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Self-Published Book – Health Data Privacy, HIPAA, and COVID-19

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Self-Published Book – Health Data Privacy, HIPAA, and COVID-19

I just self-published a book that is a brief guide to health information data privacy, the HIPAA Privacy Rule, and COVID-19. I'm an attorney and web developer and hope you find this helpful. Here are some links: - Sample Excerpt (PDF): https://www.dropbox.com/s/v2p2ia224u5efqx/%5Bexcerpt%5D%20Healthtech_HIPAA_March_2020_unique.pdf?dl=0 - Paperback (on Amazon.com): https://www.amazon.com/dp/B086B9QHBL/ - Kindle (on Amazon.com): https://www.amazon.com/dp/B0868VXCGH Please let me know of any feedback. If you buy the book, please know that 100% of the profits will be donated to restaurant workers furloughed without pay during this time. (I once worked at Domino's Pizza before law school.)

Visit product View on Hacker NewsMar 24, 2020

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Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

27%27% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

17%17% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: profit · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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