HIS Cost-Benefit Analysis: Vila Health Rural Hospitals
Build the spreadsheet before the summary — and remember that doing nothing has a cost too, or the proposal is being compared against a free alternative that does not exist.
Editorial process
Last reviewed · August 9, 2026
The spreadsheet comes first
There are two deliverables here and they do different jobs, so build them in the right order. The spreadsheet is the analysis; the two-to-three page executive summary is the argument drawn from it. Complete the spreadsheet first, because the summary's conclusions have to follow from numbers that exist rather than the numbers being assembled afterwards to support a conclusion already written. Note how short the summary is — two to three pages is tight, and it is meant to be. It forces you to report the result, the assumptions it depends on, and the recommendation, without walking the reader through every calculation. The detail lives in the spreadsheet, and the summary points at it. Getting that division of labour right is a substantial part of what this assessment is testing. Label the spreadsheet clearly enough that a reader can follow it without you present, since it is the evidence base your summary rests on and an unlabelled model is indistinguishable from an assertion.
The costs are the easy half and students usually get them roughly right, though the recurring ones are frequently understated. Beyond licensing and hardware there is implementation labour, data migration from whatever the rural sites currently run, interface work, training, the productivity loss during and after go-live, ongoing support and licence renewal, and the eventual upgrade cycle. Two categories are missed most often. First, the *lost productivity* during the transition is a genuine cost and can be estimated from clinician hours. Second, there is a cost to doing nothing — continuing to run and maintain the existing systems, and continuing to work without whatever the new system provides — and a cost-benefit analysis without that baseline is comparing the proposal against a free alternative that does not exist. Distinguish one-off from recurring costs in the model as well, because a total that mixes them cannot be placed on a timeline and the timeline is what the payback period depends on.
Benefits are where the analysis is won or lost, because most of the real ones are hard to put a number on and the temptation is to list them as unquantified and move on. Separate them explicitly into tangible and intangible, and then work harder on the tangible than feels comfortable. Reduced transcription costs, fewer duplicate tests because prior results are visible, shorter records-retrieval time, lower interface maintenance, reduced billing errors and improved coding capture all have plausible dollar figures attached and can be estimated from volumes. For the intangibles — continuity of care when a patient moves between the rural site and the main hospital, clinician satisfaction, reduced error risk — state them, say why they resist quantification, and where possible give a proxy measure rather than leaving them as adjectives. Anchor each estimate to a volume figure from the simulation where you can, since a benefit derived from a stated number of tests or transfers is arguable while one derived from a percentage nobody sourced is not.
The rural context is doing real work in this brief and a generic analysis will miss it. These are *newly acquired* rural hospitals being asked to switch to the system already running at the main hospital, and that shapes both sides of the ledger. Lower patient volumes mean per-patient implementation cost is higher and fixed licence costs are spread more thinly, so an investment that is obviously worthwhile at the main hospital may not be at a small site. Rural facilities may have thinner IT staffing, older equipment and less reliable connectivity, each of which adds cost. But the benefit side gains something specific too: standardising onto one system is what makes transfers between the rural sites and the main hospital work, and that continuity benefit exists only because these hospitals are now part of one system.
Make the analysis auditable, because that is what separates a cost-benefit analysis from a list of numbers. State your time horizon and justify it — five years is conventional for a system investment and roughly matches its useful life. Say whether you are discounting future cash flows and at what rate, since a benefit arriving in year four is not worth a cost paid in year one. Report a summary measure the reader can act on: net benefit, benefit-cost ratio, and payback period each answer a different question and taking all three is inexpensive. Then run a sensitivity check on the one or two assumptions that carry the result. If the recommendation flips when the productivity-loss estimate doubles, the reader needs to know that, and saying so strengthens rather than weakens the case. Show the sensitivity result rather than only mentioning that you ran one, because the range matters more than the point estimate when a reader has to decide how much confidence the recommendation deserves.
Finish by being explicit about assumptions and by recommending something. Every figure you could not obtain from the simulation is an assumption, and assumptions stated openly are legitimate analysis while assumptions buried in a cell are a problem waiting to be found. List them, sourced where possible. Then take a position: proceed, do not proceed, or proceed under stated conditions — and note that phasing is often the honest answer here, converting one site first to test the estimates before committing to the rest. The brief says to justify your recommendation based on best practices, so tie the reasoning to published evidence rather than to the arithmetic alone, and use both supplied templates, the spreadsheet and the APA document. Say what would trigger a review of the decision as well, so that if the assumptions turn out wrong there is an agreed point at which the organisation looks again rather than continuing on a case nobody rechecks.
Ledger item | Frequently missed | How to estimate it |
|---|---|---|
Licensing and hardware | Rarely | Vendor quotes in the simulation |
Implementation labour | Sometimes | Hours by role, at loaded rates |
Data migration | Often | Record volume and conversion scope |
Training | Understated | Staff count x hours x backfill cost |
Productivity loss at go-live | Very often | Clinician hours lost over the dip period |
Cost of doing nothing | Almost always | Current maintenance plus forgone benefit |
Avoided duplicate testing | Under-claimed | Test volume x rate x unit cost |
Continuity across sites | Listed, not valued | Transfer volume as a proxy measure |
Likely learning objectives
Inferred from the brief — check these against your own rubric.
