I need to Validate SSN in such a way that redundant entry should not appear. for example if a message arrives for Patient A with ssn 123-45-6789 and next time if any message comes for Patient B with same ssn, integration engine should catch this. I am using cloverleaf as a integration engine and need to validate this.
please let me know if any logic can be suggested.
Thanks,
Anupam..
That wouldn't be a valid use case for an integration engine. You should look into acquiring a master patient index application and integrate it into your message flow.
Even then, with HL7 messaging there is generally no 100% reliable source of truth to tell you who is Patient A and who is Patient B. For example, if you get a second message for SSN 123-45-6789 and the name doesn't match the first patient is that because it's really a different person or did the patient perhaps legally change her name?
Finally relying on SSNs in health care systems is generally considered a bad idea due to the security and privacy concerns. Most modern systems actually filter out SSNs and rely on other fields to identify the patient.
Related
I always think that an address data is a value object since it is immutable and its equality is defined by the same data in all fields. For example, a billing address in a part of a payment and a shipping address is a part of an order or a fulfillment. When someone changes her/his address, a new address data is needed. But, every single sample code/application, I have run into, has an address data as an entity, which its DB table has its own ID. It would make a sense if a system wants to keep track of all addresses where all business activities/events occur. I, however, don't see such intention in those sample code/application. Do I miss something in the regard?
You can't generalize.
Examples are one thing, real world problems are another. You can't say that for all projects one solution fits it all.
I'll give you an example I had in a project conserning aggregate roots.
Logically and legally a subsidiary is an extension of its company, eg. Walmart has its HQ with tax number and everything and subsidiaries without tax number where the actual stuff is sold. Logically, for applying to a goverment funding or something similar, the HQ sends a request for its subsidiary. Here, Walmart HQ is an aggregate root and its subsidiary is a part of an aggregate in funding procedures.
This is a logical example.
What I had is that a subsidiary can legally apply for state funding without the knowledge of HQ! Therefor, HQ is not an aggregate root anymore, but a subsidiary is. It was extremely illogical, but those were the business requirements.
The point is the same with your value object question. Although you can use Address as an example that it is an entity or a value object, it is the requirements of the business that dictate what an address is, and not what is logical.
Pre-note: there are domains where an address should be an entity, like a mail service; we do not talk about those domains
From my experience, people tend to implement an address as an entity because of the persistence: it is easier to persist an address as a sub-entity to a relational database than to persist a value object because of the entities ID that act as primary keys in the storage table.
However, there are tactics that permit storing a value object as an database entity but still using it just as a value object, as it should be. Vaughn Vernon shows how to do this in his book, Chapter 6, sub-chapter Persisting Value Objects.
I'm creating a messaging system for a e-learning platform and there are some design concerns that I'd like some feedback on.
First of all, it is important for me and my system to be highly modifiable in the future. As such, maintaining a fairly high normalization across my tables is important.
On to how my system will work:
All members (students or teachers) are part of a virtual classroom.
Teachers can create tasks and exercises in these classrooms and assign them to one or multiple students (member_task table not illustrated).
A student can request help for a specific task or exercise by sending a message to the teachers of the classroom.
Messages sent by students are sent to all the teachers. They cannot address a message to a specific teacher.
Messages sent by teachers can be addressed to one or more students.
Students cannot send messages to other students.
Messages behave like chat, meaning that a private conversation starts between a student and all teachers when they send a message.
Here's the ER diagram I made:
So my question is, is this table normalized properly for my purpose? Is there anything that can be done to reduce redundancy of data across my tables? And out of curiosity, is it in BCNF?
Another question: I don't intend to ever implement delete features anywhere in my system. Only "archiving" where said classroom/task/member/message/whatever is simply hidden/deactivated. So is there any reason to actually use FK?
EDIT: Also, a friend brought to my attention that the Conversations table might be redundant, and it kinda feels so. Thoughts?
Thanks.
In response to your emphasis on "modifiability" which I'm taking to mean with respect to application and schema evolution I'm actually going to suggest a fairly extreme solution. Before that some notes some aspects you've mentioned. First, foreign keys represent meaningful constraints in your data. They should always be defined and enforced. Foreign keys are not there just for cascading delete. Second, the Conversations table is arguably redundant. It would make sense if you had a notion of "session" of chat which would correspond to a Conversation. Otherwise, you just have a bunch of messages throughout time. The Conversation table could also enable a many-to-many relation between messages and tasks/exercises if you wanted to have chats that simultaneously covered multiple exercises, for example.
