Demand Forecasting and Strategic Analysis, Explained

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Demand Forecasting and Strategic Analysis

Healthcare Organization and Management · Chapter 8: Strategic Planning and Decision-Making in HealthcareSection 8.5 · lesson 52 of 10510 min · free with a free account

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In this lesson

Forecasting healthcare demand with visible assumptions and honest ranges.

  • Distinguish need, demand, and utilization in service planning
  • Build a driver-based forecast and test it for sensitivity
  • Calculate moving averages and seasonal indexes for referral data
  • Explain supply-sensitive care and the risks of single-number forecasts

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Transcript

Everything said in the video, section by section (1,239 words). Read along, or search it.

Opening Case

Flat Volume, Growing Waiting List

Larkfield is deciding whether to expand orthopedic surgery. Tom Brennan, the finance chief, asks for one number: how many referrals in five years? This year the service did fifteen hundred operations, the same as last year. But its waiting list grew by a third. So is demand flat? And should Tom get one number at all?

Need, Demand, Utilization

Three Words That Get Blurred

Start with three words that get blurred. Need is the capacity to benefit from care, whether or not anyone asks. Demand is what's actually asked for: referrals, visits, requests. Utilization is what's delivered. Need exceeds demand when people don't come forward, because of cost, distance, language, or past experience. Demand exceeds utilization when the service can't keep up, so waiting lists grow. And utilization can exceed need, when care is delivered that brings no benefit. Larkfield's flat fifteen hundred is utilization. Forecast it forward, and you project the rationing, not the requirement.

Demand Drivers

Six Forces That Move Demand

Six drivers move demand. Population size and age: slow, predictable, and published. Disease burden: how common conditions are, and the population's risk. Coverage: who can come without cost blocking them. Access: distance, hours, language, transport. Provider supply: what's available. And referral pattern: where demand arrives. For a single department, referral pattern is often the biggest short-term driver. Volume can fall while need rises, because a competitor opened, or a referral pathway changed.

Supply-Sensitive Care

A Bed Built Is a Bed Filled

One driver is uncomfortable. For some services, use tracks the supply of capacity more closely than measured need. Milton Roemer observed it in nineteen sixty-one, in an insured population: a bed built is a bed filled. The Dartmouth Atlas calls this supply-sensitive care. Where more capacity exists, more care is delivered, without the population being sicker. It's strongest where the threshold to intervene is a judgment call. So an expansion justified by a forecast may partly create its own demand, and later utilization will seem to prove the case. Say whether a service is this type.

Forecasting Methods

Qualitative and Quantitative Families

Forecasting methods come in two families. Qualitative methods use informed judgment: expert opinion, consensus rounds like the Delphi method, and scenarios. Scenarios don't give a number. They build several coherent futures and ask what each would require. Qualitative methods are the only honest option for a new service with no history, a structural change, or a horizon too long to extrapolate. Quantitative methods project the numbers: trend extrapolation, seasonal adjustment, and driver-based models. Trend extrapolation assumes the mechanism behind the trend continues, which is exactly what fails.

Smoothing and Seasonality

Moving Averages and Seasonal Indexes

Two quick tools. A moving average smooths noise. Referrals for the last four months were one twenty-eight, one forty, one thirty-six, and one fifty. The three-month moving average for the latest month is one forty plus one thirty-six plus one fifty, over three: one forty-two. A seasonal index separates season from change. Winter months average one sixty-five referrals, against a yearly average of one fifty. One sixty-five over one fifty is one point one. So a winter month ten percent above average is season, not growth. Compare it with last winter, not last autumn.

Quick Check

A Three-Month Moving Average

Quick check. A clinic's monthly referrals are one twenty, one thirty-two, one twenty-six, and one thirty-eight. What's the three-month moving average for the latest month? Pause and predict. One thirty-two. Take only the latest three months: one thirty-two plus one twenty-six plus one thirty-eight is three ninety-six, and divided by three, one thirty-two. One twenty-nine is tempting: it's the average of all four months. But a three-month average drops the oldest month.

