Should I be using fixed effect or pooled OLS regression here?

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I have run two different regression models, one fixed effect and one pooled OLS on my data. my data looks at the number of visits to hospital regressed over age, marriage, income, insurance etc.
I have the following different outputs:
areg docvis hhkids age agesq married working linc addon, absorb(id)

Linear regression, absorbing indicators Number of obs = 6209
F( 7, 5315) = 9.41
Prob > F = 0.0000
R-squared = 0.4187
Adj R-squared = 0.3210
Root MSE = 4.5743

------------------------------------------------------------------------------
docvis | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
hhkids | .6842771 .2283976 3.00 0.003 .2365241 1.13203
age | -.2296306 .1000438 -2.30 0.022 -.4257574 -.0335037
agesq | .0038488 .0010781 3.57 0.000 .0017352 .0059624
married | -.0821362 .3648964 -0.23 0.822 -.797483 .6332105
working | -.5626292 .2482206 -2.27 0.023 -1.049243 -.076015
linc | .0877239 .2388579 0.37 0.713 -.3805356 .5559834
addon | .2961511 .6367558 0.47 0.642 -.9521517 1.544454
_cons | 5.699316 2.413246 2.36 0.018 .9683623 10.43027
-------------+----------------------------------------------------------------
id | F(886, 5315) = 3.949 0.000 (887 categories)

and
. reg docvis hhkids age agesq married working linc addon
Source | SS df MS Number of obs = 6209
-------------+------------------------------ F( 7, 6201) = 33.13
Model | 6896.48158 7 985.211654 Prob > F = 0.0000
Residual | 184416.031 6201 29.7397244 R-squared = 0.0360
-------------+------------------------------ Adj R-squared = 0.0350
Total | 191312.513 6208 30.8170929 Root MSE = 5.4534

------------------------------------------------------------------------------
docvis | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
hhkids | -.2391697 .1658536 -1.44 0.149 -.5643002 .0859609
age | -.1507832 .0726872 -2.07 0.038 -.2932753 -.008291
agesq | .0025111 .0008288 3.03 0.002 .0008863 .0041359
married | .0999155 .2074759 0.48 0.630 -.3068092 .5066403
working | -1.334794 .1698332 -7.86 0.000 -1.667726 -1.001862
linc | -.2042591 .1686214 -1.21 0.226 -.5348155 .1262974
addon | -.36392 .590928 -0.62 0.538 -1.522344 .7945038
_cons | 5.455084 1.587606 3.44 0.001 2.342826 8.567342
------------------------------------------------------------------------------

My question is this:
which is better, pooled OLS or fixed effect? How do i know which one is better, is there a test I can do on stata to see which one is more suited to my data? Additionally could someone explain why the results are different?