How can you optimize the patient experience and revenue cycle simultaneously?

Optimizing the patient experience and revenue cycle simultaneously can be achieved through various strategies. One practical approach is streamlining the patient registration process, ensuring patients receive clear instructions and guidance. This can reduce wait times and improve patient satisfaction while ensuring all necessary information is collected for billing purposes. Additionally, offering multiple payment options and providing patients with clear and transparent billing statements can increase revenue while improving the patient experience. Finally, providing ongoing communication and support to patients throughout the revenue cycle can help to build trust and ensure that any issues are addressed promptly and effectively.

You can use AI solutions for the registration process - it is the only solution that ensures one hundred percent of phone calls answered!

Key here is to reflect by digital solutions patient treatment pathway. Example from RIS / PACS solution where you can have e-referral, patient doing on-line booking for the nearest radiology clinic + provide consent + get all instructions how to prepare, there is on-line consultancy available if there are some question, you have reminder & cancellation system, diagnostic results are digitally stored and send for doctor review, diagnosis is available for patient by portal and can be shared with other doctors, doctor provide online consultancy and can send e-referral if needed without visiting the clinic, all images and patient documentation are stored and available for other clinic / doctors consultancy, we can have AI implemented as well

By leveraging Natural Language Processing - a specialized branch of AI focused on interpreting and manipulating human-generated spoken or written data. NLP can streamline intake and enrollment in. I see the data everyday, Intake and Enrollment is a huge bottleneck for providers. I am working on building a solution using NLP to meet this exact need for nonprofit Health and Human Service organizations.

Under ICD-10 detailed document of signs and symptoms plus laterality and specificity equate to better reimbursement. MSN's coding and physician educational processes strive to arm radiologists with the information they need to take their documentation to the most appropriate level of reimbursement. Requirements change annually for both MIPS and also many radiological studies. Radiologists need at least annual education to keep pace with the evolving requirements.

AI's impact on Health Outcomes and addressing Social Determinants of Health is profound. By analyzing extensive healthcare data, AI can identify patterns and risk factors that might not be evident through manual analysis. This capability allows for the development of targeted interventions and personalized care plans, significantly improving patient outcomes.

Proper digital registries allowing understanding of specific patient population in the context of diseases characteristics, screening programs execution, identify trends in drug use and how treatments are being adopted, showing current demand in all hospital departments and trend over time for better staff planning, helping to understand how treatments are being used and the associated drug stock and cost implications, allowing patient pathway re-designs with appropriate data, allowing cross hospital and country collaboration (academic, consultancy, clinical trials, other), many others

AI can help in identifying and addressing social determinants of health, such as economic stability, education access, neighborhood and built environment, healthcare access, and social and community context. By analyzing data on these factors, AI can aid in devising strategies to address these determinants, thereby improving overall health outcomes and reducing disparities. This approach aligns with the broader goals of enhancing clinical documentation and leveraging technology to foster a more equitable and effective healthcare system.

Establish a culture of ongoing quality improvement where feedback from patients and staff is regularly sought and used to make iterative changes to processes and policies.

PLICS (Patient Level Information and Costing System) are very good example of digital solutions allowing benchmarking between hospitals and treatment standards, patient pathways and cost optimization.

There are system monitoring patient satisfaction like in UK where each service provider, doctor or medical staff can get patient feedback what they like, what should be improved.

Align the healthcare delivery model around the patient’s needs and convenience, which can lead to better health outcomes and patient loyalty. Ensure patients are well-informed about their care, costs, and billing processes. Transparent communication can enhance patient satisfaction and reduce confusion or disputes over billing.

Consider "Artificial Intelligence" - Machine Learning A Path to Efficiency and Improved Health and Social Determinates of Health Outcomes. More Accurate Data - AI-driven clinical documentation reduces errors and denials, ensuring accurate billing and preventing revenue loss. Quicker Enrollments - Streamlining patient enrollment with AI minimizes administrative overhead, leading to faster care access and potential cost reductions in long-term treatments. Improved Health and Social Determinates of Health Outcomes Management - AI’s deep data analysis identifies at-risk populations, enabling tailored interventions for better health outcomes, thus reducing emergency care costs. Connect with me! Let's help improve the human condition!

Take only the highest quartile of paying patients in the service area you cover. Keep the facility only large enough to meet the demand from that tranche of patients. Slightly overhire and overpay to get consistent staffing levels.