PatientFollow Project: Difference between revisions

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Specifically, we are looking into having a single collector/laptop follow a patient for their whole admission, and how our processes would need to change to accommodate this, and what extra tools we might need.

~~== Roll-out ==~~

~~This will be rolled out~~

* at the Grace starting 2020-09-01

* at HSC starting 2020-10-15 (Thursday after Thanksgiving)

~~=== Implementation discussions ===~~

~~If there are questions or problems with the change, please put a discussion here.~~

== Identifying admissions / Starting collection ==

Line 21:

Line 13:

* '''missing a patient''' - we have been testing the Cognos tool to make sure patients are not missed from it; for PatientFollow we will simply filter that list, so if all patients were on it, they should still all be on the split list

** main office can run a check between Cognos Data and our data for the first few weeks to make sure all Cognos data is also in our data

~~=== Would the LOS have any impact on this sharing plan? ===~~

~~{{Collapsable~~

~~| always= This would not be a problem.~~

| full= * We discussed whether different [[LOS]] will cause problems with this distribution of patients. We would expect LOS to be equally distributed across Chart Numbers; if it is we should be able to ignore it in distributing patients, since the “average” patient with an “average” chart number would have an “average” LOS.}}

=== Medical Records requests ===

Split of shelves would need to become based on [[Laptop identifier]] (it may already be...);

{{Discuss |

* Could an HSC collector please have a look at [[HSC Medical Records requests]] to make sure it is consistent with these changes? Once you have dealt with that, please take out this discussion. Ttenbergen 21:34, 2020 October 15 (CDT)

}}

~~=== [[EMIP]]s ===~~

[[EMIP]]'s will be distributed to collectors/laptops in the same way as we collect ward patients, using the assigned MRN's, so over time, they should have an equal distribution based on your EFT. Further, there will no longer be special collection instructions for EMIPs under [[Change from Service Location to Service, Boarding Loc and Transfer Ready DtTm tmp entry]].

== Actual chart number split per site and per laptop ==

~~{{Discuss|~~

* I think this needs an update as to what we are supposed to do, I don't believe MineMine button is being used? (blezak)

** Correct, I have updated it, please see if it makes sense now. Ttenbergen 11:56, 2020 October 21 (CDT) }}

The split is automatically reflected in [[Cognos Admitter]], no additional filtering needed.

=== Viewing the numbers assigned to a given laptop ===

The assignment is a matter of laptop, chart number ending and the date at which point a specific distribution started. We don't want to store it here on the wiki because it is kind of messy and hard to keep updated. Use [["Show PatientFollow allocation" button]] to see which numbers are assigned to the laptop you are working on during which timeframe.

~~=== How was the distribution initially defined and validated? ===~~

We would essentially take the sum EFTs per program/site and consider them as 100%, and then assign the chart numbers based on that percentage. For example, if a site has 3 collectors that are each a .5EFT, each collector would get 33% of that site's new admissions, so collector A might get charts ending in 00-33, collector B 34-66, and collector C 67-99.

~~{{Collapsable~~

~~| always= The last two digits of chart numbers are evenly distributed and can be used for this.~~

~~| full= * Tina has taken a basic look at the distribution of these numbers and emailed Julie and Trish for feedback. Ttenbergen 17:31, 2019 August 1 (CDT)~~

** Julie did additional analysis by looking at the distribution of the '''last two digits''' numbers from last 5 years 2014 to 2018 as follows: 1) all sites together, 2) each site separately 3) each year from all sites separately and 4) each site and year - the distributions showed similarity with few peaks in some numbers. She grouped the last two digits numbers into a) 10 subgroups (e.g. 0-9,10-19,20-29, …, 90-99 ) and b) 20 subgroups (e.g. 0-4, 5-9, 10-14, 15-19, …, 95-99) and their distributions showed uniformly across subgroups. Each of the 10 subgroups showed counts close to 10% while each of the 20 subgroups showed counts close to 5%. The histograms are in ''X:\CCMDB_Special_Projects\Project_PatientFollow_ChartNumberDistribution''. The results support the viability of using the last two digits of the chart number in allocating patients among the data collectors. Additional analysis info is in S:\MED\MED_CCMED\ChartLastDigitAnalysis\NormalizedCounts_Comparison\2_Paired T-Test and Data.xlsx

*** Additional analyses were done separately for Medicine and Critical Program for each site and 1) each year, 2) each quarter and 3 )each month to determine any seasonal variation across time. The distributions are generally uniform across subgroups with relatively few peaks. However, there seems to be some seasonal variation which is observed more in Critical Care than Medicine Program. The histograms are also in in ''X:\CCMDB_Special_Projects\Project_PatientFollow_ChartNumberDistribution''.

