Healthcare Earnings Tracker Excel: Q1 2026 Pharma and Insurance Watchlist

Healthcare earnings tracker excel is a practical way to organize Q1 2026 earnings season for one of the most complex sectors in the market. Pharma, managed care, medical devices, life sciences tools, and health services all sit inside a single GICS sector, but each sub-group responds to completely different drivers. A good spreadsheet puts them on the same page so you can compare valuation, income, quality, and trend context without flipping between ten browser tabs. This guide shows how to build that workbook in Excel, which verified MarketXLS formulas power it, and how to use the template for educational market analysis rather than stock recommendations.

Q1 2026 reporting is the reason this matters right now. UnitedHealth, Johnson and Johnson, Abbott, and Elevance Health already kicked off the sector calendar in mid-April, with Eli Lilly, Merck, Pfizer, AbbVie, Thermo Fisher, and CVS Health still to come over the next two to three weeks. The market is reading several things at once: medical cost ratios at the big payors, GLP-1 demand trends at Lilly and Novo Nordisk, tariff and supply chain commentary from device makers, biopharma spending signals from the tools companies, and retail traffic at CVS. A single dashboard makes those signals easier to compare over a compressed calendar.

Here is a lightweight above-the-fold watchlist that the template is organized around.

Why a healthcare earnings tracker excel makes sense in Q1 2026

Healthcare is often labeled defensive. That label is true at the sector level and misleading underneath it. Managed care insurers trade on medical cost ratios and policy risk, not on consumer demand. Branded pharma trades on pipelines, patent cliffs, and pricing. Generic-heavy names trade on volume and contracting dynamics. Device makers sit close to hospital budgets and procedure trends. Life sciences tools follow biotech funding cycles. Health services and pharmacy chains are a mix of retail foot traffic and pharmacy benefit economics.

In Q1 2026, these sub-groups are diverging more than usual. Managed care entered the year with elevated medical cost trends after a post-pandemic utilization rebound that stayed stickier than payors expected. Any commentary on the medical loss ratio during earnings calls is therefore a bigger deal than it used to be. On the pharma side, the weight-loss category continues to reshape the large-cap landscape. Lilly is the market leader on GLP-1 receptor agonists, and the market is watching both volume trends in Zepbound and Mounjaro, and the competitive pressure from Novo Nordisk. AbbVie is still lapping the Humira biosimilar erosion, with Skyrizi and Rinvoq filling in the gap. Pfizer is working through a post-COVID comparison reset. Merck is using Q1 2026 as another test of whether its post-Keytruda pipeline narrative is on track.

The device and tools groups tell a related story. Abbott and other device makers want to see procedure volumes hold up, and any change in hospital capital spending matters. Thermo Fisher sits near the end of the biopharma funding cycle, and its outlook is one of the cleaner reads on whether biotech capex has stabilized. Life sciences tools behave more cyclically than many investors assume, which is why a single tracker is useful: the table puts TMO next to the payors and pharma names so the beta differences are visible.

Those cross-currents are exactly why a repeatable Excel workbook helps. Instead of reacting to one company headline at a time, you can use the same data structure to compare the same companies across the same metrics every quarter.

What this healthcare earnings tracker excel is designed to answer

A useful healthcare workbook should help answer a short list of practical questions during earnings season:

1. Which companies show the cleanest balance of valuation, operating margin, and dividend yield?
2. Which names are still trading near their 52-week highs on a relative basis?
3. How do payors compare to pharma on trailing valuation and margin profile?
4. Which sub-groups look more or less defensive on a beta and yield basis?
5. How should different policy and demand scenarios reshape the watchlist?

The reason this template uses six sheets instead of a single screener tab is that those five questions do not fit on one view. A one-tab screener can show quotes and ratios, but it rarely helps with scenario thinking, sizing assumptions, or comparison logic across sub-groups. The workbook in this post is meant to make earnings season a repeatable educational process.

The six-sheet workbook structure

Two files are linked below. They share the same layout.

Download the templates:

• - Pre-filled with current-style sample data and formula references
• - Live-updating formulas with no static market data in the core tables

The download pair lets you do two things at once. The static file is a lead-magnet style snapshot with a visible "Data as of" date, so the numbers in the dashboard are consistent as you read the post. The live template file is the real tool. Every data cell in the dashboard is an actual MarketXLS formula, so the workbook updates every time you open it in an Excel session with MarketXLS installed.

Here is what each sheet does.

1. How To Use

This sheet explains the full workflow and includes direct links to MarketXLS and Book a Demo. In the sample workbook, it shows the data date so users know they are looking at a static snapshot. In the live template, it notes that formulas refresh through MarketXLS rather than from static values.

