At the Snowbird ski resort in Utah in 2001, a group of 17 software developers gathered together and hashed out a manifesto.\nFifteen years later, organizations continue to benefit from the principles outlined therein \u2014 the Manifesto for Agile Software Development lives on.\nYet rather than dwell on the founding narrative\u00a0\u2014 spritely told, and worth a read\u00a0\u2014 we should perhaps look instead to how the principles of agile software development can be shared between software companies and the clients those companies serve \u2014 how software companies can help their clients find opportunities to implement the principles of agile in their own organizations.\nA fitting example exists in healthcare, where there\u2019s not only the business office side of the clients to consider, but also the clinical leaders and faculty \u2014 and in-house IT professionals, too.\nLet\u2019s take a look.\nImplementing predictive analytics in the hospital and health-system setting\nThe principle of \u201cClose, daily cooperation between business people and developers\u201d (one of 12 principles of agile development) must exist in the client-vendor relationship. Greater results are achieved through collaboration, because the agile model keeps momentum moving forward continuously through structured, incremental deliverables.\nAn implementation of predictive analytics at a large U.S. healthcare system encompassed these three phases:\n\nData validation: Rigorous testing of data attributes in the source and ancillary systems.\nReporting analytics: Creation of comprehensive analytics and reporting data warehouse.\nCustomized workflow: Operationalizing actionable analytics into work queues.\n\nThe rigorous data validation is vital for a few reasons. First, because healthcare data is disparate and diverse \u2014 it exists in multiple forms, often in multiple systems. Second, to state the obvious, meaningful data aggregation isn\u2019t as simple as dumping all the data into one place \u2014 the technical bringing-together of the data must be done correctly. Where there are inconsistencies, there must be adjustments \u2014 or the end result will simply be a proving of the maxim, \u201cgarbage in, garbage out.\u201d\nWith the data layer validated and established, we built the analytics layer. Based on collected patient-level data elements, we focused on predicting the probability that:\n\nA charge is missing \u2014 with the goal of identifying charge-capture leakage yet not creating manual exceptions.\nA patient will pay their portion of the bill\u00a0\u2014 so that the client can engage in more efficient and targeted followup.\nA patient will readmit\u00a0\u2014 so that an alert can be automatically raised (before the patient is discharged) when there\u2019s a high probability of unplanned readmission.\nA DRG was assigned in error\u00a0\u2014 so that the right claims can be automatically routed to coding\/CDI teams for followup before the claim is submitted.\n\nOur team\u2019s agile development model centered around the following core client business goals:\n\nUncovering account populations that require intervention \u2014 while simultaneously identifying root-cause process improvements.\nQuickly responding to issues and high-risk populations.\nEnabling end users at all levels to not be overwhelmed by the volume of data and enhanced access to it.\nStructuring small, consistent steps to rapidly and continuously drive change.\n\nThis approach, in turn, empowered the health system\u2019s management and staff to proactively identify issues in their areas of responsibility and bring solutions to the leadership team. Just as important, the agile development methodology bled into their efforts to improve revenue-cycle performance. The principles of agile imbued into the software development were mirrored in the efforts undertaken using that software. For example, the principle \u201cSimplicity \u2014 the art of maximizing the amount of work not done \u2014 is essential\u201d was reflected in the newfound ability of health-system staff to work by exception. They no longer had to do the work of identifying which accounts needed attention \u2014 nor did they have to attempt to manually determine which of these accounts were the highest value (and most likely to yield a positive outcome). The \u201cwork\u201d was done by the culmination of a clean, verified data warehouse, predictive analytics to identify at-risk accounts, and routing them to the staff best suited to intervene and resolve \u2014 which minimized the amount of work required by end users of the software.\nThe results\nThe principle of \u201cthe most efficient and effective method of\u00a0 conveying information to and within a development\u00a0team is face-to-face conversation\u201d led to improved communication and coordination across all revenue-cycle related departments. Automation ensured reduction in manual, non-value-add tasks. At-risk and outlier populations were effectively prioritized for proactive and immediate followup. And the organization sustained permanent improvement in the quality and integrity of their data \u2014 both in their predictive analytics solution and in hosted, installed systems.\nThey were also able to simplify their technology portfolio, removing bolt-on solutions that no longer added value or provided accurate information. One way to think about this is that they maximized the amount of vendors they don\u2019t work with \u2014 by focusing on simplicity that delivers the full functionality they need, rather than multiple vendors who all provide some sliver or approximation of what they hope to have.\nThis may all feel a bit academic \u2014 a data scientist suggesting that hospital and health system leaders need to take a page from the software development world. But what matters isn\u2019t where the ideas came from, or how they were originally applied. For business leaders, clinical leaders and technology leaders, what\u2019s important is that these principles can help ensure stronger financial performance, better use of staff time and more targeted attention paid to the patients and patient populations in greatest need of proactive intervention \u2014 all ingredients that help strengthen a healthcare organization\u2019s bottom line, providing the fuel to improve patient health and outcomes for years to come.