Healthcare Providers

To understand fully the wide spectrum of initiatives needed and being pursued by today’s provider organizations, first consider the basic, raw data that must be collected to meet the immediate need of any one of several quality, compliance or pay-for-performance program. This seemingly simple first step quickly creates the need for enhanced processes, new technology platforms, new reporting and analysis tools, and staffing and other resource deployments that are necessary to drive the needed improvements and metrics. Organizations are recognizing that additional work will be required beyond these fundamental platforms and change programs to truly become a data-driven organization, with evidence-based decision support and decision assist as the transforming performance management environment. Leading healthcare executives (and some of our most successful clients) understand that the competitive advantage goes not to the organization with parity-reaching technology or tools, but to those who commit to an enterprise platform and orientation to analytics, routinely and efficiently converting data to information, to knowledge and to action, and impacting the myriad clinical, operational and financial missions and objectives of the organization.

Challenges

The challenges that healthcare providers currently face are high in both number and complexity. No single issue has dominated the headlines more than the need for integrated clinical information, and thus the calls for “EMRs” and other interoperating systems. Independent of where clinical care is delivered or when it is consumed, patients must be able to provide their clinicians with the most comprehensive collection of both historical and up-to-date health information to enable them to make the most informed decisions. The current inability of most provider organizations to combine and integrate the diverse information collected across the continuum of care settings is no longer tolerable and, in the worst-case scenarios, a fundamental impediment to the delivery of effective care.

Disparate data is the result of transaction-based application systems implemented to meet specific, narrowly focused needs like materials management (e.g. McKesson PMM, Lawson), registration/admitting (e.g. MediPac, McKesson), OR management (e.g. Picis, Cerner), EMR (e.g. Centricity, Epic, Allscripts, Eclipsys) or revenue cycle management (e.g. HBOC, QuadraMed Financials), that are incapable of sharing information with other systems. This results in an information landscape plagued with inefficiency, redundancy, and inconsistency that frustrates the best intentions of the organization to transform or improve the effectiveness of its primary constituencies. It’s no wonder why we often hear, “It takes too long for me to get the information I need; by the time I do get it, it’s too late.” Healthcare providers must also find ways to manage the huge volume of information that comes with the endless stream of special projects, improvement initiatives, and revised rules and regulations that must be understood and implemented by clinicians and staff without incurring the various forms of resistance, pushback, and just plain “information fatigue” that results.

Healthcare is on the brink of IT-driven transformative change that several other industries have worked through over the past several decades, with operational data stores and data warehousing creating integrated analytic and management environments unheard of years earlier. At the same time, technological innovations continue being researched and implemented in such diverse settings as text analytics, automated dictation, robotics, and advances in surgical implants and hardware devices. CEOs, CIOs, CTOs and CMIOs responsible for steering both large and small providers into the information technological age of healthcare, must collaborate to devise solutions that address the competing challenges of accessing and absorbing diverse sources of critical information, arriving and available in differing granularities and dimensionalities, and conflicting dynamics, with the realities of data assimilation and information fatigue. Organizations must develop the ability to take in large amounts of data collected across various care settings, identify and characterize best practices, model and measure individual practitioners against emerging standards, and isolate areas of inefficiency and potential improvement to more optimally allocate resources.

Opportunities

Healthcare providers of every size and scope are striving daily to advance the delivery of care, relentlessly pursuing improvements in the quality, efficiency, and cost-effectiveness in both diagnostics and therapeutics.. Every organization realizes the untapped opportunities are innumerable. The first challenge is to identify and prioritize the diverse initiatives that align with the mission, focus, growth stage and readiness of your organization; to clearly understand where the tangible opportunities lie within your own operations.

A common methodology we have pursued successfully with our clients is to explore specific analytic or exploratory questions, at every level (executive, point of service, operations, back-office), that they cannot answer, and what the answers to these questions could enable. From this starting point they proceed to identify areas of overlap where individual projects, improvement initiatives, metrics programs, IT implementations, and process re-designs can begin to address the diverse and multiple issues the enterprise is facing. Actual provider organizations we have worked with, from integrated health systems to individual hospitals, from multi-specialty providers with substantial education and research programs and affiliations, to specialty cancer centers, have started with questions as diverse as:

• What is the profitability of Surgical Services from 2008-2009? Across my 7 facilities? And within each Service Line?
• How can we most effectively deploy our relationship marketing resources to most favorably impact our clinical and financial outcomes for prospective cancer patients?
• How do we integrate clinical, epidemiological, translational and other research data together in a common repository to support the pursuit of personalized medicine, the ultimate objective of our cancer diagnostic, therapeutic and research programs?
• How do I create a data governance framework that will standardize the methodology for anticipating and addressing my enterprise data issues across care settings and subject areas?
• How do I establish and implement a service line framework and delivery approach, and how do I measure performance?

Addressing these and similar questions has been shown to drive the organization to clarify and focus where the specific opportunities lie to improve clinical and operational processes; align and deploy resources for greater productivity; strengthen IT applications and support; and enhance the reporting and information management structures that feed analytics and decision making.