Plug and Play Business Intelligence?

Really? Do I have to revisit this topic? Again? 2 years ago, I wrote that there is no such thing as plug and play business intelligence. Here we are and has anything changed? The answer is a resounding NO! 

Now, let me clarify this. Analytics tools have come a long way. There are several good analytics tools out there that allow you to do quite a bit of reporting and analysis yourself.

Then why am I insisting that there is no plug and play in BI? Unless you are the Data Warehouse Ninja , ETL(extract transform, load) Samurai and you have a team of 47 Ronin who, through the years of wisdom in the scrolls given to you by the smartest kid, I would venture to say that you don't have a handle on all the data that the business is looking for. And even when you do, the requirements are ever changing. Get my point? It's the data!!!

Data integration and standardization across the enterprise is going to be your biggest challenge. Unless you have that under control, you can put the next Alien ("look it also makes me a sandwich") dashboarding tool on top of it and you will still get bad data. Ever heard the saying, "all that glitters isn't gold"? Well, all that creates dashboards isn't BI either.

Omnition partners with United States Preventive Medicine

Omnition is pleased to announce that we are partnered with United States Preventive Medicine.
http://www.prweb.com/releases/2013/11/prweb11306930.htm

Big Data

Recently, I copy-pasted a link to an article saying that Big Data is dead. That got me thinking. Is it really dead? Serves me right for copy-pasting a link! Here are my two cents on Big Data. Most people don't have Big Data. Google has big data. Yahoo has big data. But if you are a regular business, and even if you have large amounts of data, you might not need to apply big data principles. Let me clarify. If you have large amounts of "unstructured" data and you have a need to mine them, then you might have a need for applying big data principles (Dr's notes, for example) . If most of your data is "structured", no matter the volume, you may never have to apply big data principles. If your data is mostly structured, even with large volumes, it is possible to extract information in a timely manner and you may never have to use big data principles. 

To predict or not to predict?

Let's face it, if you have been to any healthcare industry conferences lately, you have heard about analytics and more importantly, "predictive analytics". Wow! Can you imagine the power of "prediction" at your fingertips? What if you could tell the number of people who are going walk through your door any given day before it happened? What if, you could tell the number of patients who are going to be cancer patients in the next few years? That would be awesome, wouldn't it? The question is, would it?

Let's take a scenario....
Let's say that I now have the predictive capability of knowing that 3 out of my 10 patients will get cancer in the next three months. Great! Which 3? What type of cancer? What can I do to prevent that from happening? The answer is, probably nothing. It is not specific enough. While there are some general changes you can make to your treatment plan, the results will likely be a hit or a miss.

So why spend so much time, effort and money on prediction? To me, a better scenario would be a retrospective inspection of what caused something to happen. In this scenario, you can drill down to the specific root cause of what went wrong and it would be specific enough for you to be able to fix. Much better, "measurable" ROI, in my opinion.

So, when choosing to go after predictive capabilities, understand your goal for it. Look to see if there is a measurable ROI for it. If not, don't try to predict, analyze.

Sometimes, even we have to brag a little....

Ok, so I am not the bragging type, but this referral from a customer is something I had to share :)
“Using Meta Analytix’s cloud based Max on Demand helped us integrate data from two different hospital systems cost effectively. We were able to generate quality analytical reporting with very little initial investment in Data Warehousing and Business Intelligence technologies. We were confronted with a very tight deadline to quickly produce quality analytics and Meta Analytix was able to deliver right on time and within our budget.” –  Executive Vice President, North East IPA Group

Functional Analytics - Data Warehouse or Data Mart?

Data Warehouse or Data Mart?
So, here is the age old question. Should I go the Kimball route (data mart first) or the Inmon route (Enterprise Warehouse first)? While both have merits and demerits (we are not going to get into that discussion here as it has been done before). I think, a "functional" approach should be taken to maximize value. Let me explain. If you look at a physical warehouse, let's say, the warehouse of a shipping company, you don't see one warehouse for canned goods and another for toys and another one for perishables. You may see sections carved out for canned goods, toys and maybe a refrigerated section for perishables. But rarely do you see three separate buildings for each type of item. So why should it be different for a Data Warehouse? Basically, if you look at the data warehousing concept, we will see data marts that are "specific" to a line of business and a warehouse who is the closest thing to a physical warehouse, but often times so scattered and/or so complex that the LOB (Line of Business, if  you didn't already know that) seldom finds use for it. So are we stuck? Not really!

