Performance management fundamentals

Aug. 22, 2014

You flop down on the couch with your tablet to book your first vacation in years. You spelunk around a travel website and run through calendars, costs, photographs and features of airfare and resorts. You’re looking for a package that will get you someplace warm and sunny with a casino and spotty cellular connections. After a relatively short period of time, you’re able to find the perfect getaway to help you disconnect and recharge. 

 A few weeks later, fresh from paradise and back to the grind, you are trying to determine where to put your casino winnings. You visit a prominent investing website, sift through investment options and, with the help of prompts and performance information, find the very best safe haven for your money.

Best vacation ever.

The above are examples of consumer decision support systems, software-based technological applications designed to put critical data into a decision-maker’s hands to improve the speed and quality of decisions. Consumer decision support systems are so widely used and so deeply integrated into our daily lives that we hardly notice them as we make purchasing or other important decisions. 

Yet, in the non-consumer environment, companies across industries understand how decision support can mobilize data to make better decisions. Businesses rely on decision support systems to improve organizational efficiency, streamline processes and promote learning. The application, technology and data may vary, but the objective is all the same: better decisions.

Better decisions mean better outcomes. So the healthcare industry, too, looks to decision support systems to deliver clinical and financial information to improve outcomes. But for Allscripts, decision support is part of a strategic “performance management” approach designed to help our clients run their businesses. 

Rick Mansour, VP Solutions Management, Allscripts
Martha Thorne, SVP Performance and Care Logistics, Allscripts

Performance management

As healthcare organizations move away from the fee-for-service reimbursement model and toward fee-for-value, they need to reduce costs and eliminate mistakes. This includes both operational and clinical mistakes. Performance management can help organizations improve care quality at the same time they improve operational efficiencies. Performance management is the perfect tool to manage the value-based care evolution.

Performance management solutions are helpful in part because of the perspective they provide. Hospitals and practices utilize a holistic view of the organization to track all facets of their organizations, from clinical choices to patient flow to billing and other customer service. These insights help healthcare organizations market their services, manage their costs and properly allocate sometimes limited resources.

Good performance management depends on meaningful clinical decision support, financial (or business) decision support and analytics. 

Clinical decision support

Improving patient outcomes and care quality are the goals of clinical decision support (CDS) efforts. CDS is intended to provide meaningful information in real time, at the point of care and within the native workflow, using tools such as alerts, reminders, clinical guidelines and diagnostic support information. When done right in a clinical setting, clinical decision support can improve the patient experience by reducing errors and adverse events.

CDS requires a tremendous amount of sophistication. It must combine information from a variety of sources – clinical, biomedical and patient – and filter it through a program to ensure data is generated properly and is useful for clinicians. Irrelevant data must be parsed. Actionable data must be highlighted. Delivering the right patient data into the workflow at the right time is critical.  

The mass of data needs to be organized and funneled to ensure that clinicians get the best information when they need it. In this way, CDS aims to reduce information as much as supply it. A good CDS finesses data, tailoring it for the organization and integrating it for sound, evidence-based decision making. MLMs are the cornerstone of this effort.

Derived from the “Arden Syntax” and a standard developed by Columbia University College of Physicians and Surgeons, a medical logic module (MLM) is the decision support tool that pulls clinical data from the electronic health record (EHR) and transforms it into an alert for the clinician at the point of care. MLMs are defined by the healthcare organization and can be configured for any number of rules or applications. 

An MLM does more than simply extract data. MLMs turn transactional clinical data into actionable information. It is an ongoing look through the evolving information in the EHR and is set to alert based on any number of criteria. It looks at all patient data, categorizing information based on condition, care and demographics. It excludes unimportant information to deliver customized data in a timely and accurate way. 

Recently, the Journal of American Medical Information Association (JAMIA) detailed a point-of-care patient safety project involving a team at the U.S. National Institutes of Health Clinical Center (NIH CC). The NIH CC team leveraged Allscripts Sunrise MLMs for pharmacogenetics, the process that evaluates genetic information to predict a patient’s response to medication.

The NIH CC team used MLMs to inform clinician decisions as they placed orders for three different medications at the point of care. A genetic variant (HLA) could predict patient reaction to these medications, which were used to treat different conditions. The NIH CC team’s goal was to provide HLA test information to help clinicians reduce the risk of adverse drug events. 

The NIH CC team developed algorithms and integrated them directly into the EHR with an MLM. As soon as a clinician ordered the drug, the MLM checked any present HLA genetic test results in the patient’s record.

The MLM allowed the clinician to see on an order form if lab results were present, absent, pending or not ordered. Then the MLM could block or allow the prescriber to place or override the order.

The MLM helped the clinician:

  • Determine if an HLA genetic test occurred and view available results; 
  • Order an HLA test from the EHR; 
  • Store HLA test results in the EHR; 
  • Order medications through “order set forms”; 
  • See everything on a single order-entry screen. 

Since its implementation, 154 different prescribers placed more than 725 medication orders for over 230 patients for these drugs. NIH CC is beginning work to continually improve or apply MLM algorithms to other medications.

Hospitals have also seen that CDS can be particularly helpful in analyzing information. It can turn data it evaluates into reports that provide quality measures on care goals and outcomes on conditions such as diabetes, asthma, pneumonia and others. 

The ability to improve clinical outcomes is what makes clinical performance management so helpful. But the other part of the equation is operational efficiency and improving the bottom line while improving the quality of care. And for that, hospitals, health systems and practices are increasingly relying on business performance management and financial decision support.

Financial decision support

The fundamental and foundational shift to value-based care means healthcare organizations must lower costs as they improve outcomes. Anecdotally, healthcare organizations have struggled with the mandate. Much of the healthcare industry is comprised of organizations with missions of care, not profit. Perhaps for this reason, the healthcare industry has lagged behind other industries in adopting systems that enable sound business decisions.

But the value-based care era is upon us, and healthcare organizations are increasingly incorporating business tools and processes, like financial decision support, to help them become more effective and efficient.

As with clinical decision support, access to information is key to sound decisions. Financial decision support solutions aggregate and deliver financial, operational and clinical data tailored by the organization to key decision-makers for better financial and clinical outcomes. The information in financial decision support does not appear in the clinical workflow but in dashboards and software that help monitor the operational performance of the organization.

And like clinical decision support, financial decision support facilitates strategic planning. It pulls together wide-ranging organizational information in useful ways, provides a view into performance that informs strategic business decisions, supports detailed business analysis and assists with resource allocation and long-term planning.

When a layer of analytics is added, performance management gains particular power with organizations gaining perspective that can truly empower superior decisions.

Empowering with analytics

Analytics is the final important component of performance management. Gathering and delivering data is important, but to succeed, decision-makers must understand the performance of their organization, both in clinical and operational contexts.

Analytics is not a separate function but rather is an integrated part of performance management. Clinical and financial decision support tools provide up-to-the-minute financial, clinical and operational data that informs decisions and analysis.

Good financial decision support solutions have features that allow users to report and parse data to understand operations from sources of revenue to understand where the organization is losing money or performing well.

From a clinical perspective, organizations can use clinical decision support to break down how alerts are used to refine rules. Clinicians can look at clinical results of treated patients to evaluate efficacy of care. And organizations can improve usability of order sets through observation of deployment patterns.

Clinical decision support improves the patient experience. Financial decision support improves the consumer experience. Improved quality of care, greater efficiency, better operations and improved service makes for healthier patients, happier customers and successful organizations.

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