Every sheet in the workbook carries a dedicated MarketXLS Functions Used section. That matters because many template users do not just want a finished spreadsheet. They want to see the exact formulas behind it so they can adapt the logic to other sectors and other earnings seasons.

2. Main Dashboard

The dashboard is the central sheet. It includes yellow input cells for:

• Portfolio size
• Max position weight
• Base scenario EPS move
• Earnings season flag

These input cells flow through the scenario and allocation sheets so you are not changing the same assumption in multiple places.

The main table tracks each company across the following fields:

• Sub-group (pharma, managed care, devices, tools, services)
• Sector
• Last price
• P/E ratio
• Dividend yield
• Beta
• Market capitalization
• Revenue
• EPS
• Operating margin
• 50-day simple moving average
• RSI
• 52-week high
• 52-week low
• Composite score

The composite score is not a buy or sell signal. It is a sorting tool. It combines a valuation component (inverse of P/E), an income component (yield), a risk component (inverse beta), a quality component (operating margin), a trend component (closeness to 52-week high), and an earnings level component (EPS relative to the group). That is a far more useful starting point than ranking by any single metric, and it keeps the workbook honest about what it can and cannot do.

3. Scenario Analysis

This sheet turns macro and policy uncertainty into structured thinking. Instead of reacting to every earnings headline, you can pre-map several environments:

• Base case with pricing pressure stable
• Bull case with pricing pressure easing and volumes improving
• Bear case with pricing pressure rising and margins contracting
• Payor-squeeze case where medical cost ratios move higher even with stable pricing
• Rate-cut case where a friendlier yield backdrop supports capital-intensive names like devices and tools

Each row shows an implied revenue move and an implied EPS move, along with a watchlist bias phrase. The point is not to forecast these outcomes. The point is to have a repeatable set of assumptions you can adjust and rerun each quarter without building the scaffolding again.

4. Strategy / Positioning

This sheet turns the dashboard data into a simple qualitative table. Each row shows the sub-group, a positioning theme, trailing yield, beta, operating margin, and a Core or Satellite label driven by a small formula. The tier formula in the live version is:

=IF(AND(Beta<0.5, OperatingMargin>0.15), "Core", "Satellite")

That rule is deliberately simple. Lower beta plus healthier operating margin moves a name toward a Core slot. Higher beta or thinner margins push it toward a Satellite slot. The point is to take an educational position on how to think about exposure, not to tell anyone what to buy.

Review triggers are listed too. Healthcare earnings calls tend to move on a few recurring signals: medical cost ratio commentary at payors, script trends in key therapeutic categories, device procedure volumes, and biotech funding color at the tools companies. Having a review trigger column makes the tracker actionable across quarters.

5. Portfolio / Allocation

This sheet sizes positions using the portfolio size and max weight inputs from the dashboard. It pulls the composite score from the dashboard, divides the scores to create proportional weights, and caps each position at the max weight input. It then multiplies weights by the portfolio size for a dollar allocation view. Finally, it shows a yield contribution per position and a beta contribution per position, with a portfolio total row at the bottom.

This is educational, not prescriptive. The allocation sheet is designed to help you think about relative sizing within a watchlist, not to produce a trade list. It assumes you already have a process for portfolio construction and risk management.

6. Correlation / Comparison

The final sheet is a comparison table. It shows price, 50-day SMA, 52-week high, 52-week low, percentage of 52-week high, dividend yield, P/E, and operating margin. The percentage of 52-week high column is the most useful for scanning relative strength across the watchlist. It is a simple formula, but over a full quarter it tells a clean story about which names the market is treating as leaders and which are consolidating.

MarketXLS formulas used in the healthcare earnings tracker

Every formula in the workbook is verified. Here are the core functions, with a short example for each.

=QM_Last("UNH")              → Current price snapshot for UnitedHealth
=PERatio("LLY")              → Trailing P/E for Eli Lilly
=DividendYield("PFE")        → Trailing dividend yield for Pfizer
=Beta("ABT")                 → Beta for Abbott Laboratories
=MarketCapitalization("JNJ") → Market cap for Johnson and Johnson
=Revenue("CVS")              → Trailing revenue for CVS Health
=EarningsPerShare("ELV")     → Trailing EPS for Elevance Health
=OperatingMargin("MRK")      → Operating margin for Merck
=SimpleMovingAverage("ABBV", 50) → 50-day SMA for AbbVie
=RelativeStrengthIndex("TMO") → 14-day RSI for Thermo Fisher
=FiftyTwoWeekHigh("UNH")     → 52-week high for UnitedHealth
=FiftyTwoWeekLow("LLY")      → 52-week low for Eli Lilly
=Sector("JNJ")               → Sector label, returns Healthcare
=Industry("ABT")             → Industry label, returns Medical Devices

The template keeps the formula surface small on purpose. These are the workhorses. For more advanced workbooks, MarketXLS exposes more than a thousand functions, including options chain, historical prices, earnings dates, and technical indicators. A good way to explore further is the MarketXLS features page.

