The collaboration will bring Multiview’s cloud-based ERP software to GPHA’s network of hospitals in a bid to boost financial management and interoperability.

The software integrates seamlessly with GPHA’s electronic health record (EHR) vendor, providing improved interoperability and streamlining operations. This partnership is also hoped to deliver better financial solutions to GPHA hospitals, with a focus on rural and critical access facilities.

“We are excited to offer Multiview’s ERP solutions to our clients to improve the efficiency of their back-office operations,” said Tana Sells, chief information officer of GPHA. “Our top priority is to provide the best solutions for our hospital clients, and we believe Multiview ERP will be able to support our clients so that they can spend more time caring for their patients and communities and less time on administration.”

Multiview ERP has a long history of delivering user-friendly financial applications to healthcare organizations. Currently, over 4 percent of US hospitals use Multiview’s solutions, including rural and community hospitals similar to those in GPHA’s network. The software’s scalability and dynamic reporting capabilities have a track record of helping healthcare organizations break down data silos, automate accounting processes and improve access to financial information.

Michael Johnson, president and CEO of Multiview, said:  “Both GPHA and Multiview share a dedication to support rural and critical access hospitals, and we are excited to bring our affordable, powerful solution to GPHA hospitals at a broader scale.”

Founded in 1950, GPHA is one of the oldest and largest not-for-profit healthcare management systems in the US. The organization manages, leases and affiliates with hospitals across Kansas and Nebraska, providing comprehensive services and expertise to support rural healthcare.

Last year, another healthcare solutions company, TruBridge announced a partnership with Multiview Financial Software, benefiting from Multiview’s ERP software. As a preferred financial management solution, with the ability to integrate TruBridge’s electronic health record (EHR), Multiview is offering enhanced interoperability.

What it means for ERP Insiders

Transforming daily operations for healthcare financial professionals

For healthcare financial professionals like controllers, CFOs and accounting managers, the partnership between Multiview Financial Software and Great Plains Health Alliance (GPHA) promises a significant transformation in day-to-day operations. By implementing Multiview’s cloud-based ERP software, GPHA’s network of rural and critical access hospitals gains advanced tools for financial management, streamlining complex workflows and enhancing interoperability with electronic health record (EHR) systems. This integration means less time reconciling fragmented data and more time on strategic financial planning. End-users can expect to see automated accounting processes, real-time financial insights and dynamic reporting capabilities tailored to the unique needs of rural healthcare facilities – making financial management more efficient and transparent.

The growing demand for interoperable ERP solutions in healthcare

The healthcare ERP market is experiencing rapid growth, driven by the increasing need for financial transparency and operational efficiency. As hospitals and healthcare organizations face rising regulatory demands and tighter budgets, solutions like Multiview’s become essential. Multiview is competing in a market that includes major players like Oracle NetSuite and SAP, which also offer ERP solutions tailored to healthcare. With over 4 percent of US hospitals already using Multiview, the vendor is carving a niche in rural and community healthcare. Partnerships like those with GPHA and TruBridge highlight a broader trend: healthcare organizations are prioritizing ERP systems that integrate seamlessly with EHRs, supporting data-driven decision-making and fostering interoperability. Analysts project the global healthcare ERP market to grow at a CAGR of 6-8 percent through 2030, signaling a robust demand for these solutions.

Criteria for evaluating healthcare ERP providers

When evaluating ERP providers, end-users should prioritize integration capabilities, scalability and user-friendliness. Seamless integration with existing EHR systems is critical to avoid new data silos. Scalability ensures the software can adapt to the evolving needs of healthcare organizations, particularly as they grow or encounter new regulatory challenges. User-friendliness, combined with robust training and support, ensures that financial teams can quickly adapt and leverage the software effectively. Furthermore, rural and critical access hospitals should seek solutions with a proven track record in their specific setting, ensuring that the ERP system aligns with their unique operational challenges. In the case of Multiview and GPHA, the partnership exemplifies a tailored approach, delivering a solution built for the nuanced demands of rural healthcare finance.

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The Clinical AI Agent helps improve patient-provider interactions by combining clinical intelligence with a multimodal voice user interface to automate and unify a wide range of clinical workflows. The Clinical AI Agent enhances physician productivity by capturing and enriching patient exchanges, improving documentation accuracy, and simplifying clinical decision-making through the power of AI.

