Objectives
A leading healthcare provider was facing issues with their existing feedback collection system. The provider wanted us to help analyze the data and gather insights. Outcomes
Beginning with the emphasis on importance of structured data, our team helped the user to define standards, gather information centrally and prepare comprehensive analysis dashboards that summarized the patient satisfaction levels, while highlighting the immediate intervention areas.
A major healthcare provider is now clearly able to monitor and analyze its usage of drugs, consumables and surgical items leading to consistent and efficient clinical care protocols
Studying and understanding the medicines and materials usage is critical to a healthcare provider from two key perspectives. First, standardizing the raw materials that goes into delivering a service brings along high predictability that leads to improved supply chain efficiency and minimal wastage. Second, this analysis helps evolve internal benchmarks for clinical care that ensures a high level of consistency in clinical response irrespective of the hospital branch and the clinician handling the case.
Understanding consumption patterns to evolve internal benchmarks
For long, the healthcare world has been struggling to answer a simple question – How much does it cost the provider to perform a surgery? While it is perceivable that the indirect costs may be difficult to allocate, it is difficult for many of the healthcare providers to present an accurate picture of even their direct costs.
With over 1,500 types of clinical procedures / surgeries and between 50-100 different SKUs per case in a multi-specialty setup, accurately understanding consumption patterns and detecting anomalies in real-time is an arduous task. It is further complicated by varying risk categories of patients, patients requiring multiple procedures and surgeries in a single episode, difference in treatment styles, issues in data capture and non-standard clinical nomenclatures.
To assist the management and the clinical teams in analyzing consumption patterns, a set of dashboards were developed. The objective was to clearly present the underlying consumption patterns, possible reasons for deviations and granular analysis into variations in the pattern leading to pointed areas of focus.
Data Analytics helps the leadership meaningfully compare consumption patterns to arrive at benchmarks
There were several key issues that had to be solved before a solution could be arrived at. The foremost being standardization of clinical nomenclature. The team developed a semiautomatic ML-based algorithm to help prioritize and standardize the clinical nomenclature. The next issue was in cases of patients undergoing multiple procedures where the consumption hadto correctly be tagged to the appropriate procedure. An automated rule-based logic helped tag the items to their headline procedures and helped estimate the correct datain places with gaps in data.
Most importantly, with troves of underlying data, a structured framework had to be conceived with accurately created metrics and visualizations that could digest all the data and directly present the insights in a clear and concise manner.
At a first level, simple statistical metrics such as the interquartile range was used to help the userdecide points at which they can get into the nextlevel of analysis. The final level of analysis presented an item level comparison of consumption pattern. The analysis automatically accounted for outliers, thereby presenting only relevant insights.
The multi-pronged impact
With the consumption costing and details of every single item starting from highest cost valve to the least cost glove available for review, clinicians could observe different patterns of consumption in handling similar kinds of clinical cases. This helped them develop internal benchmarks and practices that would allow for highly effective treatment plans.
The management could understand drug consumption patterns, discuss alternatives with the clinicians, point out areas of inefficiencies and even bring in efficiencies through economies of scale in the supply chain system for specific SKUs.
At the headquarters, management teams of hospitals with higher consumption costs were consulted about the underlying reasons and a plan was set to bring down the cost of performing procedures. With these direct cost inputs, Pricing corrections were also possible for services offered to patients.
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