Predicting Discharge Barriers to Optimize Patient Flow

Hospital IQ isn’t here just to predict and pinpoint problems, we are using the Hospital’s unique data set and providing timely and accurate recommendations before they occur, enabling leaders to manage patient flow and discharge issues proactively. By predicting discharge barriers like missed tests, care teams are able to reduce length of stay, decrease avoidable days and reduce ED boarding.

By |2022-01-13T19:01:42+00:00February 25th, 2021|

The Benefits of Machine Learning for Perioperative Leadership

EHRs are amazing sources of data, but that data is not always accessible or usable. It can be very difficult and time-consuming to aggregate and analyze, and when perioperative leaders attempt to use that data to drive improvement initiatives, stakeholders may challenge the accuracy and by default stall progress. Hospital IQ’s Perioperative solution solves this problem by collating disparate data [...]

By |2022-01-12T15:04:32+00:00January 6th, 2021|

Scale and Scalability: What’s the Right Scale for Analysis

Last year I attended an online seminar hosted by a large New England hospital. The speaker summarized some of the operational research and analytics that he and his team had developed using the hospital’s data. By pulling a variety of data from the hospital’s EHR - everything from demographic data to vital signs - and running fairly sophisticated models, they [...]

By |2020-07-23T15:10:40+00:00July 23rd, 2020|

Best Practices for COVID-19 Data Management

As the COVID-19 pandemic quickly became our clients’ top priority many of them turned to us for support in tracking, managing, and reporting their growing COVID-19 population. We had emergency late-night and early morning meetings that augmented existing analytics dashboards with relevant data feeds ranging from very granular patient-level reporting to data aggregated by unit, hospital, county, and even state. [...]

By |2020-06-11T14:26:01+00:00June 11th, 2020|

The Importance of Managing Killer Data

I was recently talking with a power-user at a client hospital. She’s a senior data analyst and combines a rigorous engineering mindset with a deep cultural understanding of how the hospital actually works. She’s off-the-charts organized and confident in her work. While making small talk before a meeting, I asked her: “Do you have a clinical background — have you [...]

By |2020-03-30T18:39:33+00:00February 11th, 2020|

Validating Validation: How to Really Know Data is Accurate and Complete

Patients sending their physician a photo of a mole or other physical presentations of disease are often disappointed to learn they still need to be seen in person for a final diagnosis and treatment plan. While phone camera quality has improved greatly in the decade since they were first introduced, for many diagnoses there’s no substitute for being seen in [...]

By |2020-03-30T18:42:37+00:00October 22nd, 2019|

Data Tolerances and Intolerances

We all know getting accurate hospital data can be a challenge. These barriers have lowered expectations industry-wide for what counts as a usable data set. But it has lowered our tolerances in other ways as well. I was recently reading a peer-reviewed article in a respectable journal on various methods the author used to improve surgical block time utilization. In [...]

By |2020-03-30T18:43:29+00:00September 24th, 2019|

3 Steps to a Highly Successful Client IT Integration Project

Data is the foundation on which Hospital IQ’s predictive analytics platform is built. But getting the required data from hospitals is not always easy. Hospital IT departments are typically overworked and understaffed. Furthermore, external data requests from vendors typically take lower priority than internal requests from known entities. Given this challenging environment, we’ve found three universal principles that accelerate any [...]

By |2021-06-02T16:46:45+00:00September 3rd, 2019|

Engaging Stakeholders to Leverage Data

If you work in the healthcare industry, you can’t swing a cat these days without hitting someone proselytizing about the importance of data. Big data, small data, data silos, data warehouses, data lakes, data-driven organizations. It’s all about data. The processes and sources that generate raw data can sometimes be opaque and hidden from end-users behind layers of cleaning and [...]

By |2020-03-30T18:46:50+00:00April 18th, 2019|
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