A few notes on the formulas above. First, the QM_ prefix means the function pulls from the QuoteMedia data feed. If these stop returning values during an Excel session, a quick refresh of the MarketXLS data connection usually resolves it. Second, SimpleMovingAverage takes a ticker and a period in days. Fifty is a common medium-term reference, but 20 or 200 work the same way. Third, DividendYield returns a decimal, so 0.0311 means 3.11 percent. The workbook is set up to display these as percentages for readability.

How to read the sample sheet for Q1 2026

The sample workbook is a snapshot. It is useful as a reading aid rather than a trading tool. A quick read of the top of the composite score ranking shows what the scoring logic tends to favor.

First, healthier operating margins matter. Merck and AbbVie score well because the margin component is weighted more than the valuation component. Healthcare operating margins vary widely across sub-groups, and giving margin a meaningful weight rewards the pharma names with more durable branded franchises.

Second, the valuation component uses inverse of P/E, so names with a lower trailing P/E get a boost. CVS and Pfizer get credit for that. Neither is a call on the business. It is just how the math works.

Third, the trend component rewards names trading closer to their 52-week high. Lilly, AbbVie, and UnitedHealth sit relatively close to recent highs in the sample. That pushes their trend contribution higher.

Fourth, the yield component rewards names with a stronger dividend. Pfizer stands out on that line, with a dividend yield north of 6 percent in the sample. Again, that is a data signal, not a recommendation.

Put those components together and the ranking is never a single story. That is the point of using a composite. You can also change the weights directly in the formula if you want to emphasize different things. A more defensive reader might increase the operating margin weight and lower the trend weight. A more income-focused reader might do the opposite.

Building a healthcare watchlist from scratch in Excel

If you want to extend the workbook or rebuild it, here is the short version of the process.

1. Start with a ticker list. Pick a healthy mix across sub-groups: payors, large-cap pharma, diversified pharma, devices, tools, and services.
2. Add company names and sub-group labels manually. The template already uses text labels because sub-group is a useful lens that is not returned by any single function.
3. Use =Sector(Ticker) and =Industry(Ticker) to confirm classification. For the tickers in this workbook, sector returns Healthcare.
4. Pull price, valuation, and quality fields with =QM_Last, =PERatio, =DividendYield, =Beta, =MarketCapitalization, =Revenue, =EarningsPerShare, and =OperatingMargin.
5. Add trend and momentum fields: =SimpleMovingAverage(Ticker, 50), =FiftyTwoWeekHigh(Ticker), =FiftyTwoWeekLow(Ticker), and =RelativeStrengthIndex(Ticker).
6. Build a composite score with a formula that blends valuation, yield, risk, quality, and trend. Keep the weights explicit so you can tune them.

If you are building your own version in the MarketXLS environment, the MarketXLS documentation and the MarketXLS for advisors pages are good references. The MarketXLS pricing page covers current tiers.

Scenario thinking for healthcare earnings

The scenario sheet uses five broad environments. Here is how each tends to shape the watchlist.

In a base case, the Federal Reserve stays patient, utilization at payors normalizes slowly, and large-cap pharma continues to trade on franchise durability. Revenue moves are modest across the group, and EPS dispersion depends more on individual company execution than on the sector backdrop.

In a bull case, pricing pressure across therapeutic categories eases, volumes in newer franchises keep climbing, and margins expand. Names with strong pipelines and meaningful exposure to high-demand categories like GLP-1 tend to benefit most. This environment also helps life sciences tools because biopharma capex tends to follow an upcycle in new drug launches.

In a bear case, pricing pressure increases, volumes soften, and margins contract. Diversified pharma and defensive payors with disciplined medical cost management tend to hold up better than high-multiple growth names. A spreadsheet that ranks names by quality rather than by momentum helps here.

A payor-squeeze scenario is a more specific downside. If the medical cost ratio at managed care insurers ticks up again, share prices in the subgroup often reprice quickly. This is where the sub-group label in the dashboard becomes useful. You can instantly see where UNH, ELV, and the other payors sit relative to the broader sector.

