How Health IT Can Improve Patient Outcomes and Clinical Efficiencies
Beyond overhauling business processes that are part of any industry, IT can underpin several trends to help improve medical outcomes or healthcare-specific concerns:
- Optimized EHRs. Decision support software working with EHRs can help doctors diagnose and assess treatment options for disease. AI-driven decision support can also help manage chronic disease and route patients to the most appropriate care settings — efforts that can improve medical outcomes and the patient experience. AI is performing higher-level work, such as interpreting images to diagnose certain cancers and converting information from wearables or other sources to an EHR.
- Wearable capabilities expanded. Despite supply-chain concerns tied to raw materials, wearable makers have been developing AI engines to help their consumers gain insights about health, fitness and more. The ability to measure heart function, sleep habits, respiration and exercise creates a 360-degree view of patient health outside the doctor’s office. Those insights will become more predictive as the technology evolves.
- Delivering care outside hospitals. Telehealth boomed during the pandemic, but technology and economics were already driving medicine to outpatient and home settings. Virtual care offers convenience and often a better experience for patients if the provider is paying attention to satisfaction measures, such as wait times. Enhancing teleconferencing technology with AI can also lead to more meaningful clinical discussions. The technology itself, however, needs to fit into the workflow of care delivery.
- Accelerating drug/vaccine/diagnostic development. Cloud computing, data and analytics, and raw processing power have enabled the rapid development of diagnostics, therapies and vaccines to treat COVID-19. Drug discovery, a risky, time-consuming process, is seeing a boost in improved technologies. Pairing molecule discovery and clinical trials with data and analytics has helped improve all stages of drug development. The net effect has been to reduce the odds of a costly failure and effectively lower investment hurdles. Leading pharmaceutical makers have estimated that data and analytics cut six months off the seven- to 12-year process of developing a drug.
- Robotic process automation. AI-powered software is adept at taking complex, repetitive, time-consuming processes and automating them, such as certain tasks in labs, regulatory compliance and revenue cycle management (billing, claims management and collections).
The promise of healthcare IT has generated a great deal of investor enthusiasm in the sector, and we expect continued merger and acquisition activity that will keep driving innovation that benefits payers, providers and patients.