| blob | 9286668d10e0eb0acdf15040dbc2614737f3d3ac |
1 /**
2 * @package OpenEMR CCDAServer
3 * @link http://www.open-emr.org
4 *
5 * @author Jerry Padgett <sjpadgett@gmail.com>
6 * @copyright Copyright (c) 2016-2021 Jerry Padgett <sjpadgett@gmail.com>
7 * @license https://github.com/openemr/openemr/blob/master/LICENSE GNU General Public License 3
8 */
10 "use strict";
11 const net = require('net');
12 const server = net.createServer();
13 const to_json = require('xmljson').to_json;
14 const bbg = require(__dirname + '/oe-blue-button-generate');
15 const fs = require('fs');
17 var conn = ''; // make our connection scope global to script
18 var oidFacility = "";
19 var all = "";
20 var npiProvider = "";
21 var npiFacility = "";
23 function trim(s) {
24 if (typeof s === 'string') return s.trim();
25 return s;
26 }
28 function fDate(str, lim8=false) {
29 str = String(str);
30 if (lim8) {
31 let rtn = str.substring(0, 8);
32 return rtn;
33 }
34 if (Number(str) === 0) {
35 return (new Date()).toISOString().slice(0, 10).replace(/-/g, "");
36 }
37 if (str.length === 1 || str === "0000-00-00") return (new Date()).toISOString().slice(0, 10).replace(/-/g, "");
38 if (str.length === 8 || (str.length === 14 && (1 * str.substring(12, 14)) === 0)) {
39 return [str.slice(0, 4), str.slice(4, 6), str.slice(6, 8)].join('-')
40 } else if (str.length === 10 && (1 * str.substring(0, 2)) <= 12) {
41 // case mm/dd/yyyy or mm-dd-yyyy
42 return [str.slice(6, 10), str.slice(0, 2), str.slice(3, 5)].join('-')
43 } else if (str.length === 14 && (1 * str.substring(12, 14)) > 0) {
44 // maybe a real time so parse
45 }
47 return str;
48 }
50 function getPrecision(str) {
51 str = String(str);
52 let pflg = "day";
54 if (Number(str) === 0) {
55 return "day";
56 }
57 if (str.length > 8) {
58 pflg = "minute";
59 }
60 if (str.length > 12) {
61 pflg = "second";
62 }
64 return pflg;
65 }
67 function templateDate(date, precision) {
68 return {'date': fDate(date), 'precision': precision}
69 }
71 function cleanCode(code) {
72 if (code.length < 2) {
73 code = "";
74 }
75 return code.replace(/[.#]/, "");
76 }
78 function isOne(who) {
79 try {
80 if (who !== null && typeof who === 'object') {
81 return (who.hasOwnProperty('extension') || who.hasOwnProperty('id') || who.hasOwnProperty('date')) ? 1 : Object.keys(who).length;
82 }
83 } catch (e) {
84 return false;
85 }
86 return 0;
87 }
89 function headReplace(content) {
90 var r = '<?xml version="1.0" encoding="UTF-8"?>\n<?xml-stylesheet type="text/xsl" href="CDA.xsl"?>\n';
91 r += content.substr(content.search(/<ClinicalDocument/i));
92 return r;
93 }
95 function populateDemographic(pd, g) {
96 let guardian = [{
97 "relation": g.relation,
98 "addresses": [{
99 "street_lines": [g.address],
100 "city": g.city,
101 "state": g.state,
102 "zip": g.postalCode,
103 "country": g.country || "US",
104 "use": "primary home"
105 }],
106 "names": [{
107 "last": g.display_name, //@todo parse first/last
108 "first": g.display_name
109 }],
110 "phone": [{
111 "number": g.telecom,
112 "type": "primary home"
113 }]
114 }];
116 return {
117 "name": {
118 "middle": [pd.mname],
119 "last": pd.lname,
120 "first": pd.fname
121 },
122 "birth_name": {
123 "middle": pd.birth_mname || pd.mname,
124 "last": pd.birth_lname || pd.lname,
125 "first": pd.birth_fname || pd.fname
126 },
127 "dob": {
128 "point": {
129 "date": fDate(pd.dob),
130 "precision": "day"
131 }
132 },
133 "gender": pd.gender.toUpperCase(),
134 "identifiers": [{
135 "identifier": oidFacility,
136 "extension": "PT-" + pd.id
137 }],
138 "marital_status": pd.status.toUpperCase(),
139 "addresses": [{
140 "street_lines": [pd.street],
141 "city": pd.city,
142 "state": pd.state,
143 "zip": pd.postalCode,
144 "country": pd.country || "US",
145 "use": "primary home"
146 }],
147 "phone": [
148 {
149 "number": pd.phone_home,
150 "type": "primary home"
151 }, {
152 "number": pd.phone_mobile,
153 "type": "primary mobile"
154 }
155 ],
156 "ethnicity": pd.ethnicity || "",
157 "race": pd.race || "",
158 "race_additional": pd.race == "White" ? "European" : "African",
159 "languages": [{
160 "language": pd.language === 'English' ? "en-US" : pd.language === 'Spanish' ? "sp-US" : 'en-US',
161 "preferred": true,
162 "mode": "Expressed spoken",
163 "proficiency": "Good"
164 }],
165 //"religion": pd.religion.toUpperCase() || "UNK",
166 /*"birthplace":'', {
167 "city": "",
168 "state": "",
169 "zip": "",
170 "country": ""
171 },*/
172 "attributed_provider": {
173 "identity": [
174 {
175 "root": "2.16.840.1.113883.4.6",
176 "extension": npiFacility || "UNK"
177 }
178 ],
179 "phone": [{
180 "number": all.encounter_provider.facility_phone || "UNK",
181 }],
182 "name": [
183 {
184 "full": all.encounter_provider.facility_name || "UNK"
185 }
186 ],
187 "address": [
188 {
189 "street_lines": [
190 all.encounter_provider.facility_street
191 ],
192 "city": all.encounter_provider.facility_city,
193 "state": all.encounter_provider.facility_state,
194 "zip": all.encounter_provider.facility_postal_code,
195 "country": all.encounter_provider.facility_country_code || "US",
196 "use": "work place"
197 }
198 ],
199 },
200 //"guardians": g.display_name ? guardian : '' //not required
201 }
203 }
205 function populateProviders() {
206 return {
207 "providers": [
208 {
209 "code": {
210 "name": "UNK",
211 "code": "UNK",
212 "code_system_name": "SNOMED CT"
213 },
214 "date_time": {
215 "low": {
216 "date": fDate(""),
217 "precision": "day"
218 },
219 "high": {
220 "date": fDate(""),
221 "precision": "day"
222 }
223 },
224 "identity": [
225 {
226 "root": "2.16.840.1.113883.4.6",
227 "extension": all.primary_care_provider.provider[0].npi || "UNK"
228 }
229 ],
230 "type": [
231 {
232 "name": all.primary_care_provider.provider[0].physician_type || "UNK",
233 "code": cleanCode(all.primary_care_provider.provider[0].physician_type_code) || "UNK",
