Inpatient occupancy ratio and conclusions from data

Being asked to create your own data set is an unusual freedom in an assignment and it is worth using deliberately rather than filling in plausible-looking numbers. You control the numbers, so choose ones that produce a finding: a small hospital sitting at 62% occupancy has a real operational problem worth discussing, whereas a tidy 100% leaves you with nothing to analyse and is not credible in any case. Make the set internally consistent — licensed beds, staffed beds, patient days over a defined period, admissions and discharges — because the assignment asks you to show your work, and inconsistent inputs become visible the moment the arithmetic is written out. Distinguish licensed from staffed beds explicitly, since occupancy against licensed capacity and occupancy against staffed capacity are different numbers and managers use them for different arguments — licensed capacity to argue for staffing, staffed capacity to argue that the unit is already full.

The second half is where the real content is. Explaining why a health care manager needs to understand what the software calculates comes down to a few concrete things: knowing which denominator was used, whether observation patients are included, whether the period is a census day or a midnight count, and therefore whether two units' figures are comparable at all. A manager who cannot interrogate the definition cannot notice when a number is wrong or when it is being presented selectively. For the board question, highlight what drives decisions rather than everything available: occupancy trend rather than a single point, average length of stay alongside it since the two move together, bed turnover, and the revenue and staffing consequences. Say why each matters to a board specifically, because a board is deciding about capital and capacity rather than about daily operations. A board dashboard and a unit huddle need different numbers even when they come from the same system.