A Flexible, Extendable model.
What if you can have the best of both worlds? What if you could rapidly deploy a warehouse, knowing that there is going to be more LOBs added later?
What if, we could deploy this warehouse, knowing that tomorrow, "perishables" may be added to the warehouse and the model has to be adept enough to add "refrigeration"?
What if, you could add more information at different levels of granularity to the same model?
And...the kicker....what if, we could correlate information across the enterprise, with the same model and don't have to create LOB specific data marts?

"Hogwash, won't happen, what did you smoke this morning?" you say?

"Functional" Approach
So, if you are working for an organization whose primary business is NOT building software, then, you, my IT colleague, is there to support the "business user". I have yet to see a business user who has come to me and said "Boy, I wish I had a data warehouse". All of  them, however, have asked me one thing. "I wish I had good quality information. And I need it today, if possible". So why not give them just that? Rapid Deployment, Ability to add more information later. Can you design such a model? The answer is a resounding YES!

Has it been done before?
Do I have to repeat myself? I did say YES, didn't I? And I added the word "resounding" to give it a dramatic emphasis! Yes we do have such a model. Unfortunately, I can't share the specifics of it just yet without an NDA or holding your first born hostage. Our FlexDimensional model does just that. It allows us to do a few things:
1. Rapidly deploy with limited up front information (business process, granularity, fact etc)
2. Add more information without having to build new star, snowflake, or whatever else schema
3. Correlate enterprise wide information in a single, extendable model.

So, there you have it. There is always a better way of delivering "good quality information" at the point of decision making!

ICD9 - ICD10 Conversion Assistant - MxConvert

Ok,
So this is pretty slick and I have to tell you about it. We recently launched an ICD9 - ICD10 conversion assistant tool called MxConvert that works within Excel. This is geared for you Code Warriors in Healthcare who have to undertake the massive task of converting ICD-9 codes to ICD-10. Take a look:
http://www.metaanalytix.com/page.php?page=38

This ain't your grandma's locker! - PHI in the Cloud

So, recently I was talking to a potential customer about our MAx on Demand offering, which is our SaaS Healthcare Informatics platform and he said that one of the challenges he's been facing is convincing his Sr. Executives that it is safe to host Protected Health Information (PHI) in the cloud. He asked me if I had any arguments for it. Boy, where do I begin? Here is a stab at it.

Not your grandma's locker!

That's right, this is not granny's locker where the key hangs "securely" around her neck! If you have doubts about how sophisticated our data protection capabilities are, take a look:

Companies like ours, take the security of our clients' and their customers' data very seriously. So, there are two high levels of security in place, Physical Security & Network Security.

Physical Security

To access our data center physically, you have to go through a series of checks. If you are an employee, you are given a badge (after background checks of course!). This badge lets you in the parking lot and to the office spaces. You still can't get to the data center. To get to the data center, you have to have biometric access and a secure access code. This will let you into the data center. From the data center, to access your server, you have to have another secure pin that allows you to physically touch the servers. All of your actions are monitored by security cameras and stored.

If you are a visitor to our data center, you have to register with the guard station. You are ID'd and photographed. You will be escorted by an employee during your visit. 

Network Security

Our network security policies and procedures ensure the protection of company wide networks, related devices, and their services from unauthorized intrusion, modification, destruction, or disclosure. Network security provides assurance that a network performs its critical functions correctly, efficiently, and without any interference. Its primary goal is to provide a reliable and secure platform, designed specifically so that users and programs perform only the actions allowed.

Firewalls – Firewalls are utilized to provide dedicated, security specific processing hardware and a complete set of Unified Threat Management (UTM) security features including stateful firewall and web filtering.