** Julie also did the distribution of the '''first two digits''' numbers and found out that the distribution was skewed to the right. Therefore, this cannot be used as a tool for allocating patients. The distribution is in ''X:\CCMDB_Special_Projects\Project_PatientFollow_ChartNumberDistribution'' .

* I think this is a good starting strategy to allocate patients among the data collectors proportionately in each site.}}

== Entering into the laptop ==

Line 65:

Line 34:

== Follow between medicine/critical care or just within one program ==

For now we are testing this just following patients within the same program, eg if a patient were admitted to a medicine ward, then ICU, and then back to the same medicine ward, then the medicine collector would get the two med admissions, and the CC collector would collect the ICU stay. This may change in the future but would require fairly significant changes to [[CCMDB.accdb Data Integrity Checks]] and other settings in [[CCMDB.accdb]].

=== Programming that would need to be updated to be able to use a laptop across programs ===

* cross checks have been checked as part of previous project, should work

Line 71:

Line 41:

* Converter functions Hosp, Loc, Prog

* ~~not~~ for ~~cross~~-~~programs~~, ~~but still needs doing~~: ~~need~~ to ~~make sure~~ the ~~workload splitter takes~~ into ~~account~~ the ~~start~~ and ~~end dates~~ in ~~case~~ the ~~workload assignments have recently changed~~.

{{Collapsable

| always= old process and questions that were addressed

| full=

=== Would the LOS have any impact on this sharing plan? ===

{{Collapsable

| always= This would not be a problem.

| full= * We discussed whether different [[LOS]] will cause problems with this distribution of patients. We would expect LOS to be equally distributed across Chart Numbers; if it is we should be able to ignore it in distributing patients, since the “average” patient with an “average” chart number would have an “average” LOS.}}

=== [[EMIP]]s ===

[[EMIP]]'s will be distributed to collectors/laptops in the same way as we collect ward patients, using the assigned MRN's, so over time, they should have an equal distribution based on your EFT. Further, there will no longer be special collection instructions for EMIPs under [[Change from Service Location to Service, Boarding Loc and Transfer Ready DtTm tmp entry]].

=== How was the distribution initially defined and validated? ===

We would essentially take the sum EFTs per program/site and consider them as 100%, and then assign the chart numbers based on that percentage. For example, if a site has 3 collectors that are each a .5EFT, each collector would get 33% of that site's new admissions, so collector A might get charts ending in 00-33, collector B 34-66, and collector C 67-99.

{{Collapsable

| always= The last two digits of chart numbers are evenly distributed and can be used for this.

| full= * Tina has taken a basic look at the distribution of these numbers and emailed Julie and Trish for feedback. Ttenbergen 17:31, 2019 August 1 (CDT)

** Julie did additional analysis by looking at the distribution of the '''last two digits''' numbers from last 5 years 2014 to 2018 as follows: 1) all sites together, 2) each site separately 3) each year from all sites separately and 4) each site and year - the distributions showed similarity with few peaks in some numbers. She grouped the last two digits numbers into a) 10 subgroups (e.g. 0-9,10-19,20-29, …, 90-99 ) and b) 20 subgroups (e.g. 0-4, 5-9, 10-14, 15-19, …, 95-99) and their distributions showed uniformly across subgroups. Each of the 10 subgroups showed counts close to 10% while each of the 20 subgroups showed counts close to 5%. The histograms are in ''X:\CCMDB_Special_Projects\Project_PatientFollow_ChartNumberDistribution''. The results support the viability of using the last two digits of the chart number in allocating patients among the data collectors. Additional analysis info is in S:\MED\MED_CCMED\ChartLastDigitAnalysis\NormalizedCounts_Comparison\2_Paired T-Test and Data.xlsx

*** Additional analyses were done separately for Medicine and Critical Program for each site and 1) each year, 2) each quarter and 3 )each month to determine any seasonal variation across time. The distributions are generally uniform across subgroups with relatively few peaks. However, there seems to be some seasonal variation which is observed more in Critical Care than Medicine Program. The histograms are also in in ''X:\CCMDB_Special_Projects\Project_PatientFollow_ChartNumberDistribution''.

** Julie also did the distribution of the '''first two digits''' numbers and found out that the distribution was skewed to the right. Therefore, this cannot be used as a tool for allocating patients. The distribution is in ''X:\CCMDB_Special_Projects\Project_PatientFollow_ChartNumberDistribution'' .

