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How will Digital Transformation impact Perioperative Care?

Digital transformation: How electronic healthcare records(EHRs), AI and wearable tech are transforming perioperative governance and research
© UCL

In this article, Dr Dan Bendel (ST7 in Anaesthesia, UCLH) describes a new phenomenon known as ‘Digital Transformation’. In this first article he describes what digital transformation in healthcare is, and how it is beginning to improve perioperative care.

Digital transformation in healthcare involves the integration of technologies such as electronic health records (EHRs), telemedicine, wearable devices, artificial intelligence (AI), and machine learning [1]. These advances are significantly impacting perioperative care, bringing with them both opportunities and challenges. This summary highlights the multifaceted implications of digital transformation on perioperative medicine.

Electronic Health Records (EHRs)

As of November 2023, 90% of NHS trusts have adopted electronic health records (EHRs), representing a major shift in UK healthcare data management [2]. EHRs offer numerous practical benefits despite the variability in initial user experience. They provide clinicians with remote access to patient notes, blood results, imaging, and other critical data through computers or smartphones. This facilitates ordering radiological investigations, prescribing medications, making referrals, and listing patients for surgery.

Advances in voice-recognition technology have further enhanced EHR functionality, allowing for streamlined, automatic documentation of clinical encounters. EHRs’ ability to incorporate structured data is crucial for various perioperative advancements, such as predictive analytics and clinical decision support systems. However, challenges remain, including user interface design issues and potential patient safety risks from automated processes, such as pre populated (i.e. suggested) drugs for inpatient charting.

Patient Portals and Apps

Patient engagement has been significantly enhanced through patient-facing EHR components. These portals and apps enable patients to manage appointments, access medical information, and interact with healthcare staff. Apps designed for perioperative care offer features for appointment management, prehabilitation programs, remote patient monitoring, and documentation of patient-reported outcome measures (PROMs) [3],[4]. By improving patient involvement and adherence to perioperative protocols, these tools aim to streamline the perioperative pathway and empower patients, providing them with a greater sense of ownership over their healthcare.

Wearable Tech, Remote Observation, and Telemedicine

Wearable sensors have become a convenient and non-invasive method for collecting and transmitting physiological and biochemical data. Coupled with AI-powered interpretation, these devices facilitate enhanced monitoring of aging and comorbid populations [5]. Algorithmic analysis of data from wearables can predict health events such as heart attacks or strokes, allowing for early intervention before the disease progresses [6],[7],[8]. This includes the prediction of specific events such as heart attacks or stroke from heart rate and sleep data [9],[10]. Additionally, wearables encourage healthy behaviours by tracking exercise, hydration, and diet.

Integration with EHRs enables remote monitoring, reducing the need for postoperative care in hospital settings [11]. Systematic reviews have shown that remote monitoring can detect early clinical deterioration and assess postoperative wounds, leading to lower complication rates. This represents a significant shift in postoperative care, improving patient outcomes and reducing the strain on hospital resources [12].

Clinical Decision Support Systems (CDSS)

Clinical decision support systems (CDSS) have evolved in tandem with EHRs. CDSS improve patient safety by preventing prescribing errors through alerts on drug-drug interactions, providing clinical management recommendations and diagnostic support. Other benefits include cost containment by suggesting cheaper medication alternatives, automation of documentation and patient decision support.

CDSS have demonstrated effectiveness in improving clinical outcomes, often through the integration of multiple processes, such as medication retrieval and administration via barcodes. However, they are not without risk [13]. New strategies for their clinical governance are still emerging, and need to be robust enough to ensure that they genuinely maintain patient safety, rather than jeopardise it [14].

EHRs: A Goldmine of Data

EHRs store vast amounts of patient data, which can be harnessed for governance, quality improvement, and research. Large datasets from initiatives like the Perioperative Quality Improvement Project (PQIP) and the Royal College of Anaesthetists’ National Audit Project (NAP) provide valuable insights into perioperative medicine [15],[16]. However, collecting and analysing this data is labour-intensive, requiring manual data entry and retrospective analysis.

EHRs simplify this process by capturing comprehensive patient data, including demographics, diagnoses, blood and imaging results, risk scores, interventions, and complications. This data can be codified, interrogated, and presented in various ways, allowing for detailed analysis of perioperative metrics and clinical outcomes. The ability to correlate different data points over time enables healthcare professionals to understand changes in clinical status and identify areas for improvement. This is new ground, and individual specialties from clinical genetics to colorectal surgery are documenting their efforts in mining their EHRs for data, and using their datasets for research [17], [18], [19], [20], [21].

Does your institution use an EHRS? Have you been involved in any programmes that use any other forms of digital transformation? What benefits have you seen? Do discuss with your fellow learners.

