By Dr Melinda Rees, CEO, Psyomics

Spend enough time in the NHS and you stop flinching at the word “productivity”.

You hear it in every strategy document, every board meeting, every government announcement.

And almost every time, it means the same thing: do more with less.

It’s the wrong framing.

After 25 years working in and around clinical services – from NHS leadership to service delivery in the independent sector to where I am building technology that works with NHS mental health services – I’d argue it’s part of why progress has been so hard to achieve and sustain.

Productivity in healthcare shouldn’t mean squeezing more out of an already over stretched workforce.

It should mean something more precise: delivering greater value per pound by protecting and deploying finite clinical expertise intelligently.

That distinction sounds subtle. In practice, it changes everything about how you approach the problem.

The demand side of this equation isn’t going to get easier.

Multi-morbidity is rising. Mental health need is growing. Cases are more complex, and patient expectations – rightly – are higher.

The assumption that we can recruit our way out of this is understandable but wrong.

Training pipelines take years. Financial resources are finite. Even in an optimistic scenario, workforce expansion alone doesn’t close the gap.

So, the real question isn’t how do we get more clinicians. It’s whether we’re deploying the ones we have with maximum precision.

And honestly, in most services, the answer is no.

• Clinical time – the most valuable finite resource in the system – is routinely lost to things that have nothing to do with clinical decision-making.
• Administration.
• Repetitive documentation.
• Poor workflow.
• Systems that don’t share information across boundaries.
• Inconsistent and variable clinical decision-making.
• Referrals that shouldn’t have reached a specialist clinic in the first place.
• Reactive care models that wait for deterioration rather than anticipating it.
• Gathering baseline information that could have been collected earlier, more consistently, and without the clinician in the room.

Meanwhile, the waiting list grows.

This isn’t a motivation problem or a workforce culture problem. It’s a system design problem.

And it’s solvable – meaningfully – if we’re willing to rethink how technology fits into the picture.

The challenge with digital implementation in the NHS has rarely been the technology itself – it’s been layering new tools onto processes that were already under strain.

A new system that digitises an inefficient workflow is still an inefficient workflow.

Real productivity gains come when technology is used to redesign how work actually happens – not just record it.

In practice, that means four things.

First, automating the tasks that don’t require clinical expertise – structured data capture, digital triage, standardised assessment pathways.

Every minute saved on documentation is a minute returned to care. At scale, those minutes add up fast.

Second, bringing patients into the process earlier.

When a patient contributes structured, meaningful information before their first appointment, the clinician and patient have a great head start.

Better routing, smarter questions, faster and safer decisions, quicker access to the right treatment.

Third, monitoring caseloads intelligently.

Utilising tools that flag deterioration or signal when a care plan needs to change, rather than waiting for a crisis to trigger a review.

Finally fourth, making sure every appointment actually advances care. That sounds obvious.

In practice, without recorded structured outcome data, it’s surprisingly hard to know.

None of this requires drastic AI transformation or futuristic promises.

Some of the biggest gains come from making simple workflow tasks consistent and seamless – the kind of unglamorous operational improvement that doesn’t make headlines but compounds quietly across thousands of patient interactions and increases productivity.

A 1-2 per cent productivity gain per clinician sounds modest.

At NHS scale, across millions of appointments, it isn’t. It’s the difference between a system grinding and one with genuine headroom to breathe.

It’s the difference between your close relative being able to get an appointment when they genuinely need one or languishing on a waiting list with little hope.

I think about this a lot through the lens of mental health services specifically, where I’ve spent most of my career and where Psyomics works.

Mental health has historically been underfunded and under-prioritised – something that disproportionately affects women, both as patients and as the clinicians and carers holding those services together.

The pressure to do more with less lands hardest here. And the argument that productivity means working harder is, in this context, particularly damaging.

Burnout in mental health services isn’t a footnote. It’s a crisis within a crisis.

The better argument – the one I’d like to see shape NHS policy – is that productivity means precision.

Precision in how we route patients. Precision in how we use structured data to reduce variation and improve decisions. Precision in how we protect clinical time for the work that only a skilled clinician can do and loves to do.

That’s not a technology story, exactly. It’s a system design story, in which technology plays an enabling role.

