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Leveraging Data to Improve Perioperative Care

By December 21, 2018 No Comments

As the United States healthcare system continues to strengthen and develop, the application of data is increasingly important for improving patient outcomes and quality of care. Medical centers have long collected data on patients undergoing surgery. However, before standardization, there was no uniform method for collecting, storing, and learning from patient data. Historically, physicians such as surgeons and anesthesiologists created hand-written patient notes, which were then placed in a file for storage. After a designated amount of time, these files were destroyed to allow room for new patient files. By failing to consolidate patient data, a valuable opportunity to elucidate trends in surgical care and outcomes was lost. The internet, electronic medical records (EMRs), and quantitative clinical research have all played an important role in improving the delivery of surgical care. In the rapidly advancing age of surgical and anesthesia care, data is a powerful tool with the ability to increase the efficacy of procedures and improve outcomes for all patients.

In clinics, private practices, and academic medical centers across the country, EMRs have become the standard method for enrolling patients into the healthcare system. Beyond functioning as a central resource for scheduling and surgical care coordination, EMRs are also valuable as a central repository for capturing patient data.[1] Many modern EMR systems can be adjusted to conform to data analysis priorities in the surgical field. With near limitless options, how do we determine which data should be collected? A team of physician-researchers investigated this question by establishing a commission to discuss the merits of a universal minimum data set for perioperative care.[2] In the end, researchers representing medical institutions from the United States and abroad established a minimum dataset consisting of 38 data collection parameters for 74 operations.  The hope is that if a significant proportion of medical centers performing a high volume of surgeries were to implement collection of these 38 parameters, the resulting data could be leveraged to examine macro-level trends for patient outcomes at the procedural and operative levels.  Thus, a universal minimum perioperative care dataset has the potential to generate significant results for research and practice.

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Once health systems have collected a sufficient amount of quality data systematically, the next step is to apply this data to address existing and future patient practices. Healthcare organizations have already begun pioneering the use of data in their efforts to improve patient outcomes. These efforts are exemplified by a case study of sepsis, a condition in which the body reacts negatively to infection.[3] Hospitals in the HCA Healthcare network have implemented a program called SPOT (Sepsis Prediction and Optimization of Therapy), which collects a number of data points from patients recovering from surgery, and then inputs the data into a machine learning algorithm that can predict whether or not the patient is susceptible to septic shock. On average, the algorithm is capable of predicting sepsis 18 hours before a physician would have diagnosed it in a patient. While such predictive technologies are still in development, the preliminary results are promising and these systems can serve as early models for effectively utilizing data to improve patient outcomes.

As healthcare technology continues to develop, patient data should be actively engaged as a highly useful tool in clinical research practices, which have the potential to improve patient safety and optimize outcomes at every stage other surgical journey.

References:

[1] Evans, R S. “Electronic Health Records: Then, Now, and in the Future.”Yearbook of Medical Informatics. Vol. Suppl 1,Suppl 1 S48-61. 20 May. 2016, doi:10.15265/IYS-2016-s006

[2] Yerokun O et al. “10.15 Development of a Universal Minimum Data Set for Perioperative Care in the Global Setting”. Academic Surgical Congress. 2018. http://www.asc-abstracts.org/abs2018/10-15-development-of-a-universal-minimum-data-set-for-perioperative-care-in-the-global-setting/

[3] “How HCA is Sniffing Out Sepsis Early.” HCA Today Blog. 10 September 2018. https://hcatodayblog.com/2018/09/10/spot-how-hca-is-sniffing-out-sepsis-early/