Wanda Wilt, RN, BSN; Nicole Smith, BS, MSHI; Katie Grant, RN, BS; Jayme Nalley, RN, BSN; Jody Pinkerton, BS
Specialty Networks, Cleveland, Ohio
KEYWORDS:
Urologic neoplasms; prostatic neoplasms; urology; patient navigation; data science; critical pathways
Through data analysis and multiple interviews and insights, this study attempted to address the inconsistency in care for patients with prostate cancer who shared similar journey time points, demographics, and care center expertise. The Consistency of Care Project aimed to evaluate the impact of efforts to improve targeted metrics surrounding crucial clinical interventions of prostate-specific antigen monitoring, surveillance scanning, and pharmacologic interventions over a 9-month period. For comparison, 15 private urology practices of like size, patient population, and demographics were monitored. Ten of the practices benefitted from reviewed workflow training on the PPS Analytics data platform; access to a PPS Analytics Clinical Analyst, who supported education for identification of actionable patients; consistent data analysis; workflow support; and regular check-in meetings to monitor progress. The 5 control sites were monitored without additional, purposeful intervention. Outcomes support the hypothesis that inconsistency in care can begin to be addressed through focused workflows, strong navigation, and attention to key performance indicators. Attrition rate differences of 32% vs 6% improvements (reengaging patients for care who had no next appointment scheduled). On average, the experimental group increased the metastatic castration-sensitive prostate cancer diagnosis rate by 10%. However, the treatment rates measured a relative increase of 35% but an average of 11% absolute improvement at the supported sites vs 6% at the control sites. Patients with metastatic castration-resistant prostate cancer at the supported sites improved by 20%, compared with those in the control group, who improved by 4%. Care teams with strong workflows, supportive resources, and consistent care pathways—when combined with data analytics—can influence care and drive increased, measurable differences.
Emerging diagnostic and therapeutic advances are transforming the treatment landscape of advanced prostate cancer (PCa), providing hope to patients and health care professionals alike.1 Statistically, 1 in 8 American men will be diagnosed with PCa, which is the second-leading cause of cancer death and the most commonly diagnosed cancer among American men. An estimated 299 010 men will receive a PCa diagnosis in 2024. Despite innovations, however, considerable variability persists in the quality of care patients with PCa receive. Although many urology practice champions and leaders adopt protocols that align with researchproven outcomes, few possess adequate resources to monitor their initiatives. Therein lies an opportunity to use data to improve awareness of protocol adherence and insight into the process disruptions that lead to deviations from the standard of care.
A robust advanced PCa program prioritizes the crucial clinical interventions of prostate-specific antigen (PSA) monitoring, surveillance scanning, and pharmacologic interventions. In private-practice urology, many programs are using a multidisciplinary care team that includes lead health care professionals, navigators, in-office dispensing, support staff, and often a clinical analyst. The Consistency of Care Project aimed to evaluate the impact of deliberate efforts to improve targeted metrics for these interventions. Participating practices benefited from training on the PPS Analytics data platform, access to a PPS Analytics clinical analyst to assist with identifying actionable patients, and regular check-in meetings to monitor progress. Throughout the project, practices were encouraged to fine-tune their operational processes based on their renewed focus. The project aimed to determine whether these measures would lead to an improvement in advanced PCa metrics while identifying obstacles or any new mechanisms that directly contributed to progress.
Ten urology practices and 5 matched control practices of varying size and demographic location were randomly selected to participate. The project spanned 9 months (April-December 2021). Key performance indicators used to evaluate advanced PCa performance and their measurements included the following:
At the conclusion of the project, data were analyzed to determine whether the implemented interventions led to an improvement in key performance indicator metrics. The results were calculated as the relative percentage increase or decrease from the initial values unless otherwise stated.
Adherence to appointments is the foundation of patient care from which every other intervention extends. Despite the importance of adherence, noncompliance with follow-up appointments continues to be a pervasive risk. Using PPS Analytics, practices were able to identify all patients with PCa who had not scheduled a return appointment (Figure 1). Determining whether patients were truly falling through the cracks of care by missing appointments was an eye-opening care delivery process for the groups. Experienced, well-respected navigators and champion physicians agreed that “we didn’t know we had a patient attrition problem.” As awareness grew about the magnitude of this opportunity, the practices independently devised strategies to recover these patients. At the conclusion of the project, on average, the experimental group had decreased its patient attrition rates by an impressive 32% compared with the control group, which had decreased its patient attrition rates by 6%. In total, the experimental practices recovered more than 16 000 patients.
Figure 1. Key performance indicator 1: patient attrition
Accurately classifying patients with advanced PCa as having nmCRPC, mCSPC, or mCRPC is vital when determining a patient’s treatment course and options. Regular PSA testing and surveillance imaging are vital to promptly capture disease progression. Filters were created within PPS Analytics to identify patients who were overdue for PSA testing and surveillance imaging. Diagnosis rates were calculated by the portion of patients diagnosed with nmCRPC, mCSPC, or mCRPC among all active patients with PCa within the practice. On average, the experimental group increased its mCSPC diagnosis rate by 10%. Otherwise, neither the control group nor the experimental group noted any additional reportable improvements or declines. There was a consensus that this key performance indicator was difficult to quantify because of the impact of extraneous variables, but focus in this area contributed to increased awareness of practice-specific protocols for imaging and frequency of PSA monitoring.
