Upload extract stage outputs 2025-11-27T17:25:33.938827Z (batch 2/2)

stage1/sample_00046/raw_response.md

@@ -1,7 +1 @@
-2004).  
-
-<|ref|>sub_title<|/ref|><|det|>[[427, 93, 564, 109]]<|/det|>
-## REFERENCES  
-
-<|ref|>text<|/ref|><|det|>[[207, 114, 789, 732]]<|/det|>
-Abdel-Mawgoud A.S.A (2004). Soosbailing to conserve rootzone stratum of heavy clay soil. Minufiya J. Agric. Res. Vol. 29 No. 6: 1456- 1478. Abdel-Mawgoud A.S.A., M. B. El Shewikh, A. N. Abdel- Aal and M.I.I. AbdelKhalik (2003). Open drainage and moiling for desalinization of Salty Clay Soils of Northeastern Egypt. Presented at the 9th International Drainage Workshop, September 10 - 13, 2003, Utrecht, The Netherlands. Abdel-Mawgoud A.S.A, A.A.S. Gendy and S.A. Ramadan (2006). Improving root zone environment and production of a salty clay soil using subsoliling and gypsum application. Assiut J. of Agri. Sci., 37, 2: 147- 164. Amer, M. H. (1999). Effect of tillage operations on some soil physical properties and water relations of corn. Egypt J. Appl. Sci., 14 (6):354- 365. Campbell, D.J. (1994). Determination and use of bulk density in relation to soil compaction. In Soane and Ouwerk (Eds). Soil compaction in crop production. Elsevier, London and Amsterdam. David Hopkins, Colac (2002). Managing wet soils: mole drainage. WWW.dse. Vic. Gov. De Leenher, L. and M. De Boodt (1965). Soil physics. Intre. Training Center for Post Graduate Soil Scientists, Gent., pp. 126- 135. Garcia, G. (1978). Soil water Engineering Laboratory Manual. Colorado State Univ. Dept. of Agric. and Chemical Engineering. Fortcollins, Colorado. Jodi Dej ong, H. (2004). Can subsoliling increase crop yields in Minnesota? Agric. World Wide Correspondent. Meredith Corporation. Lickacz, J. (1993). Management of solonetzic soils. Agdex 518- 8. Revised, Edmonton, Alberta, Canada. Moukhhtar M. M., Madiha H. El- Hakim, A.S.A. Abdel- Mawgoud, A. I. N. Abdel- Aal, M. B. El Shewikh and M.I.I. Abdel- Khalik (2003b). Drainage and role of mole drains for heavy clay soils under saline watertable, Egypt. Paper No 078. Presented at the 9th International Drainage Workshop, September 10- 13, 2003, Utrecht, The Netherlands. Moukhtar M. M., Aly I.N.Abdel- Aal, M.A.B.EI- Sheikh and M.I.I. Abdel- Khalik (2002a). The Role of Mole Drainage in Degradation Soils Under Saline Ground water Table, Egypt The Second International Conference on Sustainable Agriculture for Food, Energy and Industry September 8- 13, Beijing, China. Moukhtar, M. M., E. M. El- Hadidy, M.Y.S. El- Arquan and M.A.B. El- Shewikh (2002b). Soil Amelioration Technique of Cover Drainage Combined Subsoiling for Saline- Sodic Clay in North Egypt. XVth World Congress of the International Commission of Agricultural Engineering (CIGR) on J uly 28- 31 - 2002, Chicago, USA. Moukhtar, M.M., M.Y.S. El- Arquan, E.M. El- Hadidy and M.A.B. El- Shewikh (2003a). Amelioration of salt affected soils in north Dakhlia Governorate through application of tile drainage and subsoliling. J. Agric. Sci. Mansoura Univ., Special Issue, Sci. Symp. On Problems of soils and waters in Dakhlia and Damietta Governorate. March 18.
