Here we explore the finalists in the HTN Awards 2023 category of ‘Best use of Data’.
Priory
Overview: Priory introduced Mulesoft AnyPoint platform 18 months ago to connect and automate clinical data across multiple systems securely. Mulesoft Anypoint is a middleware software that allows information to be populated across multiple systems simultaneously on one entry.
Why? The software enables Priory to leverage FHIR-compatible APIs with “out of the box” assets, converters and libraries to facilitate interoperability between legacy healthcare systems. This makes it easier to drive standardisation across healthcare data exchange, and to provide information to clinicians from a wide variety of devices including computers, mobile phones, and tablets.
What happened? Since adopting Mulesoft, Priory have automatically created 43,500 incidents from their incident system to their patient record- saving clinicians around 3,600 hours of time and allowing Priory to respond to incidents quickly and mitigate risk. So far, it has enabled them to integrate rostering, procurement, patient administration, risk management and e-prescribing systems.
Looking ahead. As the APIs provided are secure and reusable, the company hopes to scale and deliver new integrations within three months and have already reused the APIs they have previously built.
NHS West Yorkshire ICB, Leeds City Council, North of England Commissioning Service and NHS England
Overview: The Leeds Data Model (LDM) links GP data with other NHS data and is currently in use across various ICBs and a range of partner organisations. The new data addition into the Leeds Data Model provides system visibility and allows the ICB to track patient journeys from the hospital back into independent living.
Why? The addition of risk factors into the LDM gives users the ability to identify wider determinants that will allow them to predict future impacts, providing huge potential to use data and insights to ensure the best care.
What happened? All nine population boards in the city routinely use the Leeds Data Track Model to track progress across their segments, allowing them to deliver evidence-based prioritised actions. At operational level, they have implemented patient tracking and alerting so that all practitioners and professionals across the range of provider organisations have direct access to near real time information about their patients.
Looking ahead. The organisation commented on their next steps, stating: “One of the next considerations is how we open up the Leeds Data Model for health and care research and innovation – we are working with the Leeds Academic Health Partnership (LAPH) and academic institutions across the city to consider how we harness the opportunity as we seek to understand the next steps.”
NHS Shared Business Services and Medway NHS Foundation Trust
Overview: NHS SBS worked with Medway NHS Foundation Trust to develop an analytics solution capable of predicting those at risk of leaving so the trust can implement strategies to reduce employee turnover and impact positively on patient care.
Why? Medway NHS Foundation Trust has over 1,200 registered nurses. But with an unplanned nursing staff turnover of 14 percent, and rising demand for clinical services, retention was critical. With limited insight from existing exit interviews at Medway, understanding who was at risk of leaving and why, was a priority. Knowing which positions and areas were most at risk of people leaving could help reduce churn and impact positively on staff and patients.
What happened? NHS SBS’s solution offered an opportunity to use existing data to help Medway understand the risk factors for people who may be thinking of leaving. Data from the trust’s ESR was combined with insight from staff surveys and eRoster systems, pseudonymised and analysed by NHS SBS’s workforce analytics system. NHS SBS’s predictive model pinpointed the roles most at risk of leaving, enabling it and Medway to start work on developing individual interventions to reduce staff churn.
Looking ahead. As the benefits to Medway can be replicated at other NHS trusts, the potential for NHS SBS’s workforce analysis solution is “immense and wide-ranging.” NHS SBS and Medway are currently working together to develop further interventions.
Cambridge and Peterborough NHS Foundation Trust
Overview: Cambridge and Peterborough NHS FT in partnership with Health.io have piloted Minuteful for Wound (MfW), a solution of digital wound registry, providing caseload oversight for patients living with chronic wounds. Using AI and machine learning to support clinicians, MfW calculates consistent wound measurements, simplifies quality documentation with evidence based clinical assessment flows, and provides a remote monitoring caseload review platform.
Why? Prior to piloting MfW, CPFT had no solution available other than resource intensive clinical audit to ensure consistency, quality or continuity of wound care. Real time and robust oversight of the caseload that did not involve manual audit, was needed to facilitate timely and effective operational and clinical decision making. The trust needed the ability to quickly identify ritualistic practice, treatment and education gaps to helps them reduce patient safety incidents and proactively optimise deteriorating and static wounds.
What happened? CPFT wished to provide evidence to purchase 12 wound express pumps; traditionally this would have required a manual trawl of current records which is extremely time consuming. The MfW web-based portal – a visualisation tool to support reviewing a wound caseload – enabled a quick search for a nine-week time period for all of the patients seen by community nurses with a venous leg ulcer (125 patients). They were able to apply filters in MfW to identify all the patients whose ulcers were deteriorating or static; identifying 86 patients possibly suitable for the device in one area. Annual financial savings are anticipated at around £309,448 in targeted treatment optimisation.
Looking ahead. The trust will continue to gather data on the implementation of the MfW software to inform future developments and drive transformation across other organisations.