References

  1. Mumtaz H, Riaz MH, Wajid H, Saqib M, Zeeshan MH, Khan SE, et al. Current challenges and potential solutions to the use of digital health technologies in evidence generation: a narrative review. Vol. 5, Frontiers in Digital Health. Frontiers Media SA; 2023.
  2. NHS Digital. 90% of NHS trusts now have electronic patient records [Internet]. 2023 [cited 2024 Jun 6]. Available from: https://digital.nhs.uk/news/2023/90-of-nhs-trusts-now-have-electronic-patient-records
  3. Beesoon S, Drobot A, Smokeyday M, Ali AB, Collins Z, Reynolds C, et al. Patient and Provider Experiences With a Digital App to Improve Compliance With Enhanced Recovery After Surgery (ERAS) Protocols: Mixed Methods Evaluation of a Canadian Experience. JMIR Form Res. 2023 Dec 15;7:e49277.
  4. NHS England Transformation Directorate. Development of an app based integrated prehabilitation, perioperative pathway management and patient assessment platform. [cited 2024 May 26]; Available from: https://transform.england.nhs.uk/key-tools-and-info/digital-playbooks/perioperative-digital-playbook/development-of-an-app-based-integrated-prehabilitation-perioperative-pathway-management-and-patient-assessment-platform/
  5. Shajari S, Kuruvinashetti K, Komeili A, Sundararaj U. The Emergence of AI-Based Wearable Sensors for Digital Health Technology: A Review. Vol. 23, Sensors. Multidisciplinary Digital Publishing Institute (MDPI); 2023.
  6. Jin X, Liu C, Xu T, Su L, Zhang X. Artificial intelligence biosensors: Challenges and prospects. Biosens Bioelectron. 2020 Oct;165:112412.
  7. Harrer S, Shah P, Antony B, Hu J. Artificial Intelligence for Clinical Trial Design. Trends Pharmacol Sci. 2019 Aug;40(8):577–91.
  8. Khan ZF, Alotaibi SR. Applications of Artificial Intelligence and Big Data Analytics in m-Health: A Healthcare System Perspective. J Healthc Eng. 2020 Sep 1;2020:1–15.
  9. Chen S, Qi J, Fan S, Qiao Z, Yeo JC, Lim CT. Flexible Wearable Sensors for Cardiovascular Health Monitoring. Adv Healthc Mater. 2021 Sep 6;10(17).
  10. Bayoumy K, Gaber M, Elshafeey A, Mhaimeed O, Dineen EH, Marvel FA, et al. Smart wearable devices in cardiovascular care: where we are and how to move forward. Nat Rev Cardiol. 2021 Aug 4;18(8):581–99.
  11. Marwaha JS, Raza MM, Kvedar JC. The digital transformation of surgery. Vol. 6, npj Digital Medicine. Nature Research; 2023.
  12. Knight SR, Ng N, Tsanas A, Mclean K, Pagliari C, Harrison EM. Mobile devices and wearable technology for measuring patient outcomes after surgery: a systematic review. NPJ Digit Med. 2021 Nov 12;4(1):157.
  13. Sutton RT, Pincock D, Baumgart DC, Sadowski DC, Fedorak RN, Kroeker KI. An overview of clinical decision support systems: benefits, risks, and strategies for success. Vol. 3, npj Digital Medicine. Nature Research; 2020.
  14. Poon EG, Keohane CA, Yoon CS, Ditmore M, Bane A, Levtzion-Korach O, et al. Effect of Bar-Code Technology on the Safety of Medication Administration. New England Journal of Medicine. 2010 May 6;362(18):1698–707.
  15. The Royal College of Anaesthetists. Perioperative Improvement Quality Project [Internet]. [cited 2023 May 1]. Available from: https://pqip.org.uk/pages/aboutpqip
  16. NIAA Health Services Research Centre. NAP 7: Perioperative cardiac arrest [Internet]. 2022 [cited 2023 Mar 30]. Available from: https://www.nationalauditprojects.org.uk/NAP7-Home
  17. Milinovich A, Kattan MW. Extracting and utilizing electronic health data from Epic for research. Ann Transl Med. 2018 Feb;6(3):42–42.
  18. Denaxas S, Gonzalez-Izquierdo A, Direk K, Fitzpatrick NK, Fatemifar G, Banerjee A, et al. UK phenomics platform for developing and validating electronic health record phenotypes: CALIBER. Journal of the American Medical Informatics Association. 2019 Dec 1;26(12):1545–59.
  19. Pendergrass SA, Crawford DC. Using Electronic Health Records To Generate Phenotypes For Research. Curr Protoc Hum Genet. 2019 Jan 5;100(1).
  20. Carlson J, Laryea J. Electronic Health Record-Based Registries: Clinical Research Using Registries in Colon and Rectal Surgery. Clin Colon Rectal Surg. 2019 Jan;32(1):82–90.
  21. Colquhoun DA, Shanks AM, Kapeles SR, Shah N, Saager L, Vaughn MT, et al. Considerations for Integration of Perioperative Electronic Health Records Across Institutions for Research and Quality Improvement. Anesth Analg. 2020 May;130(5):1133–46.
© UCL
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