+1. 2004). 2. 2005). 3. 2005). 4. 2005). 5. 2005). 6. 2005). 7. 2005). 8. 2005). 9. 2005). 10. 2005). 11. 2005). 12. 2005). 13. 2005). 14. 2005). 15. 2005). 16. 2005). 17. 2005). 18. 2005). 19. 2005). 20. 2005). 21. 2005). 22. 2005). 23. 2005). 24. 2005). 25. 2005). 26. 2005). 27. 2005). 28. 2005). 29. 2005). 30. 2005). 31. 2005). 32. 2005). 33. 2005). 34. 2005). 35. 2005). 36. 2005). 37. 2005). 38. 2005). 39. 2005). 40. 2005). 41. 2005). 42. 2005). 43. 2005). 44. 2005). 45. 2005). 46. 2005). 47. 2005). 48. 2005). 49. 2005). 50. 2005). 51. 2005). 52. 2005). 53. 2005). 54. 2005). 55. 2005). 56. 2005). 57. 2005). 58. 2005). 59. 2005). 60. 2005). 61. 2005). 62. 2005). 63. 2005). 64. 2005). 65. 2005). 66. 2005). 67. 2005). 68. 2005). 69. 2005). 70. 2005). 71. 2005). 72. 2005). 73. 2005). 74. 2005). 75. 2005). 76. 2005). 77. 2005). 78. 2005). 79. 2005). 80. 2005). 81. 2005). 82. 2005). 83. 2005). 84. 2005). 85. 2005). 86. 2005). 87. 2005). 88. 2005). 89. 2005). 90. 2005). 91. 2005). 92. 2005). 93. 2005). 94. 2005). 95. 2005). 96. 2005). 97. 2005). 98. 2005). 99. 2005). 100. 2005). 101. 2005). 102. 2005). 103. 2005). 104. 2005). 105. 2005). 106. 2005). 107. 2005). 108. 2005). 109. 2005). 110. 2005). 111. 2005). 112. 2005). 113. 2005). 114. 2005). 115. 2005). 116. 2005). 117. 2005). 118. 2005). 119. 2005). 120. 2005). 121. 2005). 122. 2005). 123. 2005). 124. 2005). 125. 2005). 126. 2005). 127. 2005). 128. 2005). 129. 2005). 130. 2005). 131. 2005). 132. 2005). 133. 2005). 134. 2005). 135. 2005). 136. 2005). 137. 2005). 138. 2005). 139. 2005). 140. 2005). 141. 2005). 142. 2005). 143. 2005). 144. 2005). 145. 2005). 146. 2005). 147. 2005). 148. 2005). 149. 2005). 150. 2005). 151. 2005). 152. 2005). 153. 2005). 154. 2005). 155. 2005). 156. 2005). 157. 2005). 158. 2005). 159. 2005). 160. 2005). 161. 2005). 162. 2005). 163. 2005). 164. 2005). 165. 2005). 166. 2005). 167. 2005). 168. 2005). 169. 2005). 170. 2005). 171. 2005). 172. 2005). 173. 2005). 174. 2005). 175. 2005). 176. 2005). 177. 2005). 178. 2005). 179. 2005). 180. 2005). 181. 2005). 182. 2005). 183. 2005). 184. 2005). 185. 2005). 186. 2005). 187. 2005). 188. 2005). 189. 2005). 190. 2005). 191. 2005). 192. 2005). 193. 2005). 194. 2005). 195. 2005). 196. 2005). 197. 2005). 198. 2005). 199. 2005). 200. 2005). 201. 2005). 202. 2005). 203. 2005). 204. 2005). 205. 2005). 206. 2005). 207. 2005). 208. 2005). 209. 2005). 210. 2005). 211. 2005). 212. 2005). 213. 2005). 214. 2005). 215. 2005). 216. 2005). 217. 2005). 218. 2005). 219. 2005). 220. 2005). 221. 2005). 222. 2005). 223. 2005). 224. 2005). 225. 2005). 226. 2005). 227. 2005). 228. 2005). 229. 2005). 230. 2005). 231. 2005). 232. 2005). 233. 2005). 234. 2005). 235. 2005). 236. 2005). 237. 2005). 238. 2005). 239. 2005). 240. 2005). 241. 2005). 242. 2005). 243. 2005). 244. 2005). 245. 2005). 246. 2005). 247. 2005). 248. 2005). 249. 2005). 250. 2005). 251. 2005). 252. 2005). 253. 2005). 254. 2005). 255. 2005). 256. 2005). 257. 2005). 258. 2005). 259. 2005). 260. 2005). 261. 2005). 262. 2005). 263. 2005). 264. 2005). 265. 2005). 266. 2005). 267. 2005). 268. 2005). 269. 2005). 270. 2005). 271. 2005). 272. 2005). 273. 2005). 274. 2005). 275. 2005). 276. 2005). 277. 2005). 278. 2005). 279. 2005). 280. 2005). 281. 2005). 282. 2005). 283. 2005). 284. 2005). 285. 2005). 286. 2005). 287. 2005). 288. 2005). 289. 2005). 290. 2005). 291. 2005). 292. 2005). 293. 2005). 294. 2005). 295. 2005). 296. 2005). 297. 2005). 298. 2005). 299. 2005). 300. 2005). 301. 2005). 302. 2005). 303. 2005). 304. 2005). 305. 2005). 306. 2005). 307. 