Businesses, including pharmacies, have access to more and more data than ever before.
However, trying to sort through raw data to try to obtain meaningful data insights is difficult. Pharmacy owners and self-employed pharmacists in the pharmaceutical industry can benefit greatly from the wealth of information now available to make more informed decisions, but only if the information is meaningful. New trends in data analysis are giving the pharmaceutical industry new tools for growth and development by helping generate meaningful data analysis and metrics.
Pharmacy Business Metrics
Most pharmacists do not have a business background, so may not be aware of newer business data analytics that can help them with running their pharmacy optimally as a business.
1. Gross Profit Margin
Your gross profit margin is your revenue after the cost of goods sold is subtracted, or the profit that remains after you have sold a product once all operating expenses have been taken into account.
This is an important metric that takes you beyond simply tracking profit and profit growth (or shrinking). It can be done for the different departments in a pharmacy. This helps identify what areas of the pharmacy are underperforming, highlight excessive expenses, and facilitate business decision making.
Community pharmacies should target for a gross profit margin of 30% or higher.
2. Inventory Management Metrics
Many pharmacists lose money maintaining a higher inventory than they need, increasing their storage costs and increasing the chances of expired product that needs to be thrown out.
To help optimize this side of the pharmacy business, measuring inventory turnover is important. Inventory turnover is measured by dividing the cost of goods sold by the average inventory.
For established pharmacies, inventory turnover should be planned so that the entire stock of inventory is sold 12 times per year or more. This avoids the expenses of an overly large inventory. You can significantly reduce costs by keeping an optimal inventory, while having enough product to sell and maximize profits.
3. Big Data Analytics
Big data analytics is evolving, allowing new ways to measure success and guide decision making in business and clinical areas.
Structured data, in its wide range of forms, has been traditionally used more for metrics. However, unstructured data, or Big Data, does not fit into typical data processing, because it involves extensive amounts of data that cannot be stored, processed, or analyzed using the tools that have traditionally been used. Big data is stored, and available, but not analyzed. With new tools evolving, big data analytics are becoming possible, so valuable insights can start to be discovered using the huge amounts of raw and unstructured data.
With big data analytics, more medical data, including patient data and clinical data, as well as business and other data, will start to be usable for meaningful insights. Both structured and unstructured data analytics will be possible, providing a wealth of information previously thought impossible, and making new metrics more feasible.
Big data analytics provides the foundation for predictive analytics, and helps by taking the vast amounts of data that pharmacies have to deal with, and making it into useful information. Pharmacies deal with a wide range and large numbers of medications and products, each with different patterns of usage, potentially with periods of increased usage. Big data can draw information from all of these areas and pull them together into meaningful reports. In addition to allowing predictive analytics to be effective, such as for inventory management, this can help pharmacists with analyzing price elasticity (or how much demand impacts price) and customer behavior to optimize pricing strategies and vendor performance.
4. Predictive Analytics
Predictive analytics reduces the need for calculating metrics. Predictive analytics draw from a wide range of data, including big data, and automatically analyze to predict outcomes using artificial intelligence. This speeds up and simplifies the entire process to give the end results of meaningful, actionable information.
Predictive models are being developed in all areas of business and healthcare, and the benefits of these will become increasingly more valuable for healthcare providers, including pharmacy owners and others in the pharmaceutical industry.
Predictive analytics is increasingly being used in pharmacy businesses and by pharmacists to improve patient care, streamline operations, and make data-driven decisions.
Pharmacy businesses collect data on patient prescription history, refill rates, demographics, and other relevant information. They may also integrate data from electronic health records (EHR) systems. In addition to using this to assess medication compliance and outcome monitoring, they can predict refills for accurate inventory planning. Scheduling extra employees for predicted peak days and times is also facilitated.
5. Supply Chain Data Analytics
Supply chain management is a critical concern in the pharmacy business, and data analytics on various points in the supply chain can help. Determining demand patterns, delivery schedules, and other elements, and tying into pharmacy inventory management metrics, can generate significant insights.
6. Granular Cost Reduction
To increase pharmacy operating margins as business pressures get tighter, pharmacy businesses can use granular metrics for key tasks or other areas, including average ingredient cost per prescription, rebate percentage of total drug spending, and others.
7. Optimize Sales and Marketing Strategies
With the advent of access to more data and better data analytics, pharmacy owners can benefit from metrics and reports on sales and marketing efforts. Easy and more accurate tracking of specific products and their departments is possible. This also allows for better and more meaningful monitoring of the impacts of related marketing. Pharmacy owners are empowered with better tools and metrics for improved decision-making for the pharmacy as a business.
Metrics For Health Data Analytics
In the medical and pharmaceutical industry, a range of analytic tools are evolving to help healthcare organizations.
8. Electronic Health Records
With data sharing of electronic medical records, critical elements within patient records can be tracked. Alerts can notify healthcare professionals of concerns, and prescriptions can be tracked so physicians can be aware of whether patients are following recommended treatment. Other applications may be possible to protect patient health and analyze patient data while maintaining information security. This means both doctors and pharmacists can benefit from better information about their patients, leading to improved patient outcomes.
9. Drug Research and Development
You may see new drugs become available sooner in the future. Predictive modeling is helping create safe and effective drugs faster, with machine learning, artificial intelligence, and other advanced data analytics tools. It can also use the information, paired with defined metrics, to promote a better understanding of patient profiles for personalized treatment.
10. Clinical Trials
Data analytics can help with optimizing clinical trials, including their design, execution, and ongoing monitoring. Predictive analytics can forecast outcomes, to save time, money, and risks to trial participants, and determine earlier if results are likely to fall within desired metrics.
Get Help With Your Pharmacy Business Metrics and Data Analytics
PharmaTax can help you make sure you get the right data collected and analyzed, and use the right metrics to drive your pharmacy growth. We analyze your business activities fully, and guide you with expert strategic planning, taking your pharmacy to the next level.
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