The elderly population in California is growing at rates that may mean there are parts of the state that aren't going to be ready to provide the needed nursing home services. We decided to tackle this challenge using the dataset from the CA Healthcare Foundation. It collects data and reported information from all the 1200+ facilites.

The Big Question

How prepared are we to accommodate the growth in the elderly population in California? How can we determine what districts are lacking in nursing home services, and determine which districts are lacking in high-quality nursing home services?

Who This Helps

The users we thought that would benefit would be government planning agencies, public healthcare providers, and private healthcare providers. They need information on where to target efforts.

Things Considered

Population Growth

Projections of population changes (including migrations, births, deaths) were obtained from a public dataset. It has estimates for every year for every age group for every county in California.

We assumed:

- rate for 65+ populations by county represent expected growth in demand for care

This way we could get projections for nursing home populations in the future at any T years in future.

Open Beds

We calculated this from taking the occupancy rate and number of beds in each zip code. By factoring in the expected population growth for that zip code, we estimated how many open beds would be needed in the future (or not)


To produce a score, we ultimately considered the number of beds per zip code and how that would change with respect to population growth. Because the counties differ in overall size, the scores are normalized to the total beds originally in that county. The same increase in beds for a small county would have a greater impact than the same increase in a larger county.

Areas that Lack Space

Since there was no historical information for our factors, we only used population projections to look out 5, 10, and 20 years:

- The zip code with the worst score is always the same (in Los Angeles)

- Since all areas are expecting population growth, the highest scoring areas generally stay that way

Links to Visuals

Top scores (Higher is worse)

- 5 year score http://cdb.io/1xuxARa

- 10 year score http://cdb.io/1xuyQ6T

- 20 year score http://cdb.io/1xuzhhK

- 5 year pct growth http://cdb.io/1xuzKR5

- current occup rate http://cdb.io/1xuA1mS

- bed use 5 years http://cdb.io/1xuACVM

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