2005). 308. 2005). 309. 2005). 310. 2005). 311. 2005). 312. 2005). 313. 2005). 314. 2005). 315. 2005). 316. 2005). 317. 2005). 318. 2005). 319. 2005). 320. 2005). 321. 2005). 322. 2005). 323. 2005). 324. 2005). 325. 2005). 326. 2005). 327. 2005). 328. 2005). 329. 2005). 330. 2005). 331. 2005). 332. 2005). 333. 2005). 334. 2005). 335. 2005). 336. 2005). 337. 2005). 338. 2005). 339. 2005). 340. 2005). 341. 2005). 342. 2005). 343. 2005). 344. 2005). 345. 2005). 346. 2005). 347. 2005). 348. 2005). 349. 2005). 350. 2005). 351. 2005). 352. 2005). 353. 2005). 354. 2005). 355. 2005). 356. 2005). 357. 2005). 358. 2005). 359. 2005). 360. 2005). 361. 2005). 362. 2005). 363. 2005). 364. 2005). 365. 2005). 366. 2005). 367. 2005). 368. 2005). 369. 2005). 370. 2005). 371. 2005). 372. 2005). 373. 2005). 374. 2005). 375. 2005). 376. 2005). 377. 2005). 378. 2005). 379. 2005). 380. 2005). 381. 2005). 382. 2005). 383. 2005). 384. 2005). 385. 2005). 386. 2005). 387. 2005). 388. 2005). 389. 2005). 390. 2005). 391. 2005). 392. 2005). 393. 2005). 394. 2005). 395. 2005). 396. 2005). 397. 2005). 398. 2005). 399. 2005). 400. 2005). 401. 2005). 402. 2005). 403. 2005). 404. 2005). 405. 2005). 406. 2005). 407. 2005). 408. 2005). 409. 2005). 410. 2005). 411. 2005). 412. 2005). 413. 2005). 414. 2005). 415. 2005). 416. 2005). 417. 2005). 418. 2005). 419. 2005). 420. 2005). 421. 2005). 422. 2005). 423. 2005). 424. 2005). 425. 2005). 426. 2005). 427. 2005). 428. 2005). 429. 2005). 430. 2005). 431. 2005). 432. 2005). 433. 2005). 434. 2005). 435. 2005). 436. 2005). 437. 2005). 438. 2005). 439. 2005). 440. 2005). 441. 2005). 442. 2005). 443. 2005). 444. 2005). 445. 2005). 446. 2005). 447. 2005). 448. 2005). 449. 2005). 450. 2005). 451. 2005). 452. 2005). 453. 2005). 454. 2005). 455. 2005). 456. 2005). 457. 2005). 458. 2005). 459. 2005). 460. 2005). 461. 2005). 462. 2005). 463. 2005). 464. 2005). 465. 2005). 466. 2005). 467. 2005). 468. 2005). 469. 2005). 470. 2005). 471. 2005). 472. 2005). 473. 2005). 474. 2005). 475. 2005). 476. 2005). 477. 2005). 478. 2005). 479. 2005). 480. 2005). 481. 2005). 482. 2005). 483. 2005). 484. 2005). 485. 2005). 486. 2005). 487. 2005). 488. 2005). 489. 2005). 490. 2005). 491. 2005). 492. 2005). 493. 2005). 494. 2005). 495. 2005). 496. 2005). 497. 2005). 498. 2005). 499. 2005). 500. 2005). 501. 2005). 502. 2005). 503. 2005). 504. 2005). 505. 2005). 506. 2005). 507. 2005). 508. 2005). 509. 2005). 510. 2005). 511. 2005). 512. 2005). 513. 2005). 514. 2005). 515. 2005). 516. 2005). 517. 2005). 518. 2005). 519. 2005). 520. 2005). 521. 2005). 522. 2005). 523. 2005). 524. 2005). 525. 2005). 526. 2005). 527. 2005). 528. 2005). 529. 2005). 530. 2005). 531. 2005). 532. 2005). 533. 2005). 534. 2005). 535. 2005). 536. 2005). 537. 2005). 538. 2005). 539. 2005). 540. 2005). 541. 2005). 542. 2005). 543. 2005). 544. 2005). 545. 2005). 546. 2005). 547. 2005). 548. 2005). 549. 2005). 550. 2005). 551. 2005). 552. 2005). 553. 2005). 554. 2005). 555. 2005). 556. 2005). 557. 2005). 558. 2005). 559. 2005). 560. 2005). 561. 2005). 562. 2005). 563. 2005). 564. 2005). 565. 2005). 566. 2005). 567. 2005). 568. 2005). 569. 2005). 570. 2005). 571. 2005). 572. 2005). 573. 2005). 574. 2005). 575. 2005). 576. 2005). 577. 2005). 578. 2005). 579. 2005). 580. 2005). 581. 2005). 582. 2005). 583. 2005). 584. 2005). 585. 2005). 586

