Evaluating different health care providers
Three hospitals, three rates, and a national average. The differences are small, which is the point: without case mix adjustment and some sense of precision, the ranking may not mean anything.
Editorial process
Last reviewed · August 22, 2026
Small differences, and what would make them meaningful
Define case mix precisely, because a loose definition makes the rest of the report vague. Case mix is the composition of a provider's patients by the characteristics that affect their expected outcomes and resource use: age, comorbidity, severity at presentation, and often socioeconomic and access factors. Risk adjustment is the statistical procedure that uses those characteristics to produce an expected rate for each provider, so an observed rate can be compared with what would have been expected for that provider's own patients. Unadjusted comparison of raw mortality rates therefore penalises exactly the hospitals that take the sickest patients, which usually means the tertiary referral centres. That is not a subtlety: it is the reason public reporting programmes adjust before they publish, and a report that compares the three raw rates without saying so has already made the error the assignment exists to test, whatever it says afterwards about data analysis.
Then look at the numbers, which are chosen to make a point. Hospital A sits a tenth of a percentage point above the national average and Hospital C sits three tenths below, and neither difference means anything without knowing the number of admissions behind it, since a hospital treating two hundred cases and one treating two thousand produce very differently stable rates. Hospital B is 2.6 points above, which is larger but still requires an interval before you can say it is real. Beyond case mix and precision, name the other candidate explanations: transfer practices, whether patients who die shortly after arrival are counted, do-not-resuscitate prevalence, time to reperfusion, hospice transfers, and coding differences in how a heart attack is recorded. For Part II, the response to the administrator should say what data you would need before accepting the ranking, while being careful not to sound like someone explaining away a result that might be real.
Likely learning objectives
- Define case mix and distinguish it from risk adjustment.
- Recognise that unadjusted comparison penalises providers with sicker patients.
- Treat sample size and precision as necessary before interpreting a difference.
- Identify non-quality explanations for an outcome difference.
Assignment instructions
Read the full question
Review every instruction before using the planning guidance that follows.
To help you to better understand why case mix is important to managed care and reimbursement methods; here are some fictional heart attack mortality rates for three different hospitals. Consider the national average for heart attack death rates to be 16%. Hospital Mortality Rate National Mortality Rate Hospital A 16.1% 16% Hospital B 18.6% Hospital C 15.7% Part I Write a 3-4 page report in which you answer the following questions: Explain case mix and why it is important in evaluating different health care providers. Refer to the table of heart attack mortality rates for Hospitals A, B, and C. From your reading this week, what variables might be impacting the rates in the table? Please explain and discuss the use of data analysis for evaluating this kind of information. Part II You are a staff member at Hospital B, which has the worst mortality rate from heart attacks as seen in the table. Imagine that the administrator for Hospital B has asked you to appear at a Press Conference to share your knowledge about case mix. Hospital Mortality Rate National Mortality Rate Hospital A 16.1% 16% Hospital B 18.6% Hospital C 15.7% After participating in the Press Conference, write a 2-page summary to explain the use of date for decision-making purposes, and how the technology department performs critical core business processes essential to the managed care organization.
Course-wide instructions that accompany this question
You must proofread your paper. But do not strictly rely on your computer’s spell-checker and grammar-checker; failure to do so indicates a lack of effort on your part and you can expect your grade to suffer accordingly. Papers with numerous misspelled words and grammatical mistakes will be penalized. Read over your paper – in silence and then aloud – before handing it in and make corrections as necessary. Often it is advantageous to have a friend proofread your paper for obvious errors. Handwritten corrections are preferable to uncorrected mistakes. Use a standard 10 to 12 point (10 to 12 characters per inch) typeface. Smaller or compressed type and papers with small margins or single-spacing are hard to read. It is better to let your essay run over the recommended number of pages than to try to compress it into fewer pages. Likewise, large type, large margins, large indentations, triple-spacing, increased leading (space between lines), increased kerning (space between letters), and any other such attempts at “padding” to increase the length of a paper are unacceptable, wasteful of trees, and will not fool your professor. The paper must be neatly formatted, double-spaced with a one-inch margin on the top, bottom, and sides of each page. When submitting hard copy, be sure to use white paper and print out using dark ink. If it is hard to read your essay, it will also be hard to follow your argument.
