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Field
Primary Outcomes (End Points)
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Before
The main outcome of interest will be the in individual organ donor registration rates before and after the intervention. The registration rates of each CSRs will be the ratio: number of new individuals added to the organ donor registry while served by the CSR / total number of clients served for transactions for which a CSRs is expected to ask about the desire to join the registry. We will calculate these values, before and after the intervention, for periods up to six months before and six months after, and of course for the period between the first and the second intervention wave..
ServiceOntario records some of the activities of a CSR (those related to health services such as the issue or renewal of a health card) at the transaction levels -- one different entry for each customer served. For other activities (those that are not health related, such as issuing or renewing a driver's license), recording is in a separate data system and at the day level, i.e. how many transactions, and of what type, a CSR did in a given date. To have reliable measures of the overall activity of a CSR, per day and over longer periods of time, we had to combine for the pre-intervention information, and we will have to combine in order to calculate the post-intervention performance, the two datasets. However, because the recording is at a different unit of analysis in each of the datasets, we need to perform some adjustments which, in turn, require making some assumptions, as described below.
Because, from the transaction-level (health-related) data, there are about 1.3 services per client, when aggregating the different interactions to determine how many customers a CSR served we first divide the entries from the dataset at the day level (for non-health related services) by 1.3; thus if a CSR in a given day provided 13 non-health related services, the assumption is that she served 10 clients who needed non health related services. We then sum this amount to the total number of customers served for health related products. In the day-service level data, one of the entries for the various services offered is for "joint" health and non-health services offered. These would be services to clients who needed assistance for both health and non-health transactions (e.g. renewing both a driver's license and a health card). To avoid duplication when summing to the health services reported in the transaction dataset, we do not include the "joint" transaction amounts to the total of non-health based transactions. In this way, we are more confident that we are considering non-health services offered to customers who did not also receive health-related services in the same transaction.
The organ donor registrations are reported in the transaction-level data because this is considered a health-related transaction.
Each CSR who ever registered one client will therefore appear in the transaction level data, but of course she may also appear in the day-services data if she provided also non-health services. Again, summing the daily health services (excluding organ donor registration) and daily non-health transactions divided by 1.3 (excluding the joint health / non-health transactions) gives us a plausible proxy of how many "unique" or different clients a CSR served in a given day. There may still be some noise and potentially overstating the number of different clients, but we do not expect any bias to be systematically related to certain CSRs or locations.
Note also that there are multiple reasons for a "failed" donor registration (which we code with value of zero in the columns that reports organ donor registrations at the transaction or client level): the client may have declined the offer, or the client may be already registered. Therefore a CSR does not actually have an opportunity to sign someone up at every transaction, if someone has already signed up to the registry. Again, we expect this bias to not be systematic. A further reason for a failed registration, and an important one for the purposes of this study, is if the CSR did not even ask the client.
We also keep track of the overall intensity/amount of activity of each CSR other than signing up new organ donors.
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After
The main outcome of interest will be the in individual organ donor registration rates before and after the intervention. The registration rates of each CSRs will be the ratio: number of new individuals added to the organ donor registry while served by the CSR / total number of clients served for transactions for which a CSRs is expected to ask about the desire to join the registry. We will calculate these values, before and after the intervention, for periods up to six months before and six months after, and of course for the period between the first and the second intervention wave..
ServiceOntario records some of the activities of a CSR (those related to health services such as the issue or renewal of a health card) at the transaction levels -- one different entry for each customer served. For other activities (those that are not health related, such as issuing or renewing a driver's license), recording is in a separate data system and at the day level, i.e. how many transactions, and of what type, a CSR did in a given date. To have reliable measures of the overall activity of a CSR, per day and over longer periods of time, we had to combine for the pre-intervention information, and we will have to combine in order to calculate the post-intervention performance, the two datasets. However, because the recording is at a different unit of analysis in each of the datasets, we need to perform some adjustments which, in turn, require making some assumptions, as described below.
For the transaction-level (health services) data, for each day we sum the number of entries (rows) in the dataset to obtain the number of clients served who needed any kind of health related service, including organ donor registrations. The organ donor registrations are reported in the transaction-level data because this is considered a health-related transaction.
Because, from the transaction-level (health-related) data, there are about 1.3 services (excluding organ donor registrations) per client, when aggregating the different interactions to determine how many customers a CSR served we first divide the entries from the dataset at the day level (for non-health related services) by 1.3; thus if a CSR in a given day provided 13 non-health related services, the assumption is that she served 10 clients who needed non health related services. We then sum this amount to the total number of customers served for health related products. In the day-service level data, one of the entries for the various services offered is for "joint" health and non-health services offered. These would be services to clients who needed assistance for both health and non-health transactions (e.g. renewing both a driver's license and a health card). To avoid duplication when summing to the health services reported in the transaction dataset, we do not include the "joint" transaction amounts to the total of non-health based transactions. In this way, we are more confident that we are considering non-health services offered to customers who did not also receive health-related services in the same transaction.
Each CSR who ever registered one client will therefore appear in the transaction level data, but of course she may also appear in the day-services data if she provided also non-health services. Again, summing the daily health services (excluding organ donor registration) and daily non-health transactions divided by 1.3 (excluding the joint health / non-health transactions) gives us a plausible proxy of how many "unique" or different clients a CSR served in a given day. There may still be some noise and potentially overstating the number of different clients, but we do not expect any bias to be systematically related to certain CSRs or locations.
Note also that there are multiple reasons for a "failed" donor registration (which we code with value of zero in the columns that reports organ donor registrations at the transaction or client level): the client may have declined the offer, or the client may be already registered. Therefore a CSR does not actually have an opportunity to sign someone up at every transaction, if someone has already signed up to the registry. Again, we expect this bias to not be systematic. A further reason for a failed registration, and an important one for the purposes of this study, is if the CSR did not even ask the client.
We also keep track of the overall intensity/amount of activity of each CSR other than signing up new organ donors.
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