This write up in HBR deserves a deep dive and a mandatory read. I don’t endorse their ideas completely, because it tries to “fit in outcomes” on expected lines. Healthcare assumes importance because people place their lives in someone else’s hands. However, many things can go bonkers.
How Digital Transformation Can Improve Hospitals’ Operational Decisions
However, focusing on leveraging digital transformation solely to improve clinical decision making would be a mistake. Based on our research and that of others as well as the burgeoning advances in how hospitals are using data and technology, we believe that digital transformation has a substantial role to play in optimizing hospitals’ operational decision-making, which in turn can lead to improvements in the quality and efficiency of care and patients’ access to it.
At the hospital level, data-driven operational decision-support systems can provide valuable insights to aid in making these triage, admission, and discharge decisions. For example, when a patient arrives and the provider is unsure whether the patient should be sent to the ICU or a general ward, a decision-support algorithm can provide recommendations based on the predicted benefit of ICU admission for that particular patient. Research using patient-level operational data from more than 190,000 hospitalizations across 15 U.S. hospitals shows that when patients who had a clinical need for admission to the ICU are instead admitted to another part of the hospital (e.g., a general ward), this results in longer hospital stays and higher readmission rates.
This is not completely right. Outcomes depend on perceived surgical complications, and pooled results aren’t reflective of local post-operative management. If there were a “risk” to every surgery, surgeons won’t operate. Post-operative complications aren’t reflective of surgical skill either. Therefore, providing a “management solution” is an executive pipedream and smacks of stupidity without understanding the medical context. Yes, staffing patterns and better care (real-time embeds, for example) can be used. Pooled results are fraught with “danger”.
For example, the Beth Israel Deaconess Medical Center in Boston, in collaboration with a team of operations researchers from MIT, has implemented prediction-informed dashboards to support admission and transfer decisions by displaying each ward’s current census as well as projected number of discharges.
This is a good idea.
Analytics can also be leveraged to optimize team staffing. Hospitals rely on providers to work together effectively as a team, with team members spanning different roles and levels of experience. Research shows that the composition of care teams has a significant impact on performance.
Teams are complex ecosystems. No amount of algorithmic tuning can “optimise” the performance.
Radio-frequency identification (RFID) technologies and internet-connected trackers can be used to better track and locate supplies in real-time. For example, Mayo Clinic’s Saint Marys Hospital rolled out an RFID system for their emergency room operations in 2015, which led to improved care and patient experience as well as lower costs.
I think out of the complete HBR write up, this one makes sense. Digital transformations can assist in predicting demand and supply (and stock up inventory), and you can play around with the variables. However, it still requires pushing through bureaucratic procedures and punching in ideas.
Despite the obvious shortcomings in human aspects of hospital management, digital transformation can be applied to better scheduling and staffing patterns to maximise human interaction. Users should be encouraged to explore ideas on mobile applications or information kiosks, and leave the front office staff to help them navigate through their hospital journey. If everything is done paperless (from admissions to reimbursement protocols), it will help the patients stand in good-stead. Humanise the healthcare. That’s all people want.
RadOncNotes 