Virus Protection – Antivirus software is installed on all Microsoft based servers and workstations. Automatic updates are configured to ensure latest signature download for system protections.

Logging – System logging occurs according to system settings defined by the administrator. Log records can be retrieved as needed. Successful and failed logon activities are logged by domain controllers.

Attck Monitoring - If that is not enough, you can always request 24x7 attack monitoring for your servers!

Disaster Recovery - If a disaster strikes, you can still sleep tight knowing that there is a triple redundant power supply to our data center. Oh, by the way, did I mention that this is a Category 5 hurricane resistant building?

Business Associate Agreements

And if you are still worried about liability, most reputed companies like ours will sign Business Associate Agreements as defined by HHS that makes us adhere to HIPAA laws and liable for breach of Private information: (http://www.hhs.gov/ocr/privacy/hipaa/understanding/coveredentities/contractprov.html)

So yeah, we know that you take your data protection seriously, so do we!  

Accountable Care Organizations Explained

Here is a simple, easy to read ACO article on NPR
http://www.npr.org/2011/04/01/132937232/accountable-care-organizations-explained

Predictive Modeling in Healthcare

Ok, so these are my musings over predictive modeling, not a knock on it. (That is the disclaimer). So, as I was sitting around, pretending to watch TV and ignoring the dog who seemed to want to go out and play, I thought about Predictive modeling, in a healthcare setting. Specifically, in a Healthcare Provider setting. I actually asked this question on several groups on LinkedIn and asked folks if they have had success with it. The only person who responded with a success story was Mr. Alex Zverev (you can view his profile on LinkedIn here: http://www.linkedin.com/pub/alex-zverev/1/a01/b03), and the scenarios in which he has had successes here (http://www.linkedin.com/groupAnswers?viewQuestionAndAnswers=&discussionID=90342387&gid=93115&commentID=65616962&goback=%2Egmp_93115%2Eamf_93115_10544349&trk=NUS_DISC_Q-ncuc_mr#commentID_65616962). So here are some of my thoughts.


My primary interest is in the Return on Investment of using predictive modeling. I see quite a few software providers out there touting to have predictive modeling capabilities, but haven't heard of a lot of success stories, especially in a healthcare provider setting. Even lesser information is available on the ROI of implementing a predictive modeling solution.

To me, an ultimate predictive modeling solution would be something that can predict the stock market, which has infinite number of variables to consider. But if it were that simple, everyone would be doing it. On the other hand, in healthcare, people are touting Clinical Decision Support capabilities using predictive modeling. "Which patient of yours is most likely to develop cancer?", for example. In my humble opinion, that again is quite a stretch, because of the number of variables that need to be taken into account, not to mention "objective research" that is available to create the model in the first place. 
For example, it would be easy to say that a smoker of Asian descent between the ages of 18-40 may develop cancer quicker than others. But what if he is a smoker with healthy eating habits and hits the gym 4 days a week? What if that person only smokes three cigs a day? What if he has no genetic predisposition to cancer? To me, this a cool exercise to conduct and eventually, as you gather more and more data and "evidence" really starts supporting your research in cancer, your model becomes much more reliable and this will start generating a measurable ROI, by reducing the cost of treating a patient through early screening and through preventive medicine. 


My thought is that if you are going to do predictive modeling, start with an area with a limited number of variables. Your "bang for the buck" would be realized sooner and it would be greater in that scenario. For example, the scenarios that Alex describes (Capacity Planning and Measured Display Times for Display Stations) have a better chance of an "immediate" ROI than, let's say, a cancer predicting algorithm. Now, if you are reading this, and have had successes with using Predictive modeling in different settings other than the ones described above, please let me know. I'd like to hear your stories.

