As Doctors And Hospitals Are Overwhelmed, could A.I. Based Innovation Be An Oasis?


It was my 3rd 12 hour shift that week. Flu was at an all time high that winter and sick and exhausted patients crowded the reception area, hoping to be seen quickly but disheartened by the long wait times. In the back, I went from room to room trying to see as many patients as quickly as possible. I had not eaten or even gone to the bathroom for the last 8 hours- there just wasn’t time. Pregnant with twins, my back hurt but there was not time to pause – I just wanted to do my job as best as I could. And that was to help my patients. And this was true of many of the nurses and healthcare providers for the shifts that week. See a sick patient, make a diagnosis, order tests if needed, see the next person. We tried to figure out staffing models so that we could be more efficient, and patients could be seen and get to rooms in a timely manner. But it was hard to predict using pen and paper, and this type of day often wound up being a common scenario. I was exhausted. A year later, I quit full time practice and moved mostly out of clinical medicine.

Unfortunately, this is not an isolated scenario for many doctors and nurses. Our healthcare system is broken, and healthcare workers are exhausted.

Years in the making, recent surveys have shown that 40% of the healthcare workforce intends to depart in the next 5 years. Although there are many factors that have contributed to this, including the pandemic which has had a long shadow, one area that has hurt the most is administrative tasks. In the 2023 Medscape Burnout report, 61% percentage of HCPs stated that this was a significant issue. How can we address this to help overextended health care teams and provide more efficient care?

A promising area is A.I. and innovation, particularly with regard to evidence based technologies. In addition to their inherent ability to improve patient outcomes, digital and AI based products have the potential to solve the very problems that contribute to the inefficiencies and administrative workload of our broken healthcare system. These systemic issues directly impact our healthcare workers, notably nurses and doctors, already suffering from burnout and alarmingly exiting the healthcare profession by the tens of thousands over the past two years.

One such company is Acuity Behavioral Health. Mental health inpatient facilities, in the wake of the mental health crisis, are often trying to staff facilities to take care of the many of the 14 million plus patients in our country suffering from severe mental illness (SMI) who need close and specialized care. With an estimated 13-16% of psychiatric inpatients in crisis and requiring 1:1 care, staffing psychiatric units is complex and fluid from shift-to-shift and well outside of traditional medical-surgical staffing models evident in other areas of (physical) healthcare.

But what if we could use acuity metrics, patient data, and AI to help predict staffing needs for inpatient psychiatry? One example is Acuity Behavioral Health who has developed the Behavioral Health Acuity Index (BHAI), conceived, and validated by some of our nation’s leading clinical institutions and experts. The BHAI has proven to be effective in early implementation at both Cone Health in North Carolina and Pine Rest Christian Mental Health Services in Michigan, who are use this digital solution to help access to care, and reduce burden on the healthcare team.

Another company that reduces inefficiencies and workload in the system and specifically on doctors is HPEC. HPEC automates the credentialing process for physicians, which reduces paperwork burden on them when they onboard at hospitals, and clinics. Moreover, this decreases the time it takes for hospitals to ‘onboard’ doctors, a critical key to helping with staffing issues in a time when many doctors are feeling burnout and hospitals are battling retention issues.

When a patient comes in with a complex diagnosis, where clinical guidelines are not sufficient, doctors, practitioners and healthcare experts search the literature and case reports to help with treatment. This can be a time consuming and cumbersome process often due to the overflow of data.

Therefore, often the reach out is to other experts they may know or even discuss cases without PHI on social media platforms which may not be HIPPA compliant. Recognition of diagnosis as well as best treatment is key for a patient. But what if we had a HIPPAA compliant arena where doctors could consult with each other? And what if AI could help collect this data on the backend so that clinical insights from this information was available quickly to other HCPs who had similar patients? Such is the hope of PeerMD. As Limor Amit MD stated recently ‘ we hope to enable easy consultations to reduce workload, while obtaining AI based insights from this unique data to better outcomes for patients’,

Innovations such as these can ultimately help the gaps in healthcare, while reducing the administrative burden on physicians, nurses and other health team members. Awareness and adaptation of these technologies is no longer a choice, it is a necessity. With ERs overcrowded, and hospital beds much less available, health care providers are exhausted and overextended, and patient care is in crisis. For our health system, and our patients, we must work together to quickly assess, adapt and pivot with innovation- to save our fragile health system, and help all of us get the quality health we need and deserve.


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