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Making Better Decisions in Health Care

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Health care is top of mind for many people in the U.S., often from the perspective of what needs to change in the industry. Technology, especially decision-making technology, can play a huge role. Four areas of the health care market seem to be ripe for decision management to make a difference.

  • Delivery of care: point-of-care decision-making.
  • Mobile health care: taking health care to the patient, not the patient to the health care.
  • The change from treatment to health management.
  • The growing need and demand for consumer empowerment.

To deliver on all this, health care companies will need to make better, faster decisions at every stage of the patient interaction. They will have to automate decisions previously left manual and improve the precision, consistency and agility of their automated decisions. They must ensure that medical staff gives the right advice and warnings when treating patients. They need new ways to reach out to patients at home or at work who take advantage of mobile devices and increasingly prevalent wireless access. They must use the information they have about patients to help them manage their health, not just schedule treatment. All of this must be delivered in a patient-centric way that enables patients to be participants. Despite a well-deserved reputation for being a technology laggard, the health care industry is beginning to show signs of innovation in this area.

Parkview Health, a multihospital system in Indiana, is applying the principles of enterprise decision management (EDM) to point-of-care decision-making. Automating dosage calculations and drug interaction warnings as well as medication ordering and delivery rules has allowed for faster delivery of the right medicines at the point of care. Understanding the decision being made, who is making it and in what circumstances is critical.

Kiwok is applying the principles of EDM to improve patient care differently. Its Body Kom Series ECG service includes a portable heart monitor. Worn by patients with heart conditions who require monitoring but not hospitalization, it is one of a new generation of mobile health care tools for controlling chronic conditions, for early detection and for follow-up after a change of medication or a surgery. The wearable device monitors the heart and transmits the patient’s trace to his or her physician by automating the decision of when a doctor should be alerted to a particular patient’s condition. Kiwok exposed business rules so that each doctor could set them uniquely for each patient. Multiple rules can be created, allowing any particular combination of heart activities to be the basis of an alert and to determine who should be informed. Mobile heath care is a growing business, but it won’t reach its full potential without the kind of smart monitoring possible with EDM.

Silverlink is also using EDM to interact with consumers in their homes. Silverlink uses adaptive communication sciences to enable health care companies to affordably and effectively interact with patients and members in their homes. Focusing primarily on automated outbound calls and other communication channels, Silverlink uses analytics to segment target populations and to predict their likely response. A flexible platform allows the rules about which voice to use, time to call, way to phrase the message and much more to be changed based on these analytics. Silverlink is using EDM to deliver what I call extreme personalization, where every call is essentially targeted to the desired result for a specific patient.

Healthways provides health and care support for well and chronically ill populations and is moving to a decision-centric approach as part of adopting service-oriented architecture (SOA). Using a combination of predictive analytic models and business rules, Healthways builds reusable services that answer questions like “is this patient at high risk for a heart attack.” Driven by data coming in from multiple sources, both manual and automated, these decisions control every interaction of a patient with the call center clinicians and will increasingly also support member portal and wellness Web sites. The use of data mining and analytics ensures that the data collected is put to use in improving interactions with members while the use of business rules means that those with medical know-how can participate directly in the creation, maintenance and validation of the rules. The approach delivers agility, lower costs and better care for patients.

Often in the U.S. health care market, the only unified view of prescriptions comes at the pharmacy. More than half of all U.S. patients only use a single pharmacy, and the vast majority uses only a single pharmacy chain. One major U.S. chain is using EDM to make sure that the patchwork of doctors and providers that prescribe for each patient is coordinated. Using business rules to specify which drugs interact with which and in what circumstances, it is able to automate the decision to fill or question each prescription a patient has. This ensures consistent application of drug interaction rules across pharmacists and that these rules are applied no matter how busy a pharmacist may be. Using business rules also means that the clinical staff can be directly involved in the setting of the interaction rules, eliminating potential errors of understanding. Externalizing, formalizing and managing this decision improves patient safety and offers a value-add service for the pharmacy chain.

Smart enough health care delivery is the future because it brings together mobile technology, data, medical know-how and medical professionals to deliver more effective and more cost-effective care. It’s beginning to happen now.

James Taylor is the CEO of Decision Management Solutions and is the leading expert in how to use business rules and analytic technology to build decision management systems. He is passionate about using decision management systems to help companies improve decision-making and develop an agile, analytic and adaptive business. He provides strategic consulting to companies of all sizes, working with clients in all sectors to adopt decision-making technology. Taylor is a faculty member of the International Institute for Analytics and is the author of “Decision Management Systems: A practical guide to using business rules and predictive analytics” (IBM Press, 2011). He previously wrote Smart (Enough) Systems: How to Deliver Competitive Advantage by Automating Hidden Decisions (Prentice Hall) with Neil Raden, and has contributed chapters on Decision Management to multiple books. He is a frequent contributor to Information Management and writes a regular blog at JT on EDM.

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