Journal Entry 7

Frances M. Brzycki Module 7

5 Predictions on the Future of Databases (From a Guy Who Knows Databases) Derrick Harris   URL

Why was this article, blog, post, or multimedia chosen?

This article was selected because it ties into our module with looking at the future of database technology. I’m always interested in seeing what the experts think about the future of technology and seeing if I agree or disagree with their way of thinking.   

 What makes it interesting, appropriate, or reputable? 

Michael Stonebraker “is a lightning rod in the database world and knows his stuff” (Harris, 2013). He is making five predictions regarding the future of databases in the twenty-first century.

Is it an opinion? Case study? Research study? Product review? 

This article is based on Michael Stonebraker’s opinion who is a leader in the database field.

What was the need, problem, issue or trend addressed in the article, blog, post, or multimedia? 

The author wanted to share with the user some key database management system (DBMS) considerations regarding technology prior to selecting a tool.

What was the solution for which technology had an answer? 

The solution was providing the key decision-maker with the information and knowledge to consider before bringing in-house a new database management system (DBMS). The five points to consider include: one size will fit none (consider both SQL and NoSQL to solve your problem), there’s room for a lot of winners (look at the new database system architecture before reverting to legacy relational database systems),

NoSQL will come back down to earth (this product will embrace the Atomicity, Consistency, Isolation and Durability (ACID) for performance and scalability), Oracle will feel the squeeze from SAP (these two corporations compete for customers), Facebook will keep searching for a MySQL replacement (according to Stonebraker Facebook needs to find a more state-of-the-art DBMS solution instead of resorting to legacy system technology) (Harris, 2013).  

What implications might this have in healthcare delivery? 

Database tools are needed to solve healthcare delivery problems. The strategic leaders in the organization need to evaluate the benefits and barriers or bringing a SQL versus NoSQL product in-house.  For example, looking at data storage SQL uses a relational model comprised of rows and columns. Rows contain all of the information about one specific entity and columns are all the separate data points. NoSQL encompasses a host of databases each with different data storage models. The main ones are documents, graph, key-value and columnar. Another example is scalability of a product. SQL scaling is vertical meaning more data and therefore needing a bigger server which can be expensive. NoSQL scaling is horizontal across servers meaning multiple servers can be an inexpensive commodity or cloud instance resulting in cost-savings instead of vertical scaling. You can partition complex operations across many servers/disks and have it work really fast. It all depends on your assessment and selecting the right tool to solve the problem. .

What did you learn from it that might have application for your practice? 

This article solidified my opinion that different databases can be beneficial for solving complex business or healthcare needs and all these databases can share the same “database space” e.g., Oracle versus NoSQL.  The bottom-line is the seasoned developer needs to do their due diligence in determining which database product will deliver the best end product for the client or patient that solves their problem. Databases are tools and the software developer needs to determine if the flathead screwdriver (NoSQL) or Philips screwdriver (Oracle) is needed to do the job.

References

Harris, D. (2013). 5 Predictions on the Future of Databases (From a Guy Who Knows Databases). Retrieved from https://gigaom.com/2013/12/14/5-predictions-on-the-future-of-databases-from-a-guy-who-knows-databases/

Journal Entry 6

Frances M. Brzycki Module 6

Knowledge Management and Intellectual Capital in an Enterprise Information System Souad Demigha  URL

Why was this article, blog, post, or multimedia chosen?

This article was selected because I was curious in discovering how enterprises are leveraging Knowledge Management (KM) and Intellectual Capital (IC) in information systems in the twenty-first century. The successful enterprise information systems integrates both KM and IC (Demigha, 2015).

What makes it interesting, appropriate, or reputable? 

Demigha  examines a practical methodology that aligns the  KM components comprised of people, processes and technology with the IC components of human capital, relational capital e.g., marketing communications between customers and suppliers and structural resources e.g., processes in organizational culture.

Is it an opinion? Case study? Research study? Product review? 

This article is based on a research study conducted in Paris France by the department of Computer Science.

What was the need, problem, issue or trend addressed in the article, blog, post, or multimedia? 

The author wanted to educate the user on the best KM methodology to meet their need. The author analyzed the process-centered and product-centered approach. The process-centered "understands KM as a social communication process" and product-centered "focuses on knowledge documents, their creation , storage and reuse in computer-based corporate memories" (Demigha, 2015). Demigha research team went with the integrated Business Process Management (BPM) approach.  The author believed knowledge is key and is integrated in the business on many levels e.g., contextual, experimental.

What was the solution for which technology had an answer? 

