Crossing the Quality Chasm
The chasm that exists between what is expected of the country’s healthcare system and the reality is due to the inability of the care sector to meet the advancing demands of the patients. Despite the advancements of technology and knowledge, the healthcare industry has stagnated, failing to translate these assets into practice (Institute of Medicine, 2001). One major cause of errors and inappropriate or ineffective care practices is the lack of adequate patient information. This paper assesses how my organization is harnessing the power of information technology, particularly big data, to complete information availability, and consequently, enhance quality, safety, and delivery of care.
The organization is incorporating numerous data sources into the healthcare practices, which include medical imaging, payer records, wearable, electronic health records (EHRs), and medical devices, among others. The fact that big data is expansive, it is unique from the traditional human health data and electronic medical data applied in decision making. The organization is utilizing technology to support the transmission of these high volumes of data in high velocities via different media due to variances in nature and structure. One major challenge of handling big data in healthcare is the difficulties in converting these amassed data into useful, actionable information (Dash, Shakyawar, Sharma, & Kaushik, 2019). The organization has commission software tools that are supporting the movement of big data towards value-based healthcare while, at the same time, reducing costs.
Big data analytics has been at the forefront of the facility’s endeavors to migrate from the pay-for-service model into the value-based care model. The latter model rewards physicians and caregivers based on procedures that they perform, while the latter rewards based on the health of the patients. Through healthcare data analytics, the organization is now better placed to track and measure the health of the population, thus streamlining this transition. On a different note, the leadership teams are now able to use big data to analyze patient information and incorporate evidence-based practices into the care sphere.
By harnessing the technologies of big data and healthcare data analytics, the organization is trying to keep patients healthy, expand diagnostic services, and reduce medical costs. Consumer products that use the principles of big data are becoming more critical in tracking the health of patients, for example, the Apple Watch, which provides information of patients to caregivers to aid in the formulation of a patient’s wellness program (Pastorino et al., 2019). Diagnostic services include the adoption of sensory devices and the identification of prescription errors in advance. The organization is further envisioning applying big data in identifying patients with comorbidities, making more accurate decisions, and analyzing patient populations that are prone to higher levels of risks, and thus integrate preventive measures. This integration, therefore, underscores the great potential that information technology has in transforming the system.
Albeit challenging, the organization has succeeded to a significant extent in integrating big data analytics. According to a recent survey, physicians and other care personnel asserted to having adequate and credible data that they can use as a basis for decision-making. Patient databases have been vital in reducing diagnostic timeframe, thus enhancing patient outcomes. Health administrators have confirmed that digitization of patient records has facilitated a cultural shift to data-driven medication, which is why the organization is reaping the benefit of providing consistent care at an affordable cost. The major challenge in leveraging this technology is the high investment costs (Institute of Medicine, 2001). The organization has not been able to use big data for evidence-based practice fully. Nevertheless, there is a reason for optimism that this milestone will be achieved as well.