The Informatics M.U.S.E

Recently, I was talking to a customer and he asked what I thought about a comprehensive informatics platform should contain. Currently, our focus is on Healthcare, but as I thought about it, I realized this applies everywhere. So, I said to him, "you have to have your M.U.S.E.". Ok, I am not talking about the Hollywood version with Sharon Stone, but the informatics version. So what is an informatics MUSE?
Measure
You have heard me harping about this over and over again. What are you measuring? Why are you measuring it? When you measure your business (healthcare or others), you understand your business better. So, measure everything that impacts your customers (internal or external)


Utilize
Alright, the second element for you to have a successful implementation, you need to have utilization modules. For example, in healthcare, you measure OR Utilization. Great, now that you know that your utilization is below 100%, what are you going to do about it? How about a OR scheduling module that allows you to maximize your OR scheduling? Utilize the information that you gathered during your Measuring process.

 SaaS (Software as a Service) it!
That's right, I said SaaS it. The biggest advantages between a SaaS solution for your business versus you buying the tools and technologies and building it yourself is cost savings and a much faster implementation lifecycle. It puts the focus on "information" and not the technology. Apprehensive about your data being hosted elsewhere? Don't be. Most reputable SaaS solution providers have hardened, HIPAA compliant Data Centers, with 24X7 monitoring capabilities.

Evaluate
That's right. Once your implementation is complete, constantly evaluate your data, decisions you make based on the data and evaluate your performance improvements. This'll allow you to revise your strategies on the go and allow you to make decisions as fast as small companies do.

So there, get your MUSE!

CMS releases Sunshine Act guidelines

http://m.healthcarepayernews.com/content/cms-releases-overdue-sunshine-act-guidance

ACO Fact Sheet

National Committee for Quality Assurance (NCQA) recently published a fact sheet on Accountable Care Organizations. Read the Fact sheet here (http://www.ncqa.org/tabid/1312/Default.aspx). This gives you a good overview of why you should consider becoming an ACO.

More Regulation - ACO!

If you are like me, you are probably jumping up and down in joy that there is more regulation afoot (not!). ACO (accountable care organization) regulations came out last week. You can read all 696 pages and sift through the data or I can try to provide you a snapshot. Here you go:


Measurements
Quality measurements reduced from 65 to 33! Well, that is reduced in half. Got to be a good thing. Yes, it is a good thing. The measures are now categorized into 4 domains, namely:
- Patient/Care Giver experience (7 measures)
- Care Coordination/Patient Safety (6 measures)
- Preventive Health (8 measures)
- At Risk Population (12 measures: 7 measures, including 5 component diabetes composite measure and 2 component CAD composite measures)


Pretty Simple, eh? Each domain is given a weightage percent of 25% each and then reported for each of these measures.) In the next blog, we will take a deeper dive into the measurements. And if you want to go straight into implementation, see how Meta Analytix can help you here: http://www.metaanalytix.com/page.php?page=36



Who is eligible?

The newly added section 1899 of the Social Security Act or SSA provides examples of groups of service providers and suppliers that may form an ACO, including 

(i) physicians and other health care practitioners (ACO professionals) in a group practice, 

(ii) a network of individual practices, 

(iii) a partnership or joint venture arrangement between hospitals and ACO professionals, and 

(iv) a hospital employing ACO professionals. ACOs eligible to participate in the MSSP (Medicare Shared Savings Program) will manage and coordinate care for their assigned Medicare fee-for-service beneficiaries.

What are the requirements?
According to the IRS (IRS?? - http://www.irs.gov/pub/irs-drop/n-11-20.pdf), the type of organizations wishing to become ACOs must meet the following criteria.



1) The ACO shall be willing to become accountable for the quality, cost, and overall care of the Medicare fee-for-service beneficiaries assigned to it.


(2) The ACO shall enter into an agreement with the HHS Secretary to participate in the program for not less than a 3-year period (the MSSP( (Medicare Shared Savings Program) agreement period).


(3) The ACO shall have a formal legal structure that would allow the organization to receive and distribute payments for shared savings under § 1899(d)(2) to participating providers of services and suppliers.


(4) The ACO shall include primary care ACO professionals that are sufficient for the number of Medicare fee-for-service beneficiaries assigned to the ACO under § 1899(c). At a minimum, the ACO shall have at least 5,000 such beneficiaries assigned to it under § 1899(c) in order to be eligible to participate in the MSSP.