stage1/sample_00047/document.md

@@ -4,4 +4,4 @@
 
 Larry Ream, chair Term expires December 1, 2015Gloria Nagler Term expires December 1, 2015Diana Carey Term expires December 1, 2016Kathleen Shoemaker Term expires December 1, 2016J erry N. Stehlik Term expires December 1, 2017  
 
-###End of Order###
+###End of Order##

stage1/sample_00047/raw_response.md

@@ -1,10 +1,10 @@
 1. That each member of the Executive Committee shall be selected to a term of at least 3 years, renewable for an additional 2 years, at the discretion of the Chief Bankruptcy J udge.  
 
-<|ref|>text<|/ref|><|det|>[[115, 245, 878, 335]]<|/det|>
+<|ref|>text<|/ref|><|det|>[[115, 246, 879, 334]]<|/det|>
 2. The following attorneys are members of the Executive Committee for the Program with terms of service as set forth below. J erry Stehlik is appointed to fill the Committee position vacated by J udge Alston:  
 
-<|ref|>text<|/ref|><|det|>[[171, 345, 696, 428]]<|/det|>
+<|ref|>text<|/ref|><|det|>[[172, 346, 694, 430]]<|/det|>
 Larry Ream, chair Term expires December 1, 2015Gloria Nagler Term expires December 1, 2015Diana Carey Term expires December 1, 2016Kathleen Shoemaker Term expires December 1, 2016J erry N. Stehlik Term expires December 1, 2017  
 
