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EHR Observation Period logic - please take a look


(Melanie Philofsky) #1

The EHR WG convened on July 24, August 7, and August 21 to discuss the creation of an Observation Period from EHR data. The current and future conventions are not prescriptive enough and leave room for various ways of interpretation. The goals of our discussions were to increase the standardization for the implementation of the Observation Period table by providing some general guidelines for determining the start, end, and gaps in Observation Periods. The suggestions we came up with are only “suggestions” at this point. If the community and CDM & Vocabulary WG agree with these suggestions, we suggest they be added to the Observation Period conventions, Themis rules, and DQD checks.

All of these decisions should be tempered by local understanding of patients in the EHR you are ETLing.

*Note - These suggestions are not intended for HMO EHR sites since HMO EHR Observation Periods more closely resemble claims data Observation Periods.

  1. Create general guidelines for the implementation of the Observation Period.Start_date, Observation Period.end_date, and Observation Period Gaps.

Observation Period start date

  • Generally, an Observation Period does NOT begin before birth.
  • However, it might begin before birth IF the pregnant mother receives care recorded in your EHR. The child’s record is split from the mother’s record at birth. The recommendation would be birth_date minus 9 months for the Observation Period.start_date if these Persons are in your dataset.
  • Generally, an Observation Period does NOT begin before the implementation of the EHR at your site. Any records prior to implementation are probably “history of” record types and not a complete EHR record of clinical events.
  • Special consideration should be given to migration from previous EHR, implementation at different sites within your healthcare system, implementation of different modules, etc.

Observation Period end date

  • The first date from the following:
    • Date of death + 60 days is a Themis convention to allow events after death. This date should not to exceed the date of the data pull.
    • Last clinical event + 60 days is the assumption is a person will return to the same health provider if an adverse reaction/complication/unresolved condition occurs. This date should not to exceed the date of the data pull.
    • Date of the data pull

Observation Period Gaps and Persistence Windows (borrowing language from the Drug Era conventions)

Observation Period Gaps are periods of time when a Person won’t be receiving care from your institution and therefore the Person is not being observed and should not have an Observation Period. These gaps are usually hard to determine because most Persons don’t announce their departure from an EHR/healthcare institution. Therefore, a heuristic will need to be instituted to determine Observation Period Gaps where the information is not explicit.

Observation Period Persistence Windows are the maximum time allowed between two clinical events under the assumption a Person would have a clinical event recorded, if they are not healthy and seek care.

Example: Person 1 has a series of clinical events recorded from Jan. 1, 2010 to June 15, 2012. The time between clinical events is not greater than 2 months. The next clinical event for Person 1 after June 15, 2012 is on Oct. 1, 2018. Starting Oct. 1, 2018 Person 1 has clinical events occurring at least every 3 months up to the present date.

There is a 6+ year gap between groups of clinical events recorded in the CDM. After discussion in the EHR WG, we believe this 6+ year gap is indicative of a Person not being seen within our EHR/healthcare institution. Per convention #4 for Observation Period table, “As a general assumption, during an Observation Period any clinical event that happens to the patient is expected to be recorded. Conversely, the absence of data indicates that no clinical events occurred to the patient.”

Person 1 has two Observation Periods.

1st Observation Period.start_date = 01/01/2010 and Observation Period.end_date = 08/15/2012 (Per the end_date guideline above)

2nd Observation Period.start_date = 10/01/2018 and Observation Period.end_date = 09/01/2020 (Date of the data pull, per the end_date guideline above)

Now, there are cases where a Person only receives care within you EHR system when absolutely necessary. And if your EHR doesn’t offer primary care services, the majority of Persons lack healthcare insurance or any other reason why Persons are only seen in urgent or emergent situations, the above heuristic might be too restrictive. This is a guideline.

A question the WG debated was how long between clinical events should we assume any clinical event that happens to the Person is expected to be recorded? When should we end one Observation Period and begin another? What should be the time between events for an Observation Period Persistence Window? Wellness checkups/Visits happen approximately every 12-18 months depending on a multitude of factors. If Observation Period Gaps are 548 days or more, then the previous Observation Period should end and another Observation Period should begin on the date of the next clinical event as per the Person 1 example above.

Observation Period.period_type_concept_id : The period_type_concept_id offers a means to give more information about how the observation period is determined. The current options include ‘standard algorithm’, ‘standard algorithm from claims’ and ‘standard algorithm from EHR’. We should better define these types.

  1. Cautions/things to consider when implementing the Observation Period
  • Implementation of your EHR - migration from previous EHR, implementation at different sites within your healthcare system, implementation of different modules
  • Coverage of your healthcare system within your area, population served by the healthcare system,
  • All decisions should be tempered by local understanding of patients in the EHR you are ETLing.
  1. Metadata: what should be recorded and how it should be recorded? What is important for researchers to know to ensure the data is sufficient for the question?
  • We didn’t cover this in the WG, but I think the nuances of an EHR based CDM are important to record in a standard manner.
  1. Unanswered questions:
  • How should records prior to implementation of the current ETL be recorded (this is making the assumption that these prior records are not complete, but still may have accurate dates and observations)? Options are to store in event tables but not include within observation periods, or to put in Observation table as ‘history of’.

(Melanie Philofsky) #2

@Christian_Reich and @clairblacketer ,

Please take a look at the above


(Chris Knoll) #3

Could you clarify how observation period types might impact having multiple observations covering the same time?

For example, using observation period types, is it possible to have a general observation period from 1/1/2010 to 1/1/2015 and an observation period of a different type from 6/1/2011 to 6/1/2012?

I would caution against this situation, if it is allowed, since this would have to be handled very carefully for determining time at risk for a given analysis. Although observation period types I think exist in the current CDM definition, I’m not aware of any analysis that has been performed to check that these observation periods do not overlap.


(Don Torok) #4

@Chris_Knoll, we have no intention of changing the convention that ‘Each Person can have more than one valid
OBSERVATION_PERIOD record, but no two observation periods can overlap in time for a given person.’ In your example above the two periods overlap. Does that alleviate your concern?


(Melanie Philofsky) #5

As @DTorok said, per the conventions, overlapping observation periods are not allowed.

The EHR WG would like further clarification from @Alexdavv and other Vocabulary team members on the differences between:

Is standard algorithm the parent of the other 2? Colorado has EHR data and death registry data in one CDM. Should we use ‘standard algorithm’ since it isn’t pure EHR data?


(Chris Knoll) #6

Hello, @MPhilofsky and @DTorok:

Yes, if no observation periods can overlap (regardless of observation period type), then that alleviates my concern. Thank you.

-Chris


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