Now for the extreme suggestion. You could use 6NF. In particular, you might look at its incarnation in anchor modeling. The most notable difference in this approach is each attribute is modeled as a different table. 6NF supports temporal databases (supported in anchor modeling via "historized" attributes/ties). This means handling situations like a student being associated to a task now but not later won't cause all their messages to disappear. Most relevant to you, all schema modifications are non-destructive and additive, so no old code breaks when you make a change.
There are downsides. First, it's a bit weird, and in particular anchor modeling (somewhat gratuitously?) introduces a bunch of new terms. Second, it produces weird queries for most relational databases which they may not optimize well. This can sometimes be resolved with materialized views. Third, at the physical level, every attribute is effectively nullable. Finally, the tooling and support, while present, is pretty young. In particular, for MySQL, you may only be "inspired by" what's provided on the anchor modeling site.
As far as the actual database model would go, it would look roughly similar. Anchor modeling uses the term "anchor" for roughly the same thing as an entity, and "tie" for roughly the same thing as a relation. For simplicity, dropping the Conversation relation (and thus directly connecting Message to Task), the image would be similar: you'd have an anchor for Classroom, Member, Message, and Task, and a tie replacing Recipient that you might called ReceivedMessage representing the relation of "member received message message". The attributes on your entities would be attribute nodes. Making the message attribute on the Message anchor historized would allow messages to be edited if desired and support a history of revisions.
One concern I have is that I don't see a Users table which will hold all the students and teachers info (login, email, system id, role, etc) but I assume there is something similar in our system?
Now, looking into the Members table: usually students change classes every semester or so and you don't want last semesters' students to receive new messages. I would suggest the following:
Members
=============
PK member_id
FK class_id
FK user_id
--------------
join_date
leave_date
active
role
The last two fields might be redundant:
active: is an alternative solution if you want to avoid using dates. This will become false when a user stops being member of this class. Since there is not delete feature, the Members entry has to be preserved for archive purposes (and historical log).
role: Depends on how you setup Users table and roles in your system. If a user entry has role field(s) then this is not needed. However, this field allows for the same user to assume different roles in different classes. Example: a 3rd year student, who was a member of this class 2 years ago, is now working as TA/LA (teaching/lab assistant) for the same class. This depends on how the institution works... in my BSc we had the "rule": anyone with grade > 8.5/10 in Java could volunteer to do workshops to other students (using uni's labs). Finally, this field if used as a mask or a constant, allows for roles to be extended (future-proof)
As for FKs I will always suggest using them for data consistency. Things can get really ugly really fast without FKs. The limitations they impose can be worked around and they are usually needed: What is the purpose of archiving a message with sender_id if the sender has been deleted by accident? Also, note that in most systems FKs are indexed which improves the performance of queries/joins.
Hope the above helps and not confuse things :)
I'm setting up a database to run practice management software for lawsuits. When adding people associated with the suit, some of them will be repeat parties (eg lawyers for the firm) and some will be one-off parties (witnesses, etc). Looking for input on whether to make 1 "case users" table with values for a user id as well as the rest of the info for the one-off parties, or make 2 tables, one being "case users-firm" with 2 columns for the case and the user id, and another "case users-other" with the one-off party information.
It's pretty common to have a "Persons" table, filled with things common to all people like first name, last name, and a primary key. Then store that key everywhere you might want a person. Who knows? Your lawyer might be a witness. No need to duplicate the entry, when they are in fact the same person.
I don't see why you would want to have two tables, especially if they are going to have mostly the same fields. On the other hand, if you want to keep a lot more info for the attorneys than for the witnesses (or the other way around) two tables could be beneficial...
Just one other point to add. For privacy and data protection it is best not to store, encourage your users to store, or even set up a framework for storing, any more personal data than you actually need for your purposes. ( In the UK, think 'Data Protection' law ). So unless you are planning on evolving a kind of legal-profession facebook, I would keep the tables separate on this occasion.
I've been thinking about this all evening (GMT) but I can't seem to figure out a good solution for this one. Here's the case...
I have to create a signup system which distinguishes 4 kinds of "users":
Individual sign ups (require address info)
Group sign ups (don't require address info)
Group contact (require address info)
Application users (don't require address info)
I really cannot come up with a decent way of modeling this into something that makes sense. I'd greatly appreciate it if you could share your ideas.
Thanks in advance!
Sounds like good case for single table inheritance
Requiring certain data is more a function of your application logic than your database. You can definitely define database columns that don't allow NULL values, but they can be set to "" (empty string) without any errors.
As far as how to structure your database, have two separate tables:
User
UserAddress
When you have a new signup that requires contact info, your application will create records in both tables. When a new signup doesn't require address info, your application will only create a record in the User table.
There are a couple considerations here: first, I like to look at User/Group as a case of a Composite pattern. It clearly meets the requirement: you often have to treat the aggregate and individual versions of the entity interchangeably (as you note). Implementing a composite in a database is not that hard. If you are using an ORM, it is pretty simple (inheritance).