234 "code_system_name": "Provider Codes"
235 }
236 ],
237 "name": [
238 {
239 "last": all.primary_care_provider.provider[0].lname || "UNK",
240 "first": all.primary_care_provider.provider[0].fname || "UNK"
241 }
242 ],
243 "address": [
244 {
245 "street_lines": [
246 all.encounter_provider.facility_street
247 ],
248 "city": all.encounter_provider.facility_city,
249 "state": all.encounter_provider.facility_state,
250 "zip": all.encounter_provider.facility_postal_code,
251 "country": all.encounter_provider.facility_country_code || "US"
252 }
253 ],
254 "phone": [
255 {
256 "value": {
257 "number": all.encounter_provider.facility_phone || "",
259 }
260 }],
261 "organization": [
262 {
263 "identifiers": [
264 {
265 "identifier": "2.16.840.1.113883.19.5.9999.1393" //@todo need facility oid
266 }
267 ],
268 "name": [
269 all.encounter_provider.facility_name
270 ],
271 "address": [
272 {
273 "street_lines": [
274 all.encounter_provider.facility_street
275 ],
276 "city": all.encounter_provider.facility_city,
277 "state": all.encounter_provider.facility_state,
278 "zip": all.encounter_provider.facility_postal_code,
279 "country": all.encounter_provider.facility_country_code || "US"
280 }
281 ],
282 "phone": [
283 {
284 "number": all.encounter_provider.facility_phone,
285 "type": "primary work"
286 }
287 ]
288 }
289 ]
291 }
292 ]
293 }
294 }
296 function populateMedication(pd) {
297 pd.status = 'Completed'; //@todo invoke prescribed
298 return {
299 "date_time": {
300 "low": {
301 "date": fDate(pd.start_date),
302 "precision": "day"
303 },
304 "high": {
305 "date": fDate(pd.end_date),
306 "precision": "day"
307 }
308 },
309 "identifiers": [{
310 "identifier": pd.sha_extension,
311 "extension": pd.extension || "UNK"
312 }],
313 "status": pd.status,
314 "sig": pd.direction,
315 "product": {
316 "identifiers": [{
317 "identifier": "2a620155-9d11-439e-92b3-5d9815ff4ee8",
318 "extension": "UNK"
319 }],
320 "unencoded_name": pd.drug,
321 "product": {
322 "name": pd.drug,
323 "code": cleanCode(pd.rxnorm),
324 /*"translations": [{
325 "name": pd.drug,
326 "code": pd.rxnorm,
327 "code_system_name": "RXNORM"
328 }],*/
329 "code_system_name": "RXNORM"
330 },
331 //"manufacturer": ""
332 },
333 "supply": {
334 "date_time": {
335 "low": {
336 "date": fDate(pd.start_date),
337 "precision": "day"
338 },
339 "high": {
340 "date": fDate(pd.end_date),
341 "precision": "day"
342 }
343 },
344 "repeatNumber": "0",
345 "quantity": "0",
346 "product": {
347 "identifiers": [{
348 "identifier": "2a620155-9d11-439e-92b3-5d9815ff4ee8",
349 "extension": "UNK"
350 }],
351 "unencoded_name": pd.drug,
352 "product": {
353 "name": pd.drug,
354 "code": cleanCode(pd.rxnorm),
355 /*"translations": [{
356 "name": pd.drug,
357 "code": pd.rxnorm,
358 "code_system_name": "RXNORM"
359 }],*/
360 "code_system_name": "RXNORM"
361 },
362 //"manufacturer": ""
363 },
364 "author": {
365 "date_time": {
366 "point": {
367 "date": fDate(pd.start_date),
368 "precision": getPrecision(fDate(pd.start_date))
369 }
370 },
371 "identifiers": [{
372 "identifier": "2.16.840.1.113883.4.6",
373 "extension": pd.npi || "UNK"
374 }],
375 "name": {
376 "prefix": pd.title,
377 "last": pd.lname,
378 "first": pd.fname
379 }
380 },
381 "instructions": {
382 "code": {
383 "name": "instruction",
384 "code": "409073007",
385 "code_system_name": "SNOMED CT"
386 },
387 "free_text": pd.instructions || "No Instructions"
388 },
389 },
390 "administration": {
391 "route": {
392 "name": pd.route || "",
393 "code": cleanCode(pd.route_code) || "UNK",
394 "code_system_name": "Medication Route FDA"
395 },
396 "form": {
397 "name": pd.form,
398 "code": cleanCode(pd.form_code),
399 "code_system_name": "Medication Route FDA"
400 },
401 "dose": {
402 "value": parseFloat(pd.size),
403 "unit": pd.unit,
404 },
405 /*"rate": {
406 "value": parseFloat(pd.dosage),
407 "unit": ""
408 },*/
409 "interval": {
410 "period": {
411 "value": parseFloat(pd.dosage),
412 "unit": pd.interval
413 },
414 "frequency": true
415 }
416 },
417 "performer": {
418 "identifiers": [{
419 "identifier": "2.16.840.1.113883.4.6",
420 "extension": pd.npi || "UNK"
421 }],
422 "organization": [{
423 "identifiers": [{
424 "identifier": pd.sha_extension,
425 "extension": pd.extension || "UNK"
426 }],
427 "name": [pd.performer_name]
428 }]
429 },
430 "drug_vehicle": {
431 "name": pd.form,
432 "code": cleanCode(pd.form_code),
433 "code_system_name": "RXNORM"
434 },
435 /*"precondition": {
436 "code": {
437 "code": "ASSERTION",
438 "code_system_name": "ActCode"
439 },
440 "value": {
441 "name": "none",
442 "code": "none",
443 "code_system_name": "SNOMED CT"
444 }
445 },
446 "indication": {
447 "identifiers": [{
448 "identifier": "db734647-fc99-424c-a864-7e3cda82e703",
449 "extension": "45665"
450 }],
451 "code": {
452 "name": "Finding",
453 "code": "404684003",
454 "code_system_name": "SNOMED CT"
455 },
456 "date_time": {
457 "low": {
458 "date": fDate(pd.start_date),
459 "precision": "day"
460 }
461 },
462 "value": {
463 "name": pd.indications,
464 "code": pd.indications_code,
465 "code_system_name": "SNOMED CT"
466 }
467 },*/
468 /*"dispense": {
469 "identifiers": [{
470 "identifier": "1.2.3.4.56789.1",
471 "extension": "cb734647-fc99-424c-a864-7e3cda82e704"
472 }],
473 "performer": {
474 "identifiers": [{
475 "identifier": "2.16.840.1.113883.19.5.9999.456",
476 "extension": "2981823"
477 }],
478 "address": [{
479 "street_lines": [pd.address],
480 "city": pd.city,
481 "state": pd.state,
482 "zip": pd.zip,
483 "country": "US"
484 }],
485 "organization": [{
486 "identifiers": [{
487 "identifier": "2.16.840.1.113883.19.5.9999.1393"
488 }],
489 "name": [pd.performer_name]
490 }]
491 },
492 "product": {
493 "identifiers": [{
494 "identifier": "2a620155-9d11-439e-92b3-5d9815ff4ee8"
495 }],
496 "unencoded_name": pd.drug,
497 "product": {
498 "name": pd.drug,
499 "code": pd.rxnorm,
500 "translations": [{