* I think this is a good starting strategy to allocate patients among the data collectors proportionately in each site.}}

== Process to identify Medicine patients from EPR at STB ==

Line 87:

Line 76:

In fact, there is a fair amount of “investigative” work involved in data collection such as running and reconciling 4 EPR lists per unit, and follow up of patient list entries as necessary to ascertain “true/legitimate” patient admissions so as to avoid entry error, duplication, or missing patients.

=== concerns about patient follow due to this complicated process ===

The process to identify patients for collection in our database is currently ill defined, complex and different between collectors and sites.

~~{{Discuss |~~

*It should be questioned then whether amalgamating all data collection units within a site for example there are 4 medicine collection units at STB + EMIPs how to possibly track and reconcile all these lists with any semblance of accuracy. This would be a very labor/time intensive and complicated process, as well as a significant logistical challenge. Use of EPR lists to create further lists/spreadsheets in Excel seems redundant and a risky proposition in terms of inclusion and accuracy. There are also potential PHIA considerations whereas patient information on laptops is currently stored/accessed through a separate program, what are the implications for "personal" and/or redundant storage of patient information on data collector accounts? [[User:Ppiche|Pamela Piche]] 10:19, 2019 September 5 (CDT)

** There would be no extra lists, the allocation would happen automatically within Cognos, so the processes you guys have now would just go away, you would simply enter the patients that show up on your [[Cognos Admitter]], and you wouldn't even see the ones that are not yours. RE concerns about patients that may be missing from Cognos, that is a separate issue: if pts are missing from Cognos, and still don't show up on the 2nd day after their admission, you need to tell me so we can troubleshoot that. If those are addressed then this should no longer be relevant to patientFollow. If this answers the concerns, please remove this discussion. If not, please elaborate. Ttenbergen 21:41, 2020 October 15 (CDT) }}

Line 98:

Line 87:

We needed to implement {{PAGENAME}} in order to be able to streamline collection. Doing it by location meant multiple records per admission, [[Coordination of data between collectors]], and other issues.

Also, it prevented flexible re-allocation of workload according to differing collector EFTs - under the new scheme we can split patient load according to EFT.

=== Implementation ===

* at the Grace starting 2020-09-01

* at HSC and STB Med starting 2020-10-15

* for STB_CC it turns out that the three laptops are substantially different for analysis and reporting perspectives, so it was decided to not group them together on all laptops for now (2020-10)

