To optimize payments and reimbursement in emerging value-based care models, hospitals and health systems need to more proactively measure and improve clinical and financial performance across a myriad of quality and patient safety measures and programs. The inherent challenges to achieving these goals are daunting, expensive and increasingly burdensome to all stakeholders in value-based care: Estimates of annual American deaths resulting from preventable medical error range between 250,000 and 440,000, making medical error the third most common cause of death in the U.S., after heart disease and cancer (Makary & Daniel, 2016). The Society of Actuaries estimated that medical errors cost the U.S. $19.5 billion in 2008, with non-reimbursable medical costs per error ranging from $810 to $47,099 (Milliman, 2010). Total costs, which include in-hospital mortality and short term disability costs, reached over $93,000 per error.
There is little room for guesswork in this stressful environment, especially when organizations are striving to meet the increasingly complex standards and requirements elaborated in the updated FY18 Medicare Inpatient Prospective Payment System (IPPS) Final Rule. Updated measures and increasing penalties for poor performance, including and not limited to those specified for the Hospital Readmissions Reduction Program, Hospital Value-based Purchasing Program, and the Hospital Inpatient Quality Reporting Program reinforce that payments and reimbursement throughout the healthcare ecosystem are increasingly and decisively linked to the quality and safety of care that is delivered, documented and measured.
A strategic imperative is that organizations must choose a performance management system that enables care teams to make data and information actionable for continuous quality improvement. These teams need access to the right information and data in order to reliably measure and assess progress against the organization’s value-based clinical and financial priorities. The includes using key performance indicators (KPIs) and benchmarks that avoid unwarranted variation in care that often result in suboptimal outcomes and unnecessarily high costs that apply to all patients across their case mix and payer mix.
Sharing Systems And Data
Revamping digital interfaces will be essential for the future success of health systems. This will hinge upon a system’s ability to share and make use of data. When this is limited, it creates breaches in care continuity, leading to patient harm and increasing stress for clinicians.
Therefore, creating principals for end-to-end interoperability, strengthening the overall data infrastructure, building public trust around privacy and security, and smoothing over inconsistent state and local policies on data use and sharing remain of critical importance. When the country adopts these policy frameworks, healthcare quality and costs will be more likely to improve.
The major shift in healthcare delivery organizations to data-driven management has occurred both on the frontlines of care for managing individual patients and at the organizational level for managing population health. Nevertheless, most healthcare organizations are struggling because they’re drowning in data.
Effective data management comes down to the adoption of sophisticated tools designed to foster operational efficiency that leads to safer, higher quality care. Taking a holistic approach to these IT tools is key, and should involve not only integrating new systems, but also viewing them as a single entity.
Reconfiguring System Requirements For Value-Based Reimbursement
Systems can no longer be “hard-wired” to the traditional fee-for-service model of healthcare delivery. As we move to value-based healthcare economics, systems should be tailored to capture and measure a broader range of KPIs and performance benchmarks that are covered in federal payment and reimbursement programs. While such programs and measures provide a basic framework for accountability, most current systems are hard-wired to benchmark performance for a narrow case mix of populations.
Such reconfiguration paves the way to greater transparency, with internal and external progress in alignment with value-seeking stakeholder – transcending providers, patients and payers. Their individual and collective goals and expectations all point to the need for safer, higher-quality, cost-efficient care.
Accordingly, any performance management systems that are adopted for driving improvement in patient safety and quality must be ubiquitous. They must be designed and configured to track, synthesize and measure clinical and financial performance from various source inputs, using a broader scale of KPIs beyond those currently measured, as well as KPIs required for reporting in federal programs.
Making Healthcare Safer
Proper information management in IT systems ensures that clinicians and other healthcare staff have the right information when and where they need it, while maintaining the highest standards for data integrity.
One key step is to integrate health information management professionals, IT professionals and clinical engineers into patient safety, quality and risk management programs. Another strategy is to ensure that users understand the system’s capabilities and potential problems, encouraging users to report concerns and investigating those concerns, engaging patients in information management, and harnessing the power of IT systems to enhance patient safety.
Recognizing, discussing, and addressing these issues is the best way to make healthcare safer, as is looking at the issues holistically. It’s important to encompass the elements of the socio-technical model which incorporates all stakeholders—vendors, providers, IT, human factor experts, patients and others—to make it possible for everyone to work together to make healthcare safer.