Driver-Based Forecast

Projecting Referrals From Age Groups

Now a driver-based forecast for Larkfield's orthopedic referrals. The catchment has one hundred fifty thousand people. Twenty percent, thirty thousand, are sixty-five or older. Older residents are referred at thirty per thousand: thirty thousand times point zero three is nine hundred. The other one hundred twenty thousand are referred at six per thousand: seven hundred twenty. Total today: sixteen hundred twenty. In five years, the older share rises to twenty-three percent. Thirty-four thousand five hundred times point zero three is one thousand thirty-five. The rest give six hundred ninety-three. Total: seventeen twenty-eight. The value isn't the number. It's that every assumption is visible, and can be challenged separately.

Sensitivity Testing

Finding the Breaking Assumption

Sensitivity testing varies each assumption and watches the forecast move. Planners argued about the older share. Run it from twenty-one to twenty-five percent. The forecast moves from sixteen fifty-six to eighteen hundred, about four percent either way. Not much. Nobody discussed payer coverage. But if a major payer narrowed coverage and the older referral rate fell to twenty per thousand, the forecast drops to thirteen eighty-three, about twenty percent. That's the breaking assumption: the one whose failure would invalidate the decision, not just adjust it. Monitor that one, and present a range, never a point.

Quick Check

Extra Referrals From a Rate Rise

Quick check. In five years, one hundred fifteen thousand five hundred people are under sixty-five. Suppose their referral rate rises from six to eight per thousand. How many extra referrals is that? Pause and predict. Two hundred thirty-one. The rate rises by two per thousand, so one hundred fifteen thousand five hundred times point zero zero two. Four sixty-two is tempting if you double the rise. But the change is two per thousand, not four.

Assumption Register

Matching the Horizon to the Decision

Accuracy falls with distance, faster than most charts admit. So match the horizon to the decision. Staffing needs a one-year view, and can be revised. A building commits you for fifteen years, so test it against several futures, not one forecast. And keep an assumption register beside the numbers. Population: size, age, and where people live. Coverage and payers: who's covered, and on what terms. Competition and supply: what other providers will do, the one most often left out. And practice: referral criteria and clinical thresholds, which change routinely. A written assumption can be watched, and the forecast declared invalid the month it fails.

Catchment and Share

Catchment, Market Share, and Competitors

Three questions surround any service forecast. Catchment: where do patients actually come from? Use the addresses of current users, not a circle drawn on a map. Market share: what fraction of the catchment's demand comes here? That needs the total. If you don't know it, say so; don't pass off activity as share. And competitors: who else provides this, and what changes if they expand or leave? A forecast is the best estimate, and it will be wrong. So prefer options that can scale or reverse, stage commitments, and name in advance what would trigger a stop.

Forecasting Failures

Four Errors That Recur

Four forecasting failures recur. Forecasting activity instead of demand, so rationing is projected as if it were the requirement. Assuming a trend continues through a structural change that's already been announced. Leaving out the competitor assumption because it's uncomfortable. And handing a board a single number, which becomes a commitment the moment it's minuted.

Case Resolved

A Range and a Staged Expansion

Back to Tom's one number. Tom doesn't get one. He gets a range, thirteen eighty-three to eighteen hundred, with payer coverage marked as the breaking assumption. The expansion is staged. Phase one is sized to pay its way even at the low end. Phase two waits for the payer's coverage decision. Staging costs more than building once. That premium is what Larkfield pays, to avoid locking fifteen years of building into an assumption it doesn't control.

Key Takeaways

Forecast Demand, Not Activity

To recap. Need, demand, and utilization differ, and activity data can hide rationing. Referral patterns and supply can move a department's volume more than population does. Use judgment methods where there's no history, and driver models where there is. Write the assumptions down, and find the breaking one by sensitivity testing. And give a range, with staged commitments and stop triggers.

