The integration of artificial intelligence (AI) in the healthcare sector is revolutionizing various processes, including e-prescribing in hospice care. AI’s ability to enhance accuracy and reduce prescription time is addressing long-standing challenges in the industry. The shift to AI technologies promises transformative solutions to the myriad of inefficiencies and inconsistencies that have plagued e-prescribing systems, paving the way for a more efficient and accurate future in hospice care.
The Role of Wise Hospice Options in Health IT
Wise Hospice Options, a company with 21 years of expertise, is spearheading AI integration in e-prescribing within the hospice care sector. Over two decades of operation, the company has encountered and tackled significant interoperability issues arising from varied electronic health record (EHR) systems. These challenges come from the lack of standardization among different EHRs, which has underscored the critical need for enhanced data consistency and integration.
The company experienced substantial disparities in data standards when working with Health Level 7 (HL7) and Fast Healthcare Interoperability Resources (FHIR) specifications. This inconsistency across numerous EHR platforms presented major hurdles, highlighting the necessity for standardized data and seamless integration. The ongoing struggle with diverse data standards illuminated the fragmented nature of health IT systems in hospice care, prompting Wise Hospice Options to seek innovative solutions.
Initial E-Prescribing Challenges
Upon launching e-prescribing in 2013, Wise Hospice Options faced significant hurdles, such as inconsistent data and varying drug identifiers. These inconsistencies led to notable difficulties in accurately processing drug information and prescribing instructions. The e-prescribing system struggled to manage the gaps left by varied levels of detail and different identifiers used by each EHR, hindering the processing and validation of drug and medication data.
Efforts to collaborate with EHR vendors to improve data accuracy and consistency often faced limitations due to differing priorities and technical capabilities. Vendors’ varying IT priorities made it challenging to achieve substantial improvements in data accuracy, leading to persistent issues with unrecognized drugs and sigs. These challenges underscored the overarching problem of unequal and fragmented data across multiple EHR systems.
Risks in Simplified Workflows
To mitigate some of these issues, certain systems attempted to streamline workflows by accepting and loading free-text entries from EHRs. However, this simplification posed considerable risks. Without distinct fields for dose and frequency, free-text sigs could not undergo comprehensive dosing checks. Additionally, allergy checks could be compromised due to misspellings, abbreviations, or typos, which might lead to patient harm, especially since not all EHRs offer these checks.
Recognizing the significant risks associated with simplified workflows, Wise Hospice Options and its clients agreed that such an approach was not viable. The safety of patients was paramount, leading the organization to seek more robust and innovative solutions. This decision marked a clear focus on maintaining high standards of accuracy and safety, despite ongoing challenges in interoperability.
Turning to AI for Solutions
Confronted with the need for more structured and codified data, Wise Hospice Options turned to AI technologies for solutions. The primary objectives were to enhance the e-prescribing user experience, improve the effectiveness of medication and allergy interfaces, and streamline communication channels. The company identified AI as a potential means to bridge the gap without relying on cumbersome EHR-side updates.
In pursuit of these goals, Wise partnered with health IT vendor DrFirst. The collaboration aimed to develop a customized AI tool capable of codifying medications, parsing sigs, and codifying allergies from free-text entries. This innovative approach promised significant improvements in data accuracy and functionality, delivering a more efficient and user-friendly e-prescribing system. The AI tool’s capability to transform free-text into structured, codified fields indicated a major advancement in addressing the longstanding data inconsistencies.
Enhancing Efficiency and Accuracy
The implementation of AI marked a pivotal shift in the e-prescribing process. The integration was designed to function seamlessly in the background, enhancing existing workflows without necessitating additional user involvement. This change transformed the process from “fix then prescribe” to “review then prescribe,” saving time and reducing the likelihood of errors. The streamlined workflow not only enhanced the efficiency of the e-prescribing system but also improved overall user experience.
Pre-live tests of the AI tool yielded impressive results: codifying 92% of medications, parsing 80% of sigs, and codifying 95% of allergies. These outcomes represented substantial enhancements in both efficiency and accuracy, marking a significant departure from the manual and error-prone processes of the past. The background operation of AI ensured that users could focus on reviewing prescriptions rather than correcting data, contributing to a faster and safer prescribing process.
Real-World Implementation and Performance
Following its implementation, the AI system continued to deliver exceptional performance. Consistent high conversion rates were achieved—99% for medications, 85% for sigs, and 96% for allergies. These figures underscored the AI’s efficacy in automating and streamlining the e-prescribing process, vastly reducing the manual entry required. The enhanced automation significantly reduced the time needed to e-prescribe, cutting it down from 20 seconds to just 2-3 seconds per prescription.
The practical benefits of this streamlined process were evident in the improved safety and efficiency of the prescribing process. The reduction in manual entry minimized the risk of errors, while the rapid conversion times contributed to a more efficient workflow. These improvements highlighted the transformative impact of AI on e-prescribing, moving towards a more automated and reliable system.
Continuous Improvement
The initial success of the AI integration was met with ongoing efforts for refinement and improvement. Client feedback played a crucial role in identifying areas for further enhancement. To address and promptly correct AI errors, Wise Hospice Options and DrFirst established an escalation system. This system ensured that any issues encountered were quickly resolved, maintaining the high standards of accuracy and efficiency.
Challenges also arose due to data variances at the hospice level. Different organizations exhibited diverse data entry practices, with some customizing drug entries while others adhered to prepopulated lists. The collaborative effort between Wise Hospice Options and DrFirst helped manage these nuances, leading to continuous refinements and better handling of varying data entry practices. This ongoing adaptation process was vital in ensuring the AI system’s robustness and reliability.
A Model for the Future
The integration of artificial intelligence (AI) into the healthcare sector is revolutionizing numerous processes, including e-prescribing in hospice care. AI significantly enhances the accuracy of prescriptions and reduces the time needed to write them, effectively addressing long-standing challenges faced by the industry. The adoption of AI technologies heralds transformative solutions to the myriad inefficiencies and inconsistencies that have long troubled e-prescribing systems. By implementing AI, hospice care can achieve higher levels of efficiency and precision, ultimately improving patient outcomes and streamlining medical processes.
In addition to boosting accuracy and saving time, AI’s potential in hospice care extends to predictive analytics. This can help healthcare providers make better-informed decisions regarding patient care, predicting potential complications and optimizing treatment plans. The continuous learning capabilities of AI systems also mean they can adapt to new data, improving over time and providing ever more reliable support to healthcare professionals.
Moreover, AI can enhance the ability to monitor patient conditions remotely, ensuring timely interventions and further enhancing the quality of care. Overall, integrating AI in e-prescribing and other areas within hospice care presents a promising future marked by increased efficiency, accuracy, and improved patient experience.
