MMHA 6900 · Week 5

MMHA 6900 Week 5 postoperative VTE safety analysis example

Healthcare Quality Management Walden University Free custom sample in 24 to 48h

A patient safety indicator built from billing data flagged a run of blood clots after surgery at an illustrative regional medical center, and the first finding of this analysis is that not every flag was an event. It validates the flagged cases against the chart, then traces the confirmed ones through the Systems Engineering Initiative for Patient Safety work system model to causes in design.

What this page holds

Flagged cases are validated before causes are sought in the Week 5 postoperative VTE safety analysis, an example from MMHA 6900 built on the SEIPS work system model. Searches like "mmha 6900 week 5 assignment example", "mmha6900 week 5 sample" and "mmha 6900 week 5 example" land here.

What a finished MMHA 6900 Week 5 postoperative VTE safety analysis looks like

Three parts across roughly six pages. The first explains the indicator: AHRQ's measure for perioperative pulmonary embolism or deep vein thrombosis, derived from discharge coding, and one component of the patient safety composite the Hospital-Acquired Condition Reduction Program uses. The validation section reviews every flagged chart and sorts cases into confirmed hospital-acquired events, conditions present on admission, and coding artifacts, with the sorting rules stated. Next, the confirmed cases are mapped onto the SEIPS model's work system elements: the person, the tasks, the tools and technology, the organization and the environment. Findings include a risk assessment that the order set leaves optional, prophylaxis doses missed while patients were off the unit, and no pharmacist review of prophylaxis choices. Recommendations are ranked by how much they depend on memory.

How a MMHA 6900 Week 5 example is structured

The indicator is explained before any case is examined, because a reader has to know the flag comes from coded billing data to understand why validation is necessary at all. Validation precedes analysis for a plain reason: tracing causes for events that did not happen wastes a review and, worse, points the organization at problems it does not have. Sorting rules are stated so the classification could be repeated by another reviewer. The SEIPS model structures the analysis because it spreads attention across the whole work system rather than stopping at the clinician nearest the event, and each finding is placed in the element where it lives. Recommendations are ranked by reliance on memory, favoring defaults and forcing steps over reminders. The payment program is mentioned where the indicator is introduced and not again, keeping the analysis about patients.

A flag, not an event

The indicator comes from discharge coding. Until a chart confirms it, each flag is a question rather than a finding.

Three piles

Confirmed hospital-acquired events, conditions present on admission and coding artifacts are sorted by stated rules.

Five elements of the work system

Person, tasks, tools and technology, organization and environment each receive the findings that belong to them.

An optional step, a missed dose, no second look

Risk assessment left optional, doses missed off the unit and no pharmacist review sit in three different elements.

Ranked by reliance on memory

A default order and a missed-dose alert rank above education, because they work on busy days too.

Where marks go in MMHA 6900 Week 5

Safety analyses here are credited for reaching the system, and one ending at a surgeon who forgot to order prophylaxis has stopped where the analysis should begin. Validation sets strong submissions apart: rubrics asking about data quality reward a document that checks coded events against charts before treating them as harm. Analysis credit follows the model's use, so SEIPS elements must hold findings that genuinely belong to them rather than serve as headings over a list. Accuracy about sources matters, since describing an AHRQ indicator as a clinical registry or misplacing its role in the payment composite invites correction. Recommendations earn credit for strength and fit to findings. Submissions that name the payment consequence as the reason for the analysis, instead of patient harm, tend to lose tone points with instructors.

Get a MMHA 6900 Week 5 example written to your instructions

Which safety event or indicator does the prompt concern? Say so, include any case your section distributes, attach the rubric too, and the analysis is traced through whichever model the course assigns. Nothing is charged for the first request, answered in 24 to 48 hours. No patient chart was read for the flagged cases, which were invented along with the hospital.

MMHA 6900 Week 5 questions, answered

Why validate flagged cases before analyzing them?

Because indicators derived from billing data flag cases that may not be hospital-acquired events at all: some conditions were present on admission, and some flags reflect coding rather than care. Analyzing those as harm produces fixes for problems that did not occur. The example sorts every flagged case by stated rules first, then studies only the confirmed events.

What is the SEIPS model?

The Systems Engineering Initiative for Patient Safety model, associated with Pascale Carayon and colleagues, describes a work system made up of the person, tasks, tools and technology, organization and environment, and links it to care processes and outcomes. Its central idea is that safety emerges from how those elements interact. The example uses it to place each finding in the element where a fix could act.

How does this indicator connect to payment?

The perioperative clot indicator is one component of the patient safety composite that the Hospital-Acquired Condition Reduction Program includes, alongside infection measures. Hospitals performing worst on that program's measures receive a Medicare payment reduction. The example mentions the connection once, when introducing the indicator, and keeps the analysis focused on why patients were harmed.