Team-Based Analytics & Team-based Primary Care

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Introduction:

Primary care is a crucial part of the American healthcare system. It serves as the main channel that many people use to access and engage with healthcare services. If a patient has a non-emergent healthcare problem, they visit their Primary Care Provider (PP) to evaluate them and provide guidance when necessary. In the past patient data was recorded on paper and stored in file cabinets. Today, with robust Electronic Medical Records (EMRs), reporting tools, and data analytics platforms, many practices have decided to get rid of paper and go digital. Data analytics in healthcare allows us to analyze large datasets from thousands of patients, identifying clusters and correlations between datasets, as well as developing predictive models (The Use of Big Data Analytics in Healthcare, 2022). Data can be used to not only streamline primary care workflows but also improve the primary care experience.

Here at Medicalincs we work as a Care Transformation Organization (CTO) and partner with local primary care practices in Maryland. Payer-funded care transformation initiatives support the delivery of advanced primary care throughout the state, by allowing primary care providers to play an increased role in the prevention, and management of chronic disease and preventing unnecessary hospital utilization. Tracking the progress of primary care providers would not be possible without using data analytics. For our partner practices we track Electronic Clinical Quality Measures (eCQMs), Transitional Care Management (TCM) calls, hospitalizations, demographics, and everything one can think of to make sure they are on the right track towards value-based, patient-centered care.

Current Challenges:

Of course, there are challenges when it comes to data analytics and primary care. For data analytics to be well applied in primary care or any field, the process needs to be unified, and a standard of outcomes needs to be set to guide how data is inputted and collected. Some EMRs do not have the fields for all members of the care team to enter information, and this can be a challenge. For example, if a nurse were to write a note in a patients chart as free text, it does not allow for an automated retrieval of the data for reporting. To combat that, many EMRs have smart forms, smart sheets and templates that allow users to answer questions and input data in a unified, mineable way. This allows for data analysts to pull reports and use that information to better understand their patient population and in turn helps to improve the quality of care that is delivered to these patients. Human error in inputting data is another challenge that data analysts encounter daily. Something as small as typing the wrong letter in a patient’s name or address could throw them out of the denominator and skew one’s data. This is where making sure the whole team understands the importance of accurate data, and how it impact outcome trends and patient insights becomes crucial.

Opportunities:

One of the biggest opportunities in data analytics in primary care is being worked on here at Medicalincs. As a population management company, primary care team-based care implementation & complex care management are key areas of expertise in care delivery. We have broad experience working with state and national programs tailored to the pediatric and adult populations, as well as Medicaid and Medicare populations. Doing the work has shined light on just how lacking almost every primary care EMR is when it comes to Care Management. For lack of better words, these EMRs are not tailored at all for Complex & Integrated Care Management and therefore lack the real-time data to truly analyze both interim and final care delivery outcomes. There is an opportunity here to develop EHRs that better capture this data, this brought to life our care management platform known as Cordinnate Care. Cordinnate is a full‐service technology-based platform that provides a result and data-driven electronic health record solution to health plans, medical centers, private practices, and other healthcare centers to document care management, and care coordination services, and improve care team delivery. Cordinnate is structured in modules with interfaces that provide swift & easy connectivity between healthcare providers for the patients they serve; promoting quality, efficiency, choice & and accessibility. Our Cordinnate Care module bridges the gap between Care Management Delivery and Result-Driven Data Analytics by providing the infrastructure that so many EMR’s do not.

References:

Batko K, Ślęzak A. The use of Big Data Analytics in healthcare. J Big Data. 2022;9(1):3. doi: 10.1186/s40537-021-00553-4. Epub 2022 Jan 6. PMID: 35013701; PMCID: PMC8733917

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