Disadvantages of Spreadsheets – Obstacles to Compliance in the Healthcare Industry

Most of the regulatory compliance issues we talked about concerning spreadsheets have been related to financial data. But there are other kinds of data that are stored in spreadsheets which may also cause regulatory problems in the future.

In the US, a legislation known as HIPAA or Health Insurance Portability and Accountability Act is changing the way health care establishments and practitioners handle patient records. The HIPAA Privacy Rule is aimed at protecting the privacy of individually identifiable health information a.k.a. protected health information (PHI).

Examples of PHI include common identifiers like a patient’s name, address, Social Security Number, and so on, which can be used to identify the patient. HIPAA covers a wide range of health care organisations and service providers, including: health plan payers, health care clearing houses, hospitals, doctors, dentists, etc.

To protect the confidentiality, integrity, and availability of PHI, covered entities are required to implement technical policies such as access controls, authentication, and audit controls. These can easily be implemented on server-based systems.

Sad to say, many health care organisations who have started storing data electronically still rely on spreadsheet-based systems. Those policies are hard to implement in spreadsheet-based systems, where files are handled by end-users who are overloaded with their main line of work (i.e. health care) and have very little concern for data security.

In some of these systems, spreadsheet files containing PHI may have multiple versions in different workstations. Chances are, none of these files have any access control or user authentication mechanism whatsoever. Thus, changes can easily be made without proper documentation as to who carried out the changes.

And because the files are normally easily accessible, unauthorised disclosures – whether done intentionally or accidentally – will always be a lingering threat. Remember that HIPAA covered entities who are caught disclosing PHI can be fined from $50,000 up to $500,000 plus jail time.

But that’s not all. Through the HITECH Act of 2009, business associates of covered entities will now have to comply with HIPAA standards as well. Business associates are those companies who are performing functions and services for covered entities.

Examples of business associates are accounting firms, law firms, consultants, and so on. They automatically need to comply with the standards the moment they too deal with PHI.

More Spreadsheet Blogs

Spreadsheet Risks in Banks

Top 10 Disadvantages of Spreadsheets

Disadvantages of Spreadsheets – obstacles to compliance in the Healthcare Industry

How Internal Auditors can win the War against Spreadsheet Fraud

Spreadsheet Reporting – No Room in your company in an age of Business Intelligence

Still looking for a Way to Consolidate Excel Spreadsheets?

Disadvantages of Spreadsheets

Spreadsheet woes – ill equipped for an Agile Business Environment

Spreadsheet Fraud

Spreadsheet Woes – Limited features for easy adoption of a control framework

Spreadsheet woes – Burden in SOX Compliance and other Regulations

Spreadsheet Risk Issues

Server Application Solutions – Don’t let Spreadsheets hold your Business back

Why Spreadsheets can send the pillars of Solvency II crashing down

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Energy Cooperation Mechanisms in the EU

While the original mission of the European Union was to bring countries together to prevent future wars, this has spun out into a variety of other cooperative mechanisms its founders may never have dreamed of. Take energy for example, where the European Energy Directive puts energy cooperation mechanisms in place to help member states achieve the collective goal.

This inter-connectivity is essential because countries have different opportunities. For example, some may easily meet their renewable targets with an abundance of suitable rivers, while others may have a more regular supply of sunshine. To capitalise on these opportunities the EU created an internal energy market to make it easier for countries to work together and achieve their goals in cost-effective ways. The three major mechanisms are

Joint Projects
Statistical Transfers
Joint Support Schemes

Joint Projects

The simplest form is where two member states co-fund a power generation, heating or cooling scheme and share the benefits. This could be anything from a hydro project on their common border to co-developing bio-fuel technology. They do not necessarily share the benefits, but they do share the renewable energy credits that flow from it.

An EU country may also enter into a joint project with a non-EU nation, and claim a portion of the credit, provided the project generates electricity and this physically flows into the union.

Statistical Transfers

A statistical transfer occurs when one member state has an abundance of renewable energy opportunities such that it can readily meet its targets, and has surplus credits it wishes to exchange for cash. It ?sells? these through the EU accounting system to a country willing to pay for the assistance.

This aspect of the cooperative mechanism provides an incentive for member states to exceed their targets. It also controls costs, because the receiver has the opportunity to avoid more expensive capital outlays.

Joint Support Schemes

In the case of joint support schemes, two or more member countries combine efforts to encourage renewable energy / heating / cooling systems in their respective territories. This concept is not yet fully explored. It might for example include common feed-in tariffs / premiums or common certificate trading and quota systems.