501 "name": pd.drug,
502 "code": pd.rxnorm,
503 "code_system_name": "RXNORM"
504 }],
505 "code_system_name": "RXNORM"
506 },
507 "manufacturer": ""
508 }
509 }*/
510 };
511 }
513 function populateEncounter(pd) {
514 return {
515 "encounter": {
516 "name": pd.visit_category ? pd.visit_category : 'UNK',
517 "code": "185347001",
518 "code_system": "2.16.840.1.113883.6.96",
519 "code_system_name": "SNOMED CT",
520 "translations": [{
521 "name": "Ambulatory",
522 "code": "AMB",
523 "code_system_name": "ActCode"
524 }]
525 },
526 "identifiers": [{
527 "identifier": pd.sha_extension,
528 "extension": pd.extension
529 }],
530 "date_time": {
531 "point": {
532 "date": fDate(pd.date),
533 "precision": "second" //getPrecision(fDate(pd.date_formatted))
534 }
535 },
536 "performers": [{
537 "identifiers": [{
538 "identifier": "2.16.840.1.113883.4.6",
539 "extension": pd.npi || "UNK"
540 }],
541 "code": [{
542 "name": pd.physician_type,
543 "code": cleanCode(pd.physician_type_code),
544 "code_system_name": "SNOMED CT"
545 }],
546 "name": [
547 {
548 "last": pd.lname || "UNK",
549 "first": pd.fname || "UNK"
550 }
551 ],
552 "phone": [
553 {
554 "number": pd.work_phone,
555 "type": "work place"
556 }
557 ]
558 }],
559 "locations": [{
560 "name": pd.location,
561 "location_type": {
562 "name": pd.location_details,
563 "code": "1160-1",
564 "code_system_name": "HealthcareServiceLocation"
565 },
566 "address": [{
567 "street_lines": [pd.facility_address],
568 "city": pd.facility_city,
569 "state": pd.facility_state,
570 "zip": pd.facility_zip,
571 "country": pd.facility_country || "US"
572 }],
573 "phone": [
574 {
575 "number": pd.facility_phone,
576 "type": "work place"
577 }
578 ]
579 }],
580 "findings": [{
581 "identifiers": [{
582 "identifier": pd.sha_extension,
583 "extension": pd.extension
584 }],
585 "value": {
586 "name": pd.encounter_procedures.procedures.text || encounter_reason,
587 "code": cleanCode(pd.encounter_procedures.procedures.code),
588 "code_system_name": pd.encounter_procedures.procedures.code_type || "ICD10" || "CPT4"
589 },
590 "date_time": {
591 "low": {
592 "date": fDate(pd.date),
593 "precision": "day"
594 }
595 },
596 //"status": pd.encounter_procedures.procedures.status
597 }]
598 };
599 }
601 function populateAllergy(pd) {
602 return {
603 "identifiers": [{
604 "identifier": pd.sha_id,
605 "extension": pd.id || "UNK"
606 }],
607 "date_time": {
608 "low": templateDate(pd.startdate, "day"),
609 //"high": templateDate(pd.enddate, "day")
610 },
611 "observation": {
612 "identifiers": [{
613 "identifier": "4adc1020-7b14-11db-9fe1-0800200c9a66",
614 "extension": pd.extension || "UNK"
615 }],
616 "allergen": {
617 "name": pd.title,
618 "code": cleanCode(pd.rxnorm_code) ? cleanCode(pd.rxnorm_code) : cleanCode(pd.snomed_code) ? cleanCode(pd.snomed_code) : cleanCode(pd.diagnosis_code),
619 "code_system_name": cleanCode(pd.rxnorm_code) ? "RXNORM" : cleanCode(pd.snomed_code) ? "SNOMED CT" : "ICD-10-CM"
620 },
621 "date_time": {
622 "low": {
623 "date": fDate(pd.startdate),
624 "precision": "day"
625 }
626 },
627 "intolerance": {
628 "name": "Propensity to adverse reactions to drug",
629 "code": "420134006",
630 "code_system_name": "SNOMED CT"
631 },
632 "severity": {
633 "code": {
634 "name": pd.outcome,
635 "code": cleanCode(pd.outcome_code) || "UNK",
636 "code_system_name": "SNOMED CT"
637 }
638 },
639 "status": {
640 "name": pd.status_table,
641 "code": cleanCode(pd.status_code) || "UNK",
642 "code_system_name": "SNOMED CT"
643 },
644 "reactions": [{
645 "identifiers": [{
646 "identifier": "4adc1020-7b14-11db-9fe1-0800200c9a64"
647 }],
648 "date_time": {
649 "low": templateDate(pd.startdate, "day"),
650 "high": templateDate(pd.enddate, "day")
651 },
652 "reaction": {
653 "name": pd.reaction_text,
654 "code": cleanCode(pd.reaction_code) || "UNK",
655 "code_system_name": pd.reaction_code_type || "SNOMED CT"
656 },
657 "severity": {
658 "code": {
659 "name": pd.outcome,
660 "code": cleanCode(pd.outcome_code) || "UNK",
661 "code_system_name": "SNOMED CT"
662 }
663 }
664 }]
665 }
666 }
667 }
669 function populateProblem(pd) {
670 return {
671 "date_time": {
672 "low": {
673 "date": fDate(pd.start_date_table),
674 "precision": "day"
675 },
676 /*"high": {
677 "date": fDate(pd.end_date),
678 "precision": "day"
679 }*/
680 },
681 "identifiers": [{
682 "identifier": pd.sha_extension,
683 "extension": pd.extension || "UNK"
684 }],
685 "translations": [{
686 "name": "Condition",
687 "code": "75323-6",
688 "code_system_name": "LOINC"
689 }],
690 "problem": {
691 "code": {
692 "name": trim(pd.title),
693 "code": cleanCode(pd.code),
694 "code_system_name": trim(pd.code_type)
695 },
696 "date_time": {
697 "low": {
698 "date": fDate(pd.start_date),
699 "precision": "day"
700 },
701 /*"high": {
702 "date": fDate(pd.end_date),
703 "precision": getPrecision()
704 }*/
705 }
706 },
707 "performer": [
708 {
709 "identifiers": [
710 {
711 "identifier": "2.16.840.1.113883.4.6",
712 "extension": all.primary_care_provider.provider[0].npi || "UNK"
713 }
714 ],
715 "name": [
716 {
717 "last": all.primary_care_provider.provider[0].lname || "",
718 "first": all.primary_care_provider.provider[0].fname || ""
719 }
720 ]
721 }],
722 "onset_age": pd.age,
723 "onset_age_unit": "Year",
724 "status": {
725 "name": pd.status_table,
726 "date_time": {
727 "low": {
728 "date": fDate(pd.start_date),
729 "precision": "day"
730 },
731 /*"high": {
732 "date": fDate(pd.end_date),
733 "precision": getPrecision()
734 }*/
735 }
736 },
737 "patient_status": pd.observation,
738 "source_list_identifiers": [{
739 "identifier": pd.sha_extension,
740 "extension": pd.extension || "UNK"
741 }]
742 };
744 }
746 function populateProcedure(pd) {
747 return {
748 "procedure": {
749 "name": pd.description,
750 "code": cleanCode(pd.code),
751 //"code_system": "2.16.840.1.113883.6.12",
752 "code_system_name": "SNOMED CT"
