Patient flow analysis and forecasting

Andrew Tolve reports on how patient flow analysis (PFA) can lead to better forecasts and more effective marketing strategies.



Andrew Tolve reports on how patient flow analysis (PFA) can lead to better forecasts and more effective marketing strategies.



As pharmaceutical companies seek to better understand the patient journey, they face a number of complexities: changing population dynamics, regimen usage, and remission and cure trends, to name a few.


Patient flow analysis (PFA) helps model these complexities and illuminate the mechanics behind them.


The result can be better forecasts and more effective marketing strategies.


Patient flow analysis allows forecasts to be much more customer-based, says Judith Kulich, associate principal at ZS Associates.


As pharmaceutical organizations strive to maximize the potential of their brands by tying their thinking to their patients, patient flow becomes an increasingly valuable tool.


Mining the data


Patient flow models are market-specific.


By definition, they model the unique flow of patients through a specific disease area and capture the nuances of that market's treatment process.


Creating such a model requires gathering and sorting copious amounts of patient-level data.


Analysts need to quantify how patients in a specific disease area move through that disease.


That means pinpointing how long they exhibit certain symptoms, their relapse rates, their adherence rates, their survival rates, and the therapy models they follow.


Once analysts have sufficient data, they group it under various specificationssuch as stocks, flows, and relevant patient characteristicsand plug it into systems dynamics software like Vensim, iThink, or MarketLive.


The capabilities of these software applications are essentially unbounded, so its critical that analysts keep the scope of the model manageable.


There is no use in a complicated model that captures all dynamics of the market, but which nobody understands, can use to generate a forecast or better understand their market, or has the data to populate, says Kulich.


Value versus complexity


Due to its data-intensiveness, PFA isnt always the right forecasting technique to choose.


PFA can always be effective, says Kulich.


It's more a matter of whether the value that it brings over other options is worth the additional complexity it requires.


The models are best suited for chronic disease areas, Kulich says, especially oncology, diabetes, and HIV Aids, where treatment processes evolve and are driven by treatment history.


Kulich offers an example from ZS Associates work.


How PFA works with cancer products


A biotech company with a late-stage cancer product was interested in broadening that products range to include early-stage treatment.


But the company wasnt sure how its products use in early-stage treatment would change the dynamics of late-stage treatment.


Perhaps in trying to broaden patient opportunity, the company would actually reduce it.


ZS Associates used PFA to study the efficacy of the companys product in early-stage treatment and to assess how that impacted future trends in the late-stage cancer population.


Rather than basing this products forecast on historical epidemiology trends, we were able to base it on future trends as influenced by the use of this product in early-stage treatment, says Kulich.


Clinical settings and emerging markets


Many consulting companies in the pharmaceutical space, including ZS Associates, Best Practices LLC, and MattsonJack, have started using PFA to devise better forecasts in chronic disease areas.


Patient flow analysis has become a method of choice in other healthcare environments as well.


Healthcare professionals use PFA in clinical settings to track the movement of patients and the use of personnel time.


If clinics can better understand in-coming patients needs, they can handle a higher patient volume and remain more financially viable.


Meanwhile, some pharmaceutical companies are using PFA to launch more accurate hospital-based initiatives.


Still more are using PFA to analyze emerging markets and how patients move within them.


What are adherence rates to MS treatments in India, for instance?


What percentage of patients discontinues therapy?


Patient flow analysis can help model these unknowns and thus forecast what volume a pharma company can expect to sell in a given market over a given period.


Maximizing the potential of available brands


Kulich says the growing popularity of PFA isnt likely to diminish any time soon.


As pharma companies watch their blockbuster products approach patent expiration and struggle to find replacements from their limited pipelines, theres an increased need to maximize the potential of available brands.


Our clients' interest in this approach has increased as they are looking to better understand their patients and align marketing decisions with this understanding, says Kulich.


Additionally, as pharma companies shift their focus towards specialty markets like oncology, the need to understand the complexities and movements within those specialty markets becomes all the more acute.


For more on specialty markets, listen to Rajesh Guptas podcast Marketing for specialty markets.


For more on pharmerging markets, see Forecasting in emerging markets.


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