The integrated Business Process Management (BPM) approach provided several advantages for KM. Some of these advantages include providing relevant context and navigation in Knowledge Management Systems (KMS), integrating KM towards the value chain, applying widely accepted management methods and supporting KM processes that impact KMS design and integration (Demigha, 2015).   BPM is designed to model enterprise wide business process solutions.

What implications might this have in healthcare delivery? 

These organized integrated business process workflows help health care delivery organizations and systems identify and streamline their redundant information bottle necks and strive for systems that are more efficient between departments and ultimately organizations. Enterprise success depends on how knowledge is acquired, used and shared in a project or program. Process cycle of knowledge allows enterprises to enhance their organizational learning. It has been proven that IC can positively and significantly influence KM productivity (Demigha, 2015).

What did you learn from it that might have application for your practice? I learned that KM uses both explicit and tacit knowledge. Explicit knowledge is existing knowledge that is captured and  disseminated.  Tacit knowledge is new knowledge that is spread throughout an organization. KM has two key roles: capture and document individual explicit and tacit knowledge and disseminate this knowledge within an organization (Demigha, 2015).

References

Demigha, S. (2015). Knowledge Management and Intellectual Capital in an Enterprise Information System.   Retrieved from http://search.proquest.com/openview/dd82218cdc957bbc799150e69dc20825/1?pq-origsite=gscholar

  

Journal Entry 5

Frances M. Brzycki Module 5

4 Ways Healthcare Data Analysts Can Provide Their Full Value Russ Staheli   URL

Why was this article, blog, post, or multimedia chosen?

One of the many hats I wear is the role of a data analyst. I found this article to peek my interest and wanted to explore what additional skills Russ found important that an effective analyst should possess. “I found 90-95 percent of my time was spent managing data, not analyzing it. I didn’t have the tools I needed” (Staheli, 2011).

What makes it interesting, appropriate, or reputable? 

Russ examines the healthcare data analysis lifecycle. He states “there are three stages of transforming raw data into meaningful analytics: data capture, data provisioning and data analysis”.

Is it an opinion? Case study? Research study? Product review? 

This article is an expert opinion by Russ Staheli who specializes in quality performance outcome and analysis.  

What was the need, problem, issue or trend addressed in the article, blog, post, or multimedia? 

The author wanted to educate the user on the healthcare data analysis lifecycle comprised of data capture e.g., people, processes, and devices being in the right format, data provisioning that enable clinicians to work through quality improvement issues and lastly data analysis examining data quality, data discovery, interpretation and presentation.

I found it interesting that you need to perform each one of these steps in order to achieve sustainable, meaningful healthcare analytics and not to do these as separate steps. “Interpretation is the step most people think of when analyzing data. It turns out it is the smallest sub-step in a long process” (Staheli, 2011).

What was the solution for which technology had an answer? 

Besides having a robust Enterprise Data Warehouse to help the analyst in their problem-solving. The article suggested to provide analyst with a “sandbox” to tinker and test their findings. To me this is a no brainer when you are doing “what if” analysis and want to test out your hypothesis prior to moving the changes into a production environment. Staheli suggests the analyst need the right tools to perform his/her job. For instance, business intelligence (BI) tools to forecast, trends graphics etc.  and trend data. Lastly, the analyst should have direction that allow them to drill down on the data.

What implications might this have in healthcare delivery? 

You can have the best data, however if it isn’t presented in a logical, organized fashion and not understood it doesn’t provide meaning to the reader. I’m of the opinion the presenter needs to be the story teller to weave the picture of the problem that is being analyzed and provide possible alternatives if they exist.

What did you learn from it that might have application for your practice? I look forward to reading the book regarding “The Visual Display of Quantitative Information” that examines the best way to display data for precise, effective, quick analysis using statistical graphics and detailed analysis.

References

Staheli, R. (2011). 4 Ways Healthcare Data Analysts Can Provide Their Full Value Retrieved from https://www.healthcatalyst.com/healthcare-analytics-best-practices

Journal Entry 4

Frances M. Brzycki Module 4

Understanding The Healthcare Database: Purposes, Strengths, and Weaknesses Drew Cardon   URL

Why was this article, blog, post, or multimedia chosen?

I'm always interested in learning what experts deem good design when building Online transactional processing (OLTP) databases.  I access many third party databases and home-grown databases and I’ve seen both good and poor design.  I’m of the opinion solid design is key to building an effective and powerful database tool and the time invested in doing this upfront is well spent. Electronic Health Record (EHR) is an example of an OLTP. The main strength of an OLTP is speed (Cardon, 2011). An example would be to look up the patients vital signs from their last office visit.