The NHS doesn’t need to do more with less.

The goal isn’t harder-working, exhausted clinicians – it’s smarter-working, compassionate enabled clinicians, and patients who are seen sooner.

By Katrina Zalcmane, co-founder | partnerships and growth, Véa

The global corporate wellness market reached US$70.65 billion in 2024 and is projected to hit US$128 billion by 2033 – Europe leads the charge, capturing over 39.5 per cent of market share.

Meanwhile, femtech investment hit US$2.2 billion in 2024, representing 8.5 per cent of all digital health funding.

The message is clear: companies recognise that employee wellness matters and women’s health technology is finally getting serious investment.

So why are women still drowning?

In the UK, 91 per cent of adults report experiencing high or extreme stress levels – despite consumers spending an average of US$3,342 annually on wellness and self-care.

60 per cent of women in leadership positions report feeling constantly burned out, while 69 per cent of women feel emotionally drained after every workday.

Around 1 in 4 working women say they can’t manage workplace stress, with only 44 per cent confident their employer even has a burnout plan.

The numbers don’t add up. Billions flowing into wellness programmes. A femtech revolution promising personalised solutions.

And yet women ages 25-45 – the backbone of the modern workforce – are hitting crisis levels of exhaustion.

The problem isn’t a lack of investment – it’s what we’re investing in.

The Mismatch: What Companies Offer vs What Women Actually Need

Health risk assessments captured 21.2 per cent of the European corporate wellness market in 2024, while stress management programmes hold 13 per cent market share and continue expanding.

Companies are checking boxes: biometric screenings, mental health apps, flexible work, meditation subscriptions.

Yet these programmes consistently miss three critical factors:

1. Emotional data is invisible

Modern workplaces reward thinking, problem-solving and constant cognitive output.

What gets lost is the intelligence that comes from recognising early warning signals in the body – somatic indicators that burnout is building long before it becomes visible.

Women are taught to “think through” stress rather than listen to what their bodies are telling them. By the time burnout shows up in productivity metrics or sick days, the damage is done.

2. Hormonal rhythms are ignored

Corporate wellness assumes constant, linear productivity.

But women’s bodies don’t work that way. Menstrual cycles, perimenopause, fertility journeys – all create natural energy fluctuations that impact focus, stress response and cognitive performance.

Instead of working with these rhythms, most women fight against them, blaming themselves for “productivity dips” that are actually biological.

The result is chronic disconnection from their bodies and accelerated burnout.

3. Emotional labour stays uncounted

Women carry disproportionate loads of invisible work – managing team dynamics, mentoring, smoothing conflicts, holding space for others’ stress.

This labour never appears on performance reviews or workload assessments.

It accumulates beneath the surface until women hit a wall.

The Cost of Getting It Wrong

In the UK, mental health-related absences cost the economy approximately £21.6 billion annually, with employees taking 34 million sick days each year due to stress, depression and anxiety.

Employee burnout costs an average 1,000-person company US$5.04 million per year globally. Burned-out employees are 6 times more likely to leave, costing companies 50-200 per cent of salary in recruiting and training.

For women specifically, the crisis deepens.

Women new to leadership report 70 per cent burnout rates; for women of colour in senior positions, it reaches 77 per cent..

Nearly 40 per cent of women actively seeking new jobs cite burnout as the primary reason.

Replacing a mid- or senior-level woman costs up to 213 per cent of her annual salary.

We’re not just losing individual contributors but hemorrhaging the women leaders who hold institutional knowledge, mentor the next generation and drive diversity initiatives.

What Needs to Change

Instead of more generic wellness programs, we need to fundamentally rethink how we support women at work.

1. Shift from crisis response to prevention

Only 44 per cent of women feel confident their employer has a burnout plan – but by then, you’ve already lost.

Companies must teach women to recognise burnout signals in their bodies before a crisis hits. Somatic awareness catches exhaustion early, when intervention still works.

2. Design work around cyclical energy, not constant output

Women need organisational cultures that acknowledge hormonal rhythms as legitimate biological factors affecting performance.

This means training managers to understand energy fluctuations and designing workloads that account for them instead of just offering “flexible arrangements”.

