Key Takeaways from SuiteWorld 2023: AI, Automation, Analytics, and ...
Healthcare Data Management: Turning Insights Into Action Across a Dynamic Industry
Today’s healthcare industry is a data-driven locomotive. It feeds on information, using it to streamline operations, improve patient outcomes, and bring better care to individuals and populations alike. And make no mistake – as a healthcare organization, you don’t want to miss this train because it slows for no one.
Thankfully, you don’t have to as long as you identify and embrace the right solutions to propel your organization forward. So, on that more hopeful note, let’s look at some of the key drivers impacting the data, reporting, and analytics needs in healthcare to ensure you stay on the right track.
Ownership and Control Changes
The recent tsunami of venture capital and private equity investments has considerably changed the healthcare landscape. As you might guess, this influx is driving notable ownership and control changes across the industry which, in turn, are fueling significant changes in management styles between public and private sectors as well as for-profit and nonprofit healthcare organizations.
Long story short – healthcare leaders are navigating complex ownership transitions that encompass mountains of strategic and operational data. Collectively, this information impacts everything from financial and management reporting to electronic health records (EHRs) and other critical health information. Put another way, ownership changes like the ones we’re seeing from PE and VC investments usually include all of the data in a healthcare organization, not just financials.
That said, when you’re knee-deep in an ownership transition, your primary – but not exclusive – focus is likely on the financial and management side of the data spectrum. Which is totally understandable. And while we won’t take a deep dive today into the particulars of extracting the right data for the right use cases in instances like these – that’s what our comprehensive guide, The Reporting Automation Playbook for Private Equity Funds, is for – organizations going through ownership or control changes must understand just how critical data technology is for effective transitions in today’s healthcare landscape.
Simply put, efficient and impactful data management holds the key to informed decision-making and mitigating potential risks before, during, and after such ownership and control changes. Further, just like any industry, comprehensive data analysis allows healthcare entities to accurately appraise the fair market value of their assets, whether for M&A, investment, debt obligations, or a laundry list of other triggers. Along the way, such analysis also lets leadership monitor and manage financial risks connected to shifts in ownership structure or tax status.
To provide some context to these data needs, the healthcare sector has witnessed a staggering acceleration in private equity transactions in recent years, with annual average deal figures nearly tripling last decade, from $41.5 billion in 2010 to $119.9 billion in 2019. And that trend shows no signs of backtracking any time soon. Thus, data management will continue to be front-and-center during the continued onslaught of ownership and control changes in healthcare, providing even more benefits than what we just discussed:
Effective Data Governance for Smooth Transitions: Implementing robust data governance frameworks ensures data quality, integrity, and security throughout ownership changes for both structured and unstructured data sets. Ensuring data integrity enables accurate evaluation of assets and enhances decision-making processes.
Selecting Appropriate Governance Models: Data analysis plays a critical role in selecting suitable governance models that align with strategic goals. By leveraging these data insights, healthcare leaders can make informed decisions regarding corporate structure, board composition, and governance frameworks.
Assessing Financial Health during Ownership Transitions: Leveraging key performance indicators, financial metrics, and data-driven insights helps evaluate the impact of ownership changes on financial performance. Comprehensive data analysis – including critical activities like financial due diligence, working capital analysis, and quality of earnings assessments – supports well-informed decisions and ensures financial stability throughout transitions.
Navigating Change with Data-Driven Strategies: Data analysis assists with identifying potential challenges and mitigating risks associated with workforce restructuring, resource allocation, and cultural shifts. Strategic, data-driven decision-making enables smoother transitions during times of change.
Enabling Seamless Collaboration and Integration: Effective healthcare data management promotes seamless collaboration and information exchange between systems and entities through EHR interoperability and health information exchange initiatives – more on them in a bit. Further, robust data sharing and integration enhance operational efficiency, support strategic decision-making, and foster stakeholder collaboration.
Ultimately, ownership and control changes in the healthcare industry drive much – but not all – of the need for enhanced data management functionality across the sector. In this era of big data and advanced analytics, strong data governance practices, accurate financial evaluations, and data-driven change management are essential for successful transitions. And just operations, for that matter.
Expanding Services and Care Delivery
Healthcare isn’t just undergoing significant growth and transformation on the ownership side of the equation, though. The range of services and care delivery methods patients expect is equally as dynamic, where telehealth, retail clinics, home care, and holistic wellness are rapidly becoming the norm. Care delivery models are also diversifying through a growing focus on value-based care, accountable care organizations, and patient-centered medical homes.
Therefore, care providers need to adapt and flex to rapidly shifting patient needs and expectations, making data-centric technologies and infrastructure absolute priorities for healthcare organizations trying to evolve with the times, including:
- Interoperability Requirements: Data management systems must facilitate secure and timely data exchange across provider networks and public health agencies to ensure coordinated care delivery and improved patient outcomes.