753 },
754 "identifiers": [{
755 "identifier": "d68b7e32-7810-4f5b-9cc2-acd54b0fd85d",
756 "extension": pd.extension
757 }],
758 "status": "completed",
759 "date_time": {
760 "point": {
761 "date": fDate(pd.date),
762 "precision": "day"
763 }
764 },
765 /*"body_sites": [{
766 "name": "",
767 "code": "",
768 "code_system_name": ""
769 }],
770 "specimen": {
771 "identifiers": [{
772 "identifier": "c2ee9ee9-ae31-4628-a919-fec1cbb58683"
773 }],
774 "code": {
775 "name": "",
776 "code": "",
777 "code_system_name": "SNOMED CT"
778 }
779 },*/
780 "performers": [{
781 "identifiers": [{
782 "identifier": "2.16.840.1.113883.4.6",
783 "extension": pd.npi || "UNK"
784 }],
785 "address": [{
786 "street_lines": [pd.address],
787 "city": pd.city,
788 "state": pd.state,
789 "zip": pd.zip,
790 "country": "US"
791 }],
792 "phone": [{
793 "number": pd.work_phone,
794 "type": "work place"
795 }],
796 "organization": [{
797 "identifiers": [{
798 "identifier": pd.facility_sha_extension,
799 "extension": pd.facility_extension
800 }],
801 "name": [pd.facility_name],
802 "address": [{
803 "street_lines": [pd.facility_address],
804 "city": pd.facility_city,
805 "state": pd.facility_state,
806 "zip": pd.facility_zip,
807 "country": pd.facility_country || "US"
808 }],
809 "phone": [{
810 "number": pd.facility_phone,
811 "type": "work place"
812 }]
813 }]
814 }],
815 "procedure_type": "procedure"
816 };
817 }
819 function populateMedicalDevice(pd) {
820 return {
821 "identifiers": [{
822 "identifier": pd.sha_extension,
823 "extension": pd.extension
824 }],
825 "date_time": {
826 "low": {
827 "date": fDate(pd.start_date),
828 "precision": "day"
829 }/*,
830 "high": {
831 "date": fDate(pd.end_date),
832 "precision": "day"
833 }*/
834 },
835 "device_type": "UDI",
836 "device": {
837 "name": pd.code_text,
838 "code": cleanCode(pd.code),
839 "code_system_name": "SNOMED CT",
840 "identifiers": [{
841 "identifier": "2.16.840.1.113883.3.3719",
842 "extension": pd.udi
843 }],
844 "status": "completed",
845 "body_sites": [{
846 "name": "",
847 "code": "",
848 "code_system_name": ""
849 }],
850 "udi": pd.udi
851 }
852 }
853 }
856 function populateResult(pd) {
857 let icode = pd.subtest.abnormal_flag;
858 let value = parseFloat(pd.subtest.result_value) || pd.subtest.result_value || "";
859 let type = isNaN(value) ? "ST" : "PQ";
860 type = !pd.subtest.unit ? "ST" : type;
861 value += "";
862 let range_type = pd.subtest.range.toUpperCase() == "NEGATIVE" ? "CO" : type;
863 type = value.toUpperCase() == "NEGATIVE" ? "CO" : type;
865 switch (pd.subtest.abnormal_flag.toUpperCase()) {
866 case "NO":
867 icode = "Normal";
868 break;
869 case "YES":
870 icode = "Abnormal";
871 break;
872 case "":
873 icode = "UNK";
874 break;
875 }
876 return {
877 "identifiers": [{
878 "identifier": pd.subtest.root,
879 "extension": pd.subtest.extension
880 }],
881 "result": {
882 "name": pd.title,
883 "code": cleanCode(pd.subtest.result_code) || "UNK",
884 "code_system_name": "LOINC"
885 },
886 "date_time": {
887 "point": {
888 "date": fDate(pd.date_ordered),
889 "precision": "day"
890 }
891 },
892 "status": pd.order_status,
893 "reference_range": {
894 "low": pd.subtest.low,
895 "high": pd.subtest.high,
896 "unit": pd.subtest.unit,
897 "type": type,
898 "range_type": range_type
899 },
900 "interpretations": [icode],
901 "value": value + "",
902 "unit": pd.subtest.unit,
903 "type": type,
904 "range": pd.subtest.range,
905 "range_type": range_type
906 };
907 }
909 function getResultSet(results) {
911 if (!results) return '';
913 let tResult = results.result[0] || results.result;
914 var resultSet = {
915 "identifiers": [{
916 "identifier": tResult.root,
917 "extension": tResult.extension
918 }],
919 "author": [
920 {
921 "date_time": {
922 "point": {
923 "date": fDate(tResult.date_ordered),
924 "precision": getPrecision(fDate(tResult.date_ordered))
925 }
926 },
927 "identifiers": [
928 {
929 "identifier": "2.16.840.1.113883.4.6",
930 "extension": all.primary_care_provider.provider[0].npi || "UNK"
931 }
932 ],
933 "name": [
934 {
935 "last": all.primary_care_provider.provider[0].lname || "",
936 "first": all.primary_care_provider.provider[0].fname || ""
937 }
938 ]
939 }],
940 "result_set": {
941 "name": tResult.test_name,
942 "code": cleanCode(tResult.test_code),
943 "code_system_name": "LOINC"
944 }
945 };
946 var rs = [];
947 var many = [];
948 var theone = {};
949 var count = 0;
950 many.results = [];
951 try {
952 count = isOne(results.result);
953 } catch (e) {
954 count = 0;
955 }
956 if (count > 1) {
957 for (let i in results.result) {
958 theone[i] = populateResult(results.result[i]);
959 many.results.push(theone[i]);
960 }
961 } else if (count !== 0) {
962 theone = populateResult(results.result);
963 many.results.push(theone);
964 }
965 rs.results = Object.assign(resultSet);
966 rs.results.results = Object.assign(many.results);
967 return rs;
968 }
970 function getPlanOfCare(pd) {
971 return {
972 "plan": {
973 "name": pd.code_text || "UNK",
974 "code": cleanCode(pd.code) || "UNK",
975 "code_system_name": pd.code_type || "SNOMED CT"
976 },
977 "identifiers": [{
978 "identifier": "9a6d1bac-17d3-4195-89a4-1121bc809b4a"
979 }],
980 "goal": {
981 "code": cleanCode(pd.code) || "UNK",
982 "name": pd.description || "UNK"
983 },
984 "date_time": {
985 "center": {
986 "date": fDate(pd.date_formatted),
987 "precision": "day"
988 }
989 },
990 "type": "observation",
991 "status": {
992 "code": cleanCode(pd.status)
993 },
994 "name": pd.description
995 };
996 }
998 function populateVital(pd) {
999 return {
1000 "identifiers": [{
1001 "identifier": pd.sha_extension,
1002 "extension": pd.extension
1003 }],
1004 "status": "completed",
1005 "date_time": {
1006 "point": {
1007 "date": fDate(pd.effectivetime),
1008 "precision": getPrecision(fDate(pd.effectivetime))
1009 }
1010 },
1011 // our list of vitals per organizer.
