Featured, News, Secondary Care

Delivering Patient Flow Analytics for Healthcare Organisations by Orlando Agrippa, CEO, Draper & Dash

The NHS is facing ever-rising costs through ageing populations, increased demand whilst needing to adopt new technology in a time that requires significant change. At the same time budgets are constrained and those responsible for the systems that operate healthcare facilities are changing rapidly. Across the healthcare sector, data analytics is no longer a “nice to have” but a “must have” for addressing the rising challenges and changing environment. Analytics can be used to both design and implement transformation to improve patient outcomes and reduce overall costs leading to better returns on investment and quality patient care. Change however is complex and involves a myriad of stakeholders and partners, as well as business leaders that can embrace the new and exciting.

Analytics can make sure the complexities of change can be harnessed and mission-critical decisions can be made with trusted insights and confidence. From improving patient safety, to delivering greater financial stability through better cost management, efficiencies and improvements can in many cases be attributed to data analytics. In particular, patient flow analytics is addressing a specific need to drive operational excellence as well as clinical user adoption.

Delivering quality healthcare systems

Poor quality healthcare systems deliver poor results – for patients, staff and taxpayers. Good patient flow is central to the success of healthcare facilities and patient experience, clinical safety and reducing pressure on staff. It is also essential to the delivery of national emergency care access standards as an imperative. Where implemented effectively, and when driven by data analytics, well-led teams can adopt effective improvement techniques for real benefits to patient outcomes and staff satisfaction. In addressing patient flow, at a variety of units, such as mental health, primary care units, clinical decision units, acute medical unit’s, emergency departments, admissions, transfer and discharge and frailty can significantly address and improve;

  • A reduction in hospital crowding
  • Emergency departments (EDs) decongest
  • Mortality rate reduction
  • The right care by the right unit
  • Patient harm reduced for better patient safety
  • Pressure alleviated on staff
  • Data-informed teams

Implementing good practice in such units to realise these benefits has given many hospitals significant benefits. In addressing multi-units as a cumulative effort can have a major benefit for patient flow. The risks associated in not addressing these issues are well-known and often reported in the press. These can include;

  • EDs become crowded, chaotic and unsafe
  • Patient ‘outliers’ may not get the clinical care they need
  • Ambulatory care services and clinical decision units may fill up with patients waiting for ward admission
  • inpatients are required to move between wards to make room for newcomers
  • staff are overstretched and overall activities slow down as a result
  • clinical outcomes are measurably worse, particularly for frail older people
  • patients’ and carers’ time is wasted due to delays and slow care processes

The how, where, when and who

To be clear, flow is not about the what of clinical care decisions. Rather, the how, where, when and who of care provisioning. Who provides the services, or how services are accessed, when and where assessment and treatment is available, can have as significant an impact on the quality of care. The burgeoning use of flow to improve care has received increasing traction within healthcare, especially in for those wanting to address recurring issues such as waiting times. Awareness has been growing of the ideas, first tested in other industries, and results that organisations have generated by applying flow to their organisations for the leaders who want to venture into this new environment.

National policy has started to focus intently on flow too. Tight alignment between primary care, acute services and social care, and the need to understand and improve how patients flow through systems is steadily bubbling to the top of most people’s agendas. High profile examples of failures in some situations, with regards to timeliness and quality are good reminders of times when things have gone wrong. These are often well-documented and not welcomed by many firms.

Given the constrained budgetary situation, the challenge of meeting patient flow, safety and care objectives is becoming more difficult to deliver against. The NHS is typically slow to adopt such approaches, but with national governing agencies and regulations driving this forward, we can expect to see some changes in the future.

The Draper & Dash Approach

Draper & Dash (D&D) is a healthcare data, insight, analytics and improvement company. Its solutions drive actionable insights, powered by superior information assets, which are tuned to each client’s precise requirements. We give insights into the flow in key aspects of your system enabling you to model different strategies and assess which will have the most impact in delivering improvements in patient care, performance and resourcing.

We have worked with a number of trusts to understand their baseline bed usage and benchmark them against comparable other trusts through using bed capacity and demand models. Our robust quantitative analysis on existing patient flows, cancelled treatment and bed occupancy provides new insights to senior management and clinical teams. The simulation model we developed meant they could identify and address instances of suboptimal care, manage day-case patients efficiently, and plan for high demand. We trained internal teams to run the tool so that they can continue to use it to make better bed capacity decisions.

D&D’s predictive patient flow platform uses a number of advance data science and machine learning techniques to predict demand and patient flow for hospitals. For example, predicting Emergency Department (ED) demand; predictive algorithms are used to look ahead of demand. This is done by algorithms that measure the flow of daily or hourly information relating to patients. These provide healthcare firms real-time information of incredible value, driving better capacity and management of patient flow for better overall outcomes.