(5) The ACO shall provide the HHS Secretary with such information regarding ACO professionals participating in the ACO as the Secretary determines necessary to support the assignment of Medicare fee-for-service beneficiaries to an ACO, the implementation of quality and the other reporting requirements under § 1899(b)(3), and the determination of payments for shared savings under § 1899(d)(2).


(6) The ACO shall have in place a leadership and management structure that includes clinical and administrative systems.


(7) The ACO shall define processes to promote evidence-based medicine and patient engagement, report on quality and cost measures, and coordinate care, such as through the use of telehealth, remote patient monitoring, and other such enabling technologies.


(8) The ACO shall demonstrate to the HHS Secretary that it meets patient-centeredness criteria specified by the Secretary, such as the use of patient and caregiver assessments or the use of individualized care plans.


That's about it. If you have questions, feel free to call me. If I am on the golf course, I am not answering my phone!

Micro Informatics

Recently, we launched our FREE, yes FREE, iPhone app to help providers keep track of OR Utilization. (To appease our sales and marketing folks, here is more information about the app: http://www.metaanalytix.com/page.php?page=35). It only does one thing, that is, keep track of OR Utilization. You ask me, when you have the Cadillac of informatics solutions, why launch a "micro informatics" app? One very simple reason. Delivery of information at the point of decision making. The reason why we built the app is because a couple of friends of ours, who work at surgical departments said, we are always asked how we measure in relation to our goals. We have no way of knowing it till the end of the month, nor do we have an effective way of tracking where we are or justify a lower score than what is expected of us. So, here are some reasons for "micro informatics":

* It is a great motivational tool. If you can keep track of where you are, you can change directions accordingly to achieve more.

* Educational purposes: Research is usually done at a macro level. But if you can use the results of that research and deliver it at a micro level, you can deliver the latest information at the point of care. For example, an ER doc running from patient to patient, maybe able to quickly access the latest findings in research at the point of care.

* It is a great data collection mechanism. You get better data from the "horse's mouth", so to speak. Better data, better analysis.

Skim on it now, you'll pay later

Everybody wants to cut costs. "Bad economy, can't commit enough money right now...", we have heard it all. The thought process is, let's do the one thing I need right now (at dirt cheap prices), and then we'll go from there. Well, it would be a sound financial decision.... if you are buying groceries! If you are planning an informatics initiative, however, it is a bad idea. Now, solutions like ours, are designed specifically with that kind of need in mind and can scale to need. But most are not. So if you are investing in an informatics solution, invest in it. It doesn't go bad after a week. In fact, in the long run, it will help you cut costs and save money. It really is not like buying a car where, as soon as you drive off the lot, the value drops by 10%. Over time, the more data you have, the better your analysis is going to be. It is an investment. It may not be a revenue "generator", but it certainly is an "expense reducer", if used properly. Some food for thought.

Feedback Requested

As I was talking to a very smart friend of mine who is in PR & Communications, she asked me what my company did. As any good technologist would do, I told her that we are a health informatics company and that we have an end to end informatics platform that extracts data from disparate systems and presents reliable information to key stakeholders in Healthcare for better decision making. She asked me again, "what do you do?" and explained to me the importance of simplifying our message. So here is an attempt. Your feedback will be greatly appreciated. Especially if you are in healthcare

Which one of the following sentences resonates with you about what we do?

1. Helping improve quality of care and reduce healthcare costs through reliable information.

2. Providing business and clinical intelligence to decision makers in healthcare.

3. Providing cloud based analytics and data warehousing for healthcare.

4. An end to end informatics platform for healthcare at a fraction of the cost.

5. None of the above, I still don't know what you do.

Informatics for IPAs

Some of the IPA customers we talk to, all say the same thing. "I don't have the data to defend my contract negotiations". So how can an IPA integrate data to better negotiate terms in a "shrinking profits" landscape?

