BIG Data is coming (or has already come) to healthcare. [It is supposed to usher in new eras of research, economic responsibility, quality and access to healthcare, and better patient outcomes, but that is a subject for another post because it is putting the carriage before the horse to discuss it here.]
What is a data scientist? A new form of bug, a content expert who also knows data issues, an active researcher, someone trained in data analysis and statistics, someone who is acutely aware of relevant laws and ethical concerns in mining health data, a blind empiricist?
This is a tough one because it also touches on how many $$$$$ (€€€€€. ¥¥¥¥¥ , £££££, ﷼﷼﷼﷼﷼, ₩₩₩₩₩, ₱₱₱₱₱) individuals and corporations can make off the carcass of a dying healthcare system.
Never one to back away from a big issue and in search of those who value good healthcare for all over the almighty $ € ¥ £ ₨ ﷼ ₩ ₱, here are some of my thoughts on this issue.
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Content knowledge by a well-trained, ethical individual who respects privacy concerns is Queen. Now and forever.
topics and subtopics: who is a “health” data scientist? trained in healthcare? methodology research databases management information systems psychology? psychometrics other public health? epidemiology other medicine? nursing? social work? education? biostatistics? medical informatics? applied mathematics? engineering? theoretical mathematics? theoretical-academic statistics? information technology? computer science? other? conclusions must know content 70% methods 30% must honor ethics 100% laws practice privacy criminal civil federal state other greatest concerns correctness of results conclusions ethical standards meaningfulness validity reliability privacy utility expert in content field data analysis data systems ethics and privacy other member? association with ethics standards licensed? physician nurse psychologist social worker other regulated? federal hipaa state other insured? professional liability errors and omissions continuing education requirements? ethics renewal of licensure regulatory standards insurer commonsense laws go away if not well trained content field data analysis not statistics committed clean data meaningfulness subject privacy peer review openness ethics ethics ethics are arrogant narrow-minded purely commercial primarily motivated $$$$$ blind number cruncher atheoretical © 2013 g j huba