3. Make invisible labour visible

Emotional labor must be quantified, acknowledged and redistributed.

This requires new frameworks for measuring contributions beyond traditional output metrics and structural changes preventing this work from defaulting to women.

4. Prioritise personalisation over one-size-fits-all

Workforce wellness now centres on personalisation powered by AI and data analytics.

A 27-year-old establishing her career has completely different needs than a 42-year-old navigating perimenopause while caring for ageing parents.

AI-driven platforms can deliver tailored support – virtual health assistants, personalised insights, telemedicine – making care more accessible for women balancing careers, family and wellness.

The Opportunity

Closing the women’s health gap could add at least $1 trillion annually to the global economy by 2040.

But unlocking that value requires interventions addressing burnout’s root causes, not just symptoms.

The market is already voting.

Virtual workplace wellness programmes saw substantial growth following the pandemic and Europe continues leading corporate wellness investment.

Companies in the UK and France are implementing AI-driven burnout assessments, hybrid wellness platforms and data-driven mental health monitoring.

Still, investment alone isn’t enough.

The question isn’t whether companies will spend on women’s wellness – they already are.

The question is whether they’ll invest in solutions that actually work: reconnecting women with somatic intelligence before burnout becomes visible, designing around hormonal rhythms rather than fighting them and making invisible labour visible so it can be redistributed.

The companies that do will win the talent war.

The ones that don’t will keep wondering why their best women keep leaving.

About Véa Workshops

Véa offers evidence-based corporate wellness workshops designed specifically for women professionals, addressing the root causes of burnout that traditional programs miss.

Grounded in neuroscience, psychology and somatic awareness, Véa workshops focus on prevention rather than crisis response – teaching women to recognise emotional data and somatic signals, work sustainably with hormonal rhythms and make invisible labor visible.

Available in formats from 45-minute executive sessions to half-day leadership offsites, these workshops support sustainable performance without asking women to step back from ambition.

Learn more at veajournal.app/workshops.

Healthcare CIOs have spoken – 38% of them rank EMR integration and optimization as their main capital investment priority over the next three years.

EMR systems represent a major financial commitment for healthcare organizations. The software costs swing dramatically based on practice size and requirements..

We’ll explore everything about EMR system costs here – from original implementation to ongoing maintenance. You’ll learn about common challenges and economic solutions to help you direct this investment successfully. Let’s dive in!

Understanding EMR Implementation Costs

EMR costs are like Russian nesting dolls – you keep finding more expenses tucked inside each layer. A clear picture of your investment needs a deep look at everything that affects your bottom line.

What Makes Up The Total Cost Of EMR?

EMR implementation costs go beyond just buying software. 

The budget planning needs to account for four main areas:

• Direct costs – Expenses directly tied to acquiring and setting up the system
• Indirect costs – Additional expenses indirectly related to implementation
• Staff-related costs – Expenditures for training team members
• Unexpected costs – Unforeseen expenses that emerge during implementation

Studies show that buying and installing an electronic health record system can cost between $15,000 USD and $70,000 USD per provider. A typical five-physician practice might spend around $162,000 USD on implementation, plus another $85,500 USD for first-year maintenance.

The pricing model makes a big difference to your bottom line. You’ll find options ranging from subscription-based models to pay-per-visit models. Some vendors offer perpetual licensing with one-time payments from $1,200 USD to over $500,000 USD.

Your hosting choice has a major impact on the overall EMR implementation cost. On-premise deployments usually come with higher upfront expenses, hardware, maintenance, IT staffing, and security upgrades add up quickly. 

Cloud-based systems, on the other hand, typically spread costs out through predictable monthly subscriptions, which can make budgeting easier for many organizations. 

Lifepoint Informatics helps healthcare teams evaluate these trade-offs early, so they can choose a deployment model that fits both operational needs and long-term cost planning.

Direct Vs Indirect Costs Explained

Direct costs are easy to spot and budget. These cover software licensing fees, customization expenses, and hardware costs. and implementation services.

Hardware needs change based on deployment choice. On-premise systems require servers. Cloud-based solutions cut hardware investments by using the vendor’s infrastructure.

Healthcare organizations often get caught off guard by indirect costs. 