Turn the brief into deliverables
- 01A definition of case mix and of risk adjustment.
- 02Why unadjusted comparison misleads.
- 03The variables that might explain the differences in the table.
- 04A statement about sample size and precision.
- 05The use of data analysis in evaluating such comparisons.
- 06A Part II response from the position of a Hospital B staff member.
Case mix, the variables, the analysis, then the response
What case mix is
Define it by the characteristics affecting expected outcome and resource use.
What the assessor is likely looking for
A definition tied to expected outcomes rather than to patient variety.
What risk adjustment does
Explain observed against expected rates for a provider's own population.
What the assessor is likely looking for
The observed-to-expected comparison stated explicitly.
Why the raw table misleads
Show the effect of unadjusted comparison on referral centres.
What the assessor is likely looking for
A named provider type that is systematically disadvantaged.
Precision before interpretation
Explain why sample size decides whether a difference can be read at all.
What the assessor is likely looking for
A statement that the table lacks the denominators needed.
Answering the administrator
Say what data you would need, without explaining the result away.
What the assessor is likely looking for
A request for data that could confirm as well as refute the finding.
Where risk adjustment methods are documented
Recommended databases
- CMS
- PubMed Central
- NCBI Bookshelf
- University Library
Search sequence
- 1.Find how a public reporting programme risk-adjusts its mortality measures.
- 2.Look up an example of risk adjustment changing a provider ranking.
- 3.Read on confidence intervals for rates before interpreting the table.
- 4.Check how coding practice affects reported outcome measures.
Reference shortlist
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.
Risk Adjustment for Hospital Characteristics Reduces Unexplained Hospital Variation in Pressure Injury Risk in Adult Patients in an Integrated Healthcare Delivery System
Nursing Research, via PubMed Central · 2018
Risk adjustment reducing unexplained variation between hospitals.
Hospital Readmissions Reduction Program
Centers for Medicare & Medicaid Services · 2025
A public programme that adjusts outcome measures before comparing providers.
Hypothesis Testing, P Values, Confidence Intervals, and Significance
StatPearls, NCBI Bookshelf · 2023
Significance and intervals, for whether a difference can be read at all.
Incidence
StatPearls, NCBI Bookshelf · 2023
Incidence and rates, for the denominators the table does not supply.
Patient Safety and Quality
Agency for Healthcare Research and Quality, NCBI Bookshelf · 2008
Patient safety and quality, for outcome measurement as a quality signal.
Before you submit this report
Common mistakes
- Defining case mix as the types of patients without connecting it to expected outcomes.
- Interpreting a 0.1 percentage point difference as a finding.
- Ignoring the number of admissions behind each rate.
- Listing only clinical explanations and omitting coding and transfer practice.
- Writing the Part II response as pure defence of Hospital B.
Submission checklist
- Are case mix and risk adjustment defined separately?
- Have you said why raw comparison penalises tertiary centres?
- Is sample size addressed before any rate is interpreted?
- Do your explanations include non-clinical ones?
- Does the Part II response ask for data rather than deny the result?
Use this guide to plan and review your own work. Follow your institution's rules and read Brinevia's academic-integrity policy.
Written by
Maren Caldwell
MSN, RN, CNE
Medical-surgical nursing, pharmacology and NCLEX preparation
Maren is a registered nurse with over 15 years of clinical and educational experience in medical-surgical nursing. She writes on NCLEX preparation, patient care fundamentals, pharmacology and evidence-based practice.
Reviewed by
Dr. Tessa Redmond
DNP, RN, CNE
Evidence-based practice and clinical education
Tessa is a doctorally-prepared nurse educator. She reviews Brinevia content for clinical accuracy and alignment with current evidence-based guidelines.