- Comprehensive Electronic Health Records: Integrated cloud-based electronic medical record (EMR) systems enhance the accessibility and availability of comprehensive patient data for consistent care delivery.
- Real-time Data Analytics: Data-driven approaches and analytics drive actionable insights and informed, timely decision-making, not to mention optimal use of resources.
Aside from these high-level areas, data management also drives expanded services and care delivery in some specific ways as well:
- Optimizing Service Portfolios: Organizations can use data-driven insights to adapt to competitor offerings and pricing to inform their own strategic decisions on service portfolio optimization. By analyzing market dynamics and understanding the competitive landscape, healthcare organizations can identify opportunities to differentiate their services and care delivery, enhance the patient experience, and maximize their value proposition.
- Targeted Interventions: From genomics to social factors like income, education, transportation, and food, access to specific data sets plays a crucial role in helping targeted interventions to improve individual and population health. By analyzing community health trends, providers can help develop services that address unmet needs and directly benefit the local community. Likewise, by better understanding social determinants of health and addressing specific needs, healthcare organizations can drive better health outcomes and positively impact community wellness.
- Telehealth and Remote Patient Monitoring: Telehealth and remote patient monitoring technologies are already revolutionizing healthcare delivery, and the tech is still just getting started. They enable enhanced access to care and patient engagement, particularly for remote or underserved populations, while reducing healthcare costs and minimizing the impact on already overwhelming workflows and responsibilities for healthcare workers. And just like everything else in this list, it all starts with data.
- Strategic Facility Planning: If you build it, they will come. Unless it’s in the middle of nowhere or in a generally bad spot which, like it or not, means that fancy new facility you just built is nothing more than a black hole on your balance sheet. Patient demographic data is instrumental in determining optimal locations for new facilities or virtual care capabilities. Analyzing patient demographic trends and projected demand helps healthcare organizations strategically plan their facilities and services to effectively meet the needs of their target patient population.
Ultimately, investing in data-driven health IT infrastructure allows healthcare providers to expand their service lines as efficiently and effectively as possible. It lets organizations adapt to market demands, optimize care delivery, and improve patient outcomes. Without such investment, providers will inevitably find themselves staring an extinction event in the face at some point in the not-so-distant future.
Specialized Resources and Workforce Planning
Rising demand for specialized healthcare resources poses yet another existential threat to the industry. As the population ages and more individuals manage chronic illnesses, there's an increasing need for clinicians specializing in areas like oncology, geriatrics, and cardiology.
Unfortunately, this need comes at a time when the industry is already dealing with a critical shortage in essential roles like nursing, technologists, home health aides, and social workers. Therefore, accurately forecasting workforce supply and demand in all of these areas is now crucial for health systems.
Advanced data analytics and predictive modeling are vital for developing effective long-term workforce plans. By collecting and studying factors like community diagnosis and disease patterns, treatment innovations, and changing skill requirements, health systems can anticipate gaps in specialized resource availability.
Taking it a step further, workforce analytics also informs nuanced scenario planning and "what-if" analysis, letting health organizations identify and implement optimized resource planning strategies based on any number of variables. Obviously, this is a powerful ability for organizations as they try to balance outstanding care with increasingly limited resources.
Of course, financial sustainability and growth pose additional challenges in the healthcare sector. Much to leadership's chagrin, profit margins for healthcare providers have experienced a significant decline over the years, forcing the industry to perpetually tighten an already snug belt. And with technology, labor, pharmaceutical, and administration costs continuing to climb, the financial landscape will only get more complicated and challenging.
Thus, to navigate these challenges and promote improved financial health, healthcare finance leaders must embrace this brave new(ish) world of streamlined data management or risk extinction. The good news, however, is that aside from improved margins, data and information management also provide significantly enhanced financial visibility so leadership can better navigate the corporate ship through continuously choppy seas.
Specifically, centralizing and analyzing financial data allows healthcare organizations to improve financial visibility and transparency. Data-driven financial management systems can generate accurate, timely financial reporting that stakeholders – governing boards, investors, and community members, amongst others – both crave and expect. And don't forget about the ability to forecast nuanced financial projections, measure financial performance, and detect potential areas for improvement – all potential game-changers for healthcare providers.
Extending our insights on financial management, harnessing the power of data-driven financial analysis lets healthcare organizations make informed decisions on cost controls, service pricing, capital allocation, and investment priorities. Thus, by conducting comprehensive data analysis, organizations can identify trends, assess financial risks, and uncover strategies for optimizing financial performance, all abilities that would otherwise go unaddressed.
Practically speaking, utilizing advanced integration tools and cloud-based data repositories lets organizations proactively make rapid configuration changes to address new needs, from finance and labor to compliance and interoperability – and everything in between.
