Senior leadership teams, directors, and healthcare managers across the professional medical sector are often engaged in periods of adaptation. There is an ongoing need to evolve as patient expectations, treatment protocols, medication administration techniques, regulatory standards, and legislation change.
One of the many adjustments in recent years is the federal mandate for healthcare providers to introduce an electronic medical records system. These systems have expanded considerably since they were first used in the 1960s, and now store records and data digitally. This transition signified a sweeping change for many practices, hospitals, and trusts in the form of organization-wide digitization.
Today, we’ll assess the three most significant management problems in the modern health services field and discuss how automation in healthcare can provide swift, effective resolutions, augment patient outcomes, and optimize administrative workflows.
1. Combining Robust Data Privacy Requirements With Electronic Health Records (EHR)
Across the US and Canada, EHRs are now the norm, allowing healthcare providers to collate information in one place. The difficulty is that these tools, and the workflows they require, can cause stress and frustration–particularly when employees find their EHR systems confusing or time-consuming to use.
Software acquisitions should be accompanied by thorough workforce training, ensuring both support staff and physicians understand how to use their new systems while protecting patient data. Conventionally, healthcare services have relied on paper-based processes, whereas introducing EHRs means that doctors, nurses, and other professionals also need to engage in training rather than depending on back-office support teams for clinical data extraction.
Healthcare managers can address these complexities by drawing on change management strategies, tapering transitions to replace legacy systems, and ensuring medical staff are comfortable using EHRs, particularly where new software differs considerably from previous solutions. Over the long term, a systematic and inclusive approach will help all stakeholders engage in the transition, ensuring that medical data management systems provide better outcomes, faster workflows, and improved margins while safeguarding sensitive data.
2. Information Silos and Low Interoperability Between Healthcare Providers, Clinics, and Facilities
Another prevalent issue is that health tech may not be suitably interoperable, meaning that important information, diagnoses, symptoms, and comorbidity indicators are missed. Creating risk analyses and developing long-term care plans without all the relevant data can lead to unnecessary costs and more serious issues, such as not being aware of an allergy, not having access to surgical records, or not knowing which tests have already been performed.
EHRs are intended to address these problems, where siloed information prevents practitioners from seeing the whole picture of a patient’s health. However, studies show that even practices using the same networks may not coordinate data sharing to the required level. Full-circle data integration software with advanced functionality can resolve this issue, providing a detailed and comprehensive clinical history for every patient.
3. Time Pressures to Manage Large Data Volumes and Extract Accurate Information
Our third and final problem is a lack of workflow optimization, when medical staff do not have all of the essential information necessary to provide the best practice standards at the point of care. Unoptimized workflows may mean alerts are delayed or records are incomplete.
Examples include EHR systems that load slowly, putting further strain on the time a clinician has to consult with a patient, or when records contain such large amounts of data that it can be difficult to find those most important data points within one patient record.
Advanced tech can prevent data overload using simplified reporting and visualizations to extract the meaningful data that is most relevant to the patient’s current care. The ideal is to use software that can import data from external sources and combine it with internal records, reducing the number of tools a healthcare team needs to deploy and ensuring that they have real-time updates when a patient data point changes.
Addressing Problems in Healthcare Management
The key with each of the issues discussed here is to ensure organization software solutions are suited for all needs, with the capacity and speed to manage data, workflows, information sharing, reporting, and billable claims accurately, quickly, and with automation to ease administration requirements. Evidence-based healthcare tech solutions can improve patient outcomes, lead to more precise billing and claims, and ensure clinicians make informed decisions for the benefit of their patients.