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Data Management in Durban

Posted by evanjmwaters on July 9, 2008

PIH’s team of OpenMRS implementers and data mangers based in Rwanda, Lesotho and Malawi conducted a data management workshop at the HISA 2008 Conference in Durban.  The purpose of the workshop was to identify common data management problems and brainstorm as a group to come up with good solutions.  In addition to the PIH team, current and prospective OpenMRS implementers based in Kenya, Uganda, Tanzania and South Africa were present at the workshop.

The problems discussed ranged from challenges with the initial implementation through to common issues faced by an established project with a large patient population.  Specific examples that attendees gave included:

  1. Getting started with OpenMRS at an existing HIV clinic with approximately 6,000 historical patients, but very poor paper and electronic record keeping practices
  2. Internet and/or power unavailability presenting challenges to a typical implementation
  3. Proliferation of transcription errors leading to poor data quality
  4. Lack of motivation from clinicians to use EMR forms leading to incomplete record sets
  5. Incorrect patient identifiers resulting in lab results being assigned to incorrect patients

Most of the data management problems that were discussed were common experiences for the implementers in attendance, and a number of interesting solutions were shared during the second half of the workshop.  These included:

  1. Focusing on getting a particular record set right at the beginning of an implementation over trying to get all of the data into the system at once.  In the case of the implmenter with 6,000 historical patients, this could involve building a recordset for patients currently enrolled at the clinic, and leaving out patients that were already deceased or transferred out.
  2. Being flexible with power and internet requirements.  Prior to getting internet at its clinics in Lesotho, PIH developed a system for offline data entry using Excel, which were uploaded to a central server in Maseru.
  3. Empowering the data entry team to notify clinicians of transcription errors on forms, and motivating the team to hold itself accountable.  The OpenMRS implementers in Eldorat have developed data accuracy targets and data clerks are rewarded for meeting them.
  4. Making it worthwhile for clinicians to use forms by (a) making the forms themselves improve workflow and (b) focusing on developing useful reports.  Allowing the data entry team to be part of the process by delivering the reports to the clinicians can help build good relationships between the two groups.
  5. Building an electronic system for issuing unique identifiers to patients.  In Malawi, the team from Baobab uses label printers and barcode scanners to issue ids and access patient records.

One of the overriding themes that came out of the workshop is how integral data management is with clinical practice as a whole.  From the moment a patient arrives at a hospital through to the point at which the patient’s record is entered into an EMR, there are countless opportunities for encountering data errors.  Each of these problem points poses an opportunity however, as good data management practices can greatly improve the clinical workflow as a whole.

Another theme from the discussion is that data management should not be an end point, but rather a part of a closed loop between the developers of an EMR and the clinical setting.  Some of the best solutions that were discussed in the workshop involved both a proactive data manager and an attentive development team that was able to help come up with a solution to the problem.

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