Data Analytics in the Large Urology Practice: Patient Identification, Population Management, and Protocol Adherence

Practice Profile Data Analytics in the Large Urology Practice: Patient Identification, Population Management, and Protocol Adherence John J. Azzolina Chief Technology Officer, Precision Point Specialty Analytics, Independence, OH [Rev Urol. 2017;19(1)46-48 doi: 10.3909/riu1901PP] ® © 2017 MedReviews , LLC F or the better part of a decade, physicians and other care providers have been engaged in the process of transforming medicine through the use of Electronic Medical Record (EMR) systems. EMRs can assist in reducing prescribing errors, streamlining patient care coordination and reducing billing errors. Potential benefits notwithstanding, the current generation of EMR systems suffer from drawbacks that prevent physician practices from realizing the full benefit of an electronic recordkeeping system. EMRs are not adept at addressing the needs of patient populations that have specific disease states, particularly in the realm of specialty medicine. As large urology practices commit expertise and resources to specialized and complex disease states, such as advanced prostate cancer, bladder cancer, or overactive bladder, significant opportunity exists to improve management of these patient populations. To meet the demands of an increasingly challenging healthcare environment, new data analytics platforms have been developed to fill the gaps left by traditional EMRs. These platforms overlay the EMR system; extracting, compiling, and displaying meaningful 46 • Vol. 19 No. 1 • 2017 • Reviews in Urology data points that are otherwise lost within the EMR. Physicians and staff are then able to work with large populations of patients grouped by common clinical traits. The ability to track patients with similar clinical statuses creates efficiencies and allows practices to monitor and treat patients proactively versus reactively. For example, castrate-resistant prostate cancer (CRPC) patients can be consistently scheduled for bone scans to identify metastases, or metastatic castrate-resistant prostate cancer (mCRPC) patients can be routinely queried for the appearance of symptoms. Furthermore, data analytics can be leveraged to create care protocols and manage protocol adherence within the practice. Overall, these tools create opportunities for better patient care, improved staff efficiency, and superior financial practice performance. EMR Challenges EMR systems are sophisticated and are designed to fulfill a large number of diverse and, at times, conflicting requirements. Traditionally, EMR vendors have focused on delivering general purpose Data Analytics in the Large Urology Group Practice systems capable of use across multiple practice types, specialties, and disease states. Because of this focus on broad data capture, several gaps arise when it comes to being able to extract, analyze and report on the data collected. Most modern practices see patients with dozens of different disease states daily. Given the significant differences between disease states, it is extremely challenging for an EMR vendor to design and implement a system that can be general enough to collect all data for any given patient while at the same time be precise enough to collect discrete data related to a specific disease state. This lack of specific and custom data collection and reporting is a significant barrier to an EMR’s ability to deliver patient identification and population management features. Furthermore, the creation of care pathways and adherence protocols, which are also specific to a particular disease state, is not possible without precise, discrete data that relate directly to the care pathway. Data Analytics as a Solution The emerging field of data analytics has applied statistical methods and machine learning techniques to help end-users more easily manage and interact with ever larger amounts of information. In the healthcare space, analytical tools have been used with success on the financial side of the business. Analytics software can assist with revenue cycle management, service line profitability assessment, and provider performance analysis. Once applied directly to clinical data, data analytics platforms can provide deep insights into a patient population and enable providers to identify patients that may be missing out on opportunities for enhanced therapies and the best possible care. Furthermore, effective normalization and analysis of clinical data can allow practitioners to proactively monitor patients. Modern analytics platforms can collect discrete data points, freeform text, and images from multiple data sources. This disparate data can then be combined and normalized to create a single disease statespecific view for a patient. Freeform encounter notes, radiology reports, and test results can all be analyzed and parsed for important data points relative to a patient’s progression on a care pathway. Patients can then be grouped and analyzed based on these critical data points. An interaction between a clinician and a patient often generates data that do not fall neatly into discrete data categories. The