How Care Management Improves Clinical Outcomes?

Abhinav Shashank
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Care management is often singled out as one of the missing pieces in the landscape of an affordable and equitable healthcare. Although care management solutions have been around for a while now, healthcare organizations in the pursuit of value-based care look for improving the patient’s overall experience of care. In worst cases, they lack information regarding a patient’s health status, their discharge information, or fail to retrieve that information on time. Often, health systems lack the proper analytics to monitor and measure the quality of care being provided to patients and plan timely interventions.

 

What are the problems?

Upon closer examination, care management for several healthcare organizations, although being a solution, is a myriad of complexities which were difficult to execute successfully. There are some challenges physicians and caregivers frequently faced:

  • How to reduce the manual work on excel burdening care teams and put technology to effective use to decrease complexities of the program?
  • How to integrate a patient’s health information records, from medical information to billing histories?
  • How to facilitate an easy sharing of information among members of care teams, patients, and their families who may be using different platforms?
  • How to assign the best group of health coaches and care teams to a patient to drive positive clinical and financial outcomes?
  • How to continually assess and monitor the effectiveness of care plans and stay on the correct course of action?

 

The case for care management

Most of the times, the reason behind poor care coordination is uncoordinated health systems and fragmentation in care delivery – according to a survey, 44% of high-need patients faced major coordination problems in two years. U.S. is second when it comes to the number of high-need patients. At times like this, technology is the answer to these struggles. Big data technology has been a game-changer in healthcare, and has to be leveraged to help healthcare organizations manage their highest-risk populations:

1. Integrating patient data: Bringing in data from various disparate sources set up with a different technology is one the major barriers healthcare systems face. Healthcare systems need a platform that allows seamless integration and sharing of data among every stakeholder.

2. Stratifying the patients: Big data and data analytics can be used to identify patients subject to high-risk along with the underlying risk factors. Once the population has been stratified, physicians can gain actionable information on how to treat them. 

3. Creating and automating work queues: Care coordinators have massive amounts of data pertaining to a single patient sorting through which reduces the effectiveness in addition to being time-consuming. Health coaches should instead be able to easily sift through their work queues to manage time efficiently between their patients. 

4. Ensuring adherence to care plans: There often are limited ways to keep track of a patient’s health once they have been discharged. Providers should develop post-episode care plans for patients and ensure adherence to medications, regular follow-ups, annual wellness visits, etc.

 

Datashop’s Care Management Suite

Datashop is the healthcare’s first end-to-end solution for a comprehensive value-based care, much like an operating system that powers healthcare. Datashop’s care management suite is a detailed patient-centric care coordination solution that solves these challenges:

 

  • Data Integration: Datashop’s integrated data lake aggregates data coming in from EHRs, payers, and other operational sources to retain every important information in a single source of truth.
  • Patient 360: Once the patient data has been integrated, it is stored as a holistic, longitudinal record displaying all relevant information about medical history, vital signs, claims, disease registries, and billing details – giving a 360 view of a patient.

  • 2-way interoperability: With a truly bi-directional platform, Datashop can seamlessly share vital patient data among all the stakeholders in and across the network, regardless of the difference in the technology of their platforms.

  • Automated work queues: Datashop care with an AI-assisted platform can replace manual, tedious work on Excel and substitutes it with automated work queues that match patients on various parameters and automatically assign them to the most suitable coordinators put together as a team.

  • Developing care plans: Physicians are able to document their interactions with their patients along with their demographic information, clinical data, episodes, and risk scores. Using an artificially intelligent platform, health coaches are assigned patients with complete information, so that they can come up with the right plan.

  • Predictive and intuitive: Health coaches can access up-to-date information about their patients’ health, and with the use of predictive analytics, Datashop gives care coordinators real-time decision support to come up with the most appropriate and effective care plan.

Chronic care management with Big Data

With the number of chronic conditions on the rise, and accounting for about 86% of entire healthcare spending in the U.S., it’s important that healthcare organizations focus on developing exclusive care plans, specific to chronic conditions. There are several barriers along the way:

  • Lack of an end-to-end solution for complete chronic care management.
  • Health plans once developed transparency, flexibility, and clinical data handling on the go.
  • Often yielding to high expenses, the outcomes of chronic care management are incremental.

In January 2015, CMS came up with a Chronic Care Management model that offers to reimburse providers every month on delivering care services for Medicare beneficiaries having two or more chronic conditions. Improving the health of patients hence is a critical step for providers on the path to achieving value-based care goals and calls for a strategic approach.

Datashop’s chronic care management module offers the support of a well-informed care team along with PCPs, specialists, and family and enhances the care plans for patients with chronic illnesses:

 

  • Advanced analytics: Datashop’s CCM model gives providers a systematic assessment of the patient’s medical history and performs sophisticated analytics to identify near-future trends.

  • Patient-specific care plans: Using Datashop’s Patient 360, providers can create and share an actionable patient-centered care plan based on their physical, behavioral, demographic, and environmental factors.

  • Easy communication: Datashop’s truly interoperable platform facilitates an enhanced communication between providers to share and easily access a patient’s health records and be alerted of any sudden episode in real time.

  • Patient engagement: Health coaches can reach out to patients with follow-ups after a discharge, ensuring adherence to plans and empowering them with self-managed medications.

  • Referral management: With Datashop’s referral management solution, providers can seamlessly manage referrals and coordinate with community-based providers in the vicinity.

 

The Road Ahead

Ever since Big data was introduced in healthcare, we have explored a whole new world of possibilities. A care management plan that can incorporate insights from all the caregivers in real-time and harness the potential of big data, predictive analytics, and artificial intelligence will not only deliver better health outcomes but will also drive exponential growth of a system. Datashop Care was developed to help health systems optimize their care delivery with innovative ideas aimed at achieving desired outcomes. With this comprehensive suite on hands, healthcare organizations can become the helping hands patients need and deliver true value-based care.

 

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