1012 "vital_list": [{
1013 "identifiers": [{
1014 "identifier": pd.sha_extension,
1015 "extension": pd.extension_bps
1016 }],
1017 "vital": {
1018 "name": "Blood Pressure Systolic",
1019 "code": "8480-6",
1020 "code_system_name": "LOINC"
1021 },
1022 "status": "completed",
1023 "date_time": {
1024 "point": {
1025 "date": fDate(pd.effectivetime),
1026 "precision": getPrecision(fDate(pd.effectivetime))
1027 }
1028 },
1029 "interpretations": ["Normal"],
1030 "value": parseFloat(pd.bps),
1031 "unit": "mm[Hg]"
1032 }, {
1033 "identifiers": [{
1034 "identifier": pd.sha_extension,
1035 "extension": pd.extension_bpd
1036 }],
1037 "vital": {
1038 "name": "Blood Pressure Diastolic",
1039 "code": "8462-4",
1040 "code_system_name": "LOINC"
1041 },
1042 "status": "completed",
1043 "date_time": {
1044 "point": {
1045 "date": fDate(pd.effectivetime),
1046 "precision": getPrecision(fDate(pd.effectivetime))
1047 }
1048 },
1049 "interpretations": ["Normal"],
1050 "value": parseFloat(pd.bpd),
1051 "unit": "mm[Hg]"
1052 }, {
1053 "identifiers": [{
1054 "identifier": pd.sha_extension,
1055 "extension": pd.extension_pulse
1056 }],
1057 "vital": {
1058 "name": "Heart Rate",
1059 "code": "8867-4",
1060 "code_system_name": "LOINC"
1061 },
1062 "status": "completed",
1063 "date_time": {
1064 "point": {
1065 "date": fDate(pd.effectivetime),
1066 "precision": getPrecision(fDate(pd.effectivetime))
1067 }
1068 },
1069 "interpretations": ["Normal"],
1070 "value": parseFloat(pd.pulse),
1071 "unit": "/min"
1072 }, {
1073 "identifiers": [{
1074 "identifier": "2.16.840.1.113883.3.140.1.0.6.10.14.2",
1075 "extension": pd.extension_breath
1076 }],
1077 "vital": {
1078 "name": "Respiratory Rate",
1079 "code": "9279-1",
1080 "code_system_name": "LOINC"
1081 },
1082 "status": "completed",
1083 "date_time": {
1084 "point": {
1085 "date": fDate(pd.effectivetime),
1086 "precision": getPrecision(fDate(pd.effectivetime))
1087 }
1088 },
1089 "interpretations": ["Normal"],
1090 "value": parseFloat(pd.breath),
1091 "unit": "/min"
1092 }, {
1093 "identifiers": [{
1094 "identifier": "2.16.840.1.113883.3.140.1.0.6.10.14.3",
1095 "extension": pd.extension_temperature
1096 }],
1097 "vital": {
1098 "name": "Body Temperature",
1099 "code": "8310-5",
1100 "code_system_name": "LOINC"
1101 },
1102 "status": "completed",
1103 "date_time": {
1104 "point": {
1105 "date": fDate(pd.effectivetime),
1106 "precision": getPrecision(fDate(pd.effectivetime))
1107 }
1108 },
1109 "interpretations": ["Normal"],
1110 "value": parseFloat(pd.temperature),
1111 "unit": pd.unit_temperature
1112 },
1113 {
1114 "identifiers": [{
1115 "identifier": pd.sha_extension,
1116 "extension": pd.extension_height
1117 }],
1118 "vital": {
1119 "name": "Height",
1120 "code": "8302-2",
1121 "code_system_name": "LOINC"
1122 },
1123 "status": "completed",
1124 "date_time": {
1125 "point": {
1126 "date": fDate(pd.effectivetime),
1127 "precision": getPrecision(fDate(pd.effectivetime))
1128 }
1129 },
1130 "interpretations": ["Normal"],
1131 "value": parseFloat(pd.height),
1132 "unit": pd.unit_height
1133 }, {
1134 "identifiers": [{
1135 "identifier": pd.sha_extension,
1136 "extension": pd.extension_weight
1137 }],
1138 "vital": {
1139 "name": "Weight Measured",
1140 "code": "29463-7",
1141 "code_system_name": "LOINC"
1142 },
1143 "status": "completed",
1144 "date_time": {
1145 "point": {
1146 "date": fDate(pd.effectivetime),
1147 "precision": getPrecision(fDate(pd.effectivetime))
1148 }
1149 },
1150 "interpretations": ["Normal"],
1151 "value": parseFloat(pd.weight),
1152 "unit": pd.unit_weight
1153 }, {
1154 "identifiers": [{
1155 "identifier": pd.sha_extension,
1156 "extension": pd.extension_BMI
1157 }],
1158 "vital": {
1159 "name": "BMI (Body Mass Index)",
1160 "code": "39156-5",
1161 "code_system_name": "LOINC"
1162 },
1163 "status": "completed",
1164 "date_time": {
1165 "point": {
1166 "date": fDate(pd.effectivetime),
1167 "precision": getPrecision(fDate(pd.effectivetime))
1168 }
1169 },
1170 "interpretations": ["Normal"],
1171 "value": parseFloat(pd.BMI),
1172 "unit": "kg/m2"
1173 }, {
1174 "identifiers": [{
1175 "identifier": pd.sha_extension,
1176 "extension": pd.extension_oxygen_saturation
1177 }],
1178 "vital": {
1179 "name": "O2 % BldC Oximetry",
1180 "code": "59408-5",
1181 "code_system_name": "LOINC"
1182 },
1183 "status": "completed",
1184 "date_time": {
1185 "point": {
1186 "date": fDate(pd.effectivetime),
1187 "precision": getPrecision(fDate(pd.effectivetime))
1188 }
1189 },
1190 "interpretations": ["Normal"],
1191 "value": parseFloat(pd.oxygen_saturation),
1192 "unit": "%"
1193 }
1194 ]
1195 }
1196 }
1198 function populateSocialHistory(pd) {
1199 return {
1200 "date_time": {
1201 "low": templateDate(pd.date_formatted, "day")
1202 //"high": templateDate(pd.date, "day")
1203 },
1204 "identifiers": [{
1205 "identifier": pd.sha_extension,
1206 "extension": pd.extension
1207 }],
1208 "code": {
1209 "name": pd.element
1210 },
1211 "value": pd.description,
1212 "gender": all.patient.gender
1213 };
1214 }
1216 function populateImmunization(pd) {
1217 return {
1218 "date_time": {
1219 "point": {
1220 "date": fDate(pd.administered_on),
1221 "precision": "month"
1222 }
1223 },
1224 "identifiers": [{
1225 "identifier": "e6f1ba43-c0ed-4b9b-9f12-f435d8ad8f92",
1226 "extension": pd.extension || "UNK"
1227 }],
1228 "status": "complete",
1229 "product": {
1230 "product": {
1231 "name": pd.code_text,
1232 "code": cleanCode(pd.cvx_code),
1233 "code_system_name": "CVX"
1234 /*"translations": [{
1235 "name": "",
1236 "code": "",
1237 "code_system_name": "CVX"
1238 }]*/
1239 },
1240 "lot_number": "UNK",
1241 "manufacturer": "UNK"
1242 },
1243 "administration": {
1244 "route": {
1245 "name": pd.route_of_administration,
1246 "code": cleanCode(pd.route_code) || "UNK",
1247 "code_system_name": "Medication Route FDA"
1248 }/*,
1249 "dose": {
1250 "value": 50,
1251 "unit": "mcg"
1252 }*/
1253 },
1254 "performer": {
1255 "identifiers": [{
1256 "identifier": "2.16.840.1.113883.4.6",
1257 "extension": npiProvider || "UNK"
1258 }],
1259 "name": [{
1260 "last": pd.lname,
1261 "first": pd.fname
1262 }],
1263 "address": [{
1264 "street_lines": [pd.address],
1265 "city": pd.city,
1266 "state": pd.state,
1267 "zip": pd.zip,
1268 "country": "US"
1269 }],
1270 "organization": [{
1271 "identifiers": [{
1272 "identifier": "2.16.840.1.113883.4.6",
1273 "extension": npiFacility || "UNK"
1274 }],
1275 "name": [pd.facility_name]
1276 }]
1277 },
1278 "instructions": {
1279 "code": {
1280 "name": "immunization education",
1281 "code": "171044003",
1282 "code_system_name": "SNOMED CT"
1283 },
1284 "free_text": "Needs Attention for more data."