== Related articles ==

@@ Line 2: / Line 2: @@
 Specifically, we are looking into having a single collector/laptop follow a patient for their whole admission, and how our processes would need to change to accommodate this, and what extra tools we might need.
-== Roll-out ==
-This will be rolled out
-* at the Grace starting 2020-09-01
-* at HSC starting 2020-10-15 (Thursday after Thanksgiving)
-=== Implementation discussions ===
-If there are questions or problems with the change, please put a discussion here.
 == Identifying admissions / Starting collection ==
@@ Line 21: / Line 13: @@
 * '''missing a patient''' - we have been testing the Cognos tool to make sure patients are not missed from it; for PatientFollow we will simply filter that list, so if all patients were on it, they should still all be on the split list
 ** main office can run a check between Cognos Data and our data for the first few weeks to make sure all Cognos data is also in our data
-=== Would the LOS have any impact on this sharing plan? ===
-{{Collapsable
-| always= This would not be a problem.
-| full= * We discussed whether different [[LOS]] will cause problems with this distribution of patients. We would expect LOS to be equally distributed across Chart Numbers; if it is we should be able to ignore it in distributing patients, since the “average” patient with an “average” chart number would have an “average” LOS.}}
 === Medical Records requests ===
 Split of shelves would need to become based on [[Laptop identifier]] (it may already be...);
 {{Discuss |
 * Could an HSC collector please have a look at [[HSC Medical Records requests]] to make sure it is consistent with these changes? Once you have dealt with that, please take out this discussion. Ttenbergen 21:34, 2020 October 15 (CDT)
 }}
-=== [[EMIP]]s ===
-[[EMIP]]'s will be distributed to collectors/laptops in the same way as we collect ward patients, using the assigned MRN's, so over time, they should have an equal distribution based on your EFT. Further, there will no longer be special collection instructions for EMIPs under [[Change from Service Location to Service, Boarding Loc and Transfer Ready DtTm tmp entry]].
 == Actual chart number split per site and per laptop ==
-{{Discuss|
-* I think this needs an update as to what we are supposed to do, I don't believe MineMine button is being used? (blezak)
-** Correct, I have updated it, please see if it makes sense now. Ttenbergen 11:56, 2020 October 21 (CDT) }}
 The split is automatically reflected in [[Cognos Admitter]], no additional filtering needed.
 === Viewing the numbers assigned to a given laptop ===
 The assignment is a matter of laptop, chart number ending and the date at which point a specific distribution started. We don't want to store it here on the wiki because it is kind of messy and hard to keep updated. Use [["Show PatientFollow allocation" button]] to see which numbers are assigned to the laptop you are working on during which timeframe.
-=== How was the distribution initially defined and validated? ===
-We would essentially take the sum EFTs per program/site and consider them as 100%, and then assign the chart numbers based on that percentage. For example, if a site has 3 collectors that are each a .5EFT, each collector would get 33% of that site's new admissions, so collector A might get charts ending in 00-33, collector B 34-66, and collector C 67-99.
-{{Collapsable
-| always= The last two digits of chart numbers are evenly distributed and can be used for this.
-| full= * Tina has taken a basic look at the distribution of these numbers and emailed Julie and Trish for feedback. Ttenbergen 17:31, 2019 August 1 (CDT)
-** Julie did additional analysis by looking at the distribution of the '''last two digits''' numbers from last 5 years 2014 to 2018 as follows: 1) all sites together, 2) each site separately 3) each year from all sites separately and 4) each site and year - the distributions showed similarity with few peaks in some numbers.  She grouped the last two digits numbers  into a) 10 subgroups (e.g. 0-9,10-19,20-29, …, 90-99 ) and b) 20 subgroups (e.g. 0-4, 5-9, 10-14, 15-19, …, 95-99)  and their distributions showed uniformly across subgroups. Each of the 10 subgroups showed counts close to 10% while each of the 20 subgroups showed counts close to 5%. The histograms are in ''X:\CCMDB_Special_Projects\Project_PatientFollow_ChartNumberDistribution''.  The results support the viability of using the last two digits of the chart number in allocating patients among the data collectors. Additional analysis info is in S:\MED\MED_CCMED\ChartLastDigitAnalysis\NormalizedCounts_Comparison\2_Paired T-Test and Data.xlsx
-*** Additional analyses were done separately for Medicine and Critical Program for each site and 1) each year, 2) each quarter and 3 )each month to determine any seasonal variation across time. The distributions are generally uniform across subgroups with relatively few peaks.   However, there seems to be some seasonal variation  which is observed more in Critical Care than Medicine Program. The histograms are also in  in ''X:\CCMDB_Special_Projects\Project_PatientFollow_ChartNumberDistribution''.
-** Julie also did the distribution of the '''first two digits''' numbers and  found out that the distribution was skewed to the right. Therefore, this cannot be used as a tool for allocating patients. The distribution is in ''X:\CCMDB_Special_Projects\Project_PatientFollow_ChartNumberDistribution'' .
-* I think this is a good starting strategy to allocate patients among the data collectors proportionately in each site.}}
 == Entering into the laptop ==
@@ Line 65: / Line 34: @@
 == Follow between medicine/critical care or just within one program ==
 For now we are testing this just following patients within the same program, eg if a patient were admitted to a medicine ward, then ICU, and then back to the same medicine ward, then the medicine collector would get the two med admissions, and the CC collector would collect the ICU stay. This may change in the future but would require fairly significant changes to [[CCMDB.accdb Data Integrity Checks]] and other settings in [[CCMDB.accdb]].
 === Programming that would need to be updated to be able to use a laptop across programs ===
 * cross checks have been checked as part of previous project, should work
@@ Line 71: / Line 41: @@
 * Converter functions Hosp, Loc, Prog