A fundamental aspect of an advanced PCa program is educating patients on their available treatment options. Navigators used PPS Analytics to identify patients who appeared to be candidates for sipuleucel-T and oral oncolytics. Treatment rates were calculated by the portion of patients receiving practice-approved National Comprehensive Cancer Network–concordant PCa treatments for patients with nmCRPC, mCSPC, or mCRPC (Figure 2). On average, nmCRPC treatment rates in the experimental group increased by 10% compared with a 4% increase in the control group. For patients with mCSPC, the identification of patients on androgen-deprivation monotherapy was 1 of the greatest outcomes of this project. At the time of this project, awareness of this disease state and the inconsistency in treatment regimens has increased at conferences and in print. This project provided a designated platform for each participating practice to dive into each and every case. Both the experimental group and the control group improved by a relative percentage of 38%, but the experimental group saw an average of 11% absolute improvement compared with the control group, which improved by an absolute 6%. For patients with mCRPC, the experimental group improved by 20% compared with the control group, which improved by 4%.
Figure 2. Key performance indicator 3: metastatic castration-sensitive prostate cancer treatment rate
Figure 3. Key performance indicator 4: dispensing rate
The last evaluated key performance indicator was the in-office dispensing rate, which is the proportion of patients receiving oral oncolytics through the office’s dispensary compared with all documented patients on an oral oncolytic. It is advantageous to fill prescriptions at the office because the convenience reduces barriers to obtaining prescription medication. There were substantial practice-level variations in the results. On average, both the experimental group and the control group saw improvements in their in-office dispensing rates. The experimental group improved by 15% and saw 6% absolute improvement, whereas the control group saw a 23% relative improvement (1 of the 5 groups far outperformed the control group) and a 5% absolute improvement (Figure 3).
Participants quickly discovered that they first had to accept their baseline data, despite the figures being unexpected, and recognize that growth opportunities existed in areas they had previously considered strengths. Participants also unanimously agreed that patient navigators were the catalyst to success, with their extensive hours spent reengaging and scheduling patients lost to follow-up, identifying patients overdue for PSA testing and surveillance imaging, and facilitating initiation of advanced therapies such as sipuleucel-T and oral oncolytics.
Levels of support from administrators and practice leaders varied and seemed to have a direct impact on individual practice results. Top-performing practices dedicated additional resources to this initiative and took the opportunity to retrospectively identify workflow gaps. Common approaches that consistently delivered included dedicating employees to patient reengagement, retraining staff members on scheduling policies to ensure that each patient leaves with a return appointment, and reinforcing the importance of prompt advanced PCa referrals and other practice protocols that align with the standard of care. Practices that realized the most dramatic improvements embraced a culture where each staff member internalized a responsibility for the quality of care provided to patients.
Key insights for each of key performance indicator were as follows:
– No patient leaves the office without the next appointment scheduled.
– PPS Analytics can be used to produce a consistent workflow to identify any patient without a follow-up appointment.
– Staff must be educated on the importance of scheduling patient appointments, reporting cancellations, and having a process to reschedule patients.
– Monitoring and having a workflow that includes detailed analytics and complete population management ensure that every patient is offered the right test or treatment as early as possible.
– Practice-specific protocols serve as the guardrails of patient care, providing the guidelines for staff members to identify patients who may need additional testing or treatment.
– All prescriptions should be run through the practice dispensary. If the practice is unable to dispense, prescriptions can be forwarded to a specialty pharmacy.
– Working with the Specialty Networks in-office dispensing specialty team on a comprehensive prescription analysis provided support for and additional insights into patients who were being missed and were ultimately brought into the practice dispensary.
It is worth noting that 2 years after completion of this project, the participating groups continue to improve in each of the areas, and the treatment groups are performing an average of 20% better than the control groups. No doubt many influences are contributing to ongoing improvement, but the support, education, and provision of additional data for conviction were probably a catalyst to get practices started on a journey to improve patient identification, treatment, and in-office dispensing and decrease attrition rates.
Participating practices may have received the necessary tools to begin this project, but it was their creativity, drive, and—most importantly—their devotion to their patients that led to meaningful outcomes. As a result, permanent operational and workflow adaptations will have a lasting impact on patients’ lives. This initiative spanned only 9 months, but its impact (especially in lowering attrition, increasing dualtherapy treatment rates in the patients with mCSPC, and increasing the practices’ in-office dispensing rates) was measurable and significant. Given the inconsistency in care that can be addressed through focused workflows, strong navigation, and attention to key performance indicators, this study raised the question, “What else can we do to ensure that every patient is offered the right testing and therapy at the right time?”
Published: March 31, 2024.
Conflict of Interest Disclosures: The authors are part of the PPS Analytics clinical team that worked directly with the practices.
Funding/Support: No funding support was received for writing this article.
Author Contributions: All authors contributed equally to this article.
Data Availability Statement: PPS Analytics, a Specialty Networks Company.
Acknowledgments: A special thank you to the practices, physicians, administrators, and navigators who participated in this project. Their willingness to be transparent and share their insights will continue to improve PCa care for patients across the private practice urology space. A project like this is impossible without you. To Janssen Pharmaceutical, now known as J&J, and the dedicated Janssen Urology Marketing team, thank you for your sponsorship, passion, and unwavering support to every man, family, and health care professional in the PCa space.
Citation: Wilt W, Smith N, Grant K, Nalley J, Pinkerton J. Opportunities for care consistency in prostate cancer. Rev Urol. 2024;23(1):e21-e26.
Corresponding author: Wanda Wilt, RN, BSN, Executive VP of Provider Solutions, Specialty Networks, 600 Superior Ave, Ste 1500, Cleveland, OH 44114 (w.wilt@specialtynetworks.com)