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Module 4: Ocean Studies Module 4 Agenda Basic Concepts for Research on Ocean Creating your first study and exporting data Pseudonymization Not just another.

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Presentation on theme: "Module 4: Ocean Studies Module 4 Agenda Basic Concepts for Research on Ocean Creating your first study and exporting data Pseudonymization Not just another."— Presentation transcript:

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2 Module 4: Ocean Studies

3 Module 4 Agenda Basic Concepts for Research on Ocean Creating your first study and exporting data Pseudonymization Not just another long word… Research Study Features Advanced features for comprehensive studies

4 Why Use Ocean for Research  Low-Cost Potential for "do it yourself" without building an app Pseudonymization engine eliminates need for participant key management in spreadsheets  Designed for Primary Care EMR integration and drop into existing Ocean workflows Multi-site studies and automatic recruitment rules  Secure All the security you'd expect from CognisantMD

5 A Variety of Research Scenarios Example: Patient Experience Surveys at many FHTs You want to use your tablets to do anonymous surveying of patients for quality improvement or clinical research. Example: St. Michael's Hospital and Health Equity You want to capture anonymous data for clinic decision support, while also using patient responses for clinical care in that visit. Example: Mount Sinai LSS Research You want to conduct formal clinical research on a small sample (100 patients for example) Example: Dr. Harold Kim, Allergist in Kitchener; various public health initiatives in Ontario A 3 rd party wants to conduct large-scale primary care research at multiple primary care locations (with different EMRs)

6 Ocean Studies Encrypted Responses Patient's Chart in EMR Depersonalized Responses Ocean Study Repository ? If the EForm "data security" is set to anonymous or hybrid If the EForm "data security" is set to encrypted or hybrid

7 Ocean Studies: the Basics  A study repository holds data until you delete it in an encrypted format in the Ocean system (in Canada)  Has exactly one EForm associated with it  Has configuration options that control aspects of the data collection  Deleting a Study repository deletes the encryption key and the collected data permanently  You can export data at any time; the export does not remove the data from Ocean  Although can be created manually, normally they are automatically generated for you when a study EForm is completed

8 Connecting EForms and Studies  Every EForm has a data security setting Encrypted: for individual patient care; encrypted using a one-time key Anonymous: depersonalized, stripped of PHI* and stored in the Ocean research repository Hybrid: both * unless explicitly included as a field in research questionnaire form

9 Your clinic joins a research study on chronic pain. Happily, they are basing it on your assessment tool due to extensive validation in clinical settings. 1.Open your Simple Pain Tool from Module 3 2.Change the data security type to hybrid 3.Complete the questionnaire 4.Export the data from the studies tab 5.Set the data security type to anonymous and try again. What's different? Exercise: The Pain Study

10 Some Observations on your Exported Data  The eForm item refs are used as a column reference You can "override" these in the editor  The submission source tells you what device was used  The data is based on the value not the display  The source site is your site More on multi-site studies later  A participant key column contains jibberish More on this in the next section

11 Robustness of Study Data  The study responses are stored a bit like this: studyEForm = 'myPainToolRef'  myFirstQuestionRef : 'Y'  MySecondQuestionRef : 'N'  A study response never changes once it is captured  The export button takes the current version of the eForm and displays answers for each item in that form based on ref  That means that: It's possible to change a questionnaire without corrupting your data set You can end up with invisible data if you change a ref after collecting some data (but it isn't lost)

12 Pseudonymization  Scenario: you are doing a longitudinal research study. You want to assess patients at t=0 and t=6 months. You need to collate the responses such that patient Bob's responses at both points in time can be compared Proper blinding is required; the patient identity must not be known to the researchers and collected data must be depersonalized Some of the disadvantages of longitudinal studies include the fact that they take a lot of time and are very expensive … they are not very convenient. (http://en.wikipedia.org/wiki/Longitudinal_study)

13 Pseudonymization Pseudonymization is a procedure by which the most identifying fields within a data record are replaced by one or more artificial identifiers, or pseudonyms. There can be a single pseudonym for a collection of replaced fields or a pseudonym per replaced field. The purpose is to render the data record less identifying and therefore lower customer or patient objections to its use. Data in this form is suitable for extensive analytics and processing. (http://en.wikipedia.org/wiki/Pseudonymization)

14 Pseudonymization  Implemented in Ocean using Participant Keys  Auto-generated pseudonyms for patients are added to studies data by default Incorporates surname, birthdate, sex and part of the healthcard number if available If any of surname, birthdate and sex are missing, participant key is blank Different for different patients, the same for the same patient Impossible to reverse engineer to identify a patient  Example: "54b93a04e4b098d3d7053f9f"

15 Form Memory vs. Participant Keys Form Memory "Hashes"Participant Keys Based on surname, birthdate, sex (plus health number if available) Same but "salted" with a study-specific key to protect patient identity Used in scripting to drive form and tablet behaviour (e.g. "daysSinceLastCompletion > 365") Captured with study data Used in clinical and research scenarios Only relevant for research

16 Let's take a look at the study that was auto-created. 1.Go the Studies tab and click "configure" for your study 2.Notice that the pseudonymization can be disabled for true anonymity 3.Enable online access 4.Visit the link and complete the form 5.Export the data; notice the submission source Exercise: Configuring a Study

17 Multi-Form Studies  Scenario: You want to do a baseline pain assessment using the Simple Pain Tool but you want to have a simpler interim assessment at t=3months.  Introduces a twist – recall that study submissions are "salted" to protect patient identity The same patient completing different study forms would end up with different participant keys!  Solution: Participant Key Alignment Configures a study to use the same participant keys as another

18 You've been asked to coordinate a primary care research study at six sites using different EMRs. 1.Create a Very Simple Pain Tool with a single pain scale 2.Create a study for it (if not auto-created). Align the participant keys with the Simple Pain Tool. 3.Invite the Demo Site to participate. 4.Complete the two assessments on your tablet or online. 5.Instructor will send you a web questionnaire for both assessments; complete those 6.Export the data and review Exercise: Multi-Site, Multi-Form Study

19 End of Module 4 Quiz 1.What are the inputs to a participant key? 2.List 4 ways that you could have patients or clinicians complete an Ocean study questionnaire 3.You have a t=0 and a t=12 month assessment for a longitudinal study. You review the data and the participant keys for John Smith are different. What might have happened?

20 Feedback Survey


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