Hospital analytics optimize healthcare provider networks by analyzing a variety of data. These data insights help minimize losses from insurance claims, preventing fraud and improving service delivery.
Patient Satisfaction
Patient satisfaction is less concerned with medical care than patients’ expectations, formulated based on prior experiences, narratives, social cues, and more. When those expectations are met, patients are satisfied with their hospital experience.
For example, hospitals can use analytics to predict when they’ll be busier so they can staff appropriately to prevent long wait times. They can also use software to store records electronically, improving productivity and eliminating the need to transport paper between facilities.
Additionally, healthcare organizations can adjust their treatment protocols by using healthcare analytics to identify which hospital inpatients are likely to overstay their initial admittance. This minimizes overstays, reduces costs, and frees up limited hospital resources. It also helps payers negotiate better contracts with their providers.
Utilization Management
Utilization management (UM) is the process that makes sure patients receive medical treatment and services when they’re needed but at a reasonable cost. It involves analyzing a patient’s case and proposed treatment to ensure they’re necessary and effective.
A key utilization management component is determining if a treatment plan will result in positive outcomes. This helps eliminate the overuse of healthcare resources, which can amplify costs and endanger patients. For example, if an original treatment plan isn’t working, a doctor may switch to a new procedure with better success rates for similar cases.
This analysis can help reduce denials and make UM more efficient. However, a well-trained staff must properly conduct and document these reviews and analyze data.
Patient Safety
Despite the best efforts of healthcare professionals, human error remains a major cause of patient safety issues. Hospital data analytics helps mitigate such errors by ensuring that all medical information is readily available to doctors and patients. This also reduces the time it takes to complete various tasks. It eliminates the need to manually enter and track data, thus allowing healthcare professionals to focus on other crucial tasks. In addition to reducing human error, healthcare data analytics can help hospitals ensure that all patients get the right treatment for their condition. This is achieved by analyzing patient data and identifying patterns of symptoms, illnesses, or conditions.
This allows healthcare providers to identify potential risks and provide preventative measures before the problem escalates. It also helps reduce the number of patients who overstay in hospital, which can increase costs and divert resources from other pressing healthcare needs. Healthcare analytics helps healthcare facilities avoid overstaying by predicting patient details, doctor schedules, bed allocation, and medicine supplies, among other variables.
Financial Performance
Data analytics in healthcare provides several benefits for hospitals and patients. The predictive models developed by data analysts help optimize staffing, predict operating room demands, streamline pharmaceutical supplies, and reduce healthcare costs for organizations.
Hospitals need help with issues such as delays in patient admission, non-availability of doctors, and mismanaged supply of medicines.
Moreover, the software helps predict the timing of peak hours for patient admissions so that hospital management can hire additional staff to meet this demand. This reduces patients’ waiting time and ensures healthcare professionals abide by proper nurse-to-patient ratio guidelines. Medical data analytics can also help identify potential fraud by detecting duplicate or phantom expenses on the financial reports. This reduces insurance claims the hospital makes and helps eliminate unnecessary spending.