How Healthcare Can Refocus on Its Super-Customers (Patients, n =1) and Customers (Doctors and Nurses) by Leveraging Lessons from Amazon, Uber, and Watson.
Healthcare is transforming with data-intensive omics technologies and Big Data. The "revolution" has already happened in technology, but the bottlenecks have shifted to the social domain: Who can be empowered by Big Data? Who are the users and customers? In this review and innovation field analysis, we introduce the idea of a "super-customer" versus "customer" and relate both to 21st century healthcare. A "super-customer" in healthcare is the patient, sample size of n = 1, while "customers" are the providers of healthcare (e.g., doctors and nurses). The super-customers have been patients, enabled by unprecedented social practices, such as the ability to track one's physical activities, personal genomics, patient advocacy for greater autonomy, and self-governance, to name but a few. In contrast, the originally intended customers-providers, doctors, and nurses-have relatively lagged behind. With patients as super-customers, there are valuable lessons to be learned from industry examples, such as Amazon and Uber. To offer superior quality service, healthcare organizations have to refocus on the needs, pains, and aspirations of their super-customers by enabling the customers. We propose a strategic solution to this end: the PPT-DAM (People-Process-Technology empowered by Data, Analytics, and Metrics) approach. When applied together with the classic Experiment-Execute-Evaluate iterative methodology, we suggest PPT-DAM is an extremely powerful approach to deliver quality health services to super-customers and customers. As an example, we describe the PPT-DAM implementation by the Benchmarking Improvement Program at the Seattle Children's Hospital. Finally, we forecast that cognitive systems in general and IBM Watson in particular, if properly implemented, can bring transformative and sustainable capabilities in healthcare far beyond the current ones.
1 Amazon.com , Seattle, Washington.
Evelyne
E
Kolker
2 Faculty of Communications and the Office of the President, International Technology and Innovation Policy, Gaziantep University , Gaziantep, Turkey .|3 Target Technology Transfer Office (TTO) , Gaziantep Technopark, Gaziantep, Turkey .|4 Amrita School of Biotechnology, Amrita Vishwa Vidyapeetham (Amrita University) , Kerala, India .|5 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington.
Vural
V
Özdemir
5 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington.|6 CDO Analytics, Seattle Children's Hospital (SCH) , Seattle, Washington.|7 Department of Biomedical Informatics and Medical Education, University of Washington , Seattle, Washington.|8 Department of Pediatrics, School of Medicine, University of Washington , Seattle, Washington.|9 Department of Chemistry and Chemical Biology, College of Science, Northeastern University , Boston, Massachusetts.
Eugene
E
Kolker
D003695:Delivery of Health Care / Q000191:economics / Q000379:methods* / Q000458:organization & administration; D006801:Humans; D007221:Industry / Q000191:economics / Q000379:methods* / Q000458:organization & administration; D009726:Nurses; D010820:Physicians