Medical data at your fingertips to make diagnostic and therapeutic decisions to improve outcomes
Clinical analytics or clinical decision support (CDS) is a key usage among our customers. Our healthcare customers rely on the 2019, 6-time Best in KLAS Diver Platform to help them decrease costs, improve operations efficiencies, and capture revenue. Diver integrates data sources such as ERPs, EMRs, spreadsheets, and more to provide a complete view of data to make more informed and strategic decisions. Minimize your reliance on IT support for data extraction and report generation with Diver or Diver’s General Ledger Advisor Application. Users can gain real-time medical data for diagnostic and therapeutic decisions to improve outcomes, capture revenue, and reduce costs. Listed below are just a few examples of how customers are using Diver.
Chronic care patient alerting
Chronic care patients with specific conditions such as asthma, diabetes, hypertension, and elevated lipid levels that miss regularly scheduled appointments with their primary care physician show an increased tendency for unexpected Emergency Department visits and other complications. This results in diminished patient health and an increase in treatment costs.
A Diver Platform-based application can assist you with managing alerts for chronic care patients. For example, Diver can automatically generate reports to notify the providers and alert them of the need for follow-up appointments with patients that manifest chronic conditions.
The alerts for these patients can serve to significantly improve the quality of care while also helping to contain costs.
Rather than relying on staff to manually schedule follow-up visits, a Diver application could automate the process, eliminating the potential for errors or human scheduling failures.
The proactive nature of the alerts can potentially decrease expensive visits to the Emergency Department as well help physicians and patients stay abreast of their disease management regimens.
Physician leadership might want to evaluate the impact insulin regimens have on patient outcomes and to guide physicians toward better diabetes management.
With Diver, you can create a clinical intelligence system that analyzes the insulin regimens of inpatient diabetes to help physicians prescribe the best regimens to avoid complications and achieve efficient care. Insulin therapy for diabetes patients has changed over time from sliding scale to basal-bolus regimens.
Using the Diver Platform and its powerful data integration, business rules and modeling capabilities, clinical intelligence can analyze the extent to which physicians are using sub-optimal insulin regimens. Such a system can also demonstrate the impact insulin regimens have on patient outcomes and identify ways to coach physicians toward better diabetes management.
Leveraging the Diver Platform, an intelligence dashboard can analyze physician insulin therapy ordering patterns and correlate the choice of insulin regimen with patients’ glucose outcomes.
It can be difficult to objectively identify under/over-performers among healthcare staff members, but if intervention data is available, a Diver Platform-based application can help.
Once the information is in Diver, management can review the information across virtually any dimension, such as staff member, date, or type of intervention and retrieve it in a usable format.
In addition to getting a handle on interventions, the data can help management differentiate between staffers who exceed expectations and those who need to increase efforts to meet expectations.
With a Diver-based intervention and monitoring system, management can identify over and under-performers and examine root causes by utilizing multi-dimensional data analysis.
Management can learn from over-performers and find ways to encourage those behaviors in all team members.
Empowered with accurate and objective information, constructive feedback can be given and remedial action can be taken when needed.
Use Diver Platform to conduct detailed analysis of longitudinal data, revealing the treatment protocols and approaches that deliver the best outcomes for the lowest cost. This analysis can be performed across virtually any Diagnosis-Related Group (DRG) and further refined by day of week, attending physician, or facility ID.
With the Diver Platform’s powerful multidimensional data analysis capabilities, your staff can monitor virtually any metric, including healthcare-associated infections (HAI), relapse rate, surgical revisions and readmissions, and apply the resulting data to understand the root causes of problematic outcomes.
For example, by tracking potentially preventable conditions, another quality indicator that affects quality patient outcomes, the health system can reduce the number of patients who acquired preventable conditions while in the hospital.
If a patient acquires sepsis while in the hospital, you would be able to quickly see what condition the patient was admitted for and whether the order set was in place allowing for further investigation when necessary. The health system could stratify the data to see which patients received care consistent with order sets and which did not.
Diver could also help to quantify the impact of compliance on outcomes. Using the data provided by such a tool, you could confirm that order sets were effective and needed to be followed, which can also help facilitate training around that order set compliance.
Rapid angioplasty response
Rapid response to a myocardial infarction by performing angioplasty (“PTCA”) might reduce mortality of these patients. If your goal is to gain deeper insights into the root causes driving angioplasty response times, a Diver Platform-based application could track and report on the important measures.
Using integrated information from several data sources including a view of the patient, an application could drill down to individual cases to examine the specific details of that case, chart trends across patients, nursing shifts, and days of the week, and identify the root causes hindering a decrease in response times.