Patient flow
The movement of patients through a medical centre needs to be well managed or it can result in long waiting times, increased length of stay, and adverse health outcomes. The Covid-19 pandemic highlights the challenge as hospital networks experience a simultaneous surge in demand and a reduction in volumes of elective surgeries. Getting patients to the best place or unit at the right time for their condition across all current and incoming patients is no easy task.
Fortunately, as advanced, targeted solutions become increasingly affordable and accessible, healthcare providers have the opportunity to rethink their strategies.
Our research finds that the use of intelligent operations allows healthcare providers to refine back-office processes and activities, make the customer experience frictionless and increase profitability and customer retention while leveraging human resources more effectively. The move to intelligent operations is possible through applied intelligence – the combination of data with the power of automation, analytics and artificial intelligence (AI) at scale. This way, healthcare providers can rapidly achieve efficiencies and next-level performance.
In practice, this means claims management will be more streamlined. A digital claims-monitoring tool can identify claims stranded with medical aid schemes, provide a timely alert, raise late payment charges, and automate follow-ups. An AI system can also make a prior authorisation for a procedure more efficient by validating the information associated with the request and thus freeing human resources to focus on higher-value tasks. Lastly, AI tools can simplify clinical coding, reduce claim denials and under-recovery of revenue by adding AI and automation to clinical document review.
At the core of this success is the effective use of data. With accurate data on length of stay, occupancy, patient experience, and financial risk, hospitals can enhance the prediction of patient flow to optimise hospital resources. Hospitals can improve operational planning and execution; enhance patient, doctor and staff experiences; and improve clinical outcomes.
Africa’s healthcare providers need to solve for an outcome – they have to work with what they have now while preparing for what they want to do next.
Immediate steps to take include:
After this, it is important to implement the right type of automation. If the work is transactional and rules-based, it is well-suited to robotic process automation (RPA), and if it is knowledge-based, then it’s a job for AI. Next, they can find and make use of AI and analytics solutions that can be delivered cost-effectively via the cloud. Ultimately providers can refocus and upskill revenue cycle resources.
In dealing with overcrowding or improving patient flow, healthcare providers should explore the data on key metrics across multiple dimensions. For example, monitoring data on admissions and excess days per unit, physician and service line, can help with understanding the opportunity cost of inefficiencies. Next, they should create data-centric operations where staff embrace the power of data and use it effectively to work smarter. This in turn leads to the start of a culture shift where staff can be educated, upskilled and exposed to technology and data tools to remove fear. It is important to focus on areas for ongoing analytics such as the optimisation of bed allocation, or occupancy and discharge prediction to build agile operations.
Hospitals should then create a roadmap to becoming connected and cognitive. Leading hospitals are connecting the visibility of surgical flow, patient flow and staffing to provide better patient care and a better experience for staff and physicians.
In conclusion, healthcare providers need to find alternative, cost-effective ways of providing healthcare services, and the future of healthcare work is being driven by technological advances that improve sustainable care. Transforming processes to intelligent operations through Applied Intelligence helps healthcare workers direct their focus on patient care rather than administrative tasks, thus improve hospital efficiency. Using healthcare analytics and exploring the use of data, can help with better revenue cycle management and improve patient flow. By handing over some tasks to machines, healthcare providers can optimise human performance and free up healthcare workers to do more important work in personal patient care.