-<|ref|>text<|/ref|><|det|>[[403, 465, 586, 484]]<|/det|>
-###End of Order###
+<|ref|>text<|/ref|><|det|>[[404, 465, 586, 484]]<|/det|>
+###End of Order##

stage1/sample_00048/document.md

@@ -1,3 +1,5 @@
-1. The AGGLOM vector includes several variables to assess whether it is access or proximity to agglomeration economies that are driving the results. First, for nonmetropolitan counties, we include the county's own population and the population of the nearest metropolitan area. For metropolitan counties, we include the overall metropolitan area population. Then to more accurately account for spillovers over distance, the AGGLOM also includes several spatial distance measures to reflect proximity to metropolitan areas differentiated by their status in the hierarchy. Partridge et al. (2008a, 2008b, 2009) found these distance measures to be highly associated with job and population growth as well as wages and housing values dating back to the mid-20<sup>th</sup> Century. For a county that is part of a metropolitan area, the first distance is from the population-weighted center of the county to the population-weighted center of the metropolitan area. Inside a metropolitan area, the influence of longer distances would largely reflect any offsetting effects of agglomeration or congestion effects. For a nonmetropolitan county, the variable is the distance from the county center to the center of the nearest metropolitan area.7  
+7. If it is a one-county metropolitan area, this distance term is zero. Population-weighted county centroids are from the U.S. Census Bureau. The metropolitan area population category is based on initial 1990 population.  
 
-Beyond the nearest metropolitan area, we also include the incremental distances to larger higher- tiered metropolitan areas to reflect added spillovers from higher- ordered cities. They reflect the incremental or marginal costs to reach each higher- tiered (larger) metropolitan areas. First, are incremental (or additional) distances to reach metropolitan areas of at least 250,000, and then at least 500,000, and finally over 1.5 million population.<sup>8</sup> The largest category generally reflects national and top- tier regional cities. There may be measurement error bias when using straight- line distance rather than travel time, but this classic measurement error would bias the distance
+The AGGLOM vector includes several variables to assess whether it is access or proximity to agglomeration economies that are driving the results. First, for nonmetropolitan counties, we include the county's own population and the population of the nearest metropolitan area. For metropolitan counties, we include the overall metropolitan area population. Then to more accurately account for spillovers over distance, the AGGLOM also includes several spatial distance measures to reflect proximity to metropolitan areas differentiated by their status in the hierarchy. Partridge et al. (2008a, 2008b, 2009) found these distance measures to be highly associated with job and population growth as well as wages and housing values dating back to the mid- \(20^{\mathrm{th}}\) Century. For a county that is part of a metropolitan area, the first distance is from the population-weighted center of the county to the population-weighted center of the metropolitan area. Inside a metropolitan area, the influence of longer distances would largely reflect any offsetting effects of agglomeration or congestion effects. For a nonmetropolitan county, the variable is the distance from the county center to the center of the nearest metropolitan area.  
+
+Beyond the nearest metropolitan area, we also include the incremental distances to larger higher- tiered metropolitan areas to reflect added spillovers from higher- ordered cities. They reflect the incremental or marginal costs to reach each higher- tiered (larger) metropolitan areas. First, are incremental (or additional) distances to reach metropolitan areas of at least 250,000, and then at least 500,000, and finally over 1.5 million population. The largest category generally reflects national and top- tier regional cities. There may be measurement error bias when using straight- line distance rather than travel time, but this classic measurement error would bias the distance

