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• Case | HBS Case Collection | October 2018 (Revised April 2019)

  The Brigham and Women's Hospital Innovation Hub: Driving Internal Innovation

  Ariel D. Stern and Robert S. Huckman

  Keywords: healthcare; innovation; hospital; health; health care;

  Citation:

  Stern, Ariel D., and Robert S. Huckman. "The Brigham and Women's Hospital Innovation Hub: Driving Internal Innovation." Harvard Business School Case 619-026, October 2018. (Revised April 2019.)  View Details

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• Case | HBS Case Collection | October 2016 (Revised March 2019)

  Carrum Health: Scaling Bundled Payments

  Robert S. Huckman and Sarah Mehta

  Founded in 2014, Carrum Health helped self-insured employers located in three markets (San Diego, California; Seattle, Washington; and San Francisco, California) save money on their employees’ planned surgeries. It did so by contracting directly with top-quality hospitals located within the area, and negotiating a set fee (known as a bundled payment) for each of five common surgical procedures: knee replacement, hip replacement, cervical spinal fusion, lumbar spinal fusion, and coronary bypass. By 2016, the company was growing steadily and saving its clients over 40% on average on these five procedures.
  In September 2016, Sachin Jain, Carrum’s CEO, received an email from North Beach Apparel, a large retailer based in San Francisco with a growing presence near Chicago, Illinois and Columbus, Ohio. North Beach was ready to partner with Carrum, but the terms of the deal required Carrum to enter the Chicago and Columbus markets in order to serve all North Beach employees. The deal would significantly increase Carrum’s revenue and begin to move the entrepreneurial venture closer to profitability. However, by expanding to Chicago and Columbus, the young company ran the risk of spreading itself too thin, especially given the opportunity for growth in Carrum’s current three markets. But Jain knew that if he waited too long to expand geographically, Carrum might lose its first-mover advantage in several markets. With limited resources, Jain needed to decide how to scale his young company: should Carrum enter the Chicago and Columbus markets with a guaranteed initial client base and then focus on selling the existing five bundles to new customers there; or, should the company add new bundles to its product line through the existing provider networks in the three markets it currently served?

  Keywords: health financing; health insurance; value-based healthcare reimbursements; bundled payments; innovation; Scale; Health; Health Care and Treatment; Cost Management; Growth and Development Strategy; Decision Choices and Conditions; Health Industry; California; San Francisco; San Diego; Seattle;

  Citation:

  Huckman, Robert S., and Sarah Mehta. "Carrum Health: Scaling Bundled Payments." Harvard Business School Case 617-017, October 2016. (Revised March 2019.)  View Details

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• Article | Proceedings of the Hawaii International Conference on System Sciences

  Multivariate Unsupervised Machine Learning for Anomaly Detection in Enterprise Applications

  Daniel Elsner, Pouya Aleatrati Khosroshahi, Alan MacCormack and Robert Lagerström

  Existing application performance management (APM) solutions lack robust anomaly detection capabilities and root cause analysis techniques that do not require manual efforts and domain knowledge. In this paper, we develop a density-based unsupervised machine learning model to detect anomalies within an enterprise application, based upon data from multiple APM systems. The research was conducted in collaboration with a European automotive company, using two months of live application data. We show that our model detects abnormal system behavior more reliably than a commonly used outlier detection technique and provides information for detecting root causes.

  Keywords: big data; data science and analytics management; governance and compliance; organizational systems and technology; anomaly detection; application performance management; Machine learning; enterprise architecture;

  Citation:

  Elsner, Daniel, Pouya Aleatrati Khosroshahi, Alan MacCormack, and Robert Lagerström. "Multivariate Unsupervised Machine Learning for Anomaly Detection in Enterprise Applications." Proceedings of the Hawaii International Conference on System Sciences 52nd (2019): 5827–5836.  View Details

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