For example, instead of spending time navigating through drop-down menus or scrolling through screens to find information, practitioners can access critical elements of a patient’s medical history before, during, and after an appointment simply by asking the Clinical AI Agent. Integrated with the Oracle Health’s electronic health record, the Oracle Health Clinical AI Agent is designed to provide accurate draft notes in multiple languages in minutes. It also proposes clinical follow-ups, such as lab tests, and referrals for the provider to review and approve, and synchronizes all the information back to patients’ individual medical records. The Clinical AI Agent can simultaneously extract relevant data from the patient notes to automate coding, improving accuracy and helping to ensure compliance. In addition, it generates condition-specific medication history and discharge summaries to deliver rapid insights for clinical decision-making.

“Oracle Health Clinical AI Agent exemplifies the ability of Oracle AI to overcome longstanding industry challenges,” said Seema Verma, executive vice president and general manager, Oracle Health and Life Sciences. “From reducing burnout to enhancing patient satisfaction and improving reimbursement processes, the Clinical AI Agent is changing the lives of practitioners and the patients they serve.”

As a cloud solution running on Oracle Cloud Infrastructure (OCI), users benefit from military-grade security and continuous innovation, such as the regular addition of new language capabilities. Users are already providing positive feedback on the solution.

“AtlantiCare was one of the first-named innovation partners for Oracle Health Clinical AI Agent, offering us a unique opportunity to provide valuable feedback and witness the continuous enhancements,” said Michael Charlton, President and CEO, AtlantiCare. “Our physicians have seen improvements in patient engagement and professional satisfaction, thanks to reduced manual documentation. By enhancing visit summaries, we ensure that both clinical and administrative teams are aligned, ultimately improving the patient experience. And adding new language capabilities is already having a positive impact on our Spanish-speaking physicians and patients. This collaboration is a key part of our Vision 2030 strategy, which reimagines healthcare delivery with a focus on patient and community wellness.”

On average, AtlantiCare providers are seeing a 41% reduction in total documentation time—saving them 66 minutes per day.

“The Oracle Health Clinical AI Agent feedback from our team has been overwhelmingly positive. Our physicians see how it can dramatically improve their quality of life,” said Scott Eshowsky, MD, chief medical information officer, Beacon Health System. “For me personally, it has been wonderful to be able to dedicate more time counseling patients about their diagnoses and treatments, as opposed to focusing so much energy on manual documentation.”

“Compared to the previous models of AI documentation I have used, Oracle Health Clinical AI Agent has been the most reliable and accurate,” said Dr. Patricia Notario, pediatrician, Billings Clinic. “I make far less corrections using Oracle. Most importantly, I have been increasingly confident in the Oracle platform because the notes are done almost immediately for my review. I love that now I can use it for Spanish-speaking families. It works just as well as it does in English!”

What this means for ERP insiders

Integrate Clinical AI Agent with Oracle apps to maximize results. To maximize value for medical providers, Oracle’s Clinical AI Agent should integrate with the following key Oracle Health applications:

• Oracle Health Electronic Health Record (EHR): This application serves as the central repository for patient medical records, so integrating the AI Agent facilitates seamless access to patient data, enabling the AI Agent to assist in clinical documentation and decision-making processes.
• Oracle Health Multum Drug Database: This application provides comprehensive drug information, including interactions and contraindications, so integrating the AI Agent enables accurate medication guidance and alerts during patient care.
• Oracle Health Bedside Medical Device Integration: This system connects medical devices to the EHR for real-time data capture, so integrating the AI Agent allows providers to monitor and analyze patient vitals, supporting timely clinical interventions.
• Oracle Health Remote Patient Monitoring: This application provides continuous monitoring of patients outside traditional clinical settings, so extended patient data can be fed to the AI Agent, enhancing chronic disease management and post-discharge care.
• Oracle Health Data Warehouse: The role of this warehouse is to aggregate large volumes of healthcare data for analysis, so integrating the AI Agent fuels advanced analytics, supporting population health management and predictive modeling.
• Oracle Health Unified Analytics and Reporting: These are tools for comprehensive data analysis and reporting, so they can enable the AI Agent to generate actionable insights and support evidence-based clinical decisions.