Conclusion

A common thread runs through these three cooperative mechanisms and there are close interlinks. The question in ecoVaro?s mind is the extent to which the system will evolve from statistical support systems, towards full open engagement.

A Definitive List of the Business Benefits of Cloud Computing ? Part 4

Lowers cost of analytics

Big data and business intelligence (BI) have become the bywords in the current global economy. As consumers today browse, buy, communicate, use their gadgets, and interact on social networks, they leave in their trail a whole lot of data that can serve as a goldmine of information organisations can glean from. With such information at the disposal of or easily obtainable by businesses, you can expect that big data solutions will be at the forefront of these organisations’ efforts to create value for the customer and gain advantage over competitors.

Research firm Gartner’s latest survey of CIOs which included 2,300 respondents from 44 countries revealed that the three top priority investments for 2012 to 2015 as rated by the CIOs surveyed are Analytics and Business Intelligence, Mobile Technologies, and Cloud Computing. In addition, Gartner predicts that about $232 million in IT spending until 2016 will be driven by big data. This is a clear indication that the intelligent use of data is going to be a defining factor in most organisations.

Yet while big data offers a lot of growth opportunities for enterprises, there remains a big question on the capability of businesses to leverage on the available data. Do they have the means to deploy the required storage, computing resources, and analytical software needed to capture value from the rapidly increasing torrent of data?

Without the appropriate analytics and BI tools, raw data will remain as it is – a potential source of valuable information but always unutilised. Only when they can take the time, complexity and expense out of processing huge datasets obtained from customers, employees, consumers in general, and sensor-embedded products can businesses hope to fully harness the power of information.

So where does the cloud fit into all these?

Access to analytics and BI solutions have all too often been limited to large corporations, and within these organisations, a few business analysts and key executives. But that could quickly become a thing of the past because the cloud can now provide exactly what big data analytics requires – the ability to draw on large amounts of data and massive computing power – at a fraction of the cost and complexity these resources once entailed.

At their end, cloud service providers already deal with the storage, hardware, software, networking and security requirements needed for BI, with the resources available on an on-demand, pay-as-you-go approach. In doing so, they make analytics and access to relevant information simplified, and therefore more ubiquitous in the long run.

As the amount of data continues to grow exponentially on a daily basis, sophisticated analytics will be a priority IT technology across all industries, with organisations scrambling to find impactful insights from big data. Cloud-based services ensure that both small and large companies can benefit from the significantly reduced costs of BI solutions as well as the quick delivery of information, allowing for precise and insightful analytics as close to real time as possible.

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User-Friendly RASCI Accountability Matrices

Right now, you’re probably thinking that’s a statement of opposites. Something dreamed up by a consultant to impress, or just to fill a blog page. But wait. What if I taught you to create order in procedural chaos in five minutes flat? ?Would you be interested then?

The first step is to create a story line ?

Let’s imagine five friends decide to row a boat across a river to an island. Mary is in charge and responsible for steering in the right direction. John on the other hand is going to do the rowing, while Sue who once watched a rowing competition will be on hand to give advice. James will sit up front so he can tell Mary when they have arrived. Finally Kevin is going to have a snooze but wants James to wake him up just before they reach the island.

That’s kind of hard to follow, isn’t it ?

Let’s see if we can make some sense of it with a basic RASCI diagram ?

Responsibility Matrix: Rowing to the Island
Activity	Responsible	Accountable	Supportive	Consulted	Informed
Person	John	Mary	Sue	James	Kevin
Role	Oarsman	Captain	Consultant	Navigator	Sleeper

Now let’s add a simple timeline ?

Responsibility Matrix: Rowing to the Island
?	Sue	John	Mary	James	Kevin
Gives Direction	?	?	A	?	?
Rows the Boat	?	R	?	?	?
Provides Advice	S	?	?	?	?
Announces Arrival	?	?	A	C	?
Surfaces From Sleep	?	?	?	C	I
Ties Boat to Tree	?	?	A	?	?

Things are more complicated in reality ?

Quite correct. Although if I had jumped in at the detail end I might have lost you. Here?s a more serious example.

There?s absolutely no necessity for you so examine the diagram in any detail, other to note the method is even more valuable in large, corporate environments. This one is actually a RACI diagram because there are no supportive roles (which is the way the system was originally configured).

Other varieties you may come across include PACSI (perform, accountable, control, suggest, inform), and RACI-VS that adds verifier and signatory to the original mix. There are several more you can look at Wikipedia if you like.