-* not for cross-programs, but still needs doing: need to make sure the workload splitter takes into account the start and end dates in case the workload assignments have recently changed.
+{{Collapsable
+| always= old process and questions that were addressed
+| full=
+=== Would the LOS have any impact on this sharing plan? ===
+{{Collapsable
+| always= This would not be a problem.
+| full= * We discussed whether different [[LOS]] will cause problems with this distribution of patients. We would expect LOS to be equally distributed across Chart Numbers; if it is we should be able to ignore it in distributing patients, since the “average” patient with an “average” chart number would have an “average” LOS.}}
+=== [[EMIP]]s ===
+[[EMIP]]'s will be distributed to collectors/laptops in the same way as we collect ward patients, using the assigned MRN's, so over time, they should have an equal distribution based on your EFT. Further, there will no longer be special collection instructions for EMIPs under [[Change from Service Location to Service, Boarding Loc and Transfer Ready DtTm tmp entry]].
+=== How was the distribution initially defined and validated? ===
+We would essentially take the sum EFTs per program/site and consider them as 100%, and then assign the chart numbers based on that percentage. For example, if a site has 3 collectors that are each a .5EFT, each collector would get 33% of that site's new admissions, so collector A might get charts ending in 00-33, collector B 34-66, and collector C 67-99.
+{{Collapsable
+| always= The last two digits of chart numbers are evenly distributed and can be used for this.
+| full= * Tina has taken a basic look at the distribution of these numbers and emailed Julie and Trish for feedback. Ttenbergen 17:31, 2019 August 1 (CDT)
+** Julie did additional analysis by looking at the distribution of the '''last two digits''' numbers from last 5 years 2014 to 2018 as follows: 1) all sites together, 2) each site separately 3) each year from all sites separately and 4) each site and year - the distributions showed similarity with few peaks in some numbers.  She grouped the last two digits numbers  into a) 10 subgroups (e.g. 0-9,10-19,20-29, …, 90-99 ) and b) 20 subgroups (e.g. 0-4, 5-9, 10-14, 15-19, …, 95-99)  and their distributions showed uniformly across subgroups. Each of the 10 subgroups showed counts close to 10% while each of the 20 subgroups showed counts close to 5%. The histograms are in ''X:\CCMDB_Special_Projects\Project_PatientFollow_ChartNumberDistribution''.  The results support the viability of using the last two digits of the chart number in allocating patients among the data collectors. Additional analysis info is in S:\MED\MED_CCMED\ChartLastDigitAnalysis\NormalizedCounts_Comparison\2_Paired T-Test and Data.xlsx
+*** Additional analyses were done separately for Medicine and Critical Program for each site and 1) each year, 2) each quarter and 3 )each month to determine any seasonal variation across time. The distributions are generally uniform across subgroups with relatively few peaks.   However, there seems to be some seasonal variation  which is observed more in Critical Care than Medicine Program. The histograms are also in  in ''X:\CCMDB_Special_Projects\Project_PatientFollow_ChartNumberDistribution''.
+** Julie also did the distribution of the '''first two digits''' numbers and  found out that the distribution was skewed to the right. Therefore, this cannot be used as a tool for allocating patients. The distribution is in ''X:\CCMDB_Special_Projects\Project_PatientFollow_ChartNumberDistribution'' .
+* I think this is a good starting strategy to allocate patients among the data collectors proportionately in each site.}}
 == Process to identify Medicine patients from EPR at STB ==
@@ Line 87: / Line 76: @@
 In fact, there is a fair amount of “investigative” work involved in data collection such as running and reconciling 4 EPR lists per unit, and  follow up of patient list entries as necessary to ascertain “true/legitimate” patient admissions so as to avoid entry error, duplication, or missing patients.
 === concerns about patient follow due to this complicated process ===
 The process to identify patients for collection in our database is currently ill defined, complex and different between collectors and sites.
-{{Discuss |
 *It should be questioned then whether amalgamating all data collection units within a site for example there are 4 medicine collection units at STB + EMIPs how to possibly track and reconcile all these lists with any semblance of accuracy. This would be a very labor/time intensive and complicated process, as well as a significant logistical challenge. Use of EPR lists to create further lists/spreadsheets in Excel seems redundant and a risky proposition in terms of inclusion and accuracy. There are also potential PHIA considerations whereas patient information on laptops is currently stored/accessed through a separate program, what are the implications for "personal" and/or redundant storage of patient information on data collector accounts? [[User:Ppiche|Pamela Piche]] 10:19, 2019 September 5 (CDT)
 ** There would be no extra lists, the allocation would happen automatically within Cognos, so the processes you guys have now would just go away, you would simply enter the patients that show up on your [[Cognos Admitter]], and you wouldn't even see the ones that are not yours. RE concerns about patients that may be missing from Cognos, that is a separate issue: if pts are missing from Cognos, and still don't show up on the 2nd day after their admission, you need to tell me so we can troubleshoot that. If those are addressed then this should no longer be relevant to patientFollow. If this answers the concerns, please remove this discussion. If not, please elaborate. Ttenbergen 21:41, 2020 October 15 (CDT) }}
@@ Line 98: / Line 87: @@
 We needed to implement {{PAGENAME}} in order to be able to streamline collection. Doing it by location meant multiple records per admission, [[Coordination of data between collectors]], and other issues.
 Also, it prevented flexible re-allocation of workload according to differing collector EFTs - under the new scheme we can split patient load according to EFT.
+=== Implementation ===
+* at the Grace starting 2020-09-01
+* at HSC and STB Med starting 2020-10-15
+* for STB_CC it turns out that the three laptops are substantially different for analysis and reporting perspectives, so it was decided to not group them together on all laptops for now (2020-10)
 == Related articles ==