- 01Build a cost-benefit model before drawing conclusions from it.
- 02Include the cost of the do-nothing baseline in the comparison.
- 03Quantify benefits that are usually left as adjectives.
- 04Test whether the recommendation survives its own assumptions.
Read the full question
Review every instruction before using the planning guidance that follows.
What the analysis and summary must contain
- 01A completed cost-benefit spreadsheet on the supplied template.
- 02An executive summary of 2-3 pages on the APA template.
- 03Short-term and long-term costs, itemised.
- 04Tangible and intangible benefits, separated.
- 05A stated time horizon and discounting approach.
- 06Summary measures such as net benefit, ratio and payback.
- 07A recommendation justified against best practice.
From baseline to a recommendation that holds
Scope and baseline
Define what is being compared, including the cost of not proceeding.
Costs, short and long term
Itemise capital, implementation, transition and recurring costs.
Benefits, tangible and intangible
Quantify what can be quantified and proxy what cannot.
The rural adjustment
Reflect low volume, thin IT staffing and connectivity in the model.
Result, sensitivity and recommendation
Report the measures, test the assumptions, and commit to a position.
Take the simulation's figures before assuming any
Recommended databases
- The Vila Health simulation cost data
- PubMed Central
- Health economics literature
- AHRQ and HIMSS value studies
Search sequence
- 1.Extract every figure the simulation supplies before looking anywhere else, because those are the only numbers specific to this case and everything else is an assumption.
- 2.Find a published economic evaluation of a health IT investment so your model's structure follows an accepted method rather than an invented one.
- 3.Look for evidence on what determines whether health IT investment returns value, which is what the brief means by justifying against best practices.
- 4.Search for benefit estimates you can use as benchmarks, so your tangible figures are defensible rather than assumed.
Worked evaluations and investment frameworks
These are authoritative starting points, not a ready-made bibliography. A qualified reviewer must confirm that each source fits the assignment and supports the claim beside which it is cited.
Nothing here is cleared for citation until you have read it.
- 01
Hospital Investment Decisions in Healthcare 4.0 Technologies: Scoping Review and Framework for Exploring Adoption Determinants
Journal of Medical Internet Research · 2021
A framework for what actually drives a hospital investment decision, which is what the brief means by justifying the recommendation against best practice rather than against the arithmetic alone.
- 02
Economic analysis of cloud-based desktop virtualization implementation at a hospital
BMC Medical Informatics and Decision Making · 2012
A worked hospital IT cost-benefit analysis with its cost categories and time horizon set out explicitly. The closest published model for the structure your spreadsheet should take.
- 03
Valuing hospital investment in information technology: does governance make a difference?
Health Care Financing Review · 2006
Evidence that the same investment returns different value depending on how it is governed, which supports recommending conditions alongside a decision rather than a bare yes or no.
- 04
An economic evaluation of the effectiveness of telemedicine in hematooncology
PLOS ONE · 2023
A recent economic evaluation in a setting where distance is the problem being solved, which is the closest analogue to connecting rural sites to a main hospital. Useful for how it handles benefits that resist direct pricing.
Before the cost-benefit analysis is submitted
Common mistakes
- Writing the summary first and fitting the numbers to it.
- Walking through every calculation in a two-to-three page summary.
- Omitting the cost of continuing as things are.
- Understating training by ignoring backfill.
- Leaving out the productivity dip at and after go-live.
- Listing intangible benefits without proxies or explanation.
- Applying main-hospital economics to a low-volume rural site.
- Ignoring rural constraints on IT staffing and connectivity.
- Stating no time horizon, so costs and benefits are not comparable.
- Reporting one summary measure where three answer different questions.
- Burying assumptions in spreadsheet cells rather than listing them.
Submission checklist
- The spreadsheet was completed before the summary was written.
- Costs include implementation, migration, training and support.
- The productivity loss at transition is costed.
- A do-nothing baseline is included.
- Tangible benefits carry estimated figures.
- Intangible benefits carry proxies or a stated reason they cannot.
- Rural volume and staffing differences are reflected in the numbers.
- The time horizon is stated and justified.
- Discounting is addressed.
- A sensitivity check is run on the decisive assumptions.
- The recommendation is explicit and tied to best practice.
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Written by
Aaron Bishop
MA, Education
assignment interpretation and research-methods coaching across disciplines
Aaron leads the EssayCrackers editorial desk. He works on how assignment briefs are read — what a rubric is actually asking for, and where students most often answer a different question than the one set.
Reviewed by
Dr. Nathan Cole
PhD, Rhetoric & Composition
Argumentation and thesis development
Nathan teaches first-year composition and directs a university writing center. He reviews EssayCrackers guides for argumentative soundness and citation accuracy.