1285 }
1286 };
1287 }
1289 function populatePayer(pd) {
1290 return {
1291 "identifiers": [{
1292 "identifier": "1fe2cdd0-7aad-11db-9fe1-0800200c9a66"
1293 }],
1294 "policy": {
1295 "identifiers": [{
1296 "identifier": "3e676a50-7aac-11db-9fe1-0800200c9a66"
1297 }],
1298 "code": {
1299 "code": "SELF",
1300 "code_system_name": "HL7 RoleCode"
1301 },
1302 "insurance": {
1303 "code": {
1304 "code": "PAYOR",
1305 "code_system_name": "HL7 RoleCode"
1306 },
1307 "performer": {
1308 "identifiers": [{
1309 "identifier": "2.16.840.1.113883.19"
1310 }],
1311 "address": [{
1312 "street_lines": ["123 Insurance Road"],
1313 "city": "Blue Bell",
1314 "state": "MA",
1315 "zip": "02368",
1316 "country": "US",
1317 "use": "work place"
1318 }],
1319 "phone": [{
1320 "number": "(781)555-1515",
1321 "type": "work place"
1322 }],
1323 "organization": [{
1324 "name": ["Good Health Insurance"],
1325 "address": [{
1326 "street_lines": ["123 Insurance Road"],
1327 "city": "Blue Bell",
1328 "state": "MA",
1329 "zip": "02368",
1330 "country": "US",
1331 "use": "work place"
1332 }],
1333 "phone": [{
1334 "number": "(781)555-1515",
1335 "type": "work place"
1336 }]
1337 }],
1338 "code": [{
1339 "code": "PAYOR",
1340 "code_system_name": "HL7 RoleCode"
1341 }]
1342 }
1343 }
1344 },
1345 "guarantor": {
1346 "code": {
1347 "code": "GUAR",
1348 "code_system_name": "HL7 Role"
1349 },
1350 "identifiers": [{
1351 "identifier": "329fcdf0-7ab3-11db-9fe1-0800200c9a66"
1352 }],
1353 "name": [{
1354 "prefix": "Mr.",
1355 "middle": ["Frankie"],
1356 "last": "Everyman",
1357 "first": "Adam"
1358 }],
1359 "address": [{
1360 "street_lines": ["17 Daws Rd."],
1361 "city": "Blue Bell",
1362 "state": "MA",
1363 "zip": "02368",
1364 "country": "US",
1365 "use": "primary home"
1366 }],
1367 "phone": [{
1368 "number": "(781)555-1212",
1369 "type": "primary home"
1370 }]
1371 },
1372 "participant": {
1373 "code": {
1374 "name": "Self",
1375 "code": "SELF",
1376 "code_system_name": "HL7 Role"
1377 },
1378 "performer": {
1379 "identifiers": [{
1380 "identifier": "14d4a520-7aae-11db-9fe1-0800200c9a66",
1381 "extension": "1138345"
1382 }],
1383 "address": [{
1384 "street_lines": ["17 Daws Rd."],
1385 "city": "Blue Bell",
1386 "state": "MA",
1387 "zip": "02368",
1388 "country": "US",
1389 "use": "primary home"
1390 }],
1391 "code": [{
1392 "name": "Self",
1393 "code": "SELF",
1394 "code_system_name": "HL7 Role"
1395 }]
1396 },
1397 "name": [{
1398 "prefix": "Mr.",
1399 "middle": ["A."],
1400 "last": "Everyman",
1401 "first": "Frank"
1402 }]
1403 },
1404 "policy_holder": {
1405 "performer": {
1406 "identifiers": [{
1407 "identifier": "2.16.840.1.113883.19",
1408 "extension": "1138345"
1409 }],
1410 "address": [{
1411 "street_lines": ["17 Daws Rd."],
1412 "city": "Blue Bell",
1413 "state": "MA",
1414 "zip": "02368",
1415 "country": "US",
1416 "use": "primary home"
1417 }]
1418 }
1419 },
1420 "authorization": {
1421 "identifiers": [{
1422 "identifier": "f4dce790-8328-11db-9fe1-0800200c9a66"
1423 }],
1424 "procedure": {
1425 "code": {
1426 "name": "Colonoscopy",
1427 "code": "73761001",
1428 "code_system_name": "SNOMED CT"
1429 }
1430 }
1431 }
1432 };
1433 }
1435 function populateHeader(pd) {
1436 var head = {
1437 "identifiers": [
1438 {
1439 "identifier": oidFacility,
1440 "extension": "TT988"
1441 }
1442 ],
1443 "code": {
1444 "name": "Continuity of Care Document", //change to toc w/code
1445 "code": "34133-9",
1446 "code_system_name": "LOINC"
1447 },
1448 "template": [
1449 "2.16.840.1.113883.10.20.22.1.1",
1450 "2.16.840.1.113883.10.20.22.1.2"
1451 ],
1452 "title": "OpenEMR Transitions of Care : Consolidated CDA",
1453 "date_time": {
1454 "date": pd.created_time_timezone,
1455 "precision": "none"
1456 },
1457 "author": {
1458 "author": [
1459 {
1460 "time": pd.created_time_timezone,
1461 "identifiers": [
1462 {
1463 "identifier": "2.16.840.1.113883.4.6",
1464 "extension": pd.author.npi || "UNK"
1465 }
1466 ],
1467 "name": [
1468 {
1469 "last": pd.author.lname,
1470 "first": pd.author.fname
1471 }
1472 ],
1473 "address": [
1474 {
1475 "street_lines": [
1476 pd.author.streetAddressLine
1477 ],
1478 "city": pd.author.city,
1479 "state": pd.author.state,
1480 "zip": pd.author.postalCode,
1481 "country": pd.author.country || "US",
1482 "use": "work place"
1483 }
1484 ],
1485 "phone": [
1486 {
1487 "number": pd.author.telecom || "UNK",
1488 "type": "WP"
1489 }
1490 ],
1491 "organization": [
1492 {
1493 "identity": [
1494 {
1495 "root": "2.16.840.1.113883.4.6",
1496 "extension": npiFacility || "UNK"
1497 }
1498 ],
1499 "name": [
1500 pd.encounter_provider.facility_name
1501 ],
1502 "address": [
1503 {
1504 "street_lines": [
1505 pd.encounter_provider.facility_street
1506 ],
1507 "city": pd.encounter_provider.facility_city,
1508 "state": pd.encounter_provider.facility_state,
1509 "zip": pd.encounter_provider.facility_postal_code,
1510 "country": pd.encounter_provider.facility_country_code || "US",
1511 "use": "work place"
1512 }
1513 ],
1514 "phone": [
1515 {
1516 "number": pd.encounter_provider.facility_phone,
1517 "type": "work primary"
1518 }
1519 ]
1520 }
1521 ]
1522 }
1523 ]
1524 },
1525 "custodian": {
1526 "identity": [
1527 {
1528 "root": "2.16.840.1.113883.4.6",
1529 "extension": npiFacility || "UNK"
1530 }
1531 ],
1532 "name": [
1533 pd.encounter_provider.facility_name
1534 ],
1535 "address": [
1536 {
1537 "street_lines": [
1538 pd.encounter_provider.facility_street
1539 ],
1540 "city": pd.encounter_provider.facility_city,
1541 "state": pd.encounter_provider.facility_state,
1542 "zip": pd.encounter_provider.facility_postal_code,
1543 "country": pd.encounter_provider.facility_country_code || "US"
1544 }
1545 ],
1546 "phone": [
1547 {
1548 "number": pd.encounter_provider.facility_phone,
1549 "type": "work primary"
1550 }
1551 ]
1552 },
1553 /*"data_enterer": {
1554 "identifiers": [
1555 {
1556 "identifier": "2.16.840.1.113883.4.6",
1557 "extension": "999999943252"
1558 }
1559 ],
1560 "name": [
1561 {
1562 "last": pd.data_enterer.lname,
1563 "first": pd.data_enterer.fname
1564 }
1565 ],
1566 "address": [
1567 {
1568 "street_lines": [
1569 pd.data_enterer.streetAddressLine
1570 ],
1571 "city": pd.data_enterer.city,
1572 "state": pd.data_enterer.state,
1573 "zip": pd.data_enterer.postalCode,
1574 "country": pd.data_enterer.country
