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HIStalk Advisory Panel: Analytics Success

February 11, 2014 Advisory Panel 3 Comments

The HIStalk Advisory Panel is a group of hospital CIOs, hospital CMIOs, practicing physicians, and a few vendor executives who have volunteered to provide their thoughts on topical industry issues. I’ll seek their input every month or so on an important news developments and also ask the non-vendor members about their recent experience with vendors. E-mail me to suggest an issue for their consideration.

If you work for a hospital or practice, you are welcome to join the panel. I am grateful to the HIStalk Advisory Panel members for their help in making HIStalk better.

This question this time: What are examples of major operational or clinical successes your organization has experienced in the past year from using analytics or data reporting tools?


No operational successes of any kind as our medical staff as well as administration does not even know the meaning of analytics nor what to do with it. We lack even the basic reporting capabilities needed to know our observation and LOS. We did well with core measures and scored high and used that as a marketing tip, however we did not use any sophisticated tools to get there. The physicians do not get any personal performance data to look at to compare with their peers and are not used to looking at their own data at all. It is part of the reason why I believe the institution failed so miserably and ended up being acquired by a lager hospital chain.


Improved GI lab throughput. Reduction in the use of blood products. Improvements in GI Billing process. Improvements in GI DNKA.


None.


Hard to know what success we have had from using analytics. If we decide, based on environmental scans and analytics to to focus on, say, total joint replacement, there will never be a time when we can say, "Ah, that was the right decision", even if your hospital is still afloat, or doing well. It may be that another service line or focus or workflow or supplier would have been better. Analytics comforts us into thinking we aren’t making a WAG, but there aren’t answers in the back of the book. On the more micro level, cost-benefit does help balance the budget.


Over the past year we deployed reporting tools to our front-line providers, departments, sites, divisions and company-wide providing actual results compared to our goals for people, service, cost, quality, access, and primary care flow. Particularly in service and access we improved performance compared to baseline and moved closer to (and in some cases exceeded) goals. Patients report improved experiences and appointing wait times have come down. There’s probably a link between the two improvements. 


We used some basic reporting tools to identify high risk patients who are overdue (e.g. diabetic with A1C over 8 not seen in six months). We then tried multiple methods of outreach and found email, letters and robocalls had minimal impact on this group. We finally found  success with having our call center staff call them during the late afternoon when there was low incoming call volume. Turns out they responded very well to real people calling them who could make their appointments right then!


No use of data beyond mandated reporting: MU, Core Measures, etc.


Using a SaaS population health data analytics tool, which blends CMS claims and EMR clinical data, to identify leakage of ACO patients outside our Network, which identifies opportunities for providing services not currently offered by our network in order to capture the lost revenue and reduce the expense to the CMS Medicare program.


We’ve been able to push an Analytics Dashboard to each member of our clinical leadership team that allows them to have real-time data as to the patients on their units, the patients that were discharged yesterday, and so on. Dramatically reducing the turn-around time for actionable data and ‘teaching them how to fish” has resulted in greater satisfaction amongst them and allowed my folks to focus on other projects instead of grinding out repetitive reports.


Minimizing the readmission rates in our high risk population such as those who had an MI or uncontrolled diabetic states  – two major clinical categories. Minimizing ER visits of high risk patients


We have set up a few transitional care clinics where we try to work with patients, post discharge, to ensure that they get/take their meds, get in to their PCP’s office as ordered, and generally try to get them compliant with their treatment plan in order to keep them out of the hospital again. (Basically, trying to prevent re-admits). We are using a number of tools and reports to generate data to assist with this process, but we are investigating new ones (e.g., PHM systems) that are specifically designed to do this.


Data on our clinical initiatives to improve clinical performance on readmissions, VTE prevention and early recognition of clinical deterioration have been very helpful in terms of showing benefits of these projects.


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3 Responses to “HIStalk Advisory Panel: Analytics Success”

  1. 1
    Howard Says:

    I recently came across a Forrester study called “Competitive Differentiation Through Innovative Business Intelligence.” What’s really interesting to me is their key findings from the global organizations participating – these rarely exist in healthcare. #1 on the list is “a majority of organizations regard data as a key strategic asset.” Many healthcare provider organizations probably believe in this statement, but I would argue most do not follow through. The data warehouse never matures, another silo is brought and validated by some subset of users with a business need. Same applies to BI tools as one flavor replaces another. Ultimately, data is not used as a strategic asset. It’s more of a liability in healthcare today, and this needs to change.

  2. 2
    Dale Sanders Says:

    I’m surprised by two things in these comments: (1) The variation in the answers; (2) The lack of widespread value that organizations are deriving from analytics; I thought everyone would respond with at least 2-3 examples of success.

    It’s pretty clear that the best organizations in healthcare for delivering better care at lower cost have been leveraging data and analytics to do so, for many years. I suspect that the lack of greater adoption and value as indicated in these comments may be due to a lack of time and resources to devote to analytics when considering all the competing priorities, e.g., EMR implementations, Meaningful Use, health information exchanges, formation of accountable care organizations, ICD10 conversion, and HIPAA/information security risk management.

    If I were King of HHS for a Day, I would figure out a way to franchise the Advanced Training Program at Intermountain Healthcare and make it a requirement for, say, 50% of a healthcare organization’s staff to graduate from some version of that program. I’ve never seen anyone graduate from that program that didn’t come out of it with a passion and deep understanding of how to apply analytics to the betterment of the industry.

    Becoming data driven isn’t an option anymore, as implied in the comment above about being acquired by a larger organization, and in Howard’s comment. In the next 2-3 years, organizations will either eat or be eaten by the changes in the market– it’s already happening, actually– and the ability or inability to leverage data will determine where you fit in the food chain.

  3. 3
    flpoggio Says:

    I am not surprised at all by the responses. Keep in mind health care is just starting to be exposed to BD/analytics. In part because the core base data has never really been there, and what was there was a mishmash of governmental warped data.
    I think the comments show that at this juncture there is still a lot of education that needs to happen and KISS (Keep It simple Stupid!) still works best.

    I covered this awhile back in my HIS Talk piece entitled, Big Data and Analytics; The next HIT Boondoggle?”
    http://histalk2.com/2013/09/09/readers-write-big-data-the-next-hitemr-boondoggle/
    and
    http://histalk2.com/2013/11/20/readers-write-seven-safety-checks-before-diving-into-the-big-data-ocean/

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