How healthcare providers can boost productivity with data and analytics
The market for outsourcing health services such as logistics, payment solutions, and data and software platforms is expected to rise at a compound annual growth rate of more than 10 percent. Shifting value pools offer new opportunities for healthcare solutions providers. Based on previous waves of consolidation, it is likely that the payer, health systems, and life-sciences markets will continue to consolidate through payment and delivery innovations and accelerated horizontal and vertical mergers, acquisitions, and partnerships. To survive and grow in this new world, healthcare solutions providers may consider converging ecosystems; offer more complete, accurate, speedy, and embedded solutions; and expand their solutions and capabilities into new markets and customer segments.
Building tailored health benefits solutions
The quickest way to ruin a customer experience in healthcare is to treat everyone the same. Patients don’t want to feel like just another number. They crave personalized service that helps them find the right solutions. With new technology and old-fashioned personal interaction, offering personalisation in healthcare has never been easier.
Tailored solutions helps you understand patients
This view of personalized healthcare begins with a few simple exercises for the clinician before ever walking through a curtain or the door of a clinic. It makes an enormous difference to people, and they are more likely to feel cared for, adhere to treatment plans, and recover more quickly.
In fact, Using patient-identification techniques to consolidate records and building standard data models and pre-packaged analytics, for instance, could improve efficiency and quality of insight generation. Data and analytics marketplaces could further spur innovation, reducing the transactional friction between data and analytics, and generate additional insights.
2 steps to turn data into powerful insights
1. Access to diverse healthcare data
The analytical capabilities often associated with healthcare solutions providers would be useless without access to underlying data sets. The real secret lies in the diversity of data in terms of their type, volume, and variety (for example, claims, clinical, and social determinants of health). The more diverse and proprietary the data are, the greater the opportunity to generate distinctive insights. The diversity of data must also be easy to access: several organizations with massive amounts of data still struggle because of compartmentalization and silos, which prevent integration at scale.
To begin forming a full picture of overall spending and opportunities to reduce it, vendors could draw on both core and supporting varieties of data:
Core-data sources. Data from claims, electronic medical records, pharmacies, and labs form the traditional view of the patient and are the basis for concrete and reliable insights about the patients and patient types that underpin the data.
Supporting-data sources. Social determinants of health, patient-reported outcomes, consumer-coverage data, contract data, and others sources can create a more robust view of the patient that incorporates aspects outside the traditional health system.
2. Data aggregation for longitudinal member records
Organizations across the healthcare industry increasingly require an all-encompassing view of each individual with a single source of truth and a longitudinal understanding of that patient’s history. Tracing both diagnoses and outcomes can allow payers to price risk more accurately and coordinate care and reduce costs, health systems to deliver better care and preventive treatment, and life-sciences companies to better develop and promote certain treatments. For example, information captured at the crucial intersection between patient and doctor can have huge value when aggregated and analyzed at scale.
Understanding the data to boost productivity
Advanced analytics
Translating data into useful insights requires techniques that are at the forefront of advanced and predictive analytics—for example, machine learning for predictive modeling, next-best-action analytics, natural-language processing of unstructured data, automated insight generation through an embedded platform, and integration of data mining across multiple data sets.
To apply analytics to underlying data sets, a provider needs the ability to ingest and translate data from a variety of structures, ranging from paper medical records to digital-claims flows to data scraped from the internet. On behalf of a payer, for example, they could run real-time analysis of large data sources to determine the integrity of prospective payments or create a market-access feedback loop for a life-sciences company.
Access to analytics capabilities is becoming increasingly democratized. For example, many cloud platforms now provide deep analytics without the huge upfront investment that traditional servers require. Nevertheless, healthcare providers with strong data-science, data-engineering, data-architecture, and business-translator talent in-house can best deploy different analytics techniques and algorithms to make the consumption of insights customer friendly.
Multidomain intelligence and expertise
Payers, health systems, and life-sciences companies look to Health Solutions Technology vendors to provide more than access to data and analytical firepower. An “enterprise content library” can mix data and insights, creating deeper healthcare-industry expertise within individual markets and across multiple markets. In an ecosystem model, healthcare providers are likely to need expertise in multiple areas that will enable them to uncover patterns and insights that a siloed vendor would be unable to see.
In the case of payment integrity, for example, multiple vendors review the flow of claims for payment errors. This review includes the application of medical content (in other words, the translation of medical guidelines to identify improper treatments or incorrect prescription dosages) to a payer’s claims flow.
5. Workflow integration
A final point of differentiation is workflow integration. This involves letting core business practices become embedded with insights into day-to-day workflows. When insights are easy and actionable, customers are more inclined to use them. If insights are not embedded in a customer’s workflow—ideally, at the click of a button—the customer’s employees must expend extra effort, making them less useful. Solutions that can seamlessly push insights into business processes and workflows better enable employees to find value.
Because your health is our priority
Members want us to be personable and remember them. It makes a difference.