1575 }
1576 ],
1577 "phone": [
1578 {
1579 "number": pd.data_enterer.telecom,
1580 "type": "work place"
1581 }
1582 ]
1583 },
1584 "informant": {
1585 "identifiers": [
1586 {
1587 "identifier": "2.16.840.1.113883.19.5",
1588 "extension": "KP00017"
1589 }
1590 ],
1591 "name": [
1592 {
1593 "last": pd.informer.lname || "",
1594 "first": pd.informer.fname || ""
1595 }
1596 ],
1597 "address": [
1598 {
1599 "street_lines": [
1600 pd.informer.streetAddressLine || ""
1601 ],
1602 "city": pd.informer.city,
1603 "state": pd.informer.state,
1604 "zip": pd.informer.postalCode,
1605 "country": pd.informer.country
1606 }
1607 ],
1608 "phone": [
1609 {
1610 "number": pd.informer.telecom || "",
1611 "type": "work place"
1612 }
1613 ]
1614 },*/
1615 /*"service_event": {
1616 "code": {
1617 "name": "UNK",
1618 "code": "UNK",
1619 "code_system_name": "SNOMED CT"
1620 },
1621 "date_time": {
1622 "low": {
1623 "date": "2021-03-11",
1624 "precision": "day"
1625 },
1626 "high": {
1627 "date": pd.created_time,
1628 "precision": "day"
1629 }
1630 },
1631 "performer": [
1632 {
1633 "performer": [
1634 {
1635 "identifiers": [
1636 {
1637 "identifier": "2.16.840.1.113883.4.6",
1638 "extension": npiProvider
1639 }
1640 ],
1641 "name": [
1642 {
1643 "last": pd.information_recipient.lname || "DAH",
1644 "first": pd.information_recipient.fname || "DAH"
1645 }
1646 ],
1647 "address": [
1648 {
1649 "street_lines": [
1650 pd.information_recipient.streetAddressLine
1651 ],
1652 "city": pd.information_recipient.city,
1653 "state": pd.information_recipient.state,
1654 "zip": pd.information_recipient.postalCode,
1655 "country": pd.information_recipient.country || "US"
1656 }
1657 ],
1658 "phone": [
1659 {
1660 "number": pd.information_recipient.telecom,
1661 "type": "work place"
1662 }
1663 ],
1664 "organization": [
1665 {
1666 "identifiers": [
1667 {
1668 "identifier": "2.16.840.1.113883.19.5.9999.1393"
1669 }
1670 ],
1671 "name": [
1672 pd.encounter_provider.facility_name
1673 ],
1674 "address": [
1675 {
1676 "street_lines": [
1677 pd.encounter_provider.facility_street
1678 ],
1679 "city": pd.encounter_provider.facility_city,
1680 "state": pd.encounter_provider.facility_state,
1681 "zip": pd.encounter_provider.facility_postal_code,
1682 "country": pd.encounter_provider.facility_country_code || "US"
1683 }
1684 ],
1685 "phone": [
1686 {
1687 "number": pd.encounter_provider.facility_phone,
1688 "type": "primary work"
1689 }
1690 ]
1691 }
1692 ],
1693 "code": [
1694 {
1695 "name": "UNK",
1696 "code": "",
1697 "code_system_name": "Provider Codes"
1698 }
1699 ]
1700 }
1701 ],
1702 "code": {
1703 "name": "Primary Performer",
1704 "code": "PP",
1705 "code_system_name": "Provider Role"
1706 }
1707 }
1708 ]
1709 }*/
1710 };
1711 return head;
1712 }
1714 function getMeta(pd) {
1715 var meta = {};
1716 meta = {
1717 "type": "CCDA",
1718 "identifiers": [
1719 {
1720 "identifier": oidFacility || "UNK",
1721 "extension": "TT988"
1722 }
1723 ],
1724 "confidentiality": "Normal",
1725 "set_id": {
1726 "identifier": oidFacility + ".1" || "UNK",
1727 "extension": "sTT988"
1728 }
1729 }
1730 return meta;
1731 }
1733 function genCcda(pd) {
1734 var doc = {};
1735 var data = {};
1736 var count = 0;
1737 var many = [];
1738 var theone = {};
1740 all = pd;
1741 npiProvider = all.primary_care_provider.provider[0].npi;
1742 oidFacility = all.encounter_provider.facility_oid ? all.encounter_provider.facility_oid : "2.16.840.1.113883.3.8888.999999";
1743 npiFacility = all.encounter_provider.facility_npi;
1745 // Demographics
1746 let demographic = populateDemographic(pd.patient, pd.guardian, pd);
1747 // This populates documentationOf. We are using providerOrganization also.
1748 Object.assign(demographic, populateProviders());
1750 data.demographics = Object.assign(demographic);
1752 // vitals
1753 many.vitals = [];
1754 try {
1755 count = isOne(pd.history_physical.vitals_list.vitals);
1756 } catch (e) {
1757 count = 0
1758 }
1759 /*if (count > 1) {
1760 for (let i in pd.history_physical.vitals_list.vitals) {
1761 theone = populateVital(pd.history_physical.vitals_list.vitals[i]);
1762 many.vitals.push.apply(many.vitals, theone);
1763 }
1764 } else if (count === 1) {
1765 theone = populateVital(pd.history_physical.vitals_list.vitals);
1766 many.vitals.push(theone);
1767 }
1768 data.vitals = Object.assign(many.vitals);*/
1769 if (count !== 0) {
1770 data.vitals = Object.assign(populateVital(pd.history_physical.vitals_list.vitals));
1771 }
1772 // Medications
1773 let meds = [];
1774 let m = {};
1775 meds.medications = [];
1776 try {
1777 count = isOne(pd.medications.medication);
1778 } catch (e) {
1779 count = 0
1780 }
1781 if (count > 1) {
1782 for (let i in pd.medications.medication) {
1783 m[i] = populateMedication(pd.medications.medication[i]);
1784 meds.medications.push(m[i]);
1785 }
1786 } else if (count !== 0) {
1787 m = populateMedication(pd.medications.medication);
1788 meds.medications.push(m);
1789 }
1790 data.medications = Object.assign(meds.medications);
1791 // Encounters
1792 let encs = [];
1793 let enc = {};
1794 encs.encounters = [];
1795 try {
1796 count = isOne(pd.encounter_list.encounter);
1797 } catch (e) {
1798 count = 0
1799 }
1800 if (count > 1) {
1801 for (let i in pd.encounter_list.encounter) {
1802 enc[i] = populateEncounter(pd.encounter_list.encounter[i]);
1803 encs.encounters.push(enc[i]);
1804 }
1805 } else if (count !== 0) {
1806 enc = populateEncounter(pd.encounter_list.encounter);
1807 encs.encounters.push(enc);
1808 }
1809 data.encounters = Object.assign(encs.encounters);
1811 // Allergies
1812 let allergies = [];
1813 let allergy = {};
1814 allergies.allergies = [];
1815 try {
1816 count = isOne(pd.allergies.allergy);
1817 } catch (e) {
1818 count = 0
1819 }
1820 if (count > 1) {
1821 for (let i in pd.allergies.allergy) {
1822 allergy[i] = populateAllergy(pd.allergies.allergy[i]);
1823 allergies.allergies.push(allergy[i]);
1824 }
1825 } else if (count !== 0) {
1826 allergy = populateAllergy(pd.allergies.allergy);
1827 allergies.allergies.push(allergy);
1828 }
1829 data.allergies = Object.assign(allergies.allergies);
1831 // Problems
1832 let problems = [];
1833 let problem = {};
1834 problems.problems = [];
1835 try {
1836 count = isOne(pd.problem_lists.problem);
1837 } catch (e) {
1838 count = 0
