HIM 400 is SNHU’s Communication and Technologies II course. It centers on health data and technology management: project scope, schedules and risk for information technology work, relational database design and data dictionaries, structured queries and data requests, data quality, trend analysis and control charts, data mining and predictive models, bias in algorithms, health information exchange, patient access and information blocking, and system acquisition through requests for proposals and weighted vendor scoring. Every module below opens a full sample paper or takes a free request for one; searches like "him 400 module 3", "HIM400 sample paper" and "HIM 400 milestone example" land on this page.
What HIM 400 is really about
As the second communication and technologies course in SNHU's BS Health Information Management sequence, HIM 400 rewards data work that another analyst could repeat. Graders look for correct database vocabulary, queries and definitions stated precisely, analyses that name their denominators and time windows, models judged on fairness as well as accuracy, sharing rules applied to the right actor and technology purchases justified with criteria and total cost.
All samples here come from a composite health informatics analyst at Cold Brook Health, a two-hospital system in rural Maine with 14 primary care practices and about 6,800 adult patients with diabetes. The registry misses patients whose lab results arrive from outside labs, 28% of patients with diabetes had a latest HbA1c above 9% or no test in the past year and about 12% of primary care visits end as no-shows. Across the term, the analyst designs, queries, analyzes and proposes. The analyst and system are illustrative.
What HIM 400’s modules ask for
Across eight modules, HIM 400 typically asks for discussions of technology project management and of algorithms in health data, short papers on database structures, data extraction, data mining and data sharing regulation, a Module 4 project that analyzes trends and patterns in a data set, a second project that proposes a system acquisition and knowledge activities in data analytics.
Where students lose points in HIM 400
The most common HIM 400 deduction is data work described too vaguely to repeat: a query with no stated inclusion rules, a rate with no denominator or time window, or a trend claimed from two data points. The second is treating a predictive model as good because it is accurate, without asking whom it misses. Graders also mark down sharing papers that confuse HIPAA with information blocking rules and acquisition proposals that compare license prices but ignore staff, training and interface costs. The fix is to define every measure and weigh every trade-off.
The HIM 400 drawers
HIM 400 Module 1 Discussion example
The course opens with a composite health informatics analyst explaining why a lab interface project at a rural health system is ten weeks late, using Kaplan and Harris-Salamone on why health IT projects succeed or fail and Sittig and Singh's sociotechnical model to argue that scope, sponsorship and workflow, not software, sank the schedule. Full sample paper, read it free.
HIM 400 Module 2 Database Structures Short Paper example
A composite health informatics analyst redesigns a spreadsheet diabetes registry as a relational database: seven tables with primary and foreign keys, an attribution table for the many-to-many link between patients and clinicians, normalization to third normal form, LOINC and ICD-10-CM fields, a data dictionary excerpt and plausibility constraints, with Hripcsak and Albers on phenotypes, Weiskopf and Weng on data quality and Bates and colleagues on registry analytics. Full sample paper, read it free.
HIM 400 Module 3 Data Extraction Short Paper example
A composite analyst answers two data requests from the same registry: an internal outreach list of patients with an HbA1c above 9%, built clause by clause in SQL with stated inclusion, exclusion and look-back rules, and an outside university's request, answered with a limited data set under a data use agreement, with Kern, Parsons and colleagues on how query-based measures miss care and El Emam and colleagues on re-identification. Full sample paper, read it free.
HIM 400 Module 4 Project One example
A trends and patterns analysis by a composite health informatics analyst: eight quarters of poor HbA1c control across a rural system's 14 practices, a p-chart showing a sustained rise, the rise split into untested and poorly controlled patients, subgroup patterns by age, coverage and travel distance, a funnel plot flagging two practices and a data capture caveat, drawing on Ali, Benneyan, Mohammed, Spiegelhalter and Parsons and colleagues. Full sample paper, read it free.
HIM 400 Module 5 Data Mining Short Paper example
A composite analyst mines two years of primary care appointments to predict no-shows: the data mining process, candidate predictors, a logistic regression and a tree-based model tested on a later year, sensitivity and positive predictive value at a 15% flag threshold, subgroup results by coverage and distance and a decision to use flags for outreach instead of overbooking, drawing on Dantas, Rajkomar, Obermeyer and Char and colleagues. Full sample paper, read it free.
HIM 400 Module 6 Data Sharing Short Paper example
A composite analyst applies data sharing rules to three situations at a rural health system: a seven-day hold on portal lab results, a partner clinic's request through the statewide exchange that includes substance use treatment notes and a patient's third-party app pulling records through a FHIR API, sorting what HIPAA permits from what the Cures Act information blocking rules require, with Menachemi, Adler-Milstein and Pfeifer and Mandel and colleagues. Full sample paper, read it free.
HIM 400 Module 7 Project Two example
A system acquisition proposal from a composite analyst: requirements drawn from the term's registry, query and trend work, three options (the record vendor's population health module, an independent platform and an in-house build), a request for proposals with scripted demonstrations and usability testing, weighted scoring, five-year total cost of ownership, a recommendation and an implementation plan with a charter, phases, risks and success measures, citing Cresswell, Sittig and Singh, Ratwani, Adler-Milstein and Bates and colleagues. Full sample paper, read it free.
HIM 400 Module 8 Discussion example
The closing post from the composite analyst asks what it would take for clinicians and patients to trust the platform's lists and risk scores, drawing on Rajkomar and colleagues on how machine learning fails when data shift, Obermeyer and colleagues on proxy labels and Char and colleagues on the incentives of those who build models, and names three habits of a trustworthy data team. Full sample paper, read it free.
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Using a HIM 400 sample the right way
Read an HIM 400 sample by checking whether every measure has a stated numerator, denominator and period, whether queries and models could be rebuilt from the description and whether each technology choice names its costs and risks. For HIM 400, send the assignment wording, any data set or scenario and the rubric; a first custom sample is returned free in 24-48h.
HIM 400 questions, answered
What does HIM 400 cover?
Project management, database structures, data extraction, data analysis and mining, data sharing and regulation and system acquisition for health information technology.
Do I need to write SQL in HIM 400?
Many versions include query exercises and data analytics activities, so samples show queries written out and explain the logic behind each clause.
What makes a strong HIM 400 paper?
Precise definitions, repeatable methods, measures with denominators and time windows and technology decisions weighed on cost, risk and fairness.