Healthcare industry must overcome obstacles to benefit fully from AI. Between 2019 and 2022, investors allocated approximately US$31.5 billion to healthcare AI technologies, underscoring a robust commitment to integrating AI solutions within the sector. Despite substantial investments, the healthcare sector faces challenges in widescale AI implementation, including regulatory hurdles, data privacy concerns, and the need for ethical guidelines to ensure responsible AI use. A 2024 McKinsey survey revealed that over 70% of healthcare organizations are pursuing or have already implemented generative AI capabilities, indicating a proactive approach toward AI integration. The evolving regulatory landscape and ethical considerations play a crucial role in AI adoption, with organizations needing to navigate compliance pressures and cybersecurity threats amid resource constraints.

Proactively address patient concerns regarding the role of AI in their care. AI systems require vast amounts of patient data, raising the risk of data breaches or unauthorized access. Providers should ensure robust data encryption and compliance with privacy regulations like GDPR or HIPAA and communicate clearly with patients how data is used and protected. If AI algorithms are trained on biased or incomplete datasets, they may perpetuate inequities in care. Physicians should be transparent with patients regarding how AI models are developed and validated, and should work with their teams to monitor systems to detect and mitigate algorithmic bias. Over-reliance on AI for diagnosis or treatment planning could lead to errors if systems are not adequately supervised by medical professionals. Healthcare providers need to maintain a “human-in-the-loop” approach and retain full accountability for clinical decisions, even when AI is involved. AI may identify patterns that are not clinically significant, leading to unnecessary tests or treatments. As such, providers must maintain critical oversight of AI-driven insights and employ balanced approaches that integrate AI recommendations with clinical context.

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As shown by a recent Process Optimization Report from Celonis, 63 percent of enterprise leaders say that sub-optimal processes are costing them time and reducing productivity, even though 83 percent see processes as “their greatest lever for value and the fastest lever for change.”

Some of these realizations are perhaps the reason behind the recent boom of process intelligence (PI), which contributes to organizations by taking data from sources such as ERPs and CRMs, and using process mining technology to turn that data into a moving digital twin of a business’ end-to-end processes. Using AI algorithms and specialized process improvement knowledge, PI then directs teams to the places where value is hiding in their processes.

As a global leader in process mining and process intelligence, Celonis is advancing this new frontier for the world’s biggest businesses to become more productive and agile. Recently, Celonis has embarked on a mission to expand its process intelligence expertise, bringing it to more users with some UK-based developments making for interesting case studies.

The United Kingdom is one of the biggest software markets globally, within which “the company is gaining footprint,” Rupal Karia, recently appointed UK GM of Celonis, tells us. “We’ve got some very successful customers and it’s a large portion of FTSE companies – 25 percent of the Fortune 500 globally,” he adds, with the company planning to add to its 150 employees in the UK.

With an ambition to cement its strengths in every industry without straying from the company’s core, Celonis can be seen investing in healthcare, banking and the public sector in the nation, with an ambition to broaden into central government accounts.

Delving into various cases within the UK’s National Health Service (NHS), Celonis has started work within five trusts in the country, with University Hospitals Coventry and Warwickshire NHS Trust (UHCW NHS Trust) being one of the first of these to benefit from the partnership.

In that particular trust lay a fundamental issue – “there was a really high number of people who did not show up for their appointments, or canceled last minute, which is a problem because you can’t reuse that appointment,” Karia says.

Using the process mining and intelligence approach, Celonis worked to delve into how and when updates to appointments are triggered to reach a better adoption rate.

“So just by looking at that particular issue and sending text messages had a huge improvement to the number of people who turned up. We suggested changing text messages from roughly four days and then again one day prior, to 14 and four days prior, which meant any canceled appointments were re-utilized, given the team had more time to fill them. So that was a really simple use case.”

With the NHS being a good example of a complex use case with a large amount of disparate information, Celonis dug into its processes to identify more key bottlenecks. For example, despite common assumptions that the lack of doctors and nurses in a particular trust was creating long delays, the team found that the bottleneck could not be down to medical staffing issues at all.

“It could be that patients weren’t taken up to the theatre soon enough or the room or surgical instruments weren’t sterilized and therefore the room wasn’t available,” Karia reveals.

This realization plays a key role in problem-solving and optimizing NHS resources because “even adding 20 more doctors, if the assigned room is unavailable – and these are some very early indications, but we will prove this quite quickly. [Basically] if we just fixed those figures and secured hospital porters [instead of stretching budgets even further] for more doctors, it will make all the difference,” Karia shares.