Step 1: Remember step 1? METRIC? (Measure Everything That Really Impacts Customers"? Yes, step 1 hasn't changed. Not one bit. In this particular case, since your negotiations are probably based on HEDIS and PQRI measures, that's the first thing you want to list out. Which of those measures will help you show your quality of care and performance.

Step 2. Collect Data. If you are like most IPAs, you have 5 or more EMRs to deal with that are being used within the physician practices. Most EMRs, save a few, have ODBC compliant databases. Solutions like ours can pull data directly from those systems. And for the others, you can integrate data using the more traditional, "flat file" approach. This is more technical than anything else.

Step 3: Define your reports. What reports will help you better negotiate rates? If you find anomalies with regards to physician performance, how can you get that one practice up to speed with everyone else so that you can negotiate better? How often do you need these reports? Define these and the next time you walk into contract negotiations and the payer tells you that your Physician performance is "this" based on claims data, you can confidently say, "no, our data shows a different picture".

So negotiate away, you IPA samurais, and bring up that profitability level!

Wonder Why BI implementations fail?

Take a look!

http://www.youtube.com/watch?v=78FJBDKSYPY

ACO Series, Part I

So, people have been (I hate saying "people", it's like saying "they say...". My first question is, "Who are the famed "they"? In this case, who are these "people"? But for the purposes of this post, I can't take names, so "people" ) have been asking me about ACOs and the role of analytics in it. I read a recent study done by American Hospital Association and McManis consulting titled "Activities and Costs to Develop an Accountable Care Organization". If you haven't read it, it is a good read. In the report, they break it down into four major categories:

1. Network Development and Management

2. Care Coordination, Quality Improvement & Utilization Management

3. Clinical Information Systems and, my favorite

4. Data Analytics.

Now, it is interesting that they broke out Data Analytics as a separate entity. In my humble opinion, Data Analytics has implications in all three of the other areas. For example, the stated definition of ACOs is: "intended to manage the health of a defined population and to be held accountable and reimbursed based on measurable improvements in quality and patient satisfaction, plus reductions in costs". Sound familiar? If you have been reading my blogs for the last two years, you would have heard these two terms repeatedly:

1. Improving Quality of Care

2. Reducing cost of care

And why do I think Analytics has implications in all three? Well, let's put it this way. You don't throw money at something and hope that it sticks do you? If you answered yes, well...you are reading the wrong blog, but if you didn't, then read on.

Let's take a look at section 1 of the study, Network development and management. The study details about 9 activities that you have to do to achieve the goals of this section. I am not going to go into details of all of them. But let's examine a couple.

* Recruiting/acquiring primary care professionals, right-sizing practices

Great goal. But how do you achieve this? Do you want to acquire every PCP that is associated with you? Probably not. You want to acquire the "best" ones. You criteria for defining the "best" might differ from your neighbor's, but you still want to acquire the best and drop off the dead weight. (Remember the fact that you are trying to "reduce costs" through this activity). So how do you know who is your best target for acquisition? Historical data of course! So, define the metrics which allow you to define your "best case scenario", run those metrics against your historical data and see who pops up at the top! You might be surprised. If I were a betting man, I would bet a dollar on it!

* Compensating physician leaders

Uh oh! Yes, I went there. This is a touchy subject. Well, the question is, how do you define a "leader"? Is it the physician who can do 40 surgeries, play 18 holes of golf, take the kids to soccer practice and have dinner with the family all in a day? Could be. It could also be the physician who has the least infection rates. It could also be the physician with a 100% patient satisfaction rate. So now we have a combination of metrics (weighted, of course to come up with the definition of a "leader"). Again, run these metrics against your historical data ( you do have historical data as much you think you may not), and see who pops up at the top. Again, I will bet a dollar that you might be surprised.

So you see, analytics is not a separate "reporting only" solution. You can use it to make intelligent decisions. But if you are reading this blog and haven't slept yet, you already knew that. That is why I think analytics has implications in all three of the major categories in achieving a true ACO.

ACO Series Part II: Care Coordination, Quality Improvement and Utilization Management

Coming soon to a blog near you.