Corporación La Esperanza (CLE) has been offering free outpatient and residential drug rehabilitation services to underserved communities across Chile since 1995. They’ve gone from one clinic to seven throughout this time, allowing them to provide a much needed resource for over 500 men and women every year. As a nonprofit, donors constantly pose different requirements and questions about their program, making impact a moving target.
Folks who’ve work at CLE can readily tell you countless stories and anecdotes on how the program has improved peoples lives, warmly remembering those that have managed to turn their life around after suffering from years of addiction. Dedicated directors, therapists, and staff use these stories and collective experiences to improve the quality of the program everyday. Over the last few years, CLE has found that those stories might not be enough to prove the success of the program. Externally, the trends from the clinical, governmental, and donor communities have been to demonstrate impact based on statistics, graphs, and reports. Internally, CLE staff have been greatly interested in knowing their impact by applying new treatments with evaluation frameworks, developing indicators, and conducting an evaluation of their patients and services.
Meeting both these external and internal needs requires clean data. A lot of clean data. This has proven to be a logistical and administrative challenge, given that all their medical records in the past twenty years are kept on paper. Questions like “how many patients between the ages of 19-25 have used crack cocaine” requires days of effort for already overwhelmed administrative staff. Gathering and disseminating these numbers is simply not what people should spend time doing. In 2012, CLE implemented an Excel based database that allowed them to keep digital records for the first time. In order to manage the volume of data, changes to the forms being used, and administrative capacity of staff, compromises had to be made and data collection was kept to a minimum. Additionally, the Excel tool became logistically difficult as heavy files needed to be mailed or sent by couriers in USB drives to headquarters when an update or an report was needed. Ultimately, all of these headaches lead to bad data.
Understanding these limitations, the project at hand is using a cloud-based tool to replace the Excel tool and provide additional functionality for CLE staff. This requires replicating the current data flow and analyses, while allowing CLE to take advantage of new functionality where improvements can be made.
At the launch of the project, the central questions we set out to guide the implementation were:
· How can data help us achieve better results?
· How can we improve access to data across the organization?
· What is the value added of having a cloud-based system of record?
· Once we have this data, what do we want to know about our services and patients?
Currently, the new tool is built to track the same data that the Excel database contained so as to minimize change management. We’ve also been able to effectively migrate all digital data from each clinic into the new system in a matter of days. As forms change, new fields can be added with just a few clicks. Data privacy and security can be maintained using permissions and roles. New functionality allows clinics to collaborate using an internal social platform. Reports and dashboards are programmed once, updated automatically, and universally accessible as new records are created. Statistics and graphs can be pulled as needed for anyone who needs them. Business development staff no longer have to ask clinics to drop everything to generate a report for a new donor.
Regardless of the technological and system improvements, some of our guiding questions still remain unanswered. Whatever tool organizations use, simply having data might never provide those answers. However, having data can give rise to new questions or uncover answers that were previously obscured. Improved systems can lead to more time thinking about data instead crunching it. Increased data transparency can lead to greater collaboration across the organization.
Having already bridged the process with the tool, a new challenge lies in bridging the tool with the institution. The most difficult challenge, however, will be in bridging any tool with improved outcomes and improved services.
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