The team has identified that proving and fixing this problem has a huge potential for improvement in productivity, which also highlights that sometimes the need for more staff might not be the way to fix the root issue. 

He adds: “If you can disseminate all of that, really start to work out these links and you realize which system we get that information from – once you start putting out all these different [elements], you can see where the real bottleneck is.”

While demonstrating the practical application of PI, there is one common misconception that users have – that process intelligence would replace other platforms they are using. “They sometimes ask, ‘Which platform am I replacing and what’s the benefit?’ Actually we don’t see it like that, we see it like this: the benefit of process intelligence as a top layer over your current systems should make those more impactful and therefore enable for better ROI.”

As more users tap into the added visibility that process intelligence provides, they can witness the benefits of PI and how those systems work better, increasing understanding of where bottlenecks are. Drawing insights from these direct NHS examples helps demonstrate the advantages of applying process mining that a growing number of enterprises are utilizing to stay ahead of the competition.

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No one said it was going to be easy. When NHS England merged with NHS Digital earlier this year, the idea was to create “a closer link between the collection and analysis of data to help drive improvement to patient outcomes,” said the press release. Technology and more specifically patient data, was going to be at the heart of transformation. So when in May, a report revealed that 20 NHS trusts have been sharing patient details with Facebook without consent, via the site’s advertising measurement tool Meta Pixel, it surely undermined trust.

Understandably, NHS England is defensive when it comes to handling patient data. An NHS spokesperson told ERP Today in a prepared statement that “most people are comfortable with their patient data being used to improve their individual care, to improve the health of others and to plan and improve services. The NHS always remains in control of patient data and no third party can access or use it for their own purposes.”

In terms of the Meta Pixel incident, NHS England says that there are clear rules and processes in place to protect patient data, referring to a recent protection of patient data document. NHS trusts are responsible for ensuring they follow these rules but clearly this highlights the complexities of data management and privacy, and the fallibility of relying on guidance documents. Data literacy, or illiteracy surely comes into play here and only last year the Open Data Institute (ODI) warned the Government that its data literacy policies lacked consistency and direct application.

The problem with data illiteracy is that it leads to human error and avoidable data breaches. NHS England’s claim that it “always remains in control of patient data” cannot really be backed-up by what is happening in the real world. While a claim by the Russian ALPHV/BlackCat ransomware gang in July this year that it has stolen 7TB of data from Barts NHS Trust in London cannot necessarily be linked to human error, the data breaches keep coming.

In June, NHS England reported a data breach involving GP information following a cyber-attack concerning Capita, affecting 90 NHS organizations. Also in June, details of more than a million NHS patients were compromised following a ransomware attack at the University of Manchester. Insider threats (either malicious or errors due to lack of data literacy), weak passwords and unpatched security systems are the most common causes of breaches.

The point is, like any organization, the NHS has to juggle data availability and sharing across a wide range of systems while also trying to keep it safe and only used for what it is intended to be used. As it goes through a major digital transformation that can become increasingly complicated. While no one doubts the potential of sharing patient information, NHS England has to walk an unenviable tight rope.

“The NHS is sitting on a goldmine of data,” says Nigel Jones, co-founder, Privacy Compliance Hub. “Primary care records span 55 million people, and there are a further 23 million care records where patients received secondary or specialist care. The opportunity to use that data to research and improve patient monitoring, prevent disease and the worsening of long-term conditions and innovate new treatments is huge.”

But, admits Jones, it is also one that is “fraught with fears for privacy and fear of private sector involvement with the NHS.” Trust, he adds, “is at the heart of the problem.”

This, he says, comes in three forms – lack of trust in government to deliver when it comes to health (or to deliver without corruption/cronyism); lack of trust in technology companies to keep our data safe; and lack of trust in any private company motivated by profit, not to use our data for unwanted/unknown purposes.

Lack of skills

However, given the size of the transformation task, ensuring all houses are in order by 2024 (the supposed end date of the transformation) is going to be tricky, to say the least. Many of the issues are typical of large organizations. A House of Commons Health and Social Care committee report in June this year blamed legacy technology as a key factor, as well as the NHS’s inability to attract sufficient IT talent. Again, this smacks of a lack of in-house digital and data literacy, which could undermine longer-term plans for a smooth and secure digital operation.

“To achieve digital transformation, we need to build general digital literacy, expert digital skills and digital leadership in the health and social care workforce. This includes leaders across the sector,” said the report.