1839 }
1840 if (count > 1) {
1841 for (let i in pd.problem_lists.problem) {
1842 problem[i] = populateProblem(pd.problem_lists.problem[i], pd);
1843 problems.problems.push(problem[i]);
1844 }
1845 } else if (count !== 0) {
1846 problem = populateProblem(pd.problem_lists.problem);
1847 problems.problems.push(problem);
1848 }
1849 data.problems = Object.assign(problems.problems);
1850 // Procedures
1851 many = [];
1852 theone = {};
1853 many.procedures = [];
1854 try {
1855 count = isOne(pd.procedures.procedure);
1856 } catch (e) {
1857 count = 0
1858 }
1859 if (count > 1) {
1860 for (let i in pd.procedures.procedure) {
1861 theone[i] = populateProcedure(pd.procedures.procedure[i]);
1862 many.procedures.push(theone[i]);
1863 }
1864 } else if (count !== 0) {
1865 theone = populateProcedure(pd.procedures.procedure);
1866 many.procedures.push(theone);
1867 }
1868 data.procedures = Object.assign(many.procedures);
1869 // Medical Devices
1870 many = [];
1871 theone = {};
1872 many.medical_devices = [];
1873 try {
1874 count = isOne(pd.medical_devices.device);
1875 } catch (e) {
1876 count = 0
1877 }
1878 if (count > 1) {
1879 for (let i in pd.medical_devices.device) {
1880 theone[i] = populateMedicalDevice(pd.medical_devices.device[i]);
1881 many.medical_devices.push(theone[i]);
1882 }
1883 } else if (count !== 0) {
1884 theone = populateMedicalDevice(pd.medical_devices.device);
1885 many.medical_devices.push(theone);
1886 }
1887 data.medical_devices = Object.assign(many.medical_devices);
1889 // Results
1890 if (pd.results) {
1891 data.results = Object.assign(getResultSet(pd.results, pd)['results']);
1892 }
1893 // Immunizations
1894 many = [];
1895 theone = {};
1896 many.immunizations = [];
1897 try {
1898 count = isOne(pd.immunizations.immunization);
1899 } catch (e) {
1900 count = 0;
1901 }
1902 if (count > 1) {
1903 for (let i in pd.immunizations.immunization) {
1904 theone[i] = populateImmunization(pd.immunizations.immunization[i]);
1905 many.immunizations.push(theone[i]);
1906 }
1907 } else if (count !== 0) {
1908 theone = populateImmunization(pd.immunizations.immunization);
1909 many.immunizations.push(theone);
1910 }
1911 data.immunizations = Object.assign(many.immunizations);
1912 // Plan of Care
1913 many = [];
1914 theone = {};
1915 many.plan_of_care = [];
1916 try {
1917 count = isOne(pd.planofcare.item);
1918 } catch (e) {
1919 count = 0
1920 }
1921 if (count > 1) {
1922 for (let i in pd.planofcare.item) {
1923 if (cleanCode(pd.planofcare.item[i].code) === '') {
1924 i--;
1925 continue;
1926 }
1927 theone[i] = getPlanOfCare(pd.planofcare.item[i]);
1928 many.plan_of_care.push(theone[i]);
1929 }
1930 } else if (count !== 0) {
1931 theone = getPlanOfCare(pd.planofcare.item);
1932 many.plan_of_care.push(theone);
1933 }
1935 data.plan_of_care = Object.assign(many.plan_of_care);
1936 // Social History
1937 many = [];
1938 theone = {};
1939 many.social_history = [];
1940 try {
1941 count = isOne(pd.history_physical.social_history.history_element);
1942 } catch (e) {
1943 count = 0
1944 }
1945 if (count > 1) {
1946 for (let i in pd.history_physical.social_history.history_element) {
1947 if (i > 0) break;
1948 theone[i] = populateSocialHistory(pd.history_physical.social_history.history_element[i]);
1949 many.social_history.push(theone[i]);
1950 }
1951 } else if (count !== 0) {
1952 theone = populateSocialHistory(pd.history_physical.social_history.history_element);
1953 many.social_history.push(theone);
1954 }
1956 data.social_history = Object.assign(many.social_history);
1958 // ------------------------------------------ End Sections ----------------------------------------//
1960 doc.data = Object.assign(data);
1961 let meta = getMeta(pd);
1962 let header = populateHeader(pd);
1964 meta.ccda_header = Object.assign(header);
1965 doc.meta = Object.assign(meta);
1966 let xml = bbg.generateCCD(doc);
1968 // Debug
1969 fs.writeFile("ccda.json", JSON.stringify(all, null, 4), function (err) {
1970 if (err) {
1971 return console.log(err);
1972 }
1973 console.log("Json saved!");
1974 });
1975 fs.writeFile("ccda.xml", xml, function (err) {
1976 if (err) {
1977 return console.log(err);
1978 }
1979 console.log("Xml saved!");
1980 });
1982 return xml;
1983 }
1985 function processConnection(connection) {
1986 conn = connection; // make it global
1987 var remoteAddress = conn.remoteAddress + ':' + conn.remotePort;
1988 //console.log(remoteAddress);
1989 conn.setEncoding('utf8');
1991 var xml_complete = "";
1993 function eventData(xml) {
1994 xml = xml.replace(/(\u000b|\u001c)/gm, "").trim();
1995 // Sanity check from service manager
1996 if (xml === 'status' || xml.length < 80) {
1997 conn.write("statusok" + String.fromCharCode(28) + "\r\r");
1998 conn.end('');
1999 return;
2000 }
2001 xml_complete += xml.toString();
2002 if (xml.toString().match(/\<\/CCDA\>$/g)) {
2003 // ---------------------start--------------------------------
2004 let doc = "";
2005 xml_complete = xml_complete.replace(/\t\s+/g, ' ').trim();
2007 to_json(xml_complete, function (error, data) {
2008 // console.log(JSON.stringify(data, null, 4));
2009 if (error) { // need try catch
2010 console.log('toJson error: ' + error + 'Len: ' + xml_complete.length);
2011 return;
2012 }
2013 doc = genCcda(data.CCDA);
2014 });
2016 doc = headReplace(doc);
2017 doc = doc.toString().replace(/(\u000b|\u001c|\r)/gm, "").trim();
2018 //console.log(doc);
2019 let chunk = "";
2020 let numChunks = Math.ceil(doc.length / 1024);
2021 for (let i = 0, o = 0; i < numChunks; ++i, o += 1024) {
2022 chunk = doc.substr(o, 1024);
2023 conn.write(chunk);
2024 }
2025 conn.write(String.fromCharCode(28) + "\r\r" + '');
2026 conn.end();
2027 }
2028 }
2030 function eventCloseConn() {
2031 //console.log('connection from %s closed', remoteAddress);
2032 }
2034 function eventErrorConn(err) {
2035 //console.log('Connection %s error: %s', remoteAddress, err.message);
2036 }
2038 // Connection Events //
2039 conn.on('data', eventData);
2040 conn.once('close', eventCloseConn);
2041 conn.on('error', eventErrorConn);
2042 }
2044 function setUp(server) {
2045 server.on('connection', processConnection);
2046 server.listen(6661, 'localhost', function () {
2047 //console.log('server listening to %j', server.address());
2048 });
2049 }
2051 setUp(server);