What  makes it interesting, appropriate, or reputable? 

Supporting key decision-makers in both the hospital and physician setting I see my share of OLTP clinical systems ranging from CPOE, Finance and claim data to name a few. Some of these databases are integrated and some of them are not.  That is were the challenge exists for both the clinical business users that analyze the data and the information technology department that maintain the backend of these OLTP applications. For instance, our organization just rolled out the ICD-10 codes from ICD-9, needless to say this was a mammoth undertaking with extensive collaboration and coordination between the business and information technology teams.

Is it an opinion? Case study? Research study? Product review? 

This article is an expert opinion by Drew Cardon who specializes in data architect and information technology implementation.

What was the need, problem, issue or trend addressed in the article, blog, post, or multimedia? 

The author wanted to educate the user on how databases worked and the role they play in healthcare. One of the biggest benefits of OLTP is the amount of data that can be captured and stored.  This data can be transformed into business intelligence and enabling key stakeholders to make better informed decision for patient care and cost-saving metrics (Carlson, 2011).  As Carlson pointed out the benefit of having all this data is also a curse.  Too much data can cause information overload to CEOs to clinicians. The information needs to be “targeted and actionable” per Carlson.

What was the solution for which technology had an answer? 

The solution to manage all this data is called “Enterprise Data Warehouse” (EDW).  The database to manage this is called Online Analytical Processing or OLAP for short.  

What implications might this have in healthcare delivery? 

Both OLAP and OLTP have a place in the organization. These are both tools and like any good tool they need to perform the job they were designed to do.  The OLAP tool will focus on analytical data mining and the OLTP tool will focus on the transaction processing regarding data and information for the business.  

What did you learn from it that might have application for your practice? 

Just like a good cook a good software developer has tools that perform specific functions to accomplish a goal and this needs to be kept in mind when feeling overwhelmed with the flood of raw data.

References

Cardon, D. (2011). Understanding The Healthcare Database: Purposes, Strengths, and Weaknesses  

Retrieved from https://www.healthcatalyst.com/healthcare-database-purposes-strengths-weaknesses

Journal Entry 3

Frances M. Brzycki Module 3

How to design next-generation EHR data models, Shahid Shah URL  

Why was this article, blog, post, or multimedia chosen?

I'm always interested in learning what experts deem good design when building and/or modifying existing EHR data models.   I've worked on EHRs that were designed well and ones that weren't.  This topic is germane to our database discussion in class. Today's patient management team provides disjointed care and don't know what each other is doing for the patient in real-time (Shah, 2012). 

What  makes it interesting, appropriate, or reputable? 

Working in information and business for over 30 years it was encouraging to read that in designing a successful system the people on the project team must be comprised of both the clinical user and information technology specialist.  The significant observation is the team isn't purely comprised of business users and vice versa not comprised of only technical experts.  It needs to be a team of hybrid stakeholders.   I'm of the opinion it's all about engaging your user and giving them a great experience when using the application or system. If this isn't a core objective the system won't be used.

Is it an opinion? Case study? Research study? Product review? 

This article is an expert opinion by Shahid Shah who specializes in  healthcare IT enterprise software  with an emphasis on EHR.

What was the need, problem, issue or trend addressed in the article, blog, post, or multimedia? 

The author shared with the reader it is important to have clinicians "not a bunch of engineers and other geeks around a table" (Shah, 2012) when building a  system.  Additionally, "data modeling is about understanding all of the users of the data, the relationships, attributes and most importantly how the data management will grow and change in the future" (Shah, 2012).

What was the solution for which technology had an answer? 

Besides understanding the needs of all the users of the data, building primary and foreign keys that provide flexibility when searching and querying the data is paramount in solid data model EHR design. Additionally, Shah supports long-term storage and change management control of all entity attribute that are updated in the system.  

What implications might this have in healthcare delivery? 

I have mixed feelings about this data model design. While flexibility is important to building good EHR primary and foreign keys for efficiencies the designer can take this too far and over engineer the primary and foreign keys and bring the system down regarding speed.  The bottom-line the designer needs to be mindful and build a system that has a  good balance between efficiency and speed. 

What did you learn from it that might have application for your practice? 

As a software  developer I would be mindful and build a system that has a  good balance between efficiency and speed.  I would not over engineer the primary and foreign keys.

References

Shah, S. (2012). How to design next-generation EHR data models. Healthcare IT News. Retrieved from                 http://www.healthcareitnews.com/blog/how-design-next-generation-ehr-data-models