Segmented Linear Regression Models for Assessing Change in Retrospective Studies in Healthcare

<div>Interrupted time series analysis for time to surgery versus <i>t</i> days. The line of best fit pre-HFS (solid black line) was <i>y</i> = − 0.0056t + 30.97. Extrapolation of the pre-HFU trend is shown as the dashed line. The line of best fit post-HFU (solid black line) was <i>y</i> = 0.0029 (<i>t</i> − 1550) + 19.59. Slope change = +0.0085. Intercept change = +1.862. Change in slope: <span class="nowrap"><svg height="11.7782pt" id="M37" style="vertical-align:-3.42938pt" version="1.1" viewbox="-0.0498162 -8.34882 57.0529 11.7782" width="57.0529pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M570 304C570 398 525 448 414 448C385 448 343 445 312 434L329 511L321 518C297 504 262 482 244 460L233 411C195 397 159 381 128 358L135 332C160 347 189 360 224 373L111 -147C97 -210 84 -218 17 -231L13 -257L254 -247L259 -218L233 -216C183 -212 177 -202 189 -142L218 -1C238 -10 266 -12 283 -12C351 3 429 48 483 105C543 168 570 242 570 304ZM482 289C482 161 380 33 304 33C278 33 248 51 233 69L303 396C326 400 352 403 369 403C428 403 482 380 482 289Z"></path></g><g transform="matrix(.013,0,0,-0.013,11.342,0)"><path d="M535 323V373H52V323H535ZM535 138V188H52V138H535Z"></path></g><g transform="matrix(.013,0,0,-0.013,22.605,0)"><path d="M241 635C89 635 35 457 35 312C35 153 89 -12 240 -12C390 -12 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d="M285 378C315 398 338 416 353 432C373 451 384 474 384 503C384 579 325 635 236 635H235C182 635 136 610 108 579L65 516L85 496C110 533 150 575 205 575C258 575 300 543 300 481C300 407 232 369 141 339L147 310C163 315 188 321 211 321C268 321 338 284 338 192C338 94 288 40 217 40C160 40 119 68 93 91C85 98 77 97 69 91C60 84 47 71 46 58C44 46 48 35 62 22C75 10 116 -12 162 -12C234 -12 424 62 424 224C424 297 373 359 285 376V378Z"></path></g><g transform="matrix(.013,0,0,-0.013,50.529,0)"><path d="M412 140C382 77 369 73 315 73H129L270 222C362 320 402 379 402 466C402 571 322 635 234 635C177 635 130 609 99 576L42 495L64 475C90 514 133 568 201 568C274 568 318 519 318 435C318 349 255 267 193 193C144 135 87 78 32 23V0H405C417 45 427 89 440 131L412 140Z"></path></g></svg>;</span> change in intercept: <span class="nowrap"><svg height="11.7782pt" id="M38" style="vertical-align:-3.42938pt" version="1.1" viewbox="-0.0498162 -8.34882 57.0529 11.7782" width="57.0529pt" xmlns="http://www.w3.org/2000/svg" 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Computational and Mathematical Methods in Medicine

fig7

Figure 7

Figure 7: Segmented Linear Regression Models for Assessing Change in Retrospective Studies in Healthcare 