On the other part of the question, you always have the ability to create data structures that are mostly empty. Generally, that's a bad idea. So you can say 'well, in the beginning, we don't have any information about the User so we will just leave all the other fields blank.' A better approach is to try and model the phases as if they were part of an FSM. One of the clearest ways to do this in this particular case is to distinguish between Users, Accounts and some other more domain-specific entity, e.g. Subscriber or Customer. Then, I can come and browse using User, sign up and make an Account, then later when you want address and other personal information, become a subscriber. This would also imply inheritance, and you have the added benefit of being able to have a true representation of the population at any time that doesn't require stupid shenanigans like 'SELECT COUNT(*) WHERE _ not null,' etc.
Here's a suggestion from my end after weighing pro's and con's on this model. As I think the ideal setup is to have all users be a user entity that belong to a group without differentiating groups from individuals (except of course flag a group contact person and creating a link with a groups table) we came up with the alternative to copy the group contact user details to the group members when they group is created.
This way all entities that actually are a person will get their own table.
Could this be a good idea? Awaiting your comments :)
I've decided to go with a construction where group members are separated from the user pool anyway. The group members eventually have no relation with a user since they don't require access to mutating their personal data, that's what a group contact person is for. Eventually I could add a possibility for groups to have multiple contact persons, even distinguishing persons that are or are not allowed to edit any member data.
That's my answer on this one.
What is the best-practice for maintaining the integrity of linked data entities on update?
My scenario
I have two entities "Client and
Invoice". [client is definition and
Invoice is transaction].
After issuing many invoices to the
client it happens that the client
information needs to be changed
e.g. "his billing address/location
changed or business name ... etc".
It's normal that the users must be
able to update the client
information to keep the integrity of
the data in the system.
In the invoice "transaction entity"
I don't store just the client id but
also all the client information related to the
invoice like "client name, address,
contact", and that's well known
approach for storing data in
transaction entities.
If the user created a new invoice the
new client information will be
stored in the invoice record along
with the same client-id (very
obvious!).
My Questions
Is it okay to bind the data entities
"clients" from different locations
for the Insert and the update?
[Explanation: if I followed the
approach from step 1-4 I have to
bind the client entity from the
client table in case of creating new
invoice but in case of
updating/printing the invoice I have
to bind the client entity from the
invoice table otherwise the data
won't be consistent or integer...So
how I can keep the data integrity
without creating spaghetti code in
the DAL to handle this custom
requirements of data binding??]
I passed through a system that was
saving all previous versions of an
entity data before the update
"keeping history of all versions".
If I want to use the same method to
avoid the custom binding how I can
do this in term of database design
"Using MYSQL"? [Explanation: some
invoices created with version 1.0 of
the client then the client info
updated and its version became 1.1
and new invoices created with last
version...So is it good to follow
this methodology? and how I should
design my entities/tables to fulfil the requirements of entity
versioning and binding?
Please provide any book or reference
that can kick me in the right
direction?
Thanks,
What you need to do is leave the table the way it is. You are correct, you should be storing the customer information in the invoice for history of where the items were shipped to. When it changes, you should NOT update this information except for any invoices which have not yet been shipped. To maintain this type of information, you need a trigger on the customer table that looks for invoices that have not been shippe and updates those addresses automatically.
If you want to save historical versions of the client information, the correct process is to create an audit table and populate it through a trigger.
Data integrity in this case is simply through a foreign key to the customer id. The id itself should not ever change or be allowed to change by the user and should be a surrogate number such as an integer. Becasue you should not be changing the address information in the actual invoice (unless it has not been shipped in which case you had better change it or the product will be shipped to the wrong place), this is sufficent to maintain data integrity. This also allows you to see where the stuff was actually shipped but still look up the current info about the client through the use of the foreign key.
If you have clients that change (compaies bought by other companies), you can either run a process onthe server to update the customer id of old records or create a table structure that show which client ids belong to a current parent id. The first is easier to do if you aren;t talking about changing millions of records.
"This is a business case where data mnust be denormalized to preserve historical records of what was shipped where. His design is not incorrect."
Sorry for adding this as a new response, but the "add comment" button still doesn't show.
"His design" is indeed not incorrect ... because it is normalized !!!
It is normalized because it is not at all times true that the address corresponding to an invoice functionally depends on the customer ID exclusively.
So : normalization, yes I do think so. Not that normalization is the only issue involved here.
I'm not completely clear on what you are getting at, but I think you want to read up on normalization, available in many books on relational databases and SQL. I think what you will end up with is two tables connected by a foreign key, but perhaps some soul-searching per previous sentence will help you clarify your thoughts.