About Healthcare Organization and Management at UPI Study

Healthcare Organization and Management (Health 302) is a self-paced online course of 105 video lessons in 18 chapters, from health systems and the law to ethics, leadership, teams, strategy, informatics, finance, quality, human resources, marketing and evidence-based practice. It carries a NCCRS credit recommendation for 3 semester credits.

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Universities that work with NCCRS

Healthcare Organization and Management carries a NCCRS credit recommendation. These universities work with NCCRS; some are UPI Study's signed partners. ACE and NCCRS have over 2,100 cooperating colleges that will consider accepting credits; the final decision is with the universities.

Thomas Edison State UniversityThomas Edison State UniversitySigned partnerUniversity of the PeopleUniversity of the PeopleSigned partnerCharter Oak State CollegeCharter Oak State CollegeSigned partnerStrayer UniversityStrayer UniversitySigned partnerColumbia Southern UniversityColumbia Southern UniversitySigned partnerIndiana TechIndiana TechSigned partnerPenn StatePenn StateWorks with NCCRSSouthern New Hampshire UniversitySouthern New Hampshire UniversityWorks with NCCRSSUNYSUNYWorks with NCCRS +many more cooperating universitiesFind my college →

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FAQ

Questions students ask us

About Demand Forecasting and Strategic Analysis

What is the difference between need, demand, and utilization in healthcare?
Need is the capacity to benefit from care, whether or not anyone asks. Demand is what is actually requested, such as referrals and visits. Utilization is the care actually delivered. Need can exceed demand when cost, distance, or language keep people away, and demand can exceed utilization when a service cannot keep up. Forecasting from utilization alone can project rationing as if it were the requirement.
What is supply-sensitive care?
Supply-sensitive care is care whose use tracks the available capacity more closely than measured need, a pattern the Dartmouth Atlas documents. Milton Roemer observed it in 1961, and it is often summarized as a bed built is a bed filled. It is strongest where the decision to intervene is a judgment call, so an expansion justified by a forecast may partly create its own demand.
How do you calculate a three-month moving average of referrals?
Add the latest three months and divide by three, dropping older months. For monthly referrals of 120, 132, 126, and 138, the latest three sum to 396, giving an average of 132. A common mistake is averaging all four months, which gives 129. A moving average smooths noise, while a seasonal index separates seasonal swings from real change.
What is sensitivity testing in demand forecasting?
Sensitivity testing varies one assumption at a time and watches how much the forecast moves. An assumption that barely shifts the result matters less than one whose failure would invalidate the decision, called the breaking assumption. A modest change in the older population share might move a forecast by about 4 percent, while a payer narrowing coverage could cut it by about 20 percent.

About the Healthcare Organization and Management course

How many college credits is Healthcare Organization and Management?
Healthcare Organization and Management (Health 302) carries a NCCRS credit recommendation for 3 semester credits. ACE and NCCRS have over 2,100 cooperating colleges that will consider accepting credits; the final decision is with the universities.
How much does Healthcare Organization and Management cost and what is included?
$250, paid once, with lifetime access: all 105 video lessons, a practice quiz after each, the graded work and final exam, and an official transcript when you finish. Students who want several courses choose UPI Study PRO instead.
Which universities accept UPI Study credits?
UPI Study has signed partner agreements with universities such as Thomas Edison State University, University of the People and Charter Oak State College, and works with universities such as Penn State, SNHU and SUNY. ACE and NCCRS have over 2,100 cooperating colleges that will consider accepting credits; the final decision is with the universities. Use "Find my college" on this page to check yours.
How long does Healthcare Organization and Management take?
It is self-paced with no deadlines. The 105 lessons total about 17 hours of video; most students add reading and practice time and finish in a few weeks to a few months, on their own schedule.
How are the exams done?
Quizzes and assignments are online in the course. The final exam is taken online with proctoring; a person on the UPI Study team checks assignments, usually within two days.
How do my credits reach my college?
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