“There needs to be urgent action taken to carry out the recommendations within the report, but this can only be done if the correct skills are in place,” says Dame Barbara Hakin, chair of the Health Tech Alliance, and former deputy chief executive of NHS England. Hakin suggests that NHS England’s recent Workforce Plan may solve some skills issues although it remains to be seen whether the NHS could compete with the private sector, especially on IT. Although the report also suggests upskilling, this takes time.

Hakin remains optimistic. She says that the merger of NHS England and NHS Digital into one system has provided a huge opportunity for digital innovations to be adopted into NHS practices and ways of working.

“With attention directed to engaging and improving the digital skills of existing staff, and leveling the digital playing field for different regions, the digital transformation will culminate in a smoother running and more efficient NHS,” she adds.

Of course, this is the dream. The reality, for the moment at least, is skills shortages and these could continue to impact the speed of transformation, as well as service performance. Coupled with a transformation project that still has at least a year to run, this feels a little shaky, especially with so much patient data flying around.  So when can we start to look forward to improved interoperability and secure data sharing?

Alex Case, a senior director and public sector industry principal at Pegasystems, previously worked as a senior official at No.10 and the Cabinet Office, leading large government IT and transformation programs. He says that the considerations for investment in technology solutions are crucial as this sets the tone to transform patient experience and optimize healthcare provision.

“A unified platform that can better automate patient data, across all components of an Integrated Care Systems (ICS) structure,” says Case, “ensures the ability to place patients more effectively on the right pathway to get the right treatment, at the right time, applying a 1:1 focus, but in the wider context of total workload, backlog and prioritization.”

Any thoughts on prioritization?

“Often in government, organization and policy frameworks are greater blockers to digital transformation than the IT itself,” replies Case. “With that in mind the success of the NHS England and NHS Digital merger will be measured in how well it now transforms process and working practice, to tackle patient backlogs and increase administrative efficiency.”

Case talks about how intelligent automation could be used to manage the data, triage backlogs and prioritize urgent cases. He also talks about the potentials for low code no code citizen development, to “empower NHS administration teams to develop their own automated processes to overcome obstacles and any institutional inertia.”

It’s not a bad idea but again we go back to data and digital literacy issues and the need to upskill existing employees.

AI or intelligent automation makes so much more sense given the scale of NHS data. For Tina Woods, CEO, Business for Health and author of Live Longer with AI, it’s a must if the NHS is to truly see the cost and service efficiency benefits of its current technology upgrade. She talks about “streamlining” admin tasks including patient management, using algorithms to triage and optimize schedules.

“Current medical records are often disconnected and not shared across the system meaning that patients must repeat their histories at every appointment, which is frustrating and wastes valuable time in the consultation,” says Woods.

This is where transformation will have its public face, in its ability to improve patient experiences. Behind the scenes, it’s about standards, enabling interoperability and driving digital literacy. In terms of scale, cost and its relevance to the whole country, NHS England’s digital transformation of the NHS is perhaps the most important digital transformation in England. However, the sheer scale and budget of the NHS and its mass of personal patient data will always make it a target. While the relative success of NHS app has shown that people are prepared to share data, it is built on trust and trust is really what underpins this transformation.

The post Has NHS privacy faux pas set transformation and skills alarm bells ringing? appeared first on ERP Today.

Her challenge was not just to find people but to get the right vehicle with the right skill. Do we want a paramedic? Do we need an emergency care assistant? As the demand grows and fades in the next few hours, how will our needs in skills change? She needed to get that right time every time to dispatch an ambulance that would land out of the sky next to a patient in seven minutes. The massive spreadsheet combining all resourcing data across the service took 15 minutes to open that day.

Mags is not alone in this situation. As digitization progresses, large complex organizations – like any NHS trust- become overwhelmed by data arriving from all its corners. Elsewhere across the UK, NHS planners in different departments, whether resourcing, procurement or finance, are drowning in a sea of disparate data from different sources to make the right decisions.

For NHS to get the digital transformation right, taking control of data is essential. Most importantly, it’s not all a dream but a reality some NHS trusts are already living today. So, what can the stories of those who have already successfully undergone this process tell us?