Regulatory Compliance and Risk Mitigation
Cyber security has become an absolute necessity. In today’s marketplace and business environment, safeguarding Protected Health Information (PHI) and Personally Identifiable Information (PII) is not negotiable at any cost. Therefore, it’s imperative for healthcare organizations to know where their data is and fully understand the sensitivity of that data. Without such understanding, safeguarding all of that critical information is impossible. And that’s not good.
Likewise, leadership shouldn’t sleep on every finance organization's greatest hits – the robust financial accounting, audit procedures, controls, and reporting mechanisms that keep everything on the straight and narrow. All these aspects of compliance and risk mitigation are critical to any healthcare enterprise's well-being and viability. And they all rely on effective data management as operational oxygen.
Adapting to Regulations
Taking a closer look at regulatory compliance, regulations in healthcare don't begin and end with everyone’s good friend, HIPAA, the Health Insurance Portability and Accountability Act. Far from it. In fact, adapting to the ever-changing regulatory landscape is a constant challenge in the healthcare industry. Organizations must remain agile and responsive to updated or new policies from an alphabet soup of entities – HHS, CMS, FDA, AHRQ, and ONC, to name a few.
However, shifting focuses around telehealth expansion, price transparency, interoperability, and value-based reimbursement often complicate compliance. As a result, health organizations must rely on proactive monitoring, robust data collection, analysis, and reporting capabilities to stay on the regulators' good side.
Allocating Resources for Regulatory Readiness
Given such challenges, devoting resources to ensure regulatory readiness for emerging data requirements is crucial. A proactive approach on this front helps organizations avoid substantial penalties and eliminates potential bottlenecks that may arise due to non-compliance. By investing in the right resources and technologies, healthcare organizations can adapt to regulatory changes efficiently.
Most importantly, adopting a data-centric approach and leveraging advanced technology solutions lets healthcare organizations remain vigilant and prepared to collect, aggregate, and report new data points. These are all essential components for healthcare compliance, operational efficiency, and delivering high-quality patient care in this data-driven environment.
Finally, to state the obvious, technological advancements are at the heart of everything we've spoken of today, propelling this data-driven revolution in the healthcare industry. Innovations such as AI, cloud-based apps, remote patient monitoring, genomic testing, wearables, and robotics all rely on gathering and analyzing vast volumes of data. Together, such advancements can significantly impact healthcare in distinct, critical ways:
Harnessing the Power of Artificial Intelligence and Machine Learning
Like many industries, AI and machine learning now offer transformative opportunities in healthcare. These technologies can enhance diagnostic accuracy, enable predictive analytics for disease management, and support personalized treatment plans. By leveraging vast sets of medical data and advanced algorithms, healthcare organizations can make more accurate and efficient clinical decisions which, ultimately, help inform business decisions as well.
Additionally, AI-driven automation and natural language processing systems can streamline administrative tasks, improve operational efficiency, and enhance the overall patient experience. And, once again, they all rely on accurate, relevant, timely data.
Enabling Interoperability for Seamless Data Exchange
Drilling down into a previously-mentioned topic, interoperability is critical in facilitating seamless data exchange between different healthcare systems and providers. By breaking down data silos and ensuring interoperability, healthcare organizations can enhance care coordination, improve patient safety, and optimize healthcare delivery.
However, successfully executing this requires the development of new interfaces, data governance policies, and exchange protocols. Unfortunately, organizations that rely on inflexible legacy systems or siloed data face challenges in adapting to these requirements. But here’s the good news – this is yet another area where advanced integration tools and cloud-based data repositories can save the day.
Ultimately, effective interoperability enables access to a patient's records and complete medical history, ensuring the efficient transfer of electronic health records and supporting interdisciplinary collaboration for better patient health outcomes. And that’s a noble endeavor if there ever was one.
Unlocking the Potential of Blockchain Technology
Blockchain technology has the potential to transform healthcare by enabling secure and transparent sharing of electronic medical records. It ensures data integrity, privacy, and patient consent management through decentralized and immutable record-keeping mechanisms. Additionally, blockchain can facilitate efficient claims processing and billing, reducing administrative burdens and enhancing data security in healthcare transactions.
However, no matter the technology – be it blockchain, data repositories, AI, or anything else – healthcare organizations must continuously evaluate their data infrastructure and analytics capacities. Because you can’t adopt the right tools unless you first understand your needs. For example, enhancing scalability through virtual visits is an admirable goal but requires real-time dashboards, IoT data from remote medical devices, and developing algorithms to predict utilization.
And this is where things get tricky – nearly any need you identify requiring data management solutions will rely on analytics architecture, skilled teams, and strategic resource allocation. In other words, you need experience and expertise. Thankfully, that's exactly what Embark's team brings to the fold, giving you access to best-in-class insights and boots-on-the-ground, practical experience. So, if you want to learn more about how data and information management solutions can benefit your healthcare organization, let's talk.