PAHM common mistakes
PAHM · Understand the traps and how to avoid them.
Treating Medicare, Medicaid, and commercial insurance as interchangeable when answering questions about eligibility, benefits, or who bears financial risk.
Candidates memorize program names but not the underlying federal-state split, mandatory vs. optional populations, and the different cost-sharing structures, so they default to whichever program they have seen most in their own workplace.
What to do instead
Build a one-page comparison grid for Medicare (Part A/B/C/D, eligibility by age/disability/ESRD), Medicaid (federal floor, state options, FMAP, waiver authority), and commercial products. Before answering, identify which program the stem names and recall that row of the grid.
Confusing the delivery model with the payment model, e.g., labeling an ACO a capitated HMO or calling a patient-centered medical home a payment arrangement.
Real organizations combine several structures at once, so candidates collapse overlapping terms into a single label instead of separating who delivers care from how providers are paid and who holds risk.
What to do instead
For each scenario, answer three separate questions: what entity delivers care, what payment method applies, and where risk sits. Keep a glossary that lists each model under exactly one of those three headings.
Mixing up HMO, PPO, POS, and EPO on the specific dimensions of network use, referral requirements, and out-of-network coverage.
The plan types share features and the labels are used loosely in marketing, so candidates rely on vague impressions such as 'HMO is cheaper' rather than the structural rules.
What to do instead
Memorize a four-column table (network requirement, PCP/referral gatekeeping, out-of-network benefit, typical cost-sharing) and practice classifying short vignettes until each plan type is identified from its rules rather than its price.
Applying the wrong cost-sharing term to the wrong stage of the claim, e.g., calling the annual maximum an out-of-pocket limit or treating coinsurance as a flat dollar amount.
Deductible, copay, coinsurance, out-of-pocket maximum, and benefit maximum are learned as a list rather than as a sequence, so candidates cannot place a dollar figure in the correct step of adjudication.
What to do instead
Walk claims through the sequence in order: allowed amount, deductible, coinsurance or copay, then out-of-pocket maximum accumulation. Compute two or three small numeric examples by hand so the order becomes automatic.
Reversing the direction of risk in capitation and shared-savings questions, e.g., stating the payer bears utilization risk under capitation or that savings accrue to the provider in a downside-only arrangement.
Candidates focus on the payment formula and not on who keeps or absorbs the surplus and loss, which is the point the question is testing.
What to do instead
For every payment question, explicitly write 'who pays whom, for what, and who keeps the surplus or absorbs the loss' before selecting an answer. Practice with upside-only, downside-only, and two-sided risk variants.
Calculating revenue-cycle metrics such as days in accounts receivable, clean-claim rate, or net collection rate with the wrong numerator or denominator, or mixing gross and net figures.
Formulas are memorized as strings without understanding what each component represents, and gross charges versus contractual allowances are used interchangeably.
What to do instead
Learn each metric with a worked example and a statement of what a rising or falling value means operationally. Always confirm whether the metric is defined on gross or net revenue before computing.
Choosing a quality improvement tool that does not match the problem, such as using a control chart for a one-time process redesign or a Pareto chart when the goal is testing a change.
Candidates recognize tool names but not the question each tool answers, so they select by familiarity rather than by fit to the stated aim.
What to do instead
Map each tool to its purpose: Pareto for prioritizing causes, fishbone for cause generation, control chart for distinguishing common from special cause variation, PDSA for testing changes, FMEA for prospective risk. Read the stem's stated goal first, then pick the tool.
Treating accreditation standards, conditions of participation, and state licensure as a single undifferentiated compliance obligation.
All three are encountered as 'rules the organization must follow,' and candidates do not distinguish who issues them, what they cover, and what happens when they are not met.
What to do instead
Create a three-column table (issuer, scope, consequence of noncompliance) for accreditation bodies, CMS conditions of participation, and state licensure. When a stem names a requirement, first ask which of the three issuers would have set it.
Overlooking privacy and security obligations in operational scenarios, such as permitting disclosure for treatment, payment, or operations without checking minimum necessary or authorization requirements.
Candidates remember that protected health information is confidential but not the permitted-use categories and their limits, so they apply a blanket 'never share' or blanket 'always share' rule.
What to do instead
Memorize the permitted disclosure categories and the minimum-necessary standard, then for each scenario identify the purpose of the disclosure and whether an authorization is required. Practice distinguishing treatment, payment, and operations from marketing and research.
Endorsing a data-analytics conclusion without checking data quality, denominator definition, or confounding, e.g., accepting a readmission rate comparison across populations with different risk profiles.
Candidates focus on the reported number and the dashboard presentation rather than on how the measure was constructed, and small or unadjusted comparisons look convincing.
What to do instead
Before accepting any metric, ask four questions: what is the denominator, is the population risk-adjusted, what is the data source and completeness, and is the difference larger than expected variation. Apply these to every analytics stem before choosing an answer.