The trials and tribulations of NHS trusts

One of these forward-looking organizations is South Central Ambulance Service (SCAS), which covers 35,000 square miles in Berkshire, Buckinghamshire, Oxfordshire and Hampshire. It employs four and a half thousand staff responding to 1.2 million emergency 999 calls and 1.3 million 111 calls yearly, plus doing more than 700,000 patient transport journeys. To make things more challenging, the target is to be with the most urgent patients within 420 seconds after the call.

However, delivering an effective emergency response demands more than racing to the scene. Trained people must be on hand to answer emergency calls when they arrive. Then, the right people and resources must be in the right place at the right time to ensure the best possible outcomes. To achieve the optimum balance between resource capacity and demand, SCAS must predict the number of daily emergency calls it will receive and use this data to allocate human resources with a detailed workforce plan. Although SCAS’s planning cycle kept services running, its manual, spreadsheet-based processes created additional costs and complexity. SCAS sought to replace manual planning with automated processes. That’s why the service sought to replace manual planning with automated processes.

For the Manchester University NHS Foundation Trust (MFT), one of the UK’s largest acute and community healthcare providers, the challenge was both similar and different. Formed in 2017 to provide a single hospital service across Manchester and Trafford, it includes health centers and ten hospitals like Royal Manchester Children’s Hospital, the busiest in the country. MFT has 30,000 staff and a turnover of just over £2.6 bn, dealing with 6,000 suppliers and 270,000 invoices yearly.

Edd Berry, Director of Financial Innovation at MFT, explains one of the challenges for an organization of this size and complexity: “We had one massive payroll spreadsheet – and you were lucky if it opened. It made just querying the data very time-consuming – a bit of a nightmare!”

Another behemoth of Edd’s life was annual financial planning, driven by the regulator and NHS England. It takes up huge amounts of time for finance teams in January-March. However, for the NHS, winter is the busiest time, too. Edd felt they were spending too much time on bureaucratic processes and trying to untangle and unify all the data for the annual reporting and planning.

He calculated that their management accountants typically spend 160,000 hours a year extracting data from their system, validating and cleaning it, performing simple transactions, reviewing it and preparing it for reporting. So, his ambition was to free up 25 percent, or 40,000, of those hours, so financial professionals could work more closely with doctors and nurses to ensure they receive the professional support they need.

Making data your ally

For many organizations within NHS and beyond, becoming more agile is all about freeing the data from its silos.

SCAS started its resource planning transformation by creating a data warehouse combining huge data volume across all the organization into one source of truth, enabling it to be transferred into the planning and forecasting model on the cloud. The model then processes billions of data points monthly to forecast how many ambulances with certain specialists on board will be needed. The data is displayed on dashboards that can be viewed on any device, including tablets.

Most importantly, it’s also updated every 15 minutes to accurately record the overtime shifts and sick leaves, offering everyone in the resource planning team a living and accurate tool.

For MFT, despite its size, the transition to smart financial planning was at breakneck speed. Within two and a half months after starting the process, it brought all the teams together and had a detailed working pay model for all their c. 30,000 staff, and at a level of detail they had never had before. As a result, MFT has been able to harmonize data and planning across the group, bringing together all the stakeholders and engaging them in creating a single, standardized process.

What’s done and what’s yet to come for NHS and beyond

Since SCAS started implementing a dynamic forecasting approach, the accuracy of forecasts improved by 1.7 percent, significantly helping the service have the right staff where and when needed. Moreover, every 0.1 percent improvement in forecasting generates around £70,000 in savings for an annual overall resource budget of £150m.

The next action point for ambulance services who already implemented smart forecasting is to work with hospitals to ensure swift and correct attendance to their ambulances. MFT is bridging this gap from its end, too. Now that they have completed the first phase of the annual plan project, they are looking at other areas of application, such as monthly pay reconciliation and improving forecasting. They have already built a forecast model and piloted it successfully with two of the largest hospitals in the group. Even during the initial pilot run, with staff new to the model, it took much less time than the previous manual process. “We’re looking to roll out the model trust-wide over the next two months and explore the potential of Anaplan’s AI capabilities to reduce the new process time further,” adds Edd.

Transforming data into a powerful ally in practice means creating a pool of data from all sources, building the planning models, and mining for insights to inform future operations. Many NHS trusts across the UK are already connecting their functions for data analysis, planning and forecasting. But ultimately, the whole system will need to combine all of its data to avoid bottlenecks and create a seamless experience for the people, patients and staff alike.

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