Monthly Archives

January 2017

Moving from Manual Processes to New Research Methodologies

By | Data Sheets


Spreadsheets are a great tool for collecting data on patients within the context of clinical research, as well as being familiar and free.  But do Spreadsheets truly address the needs of the modern researcher?

Medical innovations and technological breakthroughs are attributed, to a large degree, to the accumulation and use of data.  As the amount of data and its complexity increase, Spreadsheets begins to exhibit shortcomings.  These gaps are filled by Cloud Data Management Systems (CDMA), which bring with them a set of tools that accommodate large data quantities, comply with regulatory constraints and provide useful insight.

When Spreadsheets No Longer Delivers

While Spreadsheets are a great tool for many purposes, they have some significant shortcomings in the area of clinical research – particularly when the amount of data collected increases beyond a few hundred records.

  • Spreadsheets are two-dimensional products, which makes it difficult to create and view depth of data. In contrast, CDMAs are multi-dimensional products that allow you to dig deep into any field to view additional detail through the use of hyperlinks.
  • Researchers that work in groups find it difficult to share spreadsheet databases since spreadsheets, by definition, are not collaborative products. CDMAs are designed for groups of researchers working across the room from each other, or across the globe.  They are housed in a secure Cloud, allowing multiple users to access and modify data at any given time, based on a set of administrator-controlled permissions.
  • Researchers and the organizations in which they live could greatly benefit from the sharing of information between clinical research and care systems. Interoperability between EHR systems, for example, and spreadsheets is non-existent and manual data sharing is extremely cumbersome and time consuming.  Most CDMAs interface clinical care systems that contain APIs and enable the simple migration of data with alerts that identify errors and inconsistancies.
  • Creating a form or questionnaire in a spreadsheet is far more cumbersome and time-consuming than with CDMAs, and ultimately contains a far more limited set of built-in abilities.
  • An important element of clinical research is the integrity of the data collected. Data entered into spreadsheets could contain errors and inconsistencies, which are difficult to identify and correct.  CDMAs often have built-in data validation tools that alert users about errors and inconsistencies.
  • Of critical importance in clinical research is data security. CDMAs typically comply with HIPPA rules, employing a series of security measures around their cloud, and have built data protection mechanisms into their solution such as two-factor access authentication, methods for detecting the potential sharing of PHI, and more.  Spreadsheets offer no security measures beyond password protection.
  • Most spreadsheets enable the use of sophisticated queries but require deep understanding of the product and often of the use of formulas. CDMAs include filtering and query tools that can be performed in seconds or minutes.

These are just a few examples of the shortcomings of spreadsheets for clinical research.  CDMAs, by contrast, are robust solutions that provide researchers with advanced data-entry and data management and insight tools.  It is really like comparing a go-kart with no engine to an S-Class Mercedes Benz!

Case Study with the Center for Specialized Medical Examinations

By | Customer Stories

Institute Overview

MALRAM (the Institute for Special Medical Services) is a unit within Sourasky Medical Center in Tel Aviv where routine annual general health check-up evaluations are performed on individuals as a preventive measure as well as to identify specific ailments.

Researchers at the Institute have been performing research since 2003, collecting more than 5,000 pieces of data on each of more than 20,000 subjects.  In addition to patient-derived information, other data sources include the EHR system as well as external data on air pollution and the Israel National Cancer Registry.


In 2003 the Institute implemented a customized software solution designed for researchers, which was used over a period of 5 years.  The software became cumbersome and expensive to use and service was limited.  They then began using Excel and Access, but as the amount of data grew, its shortfalls became more pronounced:

  • Multiple databases were used to collect information
  • A significant amount of time was dedicated to copying data from other systems and pasting into the database since it did not interface with them
  • Dependency on IT personnel resulted in significant delays in drawing clinical data from the EHR
  • Manual data entry was unreliable and error-prone and was influenced by the work habits of each person entering the data
  • The amount and complexity of data became cumbersome to manage
  • Calculations were performed manually in Excel
  • Modifying and updating questionnaires was inflexible

“The tools we used for research became ineffective, mainly because of the large amounts of data we collected. Data+ created a unified database.  The interfaces alone save us more than 75% of the time we used to spend on copying and pasting clinical information.  Using Data+ means we have complete control over the system and do not depend on others to provide us clinical care information, to make changes to forms and questionnaires, create and reposition fields, establish new research, etc.  With Data+ we work more efficiently.”

Prof. Sharon Toker, Faculty of Management, Tel Aviv University

“The team at Data+ truly has a “can-do” attitude. They’ve worked closely with us from the start, learning from our experience and needs and designing relevant, tailored solutions.  The ability to pull up-to-date, reliable data any time from other systems like the EHR has brought us tremendous value.  The mechanism that assures data integrity has proven very valuable as well.”

Dr. Shani Shenhar – Tsarfaty, researcher at Sourasky Medical Center


Prior to working with Data+, researchers at the Institute used Excel and Access for data collection and management.  When Data+ was implemented, it enabled users to upload already collected data, while automatically identifying inaccuracies, incompatibilities and missing data.  It further addressed the following challenges:

  • Single, secure database containing reliable data, which could be used for sophisticated research and analysis.
  • Seamlessly and ad-hoc pull data from the EHR system through a direct interface
  • Custom-design automatically calculate scores
  • Automated patient engagement tools.  Independently-built questionnaires and patient feedback reports
  • Keyboard-based UI, designed for typists needs

MALRAM Users Say…

“The system is very intuitive and offers all the functionalities you need. When I explained it to people, it didn’t take more than once”

“The system minimizes errors and prevents inconsistency. With hard copies, sometimes people would skip certain fields, whether intentionally or not. With Data+, that doesn’t happen. Also, you can always go back and correct any mistakes you made”

“In one of our departments, each process is different and requires different templates. NextStep built a custom feature that enables us to create our own templates independently, at any given time, which is a big advantage”

“One of Data+ biggest advantages is flexibility and simplicity. It doesn’t have hard-set limitations. I can perform any action without too much effort”