These show up as:

1. Productivity drops during transition – Teams slow down while learning new systems
2. Maintenance and updates – Yearly costs run between $60,000 USD and $100,000 USD
3. Staff overtime during implementation – Often missed in original budgets
4. Opportunity costs – Clinical time spent on EMR instead of patient care

Why Costs Vary By Practice Size

Practice size creates big cost differences through economies of scale. A solo practitioner pays about three times more per provider than a 50-physician group pays for the same EMR system.

Research backs this up. Solo practices spend around $1,200 USD per user yearly, while larger practices pay just $685 USD per user for similar features. 

The math isn’t straight multiplication – a 10-physician practice doesn’t pay ten times a solo practitioner’s cost. Core infrastructure work stays the same, so implementation costs don’t double with twice the providers..

Support and maintenance typically cost 15-20% of licensing fees each year. This means larger practices face bigger total bills but smaller per-provider expenses.

Deployment Models and Their Cost Impact

Picking the right EMR deployment model is like deciding whether to buy or rent a house. Your choice will affect your finances both now and down the road.

Cloud-Based Vs On-Premise Systems

Cloud-based and on-premise EMR systems are different in two main ways: where your data lives and who takes care of it. Cloud-based EMRs run on remote servers you can access through the internet. On-premise systems live on local servers inside your facility.

These models create two very different financial pictures:

Initial Investment:

• Cloud-based EMR: You just need computers with internet access, which means lower upfront costs.
• On-premise EMR: The original investment is much higher. You’ll pay for servers, setup costs, and installation fees.

A study from the University of Michigan School of Dentistry showed that on-premise solutions cost $2 million more than cloud options over two years. Cloud solutions came with no hidden costs. On-premise systems, however, had unexpected expenses that made up 8% of total costs.

The way updates and security work is different, too. Cloud vendors handle all updates, security, and infrastructure management. This means you need fewer IT staff members. With on-premise systems, your practice has to manage everything. This often leads to higher staff costs.

Subscription Vs Perpetual Licensing

The way you pay for your EMR system will affect your budget now and in the future.

Perpetual licensing works like traditional software:

• You pay one big fee up front to use the software forever
• Yearly maintenance agreements take care of patches, upgrades and support
• Costs usually level out after the first year, mainly covering support and infrastructure
• This works best for organizations that have money available and want to own their software

Subscription models (usually part of cloud-based systems):

• Setup costs are lower because there’s no big initial payment
• You pay monthly or yearly fees based on how many users or providers you have
• The subscription includes updates, maintenance, and security
• Budget planning becomes easier with predictable expenses

People often say subscriptions cost more than buying the software after 3-4 years. In spite of that, this view often misses two things: the need to update software later and the inefficiency of running outdated systems.

Organizations should think about both their current budget limits and long-term financial plans when choosing between these options. Practices with limited cash find subscriptions are a great way to get started, even if the lifetime costs might be higher.

How Deployment Affects Long-Term Cost

The Total Cost of Ownership (TCO) helps practices learn about the complete financial effect of their EMR choices beyond just the price tag.

The University of Michigan study found that over two years, on-premise solutions cost more than cloud-based ones. One-time costs were 40.5% higher and ongoing costs were 20.5% higher.

Long-term costs are different for several reasons:

1. Scaling flexibility: Cloud systems let you add users easily without buying new hardware. On-premise scaling usually means buying more hardware.
2. Maintenance burden: On-premise systems need constant server maintenance, security updates, and often full-time IT staff. Cloud vendors include these services in your subscription.
3. Upgrade paths: Cloud vendors usually include regular updates in your subscription. On-premise systems often make you buy upgrades or new versions, which leads to surprise expenses.
4. EMR integration complexity: Connecting with other systems is usually easier with cloud solutions. This can save money as your technology needs grow.

Small and medium practices usually spend less over 5 years with cloud deployments. They save on equipment costs, and maintenance is simpler. Large hospitals that need custom features sometimes find that on-premise solutions cost about the same after they factor in depreciation and internal savings.

These long-term effects show why practices shouldn’t focus only on initial prices when they review their EMR options.

