Analytics opportunities- ata analytics tools have the potential to transform health care in many different ways. In the near future, routine doctor’s visits may be replaced by regularly monitoring one’s health statusand remote consultations. The inpatient setting will be improved by more sophisticated quality metrics drawn from an ecosystem of interconnected digital health tools. The care patients receive may be decided in consultation with decision support software that is informed not only by expert judgments but also by algorithms that draw on information from patients around the world, some of whom will differ from the “typical” patient. Support may be customized for an individual’s personal genetic information, and doctors and nurses will be skilled interpreters of advanced ways to diagnose, track, and treat illnesses. In a number of different ways, policymakers are likely to have new tools that provide valuable insights into complicated health, treatment, and spending trends.
However, recent developments in data analytics also suggest barriers to change that might be more substantial in the health care field than in other parts of the economy. Despite the immense promise of health analytics, the industry lags behind other major sectors in taking advantage of cutting-edge tools. Most health care organizations, for example, have yet to devise a clear approach for integrating data analytics into their regular operations. One study even showed that 56 percent of hospitals have no strategies for data governance or analytics.
Compared to other industries, the slow pace of innovation reflects challenges that are unique to health care in implementing and applying “big data” tools. These barriers include the nature of health care decisions, problematic data conventions, institutionalized practices in care delivery, and the misaligned incentives of various actors in the industry. To address these barriers, federal policy should emphasize interoperability of health data and prioritize payment reforms that will encourage providers to develop data analytics capabilities.
Despite the immense promise of health analytics, the industry lags behind other major sectors in taking advantage of cutting-edge tools.
SENSITIVITY OF CARE DECISIONS
A major barrier to the widespread application of data analytics in health care is the nature of the decisions and the data themselves. Unlike many other industries, health care decisions deal with hugely sensitive information, require timely information and action, and sometimes have life or death consequences. Each of these features creates a barrier to the pervasive use of data analytics.
The immediacy of health care decisions requires regular monitoring of data and extensive staffing and infrastructure to collect and tabulate information. The nature of health care decisions are more immediate and intrinsic than those made in other settings, creating a hesitancy about overhauling any major aspect of care provision. Health care decisions must take into account patient preferences, which at times differ from expert recommendations.