Indeed there is a very well developed spectral perturbation theory which tells you that two nearby operators have close spectra.
Nevertheless, for the problem in hand, there is a much simpler alternative as follows: choose a big enough real number $M$ such that all operators under consideration have norm at most $M$. Then find a sequence $\{p_n\}_n$ of real polynomials converging uniformly to the function $x\mapsto \sqrt x$ on the interval $[0,M]$.
Then, for every positive operator $T$ with $\|T\|\le M$, one has that the spectrum of $T$ is contained in $[0,M]$ and
$$
\|p_n(T)-\sqrt {T}\|\le \sup_{x\in [0,M]}|p_n(x)-\sqrt {x}|,
$$
from where it follows that
$p_n(T)\to \sqrt{T}$, in norm.
With this it is now easy to see that $\sqrt{T}$ is continuous in the variable $T$.
Edit: Here is a proof of the inequality above in a nutshell, using only: (1) the fact that the spectrum of a self-adjoint operator is contained in $\mathbb R$, (2) the spectral mapping theorem for polynomials, that is, $\sigma(p(T))=p(\sigma(T))$, and (3) the fact that the norm of a self-adjoint operator coincides with its spectral radius
$$
\text{spr}(T) =\sup _{\lambda \in\sigma(T)}|\lambda|.
$$
Given a self-adjoint operator $T$, consider the subspace $P\subseteq C(\sigma(T))$ formed by the polynomial functions.
For each $p$ in $P$, define $\phi(p)=p(T)$, so that $\phi $ is a linear map from $P$ to $B(H)$. It is also norm preserving because
$$
\|\phi(p)\|=\|p(T)\|=\text{spr}(p(T))= $$$$=
\sup _{\lambda \in\sigma(p(T))}|\lambda|=
\sup _{\lambda \in\sigma(T)}|p(\lambda)| =\|p\|.
$$
Since $P$ is dense in $C(\sigma(T))$, we may extend $\phi$ to $C(\sigma(T))$ by continuity. The extended map is then clearly an isometric homomorphism of Banach $^*$-algebras
$$
\phi:C(\sigma(T))\to B(H).
$$
It is often also called the "continuous functional calculus".
A word about notation: whenever $f$ is in $C(\sigma(T))$, most people write $f(T)$ for $\phi(f)$.
Observe that, since $\sqrt{\cdot}$ is a function whose square is the identity, then $\sqrt{T}$ is indeed the square root of $T$.
We are thus ready for the punch line
$$
\|p_n(T)-\sqrt {T}\|=
\|\phi(p_n-\sqrt{\cdot})\| = $$$$=
\|p_n-\sqrt{\cdot}\| = \sup_{x\in \sigma(T)}|p_n(x)-\sqrt {x}|\le $$$$\le
\sup_{x\in [0,M]}|p_n(x)-\sqrt {x}|.
$$