Connected healthcare operations propel healthcare reform

Healthcare transformation and the changes required to survive it often distresses many healthcare leaders. Challenges in quality, patient safety, and revenue are not uncommon. However, new care and payment models require intense collaboration, transparency, and data sharing across healthcare operations silos.

Crucial data connections across the healthcare enterprise enable efficient and effective hospital operations to:

  • Smooth out inefficiencies in workforce management that contribute to worker burnout and fatigue
  • Spotlight costly subpar performance—but seek to correct it non-punitively as true provider-focused performance improvement
  • Surface the value (or lack thereof) of contracts and capital purchases, helping hospitals avoid financial drain from making poor decisions due to a lack of enterprise-wide visibility 

The ability to deliver safe, high-quality patient care has always depended on an intricate balance of strategic planning, human resources allocation, and data management. While COVID-19 upended plans, it also created a new paradigm for looking at old problems, ranging from seesawing capacity levels to staff shortages. It’s critical to not view data in a silo, but in full context of operations across the enterprise. 

The delivery of superior healthcare truly requires a well-coordinated village—but most health systems often suffer from multiple enterprise-level disconnections. Now, under value-based payment models, reimbursement is tied to patients’ perceived value, individual providers’ ability to contain costs, and benchmarked care/service quality. These factors amplify the need for better coordinated operations that can lead to better outcomes. 

The level of efficiency that successful healthcare reform requires can’t be achieved by using single, siloed solutions. For example, in workforce management, it’s crucial to make financially sound staffing and scheduling decisions in all departments and roles to eliminate bottlenecks. In receiving delayed care, patients see cracks in healthcare delivery services and may devalue otherwise exemplary care. The same holds true for other areas like talent management, spend management, compliance, and safety, that all need to be built on systems that can talk to each other.

Care delays create revenue waste in the form of preventable overtime. An eight-week study at Stanford University Hospital found that it experienced specialty consult-related delays annually. The delays were largely attributable to provider staffing shortages. The estimated total cost: $2.3 million per year (Arifeen, et al.). While every healthcare organization faces unique workforce challenges, understanding the volume of consult requests by specialty can be achieved by analyzing your existing scheduling data. Data-driven insights can then be applied to strategic planning to recruit or retain the appropriate number and types of providers.

Technological advances make it easier to streamline operations by using connected suites of software that integrate and coordinate tasks, allowing healthcare organizations and their staff to better organize the time and resources. 

Simply put, we’re in an era where operational challenges can be more easily identified and mitigated. Health systems, however, must select and implement the technologies that are best suited for their unique needs, while also being scalable and connected across the organization.

Once healthcare organizations used a labyrinth of technologies and software to avoid risk, maintain quality, comply with regulations, and ultimately keep patients and staff safe. However, in today’s data-driven age, operational efficiency and building a systems view are key to navigating changing needs and propelling them forward successfully toward healthcare reform.  

Reference

Arifeen, S. R., Shi, S., Meza, P. K., Justin, L. J., Svec, D., & Shieh, L. (2019). Waiting it out: Consultation delays prolong in-patient length of stay. Postgraduate Medical Journal, 95(1119), 1. doi: http://dx.doi.org/10.1136/postgradmedj-2018-136269

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