A rate-cut scenario benefits capital-intensive parts of the sector most. Devices and tools names with long investment cycles tend to re-rate on a friendlier yield backdrop. Payors and diversified pharma benefit less directly.

None of these scenarios are predictions. They are educational overlays that help you think about a watchlist across different possible environments. That is the analytical habit the workbook is designed to support.

Policy and pricing risk

One sentence of honesty here: healthcare is the sector with the most policy risk in the market. Drug pricing rules, Medicare Advantage rate notices, pharmacy benefit manager reform, and biosimilar entry schedules all shape earnings outcomes. That is part of why a repeatable tracker matters. Policy headlines come at irregular intervals and from multiple sources. A workbook that resets quickly lets you rerun the same comparisons as conditions change.

The workbook deliberately avoids specific policy forecasts. It does not try to predict rate notices, settlement rulings, or legislative timelines. Instead, the scenario sheet encodes the direction of pricing and utilization pressure at a general level, which is usually the most useful frame for educational analysis.

Tying the healthcare tracker into a broader process

A healthcare earnings tracker works best when it is one piece of a larger process. A few practical tie-ins:

• Sector allocation: compare the workbook against a similar template for other defensive sectors like consumer staples or utilities. Healthcare is not as uniformly defensive as those sectors, but it occupies a similar slot in many portfolios.
• Macro overlay: pair it with a sector rotation model that shifts weights by Fed stance or yield curve state. Healthcare behaves differently under cuts than under hikes.
• Individual sub-group deep dives: if you want a closer look at one subgroup, a more focused workbook such as a regional bank earnings tracker is a good reference for the single-sub-group layout. A pharma-only version of this workbook would look similar.
• Income focus: combine the yield column with a broader dividend calendar workbook and a dividend reinvestment view.

The broader point is that this tracker slots into a process of ongoing comparison, not a one-off check.

FAQ: Healthcare earnings tracker excel

What does the healthcare earnings tracker excel do?

The workbook compares ten large-cap healthcare names across valuation, income, quality, and trend fields in a single Excel dashboard. It organizes them by sub-group (pharma, managed care, devices, tools, services) and calculates a composite score for sorting. It also includes scenario analysis, a simple positioning sheet, an allocation view, and a correlation-style comparison table.

Which MarketXLS formulas power the tracker?

The core functions are QM_Last, PERatio, DividendYield, Beta, MarketCapitalization, Revenue, EarningsPerShare, OperatingMargin, SimpleMovingAverage, RelativeStrengthIndex, FiftyTwoWeekHigh, FiftyTwoWeekLow, Sector, and Industry. Every sheet in the workbook carries a MarketXLS Functions Used section so users can see exactly which formulas drive each view.

Is this a buy list or investment advice?

No. The workbook is educational. The composite score is a sorting tool, not a recommendation. The scenario analysis uses directional assumptions, not forecasts. All positioning and allocation sheets are designed to help structure thinking, not to suggest specific trades.

How is this different from a generic stock screener?

Most screeners return a one-time list. This workbook is a repeatable process. It has named input cells, a scenario sheet, a positioning sheet, and an allocation sheet, all linked back to the dashboard. You can update the watchlist or change the input assumptions and the rest of the workbook updates with them. It is built to be run every quarter during earnings season, not once.

How do I customize the composite score?

The score formula lives directly in the dashboard. Each component has an explicit weight: valuation, yield, risk, quality, trend, earnings level, and relative price level. You can rebalance the weights by editing the numbers in the formula. A more income-focused user might increase the yield weight and reduce the valuation weight. A more growth-focused user might do the opposite.

Why include a life sciences tools name alongside pharma and payors?

Because the sub-group mix is the point. Thermo Fisher behaves differently from a managed care payor and from a large-cap pharma company. Putting them in the same workbook is what lets the user see the beta difference, the margin difference, and the trend difference side by side. That cross-sub-group view is the main reason to use a sector workbook rather than a sub-group workbook.

The bottom line

A healthcare earnings tracker excel is most useful when it is simple, repeatable, and honest about what it can do. The workbook in this post uses a small number of verified MarketXLS formulas, a clear composite score, and a set of scenario overlays that can be tuned without rebuilding the sheet. It is meant for advisors and self-directed investors who want a documented, reusable process for Q1 2026 and for every earnings season after that.

If you want to go deeper, explore the MarketXLS features page for the full function library, or book a demo to see how MarketXLS connects live financial data into Excel in a production workflow.

Disclaimer: This content is for educational purposes only. It is not investment advice, a recommendation to buy or sell any security, or a forecast of market returns. Always do your own research or consult a licensed advisor before making investment decisions.