By Margaret Czart, DrPH
Historically, health insurers relied on information technology mainly to automate reimbursement procedures and crunch numbers for actuarial tables. They collected the historical claims data for a patient, while the provider collected the clinical data - two very different kinds of health information, used in very different ways by two groups with very different goals. Insurers focused on the financial aspects, while providers aimed to improve the health of their patients.
Today, payers face monumental changes in the way they use data. Increasingly, payers turn to the same kinds of clinical information systems used by hospitals to review diagnoses and treatments to monitor their costs and appropriateness. And as the healthcare industry shifts to new payment models that pay for value and outcomes rather than for volume of services, health insurers are also investing in clinical analytics to standardize health information.
Why the shift? As a provision of the Affordable Care Act (ACA), payers will no longer be able to reject consumers with pre-existing conditions. To manage their risk and control their costs, they're placing a new emphasis on health outcomes in the insured population.
They are using that data to assess patient outcomes and to determine best practices in terms of interacting with patients to improve health. For example, health insurers are now using hard data to drive initiatives with goals such as preventing hospital readmissions, managing chronic diseases more effectively, and tracking medication compliance.
As a result, health plans may soon end up with a better idea of the type of treatment a patient receives by the provider because they get a big-picture view of all provider encounters, while each specialist is likely to view only a limited subset of patient data. The evolving practice of health information exchange (HIE), still in its very earliest stages, is expected to change this, by allowing providers from one health system to "see" into another health system where a patient may have had tests, outpatient procedures, etc.
With all this clinical data now being collected and analyzed by both payers and providers, the next logical step will be for the two parties to share data in a collaborative way, to actually improve patient health and population health, rather than just for billing and reimbursement purposes. Moving forward, it only makes sense to bring data resources together for a common goal.
The idea would be for payers to not only pull data from providers to calculate payments, but to push data to clinicians and hospitals as well. By pooling all these types of patient data, both parties can gain greater insights as previously unseen trends or associations become apparent. With the right type of analytics tools, the industry can establish a kind of feedback loop that would benefit everyone: Payers channel their analytics capabilities to help providers target the patients in need of interventions, protecting their bottom line while ultimately promoting health and wellness.
For example, a physician alone may have no way to know if patients with high blood pressure are filling their prescriptions each month - but the insurer can extrapolate this from claims data. If claims data pertinent to medication compliance is shared with physicians, they can take steps to improve compliance. Perhaps the patient is experiencing troubling side effects that the physician can address - or perhaps a case manager can make a monthly reminder call or recommend a smartphone app designed for forgetful patients. While this is a very simple example of the benefits of collaboration, the possibilities are broad. With a large pool of clinical data to draw from, payers may even be able to help providers identify which treatments are truly evidence-based.
A possible scenario for provider-payer collaboration is this: A payer and provider agree upon clinical goals for improving the health of their diabetic patients. One such goal might be to move from episodic care to continuous care, as a way to prevent diabetic complications from developing. The provider then uses clinical analytics tools in conjunction with the EHR to identify all diabetic or potentially diabetic patients in the practice. These patients receive an evidence-based care plan that includes regular screenings, patient education, etc. The payer uses analytics to support the physician, acting almost like a member of the care team. Both parties collaborate on financial compensation as well - perhaps agreeing that physicians will receive a bundled payment to care for a defined diabetic population and are allowed to allocate the money as they see fit.
In this way, the goals of healthcare providers and healthcare insurers have become more closely aligned to collect and leverage clinical data in ways that can enhance care delivery, manage costs, maximize patient safety, and ultimately improve the health of a whole population.
The role of education in this new landscape
It seems certain that HIM HCI, HIT and professionals from other related fields will need to be flexible and adaptable in this changing environment. As the goals for managing clinical data change, so will the roles of HI staff. Managing patient records will very likely evolve from a task-oriented role to one that requires skills such as analytical thinking, process design, change management, and project management. Health informatics professionals also may be called upon to support providers, payers, and administrators as they implement clinical and financial applications related to the medical record and employ predictive analytics. They will need continuing education to build and maintain these skills, as the impact of technology on healthcare industry increases.
Industry trade groups such as the Health Information & Management Systems Society are gearing up with expanded programs for professional development. Advanced degree programs are also putting a spotlight on analytics - not just on the technical skills needed, but on the business applications that are specific to healthcare, as colleges and universities respond to the industry's changing needs. These master's level education programs can provide both future and current HIM professionals with the skills they need to qualify for emerging job roles.
Margaret Czart holds the post of assistant professor of health care informatics at American Sentinel University.