administrative leads. The committee members were highly skilled specialists who did not necessarily work together or know each other’s needs and processes. To ensure that they worked well with each other, we engaged in a months-long effort to build bridges of understanding and common purpose between them.
6. Create a feedback loop to improve and enhance the dashboard.
Following optimization of data collection and storage mechanisms, along with accrual of data on nearly 20,000 cases, we began to identify a methodological paradigm for using this robust real-time data. This led to the design and development of a dashboard that would transform complex data into actionable information for quality-monitoring, operations decisions, and contracting with payers.
The framework for the dashboard outlined these items as critical requirements:
- Data that could be imported from multiple sources (neurosurgery registry, cost, and RVU information from a separate organizational platform) on an automated basis
- Data that summarized key metrics by site, surgeon, and procedure type and could be displayed visually
- Data that could be exported when a critical review of underlying information was required — for example when a specific patient number is needed to review the exact details of a surgical case or group of cases
As it was being developed, the dashboard was continuously reviewed by stakeholders involved — department and project leadership as well as financial analysts — to assess its operational capabilities, clinical appropriateness, and relevance to shaping the market strategy.
7. Include predictive analytics.
In addition to descriptive analytics that allow you to interpret historical data to better understand changes that have occurred, our team developed a predictive component tool that we termed “the neurosurgical risk calculator.” Based on real-time evidence from the Mayo Clinic practice, the calculator allows the neurosurgeon and patient to estimate the operative risk for a particular patient profile. This risk calculator provides another way for doctor and patient to discuss options, estimate the risks, including potential complications after surgery, and share the decision-making.
8. Use the data.
Hospitals collect data that often sits unutilized and unviewed. To avoid such a scenario, we created period reports for the neurosurgery department chairs at the six sites, solicited research proposals from the various faculty of the departments, and launched system-wide quality-improvement projects to address areas of relative underperformance. The department also utilized the data to gain competitive contracts with employers and insurers, including bundled care arrangements. Showing them the outcomes of their patients and how they compare to national benchmarks has caused payers to increase patient referrals to the department, resulting in increased volume. Data from this registry is also being used in shared decision-making with patients and to provide patients with expected outcomes after surgery.
After significant investment and commitment, we developed a database and dashboard that is accomplishing its goals of providing hard data on quality, cost, volumes, and outcomes. It has been helping us transform our practice.
Originally published at https://hbr.org on September 30, 2021.
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