oftenunpredictable nature of patientprovider conversations during a consult further complicates the task of collecting actionable data. In the context of advanced prostate cancer, this means that important data points for a patient, such as symptoms related to bone metastases, may be captured in a physician’s narrative notes but rarely documented as a discrete data point in the EMR. New data analytics tools offer more solutions for extracting this chart information. This comprehensive data set can then be used to group entire patient populations or to identify individual patients that might be candidates for monitoring, therapy, or inclusion into clinical trials. Effective utilization of a data analytics tool necessitates an operational end-user within a urology practice. This operational end-user may be an administrator, practice navigator, or nurse that has been empowered by practice leadership to execute specific agreed-upon processes that prevent patients from falling through the cracks. Physician leaders can establish these processes in areas of interest for patient populations that require closer monitoring or that might require evaluation for advanced therapies. An additional benefit for navigators is the ability to develop customized lists of patients that update continuously based on patient status. The automatic nature of these data analytics platforms has clear advantages over spreadsheet-based manual systems such as luteinizing hormone-releasing hormone logs. This consistent approach to patient management can allow urology practices to more predictably support established centers of excellence or service lines, such as an advanced prostate cancer clinic. Monitoring Protocol Adherence Implementing a data analytics solution within a practice opens new opportunities to enhance the overall quality of care by facilitating the creation and easy monitoring of care protocols. To start, practices can use historical data to benchmark what is being done currently for a given disease state. Testing and imaging frequency, combinatorial therapy utilization, and medication sequencing and timing can be measured to establish a current baseline. Then goals and guidelines can be created to move the practice towards more consistent and higher quality care. Periodically, providers can be evaluated for adherence to the new guidelines. These same processes can be used to evaluate EMR data for adherence to quality measures that are a part of new MIPS and MACRA payment programs. Complex workflows based on clinical data can also be developed to facilitate moving patients through care pathway from initial Vol. 19 No. 1 • 2017 • Reviews in Urology • 47 Data Analytics in the Large Urology Group Practice continued diagnosis to first line therapy to advanced treatments without allowing the patient to fall through the cracks. Because analytics provides visibility into clinical data such as symptom scores, medication utilization, or progression on therapy, workflows can be created that focus on the highest-priority patients first. Implementation of a data analytics platform provides practice leaders unprecedented visibility into how their practice treats patients along with a toolset that helps them achieve real change in terms of consistency of treatment and quality of care. Data Analytics in Action Maria Webster at Chesapeake Urology Associates in Maryland uses the PPS Analytics Platform (Independence, OH) to manage and monitor advanced prostate cancer (APC) patients. Maria says that the PPS Analytics Platform allows her to identify patients that would be candidates for advanced therapies and move them through to therapy much faster than was previously possible. Once a candidate has been identified, Maria reviews the patient chart and then messages the head of the practice’s APC program to confirm the patient’s candidacy. Once confirmed, Maria and her team reach out directly to the treating urologist to coordinate the new therapy. Other practices have developed different workflows based on their patient population and staffing models. The PPS Analysis Platform allows Maria to search for patients based on new PSA results, rises in PSA, androgen deprivation therapy status, CRPC status, and many other data points specifically relevant to prostate cancer. Using this search capacity, Maria can build lists of patients that nearly meet 48 • Vol. 19 No. 1 • 2017 • Reviews in Urology the criteria for an advanced therapy such as radium Ra 223 dichloride or sipuleucel-T and then closely monitor those patients so that they are given the proper therapy as soon as their clinical status changes and they meet the indications. Conclusions Today’s EMR systems are powerful tools for improving healthcare delivery and patient outcomes. However, EMRs currently lack important features that facilitate patient identification and population management on a disease state–specific basis. To fill this gap, powerful add-on analytics platforms are available to help practices extract the most utility from their EMR data. Utilizing these new analysis platforms, practices can deliver the correct care to a greater range of patients more quickly with less effort.