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Top Tips for Selecting and Implementing Population Health Management Analytic Systems
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Top Tips for Selecting and Implementing Population Health Management Analytic Systems

From organizations who have recently implemented systems

Included below are tips for selecting and implementing population health management analytic and integrated data systems derived from Primary Care Associations, Health Center Controlled Networks, and health centers who have gone through this experience.



Identifying Need

  • Use a collaborative process to determine what priorities in a system are, ensuring input is received from those expected to participate in using the system.
    • Example:
      • Several organizations found success with creating steering committees with representation from participating health centers, and those groups guided the process.
  • Shared priorities, buy-in, and agreement as to the purpose and benefit of adopting a system help ensure that groups can work together in implementation phase.
  • Invite staff or leadership to join into the decision making process to foster support and create champions.
  • Consider how near term and medium tern funding will be handled. For example, will central entity (i.e., PCA, HCCN) pay for the system up from and health centers will pay to maintain from that point forward? Or will it be group purchasing?
    • Consider putting formal agreements in place to document these decisions and minimize risk.

Receiving Quotes and Proposals

  • Create a Request for Proposals (RFP) based on the priorities identified in the collaborative process and stick with it; most vendors will not offer all the functionality, but using a single structured RFP allows for assessing the various vendors across shared features.
  • Determine funds available for the system and communicate those up front; it is not beneficial to look at systems that are simply outside of your price range.
    • Examples:
      • One state sent their RFP out with a maximum cost, and encouraged vendors to respond to the RFP only if they could do so under the maximum cost.
      • Another state determined that they would pay for the system set up, as well as for the first year, and that health centers would share costs thereafter. Communicating this to everyone involved proved essential.
  • Ensure that any quotes received have been vetted by the vendor’s implementation team, not just salespeople, and include total cost for implementation, not just build or set up.



Data Validation

  • Conducting the data validation and mapping necessary to make a system meaningful can take a great deal of time.
  • Structured data elements must be used whenever possible, and limited as to how many options there are for input.
    • If this is not currently the case, resources may be better spent refining workflow and EHR configuration then implementing a new system.
  • Engaging in robust data validation in advance of system implementation makes the process much smoother and makes the need to go back and repeat work less likely.
    • Example: One state purchased a PHM data system with grant money that was available, and therefore had to move quickly to select and implement, so data integrity and mapping was largely an afterthought, and data was not structured appropriately. Since implementation, they have had to go back to conduct data validation and redo almost all mapping that was done. This has taken an estimated extra 9 months and has cost some trust in the system.
  • Data governance is essential to success. There must be accountability in participating organizations, and they must prioritize data quality through all levels of the organization, as well as using data for decision making.
    • Leadership buy-in in this concept is critical.


  • Creating and communicating a credible, feasible timeline with milestones, and delivering on those, fosters the trust needed to keep the process moving when there are the inevitable bumps in the road.
  • As with many things, a “carrot and stick” approach may be necessary to facilitate full acceptance and adoption.  
    • In communicating this, it may be that the carrot is improvements in care or clinical decision making that can be realized through use of the system as well as measure reporting that may can come out of the system (i.e., performance measures, grant reporting) and the stick may be that those organizations who do not participate or hold up their end of the deal will not get the financial benefit that other participants may get (such as grant funding based on data from the system).
  • The message that this is not a “set it and forget it” system must be received by all participating health centers. Outline the expectations so that participants know what ongoing efforts (in addition to benefits) to expect.


  • Maintaining engagement and mapping is key to continued success of the system. Planning in advance for how this will be done, and what metrics will be monitored is helpful.
    • Example:
      • Some organizations monitor utilization reports, so if a participating health center does not go into the system for a given length of time, that is apparent from the report and that health center can be followed up with to ensure they are engaged and not having any problems.
      • Quality improvement staff may constantly monitor participants and proactively reach out about any changes in data or anomalies that appear.
  • Maintenance must be ongoing. Changes in workflow or EHR updates can have dramatic impacts on the data that is pulled in.
    • Allot specified time and responsibilities for these maintenance duties.
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