stage1/sample_00048/raw_response.md

@@ -1,4 +1,7 @@
-1. The AGGLOM vector includes several variables to assess whether it is access or proximity to agglomeration economies that are driving the results. First, for nonmetropolitan counties, we include the county's own population and the population of the nearest metropolitan area. For metropolitan counties, we include the overall metropolitan area population. Then to more accurately account for spillovers over distance, the AGGLOM also includes several spatial distance measures to reflect proximity to metropolitan areas differentiated by their status in the hierarchy. Partridge et al. (2008a, 2008b, 2009) found these distance measures to be highly associated with job and population growth as well as wages and housing values dating back to the mid-20<sup>th</sup> Century. For a county that is part of a metropolitan area, the first distance is from the population-weighted center of the county to the population-weighted center of the metropolitan area. Inside a metropolitan area, the influence of longer distances would largely reflect any offsetting effects of agglomeration or congestion effects. For a nonmetropolitan county, the variable is the distance from the county center to the center of the nearest metropolitan area.7  
+7. If it is a one-county metropolitan area, this distance term is zero. Population-weighted county centroids are from the U.S. Census Bureau. The metropolitan area population category is based on initial 1990 population.  
 
-<|ref|>text<|/ref|><|det|>[[113, 490, 881, 680]]<|/det|>
-Beyond the nearest metropolitan area, we also include the incremental distances to larger higher- tiered metropolitan areas to reflect added spillovers from higher- ordered cities. They reflect the incremental or marginal costs to reach each higher- tiered (larger) metropolitan areas. First, are incremental (or additional) distances to reach metropolitan areas of at least 250,000, and then at least 500,000, and finally over 1.5 million population.<sup>8</sup> The largest category generally reflects national and top- tier regional cities. There may be measurement error bias when using straight- line distance rather than travel time, but this classic measurement error would bias the distance
+<|ref|>text<|/ref|><|det|>[[113, 135, 883, 483]]<|/det|>
+The AGGLOM vector includes several variables to assess whether it is access or proximity to agglomeration economies that are driving the results. First, for nonmetropolitan counties, we include the county's own population and the population of the nearest metropolitan area. For metropolitan counties, we include the overall metropolitan area population. Then to more accurately account for spillovers over distance, the AGGLOM also includes several spatial distance measures to reflect proximity to metropolitan areas differentiated by their status in the hierarchy. Partridge et al. (2008a, 2008b, 2009) found these distance measures to be highly associated with job and population growth as well as wages and housing values dating back to the mid- \(20^{\mathrm{th}}\) Century. For a county that is part of a metropolitan area, the first distance is from the population-weighted center of the county to the population-weighted center of the metropolitan area. Inside a metropolitan area, the influence of longer distances would largely reflect any offsetting effects of agglomeration or congestion effects. For a nonmetropolitan county, the variable is the distance from the county center to the center of the nearest metropolitan area.  
+
+<|ref|>text<|/ref|><|det|>[[114, 492, 883, 681]]<|/det|>
+Beyond the nearest metropolitan area, we also include the incremental distances to larger higher- tiered metropolitan areas to reflect added spillovers from higher- ordered cities. They reflect the incremental or marginal costs to reach each higher- tiered (larger) metropolitan areas. First, are incremental (or additional) distances to reach metropolitan areas of at least 250,000, and then at least 500,000, and finally over 1.5 million population. The largest category generally reflects national and top- tier regional cities. There may be measurement error bias when using straight- line distance rather than travel time, but this classic measurement error would bias the distance

stage1/sample_00049/document.md

@@ -1,27 +1,25 @@
-0.000
+0
 
-# Critical Values Reporting QT10
+## Critical Values Reporting QT10 
 
-Laboratories commonly refer to critical values as results requiring immediate notification to the physician or caregiver for necessary patient evaluation or treatment. Regulations from agencies and accreditors such as the CMS, The Joint Commission, and the CAP (GEN.20316, COM.30000) mandate that laboratories develop and implement an alert system for critical values. Use this monitor to document compliance with your laboratory's alert plan.
+Laboratories commonly refer to critical values as results requiring immediate notification to the physician or caregiver for necessary patient evaluation or treatment. Regulations from agencies and accreditors such as the CMS, The Joint Commission, and the CAP (GEN.20316, COM.30000) mandate that laboratories develop and implement an alert system for critical values. Use this monitor to document compliance with your laboratory's alert plan. 
 