Hidden and Overlooked Expenses

EMR implementation costs go far beyond the bottom line. Your budget can balloon due to hidden costs that lurk beneath the surface. Healthcare organizations often face budget overruns and financial strain because they miss these overlooked expenses.

Training And Onboarding Costs

Many practices underestimate the investment needed for training. The cost ranges between $1,000 USD and $5,000 USD per provider or staff member. Larger practices might need to spend tens of thousands on complete training programs.

Several factors push these costs higher:

• Development of training materials and programs
• Staff time spent in training sessions
• External consultants’ fees
• Regular refresher training after implementation

A typical five-physician practice’s training expenses can reach $20,000 USD or more. The simple EMR setup needs $5,000-$20,000 USD for complete training. Budget EMR systems often lack detailed training resources. This creates inefficiencies and errors that cost more as time goes on.

Paid EMR systems come with better onboarding. They include hands-on instruction and setup help, but cost more – usually $1,000 USD to $10,000 USD for implementation and training.

Productivity Loss During Transition

The highest hidden cost comes from reduced productivity as staff learn new systems. Data shows EMR implementation cuts practice productivity by about 18 patients per physician per quarter – roughly 108 patients lost quarterly.

Each practice experiences different productivity effects. Some bounce back quickly, while others struggle with efficiency losses long after implementation.

Money loss goes beyond seeing fewer patients. The staff needs time to learn the system and works slower initially. Senior staff members train newcomers, which creates a double productivity drop.

These steps help minimize the impact:

1. Schedule fewer appointments during the go-live phase
2. Budget for lower clinic productivity early on
3. Roll out the system in phases when possible
4. See more patients before implementation to balance reduced access during transition

Customization and integration fees

Standard EMR solutions rarely work perfectly without changes. Customization costs range from $2,000 USD to $10,000 USD based on complexity. Complex customizations can reach $5,000 USD to $20,000 USD.

Third-party system integration (EMR Integration) adds more expense. Each connection to labs, pharmacies, or billing systems costs about $1,000 USD to $5,000 USD. Healthcare organizations with complex needs face much higher expenses.

The right amount of EMR customization matters. Too few changes limit usefulness, while too many create problems and raise costs. Starting with needed customizations and adding more later works best for many practices.

Support And Maintenance Charges

Support becomes an ongoing expense after implementation. Annual maintenance and support fees range from $10,000 USD to $30,000 USD. Larger practices might pay $10,000 USD to $100,000 USD annually.

These fees cover:

• Software updates and security patches
• Technical support for troubleshooting
• System optimization and performance monitoring

First-year support costs often rise as staff learns the system. The expenses level out later but remain a regular budget item. These fees usually run about 15-20% of the original implementation cost each year.

Cutting corners on support backfires. Poor support leads to more downtime, slower fixes, and risks to patient care. Vendors offer different support levels – premium tiers reduce downtime, while budget options might leave doctors waiting days for help.

Conclusion

Healthcare organizations of all sizes must commit substantial funds to implement EMR systems. The costs can vary based on practice size, deployment models, and vendor selection..

Software and hardware costs are just the start. Many organizations get caught off guard by hidden expenses like staff training, productivity dips, and data migration. These indirect costs can actually exceed the direct expenses when not predicted properly.

The way you deploy your system will affect your long-term finances. Cloud-based systems need less money upfront but come with higher monthly fees. Large organizations might find on-premise solutions more cost-effective over time, despite the hefty initial investment.

The difference between success and budget nightmares lies in proper planning. A realistic budget should factor in total ownership costs, including maintenance, support, and unexpected issues. Smart organizations keep 20-30% extra funds ready to handle inevitable challenges.

Note that picking an EMR system isn’t just about comparing prices. The right system needs to line up with your practice’s workflow, specialty requirements, and growth plans. A proper EMR integration with your existing tech setup will prevent countless problems later.

Staff resistance and data migration complexities are common hurdles, but good planning helps overcome them. Organizations succeed when they assess vendors carefully, ask direct questions about pricing, and get their teams ready.

EMR implementation might look daunting, but its benefits make the investment worthwhile. This detailed guide gives you the knowledge to budget wisely, dodge common mistakes, and pick the right system that fits your healthcare organization’s needs.