-# Objective
+## Objective 
 
-Evaluate the documentation of successful critical values reporting in the general laboratory for inpatients (including discharged inpatients) and outpatients.
+Evaluate the documentation of successful critical values reporting in the general laboratory for inpatients (including discharged inpatients) and outpatients. 
 
-# Data Collection
+## Data Collection 
 
-On a monthly basis, participants will evaluate 120 inpatient, 20 discharged inpatient, and 120 outpatient critical values.Data collection will include general chemistry, hematology, and coagulation analytes on the critical values list. Retrospectively,participants will record the total number of critical values monitored and the number with documentation of successful notification. In addition, participants will provide the number of critical values that were not communicated within three hours,the number of failed notifications due to laboratory oversight, and the number of successful notifications to licensed caregivers.This monitor will exclude critical values for cardiac markers, drugs of abuse, therapeutic drug levels, urinalysis, blood gases,point-of-care tests, and tests performed at reference laboratories.
+On a monthly basis, participants will evaluate 120 inpatient, 20 discharged inpatient, and 120 outpatient critical values. Data collection will include general chemistry, hematology, and coagulation analytes on the critical values list. Retrospectively, participants will record the total number of critical values monitored and the number with documentation of successful notification. In addition, participants will provide the number of critical values that were not communicated within three hours, the number of failed notifications due to laboratory oversight, and the number of successful notifications to licensed caregivers. This monitor will exclude critical values for cardiac markers, drugs of abuse, therapeutic drug levels, urinalysis, blood gases, point-of-care tests, and tests performed at reference laboratories. 
 
-# Performance Indicators
+## Performance Indicators 
 
-·Total critical values reporting rate (%)
+• Total critical values reporting rate (%) 
 
-·Inpatient critical values reporting rate (%)
+• Inpatient critical values reporting rate (%) 
 
-·Discharged inpatient critical values reporting rate (%)
+• Discharged inpatient critical values reporting rate (%) 
 
-·Outpatient critical values reporting rate (%)
+• Outpatient critical values reporting rate (%) 
 
-·Failed notification (<3 hours) rate (%)
-
-Look for your input forms approximately three weeks prior to the quarter.
+• Failed notification (<3 hours) rate (%)

stage1/sample_00049/raw_response.md

@@ -1,40 +1,37 @@
-0.000
+0
 
-<|ref|>title<|/ref|><|det|>[[338, 93, 689, 114]]<|/det|>
-# Critical Values Reporting QT10
+<|ref|>sub_title<|/ref|><|det|>[[337, 93, 689, 115]]<|/det|>
+## Critical Values Reporting QT10 
 
-<|ref|>text<|/ref|><|det|>[[94, 125, 890, 185]]<|/det|>
-Laboratories commonly refer to critical values as results requiring immediate notification to the physician or caregiver for necessary patient evaluation or treatment. Regulations from agencies and accreditors such as the CMS, The Joint Commission, and the CAP (GEN.20316, COM.30000) mandate that laboratories develop and implement an alert system for critical values. Use this monitor to document compliance with your laboratory's alert plan.
+<|ref|>text<|/ref|><|det|>[[95, 125, 890, 185]]<|/det|>
+Laboratories commonly refer to critical values as results requiring immediate notification to the physician or caregiver for necessary patient evaluation or treatment. Regulations from agencies and accreditors such as the CMS, The Joint Commission, and the CAP (GEN.20316, COM.30000) mandate that laboratories develop and implement an alert system for critical values. Use this monitor to document compliance with your laboratory's alert plan. 
 
-<|ref|>title<|/ref|><|det|>[[95, 206, 175, 218]]<|/det|>
-# Objective
+<|ref|>sub_title<|/ref|><|det|>[[95, 205, 174, 218]]<|/det|>
+## Objective 
 
-<|ref|>text<|/ref|><|det|>[[95, 222, 921, 251]]<|/det|>
-Evaluate the documentation of successful critical values reporting in the general laboratory for inpatients (including discharged inpatients) and outpatients.
+<|ref|>text<|/ref|><|det|>[[95, 222, 922, 252]]<|/det|>
+Evaluate the documentation of successful critical values reporting in the general laboratory for inpatients (including discharged inpatients) and outpatients. 
 
-<|ref|>title<|/ref|><|det|>[[95, 264, 218, 276]]<|/det|>
-# Data Collection
+<|ref|>sub_title<|/ref|><|det|>[[95, 264, 217, 277]]<|/det|>
+## Data Collection 
 
-<|ref|>text<|/ref|><|det|>[[94, 282, 920, 385]]<|/det|>
-On a monthly basis, participants will evaluate 120 inpatient, 20 discharged inpatient, and 120 outpatient critical values.Data collection will include general chemistry, hematology, and coagulation analytes on the critical values list. Retrospectively,participants will record the total number of critical values monitored and the number with documentation of successful notification. In addition, participants will provide the number of critical values that were not communicated within three hours,the number of failed notifications due to laboratory oversight, and the number of successful notifications to licensed caregivers.This monitor will exclude critical values for cardiac markers, drugs of abuse, therapeutic drug levels, urinalysis, blood gases,point-of-care tests, and tests performed at reference laboratories.
+<|ref|>text<|/ref|><|det|>[[95, 281, 921, 385]]<|/det|>
+On a monthly basis, participants will evaluate 120 inpatient, 20 discharged inpatient, and 120 outpatient critical values. Data collection will include general chemistry, hematology, and coagulation analytes on the critical values list. Retrospectively, participants will record the total number of critical values monitored and the number with documentation of successful notification. In addition, participants will provide the number of critical values that were not communicated within three hours, the number of failed notifications due to laboratory oversight, and the number of successful notifications to licensed caregivers. This monitor will exclude critical values for cardiac markers, drugs of abuse, therapeutic drug levels, urinalysis, blood gases, point-of-care tests, and tests performed at reference laboratories. 
 
-<|ref|>title<|/ref|><|det|>[[95, 397, 276, 409]]<|/det|>
-# Performance Indicators
+<|ref|>sub_title<|/ref|><|det|>[[95, 397, 274, 410]]<|/det|>
+## Performance Indicators 
 
-<|ref|>text<|/ref|><|det|>[[98, 415, 356, 427]]<|/det|>
-·Total critical values reporting rate (%)
+<|ref|>text<|/ref|><|det|>[[97, 414, 364, 428]]<|/det|>
+• Total critical values reporting rate (%) 
 
-<|ref|>text<|/ref|><|det|>[[98, 433, 387, 445]]<|/det|>
-·Inpatient critical values reporting rate (%)
+<|ref|>text<|/ref|><|det|>[[97, 432, 384, 446]]<|/det|>
+• Inpatient critical values reporting rate (%) 
 
-<|ref|>text<|/ref|><|det|>[[98, 450, 464, 463]]<|/det|>
-·Discharged inpatient critical values reporting rate (%)
+<|ref|>text<|/ref|><|det|>[[97, 450, 464, 465]]<|/det|>
+• Discharged inpatient critical values reporting rate (%) 
 
-<|ref|>text<|/ref|><|det|>[[98, 468, 400, 481]]<|/det|>
-·Outpatient critical values reporting rate (%)
+<|ref|>text<|/ref|><|det|>[[97, 468, 397, 483]]<|/det|>
+• Outpatient critical values reporting rate (%) 
 
-<|ref|>text<|/ref|><|det|>[[98, 486, 360, 499]]<|/det|>
-·Failed notification (<3 hours) rate (%)
-
-<|ref|>text<|/ref|><|det|>[[241, 867, 722, 879]]<|/det|>
-Look for your input forms approximately three weeks prior to the quarter.
+<|ref|>text<|/ref|><|det|>[[97, 486, 360, 500]]<|/det|>
+• Failed notification (<3 hours) rate (%)